-74813b3e17f460286df1cc3 20220702061703218 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Recent Technology and Engineering (IJRTE) IJRTE 22773878 10.35940/ijrte.2277-3878 https://www.ijrte.org/ 07 30 2022 11 2 Department of Mechanical Engineering, JNTUA College of Engineering, Anantapur (AP), India Kanikicharla Jaya Sudheer Kumar Dr. B. Chandra Mohan Reddy Department of Mechanical Engineering, JNTUA College of Engineering, Anantapur (AP), India. According to this study, because of its light weight, high specific strength, and stiffness at high temperatures, Al6061 is the most appropriate material in the transportation business. The major goal of this research is to evaluate the physical properties of Al6061, such as thermal conductivity and electrical resistivity, by experimental investigation utilizing the multivolt drop approach. As Artificial Intelligence techniques become more widespread, they are being used to forecast material properties in engineering research. So, the second goal of this research is to employ Artificial Neural Networks to build a prediction model with fewer errors by utilizing experimental data. It will reduce the situation of direct observations throughout a wide range of temperatures where the physical properties of Al6061 are significant. As a consequence, it was discovered that the enhanced optimum ANN has significant mechanical properties that impact prediction. The anticipated results in electrical resistivity and thermal conductivity had Root Mean Squared Errors of 0.99966 and 0.99401, respectively, with R-Square average values of 0.820105. Various tests and ANN methodologies were used to validate and compare the suggested results. The comparison of predicted values with multivolt drop experimental results demonstrated that the projected ANN model provided efficient Al6061 accuracy qualities. 07 30 2022 78 87 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.B7128.0711222 https://www.ijrte.org/portfolio-item/b71280711222/ Administrative Management College, Bangalore (Karnataka), India Dr. Puja Shashi Cloud helps in offering on-demand latest technology that helps in deploying, accessing and using network-accessed information along with various applications and resources. Nowadays electronic health records are maintained by many hospitals that want to undergo a change in their legacy system. This type of transformation has helped physicians, nurses and also administrative staff access the desired record whenever needed. They believe that this may change the complete face of health information technology. However, lack of security and privacy are two important concerns that may provide hazards when choosing cloud solutions for various health-related factors. This problem can be avoided to some extent by evaluating cloud technology in an effective manner before its complete adoption. This paper uses four major aspects i.e., technology, security, legal and management for finding different types of challenges of this computing model. When any health services want to migrate from traditional to cloud-based health services then they can do different types of strategic planning for determining strategy, allocated resources and direction for maintaining a cloud environment in their organization. 07 30 2022 88 95 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.B7133.0711222 https://www.ijrte.org/portfolio-item/b71330711222/ Research & Development Software Engineering, OnePlus India. Gaurav Sharma This Paper will be an exercise in net extraction, natural language processing (NLP), and named entity recognition (NER). For the NLP, we will primarily be using the open-supply Python libraries NLTK and Spacy. This paper is meant to be a demonstration of a use-case for net extraction and NLP, now no longer a complete novice educational to the use of both techniques. We extricated joins from a web page, at that point utilized those joins to extricate indeed more substance from the internet location. We utilized that substance to at that point extricate and upgrade that data utilizing outside APIs, ML clustering calculations, and NLP. 07 30 2022 103 108 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijrte.org true 10.35940/ijrte.B7145.0711222 https://www.ijrte.org/portfolio-item/b71450711222/ Security Network Consulting Engineer, Aryaka Networks, Bengaluru (Karnataka), India. Swathi Dayanand Dr. Chaitra N Associate Professor, Department of Electronics and Communication Engineering, BNM Institute of Technology, Bengaluru (Karnataka), India. Remarkable advances in cyberspace, have amassed a magnanimous set of Internet users worldwide. While people engage in various activities and use the web for various needs, the prospective fear of cyber attacks, crime and threats is indubitable. Though a plethora of preventive measures are in use, it is impossible to circumvent cyber threats completely. Cybersecurity is a domain that deals with prevention of cyber attacks by use of effective precautionary and remedial measures. With the advent of Artificial Intelligence (AI) and Machine Learning (ML) and its profound scope in contemporary technical innovations, it is a critical necessity to inculcate its techniques in enhancement of existing cybersecurity techniques. This paper offers a detailed review of the concepts of cybersecurity, commonly encountered cyber attacks, the relevance of AI and ML in cybersecurity along with a comparative performance analysis of distinct ML algorithms to combat network anomaly detection and network intrusion detection. 07 30 2022 96 102 10.35940/ijrte.B7150.0711222 https://www.ijrte.org/portfolio-item/b71500711222/