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.

As the number of electronic control units (ECUs) or sensors connected to a controller area network (CAN) bus increases, so does the bus load. When a CAN bus is overloaded by a large number of ECUs, both the waiting time and the error probability of the data transmission are increased. Because the duration of the data transmission is proportional to the frame length, it is desirable to reduce the CAN frame length. In this paper, we present an improved CAN data-reduction (DR) algorithm to reduce the amount of data to be transferred in the CAN frame length. We also implement the data reduction algorithm using the CANoe software, and measure the CAN bus load using a CANcaseXL device. Experimental results with a Kia Sorento vehicle indicate that we can obtain additional average compression ratio of 11.15% with the proposed method compared with the ECANDC algorithm. By using the CANoe software, we show that the average message delay is within 0.10ms and the bus load can be reduced by 23.45% with 20 ECUs using the proposed method compared with the uncompressed message.

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.

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.

This letter presents a method for solving several linear equations in max-plus algebra. The essential part of these equations is reduced to constraint satisfaction problems compatible with mixed integer programming. This method is flexible, compared with optimization methods, and suitable for scheduling of certain discrete event systems.

In this paper, we present an FPGA hardware implementation for a phylogenetic tree reconstruction with a maximum parsimony algorithm. We base our approach on a particular stochastic local search algorithm that uses the Progressive Neighborhood and the Indirect Calculation of Tree Lengths method. This method is widely used for the acceleration of the phylogenetic tree reconstruction algorithm in software. In our implementation, we define a tree structure and accelerate the search by parallel and pipeline processing. We show results for eight real-world biological datasets. We compare execution times against our previous hardware approach, and TNT, the fastest available parsimony program, which is also accelerated by the Indirect Calculation of Tree Lengths method. Acceleration rates between 34 to 45 per rearrangement, and 2 to 6 for the whole search, are obtained against our previous hardware approach. Acceleration rates between 2 to 36 per rearrangement, and 18 to 112 for the whole search, are obtained against TNT.

In this letter, we explore joint optimization of perceptual gain function and deep neural networks (DNNs) for a single-channel speech enhancement task. A DNN architecture is proposed which incorporates the masking properties of the human auditory system to make the residual noise inaudible. This new DNN architecture directly trains a perceptual gain function which is used to estimate the magnitude spectrum of clean speech from noisy speech features. Experimental results demonstrate that the proposed speech enhancement approach can achieve significant improvements over the baselines when tested with TIMIT sentences corrupted by various types of noise, no matter whether the noise conditions are included in the training set or not.

High Efficiency Video Coding (HEVC/H.265) obtains 50% bit rate reduction than H.264/AVC standard with comparable quality at the cost of high computational complexity. Merge mode is one of the most important new features introduced in HEVC's inter prediction. Merge mode and traditional inter mode consume about 90% of the total encoding time. To address this high complexity, this paper utilizes the merge mode to accelerate inter prediction by four strategies. 1) A merge candidate decision is proposed by the sum of absolute transformed difference (SATD) cost. 2) An early merge termination is presented with more than 90% accuracy. 3) Due to the compensation effect of merge candidates, symmetric motion partition (SMP) mode is disabled for non-8×8 coding units (CUs). 4) A fast coding unit filtering strategy is proposed to reduce the number of CUs which need to be fine-processed. Experimental results demonstrate that our fast strategies can achieve 35.4%-58.7% time reduction with 0.68%-1.96% BD-rate increment in RA case. Compared with similar works, the proposed strategies are not only among the best performing in average-case complexity reduction, but also notably outperforming in the worst cases.

Self-paced e-learning provides much more freedom in time and locale than traditional education as well as diversity of learning contents and learning media and tools. However, its limitations must not be ignored. Lack of information on learners' states is a serious issue that can lead to severe problems, such as low learning efficiency, motivation loss, and even dropping out of e-learning. We have designed a novel e-learning support system that can visually observe learners' non-verbal behaviors and estimate their learning states and that can be easily integrated into practical e-learning environments. Three pairs of internal states closely related to learning performance, concentration-distraction, difficulty-ease, and interest-boredom, were selected as targets of recognition. In addition, we investigated the practical problem of estimating the learning states of a new learner whose characteristics are not known in advance. Experimental results show the potential of our system.

