A novel design of a simple circular ring with open-ended monopole antenna for wireless local area network (WLAN) applications is proposed in this article. The proposed antenna consists of an open-ended circular ring and $50-{\Omega}$ microstrip feed-line. The proposed antenna is capable of generating two separate resonant modes with good impedance-matching conditions. A prototype of the proposed antenna is designed, fabricated, and measured. Acceptable agreement between the measurement and simulation results is achieved. Experimental results show that the proposed antenna has operating bandwidths of 1.99-3.04 GHz and 5.08-6.1 GHz with a return loss of less than -10 dB, covering the required bandwidths of the 2.4/5.2/5.8-GHz WLAN standards. This is a microstrip antenna for IEEE 802.11a/b wireless local area networks applications. Meanwhile, the two-dimensional (2D) radiation patterns and three-dimensional (3D) gain performance of the antenna are also observed and discussed.

We consider the sensor selection problem in large sensor networks where the goal is to find the best set of sensors that maximizes application objectives. Since sensor selection typically involves a large number of sensors, a low complexity should be maintained for practical applications. We propose a geometry-based sensor selection algorithm that utilizes only the information of sensor locations. In particular, by observing that sensors clustered together tend to have redundant information, we theorize that the redundancy is inversely proportional to the distance between sensors and seek to minimize this redundancy by searching for a set of sensors with the maximum average distance. To further reduce the computational complexity, we perform an iterative sequential search without losing optimality. We apply the proposed algorithm to an acoustic sensor network for source localization, and demonstrate using simulations that the proposed algorithm yields significant improvements in the localization performance with respect to the randomly generated sets of sensors.

A recent major development in computer technology is the advent of wearable computer systems. Wearable computer systems employ a wireless universal serial bus (WUSB), which refers to a combination of USB with the WiMedia wireless technical specifications. In this study, we focus on an integrated system of WUSB over wireless body area networks (WBANs) for wireless wearable computer systems. However, current WBAN MACs do not have well-defined quality of service (QoS) mapping and resource allocation mechanisms to support multimedia streams with the requested QoS parameters. To solve this problem, we propose a novel QoS-aware time slot allocation method. The proposed method provides fair and adaptive QoS provisioning to isochronous streams according to current traffic loads and their requested QoS parameters by executing a QoS satisfaction algorithm at the WUSB/WBAN host. The simulation results show that the proposed method improves the efficiency of time slot utilization while maximizing QoS provisioning.

The wireless sensor networking standard DASH7 operates in low-power communication with a better transmission quality in active RFID networks. The DASH7 security standard supports public key cryptography. At present, the DASH7 standard uses the message authentication code in the network layer for authentication and integrity. However, its security standard is still in an incubation stage with respect to the implementation of a crypto exchange over a DASH7 network. Effective key management is an important factor for privacy and security. If organizations are not careful about where and how keys are stored, they leave the encrypted data vulnerable to theft. In this regard, we present a key management system designed for efficient key management through public key infrastructure authentication as well as a non-repudiation feature for the DASH7 standard. We analyze the performance of the proposed system on a basis of various performance criteria such as latency and throughput.

Vehicular-to-anything (V2X) technology is attractive for wireless vehicular ad-hoc networks (VANETs) because it allows for opportunistic choice of a vehicular protocol between vehicular-to-vehicular (V2V) and vehicular-to-infrastructure (V2I) communications. In particular, achieving seamless connectivity in a VANET with nearby network infrastructure is challenging. In this paper, we propose a density-based opportunistic broadcasting (DOB) protocol, in which opportunistic connectivity is carried out by using the nearby infrastructure and opposite vehicles for solving the problems of disconnection and long end-to-end delay times. The performance evaluation results indicate that the proposed DOB protocol outperforms the considered comparative conventional schemes, i.e., the shortest path protocol and standard mobile WiMAX, in terms of the average end-to-end delay, packet delivery ratio, handover latency, and number of lost packets.

