This paper presents an ontology-based driving decision making system, which can promptly make safety decisions in real-world driving. Analyzing sensor data for improving autonomous driving safety has become one of the most promising issues in the autonomous vehicles research field. However, representing the sensor data in a machine understandable format for further knowledge processing still remains a challenging problem. In this paper, we introduce ontologies designed for autonomous vehicles and ontology-based knowledge base, which are used for representing knowledge of maps, driving paths, and perceived driving environments. Advanced Driver Assistance Systems (ADAS) are developed to improve safety of autonomous vehicles by accessing to the ontology-based knowledge base. The ontologies can be reused and extended for constructing knowledge base for autonomous vehicles as well as for implementing different types of ADAS such as decision making system.

Shrinking feature sizes and higher levels of integration in semiconductor device manufacturing technologies are increasingly causing the gap between defect levels estimated in the design stage and reported ones for fabricated devices. In this paper, we propose a unified weighted fault coverage approach that includes both bridge and open faults, considering the critical area as the incident rate of each fault. We then propose a test pattern reordering scheme that incorporates our weighted fault coverage with an aim to reduce test costs. Here we apply a greedy algorithm to reorder test patterns generated by the bridge and stuck-at automatic test pattern generator (ATPG), evaluating the relationship between the number of patterns and the weighted fault coverage. Experimental results show that by applying this reordering scheme, the number of test patterns was reduced, on average, by approximately 50%. Our results also indicate that relaxing coverage constraints can drastically reduce test pattern set sizes to a level comparable to traditional 100% coverage stuck-at pattern sets, while targeting the majority of bridge faults and keeping the defect level to no more than 10 defective parts per milion (DPPM) with a 99% manufacturing yield.

This letter proposes a heuristic algorithm to select check variables, which are points of comparison for error detection, for soft-error tolerant datapaths. Our soft-error tolerance scheme is based on check-and-retry computation and an efficient resource management named speculative resource sharing (SRS). Starting with the smallest set of check variables, the proposed algorithm repeats to add new check variable one by one incrementally and find the minimum latency solution among the series of generated solutions. During the process, each new check variable is selected so that the opportunity of SRS is enlarged. Experimental results show that improvements in latency are achieved compared with the choice of the smallest set of check variables.

The 1-bit band-pass delta-sigma modulator (BP-DSM) achieves high resolution by using the oversampling technique. This method allows direct RF signal transmission from a digitally modulated signal, using a 1-bit digital pulse train. However, it has been previously reported that the adjacent channel leakage ratio (ACLR) in a target frequency band degrades due to the pulse transition mismatch between rising and falling waveforms in the time domain. This paper clarifies that the spurious distortion in BP-DSM is caused by the asymmetricity of the waveform about the center of an eye pattern in the time axis, and proposes a 1-bit BP-DSM with the compensator consisting of a fractional delay filter and a binary data differentiator to cancel out the asymmetry in the target frequency band. This can accurately provide a wideband cancellation signal with more than 100MHz bandwidth, including the adjacent channel, within 50dB power dynamic range. Using long term evolution (LTE) signals with 5MHz bandwidth at 0.8GHz, we simulated the spurious distortion, performing various combinations of rising and falling times in the eye pattern, and the proposed 1-bit BP-DSM always achieved high ACLR, up to 60dB, in 140MHz bandwidth, under all conditions.

