iosr-JCE   Volume-24 ~ Issue-1 ~ Jan. - Feb. 2022

Abstract: Car plate recognition (CPR) systems provide valuable benefits to both the people and governments. At the level of people, CPR systems facilitate performing tasks related to parking and reporting stealing cars, while at the governmental level they can be employed for arranging traffic flow, monitoring borders and tracking criminal traffic. Due to these advantages, CPR systems have been received significant attention from research groups. Traditional CPR systems suffer from high computational costs as well as low performance and recognition accuracy. To overcome this challenge, deep learning technique are used. However, to build a robust CPR system, two kinds of factors must be taken into consideration......

Key Word: car plate recognition (CPR); factors; deep learning; Convolutional Neural Network (CNN); Cost; performance.

[1]. Ahsan, Mominul, Md Based, and Julfikar Haider. "Intelligent System for Vehicles Number Plate Detection and Recognition Using Convolutional Neural Networks." Technologies 9.1 (2021): 9.
[2]. Yauri-Machaca, Melissa, et al. "Design of a vehicle driver drowsiness detection system through image processing using matlab." 2018 IEEE 38th Central America and Panama Convention (CONCAPAN XXXVIII). IEEE, 2018.
[3]. Vilke, Siniša, and Frane Tadić. "Review of Good Practices in the Introduction of Traffic Management Systems and Urban Mobility." Pomorski zbornik 59.1 (2020): 95-113.
[4]. Mohammadiha, A., Malakooti, H., & Esfahanian, V. (2018). Development of reduction scenarios for criteria air pollutants emission in Tehran Traffic Sector, Iran. Science of the Total Environment, 622, 17-28.
[5]. Wilén, Nina. "Achieving a gendered transformation of the post-conflict military through security sector reform: unpacking the private–public dynamics." International Feminist Journal of Politics 22.1 (2020): 86-105.

Abstract: Cloud computing lead to abrupt variations resulting to immense number of data streams for storage, which are considered as tasks in a heterogeneous cloud environment. To address this problem, many researchers proposed different solutions, but still resource utilization with energy consumption remains an issue. In this research a task classification model for energy efficiency using greedy heuristic in heterogeneous cloud is proposed. The technique adopts resource requirement rate for task classification resource utilization. The CPU utilization is predictor of the overloaded and under loaded virtual and physical machines while classifying the tasks based on intensiveness. The proposed approach classified task based on intensiveness thereby reducing the energy consumption free of Service Level Agreement (SLA) violation..

Key Word: Task Classification, Energy efficiency, Cloud Computing, Heterogeneous

[1]. Afzal S. & Kavitha G. (2019). Load balancing in cloud computing–A hierarchical taxonomical classification. Journal of Cloud Computing, 8(1), 1-24.
[2]. Arroba P; Moya J. M; Ayala Jose L. & Buyya R. (2017). Dynamic Voltage and Frequency Scaling‐aware dynamic consolidation of virtual machines for energy efficient cloud data centers. Concurrency and Computation: Practice and Experience, 29(10), e4067.
[3]. Barroso L. A; Hölzle U. & Ranganathan P. (2018). The datacenter as a computer: Designing warehouse-scale machines. Synthesis Lectures on Computer Architecture, 13(3), i-189.
[4]. Buyya R; Srirama S. N; Casale Giuliano C. R.; Simmhan Y; Varghese B. G. E; Javadi B; Vquero L; M; Netto M. AS. (2018). A manifesto for future generation cloud computing: Research directions for the next decade. ACM computing surveys (CSUR), 51(5), 1-38.
[5]. Chang Y., Huang R; Ries R. J; & M. E. (2015). Life-cycle comparison of greenhouse gas emissions and water consumption for coal and shale gas fired power generation in China. Energy, 86, 335-343

Abstract: During the COVID-19 education has shifted from face to face to online to avoid large gatherings and crowds for blocking the virus transmission. To analyze effect of virus on the user experience. This paper adopts the evaluation to analyze user experience before and after the outbreak of pendemic COVID-19. We will present the findings of change of users' concerns for mode of online education. The access speed, reliability, technology of video information, course management, communication and interaction, and learning technical support. This paper presents abilities and response of online education platforms during COVID-19..

Key Word: COVID-19, education system, online classes, assessment during covid-19

[1]. The Impact of the COVID-19 Pandemic on User Experience with Online Education Platforms in China, Tinggui Chen 1,*,Lijuan Peng, 1,Bailu Jing, 2,Chenyue Wu, 2,Jianjun Yang 3 andGuodong Cong
[2]. A Literature Review on Impact of COVID-19 Pandemic on Teaching and Learning Sumitra Pokhrel1 and Roshan Chhetri2
[3]. Teaching and teacher education in the time of COVID-19 Jeanne AllenGriffith University, Australia, jeanne.allen@griffith.edu.au
[4]. The impact of COVID-19 on education and on the wellbeing of teachers, parents, and students: Challenges related to remote (online) learning and opportunities for advancing the quality of education Zamira Hyseni Duraku* Linda Hoxha
[5]. Big Data Analytics Challenges and Solutions in Cloud Ms. Manju Sharma College of Computer Science & Information Systems, Jazan University Jazan, Kingdom of Saudi Arabia

Abstract: The efficiency and efficacy, information technology has becoming more widely used in university administration. In the early stages of its development, the major purpose and use of management information systems (MIS) was to improve the efficiency of university office functions. It was utilized to keep track of I for-mation for students and employees. The focus on data entry and collation rather than data transmission and analysis was the most major cause of concern. The value of management data was apparent during the integra-tion phase. Workload, time management, and report quality have all improved. In the literature, time con-straints, a lack of confidence......