This paper investigates the shaping operation problem introduced by Callahan et al., namely the k-fragility maximization problem (k-FMP), whose goal is to find a subset of personals within a terrorist group such that the regeneration capability of the residual group without the personals is minimized. To improve the impact of the shaping operation, the degree centrality of the residual graph needs to be maximized. In this paper, we propose a new greedy algorithm for k-FMP. We discover some interesting discrete properties and use this to design a more thorough greedy algorithm for k-FMP. Our simulation result shows that the proposed algorithm outperforms Callahan et al.'s algorithm in terms of maximizing degree centrality. While our algorithm incurs higher running time (factor of k), given that the applications of the problem is expected to allow sufficient amount of time for thorough computation and k is expected to be much smaller than the size of input graph in reality, our algorithm has a better merit in practice.

A numerical method for solving Hamiltonian equations is said to be symplectic if it preserves the symplectic structure associated with the equations. Various symplectic methods are widely used in many fields of science and technology. A symplectic method preserves an approximate Hamiltonian perturbed from the original Hamiltonian. It theoretically supports the effectiveness of symplectic methods for long-term integration. Although it is also related to long-term integration, numerical stability of symplectic methods have received little attention. In this paper, we consider explicit symplectic methods defined for Hamiltonian equations with Hamiltonians of the special form, and study their numerical stability using the harmonic oscillator as a test equation. We propose a new stability criterion and clarify the stability of some existing methods that are visually based on the criterion. We also derive a new method that is better than the existing methods with respect to a Courant-Friedrichs-Lewy condition for hyperbolic equations; this new method is tested through a numerical experiment with a nonlinear wave equation.

This article presents key research needs in three-dimensional integrated circuit (3D IC) architectural floorplanning. Architectural floorplaning is done at a very early stage of 3D IC design process, where the goal is to quickly evaluate architectural designs described in register-transfer level (RTL) in terms of power, performance, and reliability. This evaluation is then fed back to architects for further improvement and/or modifications needed to meet the target constraints. We discuss the details of the following research needs in this article: block-level modeling, through-silicon-via (TSV) insertion and management, and chip/package co-evaluation. The goal of block-level modeling is to obtain physical, power, performance, and reliability information of architectural blocks. We then assemble the blocks into multiple tiers while connecting them using TSVs that are placed in between hard IPs and inside soft IPs. Once a full-stack 3D floorplanning is obtained, we evaluate it so that the feedback is provided back to architects.

Motion estimation is a core part of most video compression systems since it directly affects the output video quality and the encoding time. The full search (FS) technique gives the highest visual quality but has the problem of a significant computational load. To solve this problem, we present in this paper a modified median (MMED) operation and advanced search strategies for fast motion estimation. The proposed MMED operation includes a temporally co-located motion vector (MV) to select an appropriate initial candidate. Moreover, we introduce a search procedure that reduces the number of thresholds and simplifies the early termination conditions for the determination of a final MV. The experimental results show that the proposed approach achieves substantial speedup compared with the conventional methods including the motion vector field adaptive search technique (MVFAST) and predictive MVFAST (PMVFAST). The proposed algorithm also improves the PSNR values by increasing the correlation between the MVs, compared with the FS method.

This paper describes an efficient framework for the extraction of a brain tumor from magnetic resonance (MR) images. Before the segmentation process, a median filter is used to filter the image. Then, the morphological gradient is computed and added to the filtered image for intensity enhancement. After the enhancement process, the thresholding value is calculated using the mean and the standard deviation of the image. This thresholding value is used to binarize the image followed by the morphological operations. Moreover, the combination of these morphological operations allows to compute the local thresholding image supported by a flood-fill algorithm and a pixel replacement process to extract the tumor from the brain. Thus, this framework provides a new source of evidence in the field of segmentation that the specialist can aggregate with the segmentation results in order to soften his/her own decision.