This is a method and a system for designing a personalized therapeutic intervention for an individual. Each individual has a unique composition of microbiome in the gut, one probiotic or dietary regimen may not have same efficacy in different individuals. The disclosure recommends a personalized therapeutic intervention for improving gut health of an individual by designing personalized therapeutics and diet based on functions of microbiome. The personalized therapeutic intervention is recommended based on several steps including generating a set of knowledge bases, identifying a change in the gut health of an individual by monitoring the gut samples and recommending a personalized therapeutic intervention. The personalized therapeutic intervention comprises at least one of a prebiotic, a probiotic and an optimized diet, wherein the optimized diet is estimated based on optimizing a gut food score, where the gut food score is computed based on the change in the gut health of an individual.
This disclosure relates generally to the field of taxonomic profiling of microbial organisms such as bacteria, and, more particularly, to system and method for simultaneous interpretation of taxonomic distribution and replication rates of microbes constituting microbial communities. The present disclosure extracts bacterial genomic DNA from a plurality of bacterial organisms comprised in collected microbiome sample. Maps the plurality of the DNA sequence fragment reads to a precomputed reference sequence database of a plurality of all available completely sequenced bacterial genomes. Based on the mapping, the read coverage is measured at the genomic locations of the phylogenetic marker genes, wherein measured read coverage is used for interpretation of taxonomic distribution of the plurality of bacterial organisms. A plurality of slopes is obtained by fitting a linear function. The present disclosure interprets a replication rate for each of the plurality of bacterial organisms identified from the collected microbiome sample.
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16B 30/00 - ICT specially adapted for sequence analysis involving nucleotides or amino acids
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
State of the art systems used for industrial plant monitoring have the disadvantage that they fail to correctly assess reason for dip in performance of the plant and in turn trigger appropriate corrective measures. The disclosure herein generally relates to industrial plant monitoring, and, more particularly, to a system and method for development and deployment of self-organizing cyber-physical systems for manufacturing industries. The system monitors and collects data with respect to various parameters, from the industrial plant. If any performance dip is detected, the system determines corresponding cause, and also triggers one or more corrective actions to improve performance of the plant and different plant components to a desired performance level.
Material balancing is one of the important feature of the manufacturing plant. The existing methods for material balancing have limited applicability as they require lot of manual intervention by experienced plant engineers. A system and a method for achieving automated material balancing or mass balancing and data reconciliation in a manufacturing or a process plant to solve the technical problems of the prior art. The system is configured to automatically identify operating process flow circuit in real-time for data reconciliation and material balancing in the manufacturing plant. The automated preprocessing identifies and flags whether the material is balanced at each nodes present in the plant and also identifies the flow rates based on their values. These flags help in identifying the nodes and tags or material flow rates and further give importance to those nodes and tags for which mass is not balanced during the mass balance and reconciliation activity.
Trajectory optimization is process of designing a trajectory of operating variables that optimizes measure of performance while satisfying a set of constraints, when the system moves from one state to another. It is very necessary to achieve optimization in real time. A system and method for real-time trajectory optimization has been provided. The trajectory optimization of a process can be performed in any dynamical automated system. The system is configured to optimize the trajectory in both online and offline mode. In the online mode, the system optimizes the trajectory of the process in real-time. The system has the ability to handle both machine learning and deep learning based time series models along with first principles based models represented by ordinary / partial differential equation or differential algebraic equation based dynamic models of the process to estimate process variables given the disturbance profile and the actuation profile of manipulated variables.
G05B 13/00 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
Crop loss estimation allows a user to monitor and estimate damage to the crops due to various natural events/factors. State of the art systems used for the crop loss estimation have the disadvantage that they do not convey to the users extent of damage. In addition to this, the existing methods do not take into account the recovery factor of the crops due to multiple factors and end up in overestimating the loss. The disclosure herein generally relates to crop monitoring, and, more particularly, to a method and system for crop loss estimation. In this method, crop loss is assessed based on real-time weather parameters and remote sensing data collected and processed, and crops are classified as being in one of a repairable damage class and a permanent damage class. The system also quantifies the crop loss, which allows the user to understand magnitude of the crop loss.
This disclosure relates generally to detection of pathogens from a gaseous mixture associated with secretions. Conventional methods typically involve invasive or biohazardous techniques, the requirement of quantity limits utility of several natural secretions, there is a dependency on immunological reactions to develop in a subject being monitored resulting in long time taken for detecting pathogens, which increases risk to health and environment. There is also reduced specificity and sensitivity considering the dependency on signature identification or training of machine learning models. Again, prior art focusses on designing antibodies for a particular type of sensor which is challenging when dealing with natural immunoglobulin. The present disclosure addresses these challenges by enabling identification of a most viable sensor for the natural immunoglobin, the viability being based on mathematical representations of the relationship between a sensor and the immunoglobulin using an ontology of domain knowledge associated with pathogens, technology, processing and detection.
All the model-driven systems may not have capability to perform designing and execution of experiments, which limits functionality of such model-driven systems. The disclosure herein generally relates to Design of Experiments (DOE), and, more particularly, to a model driven sub-system for design and execution of experiments. The sub-system when plugged into the model driven system, uses legacy components as well components of the sub-system to perform designing and execution of the design of experiments.
G06F 3/06 - Digital input from, or digital output to, record carriers
G16B 40/00 - ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
9.
METHOD AND SYSTEM FOR OPTIMIZING AND ADAPTING TELECOM ORGANIZATION IN DYNAMIC ENVIRONMENT
The communications service provider (CSP) is a service provider that transports information electronically which includes the telecommunications services. The existing methods for optimizing and adapting operational processes in the telecom organization are not fully efficient as the communication service providers (CSPs) operate in a dynamic and uncertain environment. A method and system for optimizing and adapting operational processes in the telecom organization has been provided. The proposed method and system describe a multi-modelling based simulatable digital twin that enables in-silico quantitative exploration of design space to help human experts arrive at the right product offerings and customer engagement services. The proposed method and system initially construct a high-fidelity simulatable digital twin, validate it, set it up with real data, and simulate various adaptation and design alternatives to understand their impacts on the key performance indicators (KPIs).
A processor implemented method of detecting a concentration of plurality of chemical residue in an agricultural produce is provided. The method include (a) receiving, by a hyper spectral device, a data set associated with one or more reflectance measurements of the agricultural produce; (b) determining, data associated with a plurality of bands; (c) dynamically reiterating, the steps (a) and (b) at predetermined time interval to obtain a trained dataset; (d) determining, relevant wavelengths among the selected trained data sets based on a feature selection technique to form an array of emitters; (e) calibrating, by the identified array of emitters, to emit light on the detecting region of one or more sample of the agricultural produce to obtain data associated with reflectance and transmittance; and (f) calculating, a calibration index with a de-multiplication flag to detect presence or absence of the plurality of chemical residue in the agricultural produce.
In a distributed job execution environment, multiple execution agents having different capabilities are available for execution of a job. However random assignment of the job to an available execution agent(s) may not guarantee a most appropriate execution agent being assigned with the responsibility of executing the job. The disclosure herein generally relates to job processing, and, more particularly, to a method and system for distributed job execution. In this approach, the system has information on real-time values of various performance parameters of the execution agent and number of external tool license available, at any instance of time, to determine one or more job execution agents matching properties of a plugin of one or more jobs to be executed. By considering the real-time values, the system determines one or more execution agents for executing the one or more jobs, and then the one or more jobs are accordingly assigned.
Skin-associated autoimmune diseases are common these days. A method and composition for microbiome based amelioration of skin associated autoimmune inflammatory diseases has been provided. The composition is made of at least one or more of microbiome-associated compounds such as proteins, metabolites, antibiotics, probiotics, etc. The method provides a composition for an affected individual through application of these compositions aimed at improving the bioavailability of lipoic acid. It acts through modulation of the lipoic acid metabolic pathway to do the same. The suggested microbes and compounds can either be used as an effective probiotic supplement in increasing the microbial population involved in lipoic acid biosynthesis (only), or increasing the number of competitors of the microbes involved in escalation of lipoic acid salvage system, or through direct antibiotic or physical action against the latter.
C12Q 1/6883 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
State-of-the-art systems use active energy sources like lasers for capturing turbid media. Identification of turbid media of interest in presence of other turbid media is not addressed. Prediction of events, such as outbursts, in ROI is derived by relying only on current data of a turbid activity. Method and system for monitoring of turbid media of interest to predict events utilizes spatio-temporal features extracted from the images captured by visual cameras in fusion with features extracted from other sensors and cameras of different modalities to rightly identify turbid regions. A set of parameters defining parameters relevant to the turbid media of interest enables the system to rightly identify the turbid media of interest from plurality of turbid media present in ROI. The system accurately predicts potential outburst regions by utilizing historical data (time series data providing variations of temperature profile and temporal signatures of past events) along with current data.
