Although Wolf Pack Algorithm (WPA) is a novel optimal algorithm with good performance, there is still room for improvement with respect to its convergence. In order to speed up its convergence and strengthen the search ability, we improve WPA with the Differential Evolution (DE) elite set strategy. The new proposed algorithm is called the WPADEES for short. WPADEES is faster than WPA in convergence, and it has a more feasible adaptability for various optimizations. Six standard benchmark functions are applied to verify the effects of these improvements. Our experiments show that the performance of WPADEES is superior to the standard WPA and other intelligence optimal algorithms, such as GA, DE, PSO, and ABC, in several situations.

This paper introduces a random selection cooperation scheme that takes the Decode-and-Forward (DF) approach to solve the unfairness problem in selection cooperation. Compared to previous work which obtained fairness but introduced performance loss, the proposed scheme guarantees fairness without performance loss. Its essence is to randomly select from the relays that can ensure the successful communication between the source and the destination, rather than to select the best relay. Both a theoretical analysis and simulation results confirm that the proposed scheme could achieve fairness and introduce no performance loss. We also discuss the conditions under which the proposed scheme is practical to implement.

In modern automobiles, Controller Area Network (CAN) has been widely used in different sub systems that are connected by using gateway. While a gateway is necessary to integrate different electronic sub systems, it brings challenges for the analysis of Worst Case Response Time (WCRT) for CAN messages, which is critical from the safety point of view. In this paper, we first analyzed the challenges for WCRT analysis of messages in gateway-interconnected CANs. Then, based on the existing WCRT analysis method proposed for one single CAN, a new WCRT analysis method that uses two new definitions to analyze the interfering delay of sporadically arriving gateway messages is proposed for non-gateway messages. Furthermore, a division approach, where the end-to-end WCRT analysis of gateway messages is transformed into the similar situation with that of non-gateway messages, is adopted for gateway messages. Finally, the proposed method is extended to include CANs with different bandwidths. The proposed method is proved to be safe, and experimental results demonstrated its effectiveness by comparing it with a full space searching based simulator and applying it to a real message set.

Among the cognitive radio technologies, cooperative spectrum sensing has been corroborated to be an effective approach to counter channel fading. Recent research about it is mainly with the assumption that secondary users (SUs) are synchronous with primary users (PUs). In this letter, we discuss the asynchronous situation for the first time, which means SUs have no idea about the communication time table of PUs' network. Based on the ON/OFF channel model, we derive the detection and false alarm probabilities, and the optimal sensing parameters under such asynchronous scenario. Simulation results are shown in the end.

The sensing scheme based on the generalized likelihood ratio test (GLRT) technique has attracted a lot of research interest in the field of cognitive radios (CR). Although its potential advantages in detecting correlated primary signal have been illustrated in prior work, no theoretical analysis of the positive effects of the correlation has appeared in the literature. In this letter, we derive the theoretical false-alarm and detection probabilities of GLRT detector. The theoretical analysis shows that, in the low signal-to-noise ratio (SNR) region, the detector's performance can be improved by exploiting the high correlations between the primary signal samples. The conclusions of the analysis are verified by numerical simulation results.

In resent years, providing location services for mobile targets in a closed environment has been a growing interest. In order to provide good localization and tracking performance for drones in GPS-denied scenarios, this paper proposes a multi-tag radio frequency identification (RFID) system that is easy to equip and does not take up the limited resources of the drone which is not susceptible to processor performance and cost constraints compared with computer vision based approaches. The passive RFID tags, no battery equipped, have an ultra-high resolution of millimeter level. We attach multiple tags to the drone and form multiple sets of virtual antenna arrays during motion, avoiding arranging redundant antennas in applications, and calibrating the speed chain to improve tracking performance. After combining the strap-down inertial navigation system (SINS) carried by the drone, we have established a coupled integration model that can suppress the drift error of SINS with time. The experiment was designed in bi-dimensional and three-dimensional scenarios, and the integrated positioning system based on SINS/RFID was evaluated. Finally, we discussed the impact of some parameters, this innovative approach is verified in real scenarios.

With the popularity of BitTorrent-like P2P applications, improving its performance has been an active research area. Super-seeding, a special upload policy for the initial seeder, improves the efficiency in producing multiple seeds and reduces the uploading bytes of content initiators, thus being highly expected as a promising solution for improving downloading performance while decreasing uploading cost. However, the overall impacts of super seeding upon BitTorrent performance remain a question and have not been analyzed so far in literature. In this paper, we present an analytical and experimental study over the performance of super-seeding scheme. We attempt to answer the following questions: whether and how much super-seeding saves uploading cost, whether the overall downloading time is decreased by super-seeding, and in which circumstances super-seeding performs worse. Based on the seeding process, our analytical study gives formulas on the new piece distribution time, average downloading time and minimum distribution time for heterogeneous P2P file distribution system with super-seeding. Robust evidence supporting the use (or not) of super-seeding is given based on our worldwide Internet experiments over wide distribution of 250 PlanetLab nodes. With a well-designed experimental scenario, we study the overall download time and upload cost of super seeding scheme under varying seed bandwidth and peer behavior. Results show that super-seeding can save an upload ratio of 20% and does help speeding up swarms in certain modes. Tentative conclusions about the effectiveness of super-seeding and its optimal working circumstances are given with inside mechanism analyzed and negative factor identified. Our work not only provides reference for the potential adoption of super-seeding in BitTorrent and other P2P applications, but also much insights for the tussle of enhancing of Quality of Experience (QoE) and saving cost for a large-scale BitTorrent-like P2P commercial application.

