This paper proposes a method for retrieving human motion data with concise retrieval rules based on the spatio-temporal features of motion appearance. Our method first converts motion clip into a form of clausal language that represents geometrical relations between body parts and their temporal relationship. A retrieval rule is then learned from the set of manually classified examples using inductive logic programming (ILP). ILP automatically discovers the essential rule in the same clausal form with a user-defined hypothesis-testing procedure. All motions are indexed using this clausal language, and the desired clips are retrieved by subsequence matching using the rule. Such rule-based retrieval offers reasonable performance and the rule can be intuitively edited in the same language form. Consequently, our method enables efficient and flexible search from a large dataset with simple query language.

A low power impulse radio ultra-wideband (IR-UWB) receiver for DC-960 MHz band is proposed in this paper. The proposed receiver employs multiple DC power-free charge-domain sampling correlators to eliminate the need for phase synchronization. To alleviate BER degradation due to an increased charge injection in a subtraction operation in the sampling correlator than that of an addition operation, a comparator with variable threshold (=offset) voltage is used, which enables an addition-only operation. The developed receiver fabricated in 1.2 V 65 nm CMOS achieves the lowest energy consumption of 17.6 pJ/bit at 100 Mbps in state-of-the-art correlation-based UWB receivers.

Chinese new words and their part-of-speech (POS) are particularly problematic in Chinese natural language processing. With the fast development of internet and information technology, it is impossible to get a complete system dictionary for Chinese natural language processing, as new words out of the basic system dictionary are always being created. A latent semi-CRF model, which combines the strengths of LDCRF (Latent-Dynamic Conditional Random Field) and semi-CRF, is proposed to detect the new words together with their POS synchronously regardless of the types of the new words from the Chinese text without being pre-segmented. Unlike the original semi-CRF, the LDCRF is applied to generate the candidate entities for training and testing the latent semi-CRF, which accelerates the training speed and decreases the computation cost. The complexity of the latent semi-CRF could be further adjusted by tuning the number of hidden variables in LDCRF and the number of the candidate entities from the Nbest outputs of the LDCRF. A new-words-generating framework is proposed for model training and testing, under which the definitions and distributions of the new words conform to the ones existing in real text. Specific features called "Global Fragment Information" for new word detection and POS tagging are adopted in the model training and testing. The experimental results show that the proposed method is capable of detecting even low frequency new words together with their POS tags. The proposed model is found to be performing competitively with the state-of-the-art models presented.

To deal with the increasing number of mobile devices accessing the Internet and the increasing demands of mobility management, IETF has proposed Mobile IPv6 and its fast handover protocol FMIPv6. In FMIPv6, the possibility of Care-of Address (CoA) collision and the time for Return Routability (RR) procedure result in long handover delay, which makes it unsuitable for real-time applications. In this paper, we propose an improved handover scheme for FMIPv6, which reduces the handover delay by using proactive CoA acquisition, configuration and test method. In our proposal, collision-free CoA is proactively prepared, and the time for RR procedure does not contribute to the handover delay. Furthermore, we analyze our proposal's benefits and overhead tradeoff. The numerical results demonstrate that it outperforms the current schemes, such as FMIPv6 and enhanced FMIPv6, on the aspect of handover delay and packet transmission delay.

The mobility control of mobile nodes can be an alternative to the transmitting power adjustment in case that fixed transmitting power is just used in the topology control. Assuming the controllable mobility of nodes, we propose four distributed mobility control algorithms assuring the network connectivity and the capacity improvement. We compare the throughput of each algorithm with the widely accepted capacity scale law considering the energy consumption. The proposed mobility-based topology control algorithms are named according to its operational characteristics; RP (Rendezvous Point), NNT (Nearest Neighbor Tracking), DM (Diffusion Model), and GP (Grid Packing). Through extensive simulations, we show that all the proposed algorithms successfully change a partitioned random network topology into a connected network topology without the power control. Furthermore, the topology reconfigured by the mobility control has the improved network capacity beyond that of the initial network. In the newly defined performance metric, effective capacity, the simulation results show that GP provides more improved and stable performance over various node densities with the short completion time.

A diversity scheme with Fractional Sampling (FS) in an OFDM receiver has been investigated recently. Through FS, it is possible to separate multipath components and obtain diversity gain in OFDM systems. Enlargement of the bandwidth of the total frequency response between transmit and receive baseband filters allows the FS scheme to achieve path diversity. However, the transmit filter has to be designed according to the spectrum mask of the wireless standards such as IEEE802.11a/g to avoid interference to the other communication systems and the frequency response of the composite channel including the transmit and receive filters has often been set to minimal bandwidth to eliminate adjacent channel signals. In order to achieve the maximum signal-to-noise ratio (SNR), the same filter is commonly used in the transmitter and the receiver. In this paper, the trade-off among the SNR deterioration, adjacent channel interference, and the diversity gain due to the enlargement of the bandwidth of the receive filter is investigated. Numerical results from computer simulations indicate that the BER performance with wider bandwidth in the receiver shows better performance than that with the minimal bandwidth for maximizing the SNR in certain conditions.

