2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)最新文献_第7页

Enhanced Mayfly Optimization with Active Elite Approach Based Cluster Head Selection for Energy Efficient IoT based Healthcare Monitoring System 基于高效节能物联网医疗监测系统的基于主动精英方法的簇头选择增强蜉蝣优化

2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN) Pub Date : 2023-04-21 DOI: 10.1109/ICSTSN57873.2023.10151534

D. Balakishnan, T. Rajkumar

{"title":"Enhanced Mayfly Optimization with Active Elite Approach Based Cluster Head Selection for Energy Efficient IoT based Healthcare Monitoring System","authors":"D. Balakishnan, T. Rajkumar","doi":"10.1109/ICSTSN57873.2023.10151534","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151534","url":null,"abstract":"In order to conserve energy in the Internet of Things (IoT) network and also effectively handle the integrity and security issues in medical information, a framework for transmitting data that is both secure and energy efficient was proposed. It was used Enhanced Mayfly Clustering-based Q Learner Routing (EMCQLR) and Exponential Key-based Elliptical Curve Cryptography (EKECC) techniques. In EMCQLR, Enhanced Mayfly optimization Algorithm (EMOA) was used to select the Cluster Head (CH) for data collection from the nodes and form clusters of IoT medical sensors. This paper proposes a new approach called EMOA with Active Elite Approach (EMOA-AEA) to deal with the issues of slow convergence speed and the tendency of EMOA to fall into local optimum. The EMOA-AEA algorithm establishes a definite area around the most optimal mayfly in the present population, which is used to identify the top-performing CH. This region’s search radius is then adjusted as needed. Elite mayflies are subsequently produced within this designated zone, and if their fitness level surpasses that of the most exceptional mayfly, the finest cluster head from these new elite mayflies is selected to replace the current population’s top mayfly. After the selection of cluster head, Path-Weighted Q Reinforcement Learning (PWQRL) is used for data routing. At last, EKECC algorithm encrypts the medical records to provide data security. The experimental outcomes prove that the EMOA-AEA method surpasses the existing method in terms of network lifetime, average energy consumption, and throughput.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114471956","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}

引用次数: 0

The Secret Sauce of Student Success: Cracking the Code by Navigating the Path to Personalized Learning with Educational Data Mining 学生成功的秘诀:用教育数据挖掘导航个性化学习的道路，破解密码

2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN) Pub Date : 2023-04-21 DOI: 10.1109/ICSTSN57873.2023.10151558

Ashraf Alam

{"title":"The Secret Sauce of Student Success: Cracking the Code by Navigating the Path to Personalized Learning with Educational Data Mining","authors":"Ashraf Alam","doi":"10.1109/ICSTSN57873.2023.10151558","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151558","url":null,"abstract":"The growing need for tailored learning experiences in post-secondary education has resulted in the adoption of educational data mining (EDM) methodologies to derive significant insights from educational data. The existing scholarly literatures suggest the utilisation of adaptive learning algorithms that integrate various data sources, such as student demographic information, academic performance, and physiological data, to offer individualised learning experiences for students. The algorithms have the capability to modulate the tempo of educational content in response to the cognitive burden experienced by students, which is gauged by their brainwave activity. This study explores the application of predictive models, such as classification, regression, and time-series analysis, in detecting patterns and trends in past data for the purpose of forecasting students’ forthcoming academic achievements. Predictive models have the potential to assist educators in making well-informed decisions aimed at enhancing course outcomes. This research introduces an approach to course improvement analytics that utilises diverse data sources, including student academic records, demographic data, and external platforms such as social media and online forums, to optimise educational results. Through the examination of this data, academic professionals can acquire valuable knowledge regarding student involvement, achievement, and conduct. The present study establishes that the utilisation of course improvement analytics yields valuable information regarding student engagement and behaviour, thereby enabling educators to make informed decisions aimed at enhancing students’ learning outcomes.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129511972","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}

引用次数: 0

Local Interpretable Model-Agnostic Explanations for Online Maternal Healthcare 在线产妇保健的本地可解释模型不可知解释

2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN) Pub Date : 2023-04-21 DOI: 10.1109/ICSTSN57873.2023.10151520

