Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication. Second, we use a variant of the K-Means Density clustering algorithm for selection of cluster heads. Optimal cluster heads enhance the cluster lifetime and reduce the routing overhead. The proposed model outperforms the state of the art artificial intelligence techniques such as Ant Colony Optimization-based clustering algorithm and Grey Wolf Optimization-based clustering algorithm. The performance of the proposed algorithm is evaluated in term of number of clusters, cluster building time, cluster lifetime and energy consumption.

The phenomenon of the use of a mobile learning (m-Learning) platform in educational institutions is slowly gaining momentum. However, the enthusiasm with which mobile phones have been welcomed into every aspect of our lives is not yet apparent in the educational sector. To understand the reason, it is important to understand user expectations of the system. This article documents a systematic review of existing studies to find the success factors for effective m-Learning. Our systematic review collates results from 30 studies conducted in 17 countries, where 13 critical success factors were found to strongly impact m-Learning implementation. Using these results within the framework of the diffusion of innovation model for innovation adoption and the critical success factors together help us see what aspects of the innovation decision process are the likely causes of the reduced take-up of m-Learning by university students.

a b s t r a c tUser satisfaction has always been a major factor in the success of software, regardless of whether it is closed proprietary or open source software (OSS). In open source projects, usability aspects cannot be improved unless there are ways to test and measure them. Hence, the increasing popularity of open source projects among novice and non-technical users necessitates a usability evaluation methodology. Consequently, this paper presents a usability maturity model specifically aimed at usability-related issues for open source projects. In particular, the model examines the degree of coordination between open source projects and their usability aspects. The measuring instrument of the model contains factors that have been selected from four of our empirical studies, which examine the perspectives of OSS users, developers, contributors and the industry. In addition to presenting the usability maturity model, this paper discusses assessment questionnaires, a rating methodology and two case studies.

Abstract-According to psychology, not everybody can excel at all kinds of tasks. Thus, chances of a successful outcome of software development increase if people with particular personality traits are assigned to their preferred tasks in the project. Likewise, software development depends significantly on how software practitioners perform their tasks. This empirical study surveys 100 Cuban software developers, both students and professors of the University of Informatics Sciences in Havana, Cuba. This work aims to find possible patterns that link personality traits to role preferences in a software life cycle. Among the various roles, system analyst, software designer, and programmer are found to be the most preferred among the participants. In contrast, tester and maintainer happen to be the least popular roles among software engineers.Index Terms-Human factors in software engineering, Software life cycle, Human aspects of software development, Software psychology I. INTRODUCTION AND BACKGROUND Software engineering has been one of the most prominent professions over the last 20 years, and it is projected to evolve even further. Software engineering comprises stages in distinct areas, such as analysis, design, programming, testing, and maintenance. Today, specialties within software engineering are as diverse as in any other profession. Additionally, software engineers need to communicate more effectively with users and team members, thus the people dimension of software engineering is as important as technical expertise.Software project managers have always faced the problem of assigning the tasks to the right people within a team in such a fashion that increases the chance of successful project completion [1]. Different ideas have been tried to use diverse ways to maximize performance [2] and make choices in the software engineering process [3]. Those ideas involve: motivation (software engineers tend to perform better if they are motivated to do specific tasks), the environment, and personality type, or a combination of these factors. Motivation and the environment are known to influence task performance. Motivation is generally a powerful element in the performance of task goals, especially in the IT field [4], [5]; however, motivation is often insufficient for influencing performance of goals on its own. Similarly, environmental factors cannot independently generate the performance of tasks. Hence, there are multiple factors involved in the performances of software engineers [6]. This study specifically investigates the role of individual preferences in software projects, while neglecting the elements of motivation and environment, which have been the focus of most scholarly research on this topic. Feldt et al. [7] also state that environmental factors alone cannot improve task performance. Thus this work exclusively investigates the role of individual preferences in software projects, focusing explicitly on how personality types affect preferences for specific software roles.Several studies investigate th...

The Myers-Briggs Type Indicator (MBTI) has been applied to several studies that explore various dimensions of human factors in software engineering. Accordingly, this work reviews the results of these studies to explore existing trends. In order to attain a greater understanding of human resources in the software industry, we have reviewed sixteen studies that had been performed between 1985 and 2011. This review concludes that the changes in the complexity of software processes and products have created new roles and demanded new skills for software engineers.