J. Jayashree

Bio: J. Jayashree is an academic researcher from VIT University. The author has contributed to research in topics: Cloud computing & Information technology management. The author has an hindex of 1, co-authored 5 publications receiving 3 citations.

Analysis and Issues in Cloud Operating System

Abstract: The conventional operating system usually works on a particular workstation but the same when implemented on a distributed environment like cloud faces many problems. This paper analyzes and explains how does the cloud operating system works in order to resolve these problems. It also differentiates the working mechanism of both based on basic storage management service provided by the cloud. At the end it provides the issues and the future challenges faced in the cloud operating system.

Supervised Learning Method and Neural Network Algorithm for the Analysis of Diabetic Mellius and its Comparitive Analysis

Abstract: Diabetes is the key critical issue needs to be concerned for various problems in our body. Increase in glucose and fructose content in our body results in diabetes mellitus. When a body generates higher insulin level than the required, it results in increased urination and excessive thirstiness which in turn results in kidney failure and other cardio-related issues. Many research agencies invested their funds on defining the predictive methodology and finding the root cause of those results in mellitus. Mellitus results in the highest mortality rate compared to any other disease reported by the health organizations across the globe. In this, the predictive methodologies, various classification techniques are discussed, and the results are analyzed. The classification methodology could be on medications, food habits, personal behaviors, age factors and so on. The datasets are processed and analyzed with the neural network algorithms, and the results are compared with one another. The datasets are taken from the National Family Health Survey results published during the period of 2016–2017. The result implies that men between ages 15–49 among 1 billion people have reported with diabetes mellitus. Diagnose and forecast on this disease are done by recognizing the pattern formation and grouping the similar structures. Various algorithmic techniques like M-layer perceptron, nearest neighbor, vector machines, data regressions, binary regression and their accuracy of forecast, speed and sensitivity are calculated, analyzed and compared to define the accurate prediction methodology over a short span of time. The forecast methodologies are focussed to provide solutions to avoid the intensive care system provided proper medications with a long duration when it is been predicted to be a risk factor. A statistical method of analyzing is performed for the comparative analysis. The learning and training methodologies are discussed in this system. Accuracy, specificity, sensitivity are the key parameters to define the best forecast methodology. Classification on association, regression techniques and neural algorithmic techniques is analyzed and compared to refine the best predictive forecast methodology by processing 30 samples across the states of India with focus on determining the type of mellitus along with the accuracy on definition. The forecast data utilized to define the type of mellitus and the prediction on critical measures over a period of time.

Library Cloud: Concept and Design with Security Features

Abstract: Cloud computing has the potential to change the world we see today, and this has been duly recognised due to the amazing advantages it offers. One of the main advantages it offers is that cloud computing can reduce the wastage of resources and efficient upgrade effectiveness, increasing the proper application of business computer resources or improving computing device’s effectiveness and efficiency of the cloud computing itself can achieve the best applications.Universities and Colleges are the core of innovation through their advanced research and development. Higher education libraries of different size and type all over the world suffer from common problems such as shrinking budgets, accommodating resources within the budgetary constraints, Countering increased scope of interdisciplinary and multidisciplinary nature of subjects, flexibility associated with the e-data, diminished levels of efficiency, and huge cost involved in managing the entire IT infrastructure in the modern day academic libraries. Cloud computing can overcome these problems and transform the library infrastructure through digitization.In the proposed paper, the plan is to design a “Library Cloud” which would be the consortium of many digital libraries of different universities/academic institutions and also discuss the security features required to implement this cloud. This “Library Cloud” would help in saving so many resources of the libraries involved and sharing of knowledge amongst the members of the institutions concerned, which otherwise individually would not be feasible and possible.