Process variation has become prominent in the advanced CMOS technology, making the timing of fabricated circuits more uncertain. In this paper, we propose a Layout-Aware Path Selection (LAPS) technique to accurately estimate the circuit timing variation from a small set of paths. Three features of paths are considered during the path selection. Experiments conducted on benchmark circuits with process variation simulated with VARIUS show that, by selecting only hundreds of paths, the fitting errors of timing distribution are kept below 5.3% when both spatial correlated and spatial uncorrelated process variations exist.

RAID has been widely deployed in disk array storage systems to manage both performance and reliability simultaneously. RAID conducts two performance-critical operations during disk failures known as degraded reads/writes and recovery process. Before the recovery process is complete, reads and writes are degraded because data is reconstructed using data redundancy. The performance of degraded reads/writes is critical in order to meet stipulations in customer service level agreements (SLAs), and the recovery process affects the reliability of a storage system considerably. Both operations require fast data reconstruction. Among the erasure codes for fast reconstruction, Local Reconstruction Codes (LRC) are known to offer the best (or optimal) trade-off between storage overhead, fault tolerance, and the number of disks involved in reconstruction. Originally, LRC was designed for fast reconstruction in distributed cloud storage systems, in which network traffic is a major bottleneck during reconstruction. Thus, LRC focuses on reducing the number of disks involved in data reconstruction, which reduces network traffic. However, we observe that when LRC is applied to primary array storage systems, a major bottleneck in reconstruction results from uneven disk utilization. In other words, underutilized disks can no longer receive I/O requests as a result of the bottleneck of overloaded disks. Uneven disk utilization in LRC is due to its dedicated group partitioning policy to achieve the Maximally Recoverable property. In this paper, we present Distributed Reconstruction Codes (DRC) that support fast reconstruction in primary array storage systems. DRC is designed with group shuffling policy to solve the problem of uneven disk utilization. Experiments on real-world workloads show that DRC using global parity rotation (DRC-G) improves degraded performance by as much as 72% compared to RAID-6 and by as much as 35% compared to LRC under the same reliability. In addition, our study shows that DRC-G reduces the recovery process completion time by as much as 52% compared to LRC.

An optical intensity distribution under light irradiation in the organic photovoltaic cell affects the absorbance of the active layer, which determines the photovoltaic performance. In this research, we evaluated the optimum thickness of the organic active layer with poly[4,8-bis(5-(2-ethylhexyl)thiophen-2-yl)benzo[1,2-b;4,5-b']dithiophene-2,6-diyl-alt-(4-(2-ethylhexyl)-3-fluorothieno[3,4-b]thiophene-)-2-carboxylate-2-6-diyl)] and [6,6]-phenyl C71-butyric acid methyl ester. The spectral response of external quantum efficiency was good agreement with the simulated optical intensity distribution within a device stack as a function of the position and the wavelength. As a result, the highest photoconversion efficiency of 10.1% was achieved for the inverted device structure.

In this paper, we propose a method to find similar sentences based on language resources for building a parallel corpus between English and Korean from Wikipedia. We use a Wiki-dictionary consisted of document titles from the Wikipedia and bilingual example sentence pairs from Web dictionary instead of traditional machine readable dictionary. In this way, we perform similarity calculation between sentences using sequential matching of the language resources, and evaluate the extracted parallel sentences. In the experiments, the proposed parallel sentences extraction method finally shows 65.4% of F1-score.

