International Journal of Innovative Research in Science, Engineering and Technology最新文献_第6页

Density Based Traffic Control System 基于密度的交通控制系统

International Journal of Innovative Research in Science, Engineering and Technology Pub Date : 2023-05-15 DOI: 10.59256/ijire.2023040384

Sindhu U.L., Sandhiya S, Visalatchi T

引用次数: 0

Experimental Investigation on Green Concrete by Using Natural Fiber as Chicken Feather 以天然纤维为鸡毛的绿色混凝土试验研究

International Journal of Innovative Research in Science, Engineering and Technology Pub Date : 2023-05-15 DOI: 10.59256/ijire.2023040385

Prabhavathi S, Gokul R, Mohanraj M, Sugavaneshwran I.C.

引用次数: 0

Cyber bullying Detection on Social Media Using Machine Learning 基于机器学习的社交媒体网络欺凌检测

International Journal of Innovative Research in Science, Engineering and Technology Pub Date : 2023-05-15 DOI: 10.59256/ijire.2023040390

G. S, M. S, Nilani K, P. G, R. S, Roshini P

{"title":"Cyber bullying Detection on Social Media Using Machine Learning","authors":"G. S, M. S, Nilani K, P. G, R. S, Roshini P","doi":"10.59256/ijire.2023040390","DOIUrl":"https://doi.org/10.59256/ijire.2023040390","url":null,"abstract":"Cyber bullying has become a growing concern in today's society, with more and more people turning to the internet to harass and intimidate others. Digital forensics is an essential tool for investigating cyber bullying activities, as it allows for the collection and analysis of digital evidence. However, traditional digital forensics techniques can be time-consuming and require a significant amount of human effort. In this paper, we propose the use of machine learning algorithms to aid in the investigation of cyber bullying activities. By training these algorithms on a dataset of known cyber bullying incidents, we can create a predictive model that can automatically classify new instances of cyber bullying. This can significantly reduce the time and effort required for investigations, allowing for a more efficient response to cyber bullying incidents. The challenges associated with using machine learning for cyber bullying detection, including the need for high-quality training data and the potential for bias in the algorithms. We also explore the various types of digital evidence that can be used in cyber bullying investigations, such as social media posts, emails, and instant messages. We present a case study in which we apply our proposed approach to a real-world cyber bullying incident. Our results show that the machine learning algorithm was able to accurately identify the cyber bullying activity with a high level of precision, demonstrating the potential of this approach for improving the efficiency and effectiveness of cyber bullying investigations.","PeriodicalId":14005,"journal":{"name":"International Journal of Innovative Research in Science, Engineering and Technology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89366854","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

Precision Agriculture Using Hanging Robot 使用悬挂式机器人的精准农业

International Journal of Innovative Research in Science, Engineering and Technology Pub Date : 2023-05-15 DOI: 10.59256/ijire.2023040389

Dhivyadharshini S, Shalini S, Radhakrishnan C

{"title":"Precision Agriculture Using Hanging Robot","authors":"Dhivyadharshini S, Shalini S, Radhakrishnan C","doi":"10.59256/ijire.2023040389","DOIUrl":"https://doi.org/10.59256/ijire.2023040389","url":null,"abstract":"The precision agriculture monitoring system is an emerging concept. The sensors are capable of providing information about agricultural fields and then Artificial Intelligence takes decision automatically based on the sensor values. Monitoring environmental conditions is the major factor to improve yield of the efficient crops. In this project, we present a new approach by using hanging robot with virtual assistance in the agriculture field by monitoring moisture, temperature etc.It further provides a review on the most common sensing principles that can be used for in-situ and real-time temperature and and humidity level, as well as an overview of the difficulties for deploying these sensing systems and their electronic interfaces in the harsh soil environment. It reviews existing agricultural circuits and sensing systems designed for agricultural monitoring and their limitations whilst highlighting remaining challenges in order to make automated, decision- making systems for precision agriculture, a reality. Key Word: Integrated circuit, Motor driver supply, Sinusoidal signal, Communication port, Integrated Development Environment.","PeriodicalId":14005,"journal":{"name":"International Journal of Innovative Research in Science, Engineering and Technology","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76063950","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 Powered Smart Strata Monitoring System for early and precise detection of Convergence in Underground Coal Mines 基于物联网的智能地层监测系统，实现煤矿井下超前、精准的收敛检测

International Journal of Innovative Research in Science, Engineering and Technology Pub Date : 2023-05-15 DOI: 10.59256/ijire.2023040388