This disclosure relates generally to for time lag identification in an industry. The disclosure proposes to monitor an industry continuously at real time to identify one or more parameters from plurality of sources (processes/units/plants) and a time delay or delayed performance or functional impact the identified parameter has on a plurality of Key Performance Indicator (KPI). The proposed time lag identification is performed using one-time lag identification from the proposed plurality of time lag identification techniques that include an individual time lag identification technique, a group-wise time lag identification technique and group-wise/individual time lag identification technique. Further the time lag identification is performed based on domain knowledge as well as data driven techniques. The identified time-lag is used for prediction and forecasting or detection of anomalies in process and manufacturing industries.
This disclosure relates generally to a system and method for monitoring performance of low-cost sensors plied in a field for soil moisture measurement. The low-cost sensors are calibrated to give useful derived parameters to support farming such as volumetric water content (VWC) of the soil. Further, the steps are being incorporated to de-noise their response to derive stable measurements similar to expensive rugged sensors. The calibration of the low-cost sensor and normalization of incoming values from the low-cost sensor are based on values determined through rugged sensors for soil moisture measurement. The normalization involves finding a minimum value and maximum value of soil moisture. Performance of the low-cost sensors are analyzed based on a range of values of the soil moisture. Finally, the performance analysis provides degradation stages and based on the degradation stages evaluated recommendations to modify the sensor are shared with the user.
Nocturia has been defined as the need for an individual to wake up one or more times during the night to void. Further, Nocturia detection also requires analysis of sleeping pattern of the person. In such cases a lot of assumptions are made when the person is not in bedroom during nights. A method and system for detection and validation of Nocturia in the person has been provided. The system is utilizing a statistical based analysis, a rule based analysis, a machine learning based analysis and analysis of sleeping pattern of the person to detect and validate Nocturia. The system ensures that the person is not disturbed in his/her daily activities. Further, the processes deployed in the system are completely un-supervisory in nature meaning it does not have the dependency of needing to have trained machine learning dataset.
Conventionally, root cause analysis and process documentation in process industries has been manually performed resulting in time consuming effort, cost, and human resources. Moreover, in the event of failure, looking at such document and searching for possible root causes is practically impossible in the interest of time and cost associated. Systems and methods of the present disclosure systematically curate knowledge of industrial process(es) from various sources and generate process ontology via meta model(s). Root cause graph (RCG) is created wherein the RCG corresponds to process and root cause and failure modes in the process. The RCG is then transformed to machine instructions which are executed for root cause analysis in real time. The created graphs/knowledge also help in identifying conflicting knowledge or redundant knowledge. Present disclosure enables root cause analysis as soon as a failure occurs or as the systems show or indicate a tendency towards failure.
This disclosure relates generally to a method and system for real time monitoring and forecasting of fouling of an air preheater (APH) in a thermal power plant. The system is deploying a digital replica or digital twin that works in tandem with the real APH of the thermal power plant. The system receives real-time data from one or more sources and provides real-time soft sensing of intrinsic parameters as well as that of health, fouling related parameters of APH. The system is also configured to diagnose the current class of fouling regime and the reasons behind a specific class of fouling regime of the APH. The system is also configured to be used as advisory system that alerts and recommends corrective actions in terms of either APH parameters or parameters controlled through other equipment such as selective catalytic reduction or boiler or changes in operation or design.
G06Q 10/04 - Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
F23L 15/00 - Heating of air supplied for combustion
F23J 15/08 - Arrangements of devices for treating smoke or fumes of heaters
F23J 15/00 - Arrangements of devices for treating smoke or fumes
G06F 17/18 - Complex mathematical operations for evaluating statistical data
G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
19.
METHOD AND SYSTEM FOR IDENTIFICATION AND ANALYSIS OF REGIME SHIFT
This disclosure relates generally to identification and analysis of regime shift. The identification and analysis of the regime shift includes regime shift identification (RSI), root cause analysis of the identified regime shift and a recommendation unit to rectify the identified regime shift. The disclosure proposes to monitor a system continuously to identify a regime shift at real-time as presence of regime shifts in any system decreases quality of process and products and makes the system less efficient. The regime shift is identified at real-time based on key performance indicators (KPIs), a set of relevant features and real time input data using machine learning techniques. Further the disclosure also proposes techniques for detecting at least one root cause for the identified regime shift and also recommends a rectification action to rectify the identified regime shift based on optimization techniques.
G05B 19/406 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
G06Q 10/06 - Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
G06F 11/34 - Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation
Industrial plants involve a large amount of equipment, which generate a large amount of data. By analyzing this data, the operator can diagnose anomaly in the plant. Analyzing this data is difficult and time taking task. A method and system for diagnosing anomaly in an industrial system in a time efficient and convenient manner has been provided. The system is configured to diagnose the anomaly by finding out one or more sensors responsible for the anomaly. The present disclosure treats the anomaly detection model as a score generating function. Whenever for a particular instance the score given by the anomaly detection model crosses a pre-determined threshold, anomaly is reported and the diagnosis algorithm is triggered. The system is configured to diagnose the anomaly predicted in case of time series as well as non-time series data.
Industrial data mining is performed on data collected/gathered from industrial processes/equipment for monitoring performance of the processes/equipment, and in turn to make necessary changes so as to obtain an intended result. However, the existing data mining systems fail to consider relation between variables and certain Key Performance Indicators (KPI), and strength of the relation. Disclosed herein is a method and system for data mining in industrial processes or equipment in which relation between the variables and the KPIs are determined, and also the strength of relation is determined. Based on the determined relation, an order of importance of the variables with respect to each KPI is determined. This information can be used to alter/change appropriate parameters to yield intended results.
The need for extracting information trapped in unstructured document images is becoming more acute. A major hurdle to this objective is that these images often contain information in the form of tables and extracting data from tabular sub-images presents a unique set of challenges. Embodiments of the present disclosure provide systems and methods that implement a deep learning network for both table detection and structure recognition, wherein interdependence between table detection and table structure recognition are exploited to segment out the table and column regions. This is followed by semantic rule-based row extraction from the identified tabular sub-regions.
For various applications (for example, a Virtual Assistant), mechanisms that are capable of collecting user queries and generating responses are being used. While such systems handle structured queries well, they struggle to or fail to interpret an unstructured Natural Language (NL) query. The disclosure herein generally relates to data processing, and, more particularly, to a method and a system for generating responses to unstructured Natural Language (NL) queries. The system collects at least one NL query as input at a time, and generates a sketch, where the sketch is a structured representation of the unstructured NL query. Further by processing the sketch, the system generates one or more database queries. The one or more database queries are then used to search in one or more associated databases and to retrieve matching results, which are then used to generate response to the at least one NL query.
Keypoint extraction is done for extracting keypoints from images of documents. Based on different keypoint extraction approaches used by existing keypoint extraction mechanisms, number of keypoints extracted and related parameters vary. Disclosed herein is a method and system for keypoint extraction from images of one or more documents. In this method, a reference image and a test image of a document are collected as input. During the keypoint extraction, based on types of characters present in words extracted from the document images, a plurality of words are extracted. Further, all connected components in each of the extracted words are identified. Further, it is decided whether keypoints are to be searched in a first component or in a last component of all the identified connected components, and accordingly searches and extracts at least four of the keypoints from the test image and the corresponding four keypoints from the reference image.
G06K 9/68 - Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of reference, e.g. addressable memory
25.
SYSTEM AND METHOD FOR HANDLING POPULARITY BIAS IN ITEM RECOMMENDATIONS
This disclosure relates generally to method and system for handling popularity bias in item recommendations. In an embodiment, the method includes initializing an item embedding look-up matrix corresponding to items in a sequence of item-clicks with respect to a training data. L2 norm is applied to the item embedding look-up matrix to learn a normalized item embeddings. Using a neural network, a session embeddings corresponding to the sequences of item-clicks is modeled and L2 norm is applied to the session embeddings to obtain a normalized session embeddings. Relevance scores corresponding to each of the plurality of items are obtained based on similarity between the normalized item embeddings and the normalized session embeddings. A multi-dimensional probability vector corresponding to the relevance scores for the items to be clicked in the sequence is obtained. A list of the items ordered based on the multi-dimensional probability vector is provided as recommendation.
In an industrial plant, various equipment are used to handle processing of raw materials. Considering complexities involved in the processes and the equipment, constant monitoring is required to obtain desired results. The disclosure herein generally relates to industrial process and equipment monitoring, and, more particularly, to data analysis for Just In Time (JIT) characterization of raw materials in any process industry. The system collects real-time plant data among other inputs, and performs characterization of raw materials being used in the plant. The characterization involves categorizing the raw materials into different classes. The class information is further used to predict performance of the industrial plant, and in turn to generate recommendations for optimization of the industrial plant.
Schizophrenia is a chronic and severe psychiatric disorder that affects how a person thinks, feels, and behaves. If Schizophrenia is diagnosed early, most symptoms of Schizophrenia can be managed with appropriate medical interventions. A system and method for assessing the risk of Schizophrenia in a person has been provided. The system is configured to assess individuals to check the presence or absence of Schizophrenia, by quantifying the abundance of sensory proteins in their microbiome. The disclosure relates to a defined methodology that involves assessment and categorization of the person into healthy and schizophrenic based on the abundance of sensory proteins in the microbiome. The systems and methods further describe microbiota based therapeutics for management of Schizophrenia through generating a therapeutic model and administering a consortium of healthy microbes which could modulate the disease microbiome composition towards a healthy equilibrium.