This paper describes, for the first time, an experimental study on the layout design considerations of GaAs HBT MMIC switchable-amplifier-chain-based power amplifiers (SWPAs) for CDMA handsets. The transient response of the quiescent current and output power (Pout) in GaAs HBT power amplifiers that consist of a main chain and a sub-chain is often affected by a thermal coupling between power stages and their bias circuits in the same chain or a thermal coupling between power stages and/or their bias circuits in different chains. In particular, excessively strong thermal coupling inside the MMIC SWPA causes failure in 3GPP-compliant inner loop power control tests. An experimental study reveals that both the preheating in the main/sub-chains and appropriate thermal coupling inside the main chain are very effective in reducing the turn-on delay for the two-parallel-amplifier-chain topology; for example, i) the sub-power stage is arranged near the main power stage, ii) the sub-driver stage is placed near the main driver stage and iii) the main driver bias circuit is placed near the main power stage and the sub-power stage. The SWPA operating in Band 9 (1749.9 to 1784.9 MHz), which was designed and fabricated from the foregoing considerations, shows a remarkable improvement in the Pout turn-on delay: a reduced power level error of 0.74 dB from turn-off to turn-on in the sub-amplifier chain and a reduced power level error of over 0.30 dB from turn-off to turn-on in the main amplifier chain. The main RF power measurements conducted with a 3.4-V supply voltage and a Band 9 WCDMA HSDPA modulated signal are as follows. The SWPA delivers a Pout of 28.5 dBm, a power gain (Gp) of 28 dB, and a PAE of 39% while restricting the ACLR1 to less than -40 dBc in the main amplifier chain. In the sub-amplifier chain, 17 dBm of Pout, 23.5 dB of Gp, and 27% of PAE are obtained at the same ACLR1 level.

Image quality assessment (IQA) plays an important role in quality monitoring, evaluation and optimization for image processing systems. However, current quality-aware feature extraction methods for IQA can hardly balance accuracy and complexity. This paper introduces multi-order local description into image quality assessment for feature extraction. The first-order structure derivative and high-order discriminative information are integrated into local pattern representation to serve as the quality-aware features. Then joint distributions of the local pattern representation are modeled by spatially enhanced histogram. Finally, the image quality degradation is estimated by quantifying the divergence between such distributions of the reference image and those of the distorted image. Experimental results demonstrate that the proposed method outperforms other state-of-the-art approaches in consideration of not only accuracy that is consistent with human subjective evaluation, but also robustness and stability across different distortion types and various public databases. It provides a promising choice for image quality assessment development.

Recently, a high dimensional classification framework has been proposed to introduce spatial structure information in classical single kernel support vector machine optimization scheme for brain image analysis. However, during the construction of spatial kernel in this framework, a huge adjacency matrix is adopted to determine the adjacency relation between each pair of voxels and thus it leads to very high computational complexity in the spatial kernel calculation. The method is improved in this manuscript by a new construction of tensorial kernel wherein a 3-order tensor is adopted to preserve the adjacency relation so that calculation of the above huge matrix is avoided, and hence the computational complexity is significantly reduced. The improvement is verified by experimental results on classification of Alzheimer patients and cognitively normal controls.

A new class of visible light communication (VLC) systems, namely image sensor (IS) based VLC systems, has emerged. An IS consists of a two-dimensional (2D) array of photodetectors (PDs), and then VLC systems with an IS receiver are capable of exploiting the spatial dimensions invoked for transmitting information. This paper aims for providing a brief survey of topics related to the IS-based VLC, and then provides a matrix representation of how to map a series of one dimensional (1D) symbols onto a set of 2D symbols for efficiently exploit the associate grade of freedom offered by 2D VLC systems. As an example, the matrix representation is applied to the symbol mapping of layered space-time coding (L-STC), which is presented to enlarge the coverage of IS-based VLC that is limited by pixel resolution of ISs.

The purpose of this study was to examine an efficient interval encoding method with a slow-frame-rate image sensor, and show that the encoding can work to capture heart rates from multiple persons. Visible light communication (VLC) with an image sensor is a powerful method for obtaining data from sensors distributed in the field with their positional information. However, the capturing speed of the camera is usually not fast enough to transfer interval information like the heart rate. To overcome this problem, we have developed an event timing (ET) encoding method. In ET encoding, sensor units detect the occurrence of heart beat event and send their timing through a sequence of flashing lights. The first flash signal provides the rough timing and subsequent signals give the precise timing. Our theoretical analysis shows that in most cases the ET encoding method performs better than simple encoding methods. Heart rate transfer from multiple persons was examined as an example of the method's capabilities. In the experimental setup, the developed system successfully monitored heart rates from several participants.

