2021 International Conference on Innovative Trends in Information Technology (ICITIIT)最新文献_第2页

A Literature Review on Technology-Based Problem-Posing Strategies in Academia 学术界基于技术的问题提出策略研究综述

2021 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399595

P. V. Elizabeth Vinitha, V. G. Renumol

{"title":"A Literature Review on Technology-Based Problem-Posing Strategies in Academia","authors":"P. V. Elizabeth Vinitha, V. G. Renumol","doi":"10.1109/ICITIIT51526.2021.9399595","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399595","url":null,"abstract":"Problem-posing (PP) is an act by a learner to gain knowledge by generating new problems or questions in a given scenario. Studies have proved that PP is an effective student-centered method for learning. Moreover, it helps students to understand complex concepts and improve their learning outcomes. Many researchers have tried to develop technology-based learning systems using PP strategy in various domains and technology tools are playing a major role in education, in this digital era. Hence, the main objectives of this study are: a) To identify the strategies used to implement problem-posing based on technology and b) To identify the advantages of technology-based PP strategies over conventional problem-posing methods. To achieve these objectives we have conducted a literature review on 67 papers. The study has identified collaborative mobile learning, com-puter-based group activities, gaming activities, web-ap-plication-based activities and tablet-PC based activities as technology-based PP strategies. It has also identified that there are limited researches on PP in domains such as STEM, Nursing, English, and Biochemistry. We found that technology-based PP strategies have various advantages. They help students to acquire knowledge, make an impressive change in their learning outcomes, improve students' motivation and responsibility by engaging them in the learning process, improve collaborative skills and lower their cognitive load.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128941404","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

Real Time Electric Light Control using EOG Signals 使用EOG信号的实时电灯控制

2021 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399605

R. Anuradha, G. Rathi, A. GraceSelvarani, N. Gokul, M. S. Dhakshata

引用次数: 1

Assessment Methods and Interventions to Develop Computational Thinking — A Literature Review 发展计算思维的评估方法和干预措施-文献综述

2021 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399606

V.V. Vinu Varghese, V. G. Renumol

引用次数: 3

Graph Grammar for Parikh Word Representable Graphs Parikh词可表示图的图语法

2021 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399604

V. Jayakrishna, Lisa Mathew, Nobin Thomas, K. Subramanian, J. Mathew

引用次数: 0

Future Predicting Intelligent Camera Security System 未来预测智能摄像头安全系统

2021 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399597

Merin Abraham, Nikita Suryawanshi, Nevin Joseph, Dhanashree Hadsul

{"title":"Future Predicting Intelligent Camera Security System","authors":"Merin Abraham, Nikita Suryawanshi, Nevin Joseph, Dhanashree Hadsul","doi":"10.1109/ICITIIT51526.2021.9399597","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399597","url":null,"abstract":"The need for continuous human supervision, i.e. these systems are unable to perform certain functions without any operator monitoring the cctv video, is one of the major disadvantages of any camera-based monitoring system. An individual can hold his/her focus on the screen feed for a limited number of hours and not be distracted. Such poor monitoring could lead to a reduction in the effectiveness of the human operator's immediate action against a potential threat if detected on the screen. Therefore, the unique features of future prediction through the live video analysis method would have a huge effect on the surveillance system-based industries in order to address the limitations of the human attention span. The proposed system would be able to process the live stream from the cctv camera and generate output that will warn the operator of any possible danger that appears to occur or is occurring. For this method, a deep learning architectural approach is used with Convolutional Neural Networks. In this way, the surveillance camera system can detect an individual and identify and recognize those items carried by him or her on the basis of the level of danger. Similarly, the system can also identify and classify those acts that occur in the video feed into three distinct categories: natural, suspicious, malicious (based on the threat level) and send an alert to the respective human operator. Thus, the system will be able to help companies overcome security surveillance challenges and protect themselves from theft or any act of violence taking place in the area surrounding cctv.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115439459","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

Automated Question Answering Assistant 自动问答助手

2021 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2021-02-11 DOI: 10.1109/icitiit51526.2021.9399601

Rutuja Kitukale, Nachiketh Pai, P. Nerkar, Archana Shirke, J. Jose

{"title":"Automated Question Answering Assistant","authors":"Rutuja Kitukale, Nachiketh Pai, P. Nerkar, Archana Shirke, J. Jose","doi":"10.1109/icitiit51526.2021.9399601","DOIUrl":"https://doi.org/10.1109/icitiit51526.2021.9399601","url":null,"abstract":"IT firms have a number of clients from various sectors. These vendors have many questions or queries which are to be answered manually. Also the amount of questions asked are huge in numbers approximately in the club of 500 to 600. This includes reading the document thoroughly and extracting all the related information regarding the question and then representing the data in appropriate format required. Answering all such questions manually in a limited period of time is quite a tedious task. This leads to more time consumption and increases the human labour behind it. The project aims at developing an automated system which would create a deep learning model that will input the questions present in any format and answer them automatically with the help of the algorithm and give the output in the required format, thus simplifying the work of searching the answers in a given extract and finding the least error prone answer to the question thus increasing the accuracy. This will also reduce time required behind studying any document and framing the answers from them. This system will be able to answer all types of questions. The system can be used for generating answer keys for online exams. The system will encourage the research that returns answers directly instead of keyword extraction from the documents with ample number of queries. Even it can be used for open domain searching of information over the internet.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127191499","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