Colorectal cancer is a severe disease, if not assessed properly, it may lead to the death of an individual. A system and method for assessing the risk of colorectal cancer has been provided. The system is configured to assess individuals to check the risk of presence of colorectal cancer (CRC) and/or adenomatous (colonic/ rectal) polyps, by quantifying the abundance of sensory proteins in their gut microbiome. The system further categorizes the person into one of healthy, adenoma and cancerous categories based on the nature and abundance of sensory proteins in the gut microbiome. The system further describes microbiota based therapeutics for treatment of the person with colorectal adenoma and/or cancer through administration of at least one of a consortium of healthy microbes, antibiotic drugs and pre-/ pro-/ syn-/ post-biotic compounds or fecal microbiome transplant which could modulate the disease microbiome composition towards a healthy equilibrium.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
G01N 33/569 - Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
C12Q 1/68 - Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
A61K 31/437 - Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins having six-membered rings with one nitrogen as the only ring hetero atom ortho- or peri-condensed with heterocyclic ring systems the heterocyclic ring system containing a five-membered ring having nitrogen as a ring hetero atom, e.g. indolizine, beta-carboline
Prediabetes is an intermediary physiological condition (in between healthy and diabetic states) which may be reversed through timely intervention. A system and method for assessing the risk of prediabetes in a person has been provided. The system 100 is configured to assess individuals to check the absence or presence of prediabetic symptoms, by quantifying the abundance of sensory proteins in their microbiome. The invention relates to a defined methodology that involves assessment and categorization of the person into healthy and prediabetic based on the abundance of sensory proteins in the sample collected from the faeces of the person. The systems and methods further describe microbiota based therapeutics for treatment/ management of prediabetes through generating a therapeutic model and administering a consortium of healthy microbes which could modulate the disease microbiome composition towards a healthy equilibrium.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
G01N 33/569 - Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
C12Q 1/68 - Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
A61K 31/437 - Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins having six-membered rings with one nitrogen as the only ring hetero atom ortho- or peri-condensed with heterocyclic ring systems the heterocyclic ring system containing a five-membered ring having nitrogen as a ring hetero atom, e.g. indolizine, beta-carboline
The onset of Parkinson's disease (PD) is a serious concern for elderly people and it is necessary to identify the risk for PD in an individual as early as possible. A system and method for risk assessment of an individual for Parkinson's disease (PD) has been provided. The system is using a non-invasive method for risk assessment of PD through prediction of metabolic potential of the bacteria residing in gastrointestinal tract of the individual. The system 100 is configured to calculate a score, which is evaluated from the gut bacterial taxonomic abundance profile, which is indicative of its metabolic potential for production of a particular neuroactive compound. This score is subsequently used to assess the risk of an individual of being affected by PD. Further, the present disclosure also provides microbiome based therapeutic approaches that can potentially minimize the side effects through maintaining the healthy cohort of bacteria in gut.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
G01N 33/569 - Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
C12Q 1/68 - Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
A61K 31/437 - Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins having six-membered rings with one nitrogen as the only ring hetero atom ortho- or peri-condensed with heterocyclic ring systems the heterocyclic ring system containing a five-membered ring having nitrogen as a ring hetero atom, e.g. indolizine, beta-carboline
Multiple sclerosis (MS) is a neurodegenerative autoimmune disease affecting brain and the spinal cord which results in distorted communication between brain and rest of the body. It is necessary to assess the risk of MS at the earliest. A system and method for diagnosis and risk assessment of an individual for multiple sclerosis has been provided. The system is using a non-invasive method for risk assessment through prediction of metabolic potential of the bacteria residing in gastrointestinal tract of the individual. The system is configured to calculate a score, which is evaluated from the gut bacterial taxonomic abundance profile, indicative of its metabolic potential for production of a particular neuroactive compound. The score is subsequently used to predict the risk of the individual for MS. The present disclosure also provides microbiome based therapeutic approaches that can potentially minimize the side effects through maintaining the healthy cohort of bacteria in gut.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
G01N 33/569 - Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
A61K 31/437 - Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins having six-membered rings with one nitrogen as the only ring hetero atom ortho- or peri-condensed with heterocyclic ring systems the heterocyclic ring system containing a five-membered ring having nitrogen as a ring hetero atom, e.g. indolizine, beta-carboline
A system and method for risk assessment of an individual for autism spectrum disorder (ASD) has been provided. The system is using a non-invasive method for risk assessment of the individual, especially children, for ASD through prediction of metabolic potential of the bacteria residing in gastrointestinal tract of the individual. The system is configured to calculate a score, evaluated from the gut bacterial community's taxonomic abundance profile, which is indicative of its metabolic potential for production of a particular neuroactive compound. A set of metabolic pathways harboured by the bacterial community residing in gut has been utilized to develop an ASD diagnosis scheme that, when applied with the conventional screening tests, help in early diagnosis of the ASD. Further, the present disclosure also provides bacterial community based therapeutic approaches that can potentially minimize the side effects through maintaining the healthy cohort of bacteria in gut.
G06F 19/00 - Digital computing or data processing equipment or methods, specially adapted for specific applications (specially adapted for specific functions G06F 17/00;data processing systems or methods specially adapted for administrative, commercial, financial, managerial, supervisory or forecasting purposes G06Q;healthcare informatics G16H)
G01N 33/569 - Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
C12Q 1/68 - Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
A61K 31/437 - Heterocyclic compounds having nitrogen as a ring hetero atom, e.g. guanethidine or rifamycins having six-membered rings with one nitrogen as the only ring hetero atom ortho- or peri-condensed with heterocyclic ring systems the heterocyclic ring system containing a five-membered ring having nitrogen as a ring hetero atom, e.g. indolizine, beta-carboline
An autonomous mobile robot (AMR) with a single modular platform to mount plurality of material handling units is provided. The AMR includes a monolithic chassis; a top plate includes plurality of standoffs to mount at least one material handling units; the plurality of standoffs are integrated on top of the top plate; drive wheels are coupled to a wheel mount as a single unit to form a drive wheel assembly; a suspension unit is coupled symmetrically in between two main bodies which corresponds to the monolithic chassis and the drive wheel assembly with spring enclosures, suspension shafts, and coil springs; a set of side plates connect the monolithic chassis on the AMR. The top plate is sandwiched between the plurality of standoffs and the monolithic chassis. A load is transferred from the plurality of material handling units through the plurality of standoffs and the top plate to the monolithic chassis.
B25J 5/00 - Manipulators mounted on wheels or on carriages
B65G 35/00 - Mechanical conveyors not otherwise provided for
B62D 61/02 - Motor vehicles or trailers, characterised by the arrangement or number of wheels, not otherwise provided for, e.g. four wheels in diamond pattern with two road wheels in tandem on the longitudinal centre line of the vehicle
34.
SYSTEM AND METHOD FOR REAL-TIME SELF-OPTIMIZATION OF MANUFACTURING OPERATIONS
This disclosure relates generally to method and system for real-time self-optimization of manufacturing operations and systems. Generally the behavior of a manufacturing plant changes with time due to the regime changes or aging of equipment. Subsequently, the optimization configuration of the plant needs to be changed such that it suits the current plant behavior. The disclosed system identifies the change in plant behavior by monitoring disturbance variables and KPIs of the plant. Once the change in the plant exceeds a critical limit quantified in terms of changes in disturbance and process variables along with key performance indicators, the current optimization problem is deemed no longer valid, and the system triggers self-optimization of the plant. The system configures a new optimization problem considering the earlier knowledge of problem formulation and the current plant conditions.
G05B 13/00 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G05B 13/04 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
35.
METHOD AND SYSTEM FOR OPTIMIZATION OF AGGLOMERATION OF ORES
Agglomeration process in agglomeration plants is quite sensitive to changes in input feed material characteristics. End-to-end optimization of the agglomerate process by combining all the units is difficult due to unique complexities and challenges associated with combining the individual process outputs. A method and system for optimizing the operation of an agglomeration plant has been provided. The system performs real time optimization on integrated wet agglomeration and thermal agglomeration process which subsequently increases the plant productivity and agglomerate quality and minimizes the operating cost and emissions from the plant. The optimization process involves various steps such as receiving data, pre-processing of data, prediction using physics-based and data-driven models of agglomeration plant, and optimization execution and configuration. The process also involves continuous monitoring of model performance and self-learning of the models in case of a performance drift. The system is also configured to estimate the key performance parameters of agglomeration plant.
G06F 7/60 - Methods or arrangements for performing computations using a digital non-denominational number representation, i.e. number representation without radix; Computing devices using combinations of denominational and non-denominational quantity representations
G06F 7/48 - Methods or arrangements for performing computations using exclusively denominational number representation, e.g. using binary, ternary, decimal representation using unspecified devices
36.