We study fast inversion of the Paillier encryption function. Especially, we focus only on key generation, and do not modify the Paillier encryption function. We propose three key generation algorithms based on the speeding-up techniques for the RSA encryption function. By using our algorithms, the size of the private CRT exponent is half of that of Paillier-CRT. The first algorithm employs the extended Euclidean algorithm. The second algorithm employs factoring algorithms, and can construct the private CRT exponent with low Hamming weight. The third algorithm is a variant of the second one, and has some advantage such as compression of the private CRT exponent and no requirement for factoring algorithms. We also propose the settings of the parameters for these algorithms and analyze the security of the Paillier encryption function by these algorithms against known attacks. Finally, we give experimental results of our algorithms.

LCD Automatic Vision Inspection (AVI) systems automatically detect defect features and measure their sizes via camera vision. AVI systems usually report different measurements on the same defect with some variations on position or rotation mainly because we get different images. This is caused by possible variations in the image acquisition process including optical factors, non-uniform illumination, random noise, and so on. For this reason, conventional area based defect measuring method has some problems in terms of robustness and consistency. In this paper, we propose a new defect size measuring method to overcome these problems. We utilize volume information which is completely ignored in the area based conventional defect measuring method. We choose a bell shape as a defect model for experiment. The results show that our proposed method dramatically improves robustness of defect size measurement. Given proper modeling, the proposed volume based measuring method can be applied to various types of defect for better robustness and consistency.

Traditionally, popular synonym acquisition methods are based on the distributional hypothesis, and a metric such as Jaccard coefficients is used to evaluate the similarity between the contexts of words to obtain synonyms for a query. On the other hand, when one tries to compile and clean a thesaurus, one often already has a modest number of synonym relations at hand. Could something be done with a half-built thesaurus alone? We propose the use of spectral methods and discuss their relation to other network-based algorithms in natural language processing (NLP), such as PageRank and Bootstrapping. Since compiling a thesaurus is very laborious, we believe that adding the proposed method to the toolkit of thesaurus constructors would significantly ease the pain in accomplishing this task.

Future high-resolution short-range automotive radar will have a higher false alarm probability than the conventional low-resolution radar has. In a high-resolution radar, the reception signal becomes sensitive to the difference between intended and unintended objects. However, automotive radars must distinguish targets from background objects that are the same order of size; it leads to an increase in the false alarm probability. In this paper, a CFAR circuit for obtaining the target mean power, as well as the background mean power, is proposed to reduce the false alarm probability for high-resolution radars working in automotive environments. The proposed method is analytically evaluated with use of the characteristic function method. Spatial correlation is also considered in the evaluation, because the sizes of the both target and background objects approach the dimension of several range cells. Result showed the proposed CFAR with use of two alongside range cells could reduce the ratio of 6.4 dB for an example of an automotive situation.

We propose a moving picture coding by lapped transform and an edge adaptive deblocking filter to reduce the blocking distortion. We apply subband coding (SBC) with lapped transform (LT) and zero pruning set partitioning in hierarchical trees (zpSPIHT) to encode the difference picture. Effective coding using zpSPIHT was achieved by quantizing and pruning the quantized zeros. The blocking distortion caused by block motion compensated prediction is reduced by an edge adaptive deblocking filter. Since the original edges can be detected precisely at the reference picture, an edge adaptive deblocking filter on the predicted picture is very effective. Experimental results show that blocking distortion has been visually reduced at very low bit rate coding and better PSNRs of about 1.0 dB was achieved.

In this paper, an efficient method is proposed to accurately analyze large-scale power/ground (P/G) networks, where inductive parasitics are modeled with the partial reluctance. The method is based on frequency-domain circuit analysis and the technique of vector fitting, and obtains the time-domain voltage response at given P/G nodes. The frequency-domain circuit equation including partial reluctances is derived, and then solved with the GMRES algorithm with rescaling, preconditioning and recycling techniques. With the merit of sparsified reluctance matrix and iterative solving techniques for the frequency-domain circuit equations, the proposed method is able to handle large-scale P/G networks with complete inductive modeling. Numerical results show that the proposed method is orders of magnitude faster than HSPICE, several times faster than INDUCTWISE, and capable of handling the inductive P/G structures with more than 100,000 wire segments.

