The heterogeneity in the Spanish educational system has made it essential to develop certain skills to be a model citizenship. One of those is intercultural sensitivity. But before establishing a... Show More

The heterogeneity in the Spanish educational system has made it essential to develop certain skills to be a model citizenship. One of those is intercultural sensitivity. But before establishing a program to develop it, it is crucial to know its level in the students. Conscious of this social reality a research was done to study the level of intercultural sensitivity in students in the level of Secondary Compulsory Education of two schools in the region of Salamanca (Spain). The sample consisted of 220 people from two different schools, one public and one private. One of the main objectives is to see if there are significant differences in the answers given depending on the variables gender, ownership of the school and nationality (differentiating between native and foreign). On a first review, it was discovered, in general, there were not significant differences on the answers depending on type of school, gender or nationality.

The main purpose of this article is to analyze different recommendation systems and examine how they are used within digital environments to establish classifications for books. Following a... Show More

The main purpose of this article is to analyze different recommendation systems and examine how they are used within digital environments to establish classifications for books. Following a bibliographical review of recommendation systems, the performance of a number of book recommendation systems is tested. The systems tested are grouped according to whether recommendations are done by specialists, are based on social networking or use more complex statistical stylometry to help each reader find the reading materials best suited to them. Results indicate that progress in technology implementation is favoring the findability of books by combining the strengths of the various systems. The principal social implication of this research is that recommendation systems enable the reader's optimized use of books, as well as allow the development of content appropriation systems. Concerning to originality and value is important to emphasize there is no previous known work establishing the taxonomy proposed in this paper.

Nowadays, the Internet of things (IoT) is becoming a promising technology which revolutionizes and simplifies our daily life style. It allows interaction and cooperation between a large variety of... Show More

Nowadays, the Internet of things (IoT) is becoming a promising technology which revolutionizes and simplifies our daily life style. It allows interaction and cooperation between a large variety of pervasive objects over wireless and wired connections, in order to achieve specific goals. Moreover, it provides a concise integration of physical world into computer systems through network infrastructure. This paper provides an agent-based architecture for developing IoT systems. The proposed architecture is multi-layer and generic. It encompasses four layers: Physical Component Management, Local Management -Coordination, Global Management-Coordination and Specialized Operative Management Layers. The first one can be seen as a smart layer that ensures connection and communication between things and the system. The second one constitutes the intelligent core of the system which acts locally to ensure coordination and further internal functioning. The third layer ensures coordination between the local system and the externals ones. The last layer supports additional behaviors which are domain dependent. The architecture is illustrated by an IoT system diagnosis.

The concept of humanitarian logistics is evolving rapidly and gaining popularity in the research community. This research reviews the literature on humanitarian logistics for providing a thorough... Show More

The concept of humanitarian logistics is evolving rapidly and gaining popularity in the research community. This research reviews the literature on humanitarian logistics for providing a thorough outlook into the field. In this study, Authors conducted a scientometric analysis of the literature published in 1998–2015 to empirically explore the important areas and key contributors of humanitarian logistics research and providing new outlook towards publication patterns, authorship pattern, major subject areas, research impact, and research productivity. By using scientometric analysis, the research critically evaluates 509 articles published over the past 18 years and identifies some of the major contributing authors, organizations and key research topics related to the field. In the last, the paper examines the validity of Lotka's law to authorship pattern in humanitarian logistics. The result found that the author productivity distribution data in humanitarian logistics do not follow Lotka's law. The findings of the study provide a new outlook on humanitarian logistics research.

Grid computing has been used as a new paradigm for solving large and complex scientific problems using resource sharing mechanism through many distributed administrative domains. One of the most... Show More

Grid computing has been used as a new paradigm for solving large and complex scientific problems using resource sharing mechanism through many distributed administrative domains. One of the most challenging issues in computational Grid is efficient scheduling of jobs, because of distributed heterogeneous nature of resources. In other words, the job scheduling in computational Grid is an NP-hard problem. Thus, the use of meta-heuristic is more appropriate option in obtaining optimal results. In this article, the authors propose a novel hybrid scheduling algorithm which combines intelligently the exploration ability of Particle Swarm Optimization (PSO) with the exploitation ability of Extremal Optimization (EO) which is a recently developed local-search heuristic method. The hybrid PSO-EO reduces the schedule makespan, processing cost, and job failure rate and improves resource utilization. The proposed hybrid algorithm is compared with the standard PSO, population-based EO (PEO) and standard Genetic Algorithm (GA) methods on all these parameters. The comparison results exhibit that the proposed algorithm outperforms other three algorithms.

