Abstract
Handling major challenges like traffic volume estimation, mobility pattern detection and feature extraction in mobility network usually form a weak balance among them. Most of the works are focused towards one of these areas which fail in improving altogether. In this paper, we present a model with modified conventional methods meeting all three above challenges to an extent. Extracting new temporal & directional feature, we introduce Reciprocity metric. It proves to be more informative and efficient in capturing mobility pattern of the network than existing metrics. We introduce the idea of network skeleton which is a reduced form of mobility network but captures approx 90% of its inherent characteristics. Network Skeleton can extract higher level of information from the network while enhancing network's short-term predictability. Our work has the following steps: 1) extracting and building "link reciprocity", a more informative feature; 2) pattern detection in random mobility introduced by "convergence of mobility network"; and 3) estimation of network skeleton formed using a link based approach for short-term forecasting. Our network convergence method outperforms conventional approaches and detects active regions at a very fast rate compared to other approaches. Long ShortTerm Memory (LSTM), a kind of Recursive Neural Networks (RNN) capable of learning long-term dependencies is used to estimate network traffic. Indicating link based network-skeleton helps to reduce short-term forecasting error up to 6% and 3/4 times in different time-slots. Our network skeleton approach can be used to meet the general problems of the traffic-rules formulation by characterizing important routes (links), detecting regions of high importance in less time and predicting short-term traffic volume in a more accurate way. Moreover, network skeleton with reduced network-size can be easily operable with existing methodologies, which is another essential contribution of our work.

Abstract
In this review the objective is to search for technologies that supervise the exercise or physical activity of people suffering from Peripheral Arterial Disease (PAD) at home or in the community. Patients with PAD have walking limitations and their quality of life progressively deteriorates. The regular practice of exercise can help mitigate these effects and even improve their health status. The methodology used was to search for scientific articles published since 2008, with the final result of 18 articles. The results show the most frequent technologies used are based on the accelerometer device, with the tests being performed on a treadmill at a hospital. The hospital tests are expensive, so a useful and viable alternative is the usage of mobile devices to help the health professionals record the exercise performed by their patients suffering with PAD.

Abstract

Abstract
Modern distributed systems are increasingly complex both on their architectural design and on the computational logic that they execute. Their timely operation is challenged, which is critical for some domains such as cyber-physical systems where timeliness and dynamic behavior must be satisfied simultaneously. Providing real-time operation whereas supporting the inherent dynamic behavior of cyber-physical systems requires solutions that are not yet available. A number of challenging scientific and engineering problems that span across a variety of research areas are raised. The new challenges go far beyond those of traditional networked real-time systems; cyber-physical systems are autonomous, open, large-scale, real-time, embedded, and control systems that make intensive use of networks, distribution, and wireless technology. Such complex systems have different [sub]parts/systems with different levels of real-time requirements.

Abstract
The negotiation is one of the most important phase of the process of buying and selling energy in electricity markets. Buyers and sellers know about their own trading behavior or the quality of their products. However, they can also gather data directly or indirectly from them through the exchange information before or during negotiation, even negotiators should also gather information about past behavior of the other parties, such as their trustworthiness and reputation. Hence, in this scope, reputation models play a more important role in decision-making process in the undertaken bilateral negotiation. Since the decision takes into account, not only the potential economic gain for supported player, but also the reliability of the contracts. Therefore, the reputation component represents the level of confidence that the supported player can have on the opponent’s service, i.e. in this case, the level of assurance that the opponent will fulfil the conditions established in the contract. This paper proposes a reputation computational model, included in DECON, a decision support system for bilateral contract negotiation, in order to enhance the decision-making process regarding the choice of the most suitable negotiation parties.

Abstract
The genetic algorithm is a general purpose optimization metaheuristic for solving complex optimization problems. Because the algorithm usually requires a large number of iterations to evolve a population of solutions to good final solutions, it normally exhibits long execution times, especially if running on low-performance conventional processors. In this work, we present a scalable computing array to parallelize and accelerate the execution of cellular GAs (cGAs). This is a variant of genetic algorithms which can conveniently exploit the coarse-grain parallelism afforded by custom parallel processing. The proposed architecture targets Xilinx FPGAs and was implemented as an auxiliary processor of an embedded soft-core CPU (MicroBlaze). To facilitate the customization for different optimization problems, a high-level synthesis design flow is proposed where the problem-dependent operations are specified in C++ and synthesised to custom hardware, thus demanding of the programmer only minimal knowledge of low-level digital design for FPGAs. To demonstrate the efficiency of the array processor architecture and the effectiveness of the design methodology, the development of a hardware solver for the minimum energy broadcast problem in wireless ad hoc networks is employed as a use case. Implementation results for a Virtex-6 FPGA show significant speedups, especially when comparing to embedded processors used in current FPGA devices.