2021 5th International Conference on Trends in Electronics and Informatics (ICOEI), 2021
The main objective is to propose a reliable framework for data routing in wireless infrastructure... more The main objective is to propose a reliable framework for data routing in wireless infrastructure without any delays and loss from one end to the other. Therefore, a Reliable Routing through Enhanced Particle Swarm Optimization (RR_EPSO) is proposed here. The best route is identified from the Gbest nodes through route stability task and Gbest nodes are selected from the node fitness measure process. The node fitness measure is done by evaluating the node's remaining energy level and its maximum availability of bandwidth. Therefore, this method helps in reducing link failures and enhances the network lifetime. This proposed reliable routing protocol also enqueue's the other best alternate route if in case any valid path failure happens. Simulation results are given for the analysis of proposed method and to prove its efficiency in terms of delays and energy level.
2017 2nd International Conference on Communication and Electronics Systems (ICCES), 2017
In present Era, knowledge acquisition and extracting potential information in any field is very c... more In present Era, knowledge acquisition and extracting potential information in any field is very complex and voluminous. Information rich Data mining is data processing using sophisticated data search capabilities and statistical algorithms to discover patterns and correlation in large pre-existing database. The frequent pattern supports designing building block and to find out associations rules and prompt relationship between databases. Most important challenges in the framework of the uncertain database are how to handle the security and assigned probability value for each product. It reduces the complexity of stepping up process. To fulfil the gap between existing approach and progressing application requirement, a detailed pragmatic study was conducted. This study evaluates the overall work which is related to the privacy of data classification and visualization and frequent item pattern.
Initial prediction and appropriate medication are the ways to cure Chronic Kidney Disease (CKD) i... more Initial prediction and appropriate medication are the ways to cure Chronic Kidney Disease (CKD) in the early stage of progression. The rate of accuracy in the classification algorithms focuses on the usage of exact algorithms used to select he features in order to minimize the dataset dimensions. The accuracy not only relies on the feature selection algorithms but also on the methods of classification, where it predicts the severities that are useful for the medical experts in the field of clinical diagnosis. To minimize the time for computation and to maximize the classifiers accuracy level, the proposed study, Ensemble Entropy Attribute Weighted Deep Neural Network (EEAw-DNN) classification was aided to predict Chronic Kidney Disease. The rate of accuracy of the EEAw-DNN is surveyed with the help of feature selection using data reduction. Hence Hybrid Filter Wrapper Embedded (HFWE) based Feature Selection (FS) is formulated to choose the optimal subset of features from CKD set of ...
Abstract Deep Neural Network (DNN) in recent era offers new opportunities to manage the productio... more Abstract Deep Neural Network (DNN) in recent era offers new opportunities to manage the production systems with increasing complexity. In this paper, DNN is trained with discrete event simulation and a process based association to make the job shop an autonomous one. This intelligent system operates well in complex environment with constrained time limits while making optimal decisions. The DNN is henceforth combined with constrained time limits for the process of production control. The system is implemented typically in semiconductor manufacturing industries on complex job shops of a wafer fab case. The DNN is trained in such a way that it operates in complex environment with timing constraints that ships the job in accurate way without flaws in operation. The DNN rewards the selection with reduced time constraint, which tends to operates with most critical batch list. The study therefore shows that the DNN manages well the timing constraints than the standard benchmark technique.
International Journal of Engineering & Technology, 2018
Kidney Disease and kidney failure is the one of the complicated and challenging health issues reg... more Kidney Disease and kidney failure is the one of the complicated and challenging health issues regarding human health. Without having any symptoms few diseases are detected in later stages which results in dialysis. Advanced excavating technologies can always give various possibilities to deal with the situation by determining important realations and associations in drilling down health related data. The prediction accuracy of classification algorithms depends upon appropriate Feature Selection (FS) algorithms decrease the number of features from collection of data. FS is the procedure of choosing the most relevant features, removing irrelevant features. To identify the Chronic Kidney Disease (CKD), Hybrid Wrapper and Filter based FS (HWFFS) algorithm is proposed to reduce the dimension of CKD dataset. Filter based FS algorithm is performed based on the three major functions: Information Gain (IG), Correlation Based Feature Selection (CFS) and Consistency Based Subset Evaluation...
