Sustainability is an important topic for modern college and universities, many of whom are actively promoting sustainable practices and integration of sustainability topics into course curricula. The inclusion of socially-relevant projects and course “themes” has been shown to assist in attracting students to Computer and Information Science, and practical, problem-based applications have also been shown to attract females and underrepresented groups to the discipline. In Computer and Information Science education, most documented approaches attempt to integrate sustainable computing topics either as learning modules, open-ended project topics, or as concentrated courses. This paper describes a lightweight, non-intrusive pedagogical approach to integrating sustainability education in introductory programming courses. By creating introductory programming projects focused on sustainability topics, students are exposed to the general concepts and terminology involved with the important scientific and societal topic. This approach also allows students to see the practical applications of computing in a socially relevant context. Results of a two-year study of this approach have been encouraging, though more work is needed to assess the full impact of this approach and to overcome the limitations of the implementation context.

This paper portrays the demonstrating, and testing of passive suspension control techniques. The control execution of a two-degree of-opportunity quarter car passive suspension frameworks is explored utilizing Matlab/Simulink, display. A classical Proportional Integral and Derivative (PID), Linear Quadratic Control (LQR), and H2 controller design are proposed and compared with soft computing methods, such Fuzzy logic controller (FLC) and Genetic Algorithm (GA) controller. Simulation environment was used for all design methods, investigation of the effects of the control techniques in time-domain design specifications, their comparison and verification of the results obtained. The results are shows the effectiveness of the (GA) controller to satisfied design requirements compared with others methods.

Plenty data are generated each second under different locations and ways. In return, several valuable data are not used due to neglect or a wrong criteria selec-tion, affecting the results. To have the accurate decision the exact information is needed. But, in case of lack of data, an overall vision about all existing findings make a big difference especially in Medicine.
The approach of Systematic Literature Review give the possibility to have this clear vision related to a specific topic, for the right input. We aim to identify all important steps to conduct a high quality of systematic literature review, independently of research domain.
We first explain the reason behind our research and the significance of Systematic Literature Review in research fields, one of the way for minimizing the loss of infor-mation. Since our goal is to have an explicit methodolo-gy, we select several papers mentioning the procedure in different years to have a general view. Subsequently, we explain the approaches used to select the key steps to follow for selected articles.
We settle this study with a complete step resuming all finding key phases. This research highlight also the im-portance of the use of an explicit methodology to vanish any misunderstanding or ignoring basic points to accom-plish a valuable and high quality work.
This paper make a clear complete methodology to fol-low, in any domain and specially medicine, to conduct a best quality of Systematic Literature Review and reach the right gain using best practices.

As per the guidelines issued by NBA (National Board of Accreditation) of All India Council of Technical Education (AICTE) Outcome Based Education is implemented in engineering colleges of India. The outcome based evaluation model measures the performance of UG and PG programs. The performance is based on calculating attainments of Program Educational Objectives (PEOs) and Program Outcomes (PO).In this paper we will discuss the process for the attainments of POs and PEOs for Post Graduate program approved by AICTE, India. The attainments are calculated by applying direct and indirect tools. The attainments summaries are generated Batch wise and a comparison of different Batches were made. The attained PEOs and POs would help in accomplishing Vision and Mission of the department.

Open Source Software (OSS) provide a number of advantages to Higher Learning Institutions (HLIs) in developing countries, such as Tanzania. This is because they are freely available, free to make copies and free to distribute. Through literature reviewed, it has been observed that OSS usage in HLIs in Tanzania is low due to lack of awareness of OSS designed for academic purposes. This paper presents a study on how to implement a reliable and effective web-based application tool for recommendation of OSS for enhancing awareness of HLIs on existing OSS designed for academic purposes. There are three recommendation algorithms that were employed for filtering the OSS in this study: the content-based, collaborative, and demographic filtering. We used various web technologies for the implementation of application functionalities. The result is the reliable and effective web-based application tool that recommends OSS to individuals in HLIs for enhancing their awareness of OSS designed for academic purposes.

Machine Translation (MT) is a programmed conversion in which computer software is utilized to convert manuscripts from one Natural Language (like English) to a different Language (such as Hindi). To process any such conversion, through human or through automatic means, the conversion must be established such that it reinstate the complete sense of a manuscript from its base (source) linguistic into the target language. In this paper, the study of prevailing evaluation systems along with assessing their performance is achieved through the similarity metrics. Moreover, the authors have also presented an improved technique of translation employing features of Natural Language Processing and consequently, to acquire an enhanced and more accurate assessing Machine Translation system, a corpus is selected and the outcomes are compared with the prevailing methods. Besides this, two well-known systems such as Google and Bing decoders are selected to inquire and to assess the study of metrics called similarity metrics through Assessment of Text Essential Characteristics score. This is found to provide more accuracy than prevailing methods. Furthermore, evaluations are tested under various metrics systems like Jaccard similarity metrics, cosine similarity metrics, and sine metrics to deliver enhanced accuracy than prevailing methods.