The ionospheric clutter in High Frequency Surface Wave Radar (HFSWR) is the reflection of electromagnetic waves from the ionosphere back to the receiver, which should be suppressed as much as possible for the primary purpose of target detection in HFSWR. However, ionospheric clutter contains vast quantities of ionospheric state information. By studying ionospheric clutter, some of the relevant ionospheric parameters can be inferred, especially during the period of typhoons, when the ionospheric state changes drastically affected by typhoon-excited gravity waves, and utilizing the time-frequency characteristics of ionospheric clutter at typhoon time, information such as the trend of electron concentration changes in the ionosphere and the direction of the typhoon can be obtained. The results of the processing of the radar data showed the effectiveness of this method.

Mission-critical monitoring services, such as finding criminals with a monitoring camera, require rapid detection of newly updated data, where suppressing delay is desirable. Taking this direction, this paper proposes a network design scheme to minimize this delay for monitoring services that consist of Internet-of-Things (IoT) devices located at terminal endpoints (TEs), databases (DB), and applications (APLs). The proposed scheme determines the allocation of DB and APLs and the selection of the server to which TE belongs. DB and APL are allocated on an optimal server from multiple servers in the network. We formulate the proposed network design scheme as an integer linear programming problem. The delay reduction effect of the proposed scheme is evaluated under two network topologies and a monitoring camera system network. In the two network topologies, the delays of the proposed scheme are 78 and 80 percent, compared to that of the conventional scheme. In the monitoring camera system network, the delay of the proposed scheme is 77 percent compared to that of the conventional scheme. These results indicate that the proposed scheme reduces the delay compared to the conventional scheme where APLs are located near TEs. The computation time of the proposed scheme is acceptable for the design phase before the service is launched. The proposed scheme can contribute to a network design that detects newly added objects quickly in the monitoring services.

In this article, a new Beamforming Network (BFN) realized in Broadside Coupled Stripline (BCS) is proposed to feed 1×4 and 2×2 arrays antenna at 28 GHZ-Band. The new BFN is composed only of couplers and phase shifters. It doesn't require any crossover compared to the conventional Butler Matrix (BM) which requires two crossovers. The tight coupling and low loss characteristics of the BCS allow a design of a compact and wideband BFN. The new BFN produces the phase differences of (±90°) and (±45°, ±135°) respectively in x- and y-directions. Its integration with a 1×4 linear array antenna reduces the array area by 70% with an improvement of the gain performance compared with the conventional array. The integration with a 2×2 array allows the realization of a full 2-D beam scanning. The proposed concept has been verified experimentally by measuring the fabricated prototypes of the BFN, the 1-D and 2-D patch arrays antennas. The measured 11.5 dBi and 11.3 dBi maximum gains are realized in θ0 = 14° and (θ0, φ0) = (45°,345°) directions respectively for the 1-D and 2-D patch arrays. The physical area of the fabricated BFN is only (0.37λ0×0.3λ0×0.08λ0), while the 1-D array and 2-D array antennas areas without feeding transmission lines are respectively (0.5λ0×2.15λ0×0.08λ0) and (0.9λ0×0.8λ0×0.08λ0).

Today's electronic devices must meet many requirements, such as those related to performance, limits to the radiated electromagnetic field, size, etc. For such a design, the requirement is to have a solution that simultaneously meets multiple objectives that sometimes include conflicting requirements. In addition, it is also necessary to consider uncertain parameters. This paper proposes a new combination of statistical analysis using the Polynomial Chaos (PC) method for dealing with the random and multi-objective satisfactory design using the Preference Set-based Design (PSD) method. The application in this paper is an Electromagnetic Interference (EMI) filter for a practical case, which includes plural element parameters and uncertain parameters, which are resistors at the source and load, and the performances of the attenuation characteristics. The PC method generates simulation data with high enough accuracy and good computational efficiency, and these data are used as initial data for the meta-modeling of the PSD method. The design parameters of the EMI filter, which satisfy required performances, are obtained in a range by the PSD method. The authors demonstrate the validity of the proposed method. The results show that applying a multi-objective design method using PSD with a statistical method using PC to handle the uncertain problem can be applied to electromagnetic designs to reduce the time and cost of product development.

