The most commonly used scattering parameters (S parameters) are normalized to a real reference resistance, typically 50Ω. In some cases, the use of S parameters normalized to some complex reference impedance is essential or convenient. But there are different definitions of complex-referenced S parameters that are incompatible with each other and serve different purposes. To make matters worse, different simulators implement different ones and which ones are implemented is rarely properly documented. What are possible scenarios in which using the right one matters? This tutorial-style paper is meant as an informal and not overly technical exposition of some such confusing aspects of S parameters, for those who have a basic familiarity with the ordinary, real-referenced S parameters.

Deep Neural Network (DNN) is a powerful machine learning model that has been successfully applied to a wide range of pattern classification tasks. Due to the great ability of the DNNs in learning complex mapping functions, it has been possible to train and deploy DNNs pretty much as a black box without the need to have an in-depth understanding of the inner workings of the model. However, this often leads to solutions and systems that achieve great performance, but offer very little in terms of how and why they work. This paper introduces Sensitivity-characterised Activity Neorogram (SCAN), a novel approach for understanding the inner workings of a DNN by analysing and visualising the sensitivity patterns of the neuron activities. SCAN constructs a low-dimensional visualisation space for the neurons so that the neuron activities can be visualised in a meaningful and interpretable way. The embedding of the neurons within this visualisation space can be used to compare the neurons, both within the same DNN and across different DNNs trained for the same task. This paper will present the observations from using SCAN to analyse DNN acoustic models for automatic speech recognition.

This paper presents an innovative fabrication process for a planar circuits at millimeter-wave frequency. Screen printing technology provides low cost and high performance coplanar waveguides (CPW) lines in planar devices operated at millimeter-wave frequency up to 110GHz. Printed transmission lines provide low insertion losses of 0.30dB/mm at 110GHz and small return loss like as impedance standard lines. In the paper, Multiline Thru-Reflect-Line (TRL) calibration was also demonstrated by using the impedance standard substrates (ISS) fabricated by screen printing. Regarding calibration capability validation, verification devices were measured and compare the results to the result obtained by the TRL calibration using commercial ISS. The comparison results obtained by calibration of screen printing ISS are almost the same as results measured based on conventional ISS technology.

An L-shaped probe with a surrounding aperture such as a waveguide can generate circular polarization (CP) waves. Circular waveguide antennas using an L-shaped probe have broadband characteristics both in axial ratio (AR) and in input impedance, however cross-polarization (XPOL) is easily generated due to its asymmetrical structure resulting in a radiation pattern that has narrow CP azimuth range. In this paper, design techniques to reduce the XPOL generated from a circular waveguide antenna using an L-shaped probe are proposed. As a result, XPOL is reduced by around 10 dB, and CP is radiated over a wide angle range of 120-150° covering frequencies from 7.35 to 9.75GHz.

In satellite/terrestrial integrated mobile communication systems (STICSs), a user terminal directly connects both terrestrial and satellite base stations. STICS enables expansion of service areas and provides a robust communication service for large disasters. However, the cell radius of the satellite system is large (approximately 100km), and thus a capacity enhancement of the satellite subsystem for accommodating many users is needed. Therefore, in this paper, we propose an application of two methods — multiple-input multiple-output (MIMO) transmission using multi-satellites and non-orthogonal multiple access (NOMA) for STICS — to realize the performance improvement in terms of system capacity and user fairness. Through numerical simulations, we show that system capacity and user fairness are increased by the proposed scheme that applies the two methods.

This paper proposes a power supply voltage control technique, and demonstrates its effectiveness for eliminating the overkills and underkills due to the power supply characteristic difference between an automatic test equipment (ATE) and a practical operating environment of the DUT. The proposed method controls the static power supply voltage on the ATE system, so that the ATE can eliminate misjudges for the Pass or Fail of the DUT. The method for calculating the power supply voltage is also described. Experimental results show that the proposed method can eliminate 89% of overkills and underkills in delay fault testing with 105 real silicon devices. Limitations of the proposed method are also discussed.

In this paper, a novel method for an effective allocation of non-zero digits in design of CSD (Canonic Signed-Digit) coefficient FIR (Finite Impulse Response) filters is proposed. The design problem can be formulated as a mixed integer programming problem, which is well-known as a NP-hard problem. Recently, a heuristic approach using the PSO (Particle Swarm Optimization) for solving the problem has been proposed, in which the maximum number of non-zero digits was limited in each coefficient. On the other hand, the maximum number of non-zero digits is limited in total in the proposed method and 0-1PSO is applied. It enables an effective allocation of non-zero digits, and provides a good design. Several examples are shown to present the efficiency of the proposed method.