INTELLIGENT VISUAL REASONING OVER GRAPHICAL ILLUSTRATIONS USING A MAC UNIT
This disclosure relates generally to intelligent visual reasoning over graphical illustrations using a MAC unit. Prior arts use visual attention to map particular words in a question to specific areas in an image to memorize the corresponding answers, thereby resulting in a limited capability to answer questions of a specific type. The present disclosure incorporates the MAC unit to enable reasoning capabilities and accordingly attend to an area in the image to find the answer. The present disclosure therefore allows generalizing over a possible set of questions with varying complexities so that an unseen question can also be answered correctly based on the reasoning methods that it has learned. The system and method of the present disclosure can be used for understanding of visual information when processing documents like business reports, research papers, consensus reports etc. containing charts and reduce the time spent in manual analysis.
This disclosure relates generally to sequence labeling and more particularly to method and system for sequence labeling. The method includes employing a hierarchical capsule based neural network for sequence labeling, which includes a sentence encoding layer (having word embedding layer, feature extraction layer and multiple capsule layer) and a document encoding layer, Bi-LSTMs, a fully connected layer and a conditional random fields (CRF) layer. The word embedding Layer obtains fixed-size vector representation of words of sentences associated with a dialogue or an abstract, then the feature extraction layer encodes the sentences, the Capsule layer extracts high-level features from the sentence. Ah the sentence encodings are then stacked up together and are passed through another Bi-LSTM layer to derive the contextual information from sentences. A fully connected layer calculates likelihood scores. The CRF layer obtains optimized label sequence based on the likelihood scores.
State of the art techniques used for Flue Gas Desulpharization (FGD) process monitoring fail to comprehend the relationship between various process parameters, which is crucial in determining the performance of a FGD process being monitored. The disclosure herein generally relates to industrial process monitoring, and, more particularly, to a method and system for performance optimization of Flue Gas Desulphurization (FGD) Unit. The system identifies Key Performance Indicators (KPIs) associated with the process being monitored, and identifies parameters associated with each KPI. This information is used to generate several predictive models, from which a predictive model having the highest value of composite model score amongst the predictive models is selected as the predictive model for processing the input data, which is then used to perform optimization of the FGD process.
Combined cycle gas turbine (CCGT) power plants have become common for generation of electric power due to their high efficiencies. There are various problem related with improving the efficiency of CCGT plants by optimizing the manipulated variables. The method and system for optimizing the operation of a combined cycle gas turbine has been provided. The system is configured to calculate an optimal value of manipulated variables (MV) with efficiency as one of the key performance parameters (KPI). The MVs from the existing CCGT automation system, i.e. a first set of manipulated variables and the manipulated variables from the optimization approach, i.e. a second set of manipulated variables are combined to determine an optimal set of manipulated variables. The method further checks for the anomalous behavior of the system and define the root cause of the identified anomaly and the operational state of the CCGT plant.
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
F02C 6/18 - Plural gas-turbine plants; Combinations of gas-turbine plants with other apparatus; Adaptations of gas-turbine plants for special use using the waste heat of gas-turbine plants outside the plants themselves, e.g. gas-turbine power heat plants
F02C 9/28 - Regulating systems responsive to plant or ambient parameters, e.g. temperature, pressure, rotor speed
40.
METHOD AND SYSTEM FOR INDUSTRIAL ANOMALY DETECTION
The disclosure relates to anomaly detection in an industrial environment including multiple industrial units and systems, generating huge volume of data. The conventional methods rely only on sensor data alone. The techniques of handling missing data plays a crucial role in determining the performance of industrial anomaly detection system. Further, imputation of missing data could cause error in computation, thus affecting the accuracy of the industrial anomaly detection system. The present disclosure addresses the problems associated with missing data by utilizing a masking technique. Further, the present disclosure utilizes quantitative and qualitative metadata associated with industrial system along with the sensor data to improve anomaly detection performance. Furthermore, the present disclosure includes a model recommendation system which provides transfer learning based utilization of existing models for similar industrial systems.
ProteobacteriaProteobacteria Proteobacteria Proteobacteria. It is possible to target multiple pathogens simultaneously using a single target site as these pathogens belong to the same phylum and share similarities in their genetic signature. The strategy involves identifying potential target sites in the pathogen, which can be utilized to compromise its multiple virulence or essential functions at the same time.
C12Q 1/689 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria
42.
SYSTEM AND METHOD FOR COMBATING INFECTIONS DUE TO ANTIBIOTIC INDUCED PATHOGENS
C12Q 1/689 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria
43.
METHOD AND SYSTEM FOR IDENTIFICATION OF TARGET SITES IN PROTEIN CODING REGIONS FOR COMBATING PATHOGENS
A method and system for identification of target sites in protein coding regions for combating pathogens has been provided. The method relates to identifying a set of nucleotide repeat sequences that occur within the complete coding region of a specific protein that is involved in the pathogenicity of the infectious bacteria and which occurs in multiple copies on the pathogen genome and utilizing various laboratory acceptable methods to debilitate the identified target sequence on the pathogen genome, as well as use of enzymatic machinery to target and cleave its flanking genes on the genome. The set of nucleotide repeat sequences forming a part of or the complete coding region of a specific protein on the pathogen genome may be flanked by genes on either side that can be targeted as well. The present disclosure further includes administration of a cocktail comprising antimicrobial drugs, biofilm inhibitors and the novel construct.
G16B 40/00 - ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
G16B 25/00 - ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
A61P 31/00 - Antiinfectives, i.e. antibiotics, antiseptics, chemotherapeutics
Mycobacterium tuberculosisMycobacterium tuberculosisMycobacterium tuberculosis. The system provides strategies to combat pathogenic infections caused by multi-drug resistant (MDR) and extensively drug resistant (XDR) strains of Mycobacterium tuberculosis. The strategy involves identifying potential target sites in a pathogen, which can be utilized to compromise its multiple virulence or essential functions at the same time. The present disclosure utilizes the fact that a conserved stretch of nucleotide repeat sequence occurring multiple times on a pathogen genome in genomic neighborhood of genes encoding virulence factors for pathogen survival can be targeted to disrupt the overall genetic machinery of the pathogen.
C12Q 1/689 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria
Co-infection of Pseudomonas aeruginosa and Staphylococcus aureus, exacerbates the virulence gene expression as well as shows higher antibacterial resistance than when they cause infections individually thereby making the infection extremely difficult to combat. A method and system for combating infections due to Pseudomonas aeruginosa and Staphylococcus aureus has been provided. The system provides strategies to combat pathogenic infections caused by multi-drug resistant (MDR) and extensively drug resistant (XDR) strains of Pseudomonas aeruginosa and Staphylococcus aureus. The strategy involves identifying potential target sites, which can be utilized to compromise its multiple virulence or essential functions at the same time. The idea utilizes the fact that a conserved stretch of nucleotide sequence occurring multiple times on a pathogen genome encoding virulence factors or in vicinity of genes essential for pathogen survival encoded within the genome of the candidate pathogen can be targeted to disrupt the overall genetic machinery of the pathogen.
C12Q 1/689 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria
46.
METHOD AND SYSTEM FOR IDENTIFICATION OF CANDIDATE TARGET SITES FOR COMBATING PATHOGENS
A system and method for identification of target sites in a pathogenic genome and combating a pathogenic infection have been provided. The present disclosure utilizes the fact that a conserved stretch of nucleotide sequence in genomic neighborhood of genes important for bacteria can be targeted to disrupt the overall functioning of the pathogen. The method involves identification of nucleotide repeat sequences in the DNA. The method and system also involves administration of a cocktail comprising antimicrobial drugs, biofilm inhibitors and a construct. The genomic neighborhood or vicinity or 'flanking genes' refers to regions lying within a predefined number of genes to the identified conserved stretch of nucleotide repeat sequence (or its reverse complement) on the candidate pathogen genome or within a distance of predefined number of bases with respect to the conserved stretch of nucleotide repeat sequence (or its reverse complement) on the candidate pathogen genome.
C12Q 1/689 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria
47.
SYSTEM AND METHOD FOR COMBATING PLANT PATHOGENIC BACTERIAL INFECTIONS
Xanthomonas sp.Pseudomonas syringaePseudomonas syringae are developing resistance to various classes of antibiotics. A method and system for combating plant pathogenic bacterial infections have been provided. The system is configured to provide strategies to combat infections in plants caused by multi-drug resistant (MDR) plant pathogens. The strategy involves identifying potential target sites in the plant pathogen, which can be utilized to compromise its multiple virulence or essential functions at the same time. The idea used in this disclosure utilizes the fact that a conserved stretch of nucleotide sequence occurring multiple times on a pathogen genome in genomic neighborhood of genes encoding virulence factors or in vicinity of genes essential for pathogen survival encoded within the genome of the candidate pathogen can be targeted to disrupt the overall genetic machinery of the plant pathogen.
C12Q 1/689 - Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for detection or identification of organisms for bacteria
48.
METHOD AND SYSTEM FOR OPTIMUM COAL SELECTION AND POWER PLANT OPTIMIZATION
Performance optimization of power plants is one of the major challenge. Several machine learning based techniques are available which are used for optimization of the power plants. Coal selection and blending is critical to ensuring optimum operation of thermal power plants. The present disclosure provides a system and method for optimum coal selection for the power plant and power plant optimization. The system mainly comprises two components. First, a coal usage advisory module providing coal usage and blending ratio advice to the operators based on the available coal. The optimization is with respect to the entire power plant operation including its components. And second, a performance optimization advisory module provides operation instruction for boiler, SCR, APH and other power plant equipment based on the implemented coal blend in real-time.
