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Data mining based chronic kidney disease (CKID) prediction

AIP Conference Proceedings 2023年第1期2523卷

作者： T. Sathiya D. Geetha J. Surendiran H. Azath T. R. Ganesh Babu 1Department of Computer Science and Engineering Sona College of Technology Salem Tamil Nadu 636005 India 2Department of Information Science and Engineering BNM Institute of Technology Bengaluru Karnataka India 3Department of Electronics and Communication Engineering HKBK College of Engineering Nagavara Bengaluru Karnataka 560045 India 4School of Computing Science and Engineering VIT Bhopal University India 5Department of Electronics and Communication Engineering Muthayammal Engineering College Rasipuram-637408 Namakkal District TamilNadu India

Nowadays, chronic kidney illness (CKD) is one of the significant reasons for mortality, and it has a drawn-out handicap. The inclining factors for CKD incorporate hypertension, cardiovascular sicknesses, diabetes mellitus, and innate kidney issues. Renal substitution treatment is the treatment of decision for CKD. Information mining is an exact strategy that assists with anticipating the illness utilizing different techniques incorporate calculated relapse, Naive Bayes order, k-closest neighbours, and backing vector machine. Aside from these past procedures, it was essential to use an arrangement strategy for information division as indicated by their determination and relapse technique for discovering hazard *** results of the study reveal that the RNN computations show “91.75%” accuracy, and that IPM offers "96.75%" accuracy. This connection has the benefit that the interplay between expectations is less powerful. It will help experts to initiate treatments for persistent patients on time and will help to detect more individuals within a shorter period of time. In this current review, information is ordered utilizing proposed Identification of Pattern Mining, Recurrent Neural Network strategies, and Regression procedures to help diagnose a patient with CKD.

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Risk based pricing using k-means clustering

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AIP Conference Proceedings 2022年第1期2516卷

作者： N. B. Sanjana M. Ishwarya N. Balaji E. P. Siva 1Department of Computer Science (Software) Engineering SRM Institute of Science & Technology Kattankulathur 603 203 Chennai India 2Department of Mathematics SRM Institute of Science & Technology Kattankulathur 603 203 Chennai India

Credit Risk Analysis is a process adapted by loan associations to evaluate the risk -based pricing for sanctioning loans. The chances of approving loans depend on the customer’s credit score, which includes annual income, banking history, loan, insurance and different elements of risks such as default risk, credit correlation risk, collateral risk, credit concentration risk, rating migration risk and recovery risk. Results of the calculation allow lenders and customers to assess credit profile characteristics. Data Science allows discovering of new patterns within a complex data set which can be an efficient method to compute risk percentage by means of non – hierarchical clustering. K-means is an iterative algorithm - the idea is to use small unstructured groups of data of fixed size, assigned to clusters to be stored in the memory depending on the previous locations of the cluster centroids. It is validated that the suggested technique predicts better accuracy, is a faster and targeted approach than existing methods.

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Reduction in voltage drop of distribution feeders using bifurcation technique - A case study of 11kV feeder of 220kV subdivision

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AIP Conference Proceedings 2022年第1期2463卷

作者： Puneet Chawla T. R. Mudgal Sanjay Dahiya 1Department of Electrical Engineering CDL State Institute of Engineering & Technology Sirsa Haryana (India) 2Department of Physics CDL State Institute of Engineering & Technology Sirsa Haryana (India) 3Department of Computer Sci. & Engg CDL State Institute of Engineering & Technology Sirsa Haryana (India)

State Electricity Boards are main components in Distribution Sector to reduce voltage regulation and voltage drop at load points. It has been observed countrywide that distribution companies/feeders are running in overload conditions because, this system is extended without any proper planning. Now, energy requirement and consumption rates are increasing day-by-day and thus distribution sectors are under tremendous pressure. As a result service conditions and quality of supply to consumers are affecting adversely. These conditions require proper planning of pressured networks for accommodation of future needs as well to reduce above components and the technical losses. There are many methods adopted by researchers with a focus on to improve voltage profile and made suggestions for distribution sector, Deregulation power systems, HVDS system, Distribution Generation, power loss reduction by various optimization techniques. In present study, we have made an attempt to e implement bifurcation technique in feeder for solution in power sectors. By using bifurcation technique a feeder splits up into smaller sections. Object of this technique is to minimize voltage drop. In present work bifurcation technique is implemented at an 11KV distribution feeder in a 220KV subdivision of Punjab State.