{"title":"IOT Powered Smart Strata Monitoring System for early and precise detection of Convergence in Underground Coal Mines","authors":"","doi":"10.59256/ijire.2023040388","DOIUrl":"https://doi.org/10.59256/ijire.2023040388","url":null,"abstract":"Roof fall, bed separation and convergence are one of the serious life-threatening problems faced by the miners in all the underground coal mines since early mining age to current mining situations. Most of the statistics regarding fatal accidents and trapped miners in underground coal mines are the results of sudden roof fall due to bed separation of overlying strata in the underground mine galleries or roadways. In Indian underground coal mines, many of fatalities were seen over the years although this rate has been gradually decreasing since past decade only by implementing some of physical and mechanical methods to detect or monitor strata convergence. With the advancement of technology, sensors become an extensive part of everyday life. Various researchers are trying to monitor, detect and prevent fatalities due to roof fall in real time scenario in underground coal mines with the use of sensors, IOT and other technology. The main aim is to Install a non-invasive laser proximity sensor in the hole drilled into the roof where the necessity arises to remotely monitor the convergence in the strata under bad roof conditions in underground coal mines and monitor them remotely with an automated display showing the details of the bed separation, roof convergence and detailed information about the roof condition remotely. Key Word: Internet of Things, Strata Monitoring, Roof Fall, Convergence, Real time, Display device, Proximity sensors, Remote Monitoring.","PeriodicalId":14005,"journal":{"name":"International Journal of Innovative Research in Science, Engineering and Technology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87816061","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 Vehicle Transportation System Using Node MCU 基于Node单片机的智能车辆交通系统

International Journal of Innovative Research in Science, Engineering and Technology Pub Date : 2023-05-15 DOI: 10.59256/ijire.2023040387

P. G, M. R, K. P, Kalki S.K

引用次数: 0

Real-Time Drowsiness Identification Based On Eye State Analysis 基于眼状态分析的实时睡意识别

International Journal of Innovative Research in Science, Engineering and Technology Pub Date : 2023-05-14 DOI: 10.59256/ijire.2023040383

V. J, Gowri Shankar K.S, Dhavasi K, T. M, Soundharya C

引用次数: 2

Development of Pavement Condition Index for Local Street of Pune 浦那地方街道路面状况指标的制定

International Journal of Innovative Research in Science, Engineering and Technology Pub Date : 2023-05-13 DOI: 10.59256/ijire.2023040379

Kori S.S, Supriya Patil, J. Borse, Priyanka Suryawanshi, Manisha Borhade

引用次数: 0

Design and Fabrication of Spraying Agrobot 喷涂农业机器人的设计与制造

International Journal of Innovative Research in Science, Engineering and Technology Pub Date : 2023-05-13 DOI: 10.59256/ijire.2023040382

S. S., D. G, D. V., G. A., Jeganeeshwaran T

引用次数: 0

Human Signature Verification System Using CNN with Tensor flow 基于张量流的CNN人体签名验证系统

International Journal of Innovative Research in Science, Engineering and Technology Pub Date : 2023-05-13 DOI: 10.59256/ijire.2023040381

A. G, A. K, D. P, Abimanyu R, V. V

{"title":"Human Signature Verification System Using CNN with Tensor flow","authors":"A. G, A. K, D. P, Abimanyu R, V. V","doi":"10.59256/ijire.2023040381","DOIUrl":"https://doi.org/10.59256/ijire.2023040381","url":null,"abstract":"One of the most popular verification biometrics is the signature. On checks, forms, letters, applications, minutes, and other documents, handwritten signatures are required. A person's handwritten signature must be individually identified because each individual's signature is unique by nature. Signature verification is a popular technique for confirming anyone's identity while they are not present. Human verification can be inaccurate and occasionally unsure. The use of Convolutional Neural Networks (CNN) for Writer-Dependent models in signature verification is examined in this research. In order to create forged signatures, random distortions were created in real photos using an auto encoder and then fed to the classifier during training. In addition to demonstrating various test outcomes for varying the number of training sets of images, the study describes all image pre-processing procedures that were applied to the image. In the Persian dataset, the system's average test accuracy is 83% after 22 real photos were used to train it. When the model was trained on nine real photos, accuracy dropped by 9.4%. Key Word: Offline Signature Verification, WD (Writer Dependent), CNN (Convolutional Neural Network), FAR (False Acceptance Ratio), FRR (False Rejection Ratio), Auto encoder","PeriodicalId":14005,"journal":{"name":"International Journal of Innovative Research in Science, Engineering and Technology","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87510524","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