In the cellular system, the Worst Case User (WCU), whose distances to three nearest BSs are the similar, usually achieves the lowest performance. Improving user performance, especially the WCU, is a big problem for both network designers and operators. This paper works on the WCU in terms of coverage probability analysis by the stochastic geometry tool and data rate optimization with the transmission power constraint by the reinforcement learning technique under the Stretched Pathloss Model (SPLM). In analysis, only fast fading from the WCU to the serving Base Stations (BSs) is taken into the analysis to derive the lower bound coverage probability. Furthermore, the paper assumes that the Coordinated Multi-Point (CoMP) technique is only employed for the WCU to enhance its downlink signal and avoid the explosion of Intercell Interference (ICI). Through the analysis and simulation, the paper states that to improve the WCU performance under bad wireless environments, an increase in transmission power can be a possible solution. However, in good environments, the deployment of advanced techniques such as Joint Transmission (JT), Joint Scheduling (JS), and reinforcement learning is an suitable solution.

In recent years, physical layer security (PLS), which utilizes the inherent randomness of wireless signals to perform encryption at the physical layer, has attracted attention. We propose chaos modulation as a PLS technique. In addition, a method for encryption using a special encoder of polar codes has been proposed (PLS-polar), in which PLS can be easily achieved by encrypting the frozen bits of a polar code. Previously, we proposed a chaos-modulated polar code transmission method that can achieve high-quality and improved-security transmission using frozen bit encryption in polar codes. However, in principle, chaos modulation requires maximum likelihood sequence estimation (MLSE) for demodulation, and a large number of candidates for MLSE causes characteristic degradation in the low signal-to-noise ratio region in chaos polar transmission. To address this problem, in this study, we propose a versatile frozen bit method for polar codes, in which the frozen bits are also used to reduce the number of MLSE candidates for chaos demodulation. The numerical results show that the proposed method shows a performance improvement by 1.7dB at a block error rate of 10-3 with a code length of 512 and a code rate of 0.25 compared with that of conventional methods. We also show that the complexity of demodulation can be reduced to 1/16 of that of the conventional method without degrading computational security. Furthermore, we clarified the effective region of the proposed method when the code length and code rate were varied.

Hybrid automatic repeat request (HARQ) is an essential technology that efficiently reduces the transmission error rate. However, for ultra-reliable low latency communications (URLLC) in the 5th generation mobile communication systems and beyond, the increase in latency due to retransmission must be minimized in HARQ. In this paper, we propose a highly-efficient low-latency HARQ method built on non-orthogonal multiple access (NOMA) for URLLC while minimizing the performance loss for coexisting services (use cases) such as enhanced mobile broadband (eMBB). The proposed method can be seen as an extension of the conventional link-level non-orthogonal HARQ to the system-level protocol. This mitigates the problems of the conventional link-level non-orthogonal HARQ, which are decoding error under poor channel conditions and an increase in transmission delay due to restrictions in retransmission timing. In the proposed method, delay-sensitive URLLC packets are preferentially multiplexed with best-effort eMBB packets in the same channel using superposition coding to reduce the transmission latency of the URLLC packet while alleviating the throughput loss in eMBB. This is achieved using a weighted channel-aware resource allocator (scheduler). The inter-packet interference multiplexed in the same channel is removed using a successive interference canceller (SIC) at the receiver. Furthermore, the transmission rates for the initial transmission and retransmission are controlled in an appropriate manner for each service in order to deal with decoding errors caused by error in transmission rate control originating from a time varying channel. We show that the proposed method significantly improves the overall performance of a system that simultaneously provides eMBB and URLLC services.

