Directional antennas provide numerous benefits, such as higher gains, increased transmission range, and lower interferences. In this paper, we propose a reliable broadcast protocol for directional antenna referred to as beam table-based reliable broadcast for directional antennas (BTRB). The BTRB employs (1) ACK-based scheme to provide full reliability; (2) spatio-temporal ACK combination to resolve the problems of ACK implosion and transmission delay; and (3) beam table caching to represent spatial relationship among destination nodes in the broadcast group. Performance evaluation has shown that the proposed BTRB shows full reliability and outperforms existing reliable broadcast schemes with respect to transmission delay by about 55%.

Reverse-recovery modeling for p-i-n diodes in the high current-density conditions are discussed. With the dynamic carrier-distribution-based modeling approach, the reverse recovery behaviors are explained in the high current-density conditions, where the nonquasi-static (NQS) behavior of carriers in the drift region is considered. In addition, a specific feature under the high current-density condition is discussed. The proposed model is implemented into a commercial circuit simulator in the Verilog-A language and its reverse recovery modeling ability is verified with a two-dimensional (2D) device simulator, in comparison to the conventional lumped-charge modeling technique.

This paper presents two halftoning methods to improve efficiency in generating structurally similar halftone images using Structure Similarity Index Measurement (SSIM). Proposed Method I reduces the pixel evaluation area by applying pixel-swapping algorithm within inter-correlated blocks followed by phase block-shifting. The effect of various initial pixel arrangements is also investigated. Proposed Method II further improves efficiency by applying bit-climbing algorithm within inter-correlated blocks of the image. Simulation results show that proposed Method I improves efficiency as well as image quality by using an appropriate initial pixel arrangement. Proposed Method II reaches a better image quality with fewer evaluations than pixel-swapping algorithm used in Method I and the conventional structure aware halftone methods.

Three-dimensional (3-D) reconstruction techniques employed by airborne radars are essential for object recognition in scenarios where optically vision is blurry, and are required for the monitoring of disasters and coast-guard patrols. There have been reports on 3-D reconstruction methods that exploit the layover appearing in inverse synthetic aperture radar (ISAR) imagery, which are suitable for the recognition of artificial targets such as buildings, aircraft or ships. However, existing methods assume only a point target or the aggregate of point targets, and most require the tracking of the multiple points over sequential ISAR images. In the case of a solid object with a continuous boundary, such as a wire or polyhedral structure, the positioning accuracy of such methods is severely degraded owing to scattering centers continuously shifting on the target surface with changes in the rotation angle. To overcome this difficulty, this paper extends the original Range Points Migration (RPM) method to the ISAR observation model, where a double mono-static model with two transmitting and receiving antennas is introduced to suppress cross-range ambiguity. The results of numerical simulation and experimental validation demonstrate that the extended RPM method has a distinct advantage for accurate 3-D imaging, even for non-point targets.

A 60 GHz direct conversion transceiver which employs amplitude/phase imbalance cancellation technique is newly proposed. By using the proposed technique, the receive path of the transceiver achieves less than 0.2 dB of amplitude error and less than 3 of phase error at 60 GHz bands over a 10 GHz bandwidth, which relaxes the design accuracy required for baluns used in the transceiver. It also employs a simple and fast calibration algorithm to adjust the locking range of the divide-by-3 injection locked divider in the phase locked loop. Fabricated in 90 nm CMOS technology, the transceiver achieves a low power consumption of 230 mW in transmit mode and 173 mW in receive mode. The output spectrum of 1.76 Gsps π/2-BPSK/QPSK modulation shows the excellent distortion and spurious suppression that meet the IEEE802.11ad draft standard.

We investigate the impact of traffic on the performance of large-scale NAT (LSN), since it has been attracting attention as a means of better utilizing the limited number of global IPv4 addresses. We focus on the number of active flows because they drive up the LSN memory requirements in two ways; more flows must be held in LSN memory, and more global IPv4 addresses must be prepared. Through traffic measurement data analysis, we found that more than 1% of hosts generated more than 100 TCP flows or 486 UDP flows at the same time, and on average, there were 1.43-3.99 active TCP flows per host, when the inactive timer used to clear the flow state from a flow table was set to 15 s. When the timer is changed from 15 s to 10 min, the number of active flows increases more than tenfold. We also investigate how to reduce the above impact on LSN in terms of saving memory space and accommodating more users for each global IPv4 address. We show that to save memory space, regulating network anomalies can reduce the number of active TCP flows on an LSN by a maximum of 48.3% and by 29.6% on average. We also discuss the applicability of a batch flow-arrival model for estimating the variation in the number of active flows, when taking into account that the variation is needed to prepare an appropriate memory space. One way to allow each global IPv4 address to accommodate more users is to better utilize destination IP address information when mapping a source IP address from a private address to a global IPv4 address. This can effectively reduce the required number of global IPv4 addresses by 85.9% for TCP traffic and 91.9% for UDP traffic on average.

