iosr-JCE   Volume-24 ~ Issue-4 ~ Jul. - Aug. 2022

Abstract: The study analyzed the effects of product approach to language writing skills on students' performance.Product approach stresses on the final result of the writing process that writers go though in composing texts. The purpose of this study was to find out the effects of product approach to English language writing skills on students' performance within selected secondary schools of Kenya. The objectives were to determine the students' performance in the writing test before and after instruction using the product approach, and to analyze the effect of product approach on students' performance in English language writing test within selected secondary schools of Kenya......

Keywords: Product Approach, Writing Skills, Students Performance, Effect, Kenya

[1]. Akinyenye, C., &Pluddemann, C. (2016). The story of a narrative: Teaching and assessing English writing in a township school. Journal of the Reading Association of South Africa, 7 (1), 1-8.
[2]. Brown., H. D. (2001). Teaching by principles: An interactive approach to language pedagogy (2nd Ed).New York: Addison Wesley Longman.
[3]. Christmas, B. (2011). The role of brainstorming in improving students writing performance in the EFL classroom. https://sydney.educ.au/cet/docs/research.
[4]. Chow, T. (2007). The effects of the process-genre approach to writing instruction on the expository essays of ESL students in Malaysian secondary school. Unpublished dissertation, University Sains Malaysia, Penang.
[5]. Creswell, J. W., & Creswell, J. D. (2018).Research Design: Qualitative, Quantitative and Mixed Methods Approaches. (5th Ed.). USA: Sage.

Abstract: An electroencephalogram (EEG) is an experiment to determine the activity of electrical brain signals using small, metal electrodes which are affixed to the brain scalp. These EEG signals are one of most complex signals that represents the brain activity. Dataset is collected from the Physionetdata-base which comprises the motor Imagery functions of Left and right fist, both fists and both feet. These recordings might be distorted by the contamination of traces such as blinking of eyes or muscle movements etc. In this paper, the method called the common spatial patterns (CSP) has been implemented as feature extraction technique. This CSP technique includes one-hot encoding and z-score normalization. CSP is the characteristic eradication approach with the usage of spatial filtering......

Keywords: ClassificationEEG signals, Common spatial patterns (CSP), one-hot encoding, z-score normalization, convolutional neural network (CNN). Predictionsemotions.csv, deep learning, Recurrent neural network

[1]. J. R. Wolpaw, D. J. McFarland, G. W. Neat, and C. A. Forneris, "An EEG-based brain-computer interface for cursor control," Electroencephalogr. Clin. Neurophysiol., vol. 78, no. 3, pp. 252–259, 1991, doi: 10.1016/0013-4694(91)90040-B.
[2]. G. Pfurtscheller, G. R. Müller-Putz, R. Scherer, and C. Neuper, "Rehabilitation with brain-computer interface systems," Computer (Long. Beach. Calif)., vol.
[3]. https://www.brainfacts.org/core-concepts/your-complex-brain#:~:text=The%20brain%20is%20the%20body's,neurons%20in%20many%20brain%20regions.
[4]. X. Tang, W. Li, X. Li, W. Ma, and X. Dang, "Motor imagery EEG recognition based on conditional optimization empirical mode decomposition and multi-scale convolutional neural network," Expert Syst. Appl., vol. 149, 2020, doi: 10.1016/j.eswa.2020.113285.
[5]. P. Kant, S. H. Laskar, J. Hazarika, and R. Mahamune, "CWT Based Transfer Learning for Motor Imagery Classification for Brain computer Interfaces," J. Neurosci. Methods, vol. 345, no. February, p. 108886, 2020, doi: 10.1016/j.jneumeth.2020.108886.

Abstract: Cloud computing is an exceptionally versatile and effective foundation for running undertaking and web applications. Vitality utilization use and simultaneous impacts on condition are the dynamic difficulties with respect to distributed computing. We examined past investigates dependent on vitality productivity approaches and recovered the conditions to advance green distributed computing models. Server farms are considered as the foundation of cloud framework. Various organizations are putting resources into building up vast server farms to oblige diverse distributed computing administrations. These server farms assimilate tremendous measure of vitality. They are additionally mind boggling in the foundation. Throughout the years, control utilization has risen as an essential.....

Key-words: Cloud Computing, Predictive Analysis, Convex Optimization, and Energy Efficiency.

