Video inpainting is a task of filling missing regions in videos. In this task, it is important to efficiently use information from other frames and generate plausible results with sufficient temporal consistency. In this paper, we present a video inpainting method jointly using affine transformation and deformable convolutions for frame alignment. The former is responsible for frame-scale rough alignment and the latter performs pixel-level fine alignment. Our model does not depend on 3D convolutions, which limits the temporal window, or troublesome flow estimation. The proposed method achieves improved object removal results and better PSNR and SSIM values compared with previous learning-based methods.

Accurate and automatic quantitative cephalometry analysis is of great importance in orthodontics. The fundamental step for cephalometry analysis is to annotate anatomic-interested landmarks on X-ray images. Computer-aided automatic method remains to be an open topic nowadays. In this paper, we propose an efficient deep learning-based coarse-to-fine approach to realize accurate landmark detection. In the coarse detection step, we train a deep learning-based deformable transformation model by using training samples. We register test images to the reference image (one training image) using the trained model to predict coarse landmarks' locations on test images. Thus, regions of interest (ROIs) which include landmarks can be located. In the fine detection step, we utilize trained deep convolutional neural networks (CNNs), to detect landmarks in ROI patches. For each landmark, there is one corresponding neural network, which directly does regression to the landmark's coordinates. The fine step can be considered as a refinement or fine-tuning step based on the coarse detection step. We validated the proposed method on public dataset from 2015 International Symposium on Biomedical Imaging (ISBI) grand challenge. Compared with the state-of-the-art method, we not only achieved the comparable detection accuracy (the mean radial error is about 1.0-1.6mm), but also largely shortened the computation time (4 seconds per image).

In this paper, we focus on developing efficient multi-configuration selection mechanisms by exploiting the spatial degrees of freedom (DoF), and leveraging the simple design benefits of spatial modulation (SM). Notably, the SM technique, as well as its variants, faces the following critical challenges: (i) the performance degradation and difficulty in improving the system performance for higher-level QAM constellations, and (ii) the vast complexity cost in precoder designs particularly for the increasing system dimension and amplitude-phase modulation (APM) constellation dimension. Given this situation, we first investigate two independent modulation domains, i.e., the original signal- and spatial-constellations. By exploiting the analog shift weighting and the virtual spatial signature technologies, we introduce the signature spatial modulation (SSM) concept, which is capable of guaranteing superior trade-offs among spectral- and cost-efficiencies, and system bit error rate (BER) performance. Besides, we develop an analog beamforming for SSM by solving the introduced unconstrained Lagrange dual function minimization problem. Numerical results manifest the performance gain brought by our developed analog beamforming for SSM.

Data parallelism is the dominant method used to train deep learning (DL) models on High-Performance Computing systems such as large-scale GPU clusters. When training a DL model on a large number of nodes, inter-node communication becomes bottle-neck due to its relatively higher latency and lower link bandwidth (than intra-node communication). Although some communication techniques have been proposed to cope with this problem, all of these approaches target to deal with the large message size issue while diminishing the effect of the limitation of the inter-node network. In this study, we investigate the benefit of increasing inter-node link bandwidth by using hybrid switching systems, i.e., Electrical Packet Switching and Optical Circuit Switching. We found that the typical data-transfer of synchronous data-parallelism training is long-lived and rarely changed that can be speed-up with optical switching. Simulation results on the Simgrid simulator show that our approach speed-up the training time of deep learning applications, especially in a large-scale manner.

This study presents a formal verification method for Galois-field (GF) arithmetic circuits with the characteristics of more than two values. The proposed method formally verifies the correctness of circuit functionality (i.e., the input-output relations given as GF-polynomials) by checking the equivalence between a specification and a gate-level netlist. We represent a netlist using simultaneous algebraic equations and solve them based on a novel polynomial reduction method that can be efficiently applied to arithmetic over extension fields $mathbb{F}_{p^m}$, where the characteristic p is larger than two. By using the reverse topological term order to derive the Gröbner basis, our method can complete the verification, even when a target circuit includes bugs. In addition, we introduce an extension of the Galois-Field binary moment diagrams to perform the polynomial reductions faster. Our experimental results show that the proposed method can efficiently verify practical $mathbb{F}_{p^m}$ arithmetic circuits, including those used in modern cryptography. Moreover, we demonstrate that the extended polynomial reduction technique can enable verification that is up to approximately five times faster than the original one.

