Controlling synchrony as well as desynchrony in a network of neuronal oscillators has been one of the focus issues in nonlinear science and engineering. It has been well known that spike stimuli injected commonly to multiple neurons can synchronize them if the strength of the common spike stimuli is high enough. Our recent study showed that this common spike-induced synchrony could be suppressed by introducing heterogeneity to inhibitory connections, through which the common spikes are transmitted. The aim of the present study is apply this methodology to electronic neurons as a real physical hardware. Using an Axon-Hillock circuit that represents basic properties of the leaky integrate-and-fire (LIF) neuron, our experiment demonstrated that the method was quite effective for desynchronizing the neuron circuits. The experimental results are also in a good agreement with the linear response theory that describes the input-output relationship of LIF neurons. Our method of suppressing the neuronal synchrony should be of practical use for enhancement of neural information processing as well as for improvement of pathological state of the brain.

A simple but efficient method for evaluating the channel capacity of 2×2 multiple-input multiple-output (MIMO) antenna systems is proposed. First, the channel capacity of a half-wavelength dipole array antenna is calculated using the Monte Carlo method by changing the incident-wave signal-to-noise power ratio, the power difference between two elements, and the correlation coefficient. Using the calculated results, a polynomial function is derived by multivariate regression analysis to estimate the channel capacity. The validity of the developed function is confirmed by comparing the channel capacity estimated by the developed function with that calculated by the Monte Carlo method using a MIMO array antenna operated under various scenarios, including antenna-human body electromagnetic interactions and radio-wave propagation environments, for future MIMO systems. The function is also validated by means of two experimental approaches: the use of radiation patterns measured in an anechoic chamber and the use of a spatial fading emulator that can create a two-dimensional fading environment.

Thin films of vinyl derivatives of naphthalene diimide were prepared by electron-assisted vapor deposition. Monomer materials of N, N'-bis(allyl)-naphthalene diimide (Allyl-NDI) and N,N'-bis(p-vinyl-benzyl)-naphthalene diimide (Sty-NDI) were newly synthesized for this purpose. Uniform films were obtained by vapor-depositing these materials, whereas spin-coating yielded nonuniform films. IR analysis suggested that Sty-NDI can be polymerized upon vapor deposition. An insoluble film of Sty-NDI was obtained by the electron-assisted vapor deposition. On the other hand, Allyl-NDI had lower reactivity for polymerization. It was concluded that Sty-NDI is a promising material for preparing thin films of vinyl polymer having naphthalene diimide units.

Class imbalance has drawn much attention of researchers in software defect prediction. In practice, the performance of defect prediction models may be affected by the class imbalance problem. In this paper, we present an approach to evaluating the performance stability of defect prediction models on imbalanced datasets. First, random sampling is applied to convert the original imbalanced dataset into a set of new datasets with different levels of imbalance ratio. Second, typical prediction models are selected to make predictions on these new constructed datasets, and Coefficient of Variation (C·V) is used to evaluate the performance stability of different models. Finally, an empirical study is designed to evaluate the performance stability of six prediction models, which are widely used in software defect prediction. The results show that the performance of C4.5 is unstable on imbalanced datasets, and the performance of Naive Bayes and Random Forest are more stable than other models.

Recently, the Static Heterogeneous Particle Swarm Optimization (SHPSO) has been studied by more and more researchers. In SHPSO, the different search behaviours assigned to particles during initialization do not change during the search process. As a consequence of this, the inappropriate population size of exploratory particles could leave the SHPSO with great difficulties of escaping local optima. This motivated our attempt to improve the performance of SHPSO by introducing the dynamic heterogeneity. The self-adaptive heterogeneity is able to alter its heterogeneous structure according to some events caused by the behaviour of the swarm. The proposed triggering events are confirmed by keeping track of the frequency of the unchanged global best position (pg) for a number of iterations. This information is then used to select a new heterogeneous structure when pg is considered stagnant. According to the different types of heterogeneity, DHPSO-d and DHPSO-p are proposed in this paper. In, particles dynamically use different rules for updating their position when the triggering events are confirmed. In DHPSO-p, a global gbest model and a pairwise connection model are automatically selected by the triggering configuration. In order to investigate the scalability of and DHPSO-p, a series of experiments with four state-of-the-art algorithms are performed on ten well-known optimization problems. The scalability analysis of and DHPSO-p reveals that the dynamic self-adaptive heterogeneous structure is able to address the exploration-exploitation trade-off problem in PSO, and provide the excellent optimal solution of a problem simultaneously.

