This paper deals with an integral equation method for analyzing the diffraction of a transverse magnetic (TM) plane wave by a perfectly conductive periodic surface. In the region below the periodic surface, the extinction theorem holds, and the total field vanishes if the field solution is determined exactly. For an approximate solution, the extinction theorem does not hold but an extinction error field appears. By use of an image Green's function, new formulae are given for the extinction error field and the mean square extinction error (MSEE), which may be useful as a validity criterion. Numerical examples are given to demonstrate that the formulae work practically even at a critical angle of incidence.

This paper presents an experimental study of on-body ultra-wideband (UWB) radio propagation channels within an enclosed space. To facilitate high-speed wireless body area networks, UWB is a promising technology because of its low power consumption and anti-multipath capabilities. The motivation of this study is to examine the effects of nearby humans on the UWB channels by varying the population within an elevator cabin from one (subject alone) to 20 (full capacity of the elevator). The first domain (0 < delay, t ≤ 4ns) in the measured delay profiles was either a direct (for line-of-sight) or diffracted (for non-line-of-sight) wave, which was found almost unrelated to the population; whereas the second domain (t > 4ns) highly depended on it. Total received power and delay spreads decreased with increasing the population. In addition, by varying human population, average power delay profiles were modeled based on measurements.

A removable HDD “iVDR” is an international standardized medium, which has HDD features such as a large capacity and high-speed data transfer, and also is removable and compatible. We discuss the concepts of the hardware-specifications designed by the iVDR Consortium and the history of the international standardization activities for iVDR. We also discuss application expansions through these standardization activities.

Active measurement is an end-to-end measurement technique that can estimate network performance. The active measurement techniques of PASTA-based probing and periodic-probing are widely used. However, for the active measurement of delay and loss, Baccelli et al. reported that there are many other probing policies that can achieve appropriate estimation if we can assume the non-intrusive context (the load of the probe packets is ignored in the non-intrusive context). While the best policy in terms of accuracy is periodic-probing with fixed interval, it suffers from the phase-lock phenomenon created by synchronization with network congestion. The important point in avoiding the phase-lock phenomenon is to shift the cycle of the probe packet injection by adding fluctuations. In this paper, we analyse the optimal magnitude of fluctuations corresponding to the given autocovariance function of the target process. Moreover, we introduce some evaluation examples to provide guidance on designing experiments to network researchers and practitioners. The examples yield insights on the relationships among measurement parameters, network parameters, and the optimal fluctuation magnitude.

Considering the non-linear properties of the human visual system, many non-linear operators and models have been developed, particularly the logarithmic image processing (LIP) model proposed by Jourlin and Pinoli, which has been proved to be physically justified in several laws of the human visual system and has been successfully applied in image processing areas. Recently, several modifications based on this logarithmic mathematical framework have been presented, such as parameterized logarithmic image processing (PLIP), pseudo-logarithmic image processing, homomorphic logarithmic image processing. In this paper, a new single parameter logarithmic model for image processing with an adaptive parameter-based Sobel edge detection algorithm is presented. On the basis of analyzing the distributive law, the subtractive law, and the isomorphic property of the PLIP model, the five parameters in PLIP are replaced by a single parameter to ensure the completeness of the model and physical constancy with the nature of an image, and then an adaptive parameter-based Sobel edge detection algorithm is proposed. By using an image noise estimation method to evaluate the noise level of image, the adaptive parameter in the single parameter LIP model is calculated based on the noise level and grayscale value of a corresponding image area, followed by the single-parameter LIP-based Sobel operation to overcome the noise-sensitive problem of classical LIP-based Sobel edge detection methods, especially in the dark area of an image, while retaining edge sensitivity. Compared with the classical LIP and PLIP model, the given single parameter LIP achieves satisfactory results in noise suppression and edge accuracy.

