Pub Date : 2023-02-22DOI: 10.1109/ICECCT56650.2023.10179785
Vudutha Sravanthi, T. Annapurna, V. Krishna, B. Jyothi
Medical and health care have benefited greatly from IoT advancements. This technology helps both patients and doctors get a clear picture of a wide range of illnesses and make accurate diagnosis. The problem of low diagnostic accuracy in breast cancer diagnosis is, however, already included in the standard research approaches. Maintaining a strong foundation for breast cancer management and therapeutic advancement, early detection is essential. However, due to the nonappearance of indications in the early stages, early identification of cancer is challenging. As a result, cancer is still one area of medicine that scientists are working to advance in terms of detection, prevention, and therapy. The use of deep learning methods in mammogram processing has helped radiologists save money in recent years. In the current breast mass classification methods, deep learning knowledges like a (CNN). Although CNN-based systems have improved upon the pictures, several problems remain. Ignorance of semantic characteristics, analysis bound to the present patch of pictures, missing patches in low-contrast mammograms, and ambiguity in segmentation are all problems that need to be addressed. Because of these problems, this study's primary impartial is to create a deep learning-based system for classifying breast tumours in mammographic images as malignant or benign utilising two approaches: feature selection and classification. In this study, a recurrent neural network is employed for classification after the unnecessary data has been removed using the Sooty Tern Optimization Algorithm (STOA). Elite opposition-based learning optimally selects the weight and bias of Long-Short Term Memory (LSTM) (EOBL). Furthermore, two publicly accessible datasets of mammographic pictures are used to equivalence the projected approach to preexisting categorization systems. Comparative studies showed that the suggested strategy outperformed previously developed mammography categorization algorithms.
{"title":"STOA based Feature Selection with Improved LSTM Model for Breast Cancer Diagnosis in IoT","authors":"Vudutha Sravanthi, T. Annapurna, V. Krishna, B. Jyothi","doi":"10.1109/ICECCT56650.2023.10179785","DOIUrl":"https://doi.org/10.1109/ICECCT56650.2023.10179785","url":null,"abstract":"Medical and health care have benefited greatly from IoT advancements. This technology helps both patients and doctors get a clear picture of a wide range of illnesses and make accurate diagnosis. The problem of low diagnostic accuracy in breast cancer diagnosis is, however, already included in the standard research approaches. Maintaining a strong foundation for breast cancer management and therapeutic advancement, early detection is essential. However, due to the nonappearance of indications in the early stages, early identification of cancer is challenging. As a result, cancer is still one area of medicine that scientists are working to advance in terms of detection, prevention, and therapy. The use of deep learning methods in mammogram processing has helped radiologists save money in recent years. In the current breast mass classification methods, deep learning knowledges like a (CNN). Although CNN-based systems have improved upon the pictures, several problems remain. Ignorance of semantic characteristics, analysis bound to the present patch of pictures, missing patches in low-contrast mammograms, and ambiguity in segmentation are all problems that need to be addressed. Because of these problems, this study's primary impartial is to create a deep learning-based system for classifying breast tumours in mammographic images as malignant or benign utilising two approaches: feature selection and classification. In this study, a recurrent neural network is employed for classification after the unnecessary data has been removed using the Sooty Tern Optimization Algorithm (STOA). Elite opposition-based learning optimally selects the weight and bias of Long-Short Term Memory (LSTM) (EOBL). Furthermore, two publicly accessible datasets of mammographic pictures are used to equivalence the projected approach to preexisting categorization systems. Comparative studies showed that the suggested strategy outperformed previously developed mammography categorization algorithms.","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124806081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-22DOI: 10.1109/ICECCT56650.2023.10179845
K. Rajaram, M. N. V. Kumar, C. Nageswari, S. Rajan, C. M. Rubesh
The Traffic Sign Detection system is a component of an advanced driver assist system that notifies and prompts the driver regarding traffic signals and boards in front. An well organized concurrent signal detection and warning structure are presented to assist better with the existing Intelligent Transport System (ITS) and to improve the safety systems for the identification of regulatory indicators. On-board cameras record real-time video and are associated with a computing device for further processing. The process includes image framing which is blurred and distorted with Gaussian noise because of the movement of the vehicle and ambient disturbances. Hence the input image is enhanced using the median filter and nonlinear Lucy-Richardson for deconvolution. This algorithm is best suited for implementation due to its efficiency in providing an optimal and effective graded output of the processed image. Colour segmentation is performed using Y CbCr colour spacing following shape filtering algorithms using template matching. Then, using processed colour-corrected samples, the required sign is extracted as colour and shape from processed photos, allowing the sign to be distinguished from its foreground and background. The role of the classification module is to find the category of noticed traffic indications captured utilizing Multilayer Perceptron neural systems. Compared to other available systems, the proposed system outshines in every aspect treated to obtain the optimum output. The proposed method is one of the major applications of machine learning which uses Lucy-Richardson and the colour segmenting process. The developed system is implemented efficiently and results close to proximity are obtained.