A power packet dispatching system is proposed to realize the function of power on demand. This system distributes electrical power in quantized form, which is called power processing. This system has extensibility and flexibility. Here, we propose to use the power packet dispatching system as the next generation power distribution system in self-established and closed system such as robots, cars, and aircrafts. This paper introduces the concept and the required researches to take the power packet dispatching system in practical phase from the total viewpoints of devices, circuits, power electronics, system control, computer network, and bio-inspired power consumption.

Locally repairable codes (LRCs) have attracted much interest recently due to their applications in distributed storage systems. In an [n,k,d] linear code, a code symbol is said to have locality r if it can be repaired by accessing at most r other code symbols. An (n,k,r) LRC with locality r for the information symbols has minimum distance d≤n-k-⌈k/r⌉+2. In this letter, we study single-parity LRCs where every repair group contains exactly one parity symbol. Firstly, we give a new characterization of single-parity LRCs based on the standard form of generator matrices. For the optimal single-parity LRCs meeting the Singleton-like bound, we give necessary conditions on the structures of generator matrices. Then we construct all the optimal binary single-parity LRCs meeting the Singleton-like bound d≤n-k-⌈k/r⌉+2.

Spatial modulation (SM) is introduced into layered space-time coding (L-STC) used in image sensor (IS)-based visible light communication (VLC) systems. STC was basically investigated for extending the communication range of the IS-based VLC link [10], although it is out of the range when IS receivers are at the long distance from the LED array of the transmitter where the number of pixels capturing the transmitter on the image plane is less than the number of LEDs of the array. Furthermore, L-STC was done in [11] for increasing the reception rate with improving the pixel resolution while the receiver was approaching the transmitter. In this paper, SM is combined into L-STC by mapping additional information bits on the location of the pair of STC bit matrices of each layer. Experimental results show that additional SM bits are extracted with no error, without deteriorating the reception quality of and shrinking the transmission range of the original L-STC.

In general, semi-supervised clustering can outperform unsupervised clustering. Since 2001, pairwise constraints for semi-supervised clustering have been an important paradigm in this field. In this paper, we show that pairwise constraints (ECs) can affect the performance of clustering in certain situations and analyze the reasons for this in detail. To overcome these disadvantages, we first outline some exemplars constraints. Based on these constraints, we then describe a semi-supervised clustering framework, and design an exemplars constraints expectation-maximization algorithm. Finally, standard datasets are selected for experiments, and experimental results are presented, which show that the exemplars constraints outperform the corresponding unsupervised clustering and semi-supervised algorithms based on pairwise constraints.

In this paper, we propose an algorithm that enhances the number of pixels for high-speed imaging. High-speed cameras have a principle problem that the number of pixels reduces when the number of frames per second (fps) increases. To enhance the number of pixels, we suppose an optical structure that block-randomly selects some percent of pixels in an image. Then, we need to reconstruct the entire image. For this, a state-of-the-art method takes three-dimensional reconstruction strategy, which requires a heavy computational cost in terms of time. To reduce the cost, the proposed method reconstructs the entire image frame-by-frame using a new cost function exploiting two types of sparsity. One is within each frame and the other is induced from the similarity between adjacent frames. The latter further means not only in the image domain, but also in a sparsifying transformed domain. Since the cost function we define is convex, we can find the optimal solution using a convex optimization technique with small computational cost. We conducted simulations using grayscale image sequences. The results show that the proposed method produces a sequence, mostly the same quality as the state-of-the-art method, with dramatically less computational time.

Particle filter algorithm is an important algorithm in the field of target tracking. however, this algorithm faces the problem of sample impoverishment which is caused by the introduction of re-sampling and easily affected by illumination variation. This problem seriously affects the tracking performance of a particle filter algorithm. To solve this problem, we introduce a particle filter target tracking algorithm based on a dynamic niche genetic algorithm. The application of this dynamic niche genetic algorithm to re-sampling ensures particle diversity and dynamically fuses the color and profile features of the target in order to increase the algorithm accuracy under the illumination variation. According to the test results, the proposed algorithm accurately tracks the target, significantly increases the number of particles, enhances the particle diversity, and exhibits better robustness and better accuracy.