In this letter, we investigate tight analytical and asymptotic upper bounds for bit error rate (BER) of constitutional codes over exponentially correlated Nakagami-m fading channels. Specifically, we derive the BER expression depending on an exact closed-form formula for pairwise error event probabilities (PEEP). Moreover, the corresponding asymptotic analysis in high signal-to-noise ratio (SNR) regime is also explored, which is verified via numerical results. This allows us to have explicit insights on the achievable coding gain and diversity order.

Boarding is the last step of aircraft turnaround and its completion in the shortest possible time is desired. In this paper, we propose a new boarding strategy that outperforms conventional strategies such as the back-to-front strategy and the outside-in strategy. The Steffen method is known as one of the most efficient boarding strategies in literature, but it is hard to be realized in the real situation because the complete sorting of passengers in a prescribed order is required. The proposed strategy shows a performance close to that of the Steffen method and can be easily implemented by using a special gate system.

The frequency of uterine peristalsis is closely related to the success rate of pregnancy. An ultrasonic imaging is almost always employed for the measure of the frequency. The physician subjectively evaluates the frequency from the ultrasound image by the naked eyes. This paper aims to measure the frequency of uterine peristalsis from the ultrasound image. The ultrasound image consists of relative amounts in the brightness, and the contour of the uterine is not clear. It was not possible to measure the frequency by using the inter-frame difference and optical flow, which are the representative methods of motion detection, since uterine peristaltic movement is too small to apply them. This paper proposes a measurement method of the frequency of the uterine peristalsis from the ultrasound image in the implantation phase. First, traces of uterine peristalsis are semi-automatically done from the images with location-axis and time-axis. Second, frequency analysis of the uterine peristalsis is done by Fourier transform for 3 minutes. As a result, the frequency of uterine peristalsis was known as the frequency with the dominant frequency ingredient with maximum value among the frequency spectrums. Thereby, we evaluate the number of the frequency of uterine peristalsis quantitatively from the ultrasound image. Finally, the success rate of pregnancy is calculated from the frequency based on Fuzzy logic. This enabled us to evaluate the success rate of pregnancy by measuring the uterine peristalsis from the ultrasound image.

We propose two simple weight calculation methods (primary method and enhanced method), that estimate approximated phase plane from a few antenna phase and calculate weights of all antenna elements, for wireless backhaul systems that utilize millimeter wave band massive antenna arrays. Such systems are expected to be used instead of optical fiber for connecting many small cell base stations (SCBSs) to the core network, and supporting the rapid deployment of SCBSs. However, beamforming with massive antenna arrays requires many analog-digital converters (ADCs) and incurs the issue of implementation complexity. The proposed methods overcome the problem by reducing the number of ADCs. Computer simulations clarify the appropriate layout and the number of ADCs connected to antenna elements; the effectiveness of the proposed methods is confirmed by evaluations with measured channel state information (CSI) in propagation experiments on a wireless backhaul system. Experimental verifications on the case of calculating the weight of 200 elements from the phases of just 9 elements show that the array gain degradation from ideal (the case in which the phases of all elements are used estimation) with both methods is less than 0.4 dB in the direct wave dominant environment. In addition, the enhanced method holds the array gain degradation to under 0.8dB in an environment existing reflected waves. These results show that the proposed methods can attain high accuracy beamforming while reducing ADC number.

