IJMLNCE Editorial Note Volume No 03, Issue No 04: Special Issue Volume No 03, Issue No 04

International Journal of Machine Learning and Networked Collaborative Engineering

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Title IJMLNCE Editorial Note Volume No 03, Issue No 04: Special Issue Volume No 03, Issue No 04
Creator Agarwal, Shivani
Khari, Manju
Tanwar, Prakash
Subject Machine Learnining
Description The International Journal of Machine Learning and Networked Collaborative Engineering (IJMLNCE) with ISSN: 2581-3242 is now indexed in popular databases such as BASE (Bielefeld Academic Search Engine), CNKI Scholar, CrossRef, CiteFactor, Dimensions, DRJI, Google Scholar, Index Copernicus, JournalTOCs, J-Gate, Microsoft Academic, PKP-Index, Portico, ROAD, Scilit, Semantic Scholar, Socolar or WorldCat-OCLC. We are now proud to present the ninth volume of the Journal, Volume No-03 Issue No-04, with five high-quality papers written by international authors and covering different aspects related to machine learning and collaborative engineering.
The First research article authored by Priyanka and Manju Khari has written their article on the title "A Survey of Cloud Computing Security Issues." In the world of computer networking, cloud computing makes a technical shift in computing services being provided locally to being provided remotely by third-party service providers. The data which was previously retained by the control of users now under the control of service providers. Cloud computing conveys numerous economic and practical assistance, along with severe security alarms that might impend commercial endurance and business status. The cloud computing definition is still not clear in a huge portion, as of the extent of security threats and the broad expanse of virtual information being distributed over the unsecured area. This manuscript aims to assess in what way security risk issues are affecting the surviving and eventual cloud platform. This survey examines the published resources and studies, examines available concerns laterally with existing countermeasures to assess the complete assertion level of security of the cloud. The primary goal of the survey is to analyse the security risks and the existing security algorithm's performance in terms of different security parameters. This study includes the basics of cloud computing by adding its characteristics, models, and their categories. The analysis also embraced the existing security concerns faced by researchers and their imposed methodologies.
The Second  research article suggested "The mechanism for Predictive Load Control in the Implementation Framework through Genetic Intelligence" authored by   T.Pushpalatha , S.Nagaprasad.  Cloud Storage is a pay-per-use range of resources. The consumer wants to ensure that all requirements met in a limited time for optimal performance in cloud applications that are every day. Load balancing is also crucial, and one of the essential cloud computing issues. It is also called the NP-full load balancing problem since load balancing is harder with increasing demand. This paper provides a genetic algorithm (GA) framework for cloud load. Depending on population initialization duration, the urgent need for the proposal considered. The idea behind the emphasis is to think about the present world. Real-World Scenario structures have other targets that our algorithms can combine. Cloud Analyst models the suggested method. A load-balancing algorithm based on the forecasts of the end -to - end Cicada method given in this paper. The result indicates the possibility of offering a quantitative workload balancing approach that can help manage workloads through the usage of computer resources. The next generation of cloud computing would make the network scalable and use available resources effectively.   This article introduces a new approach to genetic algorithm (GA) power loads. When trying to reduce the complexity of a particular task, the algorithm handles the cloud computing fee. A software analyst model evaluated the proposed method of load balancing. Results from simulations for a standard sample program show that the suggested algorithms outperform current methods like FCFS, Round Robbing (RR), and local search algorithms Stochastic Hill Climbing (SHC).
The Third  research article entitled "Exploring the adoption of the Artificial Intelligence in the Public Sector" written by Vasileios Yfantis, Klimis Ntalianis. In this paper, the evolution of artificial intelligence boosts its usage in the private sector was discussed. However, the public sector seems to lag behind. There are specific reasons which prevent the civil servants and the citizens from using this innovative technology. This paper first identifies the advantages and potential challenges for the implementation of artificial intelligence in the public sector to prove its benefits. Afterward, a gamification framework called Octalysis is suggested as a technique to affect the intent of the stakeholders to use the artificial technology. Octalysis consists of 8 core drives that describe the types of motivations and the game elements that the ideal gamified system should have. Finally, the Octalysis model is applied to an existing chatbot of the public sector which is used to offer information about the public administration of Dubai. The application of Octalysis results in the rating of the information system regarding its potentiality of becoming a gamified system. Finally, several game elements are suggested to improve the overall score of the system and help the users to adopt successfully the artificial technology. The practical value of this paper lies in the fact that it suggests gamification and Octalysisas a useful tool for decision-makers that aim to adopt this technology in public organizations. Games could be the next big thing in both entertaining and helping the public sector to use new technologies. Unless the public administration adopts this exciting concept then the citizens will lose the opportunity to enjoy all the benefits that AI will offer for the digital world.
Fourth research article of this volume was authored by  Bhavna Dwivedi  entitled "Scanning the Database with The XSS Detection Using the Fitness Algorithm".  In this paper, we provide an overview of the tool used in XSS detection. This tool helps us to detect the XSS attacker. XSS is the malware that allows the attacker to attack in any web-application and stolen the client data from the server, which the client or customer is storage when even the fill form in that web application. We analyze a new and efficient algorithm that helps us to secure the database for the server-side. The Genetic Fitness Algorithm is used to secure the database for the server-side, there are many algorithms like multi-path, crossover, which is used to detect the XSS attacker, but this algorithm is not accurate and satisfied the database security. We will analyze the genetic fitness algorithm and have many properties to achieve security for the database. It is complicated for which it is difficult for any attackers to break the security and steal the data from the server site.
Finally, the last or the fifth research article of this volume was entitled "A Study on Biomedical Engineering in Healthcare" authored by Ayushi and Somesh. In this paper, they discussed various introductory terms related to biomedical engineering and the health care industry, which are amalgamated together. The paper further discusses the pros and cons of biomedical engineering in the health care industry. This paper mainly focuses on some of the latest medical tools, instruments and technologies like biosensors, biomedical signal processing, biomedical imaging and image processing, bioinformatics and computational biology, health informatics, biomechanics, bio robotics, diagnostic, cardiopulmonary systems engineering, and therapeutic systems, neural engineering, rehabilitation engineering, variable and implantable technologies, micro and nanotechnologies, tissue engineering and regenerative medicine, biomedical engineering in the education industry and society. A case study has also been included to support the understanding of the above technologies viz. a case study on image-guided interventions. The discussion has been concluded with the observation that biomedical engineering can be deeply integrated with healthcare, and various devices and instruments can be designed to cure various diseases.
Publisher SR Informatics, New Delhi, India
Date 2020-07-11
Type info:eu-repo/semantics/article
Peer-reviewed Article
Format application/pdf
Identifier http://www.mlnce.net/index.php/Home/article/view/133
Source International Journal of Machine Learning and Networked Collaborative Engineering; Vol. 3 No. 04 (2019): Volume No 03 Issue No 04; I-XIII
Language eng
Relation http://www.mlnce.net/index.php/Home/article/view/133/74
Rights Copyright (c) 2020 International Journal of Machine Learning and Networked Collaborative Engineering

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