The increasing demand for high-performance computing in recent years has led to active research on massively parallel systems. The interconnection network in a massively parallel system interconnects hundreds of thousands of processing elements so that they can process large tasks while communicating among others. By regarding the processing elements as nodes and the links between processing elements as edges, respectively, we can discuss various problems of interconnection networks in the framework of the graph theory. Many topologies have been proposed for interconnection networks of massively parallel systems. The hypercube is a very popular topology and it has many variants. The cross-cube is such a topology, which can be obtained by adding one extra edge to each node of the hypercube. The cross-cube reduces the diameter of the hypercube, and allows cycles of odd lengths. Therefore, we focus on the cross-cube and propose an algorithm that constructs disjoint paths from a node to a set of nodes. We give a proof of correctness of the algorithm. Also, we show that the time complexity and the maximum path length of the algorithm are O(n3 log n) and 2n - 3, respectively. Moreover, we estimate that the average execution time of the algorithm is O(n2) based on a computer experiment.

Song-level feature summarization is fundamental for the browsing, retrieval, and indexing of digital music archives. This study proposes a deep neural network model, CQTXNet, for extracting song-level feature summary for cover song identification. CQTXNet incorporates depth-wise separable convolution, residual network connections, and attention models to extend previous approaches. An experimental evaluation of the proposed CQTXNet was performed on two publicly available cover song datasets by varying the number of network layers and the type of attention modules.

Noisy labels in training data can significantly harm the performance of deep neural networks (DNNs). Recent research on learning with noisy labels uses a property of DNNs called the memorization effect to divide the training data into a set of data with reliable labels and a set of data with unreliable labels. Methods introducing semi-supervised learning strategies discard the unreliable labels and assign pseudo-labels generated from the confident predictions of the model. So far, this semi-supervised strategy has yielded the best results in this field. However, we observe that even when models are trained on balanced data, the distribution of the pseudo-labels can still exhibit an imbalance that is driven by data similarity. Additionally, a data bias is seen that originates from the division of the training data using the semi-supervised method. If we address both types of bias that arise from pseudo-labels, we can avoid the decrease in generalization performance caused by biased noisy pseudo-labels. We propose a learning method with noisy labels that introduces unbiased pseudo-labeling based on causal inference. The proposed method achieves significant accuracy gains in experiments at high noise rates on the standard benchmarks CIFAR-10 and CIFAR-100.

Distance-aware quality adaptation is a potential approach to reduce the resource requirement for the transmission and rendering of textured 3D meshes. In this paper, we carry out a subjective experiment to investigate the effects of the distance from the camera on the perceptual quality of textured 3D meshes. Besides, we evaluate the effectiveness of eight image-based objective quality metrics in representing the user's perceptual quality. Our study found that the perceptual quality in terms of mean opinion score increases as the distance from the camera increases. In addition, it is shown that normalized mutual information (NMI), a full-reference objective quality metric, is highly correlated with subjective scores.

This paper proposes a novel application of coded apertures (CAs) for visual information hiding. CA is one of the representative computational photography techniques, in which a patterned mask is attached to a camera as an alternative to a conventional circular aperture. With image processing in the post-processing phase, various functions such as omnifocal image capturing and depth estimation can be performed. In general, a watermark embedded as high-frequency components is difficult to extract if captured outside the focal length, and defocus blur occurs. Installation of a CA into the camera is a simple solution to mitigate the difficulty, and several attempts are conducted to make a better design for stable extraction. On the contrary, our motivation is to design a specific CA as well as an information hiding scheme; the secret information can only be decoded if an image with hidden information is captured with the key aperture at a certain distance outside the focus range. The proposed technique designs the key aperture patterns and information hiding scheme through evolutionary multi-objective optimization so as to minimize the decryption error of a hidden image when using the key aperture while minimizing the accuracy when using other apertures. During the optimization process, solution candidates, i.e., key aperture patterns and information hiding schemes, are evaluated on actual devices to account for disturbances that cannot be considered in optical simulations. Experimental results have shown that decoding can be performed with the designed key aperture and similar ones, that decrypted image quality deteriorates as the similarity between the key and the aperture used for decryption decreases, and that the proposed information hiding technique works on actual devices.