This paper presents a high jitter performance injection-locked clock multiplier (ILCM) using an ultra-low power (ULP) voltage-controlled oscillator (VCO) for IoT application in 65-nm CMOS. The proposed transformer-based VCO achieves low flicker noise corner and sub-100µW power consumption. Double cross-coupled NMOS transistors sharing the same current provide high transconductance. The network using high-Q factor transformer (TF) provides a large tank impedance to minimize the current requirement. Thanks to the low current bias with a small conduction angle in the ULP VCO design, the proposed TF-based VCO's flicker noise can be suppressed, and a good PN can be achieved in flicker region (1/f3) with sub-100µW power consumption. Thus, a high figure-of-merit (FoM) can be obtained at both 100kHz and 1MHz without additional inductor. The proposed VCO achieves phase noise of -94.5/-115.3dBc/Hz at 100kHz/1MHz frequency offset with a 97µW power consumption, which corresponds to a -193/-194dBc/Hz VCO FoM at 2.62GHz oscillation frequency. The measurement results show that the 1/f3 corner is below 60kHz over the tuning range from 2.57GHz to 3.40GHz. Thanks to the proposed low power VCO, the total ILCM achieves 78 fs RMS jitter while using a high reference clock. A 960 fs RMS jitter can be achieved with a 40MHz common reference and 107µW corresponding power.

This paper studies a harvested power-oriented simultaneous wireless information and power transfer (SWIPT) scheme over multiple-input multiple-output (MIMO) interference channels in which energy harvesting (EH) circuits exhibit nonlinearity. To maximize the power harvested by all receivers, we propose an algorithm to jointly optimize the transmit beamforming vectors, power splitting (PS) ratios and the receive decoding vectors. As all variables are coupled to some extent, the problem is non-convex and hard to solve. To deal with this non-convex problem, an iterative optimization method is proposed. When two variables are fixed, the third variable is optimized. Specifically, when the transmit beamforming vectors are optimized, the transferred objective function is the sum of several fractional functions. Non-linear sum-of-ratios programming is used to solve the transferred objective function. The convergence and advantage of our proposed scheme compared with traditional EH circuits are validated by simulation results.

Due to the slowdown of Moore's Law, power limitation has been one of the most critical issues for current and future HPC systems. To more efficiently utilize HPC systems when power budgets or deadlines are given, it is very desirable to accurately estimate the performance or power consumption of applications before conducting their tuned production runs on any specific systems. In order to ease such estimations, we showcase a straight-forward and yet effective method, based on the enhanced power management framework and DSL we developed, to help HPC users to clarify the performance and power relationships of their applications. This method demonstrates an easy process of profiling, modeling and management on both performance and power of HPC systems and applications. In our evaluations, only a few (up to 3) profiled runs are necessary before very precise models of HPC applications can be obtained through this method (and algorithm), which has dramatically improved the efficiency of and lowered the difficulty in utilizing HPC systems under limited power budgets.

In this paper, we present a novel portrait impression estimation method using nine pairs of semantic impression words: bitter-majestic, clear-pure, elegant-mysterious, gorgeous-mature, modern-intellectual, natural-mild, sporty-agile, sweet-sunny, and vivid-dynamic. In the first part of the study, we analyzed the relationship between the facial features in deformed portraits and the nine semantic impression word pairs over a large dataset, which we collected by a crowdsourcing process. In the second part, we leveraged the knowledge from the results of the analysis to develop a ranking network trained on the collected data and designed to estimate the semantic impression associated with a portrait. Our network demonstrated superior performance in impression estimation compared with current state-of-the-art methods.

This paper proposes a change detection method for buildings based on convolutional neural networks. The proposed method detects building changes from pairs of optical aerial images and past map information concerning buildings. Using high-resolution image pair and past map information seamlessly, the proposed method can capture the building areas more precisely compared to a conventional method. Our experimental results show that the proposed method outperforms the conventional change detection method that uses optical aerial images to detect building changes.

Scalability of distributed DNN training can be limited by slowdown of specific processes due to unexpected hardware failures. We propose a dynamic process exclusion technique so that training throughput is maximized. Our evaluation using 32 processes with ResNet-50 shows that our proposed technique reduces slowdown by 12.5% to 50% without accuracy loss through excluding the slow processes.