G01B 15/02 - Measuring arrangements characterised by the use of electromagnetic waves or particle radiation, e.g. by the use of microwaves, X-rays, gamma rays or electrons for measuring thickness
G01N 23/00 - Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups , or
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
This disclosure relates to a method and system for adaptive learning of physics-based models, data-driven models and hybrid models used in an industrial manufacturing plant. A model-based optimization and advisory device (MOAD) is configured for monitoring performance of data-driven and physics-based models of industrial process units in real-time, computing model quality index for models, triggering adaptive learning of these models and in case of drift in predictions, diagnosing the reasons for drift in predictions. Suggesting re-tuning, re-building and recreating of the models to achieve highest prediction quality, and automatic deployment of latest models. The method and system ensures that the models of industrial manufacturing plant that provide critical operational decisions to the operators are kept up-to-date with minimal human intervention, while ensuring that adaptive learning is executed only when required and not on the basis of the amount of newer operational data accumulated or the time elapsed since model deployment.
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
Generally, in complex systems such as business organizations and supply chain networks, decisions making and control are challenging due to dynamic environment thereof. The embodiments herein provide method and system that uses reinforcement learning (RL) for exploring policies and deciding control actions, and actor-based modelling and simulation for performing accurate long-term rollouts of the policies, in order to optimize operation of the complex systems. In an embodiment, a method for actor based simulation of complex system includes modeling, actors of the complex system using an actor abstraction, where actors includes RL agents embodied in each subsystem of the complex system, and executes micro-level interactions amongst the subsystems. An emergent macro-behavior of the complex system is simulated by the using the RL agents based on the micro-level interactions. Optimal decisions pertaining to actions of the RL agents are learnt based on the emergent macro-behavior of the complex subsystem.
Conventional methods for developing responsive application screens or UI screens, as per the desired wireframes is a time consuming and erroneous. The embodiments herein provide a method and system for automatically transforming wireframe screens to responsive application screens using a User Interface (UI) editor. The UI editor supported by a model editor enables user to select the controls that are present in the wireframe with its text, text properties, layout, color, background, borders and many more properties which are related to its visual appearance. Further, corresponding specification for the user selected requirements of the wireframe is generated automatically. The user can edit the specifications, for any changes required. Further, the UI editor converts the specifications to a technological independent model, which can be imported into UI models and followed by code conversion to the required technology stack. User can modify the imported specifications before going to code conversion.
Temperature measurement is an important part of many potential applications in the fields of metallurgy. Conventional temperature measurement methods do not provide accurate and precise average temperature of fluid inside an enclosed chamber. The present disclosure provides multi-sensory techniques for measuring average temperature of mixed fluid inside a chamber. The average temperature is measured based on acoustic interferometry technique on standing wave and inputs received from one or more sensors and radar. The present disclosure utilizes radar to compensate the effect of fumes, noise based on Doppler effect. Further, the inputs received from the one or more sensors are used to determine the concentration of one or more fluids present in the chamber. The method of proposed disclosure depends on the principle of dependence of temperature on sound speed in fluid. So, measurement of sound speed can be mapped to report average temperature of mixed fluid inside the chamber.
Contamination of environment by a multitude of pollutants is becoming a global health concern. Lot of methods are being used for bioremediation of those pollutants. A method and system for one or more pollutants has been provided. The sample is collected from a site containing pollutants. Pollutants are then isolated from the sample. Further, a knowledgebase various types of degraders of those pollutant is created. Using this knowledgebase a map of microbes is created. The map of microbes is then used to design a first microbial consortia and a second microbial consortia which together contributes genes, proteins and enzymes required for degradation of the pollutants. And finally, a concoction of the first and/or second microbial consortia is administered on the site. The method further comprises the checking the efficacy of the administered consortia and further comprise re-administration of the concoction.
Industrial processes and equipment are prone to operational changes and faulty operation of such processes and equipment can adversely affect output of the overall setup. Existing systems for monitoring and fault detection consider individual instances of data for fault detection, which may not be suitable for industrial processes. Disclosed herein is a system and a method for anomaly detection in an industrial enterprise. The system collects data from a plurality of sensors as input. The system processes the collected data along temporal dimension, during which the data is split to multiple segments of fixed window size. Data in each segment is processed to identify anomalous data, and data in segments identified as containing the anomalous data is further processed to identify one or more sensors that are faulty and are contributing to the anomalous data.
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
G01F 1/00 - Measuring the volume flow or mass flow of fluid or fluent solid material wherein the fluid passes through a meter in a continuous flow
55.
SYSTEM FOR SECURING COMMUNICATION BETWEEN CENTRAL CONTROLLER AND SIGNALING DEVICES IN TRAFFIC SIGNALING NETWORKS
The present disclosure provides a system for securing communication between Central Controller and signaling devices including actuator devices and signaling sensors used in railway and road traffic signaling networks. Conventional signaling systems use unsecured metal cables to communicate between the Central Controller and the signaling devices, making them vulnerable to unauthorized intrusion and mischief. In the present disclosure, two uniquely addressable communication modules, one (SCM1) securely housed with the Central Controller and another (SCM2) securely housed in an assembly also containing the signaling device and the related power switches are used to establish a transparent but standard secure digital communication protocol between them to authenticate and validate mutual communication, making them secure and safe from intrusion and undesirable manipulation.
The operation of alumina rotary kiln is complex process with the involvement of multiple variables. This disclosure relates generally to method and system for monitoring and optimizing the operation of an alumina rotary kiln. The system is utilizing a digital twin of the alumina rotary kiln for real-time monitoring, controlling and optimization of a plurality of process parameters of the alumina rotary kiln through automatic learning and diagnosis. The system comprises a thermal model and a quality model for identifying an optimum set of parameters for the operation of the alumina rotary kiln by satisfying a predetermined criterion. The system is configured to optimize the operation in real-time based on the product quality requirements, fuel changes, kiln conditions and ambient variations.
B01D 53/14 - Separation of gases or vapours; Recovering vapours of volatile solvents from gases; Chemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases or aerosols by absorption
57.
METHOD AND SYSTEM FOR MAPPING READ SEQUENCES USING A PANGENOME REFERENCE
There is a demand for low-cost efficient robust method for mapping read sequences with genome variation graph in genomic study. This disclosure herein relates to a method and system for mapping read sequences with genome variation graph by constructing a subgraph using a novel combination of graph embedding and graph winnowing techniques. The system processes the obtained plurality of read sequences and a genome variation graph for constructing the subgraph by computing an embedding for the genome variation graph utilizing a graph embedding technique. Further, graph index is generated for the genome variation graph based on the embedding and the genome variation graph utilizing the graph winnowing technique. Then computes gapped alignment score for read sequence (r) with its corresponding subgraph. Thus, enables a reliable method for read sequence with accurate, memory efficient and scalable system for mapping read sequences with genome variation graph.
Typically when labels are randomly fused into a video, it results in occlusion of main subjects in every video frames. Further, random placement of labels corresponding to multiple objects in the frame may confuse the user as he/she may struggle to identify label corresponding to each object. Disclosed herein are a method and system for identifying optimum location for label placement in a video. For a given video, the system generates a plurality of object-label pairs, and also a saliency map. The object-label pairs and the saliency map are processed by the system to identify the optimum location for placing each label such that at the optimum location conditions related to occlusion, closeness to object, intersection between connectors, and diagonal heuristic and central bias are satisfied.
Stubble burning is a serious problem resulting in pollution attributable to smog, loss of nutrients in the top soil, and risk of fires spreading out of control. Existing methodologies have attempted to predict burning areas, but have failed to do so because of inefficient sensing mechanism. Present disclosure proposes a system and method to compute burning index score pertaining to crops by detecting harvest season and predicting probable areas of burning by combining current year's crop area map along with harvesting period and historical hot spot information. Computation of the burning index score is accomplished based on inputs received from at least one of satellite imaging, multi - spectral drone based sensing devices and crowdsourcing information. This will help to prioritize the area for taking corrective measures such as training of farmers, availability of resources, optimizing the resources schedule, etc.
Existing techniques in precision farming comprise supervised event detection and need labeled training data which is tedious considering the large number of crops, differences therein and even larger number of diseases and pests. The present disclosure provides an unsupervised method and uses images of any size captured in an uncontrolled environment. The methods and systems disclosed find application in automatically localizing and classifying events, including health state and growth stage and also estimating an extent of manifestation of the event. Information of spatial continuity in pixels and boundaries in a given image is used to update the feature representation and label assignment to every pixel using a fully convolutional network. Back propagation of the pixel labels modified according to the output of a graph based method helps the neural network to converge and provide a time efficient solution.
This disclosure relates generally to system and method for managing dynamically adaptive supply network. The method includes simulating, by an exogenous model, the supply network in an analytical modeling language using at least a data populated from the supply network through a sensory data processing framework. The exogenous model provides a plurality of candidate analytical solutions corresponding to an event condition associated with the supply network based on the simulation. Corresponding to the event condition in a global context of the supply network, a satisfiable solution is identified. An endogenous model corresponding to the supply network is modified based on the satisfiable solution to obtain a modified endogenous model. The modified endogenous model is transformed into a programming language to obtain an updated endogenous model. The supply network is modified as directed by the updated endogenous model.