This paper presents the formal analysis of the feature negotiation and connection management procedures of the Datagram Congestion Control Protocol (DCCP). Using state space analysis we discover an error in the DCCP specification, that result in both ends of the connection having different agreed feature values. The error occurs when the client ignores an unexpected Response packet in the OPEN state that carries a valid Confirm option. This provides an evidence that the connection management procedure and feature negotiation procedures interact. We also propose solutions to rectify the problem.

In the field of action recognition, Spatio-Temporal Interest Points (STIPs)-based features have shown high efficiency and robustness. However, most of state-of-the-art work to describe STIPs, they typically focus on 2-dimensions (2D) images, which ignore information in 3D spatio-temporal space. Besides, the compact representation of descriptors should be considered due to the costs of storage and computational time. In this paper, a novel local descriptor named 3D Gradient LBP is proposed, which extends the traditional descriptor Local Binary Patterns (LBP) into 3D spatio-temporal space. The proposed descriptor takes advantage of the neighbourhood information of cuboids in three dimensions, which accounts for its excellent descriptive power for the distribution of grey-level space. Experiments on three challenging datasets (KTH, Weizmann and UT Interaction) validate the effectiveness of our approach in the recognition of human actions.

This paper studies the supervisory control of partially observed quantitative discrete event systems (DESs) under the fixed-initial-credit energy objective. A quantitative DES is modeled by a weighted automaton whose event set is partitioned into a controllable event set and an uncontrollable event set. Partial observation is modeled by a mapping from each event and state of the DES to the corresponding masked event and masked state that are observed by a supervisor. The supervisor controls the DES by disabling or enabling any controllable event for the current state of the DES, based on the observed sequences of masked states and masked events. We model the control process as a two-player game played between the supervisor and the DES. The DES aims to execute the events so that its energy level drops below zero, while the supervisor aims to maintain the energy level above zero. We show that the proposed problem is reducible to finding a winning strategy in a turn-based reachability game.

In this paper, MWAN (Mobile Wireless Ad hoc Networks with internet connection) is considered, which is a solution for many tasks owing to its ease of use, and practicality. Recently, MWAN is required to support large data like multimedia data transfer and it is transferred through several relay nodes. There are 2 problems that cause difficulties for large data transfer through a mobile network. First one is rerouting delay by handoff and second one is network congestion caused by handoff. Also, faulty data transfer caused by handoff delay makes extra load and causes some problems for MWAN. To solve these problems and get network reliability, we propose a new multipath routing scheme that can provide solution for seamless connection while handoff. In the proposed scheme, our MWAN can support multiple paths for data transfer, maintain end-to-end connection while handoff and get new route quickly. The performance of the proposed scheme is evaluated and compared with other multipath routing scheme to show the improvement.

60GHz wireless communication requires analog baseband circuits having a bandwidth of about 1GHz. This paper presents a wide bandwidth current-mode low pass filter technique which involves current amplifiers, resistors and capacitors. The proposed current-mode filter is obtained by replacing an integrator employing an op-amp with another integrator employing a current amplifier. With the low input impedance current amplifier having little variation of the input impedance, the proposed filter is expected to improve linearity and power efficiency. The proposed current amplifier which employs super source follower topology with complementary input is suitable for the filter because of its class AB operation. Although simulation results shows the conventional current amplifier which employs super source follower topology without the complementary input has 12Ω variation and 30Ω input impedance, the proposed current amplifier has 1Ω variation and 21Ω input impedance. A fourth order 1GHz bandwidth filter which involves the proposed current amplifiers is designed in a 65nm CMOS technology. The filter can achieve IIP3 of 1.3dBV and noise of 0.6mVrms with power consumption of 13mW under supply voltage of 1.2V according to simulation results with layout parasitic extraction models. Active area of the filter is 380μm×170μm.