Linear codes with a few weights have many applications in secret sharing schemes, authentication codes, association schemes and strongly regular graphs, and they are also of importance in consumer electronics, communications and data storage systems. In this paper, based on the theory of defining sets, we present a class of five-weight linear codes over $mathbb{F}_p$(p is an odd prime), which include an almost optimal code with respect to the Griesmer bound. Then, we use exponential sums to determine the weight distribution.

This paper proposes a novel weight derivation method to improve adaptive array interference suppression performance based on our previously conceived sample matrix inversion algorithm using common correlation matrix (CCM-SMI), by data-aided approach. In recent broadband wireless communication system such as orthogonal frequency division multiplexing (OFDM) which possesses lots of subcarriers, the computation complexity is serious problem when using SMI algorithm to suppress unknown interference. To resolve this problem, CCM based SMI algorithm was previously proposed. It computes the correlation matrix by the received time domain signals before fast Fourier transform (FFT). However, due to the limited number of pilot symbols, the estimated channel state information (CSI) is often incorrect. It leads limited interference suppression performance. In this paper, we newly employ a data-aided channel state estimation. Decision results of received symbols are obtained by CCM-SMI and then fed-back to the channel estimator. It assists improving CSI estimation accuracy. Computer simulation result reveals that our proposal accomplishes better bit error rate (BER) performance in spite of the minimum pilot symbols with a slight additional computation complexity.

Side-channel (SC) leakage from a cryptographic device chip is simulated as the dynamic current flowing out of the chip. When evaluating the simulated current, an evaluation by comparison with an actual measurement is essential; however, it is difficult to compare them directly. This is because a measured waveform is typically the output voltage of probe placed at the observation position outside the chip, and the actual dynamic current is modified by several transfer impedances. Therefore, in this paper, the probe voltage is converted into the dynamic current by using an EMC macro-model of a cryptographic device being evaluated. This paper shows that both the amplitude and the SC analysis (correlation power analysis and measurements to disclosure) results of the simulated dynamic current were evaluated appropriately by using the EMC macro-model. An evaluation confirms that the shape of the simulated current matches the measured one; moreover, the SC analysis results agreed with the measured ones well. On the basis of the results, it is confirmed that a register-transfer level (RTL) simulation of the dynamic current gives a reasonable estimation of SC traces.

C-C successive approximation register analog-to-digital converter (C-C SAR-ADC) is space-saving architecture compared to SAR-ADC with binary weighted capacitive digital-to-analog converter (CDAC). However, the accuracy of C-C SAR-ADC is degraded due to parasitic capacitance of floating nodes. This paper proposes an algorithm calibrating the non-linearity by γ-estimation to accurately estimate radix greater than 2 required to realize C-C SAR-ADC. Behavioral analyses show that the radix γ-estimation error become within 1.5, 0.4 and 0.1% in case of 8-, 10- and 12-bit resolution ADC, respectively. SPICE simulations show that the γ-estimation satisfies the requirement of 10-bit resolution C-C SAR-ADC. The C-C SAR-ADC using γ-estimation achieves 9.72bit of ENOB, 0.8/-0.5LSB and 0.5/-0.4LSB of DNL/INL.

In this paper, we investigate a model-free design of decentralized event-triggered mechanism for networked control systems (NCSs). The approach aims at simultaneously tuning the optimal parameters for the controller and the event-triggered condition, such that a prescribed cost function can be minimized. To achieve this goal, we employ the Bayesian optimization (BO), which is known to be an automatic tuning framework for finding the optimal solution to the black-box optimization problem. Thanks to its efficient search strategy for the global optimum, the BO allows us to design the event-triggered mechanism with relatively a small number of experimental evaluations. This is particularly suited for NCSs where network resources such as the limited life-time of battery powered devices are limited. Some simulation examples illustrate the effectiveness of the approach.

This paper proposes a route calculation method for a bicycle navigation system that complies with traffic regulations. The extension of the node map and three kinds of route calculation methods are constructed and evaluated on the basis of travel times and system acceptability survey results. Our findings reveal the effectiveness of the proposed route calculation method and the acceptability of the bicycle navigation system that included the method.