{"title":"Machine Learning Enabled Traffic Sign Detection System","authors":"K. Rajaram, M. N. V. Kumar, C. Nageswari, S. Rajan, C. M. Rubesh","doi":"10.1109/ICECCT56650.2023.10179845","DOIUrl":"https://doi.org/10.1109/ICECCT56650.2023.10179845","url":null,"abstract":"The Traffic Sign Detection system is a component of an advanced driver assist system that notifies and prompts the driver regarding traffic signals and boards in front. An well organized concurrent signal detection and warning structure are presented to assist better with the existing Intelligent Transport System (ITS) and to improve the safety systems for the identification of regulatory indicators. On-board cameras record real-time video and are associated with a computing device for further processing. The process includes image framing which is blurred and distorted with Gaussian noise because of the movement of the vehicle and ambient disturbances. Hence the input image is enhanced using the median filter and nonlinear Lucy-Richardson for deconvolution. This algorithm is best suited for implementation due to its efficiency in providing an optimal and effective graded output of the processed image. Colour segmentation is performed using Y CbCr colour spacing following shape filtering algorithms using template matching. Then, using processed colour-corrected samples, the required sign is extracted as colour and shape from processed photos, allowing the sign to be distinguished from its foreground and background. The role of the classification module is to find the category of noticed traffic indications captured utilizing Multilayer Perceptron neural systems. Compared to other available systems, the proposed system outshines in every aspect treated to obtain the optimum output. The proposed method is one of the major applications of machine learning which uses Lucy-Richardson and the colour segmenting process. The developed system is implemented efficiently and results close to proximity are obtained.","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134137742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-22DOI: 10.1109/ICECCT56650.2023.10179740
Nandhini M, M. V, V. Balaji
In this research article we improvised for absolute detection of edge Labeling by finding out the ordered pairs for an edge label. There are some theorems proves the distinctiveness of the edge labels in previous articles. Suppose that, if all the adjacent nodes from the parent node receives equal value for the edges, such that, the parent node gets changes according to the adjacency of the parent node to achieve non-distinct edge values. Here, the label of the adjacent vertices is static and parent node splits into multifarious singleton vertex, which depends on the dimension n. Thus, the following theorem and proofs emerge from the idea of non-distinct edge labeling of the star graphs. Here we Constructed the Successor Vertex Graphs of Edge Recursion and the lemma is stated of how the vertex function looks for set of all ordered pairs of vertex label to achieve singleton edge labels using double mean labeling.
{"title":"Possibilities of Edge Repetition using Double Mean Labeling","authors":"Nandhini M, M. V, V. Balaji","doi":"10.1109/ICECCT56650.2023.10179740","DOIUrl":"https://doi.org/10.1109/ICECCT56650.2023.10179740","url":null,"abstract":"In this research article we improvised for absolute detection of edge Labeling by finding out the ordered pairs for an edge label. There are some theorems proves the distinctiveness of the edge labels in previous articles. Suppose that, if all the adjacent nodes from the parent node receives equal value for the edges, such that, the parent node gets changes according to the adjacency of the parent node to achieve non-distinct edge values. Here, the label of the adjacent vertices is static and parent node splits into multifarious singleton vertex, which depends on the dimension n. Thus, the following theorem and proofs emerge from the idea of non-distinct edge labeling of the star graphs. Here we Constructed the Successor Vertex Graphs of Edge Recursion and the lemma is stated of how the vertex function looks for set of all ordered pairs of vertex label to achieve singleton edge labels using double mean labeling.","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131731254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-22DOI: 10.1109/ICECCT56650.2023.10179684
Merrisha John
Numerous studies have demonstrated that FRP (Fibre-reinforced Polymer) can significantly increase the strength of concrete columns. Numerous mathematical equations and manual methods are available for predicting the strength of concrete columns composed of FRP, all of which are time-consuming tasks. This present study develops a novel computerized method for determining the axial strain and axial strength of FRP (Fibre-reinforced Polymer)-confined concrete columns utilizing real-time experimental data and artificial neural networks (ANNs). In order to increase prediction accuracy, an ANN model is trained and evaluated using experimental data collected in real-time. Additionally, advanced pre-processing techniques are applied in this study to minimize noise and enhance the prediction accuracy of the suggested ANN model. To demonstrate the efficacy of this proposed strategy, this model is trained and verified using the data set. The experimental outcomes from training and validation have been compared to recent methods. It is evident from the comparison results that the proposed method has reduced MAE, RSME and regression values.