Ggaliwango Marvin, Daudi Jjingo, J. Nakatumba-Nabende, Md. Golam Rabiul Alam

{"title":"Local Interpretable Model-Agnostic Explanations for Online Maternal Healthcare","authors":"Ggaliwango Marvin, Daudi Jjingo, J. Nakatumba-Nabende, Md. Golam Rabiul Alam","doi":"10.1109/ICSTSN57873.2023.10151520","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151520","url":null,"abstract":"In culturally conservative communities, access to authentic sexual, reproductive, and adolescent information is scarce, particularly in low and middle-income countries. This has led to an over-reliance on social media and online communities to obtain such information, hence leading to the proliferation of fake and inappropriate healthcare advice. Moreover, there is no regulatory body to verify and validate shared healthcare information on online platforms. Individuals often disguise their identity while seeking sensitive information on sexual, reproductive and maternal health online. This has facilitated untraceable spread of incorrect information and harmful medical advice among social groups. These variations in social dynamics result in healthcare disparities, which reinforce health inequalities. In this paper, we propose the use of interpretable machine learning to evaluate online maternal medical advice for authenticity. We report on the negative results of Machine Learning Models attempt to distinguish between authentic and fake medical advice and urgently advocate for the establishment of a sexual, reproductive and maternal health corpus for machine learning models to learn, filter and detect medical imposters or misinformation. Our work highlights the insufficiency of explainable AI in medical contexts and underscores the need for establishing regulatory bodies to ensure the authenticity of sensitive healthcare information via social media and online platforms.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132959001","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}

引用次数: 0

Performance Comparison of Routing Protocols for IoT 物联网路由协议的性能比较

2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN) Pub Date : 2023-04-21 DOI: 10.1109/ICSTSN57873.2023.10151577

C. Thiagarajan, P. Samundiswary

{"title":"Performance Comparison of Routing Protocols for IoT","authors":"C. Thiagarajan, P. Samundiswary","doi":"10.1109/ICSTSN57873.2023.10151577","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151577","url":null,"abstract":"the IoT is a rapidly growing field with enormous potential for innovation and impact on society. Intelligent interfaces are used by the things with unique identification which helps us to enable to build wireless bridge to connect the end to end user for social communication & various purposes. As the Internet of Things evolves day by day it is critical to explore novel routing protocols. The categories of routing protocols are purely based on its unique mechanism. According to the various mechanisms of the routing protocol, an IoT network can adapt a specific routing protocol to serve and route the data from one to the other end. Therefore it is necessary to design appropriate routing protocol to connect the different entities. This article analyses and compares the performance of Ad-hoc On-demand Distance Vector (AODV) and Routing Protocol for Low Power & Lossy Networks (RPL). Further, the comparison is done for the various attributes such as throughput, Packet delivery ratio & average end-to-end delay. It is observed through the simulation results that the RPL routing protocol provides better console than the AODV mechanisms in terms of PDR & throughput.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133963639","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}

引用次数: 0

Water Quality Analysis of Gadilam river, Cuddalore based on pollution index and NSF - WQI 基于污染指数和NSF - WQI的Cuddalore Gadilam河水质分析

2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN) Pub Date : 2023-04-21 DOI: 10.1109/ICSTSN57873.2023.10151465

P. Priyanka, S. Senthilkumar, Mareike Jas, N. Nagarajan, S. Akash

引用次数: 0

Gammatone Visualization based Cough Sound Classification: Performance Comparison with Delta and Delta-Delta Features 基于γ matone可视化的咳嗽声分类:Delta和Delta-Delta特征的性能比较

2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN) Pub Date : 2023-04-21 DOI: 10.1109/ICSTSN57873.2023.10151529

B. Priya, S. Jayalakshmy, D. Saraswath

引用次数: 0

Supercapacitor and BLDC Motor-based Regenerative Braking for an Electric Vehicles 基于超级电容器和无刷直流电机的电动汽车再生制动

2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN) Pub Date : 2023-04-21 DOI: 10.1109/ICSTSN57873.2023.10151546

R. Revathy, B. Balaji, A. K. Abdul Mohasin, A. Gobinath

{"title":"Supercapacitor and BLDC Motor-based Regenerative Braking for an Electric Vehicles","authors":"R. Revathy, B. Balaji, A. K. Abdul Mohasin, A. Gobinath","doi":"10.1109/ICSTSN57873.2023.10151546","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151546","url":null,"abstract":"In today’s modern world, Electric vehicles play a critical role. For a brushless DC (BLDC) motor-driven electric vehicle, regenerative electric braking system is suggested (EV) to enhance the efficiency of energy storage system. A battery, inverter, motor and charging port is the major components included in an electric vehicle. However the vehicle’s power train is a key component. The motor’s electric vehicle should be designed based on its efficiency and cost. The power-weight ratio, speed, torque and cost of motors are compared and analyzed in this research. Because of its greater power-to-weight ratio in spite of higher maintenance and controller expenses, the BLDC motor is demonstrated to be the most suitable for an electric vehicle. Next, the regenerative braking for electric vehicles is proposed and its performance is investigated. Regenerative braking involves using the generator function of an electric car’s motor to convert mechanical energy into electrical energy. Regenerative braking converts its kinetic energy and saves it in storage devices. This technique upsurges the range or decreases the fuel usage of a vehicle. The system under study is composed of a brushless DC motor, a Buck-Boost DC converter, and super capacitors. The suitable control system is optimized to store the energy in the super capacitors. With the help of this research, electric car energy flow regulation will be improved and the maximum range per charge cycle will be realized.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"904 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116397564","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}