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Embedded system based smart walking assistance device for visually impaired people

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AIP Conference Proceedings 2022年第1期2519卷

作者： Swapnil Saurav Gangireddy Prabhakar Reddy B. Ravi Prasad S. K. Mouleeswaran 1Service Now Software India Pvt. Ltd Hyderabad Telangana India 2Department of Computer Science and Engineering Malla Reddy Institute of Engineering and Technology Secunderabad Telangana India 3Department of Computer Science and Engineering Marri Laxman Reddy Institute of Technology and Management Dundigal Telangana India 4Department of Computer Science and Engineering Dayananda Sagar University Bangalore Karnataka India

These papers set out recommendations to prepare a framework for the regeneration of neurons from the stroke patient by present solutions, which normally concentrates the reconstruction robots in order to reduce the patient’s influences as a result of stroke disease. It has an ultrasonic blind handle for speech reproduction. Visually disabled persons have traditionally used a stick to see if barriers are there. But in different respects this stick is inefficient and the individual who uses it must face many problems. The purpose of this article is to provide a better navigational stick for visually disabled persons. The ultrasonic blind handle is more powerful than the current handle as the use of sensors facilitates target tracking. Speech replay helps the blind individual take the right steps to reach the required target and the obstacles. By using a sensor on the stick, pit can be detected.

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Unattended detection in neural OCT image sequences of disease markers

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AIP Conference Proceedings 2022年第1期2519卷

作者： V. Anbarasu Sharanabasappa C. Gandage Z. Vakil V. Antony Asir Daniel 1Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur Tamil Nadu India 2Department of Computer Science and Engineering Poojya Doddappa Appa College of Engineering Hyderabad Karnataka India 3Department of Electronics and Communication Engineering Malla Reddy Institute of Engineering and Technology Hyderabad Telangana India 4Francis Xavier Engineering College Tirunelveli Tamil Nadu India

In treatment, initial diagnosis and the treatment of illness, detection, and quantitative analysis of markers in medical images are important. Supervised computer education allows results to be identified and exploited a priori after the samples of instruction by experts are annotated. But due to the number of required examples of instruction and the restriction of the marker language to recognized individuals, monitoring does not scale well. In this proof of concept research, we suggest unattended recognition of anomalies as marker applicants in retinal optical coherent imagery without a prior description restriction. We classify and categorize marker applicants that often appear in the data and prove that these markers provide a predictive value for the disease detection role. A cautious qualitative study of the established data control indicators shows, in patients with early and late-age macular degeneration, how their quantifiable frequency fits our present knowledge of the diseases. A deep denoise auto encoder is trained in multi-scaled images, and any anomalies are detected in new data with the one-class support vector machine. The anomaly cluster distinguishes stable groups. With these markers, the precision of 81,40% is measured as safe, early AMD, and late AMD cases. The model obtained a region under the Receiver operator of hackney in a second binary classification experiment with publicly accessible safe and mid-Dexter datasets.

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Multiple shooting for large-scale optimal control problems governed by the Navier-Stokes equations

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AIP Conference Proceedings 2022年第1期2425卷

作者： Liang Fang Stefan Vandewalle Johan Meyers 1Department of Mechanical Engineering KU Leuven Celestijnenlaan 300A B3001 Leuven Belgium 2Department of Computer Science KU Leuven Celestijnenlaan 200A B3001 Leuven Belgium

This research proposes and analyzes a multiple shooting based parallel-in-time algorithm for large scale time-dependent optimal control problems governed by the Navier-Stokes equations. The sequential quadratic programming (SQP) method is adopted for solving the equality constrained optimization problem introduced by the multiple shooting strategy. A quasi-Newton method is used, that employs a line search algorithm using an L1 merit function, and a watchdog strategy is used to avoid the Maratos effect. The Karush–Kuhn–Tucker (KKT) system is solved by using a preconditioned conjugate gradient (PCG) method. A block-diagonal preconditioner based on Schur complement is considered, which allows parallel computation in the time domain. For use in the PCG solver, efficient KKT matrix-vector multiplications are studied. The Hessian and inverse Hessian matrix-vector multiplications are approximated by a damped L-BFGS update. The constraint Jacobian matrix-vector multiplications are calcu- lated by linearized and adjoint solvers. Preliminary numerical results for a 2D velocity tracking problem are presented that show a promising efficiency of the proposed method.

