As the most compelling candidate for 5G, millimeter-wave communication has drawn considerable interest, despite the absence of systematic research on its performance. Therefore, this study investigates millimeter-wave cellular networks and their use of existing frequency reuse schemes and scheduling methods. To evaluate the performance of these networks, we configure a system-level simulator that reflects the eNodeB architecture and frame structure designed to overcome the millimeter-wave frequency characteristics of the Giga Korea Project. Simulations conducted using various combinations of frequency reuse schemes and scheduling methods are described. We found that the best performing radio resource management scheme changes according to the number of user equipment accessing the eNodeB. The results of this study will contribute to performance estimations of the capacity and fairness of cellular-based millimeter-wave communication systems before they are deployed.

Biomimetics is a new research field that creates innovation through the collaboration of different existing research fields. However, the collaboration, i.e., the exchange of deep knowledge between different research fields, is difficult for several reasons such as differences in technical terms used in different fields. In order to overcome this problem, we have developed a new retrieval platform, “Biomimetics image retrieval platform,” using a visualization-based image retrieval technique. A biological database contains a large volume of image data, and by taking advantage of these image data, we are able to overcome limitations of text-only information retrieval. By realizing such a retrieval platform that does not depend on technical terms, individual biological databases of various species can be integrated. This will allow not only the use of data for the study of various species by researchers in different biological fields but also access for a wide range of researchers in fields ranging from materials science, mechanical engineering and manufacturing. Therefore, our platform provides a new path bridging different fields and will contribute to the development of biomimetics since it can overcome the limitation of the traditional retrieval platform.

The present paper proposes a dynamic spectrum access policy for multi-hop cognitive radio networks (CRNs), where the transmission in each hop suffers a delay waiting for the communication channel to become available. Recognizing the energy constraints, we assume that each secondary user (SU) in the network is powered by a battery with finite initial energy. We develop an energy-efficient policy for CRNs using the Markov decision process, which searches for spectrum opportunities without a common communication channel and assigns each sensor's decision to every time slot. We first consider a single-sensor scenario. Due to the intermittent activation of the sensor, achieving the optimal sensing schedule requires excessive complexity and is computationally intractable, owing to the fact that the state space of the Markov decision process evolves exponentially with time variance. In order to overcome this difficulty, we propose a state-reduced suboptimal policy by relaxing the constrained state space, i.e., assuming that the electrical energy of a node is infinite, because this state-reduced suboptimal approach can substantially reduce the complexity of decision-making for CRNs. We then analyze the performance of the proposed policy and compare it with the optimal solution. Furthermore, we verify the performance of this spectrum access policy under real conditions in which the electrical energy of a node is finite. The proposed spectrum access policy uses the dynamic information of each channel. We prove that this schedule is a good approximation for the true optimal schedule, which is impractical to obtain. According to our theoretical analysis, the proposed policy has less complexity but comparable performance. It is proved that when the operating time of the CRN is sufficiently long, the data reception rate on the sink node side will converge to the optimal rate with probability 1. Based on the results for the single-sensor scenario, the proposed schedule is extended to a multi-hop CRN. The proposed schedule can achieve synchronization between transmitter and receiver without relying on a common control channel, and also has near-optimal performance. The performance of the proposed spectrum access policy is confirmed through simulation.

This paper presents study results regarding the analytical method for performance characteristics and application scheme, which cover a feature detection scheme using a Cyclic Prefix (CP) that is attached to an OFDM signal. The detection scheme is especially important when used as a sensing technology in advanced systems such as Device-to-Device (D-to-D) or Internet of Things (IoT). Herein, we present several basic performance characteristics of the signal processing involved in feature detection, namely, the Output S/N (Signal-to-Noise power ratio) and probability density functions of the OFDM signal and the noise measured at the output of the feature detector. The Output S/Nis described by an analytical expression and is also examined by conducting a software simulation. An analytical approach is investigated by modeling the spectral density of the OFDM signal and input noise and by executing the mathematical operations such as convolutional integration on the combination of OFDM signal and noise. The analytical results coincide closely with the simulation results. As for the applications to mobile communication system, some methods of the feature detection schemes are addressed. These are an estimation method for the Input C/N (Carrier-to-Noise power ratio) and a system discrimination scheme, especially under the assumption that two OFDM systems using different CP lengths are simultaneously operated in the same frequency. Furthermore, under the condition that two OFDM signals are transmitted in an asynchronous manner, a scheme to estimate their timing offset and signal power ratio is also described.