Due to the increasing demand for 3D video transmission over wireless networks, managing the quality of experience (QoE) of wireless 3D video clients is becoming increasingly important. However, the variability of compressed 3D video bit streams and the wireless channel condition as well as the complexity of 3D video viewing experience assessment make it difficult to properly allocate wireless transmission resources. In this paper, we discuss the characteristics of H.264 3D videos and QoE assessment of 3D video clients, and further propose a transmission scheme for 3D video transmission over a wireless communication system. The purpose of our scheme is to minimize the average ratio of stalls among all video streaming clients. By taking into account the playout lead and its change, we periodically evaluate the degree of urgency of each client as regards bitstream receipt based on fuzzy logic, and then allocate the transmission resource blocks to clients jointly considering their degrees of urgency and channel conditions. The adaptive modulation and coding scheme (MCS) is applied to ensure a low transmission error rate. Our proposed scheme is suitable for practical implementation since it has low complexity, and can be easily applied in 2D video transmission and in non-OFDM systems. Simulation results, based on three left-and-right-views 3D videos and the Long Term Evolution (LTE) system, demonstrate the validity of our proposed scheme.

Pair-wise testing is an effective test planning technique for finding interaction faults using a small set of test cases. Constraint elicitation is an important process in the pair-wise testing design since constraints determine the test space; however, the constraint elicitation process has not been well studied. It usually requires manual capturing and precise definition of constraints. In this paper, we propose a constraint elicitation process that helps combinatorial test design. Our elicitation process consists of two steps: parameter combination identification and value pair determination. We conduct experiments on some test models, and demonstrate that some extracted rules match constraints and others helps to define constraints.

This paper introduces a reversible watermarking algorithm that exploits an adaptable predictor and sorting parameter customized for each image and each payload. Our proposed method relies on a well-known prediction-error expansion (PEE) technique. Using small PE values and a harmonious PE sorting parameter greatly decreases image distortion. In order to exploit adaptable tools, Gaussian weight predictor and expanded variance mean (EVM) are used as parameters in this work. A genetic algorithm is also introduced to optimize all parameters and produce the best results possible. Our results show an improvement in image quality when compared with previous conventional works.

In this research, we investigated the reliability of a 1-out-of-2 system with two-stage repair comprising hardware restoration and data reconstruction modes. Hardware restoration is normally independently executed by two modules. In contrast, we assumed that one of the modules could omit data reconstruction by replicating the data from the module during normal operation. In this 1-out-of-2 system, the two modules mutually cooperated in the recovery mode. As a first step, an evaluation model using Markov chains was constructed to derive a reliability measure: “unavailability in steady state.” Numerical examples confirmed that the reliability of the system was improved by the use of two cooperating modules. As the data reconstruction time increased, the gains in terms of system reliability also increased.

Self-luminous light sources in the real world often have nonnegligible sizes and radiate light inhomogeneously. Acquiring the model of such a light source is highly important for accurate image synthesis and understanding. In this paper, we propose an approach to measuring 4D light fields of self-luminous extended light sources by using a liquid crystal (LC) panel, i.e. a programmable optical filter and a diffuse-reflection board. The proposed approach recovers the 4D light field from the images of the board illuminated by the light radiated from a light source and passing through the LC panel. We make use of the feature that the transmittance of the LC panel can be controlled both spatially and temporally. The approach enables multiplexed sensing and adaptive sensing, and therefore is able to acquire 4D light fields more efficiently and densely than the straightforward method. We implemented the prototype setup, and confirmed through a number of experiments that our approach is effective for modeling self-luminous extended light sources in the real world.

In this paper, we first analyze the discriminative power in the Best Match (BM) 25 formula and provide its calculation method from the Bayesian point of view. The resulting, derived discriminative power is quite similar to the exponential inverse document frequency (EIDF) that we have previously proposed [1] but retains more preferable theoretical advantages. In our previous paper [1], we proposed the EIDF in the framework of the probabilistic information retrieval (IR) method BM25 to address the instance search task, which is a specific object search for videos using an image query. Although the effectiveness of our EIDF was experimentally demonstrated, we did not consider its theoretical justification and interpretation. We also did not describe the use of region-of-interest (ROI) information, which is supposed to be input to the instance search system together with the original image query showing the instance. Therefore, here, we justify the EIDF by calculating the discriminative power in the BM25 from the Bayesian viewpoint. We also investigate the effect of the ROI information for improving the instance search accuracy and propose two search methods incorporating the ROI effect into the BM25 video ranking function. We validated the proposed methods through a series of experiments using the TREC Video Retrieval Evaluation instance search task dataset.

In this paper, we address the problem of non-parametric template matching which does not assume any specific deformation models. In real-world matching scenarios, deformation between a template and a matching result usually appears to be non-rigid and non-linear. We propose a novel approach called local rigidity constraints (LRC). LRC is built based on an assumption that the local rigidity, which is referred to as structural persistence between image patches, can help the algorithm to achieve better performance. A spatial relation test is proposed to weight the rigidity between two image patches. When estimating visual similarity under an unconstrained environment, high-level similarity (e.g. with complex geometry transformations) can then be estimated by investigating the number of LRC. In the searching step, exhaustive matching is possible because of the simplicity of the algorithm. Global maximum is given out as the final matching result. To evaluate our method, we carry out a comprehensive comparison on a publicly available benchmark and show that our method can outperform the state-of-the-art method.