{"title":"Artificial Neural Networks Model for Predicting the Strength of FRP-Contained Concrete","authors":"Merrisha John","doi":"10.1109/ICECCT56650.2023.10179684","DOIUrl":"https://doi.org/10.1109/ICECCT56650.2023.10179684","url":null,"abstract":"Numerous studies have demonstrated that FRP (Fibre-reinforced Polymer) can significantly increase the strength of concrete columns. Numerous mathematical equations and manual methods are available for predicting the strength of concrete columns composed of FRP, all of which are time-consuming tasks. This present study develops a novel computerized method for determining the axial strain and axial strength of FRP (Fibre-reinforced Polymer)-confined concrete columns utilizing real-time experimental data and artificial neural networks (ANNs). In order to increase prediction accuracy, an ANN model is trained and evaluated using experimental data collected in real-time. Additionally, advanced pre-processing techniques are applied in this study to minimize noise and enhance the prediction accuracy of the suggested ANN model. To demonstrate the efficacy of this proposed strategy, this model is trained and verified using the data set. The experimental outcomes from training and validation have been compared to recent methods. It is evident from the comparison results that the proposed method has reduced MAE, RSME and regression values.","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131842540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-22DOI: 10.1109/ICECCT56650.2023.10179776
C. Raghavendra Rao, Grandhi Prasuna, Hari Kishan Chapala, N. Jeebaratnam, Durgaprasad Navulla, Ashish Verma
The Internet of Things (IoT) can now be used to automate healthcare facilities and make patient data available for use at any time and from any location via the Internet. Healthcare-related data is now shared and accessed via the host-based Internet paradigm. Latency, mobility, and security issues are all exacerbated by its location-dependent nature. For the present host-based Internet paradigm, which is already in place, NDN has been promoted as the next Internet paradigm. The new species, unfortunately, lacks a stable healthcare system. A lightweight certificate less (CLC) signature is used to build an NDN-IoMT framework in this paper. We employ the Hyper elliptic Curve Cryptosystem (HCC) since it is cheaper than the Elliptic Curve Cryptosystem, which provides higher security with a smaller key (ECC). In addition, we use AVISPA to verify the proposed scheme's safety. In order to determine the most cost-effective solution, we look at existing certificate less signature methods. Results reveal that our proposed method utilizes very little network resources. Finally, we put the architecture into action on NDN-IoMT.