Healthcare systems have evolved to become more patient-centric. Many efforts have been made to transform paper-based patient data to automated medical information by developing electronic healthcare... Show More

Healthcare systems have evolved to become more patient-centric. Many efforts have been made to transform paper-based patient data to automated medical information by developing electronic healthcare records (EHRs). Several international EHRs standards have been enabling healthcare interoperability and communication among a wide variety of medical centres. It is a dual-model methodology which comprises a reference information model and an archetype model. The archetype is responsible for the definition of clinical concepts which has limitations in terms of supporting complex reasoning and knowledge discovery requirements. The objective of this article is to propose a semantic-mediation architecture to support semantic interoperability among healthcare organizations. It provides an intermediate semantic layer to exploit clinical information based on richer ontological representations to create a “model of meaning” for enabling semantic mediation. The proposed model also provides secure mechanisms to allow interoperable sharing of patient data between healthcare organizations.

In today's era where personalization of the learning material is a key factor towards the success of learning goal for any student according to their personality traits, learning style and cognitive... Show More

In today's era where personalization of the learning material is a key factor towards the success of learning goal for any student according to their personality traits, learning style and cognitive style, choosing a career according to personality traits is also become a key to success of job satisfaction. Hence, this article proposes the recommendation of career on the basis of candidate personality attributes. In this article, Holland's theory is used to detect candidate's personality. Weights are assigned to each personality traits to calculate the scores are calibrated manually with help of research work done in this domain before and the feedback. A survey is conducted to test the accuracy of proposed method on 217 responses. The result shows the 74.35% candidates are satisfied with the recommended career and average rating for personality traits score was 3.58/5. This article also suggests a fuzzy approach to automatic detection of career recommendation based on personality score.

This article presents a novel method to extract retinal vascular tree automatically. The proposed method consists of four steps; smoothing image using low pass spatial filter to reduce spurious... Show More

This article presents a novel method to extract retinal vascular tree automatically. The proposed method consists of four steps; smoothing image using low pass spatial filter to reduce spurious noise in the image; extracting candidate borders of the vessels based on a local window property; tracking process, starting with a candidate pixel and following in the optimum direction with monitoring the connectivity of the vessel twin border; constructing the whole tree of retinal blood vessels by connecting the vessel segments based on their spatial locations, widths and directions. The algorithm was trained with 20 images from the DRIVE dataset, and tested using the remaining 20 images.

Online services are now commonly deployed via cloud computing based on Infrastructure as a Service (IaaS) to Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS). However, workload is not... Show More

Online services are now commonly deployed via cloud computing based on Infrastructure as a Service (IaaS) to Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS). However, workload is not constant over time, so guaranteeing the quality of service (QoS) and resource cost-effectiveness, which is determined by on-demand workload resource requirements, is a challenging issue. In this article, the authors propose a neural network-based-method termed domain knowledge embedding regularization neural networks (DKRNN) for large-scale workload prediction. Based on analyzing the statistical properties of a real large-scale workload, domain knowledge, which provides extended information about workload changes, is embedded into artificial neural networks (ANN) for linear regression to improve prediction accuracy. Furthermore, the regularization with noisy is combined to improve the generalization ability of artificial neural networks. The experiments demonstrate that the model can achieve more accuracy of workload prediction, provide more adaptive resource for higher resource cost effectiveness and have less impact on the QoS.

In cloud environment, the main challenge is load balancing as it requires distributing the load among many various virtual machines (VM) while avoiding underflow and overflow conditions. In this... Show More

In cloud environment, the main challenge is load balancing as it requires distributing the load among many various virtual machines (VM) while avoiding underflow and overflow conditions. In this article, the question that which load-balancing (overflow or underflow) management will better improves the performance and quality of service has been answered with a number of experiments. For experiment purpose, scientific workflow DAG files has been used with one host configuration. Ant Colony Optimization (ACO) and BAT algorithm are used for checking underflow and overflow conditions respectively for VMs. In proposed work, initially the workflow is parsed by Predict Earliest Finish Time (PEFT) heuristic to generate initial seed for meta-heuristic algorithms which will optimize the VM in terms of makespan and cost of execution. Different workflows have been used with varying number of VMs from 2 to 20. The results shows that makespan analysis is approximately overlapped for different workflow tasks and shows no significant difference however, the cost analysis show a significant change for overflow and underflow identification with cost for overflow condition is reduced significantly.