In this paper, we present a novel photometric compensation network named CASEformer, which is built upon the Swin module. For the first time, we combine coordinate attention and channel attention mechanisms to extract rich features from input images. Employing a multi-level encoder-decoder architecture with skip connections, we establish multiscale interactions between projection surfaces and projection images, achieving precise inference and compensation. Furthermore, through an attention fusion module, which simultaneously leverages both coordinate and channel information, we enhance the global context of feature maps while preserving enhanced texture coordinate details. The experimental results demonstrate the superior compensation effectiveness of our approach compared to the current state-of-the-art methods. Additionally, we propose a method for multi-surface projection compensation, further enriching our contributions.

In this paper, we explore privacy-preserving techniques in federated learning, including those can be used with both neural networks and decision trees. We begin by identifying how information can be leaked in federated learning, after which we present methods to address this issue by introducing two privacy-preserving frameworks that encompass many existing privacy-preserving federated learning (PPFL) systems. Through experiments with publicly available financial, medical, and Internet of Things datasets, we demonstrate the effectiveness of privacy-preserving federated learning and its potential to develop highly accurate, secure, and privacy-preserving machine learning systems in real-world scenarios. The findings highlight the importance of considering privacy in the design and implementation of federated learning systems and suggest that privacy-preserving techniques are essential in enabling the development of effective and practical machine learning systems.

Thermoelectric effect of Ga-Sn-O (GTO) thin films has been investigated for Internet-of-Things application. It is found that the amorphous GTO thin films provide higher power factors (PF) than the polycrystalline ones, which is because grain boundaries block the electron conduction in the polycrystalline ones. It is also found that the GTO thin films annealed in vacuum provide higher PF than those annealed in air, which is because oxygen vacancies are terminated in those annealed in air. The PF and dimensionless figure of merit (ZT) is not so excellent, but the cost effectiveness is excellent, which is the most important for some examples of the Internet-of-Things application.

In this paper, a novel trench MOS barrier Schottky contact super barrier rectifier (TMB-SSBR) is proposed by combining the advantages of vertical SSBR and conventional TMBS. The operation mechanism and simulation verification are presented. TMB-SSBR consists of MOS trenches with a vertical SSBR grid which replaces the Schottky diode in the mesa of a TMBS. Due to the presence of top p-n junction in the proposed TMB-SSBR, the image force barrier lowering effect is eliminated, the pinching off electric field effect by MOS trenches is weakened, so that the mesa surface electric field is much larger than that in conventional TMBS. Therefore, the mesa width is enlarged and the n-drift concentration is slightly increased, which results in a low specific on-resistance and a good tradeoff between reverse leakage currents and forward voltages. Compared to a conventional TMBS, simulation results show that, with the same breakdown voltage of 124V and the same reverse leakage current at room temperature, TMB-SSBR increases the figure of merit (FOM, equates to VB2/Ron, sp) by 25.5%, and decreases the reverse leakage by 33.3% at the temperature of 423K. Just like the development from SBD to TMBS, from TMBS to TMB-SSBR also brings obvious improvement of performance.

A novel charge pump, Capacitance Varying Charge Pump (CVCP) is proposed. This charge pump is composed of variable capacitors and rectifiers, and the charge transfer is attained by changing the capacitance values in a manner similar to peristaltic pumps. The analysis of multi-stage CVCP reveals that the output voltage is exponentially dependent on the stage number. Thus, compared with the Dickson charge pump, this charge pump has an advantage in generating high voltages with small stages. As a practical example of CVCP, we present an implementation realized by a MEMS (Micro-Electro-Mechanical Systems) technology. Here, the variable capacitor is enabled by a comb-capacitor attached to a high-quality factor resonator. As the rectifier, a PN-junction diode formed in the MEMS layer is used. Simulations including the mechanical elements are carried out for this MEMS version of CVCP. The simulation results on the output voltage and load characteristics are shown to coincide well with the theoretical estimations. The MEMS CVCP is suited for MEMS devices and vibration energy harvesters.