Adoption Model of Electronic Human Resource Management (EHRM) Based Cloud Computing System for Healthcare Organizations

Abstract: The main thrust of this study is identifying most influential determinants that are related to managerial decision for adapting E-HRM based cloud computing system for healthcare organization. The aim of the study is to develop E-HRM adoption model based cloud computing for healthcare organizations. The model E-HRM based cloud computing system includes cloud healthcare applications, cloud services, cloud deployment, controls and solutions, and E-HRM. The proposed a conceptual model is an iterative approach and method that can help identify critical factors leading to adopt EHRM and cloud system, and control factors for mitigating EHRM and cloud system issues. There are four stages for EHRM issues based cloud computing such as electronic Human Resource Management activities, the level awareness of EHRM and cloud computing system, IT and cloud computing infrastructure, and management support system and quality for HRM. Futher, the EHRM issues related to control andsolutions methods such as technological, organizational, legal, and environmental dimension. Finally, Cloud computing areincreasingly influencingelectronic human resource management (EHRM) practices for healthcare organizations.

Monitoring of external predisposing factors for Diabetic Foot: A literature review and physicians' perspectives.

Abstract: Background: Diabetic foot is one of the most important complications of diabetes caused by the existence of some destructive factors in different anatomical locations of feet. Management and monitoring of these factors are very important to decrease or avoid ulcerating lesions of the foot. The purpose of this study is to identify and introduce the predisposing factors and anatomical locations associated with these destructive factors. Methods: First, we conducted a comprehensive review of different databases to identify the factors and associated anatomical locations from the previous studies. Then, we designed a questionnaire and invited physicians and specialists to express their perspectives on these factors and locations. The data were analyzed using SPSS version 23. Frequency, percentage, mean and standard deviation of these variables were calculated. Results: Based on the literature review, four factors, including pressure, moisture and sweat, temperature, and acceleration were identified as factors destructive to the tissues of the diabetic foot and worsen ulcers. The view of specialists approved the results of the literature review. Besides, there was an insignificant difference between the results of the literature review and the specialists' view in terms of anatomical locations that need to be continuously monitored. Conclusion: Monitoring the pressure in heel, first metatarsal, and first metatarsal head; moisture and sweat under the fingers, hallux and heels as well as the temperature at the first metatarsal, first metatarsal head, and the third metatarsal head are important in preventing ulceration, destructing the foot tissue, and accelerating the treatment process.

Virtual Memory Management using Memory Ballooning in OpenStack Cloud Platform

Abstract: Management of memory in an efficient manner is one of the very important topics these days in Cloud environment. Optimized memory management techniques play the important role to handle the large amount data and processes in cloud environment. The smart memory management techniques should be integrated in cloud computing to do to memory optimization. The load balancing issues and the problem of latency can be resolved with the memory optimization. The efficiency of data optimization in cloud depends upon the resource allocation based on user demand. This is the key factor of resource optimization. As the allocation of resources are done as per the user demand then in most of the case resources are underutilized and remain idle. It causes the unused resources across the cloud platform. To get rid on this problem there is need to have continues resource monitoring and check system which will monitor the idle resources across the cloud. The various virtual memory optimization techniques are available. The cloud hypervisors uses the different memory optimization techniques which follows different principal. To handle memory optimization. The Ballooning is one of the important memory management technique in which memory of ideal virtual machine is used for the virtual machines which needs more memory to run the application.

Pengaruh Pengingat Pesan Singkat (SMS) Terhadap Kepatuhan Minum Obat Pasien Diabetes Mellitus Tipe 2: Literatur review

Abstract: Introduction : Diabetes mellitus is a chronic disease that can cause serious complications if not managed properly and properly. The best way to control this complication is to follow or adhere to medication. The SMS system can be effective, because it can eliminate time and place constraints and can build good relationships between nurses and clients. Purpose: of this study is to interact with the purpose of a message system reminder application (SMS) on adherence to drug consumption in Type 2 Diabetes Mellitus. Methods: The method used is the electronic data base method, by searching 10 national and international journals through: Proquest, Clinicalkey and Google Scolar, from 2016 - 2021, with the keywords