In this paper, the performance of a vehicle information sharing (VIS) system for an intersection collision warning system (ICWS) is analyzed. The on-board unit (OBU) of the ICWS sharing obstacle detection sensor information (ICWS-ODSI) is mounted on a vehicle, and it obtains information about the surrounding vehicles, such as their position and velocity, by its in-vehicle obstacle detection sensors. These information are shared with other vehicles via an intervehicle communication network. In this analysis, a T-junction is assumed as the road environment for the theoretical analysis of the VIS performance in terms of the mean of entire vehicle information acquiring probability (MEVIAP). The MEVIAP on OBU penetration rate indicated that the ICWS-ODSI is superior to the conventional VIS system that only shares its own individual driving information via an intervehicle communication network. Furthermore, the MEVIAP on the sensing range of the ICWS-ODSI is analyzed, and it was found that the ISO15623 sensor used for the forward vehicle collision warning system becomes a candidate for the in-vehicle detection sensor of ICWS-ODSI.

We have developed membrane distributed Bragg reflector (DBR) lasers on thermally oxidized Si substrate (SiO2/Si substrate) to evaluate the parameters of the on-Si lasers we have been developing. The lasers have InGaAsP-based multi-quantum wells (MQWs) grown on InP substrate. We used direct bonding to transfer this active epitaxial layer to SiO2/Si substrate, followed by epitaxial growth of InP to fabricate a buried-heterostructure (BH) on Si. The lateral p-i-n structure was formed by thermal diffusion of Zn and ion implantation of Si. For the purpose of evaluating laser parameters such as internal quantum efficiency and internal loss, we fabricated long-cavity lasers that have 200- to 600-µm-long active regions. The fabricated DBR lasers exhibit threshold currents of 1.7, 2.1, 2.8, and 3.7mA for active-region lengths of 200, 300, 400, and 600µm, respectively. The differential quantum efficiency also depends on active-region length. In addition, the laser characteristics depend on the distance between active region and p-doped region. We evaluated the internal loss to be 10.2cm-1 and internal quantum efficiency to be 32.4% with appropriate doping profile.

Dry etching is one of the elemental technologies for the fabrication of optical devices. In order to obtain the desired shape using the dry etching process, it is necessary to understand the reactivity of the materials being used to plasma. In particular, III-V compound semiconductors have a multi-layered structure comprising a plurality of elements and thus it is important to first have a full understanding of the basic trends of plasma dry etching, the plasma type and the characteristics of etching plasma sources. In this paper, III-V compound semiconductor etching for use in light sources such as LDs and LEDs, will be described. Glass, LN and LT used in the formation of waveguides and MLA will be introduced as well. And finally, the future prospects of dry etching will be described briefly.

Due to heavy rendering load and unstable frame rate when rendering large terrain, this paper proposes a geometry clipmaps based algorithm. Triangle meshes are generated by few tessellation control points in GPU tessellation shader. ‘Cracks’ caused by different resolution between adjacent levels are eliminated by modifying outer tessellation level factor of shared edges between levels. Experimental results show the algorithm is able to improve rendering efficiency and frame rate stability in terrain navigation.

We consider a decentralized similarity control problem for composite nondeterministic discrete event systems, where each subsystem has its own local specification and the entire specification is described as the synchronous composition of local specifications. We present necessary and sufficient conditions for the existence of a complete decentralized supervisor that solves a similarity control problem under the assumption that any locally uncontrollable event is not shared by other subsystems. We also show that the system controlled by the complete decentralized supervisor that consists of maximally permissive local supervisors is bisimilar to the one controlled by the maximally permissive monolithic supervisor under the same assumption.

