2022 2nd International Conference on Intelligent Technologies (CONIT)最新文献_第3页

3DVAEReCNN: Region-based Convolutional Neural Network for Volumetric Rendering of Indoor Scenes 3DVAEReCNN:基于区域的卷积神经网络用于室内场景体绘制

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9848353

Karan Gala, Pravesh Ganwani, R. Kulkarni, R. Pawar

引用次数: 0

Limitless: A Mobile Application Featuring Next Generation Library Facilities For the Bangladeshi University Students 无限:为孟加拉国大学生提供下一代图书馆设施的移动应用程序

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9847806

Mahfuzulhoq Chowdhury, Ajoy Deb Nath

{"title":"Limitless: A Mobile Application Featuring Next Generation Library Facilities For the Bangladeshi University Students","authors":"Mahfuzulhoq Chowdhury, Ajoy Deb Nath","doi":"10.1109/CONIT55038.2022.9847806","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847806","url":null,"abstract":"The University library is one of the parts and parcels of the universities that can assist students and teachers teaching and learning work by providing necessary services related to in-formation sharing, book search, book borrow, research document access, and reading room facilities, among others. A vast amount of the literature works related to library facilities emphasize providing services via offline mode rather than online mode. Most of the existing works on online-based library services focus on a single or limited number of library facilities and resources. The existing research works on university library facilities do not consider multiple library resources, different types of users, and multiple features at the same time. Thus, the existing university library related works mainly suffer from the shortage of library resources along with higher time and cost wastage. To tackle with the existing challenges, this paper presents a mobile application featuring next-generation library facilities for university students in Bangladesh. Our proposed limitless mobile application provides several features for students like book or research document search, borrow, order and access, payment and checkout, course enrollment, reading room allocation, request or donate a book, history, notifications, track order, complaint, among others. By using our proposed application, one member of the university library can access the resources of other university libraries via the membership/join feature. Our review result indicates that the majority of the student users are satisfied with the usefulness and necessity of the proposed mobile application features.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121701697","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

Modeling and Detection of PV Panel Hard Shading Using Artificial Neural Network 基于人工神经网络的光伏板硬遮阳建模与检测

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9847671

Bryan E. Escoto

{"title":"Modeling and Detection of PV Panel Hard Shading Using Artificial Neural Network","authors":"Bryan E. Escoto","doi":"10.1109/CONIT55038.2022.9847671","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847671","url":null,"abstract":"The hard shading caused by dirt accumulation on the PV surface, shadows caused by near structures, trees, and even unwanted materials at the surface of the panels degrades the performance of the PV panels, significantly reducing the power output and its efficiency. However, the detection of shading of the solar panel is a complex and challenging process since the panel's power conversion varies and is affected by several factors such as solar irradiance, temperature, the position of the sun, location of shading, etc. This project created an Artificial Neural Network (ANN) model that detects the hard shading and its coverage to PV panels. The optimum ANN model developed in this study can detect solar panel hard shading coverage with 99.98 % accuracy. The best ANN network topology is 3-60-1 (input-hidden neurons-output) model which provides an excellent generalization ability. This model utilized the tan Sigmoid transfer function for both input-hidden and hidden-output layer, and for the optimization process, Levenberg Marquardt outperformed other algorithms. The optimum ANN model has the lowest MSE value of 0.000020333 and with highest R-values of 0.99992, 0.99989, 0.9999, and 0.99992 for training, validation, testing, and overall, respectively. Based on the sensitivity analysis result, the open-circuit voltage significantly contributes to the solar panel shading detection.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"520 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121977036","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: 1

Air Quality Analysis During COVID-19 Utilizing Satellite Data 利用卫星数据分析COVID-19期间的空气质量

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9848299

Tinku Singh, Nikhil Sharma, Vinarm Rajput, Suryanshi Mishra, Satakshi, Manish Kumar

{"title":"Air Quality Analysis During COVID-19 Utilizing Satellite Data","authors":"Tinku Singh, Nikhil Sharma, Vinarm Rajput, Suryanshi Mishra, Satakshi, Manish Kumar","doi":"10.1109/CONIT55038.2022.9848299","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848299","url":null,"abstract":"Human health is severely endangered by the novel coronavirus (COVID-19). It is viewed as the worst global health threat humans have faced since the second world war and the WHO recognized it as a pandemic on March 11, 2020. This pandemic led several nations to adopt statewide lockdowns, while the industrial, construction, and transportation activities in several nations were disrupted, which lead to a significant shift in air pollutants. The lockdown, however, significantly impacted the environment and air quality in distinct cities. There are numerous ground stations deployed by pollution control organizations to monitor and collect the air pollutants data, but it is not feasible to set up a ground station in every city. In places where ground stations are not available for data collection, Google Earth Engine (GEE) satellite captured data can be used for data analysis. This study aimed to analyze the changes in air pollutants during the different lockdowns in India, such as nitrogen dioxide(NO2), sulfur dioxide(SO2), and carbon monoxide(CO) that contribute significantly to air pollution. In India, lockdowns were imposed during different periods of 2020, 2021, and 2022, according to COVID-19 waves. The air pollutants data during different waves have been analyzed and compared with the pre-COVID year (2019) data for the same duration. According to the study results, $N$ O2 and $S$ O2 were drastically reduced, but only a minor reduction in CO. Delhi, Jaipur, Ahmedabad, and Mumbai were among the major cities that saw the largest reduction, which was up to 60%.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115781556","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: 1

An Evaluation of Prediction Accuracy of Machine Learning Algorithms for Arteriosclerosis of the Human Heart 机器学习算法对人类心脏动脉硬化预测精度的评价