{"title":"Designing a reliable and cost-effective Internet of Medical Things (IoMT) topology to minimize the maintenance and deployment cost","authors":"C. Raghavendra Rao, Grandhi Prasuna, Hari Kishan Chapala, N. Jeebaratnam, Durgaprasad Navulla, Ashish Verma","doi":"10.1109/ICECCT56650.2023.10179776","DOIUrl":"https://doi.org/10.1109/ICECCT56650.2023.10179776","url":null,"abstract":"The Internet of Things (IoT) can now be used to automate healthcare facilities and make patient data available for use at any time and from any location via the Internet. Healthcare-related data is now shared and accessed via the host-based Internet paradigm. Latency, mobility, and security issues are all exacerbated by its location-dependent nature. For the present host-based Internet paradigm, which is already in place, NDN has been promoted as the next Internet paradigm. The new species, unfortunately, lacks a stable healthcare system. A lightweight certificate less (CLC) signature is used to build an NDN-IoMT framework in this paper. We employ the Hyper elliptic Curve Cryptosystem (HCC) since it is cheaper than the Elliptic Curve Cryptosystem, which provides higher security with a smaller key (ECC). In addition, we use AVISPA to verify the proposed scheme's safety. In order to determine the most cost-effective solution, we look at existing certificate less signature methods. Results reveal that our proposed method utilizes very little network resources. Finally, we put the architecture into action on NDN-IoMT.","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132282655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-22DOI: 10.1109/ICECCT56650.2023.10179695
A. Sahu, D. Joshi
In this paper, the performance of a three-phase induction motor with space vector pulse width modulation (SVPWM) technique under artificial neural network (ANN) control is studied. The use of ANN control allows for improved performance of the induction motor, including enhanced speed control. The SVPWM technique is used to accurately control the voltage applied to the motor, resulting in improved performance of the induction motor. The operation of the induction motor is compared with proportional-integral (PI) controller. The results of the study show that the use of ANN control in conjunction with SVPWM leads to improved performance of the three-phase induction motor. The system's complete mathematical model is outlined and simulated using the MATLAB/Simulink platform.
{"title":"Performance of Three-Phase Induction Motor with Space Vector Pulse Width Modulation under Artificial Neural Network Control","authors":"A. Sahu, D. Joshi","doi":"10.1109/ICECCT56650.2023.10179695","DOIUrl":"https://doi.org/10.1109/ICECCT56650.2023.10179695","url":null,"abstract":"In this paper, the performance of a three-phase induction motor with space vector pulse width modulation (SVPWM) technique under artificial neural network (ANN) control is studied. The use of ANN control allows for improved performance of the induction motor, including enhanced speed control. The SVPWM technique is used to accurately control the voltage applied to the motor, resulting in improved performance of the induction motor. The operation of the induction motor is compared with proportional-integral (PI) controller. The results of the study show that the use of ANN control in conjunction with SVPWM leads to improved performance of the three-phase induction motor. The system's complete mathematical model is outlined and simulated using the MATLAB/Simulink platform.","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133278293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-22DOI: 10.1109/ICECCT56650.2023.10179610
Padmaja Mishra, Rajesh Kumar Patjoshi, A. Yadav
The Internet of things (IoT) becomes a new era for the imminent industry to provide an intelligent environment to control systems in real-time. Considerably, for accomplishing the delay analysis in the IoT system, it is necessary to consider the appropriate control system for the precise identification of IoT terminals and the efficient regulation of their access to the network. Therefore, the study considers about different control strategies such as PID (proportional integral derivative) $2^{text{nd}}$ process of Ziegler's Nichols, and PID Pole placement technique for finding the critical delay values under an IoT network environment. The control system is designed by considering different network constraints. Based on the network constraints and the controllers, a significant model is designed for calculating the maximum delay concerning sensor and controller along with controller and things. The controllers are premeditated using the transfer function of the particular plant i.e thing. The planned method designed here is to come across the value of delay via different design techniques using a PID controller. Finally, simulation results confirm the effectiveness of the proposed controller under MATLAB/Simulink environment.