[1]. B. Wadhwa and A. Verma, "Carbon Efficient VM Placement and Migration Technique for Green Federated Cloud Datacenters," IEEE, pp. 2297-2302, 2014.
[2]. C. Qiu, H. Shen and L. Chen, "Towards Green Cloud Computing: Demand Allocation and Pricing Policies for Cloud Service Brokerage," IEEE, pp. 203-2012, 2015.
[3]. Eduard OróVictorDepoorter,AlbertGarcia and JaumeSalom,‖Energy efficiency and renewable energy integrationin data centres. Strategies and modeling review,‖ELSEVIER,pp.1-17,2015.
[4]. F. Farahnakian, T. Pahikkala, P. Liljeberg, J. Plosila and H. Tenhunen, "Utilization Prediction Aware VM Consolidation Approach for Green Cloud Computing," IEEE, pp. 381-388, 2015.
[5]. L. A. Rocha and E. Cardozo, "A Hybrid Optimization Model for Green Cloud Computing," IEEE, pp. 11-20, 2014

Abstract: Steganography is a fascinating topic that is unique from the everyday cryptography and system administration that most of us deal with. Steganography is a type of code that can be used to communicate covertly. We looked into steganography's theoretical and practical limitations. We used the LSB methodology to print out the picture steganography system enhancement to provide a secure communication method. This steganography computer software shows how to use any text format to hide any type of information. The capacity of this application to support any type of text is its crowning achievement. Since prehistoric times......

Keywords: Encryption, Decryption, Plain Text, Cipher Text, Cryptanalysis, Steganography, Brute Force and Cryptography

[1]. Ajit, S. and Malik, S (2013) "Securing Data by Using Cryptography withSteganography", International Journal of Advanced Research in Computer Science andSoftware Engineering Volume 3, Issue 5.
[2]. Bairai, A. K., (2011) "ASCII based Even-Odd Cryptography with Gray code and Image Steganography": A dimension in Data Security, Vol.01, No.2, pp 37-41.
[3]. Bolton, R. (2002). Statistical Fraud Detection: Review, Statistical Science, 17 (3), pp. 235-255.
[4]. Barthe, E. (2006) "encryption and watermarking Publicity Campaigns "Department of Justice, p.9
[5]. Clark, R.V. (1997). "Situational crime and steganography technique". 2nd edition, New York: harrow and Heston, pp2

Abstract: In the post-COVID-19 era, online teaching has become a major means of teaching strategies of colleges and universities, and willcontinue to play a key role. At the same time, many problems have been exposed and need to be solved. This study analyzed the current situation of online teaching of colleges and universities from aspects of students, teachers, platform technology, and management system, and put forward suggestions for optimizing online teaching of colleges and universities..

Keywords: online teaching；current situation；Countermeasures

[1]. Theoretical Basis and system Choice of Online teaching. China Distance Education, 2006(7): 14.
[2]. Current situation, characteristics and paradigm of foreign MOOC research. Teaching Research, 2019(3):75.
[3]. Correctly understand and do a good job of "school suspension without school suspension" during the epidemic. China Audio-Visual Education, 2020(4): 1.
[4]. The situation of online education in colleges and universities and the consideration of the next work. http://www.moe.gov.cn/fbh/live/2020/51987/sfcl 202005/t20200514_454117. html.
[5]. Problems and countermeasures of online teaching in the context of epidemic.

Abstract: This work is ondesign and implementation of Web-Based Patient Management System (PMS). The system provides the benefits of efficient tasks, improved administration & control, patient care, and improved effectiveness. . The paper describes about an knowledge of a web-based platform that make many medical/patient processes online using Web, networking technology that can be very important in implementing the functionality of online patient management. The system was designed inC# as the front-end software, which is an Object Oriented Programming language and has connectivity with the back-end software in MySQL database..

Keywords: Patient, Employee, Web-Based, Inpatients, Outpatients, Drug.

[1]. Hospital Management Information System, Gujarat Informatics System (2012)
[2]. Praveen K.A and Gomes L.A, 2006: "A Study of the Hospital Information System (HIS) In the Medical Records Department of A Tertiary Teaching Hospital" Journal of the Academy of Hospital Administration, Vol. 18, No. 1 (2006-01 - 2006-12).
[3]. Smith M. and Gert van der Pijl, 1999: "Developments in Hospital Management and Information Systems". Tilburg University School of Economics, Netherlands.
[4]. Adebisi, O.A, Oladosu D.A, Busari O.A, and Oyewola, Y.V(2015).Design and Implementation of Hospital Management System. International Journal of Engineering and Innovative Technology (IJEIT) Volume 5,Issue 1.
[5]. Design and Implementation of Hospital Management System Using Java, IOSR Journal of Mobile Computing & Application (IOSR-JMCA,

Abstract: The client-server model, too large for proper sign up, is a response to the maladies pointed out by the common PC client-have model. The model turns out to be a response to the discomfort of the local area model where a single record server with no management force is served by various different structures. In this model the coordination of data and relation is given by a client-server scheme where the clients are allowed to be bound by common problems like correspondence shows. Keeping in view its simplicity, the client can send the arrangement to the right server in a client-server arrangement.........