Application of Artificial Intelligence for Maintenance Modelling of Critical Machines in Solid Tire Manufacturing 人工智能在实心轮胎制造关键机械维修建模中的应用

2021 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399600

R. Jayasuriya, P. A. G. M. Amarasinghe, S. Abeygunawardane

{"title":"Application of Artificial Intelligence for Maintenance Modelling of Critical Machines in Solid Tire Manufacturing","authors":"R. Jayasuriya, P. A. G. M. Amarasinghe, S. Abeygunawardane","doi":"10.1109/ICITIIT51526.2021.9399600","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399600","url":null,"abstract":"Machine maintenance is a challenging task in the manufacturing industry. The reliability and maintenance scheduling of continuously running machines are essential for the performance of manufacturing plants. In this paper, an artificial intelligence-based machine maintenance management system is proposed for a tire manufacturing plant. The proposed system consists of two main subsystems: dynamically updating maintenance scheduler and machine troubleshooter. The maintenance schedular is implemented using an Artificial Neural Network (ANN) whereas the machine troubleshooter is based on an expert system. The ANN-based maintenance schedular provides the optimum time frame to plan the preventive maintenance of critical machines based on the condition monitoring data and production data. The ANN is validated using validation performance charts and regression state charts obtained from the Matlab runtime environment. It is found that the R-squared value of the ANN is 0.998. On the other hand, a rule-based inference system is used in the machine troubleshooter. The expert system is validated by evaluating the maturity of the knowledge base. The percentage maturity of the expert system is reached to a level of 90% within 3 months.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114661742","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

Pedestrian Counting Using Yolo V3 使用Yolo V3进行行人计数

2021 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399607

Aiswarya Menon, Bini Omman, Asha S

{"title":"Pedestrian Counting Using Yolo V3","authors":"Aiswarya Menon, Bini Omman, Asha S","doi":"10.1109/ICITIIT51526.2021.9399607","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399607","url":null,"abstract":"Object detection is the process of determining the presence, location, and type or class of at least one object using a bounding box. The person detection process produces a bounding box and allot a class label as a person based on YOLO v3. In YOLO v3 the features are learned, divides the image cells and each cell says a bounding box and entity classification directly. There could be more than one bounding box per person, but the system makes use of non-maximum suppression to reduce the number of bounding boxes to one per person. Finally, the number of persons in the image and video are calculated using the count of the bounding boxes. The dataset used for static pedestrian detection is the INRIAdataset and ShanghaiTech dataset. Yolo_Mark is used for marking bounding boxes of persons and gets its annotation files using 243 images from the INRIA dataset. Darknet is used as the framework for implementing YOLOv3. From INRIA Dataset 120 images are used for testing purposes. Testing on the INRIA dataset resulted in an accuracy of 96.1%. From the Shanghai tech-B, dataset 56 images are used for testing. Testing resulted in an accuracy of 87.3%.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"277 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132457547","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: 5

Improved RSSI based Vehicle Localization using Base Station 改进的RSSI基于基站的车辆定位

2021 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399596

Debajyoti Biswas, S. Barai, B. Sau

{"title":"Improved RSSI based Vehicle Localization using Base Station","authors":"Debajyoti Biswas, S. Barai, B. Sau","doi":"10.1109/ICITIIT51526.2021.9399596","DOIUrl":"https://doi.org/10.1109/ICITIIT51526.2021.9399596","url":null,"abstract":"The physical position of the vehicles is vital information for the tracking operation. The vehicles localization have several benefits and support for safety, comfort, and reliability in future transportation systems. Thus the vehicular localization has investigated, where the base station (BS) will track the target vehicles. This paper mainly addresses a new localization scenario on distributing the coverage area based on the received signal strength indicator (RSSI). The RSSI measured in regular operation and consume minimum energy. However, wireless RSSI suffers from various interference in dynamic environments. For solving these issues, several methods have been proposed in the literature, including the signal intensity attenuation model (SIAM). This paper incorporates the fact that the motion of vehicles satisfies environmental constraints to improve the accuracy of RSSI-based localization by a new model, namely the gaussian signal attenuation model (GSAM) using most likely RSSIs. Numerical results demonstrate that the proposed method considerably outperforms the existing methods in terms of dynamic positioning accuracy.","PeriodicalId":161452,"journal":{"name":"2021 International Conference on Innovative Trends in Information Technology (ICITIIT)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134286213","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: 5

Performance Investigation of Capacitive Wireless Charging Topologies for Electric Vehicles 电动汽车电容式无线充电拓扑性能研究

2021 International Conference on Innovative Trends in Information Technology (ICITIIT) Pub Date : 2021-02-11 DOI: 10.1109/ICITIIT51526.2021.9399608

S. Kodeeswaran, M. Nandhini Gayathri

引用次数: 8