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In natural language, the same meaning can be expressed by different texts. The process of determining the inference relationship occurring between a text T and a hypothesis H is called Natural Language Inference (NLI). The NLI task aims to provide a generic framework that captures, in a unifying manner, the inference across Natural Language Processing applications such as question answering, summarization, information retrieval, and machine translation. Many tasks and datasets have been created to support the development and evaluation of the ability of the NLI task in different languages. For the Arabic language, interest in this field is gradually increasing. This paper aims to provide an overview of state-of-the-art NLI approaches for Arabic, the relevant knowledge resources and the used tools in order to support a better understanding of this growing field. Moreover, this paper points to classify the proposed approaches for Arabic NLI and compare existing NLI systems. [ABSTRACT FROM AUTHOR]

Mobile communication systems are witnessing an ongoing-increase in connected devices and new types of services. This considerable increase has led to an exponential augmentation in mobile data traffic volume. Ultra-densification is a key solution aimed at satisfying the emerging requirements in next-generation 5G networks. However, the deployment of a high number of small cells and mobile nodes on the 5G networks poses challenges for the mobility management, including frequent, unnecessary and ping-pong handovers, with additional problems related to increased delay and total failure of the handover process. In this article, a novel optimized vertical handover approach is proposed to find the optimal network to connect with a good quality of service. This approach cooperates Media Independent Handover and Software-Defined Networking for seamless vertical handover. Simulation results validate the efficiency of our proposal. [ABSTRACT FROM AUTHOR]

In current years, vehicular communication systems are evolving for Intelligent Transportation System (ITS) by providing its wireless network services with increasing demand for high data rate. Vehicular communications supports for various applications that include safety, traffic efficiency and infotainment. However, the high mobility of vehicles and frequent topology changes in such communication systems pose challenges for the mobility management, including frequent, unnecessary and ping-pong handovers, with additional problems related to increased delay and packets loss rate, and failure of the handover process. In this article, we propose a solution to optimize the handover in vehicular networks. Our solution resides in creating a novel multi-criteria network selection mechanism. The objectives of the proposed solution are: to decrease handover failure, handover delay, and packet loss rates, also to distribute traffic load uniformly among available networks to improve the average system resource utilization. The proposed mechanism is based on Fuzzy Logic scheme to support the decision making process. Simulation results demonstrate that, compared to existing works, the proposed approach significantly reduces the handover failure, handover delay and packet loss rates. In addition, the proposed solution achieved an improvement in network resources utilization. [ABSTRACT FROM AUTHOR]

Hand Gesture recognition becomes a challenging task in computer vision field especially after the appearance of mobile devices. Although gesture recognition algorithms have been widely applied to the human-mobile interaction systems, it is difficult to meet the real time requirements and the robustness in different lightening conditions and backgrounds. This paper provides a description of a practical investigation into ways of improving hand gesture recognition algorithms for computationally limited handheld Android devices. We thoroughly researched possible approaches and find out how they affect the mobile device in terms of execution time and energy consumption. We have identified a combined HOG-LBP methodology whose performance improved upon the detection rate of other systems. In this paper, we present a static hand gesture recognition system for mobile devices by combining the histogram of oriented gradients (HOG) and local binary pattern (LBP) features, which can accurately detect hand poses. With the help of combining HOG and LBP features, we achieved a detection rate of approximately 92% on the enhanced NUS dataset I. This combination performs a better result than the results obtained when using only LBP or HOG features in term of recognition rate. However, in term of execution and detection time, LBP and HOG perform better than the combined HOG-LBP. [ABSTRACT FROM AUTHOR]

Successful usability evaluation of interactive adaptive systems requires the use of appropriate methods. Different usability evaluation methods exist in the literature. These methods can be applied in association with the individual layers and with the whole adaptive system. In each situation, it is essential to apply the appropriate evaluation methods. In this paper, we propose a novel decision support approach called EvalCHOICE. It guides evaluators in the choice of appropriate usability evaluation methods for individual layers and the adaptive system as a whole. Our proposal is applied to determine the suitable evaluation methods for a given Web-based adaptive system in the field of transport. [ABSTRACT FROM AUTHOR]

Working with corpus construction becomes an interesting alternative to different applications of natural language processing, such as, question-answering, machine translation, information retrieval, etc. Similarly, with the heterogeneous data and the user demands for the accurate information, many studies have accentuated the need of the Web to highlight the corpus construction. As well as, Arabic doesn’t have an equivalent number of linguistic corpuses as compared to other languages like English. In this paper, we focus on building our corpus of Arab questions-texts. We present a method for recovering text passages. This method is based on a real automatic interrogation of Google, in order to generate passages of texts and answer the factual questions. The first part of this paper describes the formal details about this method; the second part presents some experiments and results that validate our method. [ABSTRACT FROM AUTHOR]