Quaternionic neural networks are extensions of neural networks using quaternion algebra. 3-D and 4-D quaternionic MLPs have been studied. 3-D quaternionic neural networks are useful for handling 3-D objects, such as Euclidean transformation. As for Hopfield neural networks, only 4-D quaternionic Hopfield neural networks (QHNNs) have been studied. In this work, we propose the 3-D QHNNs. Moreover, we define the energy, and prove that it converges.

In this letter, we focus on a system where N sources send n ≤ N different packets to one destination, through M ≥ N relays. Each relay employs random linear network coding to encode the packets it received by randomly choosing coefficients in a finite field Fq, then forwards it to the destination. Owing to the inherent errorprone nature of erasure channels, data packets received by the relay and the destination nodes may not be correct. We analyze the optimal throughput with respect to n, given a series of parameters and derive the upper and lower bounds of throughput performance. We also analyze the impact of the number of relays and the erasure probability on the throughput performance. Simulation results are well matched with the theoretical analysis.

The application of complex network theory to power grid analysis has been a hot topic in recent years, which mainly manifests itself in four aspects. The first aspect is to model power system networks. The second aspect is to reveal the topology of the grid itself. The third aspect is to reveal the inherent vulnerability and weakness of the power network itself and put forward the pertinent improvement measures to provide guidance for the construction of power grid. The last aspect is to analyze the mechanism of cascading failure and establish the cascading fault model of large power failure. In the past ten years, by using the complex network theory, many researchers have investigated the structural vulnerability of power grids from the point of view of topology. This letter studies the structural vulnerability of power grids according to the effect of selective node removal. We apply several kinds of node centralities including recently-presented second-order centrality (SOC) to guide the node removal attack. We test the effectiveness of all these centralities in guiding the node removal based on several IEEE power grids. Simulation results show that, compared with other node centralities, the SOC is relatively effective in guiding the node removal and can destroy the power grid with negative degree-degree correlation in less steps.

To use millimeter wave bands in future cellular and outdoor wireless networks, understanding the multipath cluster characteristics such as delay and angular spread for different polarization is very important besides knowing the path loss and other large scale propagation parameters. This paper presents result from analysis of wide-band full polarimetric double directional channel measurement at the millimeter wave band in a typical urban pico-cell environment. Only limited number of multipath clusters with gains ranging from -8dB to -26.8dB below the free space path loss and mainly due to single reflection, double reflection and diffraction, under both line of sight (LOS) and obstructed LOS conditions are seen. The cluster gain and scattering intensity showed strong dependence on polarization. The scattering intensities for ϑ-ϑ polarization were seen to be stronger compared to ϕ-ϕ polarization and on average 6.1dB, 5.6dB and 4.5dB higher for clusters due to single reflection, double reflection and scattering respectively. In each cluster, the paths are highly concentrated in the delay domain with delay spread comparable to the delay resolution of 2.5ns irrespective of polarization. Unlike the scattering intensity, the angular spread of paths in each cluster did not show dependence on polarization. On the base station side, average angular spread in azimuth and in elevation were almost similar with ≤3.3° spread in azimuth and ≤3.2° spread in elevation for ϑ-ϑ polarization. These spreads were slightly smaller than those observed for ϕ-ϕ polarization. On the mobile station side the angular spread in azimuth was much higher compared to the base station side. On average, azimuth angular spread of ≤11.4° and elevation angular spread of ≤5° are observed for ϑ-ϑ polarization. These spreads were slightly larger than in ϕ-ϕ polarization. Knowing these characteristics will be vital for more accurate modeling of the channel, and in system and antenna design.

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.

Silicon-on-insulator (SOI) has become one of the most famous materials in recent years, especially in silicon photonics applications. This paper presents a comparative performance of a SOI-based optical interconnect (OI) vs. an electrical interconnect (EI) for high-speed performances at a circuit level. The SOI-based optical waveguide was designed using OptiBPM to obtain a single mode condition (SMC). Then, the optical interconnect (OI) link was simulated in OptiSPICE and was tested as an interconnection in two-stage CS amplifiers. The results showed that the two-stage CS amplifier using OI offered several advantages in terms of electrical performances, such as voltage gain, frequency bandwidth, slew rate, and propagation delay, which makes it superior to the EI.