Input devices based on direct touch have replaced traditional ones and become the mainstream interactive technology for handheld devices. Although direct touch interaction proves to be easy to use, its problems, e.g. the occlusion problem and the fat finger problem, lower user experience. Camera-based mobile interaction is one of the solutions to overcome the problems. There are two typical interaction styles to generate camera-based pointing interaction for handheld devices: move the device or move an object before the camera. In the first interaction style, there are two approaches to move a cursor's position across the handheld display: move it towards the same direction or the opposite direction which the device moves to. In this paper, the results of a comparison research, which compared the pointing performances of three camera-based pointing techniques, are presented. All pointing techniques utilized input from the rear-facing camera. The results indicate that the interaction style of moving a finger before the camera outperforms the other one in efficiency, accuracy, and throughput. The results also indicate that within the interaction style of moving the device, the cursor positioning style of moving the cursor to the opposite direction is slightly better than the other one in efficiency and throughput. Based on the findings, we suggest giving priority to the interaction style of moving a finger when deploying camera-based pointing techniques on handheld devices. Given that the interaction style of moving the device supports one-handed manipulation, it also worth deploying when one-handed interaction is needed. According to the results, the cursor positioning style of moving the cursor towards the opposite direction which the device moves to may be a better choice.

For exploration of the functional use of dielectric anisotropy of liquid crystals (LCs), we investigated the dynamic response of molecular alignment in a nematic-phase LC cell with compressive force-induced flow behavior. The results showed that the initial alignment and thickness of the LC layer affect the capacitance of the cell when mechanical pressure is applied.

This letter presents an image quality assessment (IQA) metric for scanning electron microscopy (SEM) images based on texture inpainting. Inspired by the observation that the texture information of SEM images is quite sensitive to distortions, a texture inpainting network is first trained to extract texture features. Then the weights of the trained texture inpainting network are transferred to the IQA network to help it learn an effective texture representation of the distorted image. Finally, supervised fine-tuning is conducted on the IQA network to predict the image quality score. Experimental results on the SEM image quality dataset demonstrate the advantages of the presented method.

Universal filtered multicarrier (UFMC) systems offer a flexibility of filtering sub-bands with arbitrary bandwidth to suppress out-of-band (OoB) emission, while keeping the orthogonality between subcarriers in one sub-band. Oscillator discrepancies between the transmitter and receiver induce carrier frequency offset (CFO) in practical systems. In this paper, we propose a novel CFO estimation method for UFMC systems that has very low computational complexity and can then be used in practical systems. In order to fully exploit the coherence bandwidth of the channel, the training symbols are designed to have several identical segments in the frequency domain. As a result, the integral part of CFO can be estimated by simply determining the correlation between received signal and the training symbol. Simulation results show that the proposed method can achieve almost the same performance as an existing method and even a better performance in channels that have small decay parameter values. The proposed method can also be used in other multicarrier systems, such as orthogonal frequency division multiplexing (OFDM).

Image deformations caused by different steganographic methods are typically extremely small and highly similar, which makes their detection and identification to be a difficult task. Although recent steganalytic methods using deep learning have achieved high accuracy, they have been made to detect stego images to which specific steganographic methods have been applied. In this letter, a staganalytic method is proposed that uses hierarchical residual neural networks (ResNet), allowing detection (i.e. classification between stego and cover images) and identification of four spatial steganographic methods (i.e. LSB, PVD, WOW and S-UNIWARD). Experimental results show that using hierarchical ResNets achieves a classification rate of 79.71% in quinary classification, which is approximately 23% higher compared to using a plain convolutional neural network (CNN).

This letter proposes the use of a novel time-modulated array structure to estimate the direction of arrival (DOA). Such a time-modulated coprime array (TMCA) is obtained by exchanging a coprime array's phase shifter for a radio frequency (RF) switch. Compared with a traditional coprime array, the TMCA's structure is much simpler, and it has a higher degree of freedom and resolution compared with a time-modulated uniform linear array (TMULA) due to its exploitation of the virtual array's equivalent signals. Theoretical analysis and experimental results have validated the effectiveness of the proposed structure and method and have confirmed that a TMCA's DOA performance is better than that of a TMULA using the same number of antennas.

A method for the calibration of S11 at the front surface of a material for a coaxial-feed type cut-off circular waveguide with three reference materials inserted and no short termination condition was proposed as a preliminary step for dielectric measurement in liquids. The equations for jig calibration of S11 with these reference materials were first defined, and the electrostatic capacitance for the analytical model unique to the jig was quantified by substituting the reflection constant (calculated at frequencies of 0.50, 1.5 and 3.0 GHz using the mode-matching (MM) technique) into the equivalent circuit, assuming the sample liquid in the jig. The accuracy of S11 measured using the proposed method was then verified. S11 for the front surface of the sample material was also measured with various liquids in the jig after calibration, and the dielectric constants of the liquids were estimated as an inverse problem based on comparison of S11 calculated from an analytical model using EM analysis via the MM technique with the measured S11 values described above. The effectiveness of the proposed S11 calibration method was verified by comparison with dielectric constants estimated after S11 SOM (short, open and reference material) calibration and similar, with results showing favorable agreement with each method.