In this letter, a novel color removal method considering differences of colors in an input color image and achromatic color preservation is proposed. The achromatic color preservation is assigning lightness values to gray-levels concerning achromatic pixels for natural impression. The effectiveness and validity of the proposed method are verified by experiments.

Regular on-site testing is an elementary means to obtain real-time data and state of Electromagnetic Compatibility (EMC) of electronics systems. Nowadays, there is a lot of measured EMC data while the application of the data is insufficient. So we put forward the concept of EMC model synthesis. To carry out EMC data mining with measured electromagnetic data, we can build or modify models and synthesize variation rules of electromagnetic parameters of equipment and EMC performance of systems and platforms, then realize the information synthesis and state prediction. The concept of EMC reliability is brought forward together with the definition and description of parameters such as invalidation rate and EMC lifetime. We studied the application of statistical algorithms and Artificial Neural Network (ANN) in model synthesis. Operating flows and simulation results as well as measured data are presented. Relative research can support special measurement, active management and predictive maintenance and replenishment in the area of EMC.

In this letter, we propose a partial impedance-matching method using a two-strip resonator for noncontact Passive Intermodulation (PIM) measurements using a coaxial tube. It is shown that the strip closer to the inner tube of the coaxial tube is dominant in the observed PIM characteristics while both strips are excited equally. The ideal efficiency of power to each strip is 50%, which is a significant improvement in comparison with conventional methods.

Natural language (NL) requirements are usually human-centric and therefore error-prone and inaccurate. In order to improve the 3Cs of natural language requirements, namely Consistency, Correctness and Completeness, in this paper we propose a systematic pattern matching approach supporting both NL requirements modeling and inconsistency, incorrectness and incompleteness analysis among requirements. We first use business process modeling language to model NL requirements and then develop a formal language — Workflow Patterns-based Process Language (WPPL) — to formalize NL requirements. We leverage workflow patterns to perform two-level 3Cs checking on the formal representation based on a coherent set of checking rules. Our approach is illustrated through a real world financial service example — Global Equity Trading System (GETS).

Maximum margin clustering (MMC) is a newly proposed clustering method that extends the large-margin computation of support vector machine (SVM) to unsupervised learning. Traditionally, MMC is formulated as a nonconvex integer programming problem which makes it difficult to solve. Several methods rely on reformulating and relaxing the nonconvex optimization problem as semidefinite programming (SDP) or second-order cone program (SOCP), which are computationally expensive and have difficulty handling large-scale data sets. In linear cases, by making use of the constrained concave-convex procedure (CCCP) and cutting plane algorithm, several MMC methods take linear time to converge to a local optimum, but in nonlinear cases, time complexity is still high. Since extreme learning machine (ELM) has achieved similar generalization performance at much faster learning speed than traditional SVM and LS-SVM, we propose an extreme maximum margin clustering (EMMC) algorithm based on ELM. It can perform well in nonlinear cases. Moreover, the kernel parameters of EMMC need not be tuned by means of random feature mappings. Experimental results on several real-world data sets show that EMMC performs better than traditional MMC methods, especially in handling large-scale data sets.

One of the largest challenges for coarse-grained reconfigurable arrays (CGRAs) is how to efficiently map applications. The key issues for mapping are (1) how to reduce the memory bandwidth, (2) how to exploit parallelism in algorithms and (3) how to achieve load balancing and take full advantage of the hardware potential. In this paper, we propose a novel parallelism scheme, called ‘Hybrid partitioning’, for mapping a H.264 high definition (HD) decoder onto REMUS-II, a CGRA system-on-chip (SoC). Combining good features of data partitioning and task partitioning, our methodology mainly consists of three levels from top to bottom: (1) hybrid task pipeline based on slice and macroblock (MB) level; (2) MB row-level data parallelism; (3) sub-MB level parallelism method. Further, on the sub-MB level, we propose a few mapping strategies such as hybrid variable block size motion compensation (Hybrid VBSMC) for MC, 2D-wave for intra 44, parallel processing order for deblocking. With our mapping strategies, we improved the algorithm's performance on REMUS-II. For example, with a luma 1616 MB, the Hybrid VBSMC achieves 4 times greater performance than VBSMC and 2.2 times greater performance than fixed 44 partition approach. Finally, we achieve 1080p@33fps H.264 high-profile (HiP)@level 4.1 decoding when the working frequency of REMUS-II is 200 MHz. Compared with typical hardware platforms, we can achieve better performance, area, and flexibility. For example, our performance achieves approximately 175% improvement than that of a commercial CGRA processor XPP-III while only using 70% of its area.