In modern sensor networks, key management is essential to transmit data from sensors to the sink securely. That is, sensors are likely to be compromised by attackers, and a key management scheme should renew the keys for communication as frequently as possible. In clustered sensor networks, CHs (Cluster Heads) tend to become targets of compromise attack because they collect data from sensors and deliver the aggregated data to the sink. However, existing key renewal schemes do not change the CH role nodes, and thus they are vulnerable to the compromise of CHs. Our scheme is called DIRECT (DynamIc key REnewal using Cluster head elecTion) because it materializes the dynamic key renewals through secure CH elections. In the scheme, the network is divided into sectors to separate CH elections in each sector from other sectors. Then, sensors establish pairwise keys with other sensors in their sector for intra-sector communication. Every CH election round, all sensors securely elect a CH in their sector by defeating the malicious actions of attackers. Therefore, the probability that a compromised node is elected as a CH decreases significantly. The simulation results show that our approach significantly improves the integrity of data, energy efficiency, and network longevity.

The recent growth in available network bandwidth envisions the wide-spread use of broadband applications such as uncompressed HD-SDI (High-definition serial digital interface) over IP. These cutting-edge applications are also driving the development of a media-oriented infrastructure for networked collaboration. This paper introduces imCast, a high-quality digital media platform dealing with uncompressed HD-SDI over IP, and discusses its internal architecture in depth. imCast mainly provides cost-effective hardware-based approaches for high-quality media acquisition and presentation; flexible software-based approaches for presentation; and allows for economical network transmission. Experimental results (taken over best-effort IP networks) will demonstrate the functional feasibility and performance of imCast.

This paper presents a novel cross-layer approach to explore selection diversity for distributed clustering based wireless sensor networks (WSNs) by selecting a proper cluster-head. We develop and analyze an instantaneous channel state information (CSI) based cluster-head selection algorithm for a distributed, dynamic and randomized clustering based WSN. The proposed cluster-head selection scheme is also random and capable to distribute the energy uses among the nodes in the network. We present an analytical approach to evaluate the energy efficiency and system lifetime of our proposal. Analysis shows that the proposed scheme outperforms the performance of additive white Gaussian noise (AWGN) channel under Rayleigh fading environment. This proposal also outperforms the existing cooperative diversity protocols in terms of system lifetime and implementation complexity.

We designed and fabricated 4H-SiC PIN avalanche photodiodes (APD) for UV detection. The thickness of an intrinsic layer in a PIN structure was optimized in order to achieve the highest quantum efficiency at the wavelength of interest. The optimized 4H-SiC PIN APDs exhibited a maximum external quantum efficiency of >80% at the wavelength of 280 nm and a gain greater than 40000. Both electrical and optical characteristics of the fabricated APDs were in agreement with those predicted from simulation.

Traditional double auction protocols only concern the price information of participants without considering their QoS requirements, which makes them unsuitable for the service grid. In this paper we first introduce QoS information into double auction to present the QoS-enabled Double Auction Protocol (QDAP). QDAP tries to assign the asks which have the least candidate bids firstly to make more participants trade and provides QoS guarantee at the same time. Simulation experiments have been performed to compare QDAP with two traditional double auction protocols and the result shows that QDAP is more suitable for the service grid.

The manner of a person's eye movement conveys much about nonverbal information and emotional intent beyond speech. This paper describes work on expressing emotion through eye behaviors in virtual agents based on the parameters selected from the AU-Coded facial expression database and real-time eye movement data (pupil size, blink rate and saccade). A rule-based approach to generate primary (joyful, sad, angry, afraid, disgusted and surprise) and intermediate emotions (emotions that can be represented as the mixture of two primary emotions) utilized the MPEG4 FAPs (facial animation parameters) is introduced. Meanwhile, based on our research, a scripting tool, named EEMML (Emotional Eye Movement Markup Language) that enables authors to describe and generate emotional eye movement of virtual agents, is proposed.

An improved bidirectional search algorithm for computing the weight spectrum of convolutional codes is presented. This algorithm does not employ the column distance function of a code which plays an important role in the original bidirectional search algorithm. We show the proposed algorithm can reduce computaion time for obtaining the weigth spectrum of convolutional codes significantly compared with that of the bidirectional search algorithm.

Differential-phase-shift (DPS) quantum key distribution (QKD) is one scheme of quantum key distribution whose security is based on the quantum nature of lightwave. This protocol features simplicity, a high key creation rate, and robustness against photon-number-splitting attacks. We describe DPS-QKD in this paper, including its setup and operation, eavesdropping against DPS-QKD, system performance, and modified systems to improve the system performance.