Keywords: Client-server systems; client-server architecture; distributed computing.

[1]. Machine Learning and Medical Imaging" by Parveen Gulia and K. V. Arya, International Journal of Computer Science and Mobile Computing, 2019.
[2]. "Artificial Intelligence in Medical Imaging: A Radiological Perspective" by William W. Mayo-Smith, Journal of the American College of Radiology, 2018.
[3]. "Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, and Practical Implications" by Tarik K. Alkasab et al., Radiology, 2018.
[4]. "Applications of Deep Learning in Medical Imaging and Radiology" by Andrew Y. Ng, Journal of the American Medical Association, 2018.
[5]. "Artificial Intelligence in Radiology: Current Technology and Future Directions" by David J. Seidenwurm, Journal of the American College of Radiology, 2018.

Abstract: Big data is a term used to portray the enormous and complex datasets that are created by present day organizations and associations. These datasets can be utilized to acquire bits of knowledge into client conduct, recognize patterns, and make expectations about future occasions. Predictive big data is a subset of big data that utilizes measurable and AI strategies to foresee future results. This sort of data can be utilized to further develop independent direction, improve business processes, and forestall issues before they happen. The insurance of predictive big data is a complicated and testing issue. From one viewpoint, predictive big data can be utilized to work on our lives........

Keywords: Predictive, Big, Data, Protection

[1]. M. Gamal, R. Rizk, H. Mahdi, and B. Elhady, "Bio-inspired load balancing algorithm in cloud computing," in Proc. of The International conference on Advanced Intelligent systems and Informatics (AISI), Cairo, Egypt, pp. 579-589, September 2017. [2]. Nitin Thapliyal, Priti Dimri "Load Balancing in Cloud Computing Based on Honey Bee Foraging Behavior and Load Balance Min-Min Scheduling Algorithm", International Journal of Electrical and Electronics Research (IJEER) Volume10 Issue 1 Pages 01-06 2021
[3]. P. T. Endo, M. Rodrigues, G. E. Gonçalves, J. Kelner, D. H. Sadok, and C. Curescu, "High availability in clouds: systematic review and research challenges," Journal of Cloud Computing: Advances, Systems and Applications, pp. 5-16, 2016
[4]. S. Aslam, and M. A. Shah, "Load balancing algorithms in cloud computing: A survey of modern techniques," National Software Engineering Conference (NSEC), Pakistan, December 2015.
[5]. S. G. Domanal, and G. R. M Reddy, "Load balancing in cloud computing using modified throttled algorithm," in Proc. of International Conference on Cloud Computing in Emerging Markets (CCEM), Bangalore, India, October 2013

Abstract: The reduction of bias in training data and the improvement of algorithmic fairness may be accomplished by the use of procedures such as data preparation, data augmentation, and the oversampling of groups that are underrepresented. Another essential component is the creation of algorithms that take into consideration the principle of fairness. There have been a lot of different approaches that researchers have developed in order to guarantee that the decisions that machine learning algorithms make are objective and fair. It is necessary to include fairness......

Keywords: Bias , Natural Language Processing , Techniques ,Implications

[1]. Smith, B. (2018). The ethical challenges of artificial intelligence. Cambridge Quarterly of Healthcare Ethics, 27(4), 599-609. doi:10.1017/S0963180118000038
[2]. Buolamwini, J., & Gebru T. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Proceedings of Machine Learning Research 81:1-15
[3]. Buolamwini, J., & Gebru, T. (2018). Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification. Proceedings of the 1st Conference on Fairness, Accountability and Transparency, 77-91.
[4]. Smith-Lewis A., & Srinivasan R., (2020). Responsible Artificial Intelligence: Building Trust Through Transparency & Explainability [Whitesection]. IBM Watson Health.
[5]. Russell, S., & Norvig, P. (2016). Artificial Intelligence: A Modern Approach (3rd ed.). Pearson Education Limited