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G06F 7/00 - Methods or arrangements for processing data by operating upon the order or content of the data handled
Plant health estimation is required to be performed so as to detect any health issues in early stages, so as to take counter measures. Existing systems for the plant health estimation perform the health estimation by considering data obtained from satellite images of the plants being monitored. However this alone may not be much effective as the satellite images fail to provide information on many parameters which have direct or indirect impact on health of the plants. Disclosed herein are a method and a system for plant health estimation, wherein the system performs health estimation at a macro level and a micro level. The macro level health estimation is done using satellite images of the plants as inputs, whereas the micro level health estimation is done by collecting and processing sensor data with respect to various parameters that affect health of a plant.
There is no mechanism for vehicle utilization and optimization through continuous and incremental planning which ensures that transportation plans are based on real-time conditions. The present invention discloses systems and methods for vehicle utilization and optimization based on self-learning mechanism. A machine learning model for dynamic association of users to vehicles is provided that learns previously clubbed patterns of users with their corresponding locations. The learnt previously clubbed patterns are utilized for determining association between previously clubbed locations which is further utilized to obtain an optimal set of locations. The users are dynamically associated to vehicles allocated for the obtained optimal set of locations by honoring one or more social and vehicle constraints. The proposed system has self-learning capability which ensures effective vehicle utilization and optimization in real time.
G05D 1/00 - Control of position, course, altitude, or attitude of land, water, air, or space vehicles, e.g. automatic pilot
G05D 1/02 - Control of position or course in two dimensions
G06N 7/00 - Computing arrangements based on specific mathematical models
G06N 99/00 - Subject matter not provided for in other groups of this subclass
G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time
H04W 4/02 - Services making use of location information
64.
SYSTEM AND METHOD FOR OPERATION OPTIMIZATION OF AN EQUIPMENT
jtttttjttjtt) for a series of subsequent equipment instances after expiry of the predefined sequence of timestamps associated with a first equipment instance.
G05B 19/045 - Programme control other than numerical control, i.e. in sequence controllers or logic controllers using logic state machines, consisting only of a memory or a programmable logic device containing the logic for the controlled machine and in which the state of its outputs is dependent on the state of its inputs or part of its own output states, e.g
G05B 19/418 - Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control (DNC), flexible manufacturing systems (FMS), integrated manufacturing systems (IMS), computer integrated manufacturing (CIM)
G05B 17/02 - Systems involving the use of models or simulators of said systems electric
G05B 19/04 - Programme control other than numerical control, i.e. in sequence controllers or logic controllers
G05B 19/042 - Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
G05B 19/406 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
Health of perishable commodities such as eatables deteriorate over time. State of art systems for health monitoring of perishable commodities rely on measurement of limited parameters and also fail to consider effect of environment on the health of the perishable commodities. Disclosed herein is an apparatus and method for multimodal sensing and monitoring of perishable commodities. The apparatus allows to change environment within a closed chamber in which the perishable commodity being monitored is kept, and in turn allows to generate health data in different environment settings. This data is used to generate a health model. Data collected in real-time are processed with the health model to establish a correlation with at least one image, wherein each of such images in the health model represents certain health state. Based on the established correlation, health of the perishable commodity is determined.
Systems and methods for data migration in multi-layer model-driven applications is provided. The traditional systems and methods simply provide for comparison based migration approaches, and thus face severe challenges in case of model-driven applications, wherein continuous capturing of transformations in model changes is required. Embodiment of the proposed disclosure provide for a changelog based data migration methodology by modelling, a model-driven application conceptual model; generating, a plurality of optimized data models from the modelling; extracting, from each of the plurality of optimized data models, at least one changelog capturing one or more model changes and transformations in each of the plurality of optimized data models; and executing the data migration using each of an executing changelog.
Tool wear monitoring is critical for quality and precision of manufacturing of parts in the machining industry. Existing tool wear monitoring and prediction methods are sensor based, costly and pose challenge in ease of implementation. Embodiments herein provide method and system for monitoring tool wear to estimate Remaining Useful Life (RUL) of a tool in machining is disclosed. The method provides a tool wear model, which combines tool wear physics with data fitting, capture practical considerations of a machining system, which makes the tool wear prediction and estimated RUL more stable, reliable and robust. Further, provides cost effective and practical solution. The disclosed physics based tool wear model for RUL estimation captures privilege of physics of tool wear and easily accessible data from CNC machine to monitor and predict tool wear and RUL of the tool in real-time.
G05B 19/4065 - Monitoring tool breakage, life or condition
B23Q 17/09 - Arrangements for indicating or measuring on machine tools for indicating or measuring cutting pressure or cutting-tool condition, e.g. cutting ability, load on tool
G01N 3/58 - Investigating machinability by cutting tools; Investigating the cutting ability of tools
G05B 19/18 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
G05B 19/404 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by control arrangements for compensation, e.g. for backlash, overshoot, tool offset, tool wear, temperature, machine construction errors, load, inertia
G05B 19/406 - Numerical control (NC), i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
68.
SYSTEMS AND METHODS FOR SIMULATION OF HUMANS BY HUMAN TWIN
Systems and methods for simulation of humans using a human twin is provided. The traditional systems and methods cite for human body digitization but do not provide for real-time simulation of humans using digital twins. The embodiments of the proposed disclosure provide for optimizing a real-time operating environment by simulating humans by obtaining a first set of information comprising real-time data of humans from a plurality of sources; extracting, based upon the first set of information, a second set of information comprising real-time contextually correlated data corresponding to humans; creating, from the second set of information, a plurality of process models; simulating, by implementing the human twin, each of the plurality of process models and the first set of information for generating a set of simulated information; and optimizing the real-time operating environment using the set of simulated information.
A processor implemented method for learning knowledge graph schema via dialog is provided. The method include receiving, a set of statements pertaining to a natural language and an initial schema of at least one knowledge graph; determining, a plurality of possible interpretations associated with at least one statement from the set of statements; identifying, at least one of (i) mentions of types, and (ii) instances of initial schema entities, associated with at least one statement from the set of statements; identifying, set of possible statement graphs and corresponding probabilities associated with the at least one statement from the set of statements; generating, set of candidate statement graphs by sampling the set of possible statement graphs from a distribution; identifying, plurality of expert preferred statement graphs from the generated set of candidate statement graphs; and identifying, a subsequent preferred question from a set of possible questions to query an domain expert.
Systems and methods for predicting execution time of multi-threaded and memory bandwidth intensive batch jobs based upon a simulation of a Central Processing Unit (CPU) and memory contention is provided. None of the traditional systems and methods provide for predicting the execution time of the multi-threaded and memory bandwidth intensive batch jobs based upon a memory bandwidth requirement and a distinct service demand of threads. Embodiments of the present disclosure provide for predicting the execution time of a set of multi-threaded and memory bandwidth intensive batch jobs executing concurrently by identifying, the memory bandwidth requirement and the distinct service demand of each of the threads; auto-designing, based upon the identified memory bandwidth requirement and the distinct service demand, a job execution model; simulating the job execution model; and predicting, based upon the simulation, the execution time of each of the set of multi-threaded and memory bandwidth intensive batch jobs.
The present disclosure provides an actor model based multi robot system and optimized task scheduling method in an operating environment. Most existing architectures does not provide dynamic and optimized task allocation methods for multi robot systems with human collaboration. The disclosed architecture of the multi robot system is based on an actor model, where each physical robot has an associated robot actor in the form of a unique single threaded application. The disclosed optimized task scheduling method assigns tasks dynamically by identifying a suitable physical robot or a suitable human operator using a bid value concept and by provides an integrated solution to the problems such as Multi Agent Path Finding (MAPF), Multi Robot Task Coordination (MRTC), and Multi Robot Task decomposition (MRTD) while catering to industry 4.0 operating environments.
This disclosure relates generally to a method and system for online handwritten signature verification providing a simpler low cost system. The method comprises extracting signature data for the subject from a sensor array for the predefined time window at regular predefined time instants. Further, differentiating the matrix row wise and column wise to generate a row difference matrix and a column difference matrix. Further, determining an idle signature time fraction for the extracted signature data of the subject being monitored from the column difference matrix. Further, determining a plurality of signature parameters based on the row difference matrix and the column difference matrix. Further, analyzing the idle signature time fraction and the plurality of signature parameters of the subject being monitored based on a Support Vector Machine (SVM) classifier, wherein the SVM classifier performs online classification of the extracted signature data into one of a matching signature class and a non-matching signature class.
Systems and methods for execution time prediction of batch jobs based upon service demand of threads and instantaneous Central Processing Unit (CPU) utilization. The traditional systems and methods provide for predicting the execution time of the batch jobs based upon clock time or previously logged execution times of the batch jobs. Embodiments of the present disclosure provide for predicting the execution time of each multi-threaded batch job amongst a set of concurrently executing multi-threaded batch jobs by clustering one or more threads from a set of multi-threaded batch jobs based upon a distinct service demand of the one or more threads; deriving an instantaneous value of the CPU for the one or more threads clustered; auto-designing a job execution model; simulating the job execution model based upon the one or more threads clustered and the instantaneous CPU utilization of one or more multi-threaded batch jobs to predict the execution time.