物联网(IoT)成为即将到来的工业的新时代，为实时控制系统提供智能环境。因此，为了完成物联网系统中的时延分析，需要考虑合适的控制系统，以精确识别物联网终端并有效调节其接入网络。因此，研究考虑了不同的控制策略，如Ziegler's Nichols的PID (proportional integral derivative) $2^{text{nd}}$过程，以及PID极点放置技术来寻找物联网网络环境下的临界延迟值。考虑了不同的网络约束条件，设计了控制系统。基于网络约束和控制器，设计了传感器和控制器以及控制器和物体的最大时延计算模型。控制器是预先设定的，使用特定工厂的传递函数。这里设计的计划方法是通过使用PID控制器的不同设计技术来处理延迟的值。最后，在MATLAB/Simulink环境下进行了仿真，验证了所提控制器的有效性。
{"title":"A Delay Compensation Approach for IoT-Enabled Networks with Different Control Strategies","authors":"Padmaja Mishra, Rajesh Kumar Patjoshi, A. Yadav","doi":"10.1109/ICECCT56650.2023.10179610","DOIUrl":"https://doi.org/10.1109/ICECCT56650.2023.10179610","url":null,"abstract":"The Internet of things (IoT) becomes a new era for the imminent industry to provide an intelligent environment to control systems in real-time. Considerably, for accomplishing the delay analysis in the IoT system, it is necessary to consider the appropriate control system for the precise identification of IoT terminals and the efficient regulation of their access to the network. Therefore, the study considers about different control strategies such as PID (proportional integral derivative) $2^{text{nd}}$ process of Ziegler's Nichols, and PID Pole placement technique for finding the critical delay values under an IoT network environment. The control system is designed by considering different network constraints. Based on the network constraints and the controllers, a significant model is designed for calculating the maximum delay concerning sensor and controller along with controller and things. The controllers are premeditated using the transfer function of the particular plant i.e thing. The planned method designed here is to come across the value of delay via different design techniques using a PID controller. Finally, simulation results confirm the effectiveness of the proposed controller under MATLAB/Simulink environment.","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133249182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-22DOI: 10.1109/ICECCT56650.2023.10179632
K. Rajesh, I. Emerson, A. Ramkumar, R. Jenitha, B. Baranitharan
Lack of energy storage technology is a key worry in the period of increased global demand for electricity. The use of solar energy is on the rise and is more efficient at producing power. The utilization of solar energy has expanded to include home and commercial applications. An island mode is utilized in battery storage in off-grid power distribution systems. Off-grid power is a standalone mode that is used for household purposes in the power distribution system. The goal of my project is to create an off-grid power system in my house that stores energy in batteries. The nearby homes receive the generated electricity from the off-grid system in exchange for payment. As a result, electricity is distributed through a particular non-EB supply at the moment it is distributed through a nearby home in wireless mode. Using an Arduino with a GSM module in wireless mode. The quantity of energy used by the nearby homes is computed using the readings from the energy meters. For the outputs, the MATLAB/SIMULINK program is used to test the proposed system's functionality. The EB Distribution box uses sensors and control systems to supply power to the neighboring homes.
{"title":"Smart Power-Sharing System for Dormant Domestic Consumers using Green Energy using Wireless Networks","authors":"K. Rajesh, I. Emerson, A. Ramkumar, R. Jenitha, B. Baranitharan","doi":"10.1109/ICECCT56650.2023.10179632","DOIUrl":"https://doi.org/10.1109/ICECCT56650.2023.10179632","url":null,"abstract":"Lack of energy storage technology is a key worry in the period of increased global demand for electricity. The use of solar energy is on the rise and is more efficient at producing power. The utilization of solar energy has expanded to include home and commercial applications. An island mode is utilized in battery storage in off-grid power distribution systems. Off-grid power is a standalone mode that is used for household purposes in the power distribution system. The goal of my project is to create an off-grid power system in my house that stores energy in batteries. The nearby homes receive the generated electricity from the off-grid system in exchange for payment. As a result, electricity is distributed through a particular non-EB supply at the moment it is distributed through a nearby home in wireless mode. Using an Arduino with a GSM module in wireless mode. The quantity of energy used by the nearby homes is computed using the readings from the energy meters. For the outputs, the MATLAB/SIMULINK program is used to test the proposed system's functionality. The EB Distribution box uses sensors and control systems to supply power to the neighboring homes.","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117299458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-22DOI: 10.1109/ICECCT56650.2023.10179813
K. Arun, P. Kalyani, Shaik Fouziya Samreen, Shereen
Convolution and deconvolution are commonly employed in digital signal processing. Binary division is used in the field of digital image processing for image restoration, red-eye removal, and blur reduction via deconvolution operations. Long sequences must commonly undergo convolution and deconvolution comparable to DSP in many applications. The essential prerequisite for speed in any application is an increase in the speed of its fundamental building block. Both convolution and deconvolution have a central component known as a multiplier or divider. It is the most important component of the system, yet it is also the slowest and most time-consuming. Many approaches for increasing the multiplier and divider's speed have been explored, but the Vedic multiplier and divider are currently the focus of interest. Because it operates more swiftly and with less energy. In this work, the convolution and deconvolution modules are accelerated using Vedic multiplier and divider. Xilinx ISE 14.7 can be used to accomplish this division algorithm's operation. The suggested design is contrasted with current FPGA topologies, including the non-restoring division Algorithm and other Vedic Dividers (Paravartya Sutra, Nikhilam Sutra).