Small delay defects can cause serious issues such as very short lifetime in the recent VLSI devices. Delay measurement is useful to detect small delay defects in manufacturing testing. This paper presents a design for delay measurement to detect small delay defects on global routing resources, such as double, hex and long lines, in a Xilinx Virtex 4 based FPGA. This paper also shows a measurement method using the proposed design. The proposed measurement method is based on an existing one for SoC using delay value measurement circuit (DVMC). The proposed measurement modifies the construction of configurable logic blocks (CLBs) and utilizes an on-chip DVMC newly added. The number of configurations required by the proposed measurement is 60, which is comparable to that required by stuck-at fault testing for global routing resources in FPGAs. The area overhead is low for general FPGAs, in which the area of routing resources is much larger than that of the other elements such as CLBs. The area of every modified CLB is 7% larger than an original CLB, and the area of the on-chip DVMC is 22% as large as that of an original CLB. For recent FPGAs, we can estimate that the area overhead is approximately 2% or less of the FPGAs.

This paper presents a novel adaptable 4-moduli set {2n + k, 2n+1, 2n-1, 22n+1}. It offers diverse dynamic ranges (DRs) from 25n-2n to 25n + k-2n + k that are used to conquer the over-range issue in RNS-application hardware designs. The proposed adaptable set possesses the coarse parameter n and fine parameter k. It not only has better parallelism and larger dynamic range (DR) than the existing adaptive 3-moduli sets, but also holds more sizable and flexible than the general 4-moduli sets with single parameter. For the adaptable R-to-B conversion, this paper first derives a fast reverse converting algorithm based on Chinese Remainder Theorem (CRT) and then presents the efficient converter architecture. From the experimental results, the proposed adaptable converter achieves better hardware performance in various DRs. Based on TSMC 0.18 µm CMOS technology, the proposed converter design is implemented and its results get at least 20.93% saving of Area-Delay-Power (ADP) products on average when comparing with the latest converter works.

Estimating the packet loss ratio of TCP transfers is essential for passively measuring Quality of Service (QoS) on the Internet traffic. However, only a few studies have been conducted on this issue. The Benko-Veres algorithm is one technique for estimating the packet loss ratio of two networks separated by a measurement point. However, this study shows that it leads to an estimation error of a few hundred percent in the particular environment where the packet loss probabilities between the two networks are asymmetrical. We propose a passive method for packet loss estimation that offers improved estimation accuracy by introducing classification conditions for the TCP retransmission timeout. An experiment shows that our proposed algorithm suppressed the maximum estimation error to less than 15%.

In this paper, a systematic design of X-band (9–10 GHz) 40 W pulse-driven GaN HEMT power amplifier is presented. The design includes device evaluation, verification of designed matching circuits, and measurements of the designed power amplifier. Firstly, the optimum input and output impedances for the selected GaN HEMT chip from TriQuint Semiconductor Inc. are evaluated using load-pull measurement. The selected GaN HEMT shows extremely low optimum impedances, which are obtained using a pre-match load-pull method due to the limitation of the tuning impedance range of conventional impedance tuners. We propose a novel extraction of the optimum impedances with general pre-match circuits. The extracted optimum impedances are found to be close to those computed, using the large signal model supplied from TriQuint Semiconductor. Using the optimum impedances, the matching circuits of the power amplifier are designed employing the combined impedance transformer type based on EM co-simulation. The fabricated power amplifier has a size of 1517.8 mm2, an efficiency above 45%, power gain of 7.7–9.9 dB and output power of 47–44.8 dBm at 9–10 GHz with pulse width of 10 µsec and duty of 10%.