Previously, it is not obvious to what extent was accepted for the assessors when we see the 3D image (including multi-view 3D) which the luminance change may affect the stereoscopic effect and assessment generally. We think that we can conduct a general evaluation, along with a subjective evaluation, of the luminance component using both the S-CIELAB color space and CIEDE2000. In this study, first, we performed three types of subjective evaluation experiments for contrast enhancement in an image by using the eight viewpoints parallax barrier method. Next, we analyzed the results statistically by using a support vector machine (SVM). Further, we objectively evaluated the luminance value measurement by using CIEDE2000 in the S-CIELAB color space. Then, we checked whether the objective evaluation value was related to the subjective evaluation value. From results, we were able to see the characteristic relationship between subjective assessment and objective assessment.

In this paper, we propose a redundant task allocation method for multi-core systems based on the Duplication with Temporary Triple-Modular Redundancy and Reconfiguration (DTTR) scheme. The proposed method determines task allocation of a given task graph to a given multi-core system model from task scheduling in given fault patterns. Fault patterns defined in this paper consist of a set of faulty cores and a set of surviving cores. To optimize the average failure rate of the system, task scheduling minimizes the execution time of the task graph preserving the property of the DTTR scheme. In addition, we propose a selection method of fault patterns to be scheduled to reduce the task allocation time. In the experiments, at first, we evaluate the proposed selection method of fault patterns in terms of the task allocation time. Then, we compare the average failure rate among the proposed method, a task allocation method which packs tasks into particular cores as much as possible, a task allocation method based on Simulated Annealing (SA), a task allocation method based on Integer Linear Programming (ILP), and a task allocation method based on task scheduling without considering the property of the DTTR scheme. The experimental results show that task allocation by the proposed method results in nearly the same average failure rate by the SA based method with shorter task allocation time.

Feature representation, as a key component of scene character recognition, has been widely studied and a number of effective methods have been proposed. In this letter, we propose the novel method named coupled spatial learning (CSL) for scene character representation. Different from the existing methods, the proposed CSL method simultaneously discover the spatial context in both the dictionary learning and coding stages. Concretely, we propose to build the spatial dictionary by preserving the corresponding positions of the codewords. Correspondingly, we introduce the spatial coding strategy which utilizes the spatiality regularization to consider the relationship among features in the Euclidean space. Based on the spatial dictionary and spatial coding, the spatial context can be effectively integrated in the visual representations. We verify our method on two widely used databases (ICDAR2003 and Chars74k), and the experimental results demonstrate that our method achieves competitive results compared with the state-of-the-art methods. In addition, we further validate the proposed CSL method on the Caltech-101 database for image classification task, and the experimental results show the good generalization ability of the proposed CSL.

Bayesian networks are a powerful approach for representation and reasoning under conditions of uncertainty. Of the many good algorithms for learning Bayesian networks from data, the bio-inspired search algorithm is one of the most effective. In this paper, we propose a hybrid mutual information-modified binary particle swarm optimization (MI-MBPSO) algorithm. This technique first constructs a network based on MI to improve the quality of the initial population, and then uses the decomposability of the scoring function to modify the BPSO algorithm. Experimental results show that, the proposed hybrid algorithm outperforms various other state-of-the-art structure learning algorithms.

Task scheduling is one of the most important processes in the design of multicore computing systems. This paper presents a technique for scheduling of malleable tasks. Our scheduling technique decides not only the execution order of the tasks but also the number of cores assigned to the individual tasks, simultaneously. We formulate the scheduling problem as an integer linear programming (ILP) problem, and the optimal schedule can be obtained by solving the ILP problem. Experiments using a standard task-set suite clarify the strength of this work.

This report presents experimental measurements of mixed-mode oscillations (MMOs) generated by a weakly driven four-segment piecewise linear Bonhoeffer-van der Pol (BVP) oscillator. Such a roughly approximated simple piecewise linear circuit can generate MMOs and mixed-mode oscillation-incrementing bifurcations (MMOIBs). The laboratory experiments well agree with numerical results. We experimentally and numerically observe time series and Lorenz plots of MMOs generated by successive and nonsuccessive MMOIBs.

This paper discusses the use of a common computer mouse as a pointing interface for tabletop displays. In the use of a common computer mouse for tabletop displays, there might be an angular distance between the screen coordinates and the mouse control coordinates. To align those coordinates, this paper introduces a screen coordinates calibration technique using a shadow cursor. A shadow cursor is the basic idea of manipulating a mouse cursor without any visual feedbacks. The shadow cursor plays an important role in obtaining the angular distance between the two coordinates. It enables the user to perform a simple mouse manipulation so that screen coordinates calibration will be completed in less than a second.

In multi-view social networks field, a flexible Nonnegative Matrix Factorization (NMF) based framework is proposed which integrates multi-view relation data and feature data for community discovery. Benefit with a relaxed pairwise regularization and a novel orthogonal regularization, it outperforms the-state-of-art algorithms on five real-world datasets in terms of accuracy and NMI.