This paper presents the design and experimental evaluation of 60GHz small cell radio access based on IEEE 802.11ad/WiGig. The access point (AP) prototype used combines three RF modules with beamforming technology to provide 360° area coverage. In order to compensate for limited communication distance, multiple APs are employed to achieve wide area coverage. A handover algorithm suitable for IEEE 802.11ad/WiGig is employed to achieve flexible control of the cell coverage of each AP. As a proof of concept, a prototype system is set up at Narita International Airport and the capability of multiuser Gb/s wireless access is successfully demonstrated. In addition, the system behavior under stringent conditions is evaluated by load testing and throughput degradation due to co-channel and inter-channel interference is investigated.

An automotive control system is a typical safety-critical embedded software, which requires extensive verification and validation (V&V) activities. This article introduces a toolset for automated V&V of automotive control system, including a test generator for automotive operating systems, a task simulator for validating task design of control software, and an API-call constraint checker to check emergent properties when composing control software with its underlying operating system. To the best of our knowledge, it is the first integrated toolset that supports V&V activities for both control software and operating systems in the same framework.

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.

Self-Aligned Quadruple Patterning (SAQP) is an important manufacturing technique for sub 14nm technology node. Although various routing algorithms for SAQP have been proposed, it is not easy to find a dense SAQP compliant routing pattern efficiently. Even though a grid for SAQP compliant routing pattern was proposed, it is not easy to find a valid routing pattern on the grid. The routing pattern of SAQP on the grid consists of three types of routing. Among them, third type has turn prohibition constraint on the grid. Typical routing algorithms often fail to find a valid routing for third type. In this paper, a simple directed grid-graph for third type is proposed. Valid SAQP compliant two dimensional routing patterns are found effectively by utilizing the proposed directed grid-graph. Experiments show that SAQP compliant routing patterns are found efficiently by our proposed method.

Decentralized channel assignment schemes are proposed to obtain low system-wide spatial overlap regions in wireless local area networks (WLANs). The important point of channel assignment in WLANs is selecting channels with fewer contending stations rather than mitigating interference power due to its medium access control mechanism. This paper designs two potential game-based channel selection schemes, basically each access point (AP) selects a channel with smaller spatial overlaps with other APs. Owing to the property of potential games, each decentralized channel assignment is guaranteed to converge to a Nash equilibrium. In order that each AP selects a channel with smaller overlaps, two metrics are proposed: general overlap-based scheme yields the largest overlap reduction if a sufficient number of stations (STAs) to detect overlaps are available; whereas decomposed overlap-based scheme need not require such STAs, while the performance would be degraded due to the shadowing effect. In addition, the system-wide overlap area is analytically shown to be upper bounded by the negative potential functions, which derives the condition that local overlap reduction by each AP leads to system-wide overlap reduction. The simulation results confirm that the proposed schemes perform better reductions in the system-wide overlap area compared to the conventional interference power-based scheme under the spatially correlated shadowing effect. The experimental results demonstrate that the channel assignment dynamics converge to stable equilibria even in a real environment, particularly when uncontrollable APs exist.

Deploying low power nodes (LPNs), which reuse the spectrum licensed to a macrocell network, is considered to be a promising way to significantly boost network capacity. Due to the spectrum-sharing, the deployment of LPNs could trigger the severe problem of interference including intra-tier interference among dense LPNs and inter-tier interference between LPNs and the macro base station (MBS), which influences the system performance strongly. In this paper, we investigate a spectrum-sharing approach in the downlink for two-tier networks, which consists of small cells (SCs) with several LPNs and a macrocell with a MBS, aiming to mitigate the interference and improve the capacity of SCs. The spectrum-sharing approach is described as a multi-objective optimization problem. The problem is solved by the nondominated sorting genetic algorithm version II (NSGA-II), and the simulations show that the proposed spectrum-sharing approach is superior to the existing one.