We propose an iterative single-image haze-removal method that first divides images with haze into regions in which haze-removal processing is difficult and then estimates the ambient light. The existing method has a problem wherein it often overestimates the amount of haze in regions where there is a large distance between the location the photograph was taken and the subject of the photograph; this problem prevents the ambient light from being estimated accurately. In particular, it is often difficult to accurately estimate the ambient light of images containing white and sky regions. Processing those regions in the same way as other regions has detrimental results, such as darkness or unnecessary color change. The proposed method divides such regions in advance into multiple small regions, and then, the ambient light is estimated from the small regions in which haze removal is easy to process. We evaluated the proposed method through some simulations, and found that the method achieves better haze reduction accuracy even than the state-of-the art methods based on deep learning.

A differential on chip oscillator (OCO) is proposed in this paper for low supply voltage, high frequency accuracy and fast startup. The differential architecture helps the OCO achieve a good power supply rejection ratio (PSRR) without using a regulator so as to make the OCO suitable for a low power supply voltage of 1.38V. A reference voltage generator is also developed to generate two output voltages lower than Vbe for low supply voltage operation. The output frequency is locked to 48MHz by a frequency-locked loop (FLL) and a 3.3-ppm/°C temperature coefficient of frequency is realized by the differential voltage ratio adjusting (differential VRA) technique. The startup time is only 1.47μs because the differential OCO is not necessary to charge a big capacitor for ripple reduction.

In this paper, we present a novel method for vehicle detection based on the Faster R-CNN frame. We integrate MobileNet into Faster R-CNN structure. First, the MobileNet is used as the base network to generate the feature map. In order to retain the more information of vehicle objects, a fusion strategy is applied to multi-layer features to generate a fused feature map. The fused feature map is then shared by region proposal network (RPN) and Fast R-CNN. In the RPN system, we employ a novel dimension cluster method to predict the anchor sizes, instead of choosing the properties of anchors manually. Our detection method improves the detection accuracy and saves computation resources. The results show that our proposed method respectively achieves 85.21% and 91.16% on the mean average precision (mAP) for DIOR dataset and UA-DETRAC dataset, which are respectively 1.32% and 1.49% improvement than Faster R-CNN (ResNet152). Also, since less operations and parameters are required in the base network, our method costs the storage size of 42.52MB, which is far less than 214.89MB of Faster R-CNN(ResNet50).

This paper expands our previously proposed semi-blind uplink interference suppression scheme for multicell multiuser massive MIMO systems to support multi modulus signals. The original proposal applies the channel state information (CSI) aided blind adaptive array (BAA) interference suppression after the beamspace preprocessing and the decision feedback channel estimation (DFCE). BAA is based on the constant modulus algorithm (CMA) which can fully exploit the degree of freedom (DoF) of massive antenna arrays to suppress both inter-user interference (IUI) and inter-cell interference (ICI). Its effectiveness has been verified under the extensive pilot contamination constraint. Unfortunately, CMA basically works well only for constant envelope signals such as QPSK and thus the proposed scheme should be expanded to cover QAM signals for more general use. This paper proposes to apply the multi modulus algorithm (MMA) and the minimum mean square error weight derivation based on data-aided sample matrix inversion (MMSE-SMI). It can successfully realize interference suppression even with the use of multi-level envelope signals such as 16QAM with satisfactorily outage probability performance below the fifth percentile.

Since 2020, the service of the 5th generation (5G) mobile phone has been started. In order to increase the transmission speed in 5G mobile phones, the multi-level of the modulated signal is advanced, and for that, the power amplifier (PA) high linearity is required even at low output power. In accordance with this, the review of the linearization technology of a PA has become important. As a performance index of the distortion of the PA, the output power dependence of the gain and phase, the AM (Amplitude Modulation)-AM/PM (Phase Modulation) characteristic is well known. There has been a lot of consideration for the AM-AM/PM characteristics of PA. The AM-AM/PM characteristics are affected by both source and load impedances. In this paper, a single-stage HBT (Hetero-junction Bipolar Transistor) PA is described by a simple linear equivalent circuit with multiple parameter sets. Each parameter set is defined according to the PA output power level. With this simple model, we investigated the change of AM-AM/PM characteristics when the reactance parts of source and load impedances was changed. It has become clear that change in the AM-AM/PM characteristics of the PA when the parameters were changed was mainly due to the change in the AM-AM/PM characteristics at the base node.

This paper considers a distributed subgradient method for online optimization with event-triggered communication over multi-agent networks. At each step, each agent obtains a time-varying private convex cost function. To cooperatively minimize the global cost function, these agents need to communicate each other. The communication with neighbor agents is conducted by the event-triggered method that can reduce the number of communications. We demonstrate that the proposed online algorithm achieves a sublinear regret bound in a dynamic environment with slow dynamics.