Recent years have seen a decline in the art of analog IC design even though analog interface and analog signal processing remain just as essential as ever. While there are many contributing factors, four specific pressures which contribute the most to the loss of creativity and innovation within analog practice are examined: process evolution, risk aversion, digitally assisted analog, and corporate culture. Despite the potency of these forces, none are found to be insurmountable obstacles to reinvigorating the industry. A more creative future is within our reach.

This paper presents a high-NIR sensitivity SOI-gate lock-in pixel with improved modulation contrast. The proposed pixel has a shallow buried channel and intermediate gates to create both a high lateral electric field and a potential barrier to parasitic light sensitivity. Device simulation results showed that parasitic light sensitivity reduced from 13.7% to 0.13% compared to the previous structure.

This paper presents on-chip characterization of electrostatic discharge (ESD) impacts applied on the Si-substrate backside of a flip-chip mounted integrated circuit (FC-IC) chip. An FC-IC chip has an open backside and there is a threat of reliability problems and malfunctions caused by the backside ESD. We prepared a test FC-IC chip and measured Si-substrate voltage fluctuations on its frontside by an on-chip monitor (OCM) circuit. The voltage surges as large as 200mV were observed on the frontside when a 200-V ESD gun was irradiated through a 5kΩ contact resistor on the backside of a 350μm thick Si substrate. The distribution of voltage heights was experimentally measured at 20 on-chip locations among thinned Si substrates up to 40μm, and also explained in full-system level simulation of backside ESD impacts with the equivalent models of ESD-gun operation and FC-IC chip assembly.

This brief presents a side-channel attack (SCA) technique on a high-speed asynchronous successive approximation register (SAR) analog-to-digital converter (ADC). The proposed dual neural network based on multiple noise waveforms separately discloses sign and absolute value information of input signals which are hidden by the differential structure and high-speed asynchronous operation. The target SAR ADC and on-chip noise monitors are designed on a single prototype chip for SCA demonstration. Fabricated in 40 nm, the experimental results show the proposed attack on the asynchronous SAR ADC successfully restores the input data with a competitive accuracy within 300 mV rms error.

Reducing on-chip microwave crosstalk is crucial for semiconductor spin qubit integration. Toward crosstalk reduction and qubit integration, we investigate on-chip microwave crosstalk for gate electrode pad designs with (i) etched trenches between contact pads or (ii) contact pads with reduced sizes. We conclude that the design with feature (ii) is advantageous for high-density integration of semiconductor qubits with small crosstalk (below -25 dB at 6 GHz), favoring the introduction of flip-chip bonding.

We have proposed and demonstrated a device fabrication process of physically defined quantum dots utilizing electron beam lithography employing a negative-tone resist toward high-density integration of silicon quantum bits (qubits). The electrical characterization at 3.8K exhibited so-called Coulomb diamonds, which indicates successful device operation as single-electron transistors. The proposed device fabrication process will be useful due to its high compatibility with the large-scale integration process.

The transfer distance of the wireless power transfer (WPT) system with relay coil is longer, so this technology have a better practical perspective. But the location of the relay coil has a great impact on the transmission efficiency of the WPT system, and it is not easy to analyze. In order to research the influence law of the relay coil location on the transmission efficiency and obtain the optimal location, the paper firstly proposes the concept of relay coil location factor. And based on the location factor, a novel method for studying the influence of the relay coil location on the transmission efficiency is proposed. First, the mathematical model between the transmission efficiency and the location factor is built. Next, considering the transfer distance, coil radius, coil turns and load resistance, a lot of simulations are carried out to analyze the influence of the location factor on the transmission efficiency, respectively. The influence law and the optimal location factor were obtained with different parameters. Finally, a WPT system with relay coil was built for experiments. And the experiment results verify that the theoretical analysis is correct and the proposed method can simplify the analysis progress of the influence of relay coil location on the transmission efficiency. Moreover, the proposed method and the research conclusions can provide guidance for designing the multiple coils structure WPT system.