G09F 9/46 - Indicating arrangements for variable information in which the information is built-up on a support by selection or combination of individual elements in which the desired character is selected from a number of characters arranged one behind the other
74.
A SERVER CONTROLLED FRAMEWORK FOR CONTROLLING WIDGETS OF A TABULAR STRUCTURE
The present disclosure is related to a system and method for controlling widgets of a table on a display using a server. The system is configured to receive inputs from user for controlling widgets of the table by specifying at least one configuration at the server end for at least one of a plurality of predefined configurations. It determines a plurality of events and invokes at least one event handler at the server end according to a predefined interface for the determined event. The event handler would then provide the component with response behavior. Further, the system specifies a plurality of observable properties wherein any change in the properties would be automatically tracked by the system and invoking the specified at least one event handler to control at least one widget of the table.
G06F 3/00 - Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
75.
METHOD AND SYSTEM FOR PRE-EMPTIVE DEVIATION DETECTION FOR TELECOM PROCESS FLOW USING DIGITAL TWIN
A method and a system for pre-emptive deviation detection for a telecom process flow using digital twin. The method and system pre-emptively detects critical failures in the telecom process flow even before they occur by pre-emptively detecting deviations based on digital twin. The proposed pre-emptive deviation is dynamically detected based on digital twin wherein, a simulated digital twin of telecom process flow is compared with a simulated predicted telecom process flow. Further based on pre-emptively detected deviation, notifications are displayed to execute preventive measures to ensure critical failures are avoided.
A system and method for talent insight generation and recommendation is disclosed. The method includes obtaining a plurality of technical keywords associated with technological skills and technology vendors from a plurality of technical data sources. The plurality of technical keywords are parsed to obtain a plurality of target entities based on a plurality of rules corresponding the plurality of technical data sources. The plurality of target entities are associated with a corresponding technical context. The plurality of target entities are classified into a plurality of categories based at least on the corresponding context to obtain a plurality of classified target entities, using a supervised machine learning model. The plurality of classified target entities are linked to generate a talent insight graph.
G06F 15/18 - in which a program is changed according to experience gained by the computer itself during a complete run; Learning machines (adaptive control systems G05B 13/00;artificial intelligence G06N)
77.
METHOD AND SYSTEM PROVIDING INTEROPERABILITY BETWEEN BLOCKCHAIN ECOSYSTEMS
This disclosure relates generally to a system and method to interoperability between two or more independent ecosystems. Wherein the first ecosystem comprises a blockchain platform. The system identifies a smart contract of the blockchain platform, a set of protocols of the second ecosystem, and a format of a message of the second ecosystem. The identified smart contract, the identified set of protocols, the identified format of the message and a meta-data driven service orchestration for the transaction are analyzed by the system. Further, the system invokes at least one application programming interface (API) based on the analysis of the smart contract of the first ecosystem, the set of protocols and the format of the message of the second ecosystem, and the metadata driven service orchestration for the transaction. Finally, the system is enabled to transmit the at least one transaction between the first ecosystem and the second ecosystem.
This disclosure relates generally to a system and method for blockchain coexistence. The blockchain coexistence between a blockchain ecosystem and a non-blockchain ecosystem is enabled by a gateway which establishes communication between any existing system and the blockchain ecosystem. Herein, the system is used to connect a blockchain solution with at least one existing application by utilizing the gateway framework. The gateway framework includes a gateway and information on a set of smart solutions. The gateway incudes a simple Java APIs (Application Programming Interfaces) on one side for the existing systems or the traditional applications to connect to the distributed ledger application programming interface (DLAPI) on the other side for connecting with the different block chain technologies.
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
This disclosure relates generally to a system and method to generate a blockchain application for different blockchain technologies. The system provides a blockchain development framework that allows business application (i.e., logic) to be written once irrespective of underlying blockchain technologies. The blockchain development framework works in two stages. In the first stage, a user interface is provided to capture the metadata and a set of functions. Further, the blockchain development framework generates underlying blockchain technology specific code in the second stage. The user can write business logics for the business use case in a platform agnostic programming language. The smart contract can then be compiled and deployed on the underlying blockchain platform specified by the user. This enables easy portability among blockchain technologies and thus reduces human intervention while programming.
H04L 9/06 - Arrangements for secret or secure communications; Network security protocols the encryption apparatus using shift registers or memories for blockwise coding, e.g. D.E.S. systems
H04L 9/32 - Arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system
G06F 17/30 - Information retrieval; Database structures therefor
Systems and methods for managing Internet of Things (IoT) data for a smart city using an IoT datahub. The traditional systems and methods provide for an IoT platform for smart cities but none of them provide for an integrated platform which facilitates abstracting, storing and sharing contextually enriched structured IoT data referring PAS 182 model standards. Embodiments of the present disclosure provide for managing Internet of Things (IoT) data for smart cities using the IoT datahub by obtaining data from devices or sensors connected to the IoT datahub, transforming the data, contextually correlating the data, enhancing value of the contextually correlated data, aggregating the contextually correlated data to generate a structured data by an unified Application programming Interface (API) to be accessed by users connected to the IoT datahub.
Systems and methods for integrating heterogeneous systems in an enterprise ecosystem is provided. The traditional systems and methods provide for configurable interfaces, reducing coding efforts and message translations but do not focus on seamless bi-directional communications and collaborations and an integrated platform supporting all Enterprise Architecture Integration (EAI) patterns. The embodiments of the present disclosure provide for a simplified integration between one or more systems and synchronous integration with one or more external systems by providing for a data exchange layer (DXL) application based transformation of an external simple object access protocol (SOAP) web service to a different SOAP web service or a representational state transfer (RESTful) web service and vice versa, importing a database data into the DXL for extracting the imported data into one or more input files and performing using the database data extracted, a transformation of one or more files of different format.
A phase separation apparatus and a method for phase separation are provided. The apparatus includes a spiral shaped body, split outlets and an adjustable splitter. The spiral shaped body includes an inlet portion to receive a mixture of phases associated with distinct effective masses, an outlet portion, and multiple helical turns stacked between the inlet and outlet portion. Portion of one or more helical turns are twisted to form a twisted portion of said helical turn having opposite walls of a preceding helical turn turned relative to one another in opposite directions. The split outlets are configured at walls of the preceding helical turn to withdraw the phases based on an effective mass of said phases. The adjustable splitter is movably configured at least a portion of a cross section of the spiral shaped body to facilitate separate withdrawal of the one or more phases of the mixture.
B01D 45/16 - Separating dispersed particles from gases or vapours by gravity, inertia, or centrifugal forces by centrifugal forces generated by the winding course of the gas stream
B01D 21/26 - Separation of sediment aided by centrifugal force
B01D 53/24 - Separation of gases or vapours; Recovering vapours of volatile solvents from gases; Chemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases or aerosols by centrifugal force
B03B 5/62 - Washing granular, powdered or lumpy materials; Wet separating by hydraulic classifiers, e.g. of launder, tank, spiral or helical chute concentrator type
A mixing apparatus for mixing ingredients is provided. The mixing apparatus includes a container, an impeller assembly, and one or more protruding attachments. The container holds the ingredients. The impeller assembly is rotatably positioned in the container for stirring the ingredients. The motion of the ingredients forms a vortex in the container. The one or more protruding attachments is supported within the container by a support mechanism and positioned to vertically move upwards and downwards direction within the container. The protruding attachment(s) redirects at least a portion of the plurality of ingredients between a top portion of the vortex and a bottom portion of the vortex.
A method and system for managing lighting schedule of a plurality of lamps set up in an Area of Interest (AOI). The method provides generating an optimized lighting schedule for every lamp of the plurality of lamps set up in the AOI. The optimization is based a set of constraints that are applied to an optimization function. The set of constraints are generated from spatio- temporal predictions, which are derived by analyzing area data of the AOI. The area data may be obtained from a plurality of data sources. The set of constraints also include a plurality of regional factors associated with the AOI. The predictive component can be overridden to generate revised optimized lighting schedule when real time area data such as traffic density data or subject density data or the like are obtained from sensors at every lamp.
F21V 23/04 - Arrangement of electric circuit elements in or on lighting devices the elements being switches
G05B 13/02 - Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
H05B 33/08 - Circuit arrangements for operating electroluminescent light sources
85.
SYSTEMS AND METHODS FOR SCHEDULING TASKS AND MANAGING COMPUTING RESOURCE ALLOCATION FOR CLOSED LOOP CONTROL SYSTEMS
Systems and methods of scheduling tasks and managing computing resource allocation in a closed loop control system is provided. The system uses historical run-time statistics that includes expected run-time (μ) and standard-deviation (σ) in run-times, of the tasks. The run-time statistics are used by the system to first predictively allocate and then to order the execution of the tasks in order to minimize the make-span. The schedule predicted is a queue of tasks to be executed on each computing resource ordered by a function of the expected run-time (μ) and standard-deviation (σ). Reactive scheduling involves periodically probing the progress and reacting to imbalances in progress across computing resources by switching tasks between lagging and leading computing resources.
