Image classification plays a vital role in many areas of study, such as data mining and image processing; however, serious problems collectively referred to as the course of dimensionality have been encountered in previous studies as factors that reduce system performance. Furthermore, we also confront the problem of different graph characteristics even if graphs belong to same types. In this study, we propose a novel method of graph-type classification. Using our approach, we open up a new solution of high-dimensional images and address problems of different characteristics by converting graph images to one dimension with a discrete Fourier transformation and creating numeric datasets using wavelet and Hough transformations. Moreover, we introduce a new classifier, which is a combination between artificial neuron networks (ANNs) and support vector machines (SVMs), which we call ANNSVM, to enhance accuracy. The objectives of our study are to propose an effective graph-type classification method that includes finding a new data representative used for classification instead of two-dimensional images and to investigate what features make our data separable. To evaluate the method of our study, we conducted five experiments with different methods and datasets. The input dataset we focused on was a numeric dataset containing wavelet coefficients and outputs of a Hough transformation. From our experimental results, we observed that the highest accuracy was provided using our method with Coiflet 1, which achieved a 0.91 accuracy.

QUIC (Quick UDP Internet Connections) Chrome is an experimental transport layer network protocol designed by Jim Roskind at Google, initially implemented in 2012 and announced publicly in 2013. One of the QUIC's goals is to improve performance of connection-oriented web applications that are currently using the Transmission Control Protocol (TCP). To do that, QUIC achieves a reduced latency and a better stream-multiplexing support to avoid network congestion. In 2015, Firefox Mozilla started to work on an equivalent QUIC transport protocol for their browser. This idea was motivated by the differences between Chrome and Firefox. Despite the fact that Mozilla Firefox and Google Chrome are both web browser engines, there are some significant differences between them, such as file hierarchy, open source policies (Firefox is completely, while Chrome is only partial), tabs design, continuous integration, and more. Likewise QUIC Chrome, QUIC Firefox is a new multiplexed and secure transport based on User Datagram Protocol (UDP), designed from the ground up and optimized for Hyper-Text Transfer Protocol 2 (HTTP/2) semantics. While built with HTTP/2 as the primary application protocol, QUIC builds on decades of transport and security experience, and implements mechanisms that make it attractive as a modern general-purpose transport. In addition to describing the main design of QUIC Firefox, this paper will compare Firefox with QUIC Firefox. Our preliminary experimental results support that QUIC Firefox has a faster execution time, less latency time, and a better throughput time than the traditional Firefox.  

Abstract Started in 2008, the new Massive Open Online Courses (MOOCs) paradigm has brought challenges and innovation at all levels of education, aiming to respond to the most pressing learning needs, generated by the new development policies and the rapid evolution of technology. This paper reports on a project proposed by a group of universities and organizations specialized in training, research and consultancy with a view to develop and implement a learning ecosystem in entrepreneurship. The project is built on a package of MOOCs targeting the learning needs of young entrepreneurs in the context of "žSmart cities and specializations" policies. The article presents the project concepts and the development and implementation steps, from MOOCs design, pilot phase, consultancy activities, impact study to proposals for national policies and accreditation. This work could be a starting point for developing new programmes and customized training courses on specific learning needs to support the "žSmart cities" interventions.

Systems that react to emotional information allow for better satisfaction of the user's needs, stated or otherwise. Special support should be built-in, in order to read and measure the timevariable user's affective state. This paper presents how cursor movement can accurately measure two basic emotional states and introduces a way to measure the emotional flow graph of an application, which allows for better user design.

The aim of the current work is to assess the challenges that gamification in education are facing nowadays. Benefits and disadvantages of using gamification in classroom are both discussed to offer a clearer view on the impact of using gamification within learning process. Exploratory study —cases are provided to investigate the relation between motivation and engagement of the students and gamification in training. Following this idea, a survey was conducted to assess how students' behavior and motivation is affected by introducing a single, specific gamification element during a semester learning process. To stimulate competition among students, a ranking type plugin was introduced within the university learning management system used for extramural education. The results prove that motivation decreases by comparison to the previous semester.

In the field of "Data Exploration" many approaches have been developed to solve the problem of management of big data that are also semantically rich. Nowadays, there is a strong need to support the discovery-oriented applications where data discovery is a highly ad hoc interactive process to support the users by assisting the navigation in the data to find interesting objects. In this work starting by a theoretical data exploration system, where we identified the main features that a data exploration system must have to an efficient exploratory experience, we propose a combination of two data exploration techniques faceted navigation and data mining with the aim to improve the discovery information during exploration. This approach is contextualized better in Information Mining. Information mining, in fact, aims at discovering knowledge, i.e. more general patterns within objects or collections of objects.

Vehicle routing problem (VRP) is a Nondeterministic Polynomial Hard combinatorial optimization problem to serve the consumers from central depots and returned back to the originated depots with given vehicles. Furthermore, two of the most important extensions of the VRPs are the open vehicle routing problem (OVRP) and VRP with simultaneous pickup and delivery (VRPSPD). In OVRP, the vehicles have not return to the depot after last visit and in VRPSPD, customers require simultaneous delivery and pick-up service. The aim of this paper is to present a combined effective ant colony optimization (CEACO) which includes sweep and several local search algorithms which is different with common ant colony optimization (ACO). An extensive numerical experiment is performed on benchmark problem instances addressed in the literature. The computational result shows that suggested CEACO approach not only presented a very satisfying scalability, but also was competitive with other meta-heuristic algorithms in the literature for solving VRP, OVRP and VRPSPD problems. Keywords: Meta-heuristic algorithms, Vehicle Routing Problem, Open Vehicle Routing Problem, Simultaneously Pickup and Delivery, Ant Colony Optimization.

