In traditional mobile cloud computing, user tasks are uploaded and processed on a cloud server over the Internet. Due to the recent rapid increase in the number of mobile users connected to the network, due to overload of the Internet communication channels, there are significant delays in the delivery of data processed on cloud servers to the user. Furthermore, it complicates the optimal scheduling of the tasks of many users on cloud servers and the delivery of results. Scheduling is an approach used to reduce the tasks execution time by ensuring a balanced distribution of user tasks on cloud servers. The goal of scheduling is to ensure selection of appropriate resources to handle tasks quickly, taking into account user requirements. Whereas the goal of cloud service providers is to provide users with the required resources through performing effective scheduling so that both the user and the service provider can benefit. The article proposes a scheduling model to reduce processing time, network latency, and power consumption of mobile devices through optimal task placement in the cloudlet network in a mobile cloud computing environment.

The problem of the Internet addiction (IA) arose after the rise of the Internet. Some of the Internet users include children and teenagers and they are active in a virtual environment. Most minor users are not well aware of the dangers posed by information abundance. One of these dangers is the IA. Excessive use of the Internet is addictive, and some users experience a high risk of addiction. IA can negatively affect the children's health, psychology, socialization and other activities. There is a great need to the development of forecasting programs and various technological approaches for the identification of IA among Internet users, especially children and adolescents. This article uses machine-learning techniques to detect IA. Activities of children in the Internet environment is analyzed. The log-files of children and their IA problem are explored. To determine the degree of IA among children and adolescents an experiment is conducted on public dataset. The effectiveness of the methods is analyzed by various evaluation metrics and promising results are obtained.The results show better performance of Weighted SVM, compared to BernoulliNB, Logistic Regression, MLPClassifier, SVM classifiers. Acquired results of the research provide kids information security. To evaluate a kids IA helps to identify their psychological conditions, and it creates a better situation for parents, teachers, and other related people to communicate with children and teenagers better way.

The article proposes a comprehensive method for the multicriteria evaluation of websites. The essence of this method is that using this method we can not only evaluate a website traditionally, but also obtain the following useful results: importance coefficient of each of the criteria, the evaluation of the website for each criterion individually. Moreover, we can also compare the sampled websites and then rank them. It is noted that in order to get the precise result, the sampled websites must be referred to the same category, that is, have the same set of criteria for evaluation.

In order to improve analytical activities and providing support to decision makers in the field of terminology, the article proposes a decision support system developed based on the data warehouse technologies and online analytical processing OLAP. The architectural and technological model of the system, its integration with the terminological information system is presented. The role of this system in the National Terminology Information System is shown. The article also presents the structure of the data warehouse and the OLAP-cube developed on its basis.

The article provides a solution to the problem of placing mobile users’ queries (tasks or software applications) on a balanced virtual machine (VMs) developed on cloudlets placed near base stations of the Wireless Metropolitan Area Networks (WMAN) taking into account their technical capabilities. For this purpose, hierarchically structured architecture and algorithm based on cloudlets are proposed for the selection of virtual machines that provide the requirements (solution time and cost) to the solution of the user’s task. An approach to the optimal VM selection is proposed for the solution of Bi-Criteria selection out of set of VMs based on Skyline operator.

The article presents issues of the establishment of National Terminological Information System as one of the development perspectives of national terminology. The current state and problems in terminology sphere in Azerbaijan are explored and the necessity of system establishment is justified. Ongoing research works in computational terminology field within the system are mentioned and several conceptual approaches are presented. International practice and standards in this direction are investigated and analyzed. Conceptual foundations and architecture-technological principles of the National Terminological Information System are developed. Primary functions of web-portal developed within the system framework are presented. As a result of the study on the system establishment, the future prospects of the National Terminological Information System have been identified. The article also stresses the expected outcomes as a result of the implementation of National Terminological Information System.

At present, an anomaly detection is one of the important problems in many fields. The rapid growth of data volumes requires the availability of a tool for data processing and analysis of a wide variety of data types. The methods for anomaly detection are designed to detect object’s deviations from normal behavior. However, it is difficult to select one tool for all types of anomalies due to the increasing computational complexity and the nature of the data. In this paper, an improved optimization approach for a previously known number of clusters, where a weight is assigned to each data point, is proposed. The aim of this article is to show that weighting of each data point improves the clustering solution. The experimental results on three datasets show that the proposed algorithm detects anomalies more accurately. It was compared to the k-means algorithm. The quality of the clustering result was estimated using clustering evaluation metrics. This research shows that the proposed method works better than k-means on the Australia (credit card applications) dataset according to the Purity, Mirkin and F-measure metrics, and on the heart diseases dataset according to F-measure and variation of information metric.

The increasing amount of data and a need to analyze the given data in a timely manner for multiple purposes has created a serious barrier in the big data analysis process. This article describes the challenges that big data creates at each step of the big data analysis process. These problems include typical analytical problems as well as the most uncommon challenges that are futuristic for the big data only. The article breaks down problems for each step of the big data analysis process and discusses these problems separately at each stage. It also offers some simplistic ways to solve these problems.

Social network analysis is a widely used technique to analyze relationships among wiki-users in Wikipedia. In this paper the method to identify hidden social networks participating in information conflicts in wiki-environment is proposed. In particular, we describe how text clustering techniques can be used for extraction of hidden social networks of wiki-users caused information conflict. By clustering unstructured text articles caused information conflict we create social network of wiki-users. For clustering of the conflict articles a hybrid weighted fuzzy-c-means method is proposed.

The paper studies the concept of integration, the integration of countries, basic characteristics of the integration of countries, the integration indicators of countries. The number of contacts between countries and the number of contracts signed between countries are offered as the indicators to determine the integration degree of countries. An approach to the design of the data warehouse for the decision support system in the field of foreign policy, using OLAP-technology is offered. Designed polycubic OLAP-model in which each cube is based on a separate data mart. Given the differences between the data warehouse and data mart. Shown that, one of the cubes of this model gives full information about the chosen indicators, including their aggregation on various parameters. Method for measuring the degree of integration of the countries, based on the calculation of the weight coefficients is proposed. In this regard, was described the information model of the relevant subsystem by using graph theory. Practical application of this method was shown. Moreover, the used software was shown.

The essence, structure, formation and conditions of culture have been investigated in the article. The types of culture have been studied in accordance with the development stages of civilization and different spheres. Various approaches on information culture as a part of common culture of a human have been analyzed. The formation issues of personal information culture have been reviewed according to the requirements of information society as a new development stage of a society. The features of human behavior in the virtual environment have been examined. The influence of education, profession and activity peculiarities on the formation of personal information culture has been investigated.