In order to erase data including confidential information stored in storage devices, an unrelated and random sequence is usually overwritten, which prevents the data from being restored. The problem of minimizing the cost for information erasure when the amount of information leakage of the confidential information should be less than or equal to a constant asymptotically has been introduced by T. Matsuta and T. Uyematsu. Whereas the minimum cost for overwriting has been given for general sources, a single-letter characterization for stationary memoryless sources is not easily derived. In this paper, we give single-letter characterizations for stationary memoryless sources under two types of restrictions: one requires the output distribution of the encoder to be independent and identically distributed (i.i.d.) and the other requires it to be memoryless but not necessarily i.i.d. asymptotically. The characterizations indicate the relation among the amount of information leakage, the minimum cost for information erasure and the rate of the size of uniformly distributed sequences. The obtained results show that the minimum costs are different between these restrictions.

This paper proposes a parallel peak cancellation (PC) process for the computational complexity-efficient algorithm called PC with a channel-null constraint (PCCNC) in the adaptive peak-to-average power ratio (PAPR) reduction method using the null space in a multiple-input multiple-output (MIMO) channel for MIMO-orthogonal frequency division multiplexing (OFDM) signals. By simultaneously adding multiple PC signals to the time-domain transmission signal vector, the required number of iterations of the iterative algorithm is effectively reduced along with the PAPR. We implement a constraint in which the PC signal is transmitted only to the null space in the MIMO channel by beamforming (BF). By doing so the data streams do not experience interference from the PC signal on the receiver side. Since the fast Fourier transform (FFT) and inverse FFT (IFFT) operations at each iteration are not required unlike the previous algorithm and thanks to the newly introduced parallel processing approach, the enhanced PCCNC algorithm reduces the required total computational complexity and number of iterations compared to the previous algorithms while achieving the same throughput-vs.-PAPR performance.

A global content delivery plays an important role in the current Internet. Information-Centric Networking (ICN) is a future internet architecture which attempts to redesign the Internet with a focus on the content delivery. However, it has the potential performance degradation in the global content delivery. In this paper, we propose an ICN performance enhancing proxy (ICN-PEP) to mitigate this performance degradation. The key idea is to prefetch Data packets and to serve them to the consumer with the shorter round trip time. By utilizing ICN features, it can be developed as an offline and state-less proxy which has an advantage of scalability. We evaluate the performance of ICN-PEP in both simulation and experiment on global testbed and show that ICN-PEP improves the performance of global content delivery.

In this paper, user scheduling with beam selection for full-digital massive multi-input multi-output (MIMO) is proposed. Inter-user interference (IUI) can be canceled by precoding such as zero-forcing at a massive MIMO base station if ideal hardware implementation is assumed. However, owing to the non-ideal characteristics of hardware components, IUI occurs among multiple user terminals allocated on the same resource. Thus, in the proposed scheme, the directions of beams for allocated user terminals are adjusted to maximize the total user throughput. User allocation based on the user throughput after the adjustment of beam directivity is then carried out. Numerical results obtained through computer simulation show that when the number of user terminals in the cell is two and the number of user terminals allocated to one resource block (RB) is two, the throughput per subcarrier per subframe improves by about 3.0 bits. On the other hand, the fairness index (FI) is reduced by 0.03. This is because only the probability in the high throughput region increases as shown in the cumulative distribution function (CDF) of throughput per user. Also, as the number of user terminals in the cell increases, the amount of improvement in throughput decreases. As the number of allocated user terminals increases, more user terminals are allocated to the cell-edge, which reduces the average throughput.

In this Letter, we propose a blind and robust multiple watermarking scheme using Contourlet transform and singular value decomposition (SVD). The host image is first decomposed by Contourlet transform. Singular values of Contourlet coefficient blocks are adopted to embed watermark information, and a fast calculation method is proposed to avoid the heavy computation of SVD. The watermark is embedded in both low and high frequency Contourlet coefficients to increase the robustness against various attacks. Moreover, the proposed scheme intrinsically exploits the characteristics of human visual system and thus can ensure the invisibility of the watermark. Simulation results show that the proposed scheme outperforms other related methods in terms of both robustness and execution time.