System and method for digitized digit symbol substitution test (DSST) are disclosed. In an example, a display area of a digitized DSST device is partitioned into multiple bins. Further, a series of number symbol pairs is displayed as a lookup table on top of the display, termed as a lookup area. Furthermore, a question and answer (QA) pair corresponding to the series of number symbol pairs to an examinee in multiple trials. In addition, feature values for the QA pair are computed in each of the multiple bins in the trials, wherein the feature values comprise a response time and an accuracy of response by the examinee. Moreover, probabilities of the feature values are determined in each of the multiple bins. Also, an entropy value based on the probabilities of the feature values is computed in each of the multiple bins providing information on distribution.
Object recognition based estimation of planogram compliance provides an expected arrangement of products in shelves. Identifying whether a product is placed in an appropriate location of a shelf is a challenging task due to various real-time parameters associated with image capturing. In the present disclosure, an input image associated with shelf of a retail store is received and a product images are cropped. Further, a set of reference images stored in a database are scaled corresponding to the input image. Further, one or more composite matching scores are calculated based on normalized cross-correlation and shape based feature matching to obtain one or more probable product images associated with a location. Further, a Directed Acyclic Graph (DAG) is constructed based on the one or more composite scores and the one or more probable products. Finally, an optimal matching product image for a particular location is obtained from the DAG.
System and method for predicting repeat behaviour of customers are disclosed. In an embodiment, the method includes abstracting a customer interaction data associated with interactions of the customer with respect a target entity into a common data format (CDF) to obtain an abstracted customer interaction data. Based on at least a portion of the abstracted customer interaction data, a set of features corresponding to the target entity are extracted. The set of features characterizes customer interaction with respect to the target entity. Based on the set of features, a prediction model is predicted to predict repeat behaviour probability of the customer with respect to the target entity.
The present application provides a method and system for monitoring of mental effort is disclosed. The method and system disclosed herein comprise acquiring GSR data using a GSR sensor wherein the GSR data is collected while performing plurality of tasks of varying cognitive load, preprocessing the acquired data for artifact removal and generating a preprocessed data, extracting plurality of features from the preprocessed GSR data using feature extraction techniques including Peak Detection, Tonic power and Fluctuation analysis, selecting a most discriminative feature from the plurality of extracted feature based on a discriminative index, calculating a score and generating an effort index. The system and method also comprise determining an optimal rest period which is used as reference for computation of the effort index.
System and method for aiding communication for subjects suffering from paralysis of muscles controlled by peripheral nervous system are disclosed. A method for aiding communication for said subjects includes capturing, from a plurality of sensors, sensor data generated based on an interaction of a subject with an interactive UI. The plurality of sensors includes one or more body-parts movement tracking sensors for tracking motion of body- parts of the subject and one or more physiological signal sensors for monitoring physiological signals generated from the subject during the interaction. A plurality of model parameters indicative of characteristics of the subject related to the interaction are determined based on the sensor data. The navigation at the interactive UI is controlled on the plurality of model parameters.
A system and method for detection and analysis of learner's / performers cognitive flow have been provided. The system is configured to measure the cognitive state of the performer, while they are performing tasks of various complexity levels, using physiological responses like brain activation, heart rate variability and galvanic skin response. The system uses a Bayesian network based framework to probabilistically evaluate the cognitive state of the learner from the difficulty levels of the tasks, IQ level of the learner and observations made using the physiological sensing. The system also measures the actual cognitive state using a questionnaire. The predicted cognitive state and the actual cognitive state is compared and based on the outcome of comparison a relevant step is taken.
The present disclosure relates to sequence to sequence mapper based systems and methods for health monitoring and prognostics of a system via a health index (HI). The sequence to sequence mapper learns to reconstruct normal time series behavior, and thereafter uses reconstruction error to estimate the HI. The HI is used for generating health behavior trend, detection of anomalous behavior, and remaining useful life (RUL) pertaining to a monitored system. The present disclosure does not rely on domain knowledge, as in the prior art, when estimating the health index. The HI of the monitored system can be determined irrespective of the predictability of the time series data generated from the monitored system. Likewise, the present disclosure is relevant to time series data of varying nature: predictable, unpredictable, periodic, aperiodic, and quasi-periodic time series; short time series and long time series; and univariate and multivariate time series.
System and method for thermo-fluid management in a conditioned space are disclosed. The method includes retrieving geometry and operational information of the conditioned space from a conditioned space data. A 3D geometry of the conditioned space is automatically generated in a format suitable for a mesh generation model for numerical analysis by parsing the conditioned space data. A mesh is created within the 3D geometry using the mesh generation model. A simulation data is generated based at least on an operational data of the plurality of components. The simulation data is applied on the mesh to simulate a thermo- fluid model of the conditioned space.
A system and method for achieving auto-adaptive clustering in a sensor network has been explained. The system performs a hierarchical clustering in sensor networks to maximize the lifetime of the network. The system includes a set of sensor nodes and a sink node. The clusters in sensor networks are formed automatically from a large number of deployed nodes where the cluster characteristics are driven by the measurement requirements defined by the end-user. The system also employs a clustering algorithm to achieve adaptive clustering. The processor further includes a first level clustering module for grouping the set of sensor nodes into data level clusters based on the measurements. The processor further includes a second level clustering module for grouping the set of sensor nodes in the data level clusters into the location level clusters based on location. In another embodiment, that clustering can go on to more than two levels.
A system and method for retrieving a set of result documents from a distributed database pertaining to a material science query given by the user. The system comprises an extraction module to extract attributes of material science from a set of documents stored in distributed database. A post-processing module of the system is configured to filter the extracted information components and resolve ambiguities that arise during the extraction. Further, an indexing module of the system to generate an index table of the filtered information components to mark the location of the documents in the distributed database. A query processor module is configured to convert the user query into an updated query and a searching module to execute the updated query on the index table to retrieve a set of result documents from the distributed database. The result documents, pertaining to the user query, are the final output of the system.
Synchronized and coordinated activation of the postural muscles of the trunk and lower limbs is required for maintaining equilibrium and balance in human body. Poor postural balance control causes injury or falls in huge population and is supposed to be a critical factor of common motor skills. Single Leg Stance (SLS) is a good option for measuring postural control in any stance, which not only assesses postural steadiness in a static position by a temporal measurement (SLS-duration) but also analyses the role of body skeleton joints in postural stability and correction. This method provides a quick, reliable and easy way to screen their patients for fall risks and is easily incorporated into a comprehensive functional evaluation for older adults. An automatic unobtrusive system is proposed here to measure SLS duration and body balance. For this purpose, vibration-jitter analysis is performed which gives a clear view of relative variation of frequency of different skeleton joints over time. The whole processing is done on the dataset of skeleton joints obtained from Kinect. The dataset of skeleton joints through the Kinect setup, is used instead of video, which addresses user privacy concerns.
System and method for contract management in a data marketplace are disclosed. In an embodiment, the system performs refactoring of a contract, during which the system extracts terms and conditions from the contract and generates a simplified view of the contract. The system further performs a requirement validation based on the contract, during which the system determines features of data entity matches requirements specified by a first party or not, based on domain specific ontologies. If the data entity features are not matching with the requirements, then the system fetches one or more relevant attributes from a list of ontologies, verifies whether the features of entity along with the selected feature(s) satisfy the requirements or not. The system accordingly generates an agreeable requirement document as output of the requirement validation.
A method and system is provided for allocating a suitable price discovery mechanism in a data marketplace. The system takes a set of requirements from one or more buyers and a set of specifications for the data products from one or more sellers. The matching is performed on the set of requirements and the set of specifications of the data products to determine whether data transaction should be proceeded or not. The output is then provided to the classification module to classify the data marketplace to choose the most suitable price discovery mechanism which can be used for a particular data transaction in the data marketplace. The system can use of any of the following price discovery techniques. Bid order matching, auctioning or direct negotiation. Once the price is finalized, the finalized price then can be send to an order management module of the data marketplace.
A method and system is provided for managing complaint and reputation in a multi-party data marketplace. The system is managed by an independent external entity to monitor the data transactions in an unbiased manner. The system considers the data as commodity or resource, which is perishable and whose worth might decay with time. The system defines new parameters for reputation and liability calculation (based on complaints), for example, consideration of peer and trust network, history of peering and transaction, automatic decay of reputation and liability in case of inactive participants. According to another embodiment, the disclosure also handles any kind of collusion between external or internal entities / parties / participants. Whereas in another embodiment the disclosure also identifies and restrict influencers in a multi-party data marketplace.
Systems and methods for computing data privacy-utility tradeoff is disclosed. Large data hubs like data marketplace are a source of data that may be of utility to data buyers. However, output data provided to data sellers is required to meet the privacy requirements of data sellers and at the same time maintain a level of utility to data buyers. Conventionally known methods of achieving data privacy tend to suppress components of data that may result in reduced utility of the data. Systems and methods of the present disclosure compute this tradeoff to establish need for data transformation, if any, before data is shared with data sellers.
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