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9847910

Kiran Ingale, Neel Madane, Pradyna Patil

引用次数: 0

Control of Wind Energy Connected Single Phase Grid with MPPT for Domestic Purposes 家用MPPT对风能并网单相电网的控制

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9847854

S. Sushanth Kumar, I. Ali, A. Siddiqui

引用次数: 0

SVC-HT: Secure Vehicular Ad hoc Communications using Hybrid Trust SVC-HT:使用混合信任的安全车辆自组织通信

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9847836

V. Bhende, A. Sinha, A. Junnarkar

{"title":"SVC-HT: Secure Vehicular Ad hoc Communications using Hybrid Trust","authors":"V. Bhende, A. Sinha, A. Junnarkar","doi":"10.1109/CONIT55038.2022.9847836","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9847836","url":null,"abstract":"Because of the nature and characteristics of conveying significant level road security and enhanced traffic the executives, vehicular networks are turning into a key report subject under the intelligent transportation system (ITS). Weighty correspondence gear is introduced under vehicles, which requires a powerful stock, an on-board handling system, and information stockpiling gadgets. To keep up with and further develop the traffic signal system, an assortment of remote correspondence advances is utilized. The ITS can offer types of assistance to traffic specialists as well as security precautionary measures for drivers and travelers. Multiple ways for discussing security and protection issues for vehicle ad hoc networks (VANETs). In this paper, novel routing protocol called Secure VANET communications using Hybrid Trust (SVC-HT) is proposed to protect the communications from the malicious vehicles in the network. We integrated the hybrid trust approach with the clustering mechanism to improve the VANET performances. The proposed SVC-HT consists of two phases such as attacker detection with Cluster Head (CH) selection and reliable route formation for secure data transmission. The experimental outcomes of SVC-HT protocol are compared with three recent VANET protocols in terms of average throughput, Packet Delivery Ratio (PDR), delay, and overhead. The results of SVC-HT outperformed the existing protocols.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"29 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132372365","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 Multinomial Naïve Bayes Classifier for identifying Actors and Use Cases from Software Requirement Specification documents 从软件需求规范文档中识别参与者和用例的多项式Naïve贝叶斯分类器

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9848290

V. V., P. Samuel

{"title":"A Multinomial Naïve Bayes Classifier for identifying Actors and Use Cases from Software Requirement Specification documents","authors":"V. V., P. Samuel","doi":"10.1109/CONIT55038.2022.9848290","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848290","url":null,"abstract":"A software Requirements Specification (SRS) document is an NL (Natural Language) written textual specification that documents the functional and non-functional requirements of the system and various expectations of clients in a software development project. To understand the different requirements of the system, developers make use of this SRS document. In this paper, we apply Naive Bayes classifiers - Multinomial and Gaussian over different SRS documents and classify the software requirement entities (Actors and Use Cases) using Machine Learning based methods. SRS documents of 28 different systems are considered for our purpose and we define labels for the entities Actor and Use Case. Multinomial Naive Bayes is a popular classifier because of its computational efficiency and relatively good predictive performance. Out of the classifiers tried out, the Multinomial Naive Bayes recognizes Actors and Use Cases with an accuracy of 91%. Actors and Use Cases can be extracted with high accuracy from the SRS documents using Multinomial Naive Bayes, which then can be used for plotting the Use Case diagram of the system. Automated UML (Unified Modeling Language) model generation approaches have a very prominent role in an agile development environment where requirements change frequently. In this work, we attempt to automate the Requirement Engineering (RE) phase that can improve and accelerate the entire Software Development Life Cycle (SDLC).","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130199771","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

Improving Routing System in Vehicular Ad Hoc Network using Real Time Vehicular Traffic Information on City Roads 利用城市道路实时车辆交通信息改进车载自组网路由系统

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9847809

M. Alam, Maruf Haider Chowdhury, M. Islam, Afroza Akter, Affaf Hasan, Mahfuz Ullah

引用次数: 0

Different Techniques of Facial Image Generation from Textual Input : A Survey 基于文本输入的人脸图像生成技术综述

2022 2nd International Conference on Intelligent Technologies (CONIT) Pub Date : 2022-06-24 DOI: 10.1109/CONIT55038.2022.9848228

Eakanath Raparla, Veeresh Raavipaati, Shiva Nikhil G, Sameer S T Md, K. S

{"title":"Different Techniques of Facial Image Generation from Textual Input : A Survey","authors":"Eakanath Raparla, Veeresh Raavipaati, Shiva Nikhil G, Sameer S T Md, K. S","doi":"10.1109/CONIT55038.2022.9848228","DOIUrl":"https://doi.org/10.1109/CONIT55038.2022.9848228","url":null,"abstract":"The task of Text-to-Face synthesis is quite intricate and there hasn't been much research done on it, until recently. This is mainly due to the complex nature of human face and it's features, which vary widely over different situations. That being said, the field of Text-to-Image synthesis has gathered considerable interest quite late. In earlier research, generation is mainly done using reconstruction of visuals which correlate to the given words. Due to the rise of generative models in the field of deep learning, there has been a departure from these traditional computer vision based retrieval methods. One of the most significant factors for this change is the introduction of GANs. The idea of learning and reproducing the image as a whole, helped in producing better images. The introduction of attention based mechanisms, helped in synthesizing more detailed images which manages to show several facial features like eye brows, hair color, nose shape etc. In this survey, we discuss and summarize some of the methods used for the purpose of image & face generation and their development over the years.","PeriodicalId":270445,"journal":{"name":"2022 2nd International Conference on Intelligent Technologies (CONIT)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132625286","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