2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)最新文献_第2页

Development of Crowd Management System using FPGA Circuits 基于FPGA电路的人群管理系统开发

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010917

R. Seetharaman, I. Shivananth, M. Ganeshakumar, D. Anitha, K. Anandan, S. Gayathri

引用次数: 0

Machine Learning based Prediction of Customer Churning in Banking Sector 基于机器学习的银行业客户流失预测

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10011126

Manoj Kumara N V, Bharath Kumar K K, A. Mudhol

{"title":"Machine Learning based Prediction of Customer Churning in Banking Sector","authors":"Manoj Kumara N V, Bharath Kumar K K, A. Mudhol","doi":"10.1109/ICAISS55157.2022.10011126","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10011126","url":null,"abstract":"The term “customer churn” refers to the process of losing customers over time in the commercial and financial worlds. Businesses are more prepared to take preventative steps against customer turnover when they are aware of which of their customers are most likely to defect. The bank will gain by knowing which customers are most likely to switch banks in the near future both practically and theoretically. This article offers a technique for identifying which banking clients are most likely to move banks by using algorithms created for machine learning. This article shows how, given sufficient customer data such as age, location, gender, credit card information, balance, etc., machine learning models such as Logistic Regression (LR), Naive Bayes' (NB)can accurately predict which customers are most likely to leave the bank in the future. Additionally, this article illustrates how machine learning models like Logistic Regression (LR), Naive Bayes (NB), can accurately predict what customers are most likely toFinally, this research analysisshows that NB is better than LR.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"690 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128647167","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

Smart Traffic Light Control System Using Image Processing 基于图像处理的智能交通灯控制系统

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010764

Asha S.M Banu, Soundarya A S Lakchida, V. Shanthini, S. L. Stinsha

{"title":"Smart Traffic Light Control System Using Image Processing","authors":"Asha S.M Banu, Soundarya A S Lakchida, V. Shanthini, S. L. Stinsha","doi":"10.1109/ICAISS55157.2022.10010764","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10010764","url":null,"abstract":"Crossing the road is one of the major problems, due to the increase of fast-moving vehicles on the road. The challenges in the existing techniques utilized for traffic control can be overcome by using the Smart Traffic Light Control System using Image Processing, proposed in this paper and allowing pedestrians to walk on busy roads conveniently. It is found that the Canny Edge Detection Technique is a very effective method among the various edge detection algorithms. The suggested method reduces the waiting time in zebra crossing by immediately controlling the traffic light and gives more time for elderly and handicapped pedestrians to cross the roads safely even during heavy traffic. When compared to all the traditional techniques, image processing is an efficient method for traffic control. This technique removes the usage of unwanted hardware like sensors which are used to sense noises. This prevents the wastage of time for vehicles which is more essential for emergency vehicles. The output of the code is obtained by image matching. The results are shown in three scenarios: less traffic, moderate traffic, and more traffic.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124613924","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

IoT-based Underground Cable Fault Detection 基于物联网的地下电缆故障检测

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010910

V. V. Teresa, K. Rajeshwaran, S.Satheesh Kumar, S. Vishnupriyan, S. Dhanasekaran

{"title":"IoT-based Underground Cable Fault Detection","authors":"V. V. Teresa, K. Rajeshwaran, S.Satheesh Kumar, S. Vishnupriyan, S. Dhanasekaran","doi":"10.1109/ICAISS55157.2022.10010910","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10010910","url":null,"abstract":"Underground cables are subject to various problems due to the underground environment, abrasion, mouse, etc. In addition, it is difficult to find the cause of the fault, which requires digging the entire line to inspect and correct any faults. To make repairs as easy as possible, we now offer cable troubleshooting via Internet of things (IoT), which locates the fault. The maintenance staff knows exactly which part is faulty and only needs to dig in that area to find the source of the problem. Faster underground cable service is also possible as a result of the significant time, money, and effort savings. We employ IoT technology, which enables authorities to track and analyse defects online. The system uses a network of voltage dividers installed on the cable to identify defects. The resistance network combination determines the voltage produced when a fault develops at the location where the two wires are short-circuited. The user is alerted by the microcontroller when this voltage is found. The user receives the distance that this voltage corresponds to. The microcontroller gathers the fault line data, displays it on the LCD screen, and transfers it via the Internet for online viewing","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123480466","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: 10

Deep Learning Model for Plant Species Classification Using Leaf Vein Features 基于叶脉特征的植物物种分类深度学习模型

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10011101

P. B. R., L. P

引用次数: 2

White Blood Cell Image Generation using Deep Convolutional Generative Adversarial Network 基于深度卷积生成对抗网络的白细胞图像生成

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010838

Dwiti Pandya, Tejal Patel, D. Singh

引用次数: 3

A Cross-Domain Semantic Similarity Measure and Multi-Source Domain Adaptation in Sentiment Analysis 情感分析中的跨域语义相似度度量与多源域自适应

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10011051

Dipak Patel, Kiran R. Amin

{"title":"A Cross-Domain Semantic Similarity Measure and Multi-Source Domain Adaptation in Sentiment Analysis","authors":"Dipak Patel, Kiran R. Amin","doi":"10.1109/ICAISS55157.2022.10011051","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10011051","url":null,"abstract":"Domain adaptation becomes crucial when there is a lack of labelled data in various domains. The accuracy of traditional machine learning models degrades largely if they are trained on one domain (called the source or training domain) and classify the data of a different domain (called the target domain or test domain, which is different from the source domain). The machine needs to train on a corresponding domain to improve the classification accuracy, but labelling each new domain is a complex and time-consuming task. Hence, the domain adaptation technique is required to solve the issue of data labeling. The similarity measure plays a vital role in selecting important pivot features from the target domain that match source domains. This research article has introduced an enhanced cross-entropy measure for matching the normalized frequency distribution of different domains and found an important domain-specific feature set. In addition, the technique of using enhanced cross entropy measures is proposed in the multi-source domain adaptation model to effectively classify the target domain data. The result shows that there is an improvement of 3.66% to 9.09% using our approach.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121565743","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: 2

A Novel Approach to Early Depression Prediction and Estimation with EEG Signals 一种基于脑电图信号的早期抑郁症预测与估计新方法

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010875

S. Rosaline, R. S. Kaavya Varshitha, Keerthana Nv, K. Spoorthi

引用次数: 0

Power Quality Improvement in Wind, Solar, and DG Based Islanded Microgrid by using DVR 利用DVR改善风能、太阳能和DG孤岛微电网的电能质量

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010773

Sagar Yadav, Sachin Singh, A. Yadav, S. Srivastava

引用次数: 0

Design and Implementation of Electric Vehicle Fast Tag Charger Using Solar Photovoltaic System 基于太阳能光伏系统的电动汽车快速标签充电器的设计与实现

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010761

S. V. Kumar, Dr. C. Kathirvel, D. V. Jude, Kedar P. Pathak, Onkar V. Bhole, Mahesh B. Patil, K., Vaidya

引用次数: 0