In this paper, a new method of model predictive control (MPC) for a multi-hop control network (MHCN) is proposed. An MHCN is a control system in which plants and controllers are connected through a multi-hop wireless network. In the proposed method, (i) control inputs and (ii) paths used in transmission of control inputs are computed with constant period by solving the finite-time optimal control problem. First, a mathematical model for expressing an MHCN is proposed. This model is given by a switched linear system, and is compatible with MPC. Next, the finite-time optimal control problem using this model is formulated, and is reduced to a mixed integer quadratic programming problem. Finally, a numerical example is presented to show the effectiveness of the proposed method.

This paper focus on the development of a single portable roadside magnetic sensor for vehicle classification. The magnetic sensor is a kind of anisotropic magnetic device that do not require to be embedded in the roadway-the device is placed next to the roadway and measure traffic in the immediately adjacent lane. A novel feature extraction and comparison approach is presented for vehicle classification with a single magnetic sensor, which is based on four different feature sets extracted from the detected magnetic signal. Furthermore, vehicle classification has been achieved with three common classification algorithms, including support vector machine, k-nearest neighbors and back-propagation neural network. Experimental results have demonstrated that the Peak-Peak feature set with back-propagation neural network approach performs much better than other approaches. Besides, the normalization technology has been proved it does work.

As the scaling of CMOS technology advances, the characteristics of transistors are evolving toward digital circuit design. This means conventional analog design techniques are getting harder to apply to advanced technology, because of the low power supply voltage, narrow dynamic range of switching properties, and low trans-conductance of transistors. Despite such circumstances, analog-to-digital converter (ADC) performance is still advancing, thanks to innovative new architectures. This paper reviews the recent trend of ADCs, exploring their performance as well as use of the time interleave scheme, non-static current amplifiers, and hybrid architectures.

HTTP Adaptive Streaming (HAS) has become a popular solution for multimedia delivery nowadays. Because of throughput variations, video quality fluctuates during a streaming session. Therefore, a main challenge in HAS is how to evaluate the overall video quality of a session. In this paper, we explore the impacts of quality values and quality variations in HAS. We propose to use the histogram of segment quality values and the histogram of quality gradients in a session to model the overall video quality. Subjective test results show that the proposed model has very high prediction performance for different videos. Especially, the proposed model provides insights into the influence factors of the overall quality, thus leading to suggestions to improve the quality of streaming video.

In this paper we use equivalent circuits to analyze the wavelengths in a Fast and Slow wave Waffle-iron Ridge Guide (FS-WRG). An equivalent circuit for the transverse direction is employed and the transverse resonance method is used to determine the fast wave wavelength. Another equivalent circuit, for the inserted series reactance in the waveguide, is employed for the fast and slow wave wavelength. We also discuss the physical system that determines the wavelengths and the accuracy of this analysis by comparing the wavelengths with those calculated by EM-simulation. Furthermore, we demonstrate use of the results obtained in designing an array antenna.

The Helmholtz-Kohlrausch (H-K) effect is a phenomenon in which the perceived brightness levels induced by two stimuli are different even when two color stimuli have the same luminance and different chroma in a particular hue. This phenomenon appears on display devices, and the wider the gamut these devices have, the more the perceived brightness is affected by the H-K effect. The quantification of this effect can be expected to be useful for the development and evaluation of a wide range of display devices. However, quantification of the H-K effect would require considerable subjective evaluation experimentation, which would be a major burden. Therefore, the authors have derived perceived brightness maps for natural images using an estimation equation for the H-K effect without experimentation. The results of comparing and analyzing the calculated maps and ground truth maps obtained through subjective evaluation experiments confirm strong correlation coefficients between such maps overall. However, a tendency for the estimation of the calculation map to be poor on high chroma strongly influenced by the H-K effect was also confirmed. In this study, we propose an accuracy improvement method for the estimation of the H-K effect by correcting the calculation maps using a correction coefficient obtained by focusing on this tendency, and we confirm the effectiveness of our method.