Although the Marching Cube (MC) algorithm is very popular for displaying images of voxel-based objects, its slow surface extraction process is usually considered to be one of its major disadvantages. It was pointed out that for the original MC algorithm, we can limit vertex calculations to once per vertex to speed up the surface extraction process, however, it did not mention how this process could be done efficiently. Neither was the reuse of these MC vertices looked into seriously in the literature. In this paper, we propose a “Group Marching Cube” (GMC) algorithm, to reduce the time needed for the vertex identification process, which is part of the surface extraction process. Since most of the triangle-vertices of an iso-surface are shared by many MC triangles, the vertex identification process can avoid the duplication of the vertices in the vertex array of the resultant triangle data. The MC algorithm is usually done through a hash table mechanism proposed in the literature and used by many software systems. Our proposed GMC algorithm considers a group of voxels simultaneously for the application of the MC algorithm to explore interesting features of the original MC algorithm that have not been discussed in the literature. Based on our experiments, for an object with more than 1 million vertices, the GMC algorithm is 3 to more than 10 times faster than the algorithm using a hash table. Another significant advantage of GMC is its compatibility with other algorithms that accelerate the MC algorithm. Together, the overall performance of the original MC algorithm is promoted even further.

In medical education, many of computerized Problem-Based Learning (PBL) systems are used into their training curricula. But these systems do not truly reflect the situations which practitioners may actually encounter in a real medical environment, and hence their effectiveness as learning tools is somewhat limited. Therefore, the present study analyzes the computerized PBL teaching case, and considers how a clinical teaching case can best be presented to the student. Specifically, this paper attempts to develop a web-based PBL system which emulates the real clinical situation by introducing the concept of a "time sequence" within each teaching case. The proposed system has been installed in the medical center of National Cheng Kung University in Taiwan for testing purposes. The participants in this study were 50 of 5th grade (equivalent to 1st grade students in a medical school of the American medical education system) students for the evaluation process. Some experiments are conducted to verify the advantages of designing teaching cases with the concept of the "time sequence."

A new direction of arrival (DOA) estimation method is introduced with arbitrary array geometry when uncorrelated and coherent signals coexist. The DOAs of uncorrelated signals are first estimated via subspace-based high resolution DOA estimation technique. Then a matrix that only contains the information of coherent signals can be formulated by eliminating the contribution of uncorrelated signals. Finally a subspace block sparse reconstruction approach is taken for DOA estimations of the coherent signals.

The selection cooperation is a basic and attractive scheme of cooperative diversity in the multiple relays scenario. Most previous schemes of selection cooperation consist only one relay-stage in which one relay is selected to retransmit, and the signal from the selected relay is not utilized by other relays. In this paper, we introduce a two relay-stage selection cooperation scheme. The performance can be improved by letting all other relays to utilize the signal from the first selected relay to make another selection and retransmission in the second relay-stage. We derive the closed-form expression of the outage probability of the proposed scheme in the high SNR regime. Both theoretical and numerical results suggest that the proposed scheme can reduce the outage probability compared with the traditional scheme with only one relay-stage. Furthermore, we demonstrate that more than two relay-stage can not further reduce the outage probability. We also study the dependence of the proposed scheme on stage lengths and topology, and analyze the increased overhead.

Since the dark channel prior (DCP)-based dehazing method is ineffective in the sky area and will cause the problem of too dark and color distortion of the image, we propose a novel dehazing method based on sky area segmentation and image fusion. We first segment the image according to the characteristics of the sky area and non-sky area of the image, then estimate the atmospheric light and transmission map according to the DCP and correct them, and then fuse the original image after the contrast adaptive histogram equalization to improve the details information of the image. Experiments illustrate that our method performs well in dehazing and can reduce image distortion.

In this paper, we propose a unified algebraic design of the generalized Moreau enhancement matrix (GME matrix) for the Linearly involved Generalized-Moreau-Enhanced (LiGME) model. The LiGME model has been established as a framework to construct linearly involved nonconvex regularizers for sparsity (or low-rank) aware estimation, where the design of GME matrix is a key to guarantee the overall convexity of the model. The proposed design is applicable to general linear operators involved in the regularizer of the LiGME model, and does not require any eigendecomposition or iterative computation. We also present an application of the LiGME model with the proposed GME matrix to a group sparsity aware least squares estimation problem. Numerical experiments demonstrate the effectiveness of the proposed GME matrix in the LiGME model.

In this paper, we propose a new localization algorithm and improve the DV-Hop algorithm by using a differential error correction scheme that is designed to reduce the location error accumulated over multiple hops. This scheme needs no additional hardware support and can be implemented in a distributed way. The proposed method can improve location accuracy without increasing communication traffic and computing complexity. Simulation results show the performance of the proposed algorithm is superior to that of the DV-Hop algorithm.

Transform each coordinate of the realizations of several random variables (RVs) by the distribution function of the corresponding RV and partition the range space into a uniform grid. The expected number of occupied grid-boxes will be greatest when these RVs are independent. Based on this fact, we propose a novel measure of independence named grid occupancy (GO). We also address the problem of how to make optimum selection of the parameters in GO, i.e., the number of observations and the number of quantization levels. In addition, we apply GO to independent component analysis (ICA). The GO based ICA algorithm can separate signals with arbitrary continuous distributions and favors digital hardware implementation.