Wireless communication systems have witnessed tremendous growth over the last decades. However, the efficient and accurate characterization of the propagation channel still remains one of the most challenging and important issues in modern wireless communications. In order to meet the demands of a wide variety of applications, advanced propagation models that incorporate detailed representations of complicated propagation environments with sophisticated and efficient computational techniques are required. Moreover, the development of sophisticated models and methods increases as new applications emerge. This paper reviews current scientific and patent literature and discusses recent trends and future directions in the modeling and simulation of the wireless propagation medium. Within this context, several theoretical advances and underlying technologies used in the modeling and simulation of the radio channel are presented. A brief overview of current research trends in the capture and analysis of channel measurements and their application in channel modeling is also given.
With the rapid growth of multimedia information, video coding standards have become crucial when transmitting large amount of video data. Motion estimation promises to be the key to high performance in video coding by removing the temporal redundancy of video data for storage and transmission. Due to its fundamentality, research works on motion estimation have been conducted extensively. In this article, an overview of video compression technique is presented with emphasis on motion estimation. Then, a survey of most representative motion estimation search algorithms and the new perspectives are introduced with some patent description. An evaluation and analysis of these algorithms based on a number of experiments on several famous test video sequences is presented. Finally, an investigation of the future trend of video coding is discussed.
In distributed computing, the peer-to-peer paradigm enables two or more entities to collaborate spontaneously in an overlay network of equals (peers) by using appropriate information and communication schemes without the necessity for central coordination. The key concept of the peer-to-peer paradigm is leveraging idle resources to do something useful, based on a collaborative approach. The increasing academic and industrial interest is resulting in the definition of standards and writing of patents. In this paper we propose a categorization for the peer-to-peer overlay schemes and a survey of the most popular ones, comparing each other with respect to effectiveness and security. Most of them have been or are being used in content sharing systems, that over the last few years have enjoyed explosive popularity. Others are used in parallel and distributed computing, massively multi-player gaming, Internet streaming, ambient intelligence, etc. Considering such a wide range of applications, we discuss the importance of reputation management in supporting trust management among peer participants.
Computer-based educational systems are becoming increasingly important in all levels and types of education. Intelligent Educational Systems (IESs) are computer-based educational systems encompassing Artificial Intelligence schemes to increase the effectiveness of the learning process. In this paper, we survey patents regarding IESs. As IESs we consider either Intelligent Tutoring Systems (ITSs) or Adaptive Educational Hypermedia Systems (AEHSs) incorporating intelligent techniques. We first present indicative functions implemented in the three basic components of an IES: the domain knowledge, the user (or student) modeling unit and the pedagogical module. Afterwards, we focus on representative patents concerning IESs and present the corresponding work. At the end, we outline current and future developments regarding IESs.
Background modeling is often used to detect moving object in video acquired by a fixed camera. Recently, subspace learning methods have been used to model the background in the idea to represent online data content while reducing dimension significantly. The first method using Principal Component Analysis (PCA) was proposed by Oliver et al.  and a representative patent using PCA concerns the detection of cars and persons in video surveillance . Numerous improvements and variants were developed over the recent years. The purpose of this paper is to provide a survey and an original classification of these improvements. Firstly, we classify the improvements of the PCA in term of strategies and the variants in term of the used subspace learning algorithms. Then, we present a comparative evaluation of the variants and evaluate them with the state-of-art algorithms (SG, MOG, and KDE) by using the Wallflower dataset.
Owing to the video distribution over heterogeneous networks, Scalable Video Coding has become a trend in the last years. As the promising candidates for SVC the Wavelet-based solutions should face the challenges aroused by motion estimation and motion compensation. This paper, according to the WSVC coding context, reviews the motion estimation techniques applied in RDWT and MCTF architectures and the corresponding patents. And then a comparison between the close-loop and open loop systems is made to reveal the corresponding advantages and disadvantages of MCTF-based WSVC. The patents involved in bidirectional MEMC, spatial domain MCTF, in-band MCTF, etc. are also reviewed. Finally possible future research directions in WSVC are pointed.