In this paper, the quality and transferred data based video bitrate control method for web-conferencing services is proposed, aiming to reduce transferred data by suppressing excessive quality. In web-conferencing services, the video bitrate is generally controlled in accordance with the network conditions (e.g., jitter and packet loss rate) to improve users' quality. However, in such a control, the bitrate is excessively high when the network conditions is sufficiently high (e.g., high throughput and low jitter), which causes an increased transferred data volume. The increased volume of data transferred leads to increased operational costs, such as network costs for service providers. To solve this problem, we developed a method to control the video bitrate of each user to achieve the required quality determined by the service provider. This method is implemented in an actual web-conferencing system and evaluated under various conditions. It was shown that the bitrate could be controlled in accordance with the required quality to reduce the transferred data volume.

In this paper, we investigate optimal design of millimeter-wave (mmWave) multiuser line-of-sight multiple-input-multiple-output (LOS MIMO) systems using hybrid arrays of subarrays based on hybrid block diagonalization (BD) precoding and combining scheme. By introducing a general 3D geometric channel model, the optimal subarray separation products of the transmitter and receiver for maximizing sum-rate is designed in terms of two regular configurations of adjacent subarrays and interleaved subarrays for different users, respectively. We analyze the sensitivity of the optimal design parameters on performance in terms of a deviation factor, and derive expressions for the eigenvalues of the multiuser equivalent LOS MIMO channel matrix, which are also valid for non-optimal design. Simulation results show that the interleaved subarrays can support longer distance communication than the adjacent subarrays given the appropriate fixed subarray deployment.

This paper proposes user equipment (UE) grouping schemes and evaluates the performance of a scheduling scheme for each formed group in collaborative multiple-input multiple-output (MIMO) reception. In previous research, the criterion for UE grouping and the effects of group scheduling has never been presented. In the UE grouping scheme, two criteria, the base station (BS)-oriented one and the UE-oriented one, are presented. The BS-oriented full search scheme achieves ideal performance though it requires knowledge of the relative positions of all UEs. Therefore, the UE-oriented local search scheme is also proposed. As the scheduling scheme, proportional fairness scheduling is used in resource allocation for each formed group. When the number of total UEs increases, the difference in the number of UEs among groups enlarges. Numerical results obtained through computer simulation show that the throughput per user increases and the fairness among users decreases when the number of UEs in a cell increases in the proposed schemes compared to those of the conventional scheme.

Analog beamforming with broadband large-scale antenna arrays in millimeter wave (mmWave) multiple input multiple output (MIMO) systems faces the beam squint problem. In this paper, we first investigate the sensitivity of analog beamforming to subarray spatial separations in wideband mmWave systems using hybrid arrays, and propose optimized subarray separations. We then design improved analog beamforming after phase compensation based on Zadoff-Chu (ZC) sequence to flatten the frequency response of radio frequency (RF) equivalent channel. Considering a single-carrier frequency-domain equalization (SC-FDE) scheme at the receiver, we derive low-complexity linear zero-forcing (ZF) and minimum mean squared error (MMSE) equalizers in terms of output signal-to-noise ratio (SNR) after equalization. Simulation results show that the improved analog beamforming can effectively remove frequency-selective deep fading caused by beam squint, and achieve better bit-error-rate performance compared with the conventional analog beamforming.

Orbital angular momentum (OAM) multiplexing technology is being investigated for high-capacity point-to-point (PtP) wireless transmission toward beyond 5G systems. OAM multiplexing is a spatial multiplexing technique that utilizes the twisting of electromagnetic waves. Its advantage is that it reduces the computational complexity of the signal processing on spatial multiplexing. Meanwhile point-to-multi point (PtMP) wireless transmission, such as integrated access and backhaul (IAB) will be expected to simultaneously accommodates a high-capacity prioritized backhaul-link and access-links. In this paper, we study the extension of OAM multiplexing transmission from PtP to PtMP to meet the above requirements. We propose a backhaul prioritized resource control algorithm that maximizes the received signal-to-interference and noise ratio (SINR) of the access-links while maintaining the backhaul-link. The proposed algorithm features adaptive mode selection that takes into account the difference in the received power of each OAM mode depending on the user equipment position and the guaranteed power allocation of the backhaul capacity. We then evaluate the performance of the proposed method through computer simulation. The results show that throughput of the access-links improved compared with the conventional multi-beam multi-user multi-input multi-output (MIMO) techniques while maintaining the throughput of the backhaul-link above the required value with minimal feedback information.