In this paper, we address the problem of projective template matching which aims to estimate parameters of projective transformation. Although homography can be estimated by combining key-point-based local features and RANSAC, it can hardly be solved with feature-less images or high outlier rate images. Estimating the projective transformation remains a difficult problem due to high-dimensionality and strong non-convexity. Our approach is to quantize the parameters of projective transformation with binary finite field and search for an appropriate solution as the final result over the discrete sampling set. The benefit is that we can avoid searching among a huge amount of potential candidates. Furthermore, in order to approximate the global optimum more efficiently, we develop a level-wise adaptive sampling (LAS) method under genetic algorithm framework. With LAS, the individuals are uniformly selected from each fitness level and the elite solution finally converges to the global optimum. In the experiment, we compare our method against the popular projective solution and systematically analyse our method. The result shows that our method can provide convincing performance and holds wider application scope.

As the number of surveillance cameras keeps increasing, the demand for automated traffic-monitoring systems is growing. In this paper, we propose a practical vehicle detection method for such systems. In the last decade, vehicle detection mainly has been performed by employing an image scan strategy based on sliding windows whereby a pre-trained appearance model is applied to all image areas. In this approach, because the appearance models are built from vehicle sample images, the normalization of the scales and aspect ratios of samples can significantly influence the performance of vehicle detection. Thus, to successfully apply sliding window schemes to detection, it is crucial to select the normalization sizes very carefully in a wise manner. To address this, we present a novel vehicle detection technique. In contrast to conventional methods that determine the normalization sizes without considering given scene conditions, our technique first learns local region-specific size models based on scene-contextual clues, and then utilizes the obtained size models to normalize samples to construct more elaborate appearance models, namely local size-specific classifiers (LSCs). LSCs can provide advantages in terms of both accuracy and operational speed because they ignore unnecessary information on vehicles that are observable in faraway areas from each sliding window position. We conduct experiments on real highway traffic videos, and demonstrate that the proposed method achieves a 16% increased detection accuracy with at least 3 times faster operational speed compared with the state-of-the-art technique.

In this letter, standard particle swarm optimization (PSO) with the center-symmetric trimmed correlation matrix and the orthogonal projection technique is firstly presented for blind carrier frequency offset estimation under interleaved orthogonal frequency division multiple access (OFDMA) uplink systems. It doesn't require eigenvalue decomposition and only needs a single OFDMA data block. Second, this letter also presents adaptive multiple inertia weights with Newton method to speed up the convergence of standard PSO iteration process. Meanwhile, the advantage of inherent interleaved OFDMA signal structure also is exploited to conquer the problems of local optimization and the effect of ambiguous peaks for the proposed approaches. Finally, several simulation results are provided for illustration and comparison.

Query response times are critical for cluster computing applications in data centers. In this letter, we argue that to optimize the network performance, we should consider the latency of the flows suffered loss, which are called tardy flows. We propose two tardy flow scheduling algorithms and show that our work offers significant performance gains through performance analysis and simulations.

In this letter, we present a spectrally efficient multicast method which enables a transmitter to simultaneously transmit multiple multicast streams without any interference among multicast groups. By using unique combiners at receivers with multiple antennas within each multicast group, the proposed method simplifies multiple channels between the transmitter and the receivers to an equivalent channel. In addition, we establish the sufficient condition for the system configuration which should be satisfied for the channel simplification and provide a combiner design technique for the receivers. To remove interference among multicast groups, the precoder for the transmitter is designed by utilizing the equivalent channels. By exploiting time resources efficiently, the channel simplification (CS) based method achieves a higher sum rate than the time division multiplexing (TDM) based method, which the existing multicast techniques fundamentally employ, at high signal-to-noise ratio (SNR) regime. Furthermore, we present a multicast method combining the CS based method with the TDM based method to utilize the benefits of both methods. Simulation results successfully demonstrate that the combined multicast method obtains a better sum rate performance at overall SNR regime.

Circuit performance of SiC-MOSFET-based bidirectional isolated DC/DC converters is investigated based on circuit simulation with the physically accurate compact device model HiSIM_HV. It is demonstrated that the combined optimization of the MOSFETs Ron and of the inductances in the transformer can enable a conversion efficiency of more than 97%. The simulation study also verifies that the possible efficiency improvements are diminished due to the MOSFET-performance degradation, namely the carrier-mobility reduction, which results in a limitation of the possible Ron reduction. It is further demonstrated that an optimization of the MOSFET-operation conditions is important to utilize the resulting higher MOSFET performance for achieving additional converter efficiency improvements.