In this paper, we lay the foundation for an adaptation of the teaching process to the personality traits and academic performance of the university students enrolled in applied computer science and informatics (ACSI). We discuss how such an adaptation could be supported by an analytical software solution and present the initial version of this solution. In the form of a case study, we discuss the scores from a personality questionnaire that was administered to a group of university students enrolled in an introductory programming course at the Faculty of Technical Sciences, University of Novi Sad, Serbia. During a non-mandatory workshop on programming, the participants completed the 48-item short-scale Eysenck Personality Questionnaire—Revised (EPQ— R). By using various exploratory and analytical techniques, we inspect the student EPQ—R scores and elaborate on the specificities of the participating student group. As part of our efforts to understand the broader relevance of different student personality traits in an academic environment, we also discuss how the EPQ—R scores of students could provide information valuable to the process of improving student learning and performance in university courses in ACSI.

One of the most crucial issues, nowadays, is to provide personalized services to each individual based on their preferences. To achieve this goal, recommender system could be utilized as a tool to help the users in decision-making process offering different items and options. They are utilized to predict and recommend relevant items to end users. In this case an item could be anything such as a document, a location, a movie, an article or even a user (friend suggestion). The main objective of the recommender systems is to suggest items which have great potential to be liked by users. In modern recommender systems, various methods are combined together with the aim of extracting patterns in available datasets. Combination of different algorithms make prediction more convoluted since various parameters should be taken into account in providing recommendations. Recommendations could be personalized or non-personalized. In non-personalized type, selection of the items for a user is based on the number of the times that an item has been visited in the past by other users. However, in the personalized type, the main objective is to provide the best items to the user based on her taste and preferences. Although, in many domains recommender systems gained significant improvements and provide better services for users, it still requires further research to improve accuracy of recommendations in many aspects. In fact, the current available recommender systems are far from the ideal model of the recommender system. This paper reviews state of art in recommender systems algorithms and techniques which is necessary to identify the gaps and improvement areas. In addition to that, we provide possible solutions to overcome shortages and known issues of recommender systems as well as discussing about recommender systems evaluation methods and metrics in details.

The robots science has been developed over the past few years, where robots have become used to accomplish difficult, repetitive or accurate tasks, which are very hard for humans to carry out. In this paper, we propose an algorithm to control the motion of a swarm of robots and make them able to avoid obstacles. The proposed solution is based on forming the robots in circular fashion. A group set of robots consists of multiple groups of robots, each group of robots consists of robots forming a circular shape and each group set is a circular form of robots. The proposed algorithm is concerned with first locating the randomly generated robots in groups and secondly with the swarm robot motion and finally with the swarm obstacle avoidance and swarm reorganization after crossing the obstacle. The proposed algorithm has been simulated with five different obstacles with various numbers of randomly generated robots. The results show that the swarm in the circular form can deal with the obstacles very effectively by passing the obstacles smoothly. The proposed algorithm has been compared with flocking algorithm and it is shown that the circular formation algorithm does not need extensive computation after obstacle avoidance whereas the flocking algorithm needs extensive computation. In addition, the circular formation algorithm maintains every robot in its group after avoiding the obstacles whereas with flocking algorithm does not.

This paper introduces novel detection features for the steady-state visually evoked potential (SSVEP) based brain computer interfaces. The coefficient of variation and variation speed features were developed using the stability of SSVEP response. The developed features were tested on 13 subjects. On this dataset, for which the chance level is 12.5%, about 70% detection accuracy was obtained. Based on these results, it is considered that the coefficient of variation and the variation speed can be used as discriminative features for SSVEP. By using familiar SSVEP features and developed features together, higher SSVEP detection accuracy can be obtained. By this procedure the performance of single channel SSVEP based BCI systems can be improved.

In this study it is proposed the critical analysis of the creation of Artificial Intelligence (AI) and of Artificial General Intelligence (AGI). The unity of formal logic and rational dialectics is the methodological basis of the analysis. The main results of the analysis are as follows: (1) the model of man represents the unity of the two material aspects: "physiological body" (controllable aspect) and "psychical body" (controlling aspect); (2) the "psychical body" is the subsystem "subconsciousness + consciousness"; (3) in the comprehensive sense of the word, the thinking is an attribute of the complete system "physiological body + psychical body + environment". (3) in the broad sense of the word, thinking and creativity are an essential feature of the subsystem "subconsciousness + consciousness"; (4) in the narrow (concise) sense of the word, thinking and creativity are the attribute of the instinct of the conservation (preservation, retention, maintenance) of life (i.e., the self-preservation instinct, the survival instinct); the instinct of the conservation of life exists in subconsciousness; (5) the instinct of life conservation is a system of elementary (basic) instincts; thinking is the attribute of the each elementary instinct; (6) the mechanism of thinking and the essence of creation cannot be cognized by men; (7) a computer as a device cannot think and create (in particular, it cannot prove theorems), because a computer does not have the subconsciousness; (8) the modeling of human thinking, Human Intellect, and the creation of AI and AGI are the impossible because the essential properties of the complete system "man + environment" cannot be cognized and modeled; (9) the existence of AI and AGI conflicts with the essence of the thinking; (10) the existence of AI and AGI contradict to formal-logical and rationaldialectical laws.