This paper focuses on the latest research of switching arc both in vacuum and SF6 substitutes in our group. The crucial characteristics of vacuum arc are illustrated, including the motion and distribution of single cathode spot and multiple cathode spots, the influence of axial magnetic field on arc plasma characteristics, the influence of composite magnetic field on cathode jets, and the study of anode activities. Meanwhile, the arc characteristics in SF6 and its substitutes (Ar, CO2 and N2) at different pressures and gap distances are investigated by experiments and simulation.

This paper develops a methodology of crosstalk analysis/measurement techniques for the design and fabrication of the MEMs (Micro-ElectroMichanical system) probe card. By introducing more ground pins into the connector pins, the crosstalk characteristics can be enhanced and a design guide for the parameters, such as pin's size and pitch is proposed to satisfy the given crosstalk limitation of -30 dB for reliable high speed signal transfer. The paper also presents a novel method to characterize scattering parameters of multiport interconnect circuits with a 4-port VNA (Vector Network Analyzer). By employing the re-normalization of scattering matrices with different reference impedances at other ports, data obtained from 4-port configuration measurements can be synthesized to build a full scattering matrix of the DUT (Device-Under-Test, MEMs probe connector pins). In comparison to the conventional 2-port VNA re-normalization method, proposed technique has two advantages: saving of measuring time, and enhanced accuracy even with open-ended unmeasured ports. A good agreement of the estimated and correct S parameters verifies the validness of the proposed algorithm.

Accurate estimation of Software Code Size is important for developing cost-efficient embedded systems. The Code Size affects the amount of system resources needed, like ROM and RAM memory, and processing capacity. In our previous work, we have estimated the Code Size based on CFP (COSMIC Function Points) within 15% accuracy, with the purpose of deciding how much ROM memory to fit into products with high cost pressure. Our manual CFP measurement process would require 2.5 man years to estimate the ROM size required in a typical car. In this paper, we want to investigate how the manual effort involved in estimation of Code Size can be minimized. We define a UML Profile capturing all information needed for estimation of Code Size, and develop a tool for automated estimation of Code Size based on CFP. A case study will show how UML models save manual effort in a realistic case.

Wireless multimedia sensor networks tend to generate a large number of sensing data packets within a short period. A multi-channel TDMA scheme can avoid the hidden terminal problem and and has been shown to achieve higher performance than the CSMA scheme. In order to deliver large volumes of sensing data within a time limit, our scheme for minigroup multicast can improve the performance gain of the multi-channel TDMA by incorporating deflection routing which constrains any intermediate nodes from serving multiple sessions and establishes a new path detour the nodes on the existing path of multicast sessions. Through simulations, we show that, even though the deflection routing builds non-optimal paths, our scheme supports 95% packet delivery ratio and higher throughput than the legacy multicast routing protocol with CSMA-based media access control.

A novel long-term sub-band entropy (LT-SubEntropy) measure, which uses improved long-term spectral analysis and sub-band entropy, is proposed for voice activity detection (VAD). Based on the measure, we can accurately exploit the inherent nature of the formant structure on speech spectrogram (the well-known as voiceprint). Results show that the proposed VAD is superior to existing standard VAD methods at low SNR levels, especially at variable-level noise.

This paper presents a self-clustering algorithm to detect symmetry in images. We combine correlations of orientations, scales and descriptors as a triple feature vector to evaluate each feature pair while low confidence pairs are regarded as outliers and removed. Additionally, all confident pairs are preserved to extract potential symmetries since one feature point may be shared by different pairs. Further, each feature pair forms one cluster and is merged and split iteratively based on the continuity in the Cartesian and concentration in the polar coordinates. Pseudo symmetric axes and outlier midpoints are eliminated during the process. Experiments demonstrate the robustness and accuracy of our algorithm visually and quantitatively.

In this letter, we propose a dissimilarity metric (DM) to measure the deviation of a cognitive radio from the network in terms of local sensing reports. Utilizing the probability mass function of the DM, we present a dissimilarity-based attacker detection algorithm to distinguish Byzantine attackers from honest users. The proposed algorithm is able to identify the attackers without a priori information of the attacking styles and is robust against both independent and dependent attacks.