Device-to-device (D2D) communication allows user terminals to directly communicate with each other without the need for any base stations (BSs). Since the D2D communication underlaying a cellular system shares frequency channels with BSs, co-channel interference may occur. Successive interference cancellation (SIC), which is also called the serial interference canceler, detects and subtracts user signals from received signals in descending order of received power, can cope with the above interference and has already been applied to fog nodes that manage communications among machine-to-machine (M2M) devices besides direct communications with BSs. When differences among received power levels of user signals are negligible, however, SIC cannot work well and thus causes degradation in bit error rate (BER) performance. To solve such a problem, this paper proposes to apply parallel interference cancellation (PIC), which can simultaneously detect both desired and interfering signals under the maximum likelihood criterion and can maintain good BER performance even when power level differences among users are small. When channel coding is employed, however, SIC can be superior to PIC in terms of BER under some channel conditions. Considering the superiority, this paper also proposes to select the proper cancellation scheme and modulation and coding scheme (MCS) that can maximize the throughput of D2D under a constraint of BER, in which the canceler selection is referred to as adaptive interference cancellation. Computer simulations show that PIC outperforms SIC under almost all channel conditions and thus the adaptive selection from PIC and SIC can achieve a marginal gain over PIC, while PIC can achieve 10% higher average system throughput than that of SIC. As for transmission delay time, it is demonstrated that the adaptive selection and PIC can shorten the delay time more than any other schemes, although the fog node causes the delay time of 1ms at least.

The application of millimeter wave (mmWave) directional transmission technology in high-speed railway (HSR) scenarios helps to achieve the goal of multiple gigabit data rates with low latency. However, due to the high mobility of trains, the traditional initial access (IA) scheme with high time consumption is difficult to guarantee the effectiveness of the beam alignment. In addition, the high path loss at the coverage edge of the millimeter wave remote radio unit (mmW-RRU) will also bring great challenges to the stability of IA performance. Fortunately, the train trajectory in HSR scenarios is periodic and regular. Moreover, the cell-free network helps to improve the system coverage performance. Based on these observations, this paper proposes an efficient IA scheme based on location and history information in cell-free networks, where the train can flexibly select a set of mmW-RRUs according to the received signal quality. We specifically analyze the collaborative IA process based on the exhaustive search and based on location and history information, derive expressions for IA success probability and delay, and perform the numerical analysis. The results show that the proposed scheme can significantly reduce the IA delay and effectively improve the stability of IA success probability.

The proportion of persons over 65 years old is projected to increase worldwide between 2022 and 2050. The increasing burden on medical staff and the shortage of human resources are growing problems. Bedsores are injuries caused by prolonged pressure on the skin and stagnation of blood flow. The more the damage caused by bedsores progresses, the longer the treatment period becomes. Moreover, patients require surgery in some serious cases. Therefore, early detection is essential. In our research, we are developing a non-contact bedsore detection system using electromagnetic waves at 10.5GHz. In this paper, we extracted appropriate information from a scalogram and utilized it to detect the sizes of bedsores. In addition, experiments using a phantom were conducted to confirm the basic operation of the bedsore detection system. As a result, using the approximate curves and lines obtained from prior analysis data, it was possible to estimate the volume of each defected area, as well as combinations of the depth of the defected area and the length of the defected area. Moreover, the experiments showed that it was possible to detect bedsore presence and estimate their sizes, although the detection results had slight variations.

This study investigates the improvement of the channel capacity of 5-GHz-band multiple-input multiple-output (MIMO) communication using microwave-guided modes propagating along a polyvinyl chloride (PVC) pipe wall for a buried pipe inspection robot. We design a planar Yagi-Uda antenna to reduce transmission losses in communication with PVC pipe walls as propagation paths. Coupling efficiency between the antenna and a PVC pipe is improved by attaching a PVC adapter with the same curvature as the PVC pipe's inner wall to the Yagi-Uda antenna to eliminate any gap between the antenna and the inner wall of the PVC pipe. The use of a planar Yagi-Uda antenna with a PVC adaptor decreases the transmission loss of a 5-GHz-band microwave signal propagating along a 1-m-lomg straight PVC pipe wall by 7dB compared to a dipole antenna. The channel capacity of a 2×2 MIMO system using planar Yagi-Uda antennas is more than twice that of the system using dipole antennas.