Rapid process scaling and the introduction of the multilevel cell (MLC) concept have lowered costs of NAND Flash memories, but also degraded reliability. For this reason, the memories are depending on strong error correcting codes (ECCs), and this has enabled the memories to be used in wide range of storage applications, including solid-state drives (SSDs). Meanwhile, too strong error correcting capability requires excessive decoding complexity and check bits. In NAND Flash memories, cell errors to neighborhood voltage levels are more probable than those to distant levels. Several ECCs reflecting this characteristics, including limited-magnitude ECCs which correct only errors with a certain limited magnitude and low-density parity check (LDPC) codes, have been proposed. However, as most of these ECCs need the multiple bits in a cell for encoding, they cannot be used with multipage programing, a high speed programming method currently employed in the memories. Also, binary ECCs with Gray codes are no longer optimal when multilevel voltage shifts (MVSs) occur. In this paper, an error correction method reflecting the error characteristic is presented. This method detects errors by a binary ECC as a conventional manner, but a nonbinary value or whole the bits in a cell, are subjected to error correction, so as to be corrected into the most probable neighborhood value. The amount of bit error rate (BER) improvement is depending on the probability of the each error magnitude. In case of 2bit/cell, if only errors of magnitude 1 and 2 can occur and the latter occupies 5% of cell errors, acceptable BER is improved by 4%. This is corresponding to extending 2.4% of endurance. This method needs about 15% longer average latency, 19% longer maximum latency, and 15% lower throughput. However, with using the conventional method until the memories' lifetime number of program/erase cycling, and the proposed method after that, BER improvement can be utilized for extending endurance without latency and throughput degradation until the switch of the methods.

Wafers with smooth Au thin films (rms surface roughness: < 0.5nm, thickness: < 50nm) were successfully bonded in ambient air at room temperature after an Ar radio frequency plasma activation process. The room temperature bonded glass wafers without any heat treatment showed a sufficiently high die-shear strength of 47-70MPa. Transmission electron microscopy observations showed that direct bonding on the atomic scale was achieved. This surface-activated bonding method is expected to be a useful technique for future heterogeneous photonic integration.

We present a novel receiver for reliable IoT communications. In this letter, it is assumed that IoT communications are based on ZigBee under frequency-selective indoor environments. The ZigBee includes IEEE 802.15.4 specification for low-power and low-cost communications. The presented receiver fully follows the specification. However, the specification exhibits extremely low performance under frequency-selective environments. Therefore, a channel estimation approach is proposed for reliable communications under frequency-selective fading indoor environments. The estimation method relies on FFT operations, which are usually embedded in cellular phones. We also suggest a correlation method for accurate recovery of original information. The simulation results show that the proposed receiver is very suitable for IoT communications under frequency-selective indoor environments.

Active oxygen species (AOS), e.g., excited singlet oxygen atom [O(1D)], excited singlet oxygen molecules (1O2), ground-state oxygen atom [O(3P)] and hydroxyl radical (OH), generated under two wavelengths (185 and 254 nm) of ultraviolet (UV) light were exposed to polyethylene (PE), polypropylene (PP) and polystyrene (PS) sheets. We investigated effects of the AOS exposure on the surface modification of these polymer sheets. Nonwoven sheet was used for the surface modification to eliminate an effect of the UV light irradiation. Although hydrophobicity of the PE and PP surfaces was maintained, the PS was changed into the hydrophilic surface.

We have developed Pedestrian-Vehicular Collision Avoidance Support System (P-VCASS) in order to protect pedestrians from traffic accidents and its effectiveness has been verified. P-VCASS is a system that takes into account pedestrian's moving situations. It gives warning to drivers of neighboring vehicles in advance if there is a possibility of collision between vehicles and pedestrians. There are pedestrians to move around. They are dangerous for vehicle drivers because they have high probability of running out into the road suddenly. Hence, we need to take into account the presence of them. In this paper, we propose a new estimation method of pedestrian's running out into road by using pressure sensor and moving record. We show the validity of the proposed system by experiments using a vehicle and a pedestrian terminal in the intersection. As a result, we show that a driver of vehicle is able to detect dangerous pedestrians quickly and accurately.

This paper presents human-centered video feature selection via mRMR-SCMMCCA (minimum Redundancy and Maximum Relevance-Specific Correlation Maximization Multiset Canonical Correlation Analysis) algorithm for preference extraction. The proposed method derives SCMMCCA, which simultaneously maximizes two kinds of correlations, correlation between video features and users' viewing behavior features and correlation between video features and their corresponding rating scores. By monitoring the derived correlations, the selection of the optimal video features that represent users' individual preference becomes feasible.