In this paper, a hardware efficient design methodology for a configurable-point multiple-stream pipeline FFT processor is presented. We first compared the memory and arithmetic components of different pipeline FFT architectures, and obtained the conclusion that MDF architecture is more hardware efficient than MDC for the overall processor. Then, in order to reduce the computational complexity, a binary-tree representation was adopted to analyze the decomposition algorithm. Consequently, the coefficient multiplications are minimized among all the decomposition probabilities. In addition, an efficient output reorder circuit was designed for the multiple-stream architecture. An 128∼2048 point 4-stream FFT processor in LTE system was designed in SMIC 55nm technology for evaluation. It owns 1.09mm2 core area with 82.6mW power consumption at 122.88MHz clock frequency.

Powerful jammers are able to disable consumer-grade global navigation satellite system (GNSS) receivers under normal operating conditions. Conventional anti-jamming techniques based on the time-domain are unable to effectively suppress wide-band interference, such as chirp-like jammer. This paper proposes a novel anti-jamming architecture, combining wavelet packet signal analysis with adaptive filtering theory to mitigate chirp interference. Exploiting the excellent time-frequency resolution of wavelet technologies makes it possible to generate a reference chirp signal, which is basically a “de-noised” jamming signal. The reference jamming signal then is fed into an adaptive predictor to function as a refined jamming signal such that it predicts a replica of the jammer from the received signal. The refined chirp signal is then subtracted from the received signal to realize the aim of anti-jamming. Simulation results demonstrate the effectiveness of the proposed method in combating chirp interference in Galileo receivers. We achieved jamming-to-signal power ratio (JSR) of 50dB with an acquisition probability exceeding 90%, which is superior to many anti-jamming techniques based on the time-domain, such as conventional adaptive notch filters. The proposed method was also implemented in an software-defined GPS receiver for further validation.

Anonymous password-based authentication protocols are designed to provide not only password-based authentication but also client anonymity. In [22], Qian et al. proposed a simple anonymous password-based authentication protocol (SAPAKE). In this paper, we reconsider the SAPAKE protocol [22] by first showing that an (third party) active attacker can impersonate the server and compute a session key with probability 1. After giving a formal model that captures such attacks, we propose a simple and secure anonymous password-based authentication (for short, S2APA) protocol that provides security against modification attacks on protocol-specific values and is more efficient than YZWB09/10 [32], [33] and SAPAKE [22]. Also, we prove that the S2APA protocol is AKE-secure against active attacks as well as modification attacks under the computational Diffie-Hellman problem in the random oracle model, and provides unconditional client anonymity against a semi-honest server, who honestly follows the protocol.

Labeling a salient region accurately in video with cluttered background and complex motion condition is still a challenging work. Most existing video salient region detection models mainly extract the stimulus-driven saliency features to detect the salient region in video. They are easily influenced by the cluttered background and complex motion conditions. It may lead to incomplete or wrong detection results. In this paper, we propose a video salient region detection framework by fusing the stimulus-driven saliency features and spatiotemporal consistency cue to improve the performance of detection under these complex conditions. On one hand, stimulus-driven spatial saliency features and temporal saliency features are extracted effectively to derive the initial spatial and temporal salient region map. On the other hand, in order to make use of the spatiotemporal consistency cue, an effective spatiotemporal consistency optimization model is presented. We use this model optimize the initial spatial and temporal salient region map. Then the superpixel-level spatiotemporal salient region map is derived by optimizing the initial spatiotemporal salient region map. Finally, the pixel-level spatiotemporal salient region map is derived by solving a self-defined energy model. Experimental results on the challenging video datasets demonstrate that the proposed video salient region detection framework outperforms state-of-the-art methods.