IoT Assistive Technology for People with Disabilities
Soulease: A Mind-Refreshing Application for Mental Well-Being
AI-Powered Weather System with Disaster Prediction
AI Driven Animal Farming and Livestock Management System
Advances in AI for Automatic Sign Language Recognition: A Comparative Study of Machine Learning Approaches
Design and Evaluation of Parallel Processing Techniques for 3D Liver Segmentation and Volume Rendering
Ensuring Software Quality in Engineering Environments
New 3D Face Matching Technique for an Automatic 3D Model Based Face Recognition System
Algorithmic Cost Modeling: Statistical Software Engineering Approach
Prevention of DDoS and SQL Injection Attack By Prepared Statement and IP Blocking
In business, stress can account for a surprising energy expense, leaving employees drained and unproductive. Stress can also have detrimental effects to teamwork further hampering their ability to function. The objective of this paper is to provide a model for stress that may be used to analyze stress in practically any environment or scenario. This should subsequently provide clues, if not the means, to effectively combat stress, both in oneself and in others. This article will present a comparison of the traditional and stable models for stress and provide some solutions for managers to manage or mitigate stress of employee and employer alike. The information presented here will benefit managers by helping them reduce or manage the stress of his subordinates, thus improving their performance and productivity. As an added benefit, a less stressful working environment, thus created, will improve the attitude of all involved, again boosting productivity and possibly attracting new talent.
Software metric is one of the very important elements to predict the quality. The relationship of Number of Children metric with cyclomatic complexity is a significant matter. Here in this paper the relationship of NOC (Number of Children) and MVG (McCabe's Cyclomatic Complexity) have been explained using three real projects developed in JAVA language. The authors have also empirically computed NOC and MVG metrics of these projects and found the correlation between these two. It is found that on increasing NOC, MVG also increases in polynomial form which is showing the directly proportional relationship. This paper is providing an optimal value of NOC up to that software will be quality software.
Among the evolving researches on data mining, one such field of interests is on the education. This emerging field of research in education is called Educational Data Mining, which means the data related to the field of education. One of the main concerns in educational field is the academic scores of a student, which helps in the growth of the student as well as the Institution. To predict a student's performance is a very important one in educational field. To maintain the scores and in order to increase the scores of a student the prediction of one's performance is necessary. To achieve this objective of predicting, the performance is fulfilled by the usage of data mining. A high prediction accuracy of the student's performance is more helpful to identify the slow performance students at the beginning of the learning process. Data mining techniques are used to analyze the models or patterns of data, and it is also helpful in the decision-making [19]. Boosting technique [21][22] is one of the most popular techniques for constructing classifier by ensemble to improve the classification accuracy. Adaptive Boosting (AdaBoost) is a generation of Boosting algorithm. It is applicable for the binary classification and not used in multiclass classification directly. Therefore, an extension for the AdaBoost is proposed which is SAMME boosting technique for the multiclass classification without reducing it to a set of sub-binary classification. In this paper, the authors have evaluated student's performance prediction system to predict the performance of the students based on their data with high prediction accuracy and provide help to the slow learning students by using optimization rules.
Recently many large scale computer systems are built in order to meet the high storage and processing demands of compute and data-intensive applications. MapReduce is one of the most popular programming models designed to support the development of such applications. MapReduce is a software framework for easily writing applications which process vast amount of data in-parallel, by using multiple CPUs on various machines, in a reliable, and fault tolerant manner. The various input and output parameters, that are part of this model have been identified. The proposed architecture is implemented in open source Java. The Map Reduce programming model is easy to use, even for programmers without experience with parallel and distributed systems, since it hides the details of parallelization, faulttolerance, locality optimization, and load balancing. It has a large variety of problems which are easily expressible as MapReduce computations. Finally, an implementation of MapReduce that scales to large clusters of machines comprising thousands of machines has been developed. The implementation makes efficient use of these machine resources and therefore is suitable for use on many of the large computational problems encountered.
Research on intelligence Intrusion Detection Prevention Systems (IDPSs) found in the literature survey are effectively used to identify and detect only known Network attacks and are unable to evaluate the risk of Network service. In order to overcome limitations of the existing Intrusion Detection System (IDS), a new active defense system with Intelligence principles named IIDPS (Intelligence Intrusion Detecton Prevention System) for detecting and preventing unknown malware has been proposed in this article. This system fulfills the objectives of security like authenticity, confidentiality, integrity, availability, and non-repudiation.
Reduction of cost and time is one the major concerns in software development. Therefore, developing scalable architectures, which can efficiently accommodate evolving requirements to adapt to new environments, is worth future research. Current development approaches do not guarantee fully scalable architectures, due to their inability to detect and identify where and how new layers are to be added or incorporated to, or current layers are to be removed from the architecture being developed. In addition, there is a conceived shortage of the architectural points that will be used to connect/remove other architectures and applications. Consequently, these architectures might encounter or face a total collapse or a considerable increase in cost and time, when new changes are to be incurred to it. When businesses experience substantial increments in their services' demands, their main concern is their application architecture's ability to scale over time to assure a proper handling of these loads. The architecture is required to efficiently scale, and adapt in such manner that it will fit in both constrained and unconstrained environments, yet still being able to take full advantage of the available resources to improve its performance. There are multiple stages in the lifecycle of a software product. The development starts from the requirements analysis stage, moving on to the design, then coding, testing and then the final delivery, which may involve deployment and configuration of the means to deliver the software to its users, in the form of a final software system. This and the subsequent columns look at the definition of scalability from the perspective of software architectures.
