ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY最新文献_第3页

Leaf Diseases Detection System Using Machine Learning 基于机器学习的叶片病害检测系统

ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY Pub Date : 2023-04-30 DOI: 10.33130/ajct.2023v09i01.002

Swati Tiwari, Pranjal Patle, Pranshu Patle, Kuldeep Sonkusare, Pranali Mungate

引用次数: 0

Development of an IOT Based Industrial Fault Detection and Diagnosis System 基于物联网的工业故障检测与诊断系统的开发

ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY Pub Date : 2023-04-30 DOI: 10.33130/ajct.2023v09i01.005

Md. Nazrul Islam, Mohamad Saiful Haffiz Rahman, Kazi Muhammad Asif Ashrafi, Toufiq Ahmed

引用次数: 0

Fault Diagnosis of a Transformer using Fuzzy Model and Unsupervised Learning 基于模糊模型和无监督学习的变压器故障诊断

ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY Pub Date : 2023-04-30 DOI: 10.33130/ajct.2023v09i01.011

Akshita Dhiman, Rajesh Kumar

引用次数: 0

FE Analysis of Cornering Fatigue Test for Wheel Rim of Light Commercial Vehicle 轻型商用车轮辋转弯疲劳试验的有限元分析

ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY Pub Date : 2023-04-30 DOI: 10.33130/ajct.2023v09i01.013

Chaudhari Dhananjay D, Bhagwat Randhavan

引用次数: 0

Influencing users for paper recycling using an E-commerce website 利用电子商务网站影响用户回收纸张

ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY Pub Date : 2023-04-30 DOI: 10.33130/ajct.2023v09i01.004

Abhinav Kaushal, Harshit Rawat, Rohit Joshi, Jyotsna Seth

引用次数: 0

Use of Machine Learning Applications for Speech Impaired People 使用机器学习应用程序的语言障碍人士

ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY Pub Date : 2023-04-30 DOI: 10.33130/ajct.2023v09i01.012

Rajeshri Pravin Shinkar

引用次数: 0

Detection of Network Layer Attacks in Wireless Sensor Network 无线传感器网络中的网络层攻击检测

ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY Pub Date : 2023-04-30 DOI: 10.33130/ajct.2023v09i01.009

V.Gowtami Annapurna, K. Anusha, Chhamunya Varsha, M. Deepthi, G. Keerthi

{"title":"Detection of Network Layer Attacks in Wireless Sensor Network","authors":"V.Gowtami Annapurna, K. Anusha, Chhamunya Varsha, M. Deepthi, G. Keerthi","doi":"10.33130/ajct.2023v09i01.009","DOIUrl":"https://doi.org/10.33130/ajct.2023v09i01.009","url":null,"abstract":"— The Wireless Sensor Network (WSN) technology is being used in a huge number of monitoring applications. It consists of a large number of sensor nodes with limited battery life. These sensor devices are deployed randomly in a sensor zone to collect the data. But these are threatened and attacked by several malicious behaviors caused by some nodes, which result in security attacks. Several security attacks occur in different layers of the wireless sensor network. Due to these attacks, confidential information can be stolen by attackers or unauthorized users, which can cause several problems for authorized users. Cyber-attacks by sending large data packets that deplete computer network service resources by using multiple computers when attacking are called wormhole and Sybil attacks. It is important to identify these attacks to prevent further damage. To overcome these problems, we use a prediction module that consists of various machine learning algorithms to find the best-performing algorithm. we use XGBoost, Adaboost, Random Forest, and KNN algorithms. To train these algorithms, we have used the WHASA dataset which contains 10 different attacks of the VANET environment and benign (normal) class. By using these algorithms classification of attacks can be done which occur on the computer network service that is \" normal \" access or access under \" attack \" by Wormhole and Sybil attack as an output.","PeriodicalId":138101,"journal":{"name":"ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121098996","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

Utilizing the Internet of Things, Monitoring and Protecting System for Automated Teller Machines 利用物联网的自动柜员机监控与保护系统

ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY Pub Date : 2022-12-31 DOI: 10.33130/ajct.2022v08i03.004

Mohammad Naveed Hossain, Md. Shaba Sayeed, Sheikh Fahim Uz Zaman

{"title":"Utilizing the Internet of Things, Monitoring and Protecting System for Automated Teller Machines","authors":"Mohammad Naveed Hossain, Md. Shaba Sayeed, Sheikh Fahim Uz Zaman","doi":"10.33130/ajct.2022v08i03.004","DOIUrl":"https://doi.org/10.33130/ajct.2022v08i03.004","url":null,"abstract":"—For the vast majority of people in modern society, ATMs are the preferred method of cash withdrawal. ATM robberies have happened even in locations where CCTV cameras are installed at the ATM facility. The security mechanism will need to be tweaked. To combat these types of robberies, we developed a theft protection system for ATMs that makes use of cutting-edge technology. This system also looks at various physical assaults using ATMs. The device we propose to utilize to take an image of the individual entering the system is a Face Recognizing Camera. Anomaly behavior at an ATM can be detected using sensors that measure tilt and vibration. Any strange conduct will be detected by the LED light and buzzer, which will alert security personnel, the ATM machine will act like money withdrawing. Our system’s main goal is to send out a warning via email or other social media. IoT and GSM networks are used by both Facebook and Instagram. An alert will sent to the security force and a fake transaction process will be set to confuse the suspect. To avoid the unwanted incident after a certain time some anesthetic gas will be released, to make the suspect unconscious. Monitoring and control are now become easier because to this technology.","PeriodicalId":138101,"journal":{"name":"ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY","volume":"43 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130641384","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

Analyzing the Classification Accuracy of Deep Learning and Machine Learning for Credit Card Fraud Detection 深度学习和机器学习在信用卡欺诈检测中的分类准确性分析

ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY Pub Date : 2022-12-31 DOI: 10.33130/ajct.2022v08i03.006

Mohammad Naveed Hossain, M. Hassan, R. Monir

引用次数: 0

The use of IoT to solve Farming Problems 利用物联网解决农业问题

ASIAN JOURNAL OF CONVERGENCE IN TECHNOLOGY Pub Date : 2022-12-31 DOI: 10.33130/ajct.2022v08i03.008

Prashobh Karunakaran, S. Karunakaran, M. S. Osman, Sreeja Haridas, Prashanth Karunakaran, Arjun Karunakaran

引用次数: 1