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Journal Cover   ADCAIJ : Advances in Distributed Computing and Artificial Intelligence Journal
  [7 followers]  Follow
  This is an Open Access Journal Open Access journal
   ISSN (Print) 2255-2863
   Published by Universidad de Salamanca Homepage  [3 journals]
  • Index Vol. 3 num. 4

    • PubDate: 2015-10-06
      Issue No: Vol. 3 (2015)
  • Achievement Emotions and Peer Acceptance Get Together in Game Design at

    • Authors: Margherita BRONDINO, Gabriella DODERO, Rosella GENNARI, Alessandra MELONIO, Daniela RACCANELLO, Santina TORELLO
      Abstract: This paper presents a game design experience in primary schools, with children creating game design ideas and prototypes. Children were organized in cooperative groups. Game design tasks were organized following gamification principles, with ad-hoc gamified material. Cooperative learning and gamification served to elicit emotions and social inclusion. This paper measures them as follows. It operationalizes social inclusion with peer acceptance in three different social contexts, measured before and after the game design activity. It tracks achievement emotions experienced during game design at school. Then the paper examines the relationships between achievement emotions and peer acceptance. In this manner, it tackles an open problem in the literature concerning the links between emotions and social well-being in a game design experience. Path analyses indicate that, respectively for received choices and mutual friendships, positive emotions played a significant role in improving children’s social relations, and negative emotions were associated with a significant deterioration of social relations, but only for the extra-school leisure context. The paper concludes assessing the study limits and results in relation to game design with and for children.
      PubDate: 2015-10-05
      Issue No: Vol. 3 (2015)
  • On the Use of Compact Approaches in Evolution Strategies

    • Authors: Anderson SERGIO, Sidartha CARVALHO, Marco REGO
      Abstract: Compact evolutionary algorithms have proven to be an efficient alternative for solving optimization problems in computing environments with low processing power. In this kind of solution, a probability distribution simulates the behavior of a population, thus looking for memory savings. Several compact algorithms have been proposed, including the compact genetic algorithm and compact differential evolution. This work aims to investigate the use of compact approaches in other important evolutionary algorithms: evolution strategies. This paper proposes two different approaches for compact versions of evolution strategies. Experiments were performed and the results analyzed. The results showed that, depending on the nature of problem, the use of the compact version of Evolution Strategies can be rewarding.
      PubDate: 2015-10-05
      Issue No: Vol. 3 (2015)
  • Research Supervision Management Via A Multi-Agent Framework

    • Authors: Omar JASSIM, Moamin MAHMOUD, Mohd Sharifuddin AHMAD
      Abstract: In this paper, we propose an agent-based framework to enhance, control and manage the research supervision process. The proposed framework consists of three phases which are Research Development Activities, Performance and Completion Measurement, and Tracking Activities. The Research Development Activities phase proposes a number of activities to develop a research. Performance and Completion Measurement phase works on measuring a student performance and expected completion date. The Tracking Activities phase presents the proposed activities to track and trigger a student’s tasks. Four actors constitute the proposed framework which are, a supervisor, a student, a system administrator and a software agent. Each actor has a role and is authorized to perform specific functions. We discuss the components of the framework as possible implementation for a general application of research supervision management.
      PubDate: 2015-10-05
      Issue No: Vol. 3 (2015)
  • Reducing stress and fuel consumption providing road information

    • Abstract: In this paper, we propose a solution to reduce the stress level of the driver, minimize fuel consumption and improve safety. The system analyzes the driving style and the driver’s workload during the trip while driving. If it discovers an area where the stress increases and the driving style is not appropriate from the point of view of energy efficiency and safety for a particular driver, the location of this area is saved in a shared database. On the other hand, the implemented solution warns a particular user when approaching a region where the driving is difficult (high fuel consumption and stress) using the shared database based on previous recorded knowledge of similar drivers in that area. In this case, the proposal provides an optimal deceleration profile if the vehicle speed is not adequate. Therefore, he or she may adjust the vehicle speed with both a positive impact on the driver workload and fuel consumption. The Data Envelopment Analysis algorithm is used to estimate the efficiency of driving and the driver’s workload in in each area. We employ this method because there is no preconceived form on the data in order to calculate the efficiency and stress level. A validation experiment has been conducted using both a driving simulator and a real environment with 12 participants who made 168 driving tests. The system reduced the slowdowns (38%), heart rate (4.70%), and fuel consumption (12.41%) in the real environment. The proposed solution is implemented on Android mobile devices and does not require the installation of infrastructure on the road. It can be installed on any model of vehicle.
      PubDate: 2015-10-05
      Issue No: Vol. 3 (2015)
  • ALTAIR: Supervised Methodology to Obtain Retinal Vessels Caliber

    • Abstract: A back of the eye examination allows performing a noninvasive evaluation of the retinal microcirculation, as well as of the vascular damage induced by multiple cardiovascular risk factors. The objective of this work is to study the existing needs to lead to the development and validation (reliability and validity) of a methodology able to extract all the information from the images of the back of the eye to solve the studied needs. Its development will subsequently allow analyzing its utility in various clinical environments. Currently there are different works that evaluate the thickness of the retinal veins and arteries, but they require either full intervention by an observer or no intervention at all, so when facing incorrect analysis (none of them achieves a 100 % accuracy in automatic analysis) erroneous results can be a serious problem when drawing conclusions. The proposed solution refers to the second group (automatic), but providing a supervisor the possibility to interfere with the analysis when any kind of error is produced, which ideally will not happen many times. Thanks to this the possible subjectivity that can be introduced by the supervisor does not affect the final result of the analysis.
      PubDate: 2015-10-05
      Issue No: Vol. 3 (2015)
  • The Effect of Training Data Selection on Face Recognition in Surveillance

    • Authors: Jamal Ahmad DARGHAM, Ali CHEKIMA, Ervin Gubin MOUNG, Sigeru OMATU
      Abstract: Face recognition is an important biometric method because of its potential applications in many fields, such as access control and surveillance. In surveillance applications, the distance between the subject and the camera is changing. Thus, in this paper, the effect of the distance between the subject and the camera, distance class, the effect of the number of images per class, and also the effect of session used to acquire the images have been investigated. Three sessions are used to acquire the images in the database. The images in each session were equally divided into three distance classes: CLOSE, MEDIUM, and FAR, according to the distance of the subject from the camera. It was found that using images from the MEDIUM class for training gives better performance than using either the FAR or the CLOSE class. In addition, it was also found that using one image from each class for training gives the same recognition performance as using three images from the MEDIUM class for training. It was also found that as the number of images per class increases, the recognition performance also increases. Lastly, it was found that by using one image per class from all the available database sessions gives the best recognition performance.
      PubDate: 2015-10-05
      Issue No: Vol. 3 (2015)
  • Linguistic Models at the Crossroads of Agents, Learning and Formal

    • Abstract: This paper aims at reviewing the most relevant linguistic applications developed in the intersection between three different fields: machine learning, formal language theory and agent technologies. On the one hand, we present some of the main linguistic contributions of the intersection between machine learning and formal languages, which constitutes a well-established research area known as Grammatical Inference. On the other hand, we present an overview of the main linguistic applications of models developed in the intersection between agent technologies and formal languages, such as colonies, grammar systems and eco-grammar systems. Our goal is to show how interdisciplinary research between these three fields can contribute to better understand how natural language is acquired and processed.
      PubDate: 2015-10-05
      Issue No: Vol. 3 (2015)
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