Key Word: Management Information Systems, University Administration, University Management

[1]. Bisaso, R., & Visscher, A. (2005). Computerised school information systems usage in an emerging country – Uganda. In A. Tatnall, J. Osiorio, and A. Visscher (Eds.) Information technology and educational management in the knowledge society (pp. 81–98). New York: Springer.
[2]. Bober, M. (2001). School information systems and their effect on school operations and culture. Journal of Research on Technology in Education, 33 (5), 1–11.
[3]. Bruce A. Rocheleau. (2006). Public Management Information Systems.
[4]. Clarke, S. (2007). Information Systems Strategic Management - An Integrated Approach 2nd ed. New York: Routledge (Taylor & Francis Group).
[5]. Carnoy, M. (2004). ICT in education: Possibilities and challenges. Inaugural lecture of the Universitat Oberta de Catalunya (UOC) 2004–2005 Academic Year, Barcelona

Abstract: The number of certificate counterfeits in our society has become challenging and prevalent. Today, forging certificates has become a business tumbling from the need/want of the people for employment. Graduates with legitimate certificates/degrees are denied job opportunities by the holders of these forged credentials. To address this problem, many researchers have proposed a certificate verification system. Although the existing systems can solve some of the major problems such as accessing student's records with the provision of a central database to manage these records electronically. However, the system can easily be hacked and manipulated since it is mostly available on centralized servers. This dissertation developed a certificate generation and verification system using blockchain technology and Quick Response (QR) code. Iterative and incremental models......

Key Word: (ABS) Blockchain, IPFS, Certificate, Generation, Verification and Quick Response Code

[1]. Aniket, V. R., Sagar, S. J., Shivraj, M. P. & Madhavi G. P. (2020). Education Degree Fraud Detection and Student Certificate Verification Using Blockchain. International Journal of Scientific Research and Engineering Development, 3 (1), 287-289.
[2]. Dawi, N. M., Jusoh, A., Streimikis, J., & Mardani, A. (2018). The influence of service quality on customer satisfaction and customer behavioural intentions by moderating role of switching barriers in satellite pay TV market. Economics and Sociology, 11(4), 198-218. doi:10.14254/2071-789X.2018/11-4/13
[3]. Ehtesham Chowdhury, A. Z. M., Bhowmik, A., Hasan, H., & Shamsur Rahim, M. (2018). Analysis of the Veracities of Industry Used Software Development Life Cycle Methodologies. arXiv e-prints, arXiv-1805.
[4]. Gaonkar, P., Daruwale, P., & Nagmani, K. (2020). Centralized Digital Certificate Issuing System.
[5]. Javier, R. S., Javier H., Oscar, M., & Manel, M. (2004). Securing Certificate Revocation through Speaker Verification: the CertiVeR Project. 2nd COST 275 Workshop - Biometrics on the Internet.

Abstract: This project proposes the designing a wireless sensor network (WSN) to monitor the Light levels and the temperature of the environment and humidity through the sensor and send these grades wirelessly to the control unit to solve the problem of geographical dimension and control of places where human intervention is difficult to use three points using Arduino and GSM Arduino is a small computer that can interact and control the center around it is better than the desktop computer , GSM is used to send data to the control unit and results are extracted in the form of curves using the mat lab program and the grades are stored in the database of the excel file in the control unit .

[1]. www.jacn.net >vol3
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[4]. http://dx.doi.org/10.14257/astl.2015.95.31 (2015) (Advanced Science and Technology Letters).
[5]. https://www.researchgate.net/publication/41936100

Abstract: In this project we would be making a smart way of managing the traffic using computer vision and object detection for performing various processes for smooth flow of traffic. By using the OpenCV library, and YoloV3 algorithm, we are trying to control the traffic lights at the junctions by finding the vehicle density at the signal. The system would also be able to track the vehicles that are breaking the signal and the details would be transferred to the authorities. Majority of the code is written in Python using various libraries and the dataset that will be used is an open-source large-scale object detection, segmentation, and captioning dataset. This project will ensure effective and accurate management of traffic and will help in making traffic lights more efficient..

Key Word: Computer Vision, YoloV3, Darknet, Traffic management, Euclidean Distance

[1]. Janahan, Senthil Kumar &Murugappan, Veeramanickam&Sahayadhas, Arun &Narayanan, Kumar & R, Anandan& Shaik, Javed. (2018). IoT based smart traffic signal monitoring system using vehicle counts. International Journal of Engineering & Technology. 7. 309. 10.14419/ijet.v7i2.21.12388
[2]. Lanke, Ninad&Koul, Sheetal. (2013). Smart Traffic Management System. International Journal of Computer Applications. 75. 19-22. 10.5120/13123-0473.
[3]. C. S. Asha and A. V. Narasimhadhan, "Vehicle Counting for Traffic Management System using YOLO and Correlation Filter," 2018 IEEE International Conference on Electronics, Computing and Communication Technologies (CONNECT), 2018, pp. 1-6, doi: 10.1109/CONECCT.2018.8482380.
[4]. Song, H., Liang, H., Li, H. et al. Vision-based vehicle detection and counting system using deep learning in highway scenes. Eur. Transp. Res. Rev. 11, 51 (2019).
[5]. Nielsen, A.A. (2007). The regularized iteratively reweighted mad method for change detection in multi-and hyperspectral data. IEEE Transactions on Image processing, 16(2), 463–478