Discrete-Time fractional Brownian motion (DFBM) and its increment process, called discrete-time fractional Gaussian noise (DFGN), are usually used to describe natural and biomedical phenomena. These two processes are dominated by one parameter, called the Hurst exponent, which needs to be estimated in order to capture the characteristics of physical signals. In the previous work, a variance estimator for estimating the Hurst exponent directly via DFBM was provided, and it didn't consider point selection for linear regression. Since physical signals often appear to be DFGN-type, not DFBM-type, it is imperative to first transform DFGN into DFBM in real applications. In this paper, we show that the variance estimator possesses another form, which can be estimated directly via the autocorrelation functions of DFGN. The above extra procedure of transforming DFGN into DFBM can thus be avoided. On the other hand, the point selection for linear regression is also considered. Experimental results show that 4-point linear regression is almost optimal in most cases. Therefore, our proposed variance estimator is more efficient and accurate than the original one mentioned above. Besides, it is also superior to AR and MA methods in speed and accuracy.

Unlike analogue voice signal-oriented and narrowband-based conventional tactical systems, the future tactical networks will deal with packet-based voice traffic over a wide channel bandwidth. In this paper, a method is proposed to improve the performance of voice packet transmission for MIL-STD-188-220 military standard-based wideband communication systems. By utilizing Bump-Slots for voice packet transmissions, significant improvements are achieved. This is confirmed by extensive simulations.

This study compares the performances of waveband protection and wavelength path protection in survivable hierarchical optical path networks. Network costs and the number of switching operations necessary are evaluated for different ratios of protected demand. Numerical results demonstrate that waveband protection can drastically decrease the number of switching operations in the case of failure, while both waveband and wavelength path protection effectively reduce the network resources needed compared to single layer optical path networks.

The wireless sensor network (WSN) is a technology that senses environmental information and provides appropriate services to users. There are diverse application areas for WSNs such as disaster prevention, military, and facility management. Despite the many prospective applications, WSN s are vulnerable to various malicious attacks. In false report attacks, a malicious attacker steals a few sensor nodes and obtains security materials such as authentication keys from the nodes. The attacker then injects false event reports to the network through the captured nodes. The injected false reports confuse users or deplete the limited energy of the nodes in the network. Many filtering schemes have been proposed to detect and remove false reports. In the statistical en route filtering (SEF) scheme, each node shares authentication keys selected from a global key pool. Due to the limited memory, each node is able to store only a small portion of the global key pool. Therefore, the routing paths of the event reports significantly affect the filtering (i.e., detecting) probability of false reports. In this paper, we propose a method to determine the routing paths of event reports both hop by hop and on demand at each node. In this method, each node chooses the next node on the path from the event source to the sink node based on the key indexes of its neighbor nodes. Experiments show that the proposed method is far more energy efficient than the SEF when the false traffic ratio (FTR) is ≥ 50% in the network.

Based on a reverse converter algorithm derived from the New Chinese Remainder Theorem I, an algorithm for sign detection of RNS {2n-1, 2n, 2n+1} is presented in this paper. The hardware of proposed algorithm can be implemented using two n-bit additions and one (n+1)-bit comparator. Comparing with the previous paper, the proposed algorithm has reduced the number of additions used in the circuit. The experimental results show that the proposed circuit achieves 17.3% savings in area for small moduli and 10.5% savings in area for large moduli on an average, with almost the same speed. The power dissipations obtain 12.6% savings in average.

In this letter a general admission control strategy is proposed and mathematically analyzed. Fractional buffering finely adjusts different QoS metrics allowing them to simultaneously achieve their maximum acceptable values, maximizing system capacity. Fractional buffering also allows the adequate and fair performance comparison among different resource management strategies and/or evaluation scenarios.

In this paper, a new skin detection method using pixel color and image regional information, intended for objectionable image filtering is proposed. The method consists of three stages: skin detection, feature extraction and image classification. Skin detection is implemented in two steps. First, a Sinc function, fitted to skin color distribution in the Cb-Cr chrominance plane is used for detecting pixels with skin color properties. Next, to benefit regional information, based on the theory of color image reproduction, it's shown that the scattering of skin pixels in the RGB color space can be approximated by an exponential function. This function is incorporated to extract the final accurate skin map of the image. As objectionable image features, new shape and direction features, along with area feature are extracted. Finally, a Multi-Layer Perceptron trained with the best set of input features is used for filtering images. Experimental results on a dataset of 1600 images illustrate that the regional method improves the pixel-based skin detection rate by 10%. The final classification result with 94.12% accuracy showed better results when compared to other methods.