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.

Locally repairable codes have recently been applied in distributed storage systems because of their excellent local erasure-correction capability. A locally repairable code is a code with locality r, where each code symbol can be recovered by accessing at most r other code symbols. In this paper, we study the existence and construction of binary cyclic codes with locality 2. An overview of best binary cyclic LRCs with length 7≤n≤87 and locality 2 are summarized here.

Small group detection is still a challenging problem in crowds. Traditional methods use the trajectory information to measure pairwise similarity which is sensitive to the variations of group density and interactive behaviors. In this paper, we propose two types of information by simultaneously incorporating trajectory and interaction information, to detect small groups in crowds. The trajectory information is used to describe the spatial proximity and motion information between trajectories. The interaction information is designed to capture the interactive behaviors from video sequence. To achieve this goal, two classifiers are exploited to discover interpersonal relations. The assumption is that interactive behaviors often occur in group members while there are no interactions between individuals in different groups. The pairwise similarity is enhanced by combining the two types of information. Finally, an efficient clustering approach is used to achieve small group detection. Experiments show that the significant improvement is gained by exploiting the interaction information and the proposed method outperforms the state-of-the-art methods.

Replacement of highly stressed logic gates with internal node control (INC) logics is known to be an effective way to alleviate timing degradation due to NBTI. We propose a path clustering approach to accelerate finding effective replacement gates. Upon the observation that there exist paths that always become timing critical after aging, critical path candidates are clustered to select representative path in each cluster. With efficient data structure to further reduce timing calculation, INC logic optimization has first became tractable in practical time. Through the experiments using a processor, 171x speedup has been demonstrated while retaining almost the same level of mitigation gain.

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.

This paper presents a technique to reduce the quantum cost by making temporary changes to the functionality of a given Boolean function. This technique is one of the very few known methods based on manipulating Exclusive-or Sum-Of-Products (ESOP) expressions to reduce the quantum cost of the corresponding circuit. The idea involves adding Mixed Polarity Multiple-Control Toffoli (MPMCT) gates to temporarily change the functionality of the given function, so that the modified function has a smaller quantum cost. To compensate for the temporary change, additional gates are inserted into the circuit. The proposed method finds a small ESOP expression for the given function, and then finds a good pair of product terms in the ESOP expression so that the quantum cost can be reduced by applying the transformation. The proposed approach is likely to produce a better quantum cost reduction than the existing methods, and indeed experimental results confirm this expectation.

We study a reconfiguration problem for Steiner trees in an unweighted graph, which determines whether there exists a sequence of Steiner trees that transforms a given Steiner tree into another one by exchanging a single edge at a time. In this paper, we show that the problem is PSPACE-complete even for split graphs, while solvable in linear time for interval graphs and for cographs.

During the development of a human embryo, the position of eyes moves medially and caudally in the viscerocranium. A statistical model of this process can play an important role in embryology by facilitating qualitative analyses of change. This paper proposes an algorithm to construct a spatiotemporal statistical model for the eyeballs of a human embryo. The proposed modeling algorithm builds a statistical model of the spatial coordinates of the eyeballs independently for each Carnegie stage (CS) by using principal component analysis (PCA). In the process, a q-Gaussian distribution with a model selection scheme based on the Aaike information criterion is used to handle a non-Gaussian distribution with a small sample size. Subsequently, it seamlessly interpolates the statistical models of neighboring CSs, and we present 10 interpolation methods. We also propose an estimation algorithm for the CS using our spatiotemporal statistical model. A set of images of eyeballs in human embryos from the Kyoto Collection was used to train the model and assess its performance. The modeling results suggested that information geometry-based interpolation under the assumption of a q-Gaussian distribution is the best modeling method. The average error in CS estimation was 0.409. We proposed an algorithm to construct a spatiotemporal statistical model of the eyeballs of a human embryo and tested its performance using the Kyoto Collection.