This paper examines the potential of existing web-based collaboration services in supporting the inter-organizational connectivity throughout the collaboration process. In doing so, the paper initially presents a brief overview and a hierarchical classification with respect to the degree and complexity of service integration of existing collaboration services which are applicable in inter-organizational settings. Successively, their shortcomings in supporting the process of inter-organizational collaboration are herein determined and discussed. As a conclusion, the paper elucidates the rational and need for designing the dedicated web-based collaboration platforms for facilitating the inter-organizational connectivity within a particular business sector.

In a prior study we found out that trust is an effective factor in the acceptance and adoption of cloud computing using the UTAUT. However, various relationships from the original UTAUT were not confirmed in the extended model for cloud computing. Therefore, we present here a study aimed at investigating the mediation effect of trust on users’ attitude toward the adoption of cloud computing using UTAUT. It is also aimed to examine the role of five moderating factors which are gender, age, education, managerial level and job domain on subjects’ behavioral intention to use cloud computing services. Data were collected from 219 subjects in order to test the modified model and were analyzed using Partial Least Square (PLS) algorithm. Experimental results demonstrated that Performance Expectancy and Facilitating Conditions are strongly mediated by trust for the behavioral intention to adopt cloud computing. Statistical results, on the other hand, indicated that the majority of the moderating factors did not have a significant impact on the acceptance of cloud computing. The paper finally concludes with the limitations of current study and directions for future work.

Article studies development dynamics of mobile cloud technologies. Advantages of this technology and problems occurring during its use are analyzed. At the same time, issues related to meeting the demand of computing and memory resources of mobile equipment using this technology are studied. For this purpose, main monitoring parameters, especially delays in network, CPU usage percentage, memory usage, completion time of intended essential operations etc. are analyzed. Considering significance of selected parameters in Cloudlet creation, Integral monitoring parameter was established. In the article analyze technologies were given as the time series of integral parameter. Thus article studies conditions necessitating development of cloudlets on mobile computing clouds and solves issues of forecasting location time of cloudlets near certain base stations.

A key artifact produced during object oriented requirements analysis is Use Case Diagram. Functional requirements of the system under development and relationship of the system and the external world are displayed with the help of Use Case Diagram. Therefore, the quality aspect of the artifact Use Case Diagram must be assured in order to build good quality software. Use Case Diagram quality is assessed by metrics that have been proposed in the past by researchers, based on Use Case Diagram countable features such as the number of actors, number of scenarios per Use Case etc., but they have not considered Use Case dependency relations for metric calculation. In our previous paper, we had proposed a complexity metric. This metric was defined considering association relationships and dependency prevailing in the Use Case Diagram. The key objective in this paper is to validate this complexity metric theoretically by using Briand’s Framework and empirically by performing a Controlled experiment. The results show that we are able to perform the theoretical and empirical validation successfully.

The mobile phone is an essential part for human life all over the world. From developed to developing, developing to under developed countries are affected by the mobile phone usages, each and every corner of this universe. In every single minute we are using mobile phone for our various purposes. Even when there is no purpose we are also just using mobile phone. This scenario is almost same all over the world. The mobile phone has been affected the human behavior and changed the nature of behavior in developing countries. This paper has divided into three parts first part gathered information; second part analyses collected information and third part draw conclusions. In this paper, the result of the mobile phone used and effect on human behaviors in developing country like Bangladesh has been presented. This paper will also analyze this issue by exploring the exiting literature related to the mobile phone usages on human behavior and effect of the mobile phone on society in developing countries. Finally, this paper was presented some efficient solutions to minimize the problems in developing countries.

In this paper, a combination of dimensionality reduction technique, to address the problems of highly correlated data and selection of significant variables out of set of features, by assessing important and significant dimensionality reduction techniques contributing to efficient classification of genes is proposed. One-Way-ANOVA is employed for feature selection to obtain an optimal number of genes, Principal Component Analysis (PCA) as well as Partial Least Squares (PLS) are employed as feature extraction methods separately, to reduce the selected features from microarray dataset. An experimental result on colon cancer dataset uses Support Vector Machine (SVM) as a classification method. Combining feature selection and feature extraction into a generalized model, a robust and efficient dimensional space is obtained. In this approach, redundant and irrelevant features are removed at each step; classification presents an efficient performance of accuracy of about 98% over the state of art.

Vehicular Ad hoc network is the most fast growing which shape fresh  engineering opportunities like controlling traffic smartly, optimal resource maintenance and improved service for customers. Vehicular Ad hoc Network (VANET) is one of the most popular ad hoc networks. A vehicular ad hoc network generally faces the problems like trust modeling, congestion, and battery optimization issues. If the nodes are comparatively less than it can handle the traffic well when it comes to transferring the data at a rapid rate. But, when it comes to high-density traffic than a Vehicular network always faces congestion problem. This paper tried to find the reliable solution to the traffic management by adding up the virtual gears into the network and optimizes the congestion problem by using a trust queue which is updated with the broadcast concept of the hello packets in order to remove the unwanted nodes in the list. The network performance has been measured with QOS Parameters like delay, throughput, and other parameters to prove the authentication of the research.

Bat Algorithm is among the most popular meta-heuristic algorithms for optimization. Traditional bat algorithm work on sequential approach which is not scalable for optimization problems involving large search space, huge fitness computation and having large number of dimensions E.g. stock market strategies therefore parallelizing meta-heuristics to run on parallel machines to reduce runtime is required. In this paper, we propose two parallel variants of Bat Algorithm (BA) using MapReduce parallel programming model proposed by Google and have used these two variants for solving the Software development effort optimization problem. The experiment is conducted using Apache Hadoop implementation of MapReduce on a cluster of 6 machines. These variants can be used to solve various complex optimization problems by simply adding more hardware resources to the cluster and without changing the proposed variant code.