卷积和反卷积是数字信号处理中常用的两种方法。二值分割用于数字图像处理领域，通过反卷积操作实现图像恢复、红眼去除和模糊减少。在许多应用中，长序列通常必须经过与DSP相当的卷积和反卷积。在任何应用程序中，速度的基本先决条件是提高其基本构建块的速度。卷积和反卷积都有一个中心分量，称为乘法器或除法器。它是系统中最重要的组成部分，但也是最慢、最耗时的。人们已经探索了许多提高乘数法和分法器速度的方法，但吠陀乘数法和分法器是目前关注的焦点。因为它运行更快，耗能更少。在这项工作中，使用吠陀乘法器和除法器加速卷积和反卷积模块。Xilinx ISE 14.7可用于完成该除法算法的操作。建议的设计与当前的FPGA拓扑进行了对比，包括非恢复除法算法和其他吠陀除法(Paravartya Sutra, Nikhilam Sutra)。
{"title":"Vedic Divider: A Novel Design for Deconvolution Algorithm based on Vedic Math","authors":"K. Arun, P. Kalyani, Shaik Fouziya Samreen, Shereen","doi":"10.1109/ICECCT56650.2023.10179813","DOIUrl":"https://doi.org/10.1109/ICECCT56650.2023.10179813","url":null,"abstract":"Convolution and deconvolution are commonly employed in digital signal processing. Binary division is used in the field of digital image processing for image restoration, red-eye removal, and blur reduction via deconvolution operations. Long sequences must commonly undergo convolution and deconvolution comparable to DSP in many applications. The essential prerequisite for speed in any application is an increase in the speed of its fundamental building block. Both convolution and deconvolution have a central component known as a multiplier or divider. It is the most important component of the system, yet it is also the slowest and most time-consuming. Many approaches for increasing the multiplier and divider's speed have been explored, but the Vedic multiplier and divider are currently the focus of interest. Because it operates more swiftly and with less energy. In this work, the convolution and deconvolution modules are accelerated using Vedic multiplier and divider. Xilinx ISE 14.7 can be used to accomplish this division algorithm's operation. The suggested design is contrasted with current FPGA topologies, including the non-restoring division Algorithm and other Vedic Dividers (Paravartya Sutra, Nikhilam Sutra).","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116408572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-22DOI: 10.1109/ICECCT56650.2023.10179775
S. L. Kumar, M. Aaditi, R. M. Devi, N. Soniya, M. Maniventhan
People with loss of lower or upper extremity function are common in individuals of the aging population, people with disability post-stroke, fracture, and other neurological damage. Physiotherapy is an essential treatment for people with a disability regularly. Physiotherapists use various diagnosis, rehabilitation, and health promotion devices to promote, maintain or restore patient health. Rehabilitation exercise machines are present in rehabilitation centers and hospitals in India. It requires the presence of physiotherapists and tracks a patient's improvement status based on daily exercises. To decrease the workload of physiotherapists, telerehabilitation systems are developed. Using Information and Communication Technology (ICT), a similar rehabilitation exercise machine is developed in such a way that provides physiotherapy exercises and has continuous monitoring of a patient's improvement status.
{"title":"Design and Development of PhysioBot for upper-limb Telerehabilitation Applications","authors":"S. L. Kumar, M. Aaditi, R. M. Devi, N. Soniya, M. Maniventhan","doi":"10.1109/ICECCT56650.2023.10179775","DOIUrl":"https://doi.org/10.1109/ICECCT56650.2023.10179775","url":null,"abstract":"People with loss of lower or upper extremity function are common in individuals of the aging population, people with disability post-stroke, fracture, and other neurological damage. Physiotherapy is an essential treatment for people with a disability regularly. Physiotherapists use various diagnosis, rehabilitation, and health promotion devices to promote, maintain or restore patient health. Rehabilitation exercise machines are present in rehabilitation centers and hospitals in India. It requires the presence of physiotherapists and tracks a patient's improvement status based on daily exercises. To decrease the workload of physiotherapists, telerehabilitation systems are developed. Using Information and Communication Technology (ICT), a similar rehabilitation exercise machine is developed in such a way that provides physiotherapy exercises and has continuous monitoring of a patient's improvement status.","PeriodicalId":180790,"journal":{"name":"2023 Fifth International Conference on Electrical, Computer and Communication Technologies (ICECCT)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123220831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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