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An intelligent road traffic data management for upgrading real time performance

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AIP Conference Proceedings 2022年第1期2426卷

作者： MD. Rafeeq V. Harsha Shastri Ba Anandh V. Shanmugasundaram Prathipati Ratna Kumar D. Jyothsna 1Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Hyderabad Telangana India. 2Department of Computer Science Department Of Computer Science and Engineering Loyola Academy Secunderabad-500010 Telangana India 3Department of Electronics PSG College of Arts & Science Coimbatore - 641 014 Tamilnadu India. 4Department of Electrical and Electronics Engineering Sona College of Technology Salem - 636005 Tamilnadu India.

The distributed road traffic simulation is an important tool for control and analysis of large road traffic networks (e.g., an entire city or even state). For performing the simulation, it is necessary to divide the simulated road traffic network into sub networks, which are then simulated as processes on computers (nodes) of the distributed computer. To ensure a good performance of the distributed road traffic simulation, two aspects should be considered during the division of the road traffic network - the load-balancing of the resulting sub-networks and the minimization of the inter process communication [1, 2]. Legacy transportation systems are among the most important systems that need to be addressed in a proper manner. Congestion is considered as one of the common problems, especially during peak times of the day because of the weakness of the absorptive capacity of the roads network and the inefficiency of the transportation system to meet the required demands of the increasing traffic size

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Creating a cost-effective network of operational resources for wireless networks

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AIP Conference Proceedings 2023年第1期2523卷

作者： Venkateshwara Prasad Bhadrappa Haralayya R. Aruna Jayashree A. Kethsy Prabavathy S. Selvarasu 1Department of Management Studies Sri Sairam Engineering College Chennai Tamil Nadu India. 2Department of Management Studies Lingaraj Appa Engineering College Bidar Karnataka India. 3Department of Electronics and Communication Engineering Rajalakshmi Institute of Technology Chennai Tamil Nadu India. 4Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu India. 5Department of Electronics and Communication Engineering Muthayammal Engineering College Tamil Nadu India

Wireless Sensor Networks (WSNs) gives human civilization a stunning and clever landscape. Connections between different sensors also strategies in the Internet of Things (IoT) contribute to high energy feasting. Study into liveliness conservation and methods of energy-saving are also important. Sustainability in an energy-efficient way due to the sensors' partial power is important for wireless sensors in an IoT network. This paper aims to analyze an IoT network of remote monitoring and access points. Wireless battery charging power delivery methods are getting more mature. The electrical power supply is operated by a charging car for wireless sensors. The data sharing of the IoT network situation is a minimization challenge to conserve electric energy. A three-stage process obtains the solution. A Reboot Artificial Bee Community (RABC) approach is proposed to solve the sub-problems of the data transfer model. The RABC approach has been shown to converge asymptotically to the optimization process. computer modelling demonstrates that energy consumption can be reduced with a strong, robust function using the proposed approach in the intentional network scenario.

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On stable difference scheme for identification elliptic problem with integral and second kind boundary condition

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AIP Conference Proceedings 2021年第1期2334卷

作者： Charyyar Ashyralyyev 1Department of Mathematical Engineering Gumushane University 29100 Gumushane Turkey 2Department of Computer Technology TAU Ashgabat 744000 Turkmenistan

In this study, the first order of accuracy difference scheme for approximate solution of source identification elliptic problem with integral and second kind boundary conditions is considered. Stability and coercive stability estimates for solution of the difference scheme are described. Moreover, test example with computation results is given.

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Stability estimates for a third order of accuracy difference scheme elliptic overdetermined multi-point problem

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AIP Conference Proceedings 2021年第1期2334卷

作者： Charyyar Ashyralyyev Gulzipa Akyuz 1Department of Mathematical Engineering Gumushane University 29100 Gumushane Turkey 2Department of Computer Technology TAU Ashgabat 744000 Turkmenistan

In this work, we discuss a third order of accuracy difference scheme for approximate solution of the elliptic overdeter-mined multi-point problem in the Hilbert space. Functional operator approach is used to study existence and uniqueness of solution of difference problem. Stability, almost coercive stability and coercive stability estimates for solution of difference scheme are established.

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