引用次数: 0

Predicting Mortgage-Backed Securities Prepayment Risk Using Machine Learning Models 使用机器学习模型预测抵押贷款支持证券的提前支付风险

2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN) Pub Date : 2023-04-21 DOI: 10.1109/ICSTSN57873.2023.10151481

P. Kanimozhi, S. Parkavi, T. Kumar

{"title":"Predicting Mortgage-Backed Securities Prepayment Risk Using Machine Learning Models","authors":"P. Kanimozhi, S. Parkavi, T. Kumar","doi":"10.1109/ICSTSN57873.2023.10151481","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151481","url":null,"abstract":"An option to prepay a portion of a mortgage debt before it matures is included. This alternative, known as mortgage prepayment, puts the bank that provided the home loan at risk since it prevents them from receiving future interest payments and complicates their refinancing options. Prepayment risk refers to the possibility that borrowers would pay off their mortgages earlier than anticipated, lowering income flows to MBS investors. Actual prepayment rates that are greater or lower than anticipated might reduce cash flows while increasing the risk of extension for investors., Predicting the mortgage-backed securities prepayment risk analysis is necessary for this project using the mortgage portfolio of “Freddie Mac” to predict mortgage borrower prepayment behavior. Formulating the prepayment analysis issue will be feasible using machine learning methods. Additionally, it looked at the distribution of the target variable and offered ideas for enhancing the regression model. The accuracy of ridge regression was achieved at 78%, then 89% accuracy for testing data using Logistic Regression, and, with the KNN model, achieved an accuracy of 76%. A user interface that asks for input from the user to enter the information and forecasts whether the customer’s mortgage will be paid off has also been created.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130384974","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}

引用次数: 0

A Hyper-Graph Embedded Bandlet-Based Facial Emotion Monitoring System for Enhanced Urban Health 基于超图嵌入式手环的城市健康面部情绪监测系统

2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN) Pub Date : 2023-04-21 DOI: 10.1109/ICSTSN57873.2023.10151462

J. Swarup Kumar, M. Vignesh, Pera Manoj, I. S. Siva Rao, M. Babu, Ramu Mutyala

引用次数: 0

License Plate reader with PUC Details using Image Processing and Deep Learning 车牌阅读器与PUC细节使用图像处理和深度学习

2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN) Pub Date : 2023-04-21 DOI: 10.1109/ICSTSN57873.2023.10151566

R. Patil, Sakshi Deshpande, H. Khan, Prajakta Mhatre

{"title":"License Plate reader with PUC Details using Image Processing and Deep Learning","authors":"R. Patil, Sakshi Deshpande, H. Khan, Prajakta Mhatre","doi":"10.1109/ICSTSN57873.2023.10151566","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151566","url":null,"abstract":"As each vehicle is uniquely acknowledged by its license plate, the Transport System places a high priority on finding and recognizing of license plates. The news is constantly reporting on accidents and missing cars. Authorities must acknowledge all of these unlawful acts. As a result, research into the identification and recognition of vehicle number plates is ongoing. However, identifying a vehicle’s number plate has always been difficult for a number of reasons, such as brightness changes, shadows cast by moving vehicles, erratic license plate character types, different plate styles, and color effects caused by the surroundings. In this system, Number plate of vehicle is detected from a live video or an image. There is image preprocessing and segmentation done on the live video or number plate image. Deep learning model methods are used, the characters from it are separated and then each character gets recognized. This helps to collect the vehicle overall project then the capabilities of different techniques into one integrated automatic system are summarized. This kind of systems can be implemented on the roadside and makes a real time comparison between passing car and list of stolen cars. This detected license plate number could also be used in car parking systems. PUC which stands for Pollution Under Control, where emission levels of vehicles and the regular renovation of the PUC certificate is done or not is verified and the details are shown. This will help in keeping an overall check on vehicles and the task which most of the places do manually to check the PUC certificate for checking status, can be verified quickly and the fine can be implemented as per so.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123188215","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}

引用次数: 0