2021 5th International Conference on Trends in Electronics and Informatics (ICOEI), 2021
The main objective is to propose a reliable framework for data routing in wireless infrastructure... more The main objective is to propose a reliable framework for data routing in wireless infrastructure without any delays and loss from one end to the other. Therefore, a Reliable Routing through Enhanced Particle Swarm Optimization (RR_EPSO) is proposed here. The best route is identified from the Gbest nodes through route stability task and Gbest nodes are selected from the node fitness measure process. The node fitness measure is done by evaluating the node's remaining energy level and its maximum availability of bandwidth. Therefore, this method helps in reducing link failures and enhances the network lifetime. This proposed reliable routing protocol also enqueue's the other best alternate route if in case any valid path failure happens. Simulation results are given for the analysis of proposed method and to prove its efficiency in terms of delays and energy level.
2017 2nd International Conference on Communication and Electronics Systems (ICCES), 2017
In present Era, knowledge acquisition and extracting potential information in any field is very c... more In present Era, knowledge acquisition and extracting potential information in any field is very complex and voluminous. Information rich Data mining is data processing using sophisticated data search capabilities and statistical algorithms to discover patterns and correlation in large pre-existing database. The frequent pattern supports designing building block and to find out associations rules and prompt relationship between databases. Most important challenges in the framework of the uncertain database are how to handle the security and assigned probability value for each product. It reduces the complexity of stepping up process. To fulfil the gap between existing approach and progressing application requirement, a detailed pragmatic study was conducted. This study evaluates the overall work which is related to the privacy of data classification and visualization and frequent item pattern.
Initial prediction and appropriate medication are the ways to cure Chronic Kidney Disease (CKD) i... more Initial prediction and appropriate medication are the ways to cure Chronic Kidney Disease (CKD) in the early stage of progression. The rate of accuracy in the classification algorithms focuses on the usage of exact algorithms used to select he features in order to minimize the dataset dimensions. The accuracy not only relies on the feature selection algorithms but also on the methods of classification, where it predicts the severities that are useful for the medical experts in the field of clinical diagnosis. To minimize the time for computation and to maximize the classifiers accuracy level, the proposed study, Ensemble Entropy Attribute Weighted Deep Neural Network (EEAw-DNN) classification was aided to predict Chronic Kidney Disease. The rate of accuracy of the EEAw-DNN is surveyed with the help of feature selection using data reduction. Hence Hybrid Filter Wrapper Embedded (HFWE) based Feature Selection (FS) is formulated to choose the optimal subset of features from CKD set of ...
Abstract Deep Neural Network (DNN) in recent era offers new opportunities to manage the productio... more Abstract Deep Neural Network (DNN) in recent era offers new opportunities to manage the production systems with increasing complexity. In this paper, DNN is trained with discrete event simulation and a process based association to make the job shop an autonomous one. This intelligent system operates well in complex environment with constrained time limits while making optimal decisions. The DNN is henceforth combined with constrained time limits for the process of production control. The system is implemented typically in semiconductor manufacturing industries on complex job shops of a wafer fab case. The DNN is trained in such a way that it operates in complex environment with timing constraints that ships the job in accurate way without flaws in operation. The DNN rewards the selection with reduced time constraint, which tends to operates with most critical batch list. The study therefore shows that the DNN manages well the timing constraints than the standard benchmark technique.
International Journal of Engineering & Technology, 2018
Kidney Disease and kidney failure is the one of the complicated and challenging health issues reg... more Kidney Disease and kidney failure is the one of the complicated and challenging health issues regarding human health. Without having any symptoms few diseases are detected in later stages which results in dialysis. Advanced excavating technologies can always give various possibilities to deal with the situation by determining important realations and associations in drilling down health related data. The prediction accuracy of classification algorithms depends upon appropriate Feature Selection (FS) algorithms decrease the number of features from collection of data. FS is the procedure of choosing the most relevant features, removing irrelevant features. To identify the Chronic Kidney Disease (CKD), Hybrid Wrapper and Filter based FS (HWFFS) algorithm is proposed to reduce the dimension of CKD dataset. Filter based FS algorithm is performed based on the three major functions: Information Gain (IG), Correlation Based Feature Selection (CFS) and Consistency Based Subset Evaluation...
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Papers by S BELINA V J SARA