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Orientation is increasingly in demand, especially today in the age of digital and recent technologies, with the disappearance of some jobs and the emergence of others, and with the variety of choices in front of the students who have led professionals to seek a new method and digital solution to help them solve these issues and achieve their personal and professional success. There are a lot of institutions and associations that are organized orientation sessions for students and try to fill the gaps in that area, but it is always a poor fit in the face of a lot of students. And to make an effective decision related to guidance, we need to consider several factors such as grades, preferences, interests, and personality characteristics... which gives a sharp vision of the student and helps to know which category he belongs to. The purpose of this paper is to present a review of studies on distinctive approaches used in the orientation field such as the K-Nearest-Neighbor Method (KNN), Naïve Bayes, Fuzzy logic, Fuzzy Analytic Hierarchy Process (FAHP), and the Internet of things (IoT) in order to discover the best approach which helps students to pick and succeed in their orientation. [ABSTRACT FROM AUTHOR]

Waste production is constantly increasing worldwide and constitutes a problem that is expected to deteriorate in the future. In parallel, ensuring access to affordable and sustainable energy for all is crucial considering current environmental, economic, and social concerns. Waste-to-Energy (WtE) is an effective solution to address both issues, therefore it requires intense scientific attention. WtE management is characterized by different technologies, refers to various waste types, and needs multidisciplinary decision support. Thus, it is critical to include multiple criteria in the decision making process i.e. economic, technological, environmental, social, and political. These reflect different objectives that often come into conflict with each other. Multi-Criteria Decision Analysis (MCDA) is a tool that can effectively contribute to answer that challenge. The paper reviews the way, the scope, and the multi-criteria techniques that have been applied up-to-now to WtE Management Strategies (WtEMSs) in the globe. A critical review of 153 published papers addresses specific issues and questions. Asian and European countries are producing the most MCDAs studies on WtEMS. An increasing trend of papers commences from the year 2007. Results depict that Analytical Hierarchy Process is the most common approach, adopted in 62 real-life cases. Incineration and anaerobic digestion are mostly studied in MCDA frameworks. Emphasis is given on critical analysis and lessons that can be learnt from the available literature. Policy makers are motivated to: (i) adopt MCDA to holistically make WtEMSs decisions, (ii) adapt to local characteristics, (iii) encounter logistic problems, and (iv) efficiently promote implementation in real-life cases. Image 1 • An increasing trend of published papers commences from the year 2007. • AHP is the most common approach, adopted in 62 real life cases. • Incineration and anaerobic digestion are mostly studied in MCDA frameworks. • Socio-political criteria significantly included in MCDA studies after 2013. • MCDA principles are vital for the success of a WtE management strategy. [ABSTRACT FROM AUTHOR]

Software requirements engineering is a critical discipline in the software development life cycle. The major problem in software development is the selection and prioritization of the requirements in order to develop a system of high quality. This research analyzes the issues associated with existing software requirement prioritization techniques. One of the major issues in software requirement prioritization is that the existing techniques handle only toy projects or software projects with very few requirements. The current techniques are not suitable for the prioritization of a large number of requirements in projects where requirements may grow to the hundreds or even thousands. The research paper proposes an expert system, called the Priority Handler (PHandler), for requirement prioritization. PHandler is based on the value-based intelligent requirement prioritization technique, neural network and analytical hierarchical process in order to make the requirement prioritization process scalable. The back-propagation neural network is used to predict the value of a requirement in order to reduce the extent of expert biases and make the PHandler efficient. Moreover, the analytical hierarchy process is applied on prioritized groups of requirements in order to enhance the scalability of the requirement prioritization process. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to model the multi-criteria decision problem of identifying the most suitable facility locations for biogas plants under an integrated decision support methodology. Here the Geographical Information System (GIS) is used for measuring the attributes of the alternatives according to a given set of criteria. Measurements are taken in interval form, expressing the natural imprecision of common data, and the Fuzzy Weighted Overlap Dominance (FWOD) procedure is applied for aggregating and exploiting this kind of data, obtaining suitability degrees for every alternative. The estimation of criteria weights, which is necessary for applying the FWOD procedure, is done by means of the Analytical Hierarchy Process (AHP), used jointly with the LLSM-AHP for the estimation of upper and lower bounds for the weights. Then, a combined AHP-FWOD methodology allows identifying the more suitable sites for building biogas plants. We show that the FWOD relevance-ranking procedure can also be successfully applied over the outcomes of different decision makers, in case a unique social solution is required to exist. The proposed methodology can be used under an integrated decision support frame for identifying the most suitable locations for biogas facilities, taking into account the most relevant criteria for the social, economic and political dimensions. [ABSTRACT FROM AUTHOR]

Abstract: Currently, around 90% of Malaysia's electricity generation depends on fossil fuels. This reliance, in a long run, is not a secure option. However, renewable energy sources can contribute to a sustainable electricity generation system; but diversifying fuel supply chain is a complex process. Therefore, the aim of this paper is two folds. Firstly, various renewable resources potential are reviewed, and secondly an assessment model is developed for prioritizing renewable options. Four major resources, hydropower, solar, wind, biomass (including biogas and municipal solid waste) are considered. Their electricity generation potential, along with any likely shortcoming is also discussed. Moreover, using a multi-perspective approach based on analytic hierarchy process (AHP), an assessment model is developed. AHP model employs four main criteria, technical, economical, social and environmental aspects, and twelve sub-criteria. From the review it was found that renewable resources seem to have a sufficient potential to develop a sustainable electricity system. Furthermore, AHP model prioritize those resources, revealing that solar is the most favorable resource followed by biomass. Hydropower and wind however, are ranked third and fourth, respectively. The model also shows that each resource is inclined towards a particular criterion; solar towards economical, biomass towards social, hydropower towards technical, and wind towards environmental aspect. Besides reporting AHP model for the first time in Malaysian context, the assessment performed in this study, can serve decision makers to formulate long-term energy policy aiming for sustainability. [Copyright &y& Elsevier]

This paper proposes a new approach for tackling the uncertainty and imprecision of the service evaluation process. Identifying suitable service offers, evaluating the offers and choosing the best alternatives are activities that set the scene for the consequent stages in negotiations and influence in a unique manner the following deliberations. The pre-negotiation problem in negotiations over services is regarded as decision-making under uncertainty, based on multiple criteria of quantitative and qualitative nature, where the imprecise decision-maker’s judgements are represented as fuzzy numbers. A new fuzzy modification of the analytic hierarchy process is applied as an evaluation technique. The proposed fuzzy prioritisation method uses fuzzy pairwise comparison judgements rather than exact numerical values of the comparison ratios and transforms the initial fuzzy prioritisation problem into a non-linear program. Unlike the known fuzzy prioritisation techniques, the proposed method derives crisp weights from consistent and inconsistent fuzzy comparison matrices, which eliminates the need of additional aggregation and ranking procedures. A detailed numerical example, illustrating the application of our approach to service evaluation is given. [Copyright &y& Elsevier]