In accordance with Moore's law, recent design issues include shortening of time-to-market and detection of delay faults. Several studies with respect to formal techniques have examined the first issue. Using the equivalence checking, it is possible to identify whether large circuits are equivalent or not in a practical time frame. With respect to the latter issue, it is difficult to achieve 100% fault efficiency even for transition faults in full scan designs. This study involved proposing a redundant transition fault identification method using equivalence checking. The main concept of the proposed algorithm involved combining the following two known techniques, 1. modeling of a transition fault as a stuck-at fault with temporal expansion and 2. detection of a stuck-at fault by using equivalence checking tools. The experimental results indicated that the proposed redundant identification method using a formal approach achieved 100% fault efficiency for all benchmark circuits in a practical time even if a commercial ATPG tool was unable to achieve 100% fault efficiency for several circuits.

This letter presents a novel memory-based architecture for radix-2 fast Walsh-Hadamard-Fourier transform (FWFT) based on the constant geometry FWFT algorithm. It is composed of a multi-function Processing Engine, a conflict-free memory addressing scheme and an efficient twiddle factor generator. The address for memory access and the control signals for stride permutation are formulated in detail and the methods can be applied to other memory-based FFT-like architectures.

Regression testing is essential for assuring the quality of a software product. Because rerunning all test cases in regression testing may be impractical under limited resources, test case prioritization is a feasible solution to optimize regression testing by reordering test cases for the current testing version. In this paper, we propose a novel test case prioritization approach that combines the clustering algorithm and the scheduling algorithm for improving the effectiveness of regression testing. By using the clustering algorithm, test cases with same or similar properties are merged into a cluster, and the scheduling algorithm helps allocate an execution priority for each test case by incorporating fault detection rates with the waiting time of test cases in candidate set. We have conducted several experiments on 12 C programs to validate the effectiveness of our proposed approach. Experimental results show that our approach is more effective than some well studied test case prioritization techniques in terms of average percentage of fault detected (APFD) values.

In the newly finalized video coding standard, namely high efficiency video coding (HEVC), new notations like coding unit (CU), prediction unit (PU) and transformation unit (TU) are introduced to improve the coding performance. As a result, the reconstruction loop in intra encoding is heavily burdened to choose the best partitions or modes for them. In order to solve the bottleneck problems in cycle and hardware cost, this paper proposed a high-throughput and compact implementation for such a reconstruction loop. By “high-throughput”, it refers to that it has a fixed throughput of 32 pixel/cycle independent of the TU/PU size (except for 4×4 TUs). By “compact”, it refers to that it fully explores the reusability between discrete cosine transform (DCT) and inverse discrete cosine transform (IDCT) as well as that between quantization (Q) and de-quantization (IQ). Besides the contributions made in designing related hardware, this paper also provides a universal formula to analyze the cycle cost of the reconstruction loop and proposed a parallel-process scheme to further reduce the cycle cost. This design is verified on the Stratix IV FPGA. The basic structure achieved a maximum frequency of 150MHz and a hardware cost of 64K ALUTs, which could support the real time TU/PU partition decision for 4K×2K@20fps videos.

We investigate a finite-sized self-complementary bow-tie antenna (SC-BTA) integrated with a semiconductor mesa with respect to radiation characteristics such as the peak radiation frequency and bandwidth around the fundamental radiation mode. For this investigation, we utilize an equivalent circuit model of the SC-BTA derived in our previous work and a finite element method solver. Moreover, we derive design guidelines for the radiation characteristics in the form of size scaling-rules with respect to the antenna outer size for a terahertz transmitter.

Image sensor communication (ISC), a type of visible light communication, is an emerging wireless communication technology that uses LEDs to transmit a signal and uses an image sensor in a camera to receive the signal. This paper discusses the present status of and future trends in ISC by describing the essential characteristics and features of ISC. Moreover, we overview the products and expected future applications of ISC.

This letter introduces a new model for backscatter assisted wireless powered communication networks (BAWPCNs) that include a hybrid access point (HAP) and multiple backscatter communication (BackCom) and traditional wireless powered communication network (WPCN) users. To make full use of time to transmit information, both backscatter and harvest-then-transmit (HTT) modes are employed. In the proposed model, during the first time slot dedicated for energy transfer in traditional WPCNs, the traditional WPCN users harvest energy radiated by the HAP, and simultaneously the BackCom users reflect modulated signals to the HAP. The traditional WPCN users are scheduled during the remaining time slots via time division multiple access (TMDA). The optimal time allocation policies for the half-duplex (HD) and full-duplex (FD) BAWPCNs are obtained to maximize the system throughput. The tradeoff between backscatter and HTT modes is analyzed. Simulation results demonstrate the superiority of the proposed model.

This letter considers the robust transceiver design for multiple-input multiple-output interference channels under channel state information mismatch. According to alternating schemes, an adaptive algorithm is proposed to solve the minimum SINR maximization problem. Simulation results show the convergence and the effectiveness of the proposed algorithm.