This paper provides a new method to implement substrate integrated defected ground structure (SIDGS)-based bandpass filter (BPF) with adjustable frequency and controllable bandwidth. Compared with previous literature, this method implements a new SIDGS-like resonator capable of tunable frequency in the same plane as the slotted line using a varactor diode, increasing the design flexibility. In addition, the method solves the problem that the tunable BPF constituted by the SIDGS resonator cannot control the bandwidth by introducing a T-shaped non-resonant unit. The theoretical design method and the structural design are shown. Moreover, the configured structure is fabricated and measured to show the validity of the design method in this paper.

Human motion prediction has always been an interesting research topic in computer vision and robotics. It means forecasting human movements in the future conditioning on historical 3-dimensional human skeleton sequences. Existing predicting algorithms usually rely on extensive annotated or non-annotated motion capture data and are non-adaptive. This paper addresses the problem of few-frame human motion prediction, in the spirit of the recent progress on manifold learning. More precisely, our approach is based on the insight that achieving an accurate prediction relies on a sufficiently linear expression in the latent space from a few training data in observation space. To accomplish this, we propose Regressive Gaussian Process Latent Variable Model (RGPLVM) that introduces a novel regressive kernel function for the model training. By doing so, our model produces a linear mapping from the training data space to the latent space, while effectively transforming the prediction of human motion in physical space to the linear regression analysis in the latent space equivalent. The comparison with two learning motion prediction approaches (the state-of-the-art meta learning and the classical LSTM-3LR) demonstrate that our GPLVM significantly improves the prediction performance on various of actions in the small-sample size regime.

Various haze removal methods based on the atmospheric scattering model have been presented in recent years. Most methods have targeted strong haze images where light is scattered equally in all color channels. This paper presents a haze removal method using near-infrared (NIR) images for relatively weak haze images. In order to recover the lost edges, the presented method first extracts edges from an appropriately weighted NIR image and fuses it with the color image. By introducing a wavelength-dependent scattering model, our method then estimates the transmission map for each color channel and recovers the color more naturally from the edge-recovered image. Finally, the edge-recovered and the color-recovered images are blended. In this blending process, the regions with high lightness, such as sky and clouds, where unnatural color shifts are likely to occur, are effectively estimated, and the optimal weighting map is obtained. Our qualitative and quantitative evaluations using 59 pairs of color and NIR images demonstrated that our method can recover edges and colors more naturally in weak haze images than conventional methods.

Video-based point cloud compression (V-PCC) utilizes video compression technology to efficiently encode dense point clouds providing state-of-the-art compression performance with a relatively small computation burden. V-PCC converts 3-dimensional point cloud data into three types of 2-dimensional frames, i.e., occupancy, geometry, and attribute frames, and encodes them via video compression. On the other hand, the quality of these frames may be degraded due to video compression. This paper proposes an adaptive neural network-based post-processing filter on attribute frames to alleviate the degradation problem. Furthermore, a novel training method using occupancy frames is studied. The experimental results show average BD-rate gains of 3.0%, 29.3% and 22.2% for Y, U and V respectively.

Personalized stock recommendations aim to suggest stocks tailored to individual investor needs, significantly aiding the financial decision making of an investor. This study shows the advantages of incorporating context into personalized stock recommendation systems. We embed item contextual information such as technical indicators, fundamental factors, and business activities of individual stocks. Simultaneously, we consider user contextual information such as investors' personality traits, behavioral characteristics, and attributes to create a comprehensive investor profile. Our model incorporating contextual information, validated on novel stock recommendation tasks, demonstrated a notable improvement over baseline models when incorporating these contextual features. Consistent outperformance across various hyperparameters further underscores the robustness and utility of our model in integrating stocks' features and investors' traits into personalized stock recommendations.

This paper proposes a fault-resilient ROS platform supporting rapid fault detection and recovery. The platform employs heartbeat-based fault detection and node replication-based recovery. Our prototype implementation on top of the ROS Melodic shows a great performance in evaluations with a Nvidia development board and an inverted pendulum device.