The focus of this study is the performance of the relaying network with incremental selective decode-and-forward (ISDF) protocol in non-selective slow Nakagami-m fading channels. To enhance bandwidth efficiency, when the direct transmission is not successful the relay is used to retransmit a clean copy of the source signal. The proposed protocol achieves a significant reduction in the power consumption and an improvement in performance compared to the fixed decode-and-forward (DF). The exact symbol error rate (SER) of M-PSK modulation for the ISDF protocol over general fading channels is derived. However, as the exact SER analysis is very complicated, we provide an approximated SER expression. Based on this approximation, we provide an optimum power allocation coefficient where the aggregate transmit power constraint is imposed on the source and the relay. Our results show that at least 50% of total power must be used by the direct link, and the remaining may be used by the relay. Furthermore, power allocation in this protocol is independent of the quality of the source-destination channel and modulation constellation size. Numerical results show that the ISDF protocol can reduce the average transmit power with respect to the fixed DF protocol.

Due to the growing popularity of High Dynamic Range (HDR) images and HDR displays, a large amount of existing Low Dynamic Range (LDR) images are required to be converted to HDR format to benefit HDR advantages, which give rise to some LDR to HDR algorithms. Most of these algorithms especially tackle overexposed areas during expanding, which is the potential to make the image quality worse than that before processing and introduces artifacts. To dispel these problems, we present a new LDR to HDR approach, unlike the existing techniques, it focuses on avoiding sophisticated treatment to overexposed areas in dynamic range expansion step. Based on a separating principle, firstly, according to the familiar types of overexposure, the overexposed areas are classified into two categories which are removed and corrected respectively by two kinds of techniques. Secondly, for maintaining color consistency, color recovery is carried out to the preprocessed images. Finally, the LDR image is expanded to HDR. Experiments show that the proposed approach performs well and produced images become more favorable and suitable for applications. The image quality metric also illustrates that we can reveal more details without causing artifacts introduced by other algorithms.

Adverse weather, such as rain or snow, can cause difficulties in the processing of video streams. Because the appearance of raindrops can affect the performance of human tracking and reduce the efficiency of video compression, the detection and removal of rain is a challenging problem in outdoor surveillance systems. In this paper, we propose a new algorithm for rain detection and removal based on both spatial and wavelet domain features. Our system involves fewer frames during detection and removal, and is robust to moving objects in the rain. Experimental results demonstrate that the proposed algorithm outperforms existing approaches in terms of subjective and objective quality.

This paper describes an overview of demands on wireless communications from the point of view of robotics, oceanics and aviation technologies. These technologies are mostly applied to extreme environments, where humans cannot easily approach and directly operate equipment. In such environments, reliable and robust wireless communications are highly required to perform missions perfectly. However, there are many issues for wireless technologies to meet those requirements due to poor propagation and large delay conditions. This paper discusses wireless communication technologies required in land-sea-and-air environments based on the recent development challenges of unmanned ground and marine robots and next-generation air-transportation systems. This paper will contribute future wireless communication techniques for unmanned robots and next-generation aviations.

A method for the specification of weighting functions for a spaceborne/airborne interferometric synthetic aperture radar (SAR) sensor for Earth observation and environment monitoring is introduced. This method is based on designing an optimum mismatched filter which minimizes the total power in sidelobes located out of a specified range region around the peak value point of the system point-target response, i.e. impulse response function under the constraint imposed on the peak value. It is shown that this method allows achieving appreciable improvement in accuracy performance without degradation in the range resolution.