Sharif Digital Repository

Purpose: The purpose of this paper is to study brain drain as a social problem and elaborate a five-dimensional social justice model as the main cause of brain drain. The paper explores the effects of distributional justice, emotional justice, procedural justice, transactional justice, and informational justice on brain drain intention. Design/methodology/approach: The method of research is survey method. This research is functional in terms of target and is descriptive. Moreover, the research is a field study from the information gathering perspective; and from the aspect of relationship between variables, it has casual type. Findings: The results of this study demonstrate that justice is a... 

The authors consider the Multi-Skilled Project Scheduling Problem (MSPSP) as a version of the Multi-mode Resource-Constrained Project Scheduling Problem (MRCPSP), which extends the well-known NP-hard Resource-Constrained Project Scheduling Problem (RCPSP). In the MSPSP, it is made up of activities, which require specific skills to be done. Moreover, resources are staff members who master fixed skill(s). Thus, each resource requirement of an activity corresponds to the number of persons doing the corresponding skill that must be assigned to the activity during its whole processing time. The authors focus on taking into account the setup times when performing work, depending on the appointment... 

Why trade liberalizations increase the skill premium? To explain this empirical evidence that is in contrast with the conventional theory of Heckscher-Ohlin, I build up a general equilibrium micro-founded heterogeneous-firm model of international trade where firms make decisions on their division of labor, and firms’ skill-intensities are endogenously determined. I show why the exporters are generally more productive and skill intensive and how trade cost reductions induce more productive firms to choose a higher degree of labor specialization, become more skill intensive and start to export. I further demonstrate how such internal horizontal organizational changes, after a trade cost... 

In this paper, we propose a new mathematical programming model to tackle the multi-skilled project scheduling problem. Considering the effect of learning and forgetting on the human skills, an exponential learning function has been developed by assuming the efficiency of employees performing activities to be dynamic. Taking the nonlinearity of the function into account, we use separable programming to acquire an appropriate linear approximation for it. Moreover, the proposed model allows us to relax some of the binary variables linearly without any modifications. At the end, the final model is tested with some instances and is solved by CPLEX in order to confirm the implemented... 

Satisfying the clients' uncompromising priorities is a challenge for decision makers of organizations that face multiple projects. This paper considers an organization with a multi-skilled workforce working on several predetermined projects under time-of-use energy tariffs where distributed load energy usage is the primary concern of energy suppliers. This paper also considers different time-of-use energy tariffs, which are among the most common strategies to reach a more balanced energy utilization. The problem is stated as a bi-objective mixed-integer programming model containing two conflicting objectives; to minimize the total cost of the multi-skilled workforce and obtain a sustainable... 

Satisfying the clients' uncompromising priorities is a challenge for decision makers of organizations that face multiple projects. This paper considers an organization with a multi-skilled workforce working on several predetermined projects under time-of-use energy tariffs where distributed load energy usage is the primary concern of energy suppliers. This paper also considers different time-of-use energy tariffs, which are among the most common strategies to reach a more balanced energy utilization. The problem is stated as a bi-objective mixed-integer programming model containing two conflicting objectives; to minimize the total cost of the multi-skilled workforce and obtain a sustainable... 

Music-based therapy is an appropriate tool to facilitate multisystem development in children with autism. The focus of this study is to implement a systematic and hierarchical music-based scenario in order to teach the fundamentals of music to children with autism through a social robot. To this end, we have programmed a NAO robot to play the xylophone and the drum. After running our designed robot-assisted clinical interventions on three high-functioning and one low functioning autistic children, fairly promising results have been observed. We indicated that the high-functioning participants have learned how to play the musical notes, short sentences, and simple rhythms. Moreover, the... 

A new multi-skill multi-mode resource constrained project scheduling problem with three objectives is studied in this paper. The objectives are: (1) minimizing project's makespan, (2) minimizing total cost of allocating workers to skills, and (3) maximizing total quality of processing activities. A meta-heuristic algorithm called multi-objective invasive weeds optimization algorithm (MOIWO) with a new chromosome structure guaranteeing feasibility of solutions is developed to solve the proposed problem. Two other meta-heuristic algorithms called non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization algorithm (MOPSO) are used to validate the... 

Many chemical production systems encounter with a functionally flexible workplace which need multi-skilled workers. This research integrates the multi-skilled project scheduling problem with the resource investment problem which aims to obtain concurrent optimal policy of project scheduling and skills’ recruitment. The objective of the proposed model is minimization of total recruitment cost for different levels of the skills. An integer programming formulation is developed for the problem, and it is validated through solving several small scale instances using the GAMS software. To tackle real-life problem scales, a genetic-based and a particle-swarm-based algorithm with calibrated... 

This paper reports on a new method of automatic design. It is a simulation of "human intentional activity," appearing in management, business, various designs and physical work. It is achieved by repetitive hierarchical decomposition of human concepts using (mainly) natural language expressions. Three typical ways (skill, rule and knowledge based) to create the hierarchical decomposition have been implemented and evaluated quantitatively as a CASE tool. The rule-level operation achieves nearly 100% automatic detailing  

This article endeavors to present the impact of conducting robot-assisted music-based intervention sessions for children with low-functioning (LF) autism. To this end, a drum/xylophone playing robot is used to teach basic concepts of how to play the instruments to four participants with LF autism during nine educational sessions. The main findings of this study are compared to similar studies conducted with children with high-functioning autism. Our main findings indicated that the stereotyped behaviors of all the subjects decreased during the course of the program with an approximate large Cohen’s d effect size. Moreover, the children showed some improvement in imitation, joint attention,... 

Virtual Reality (VR) technology is a growing technology that has been used in various fields of psychology, education, and therapy. One group of potential users of VR are children with autism who need education and have poor social interactions; this technology could help them improve their social skills through real-world simulation. In this study, we evaluated the feasibility of conducting virtual music education programs with automatic assessment system for children with autism at treatment/research centers without the need to purchase a robot, resulting in the possibility of offering schedules on a larger scale and at a lower cost. Intervention sessions were conducted for five children... 

Recent researches on automatic skill acquisition in reinforcement learning have focused on subgoal discovery methods. Among them, algorithms based on graph partitioning have achieved higher performance. In this paper, we propose a new automatic skill acquisition framework based on graph partitioning approach. The main steps of this framework are identifying subgoals and discovering useful skills. We propose two subgoal discovery algorithms, which use spectral analysis on the transition graph of the learning agent. The first proposed algorithm, incorporates k′-means algorithm with spectral clustering. In the second algorithm, eigenvector centrality measure is utilized and options are... 

Hierarchical reinforcement learning facilitates learning in large and complex domains by exploiting subtasks and creating hierarchical structures using these subtasks. Subtasks are usually defined through finding subgoals of the problem. Providing mechanisms for autonomous subgoal discovery and skill acquisition is a challenging issue in reinforcement learning. Among the proposed algorithms, a few of them are successful both in performance and also efficiency in terms of the running time of the algorithm. In this paper, we study four methods for subgoal discovery which are based on graph partitioning. The idea behind the methods proposed in this paper is that if we partition the transition... 

This paper considers a preemptive multi-skilled resource constrained project scheduling problem in a just-in-time environment where each activity has an interval due date to be completed. In this problem setting, resuming a preempted activity requires an extra setup cost, while each time unit violation from the given due date incurs earliness or tardiness penalty. Also, processing cost of each skill to execute any activity depends on the assigned staff member to accomplish the skill. The objective function of the model aims to minimize the total cost of allocating staff to skills, earliness-tardiness penalties and preemption costs. Two integer formulations are proposed for the model which...