Pairing based cryptosystems can accomplish novel security applications such as ID-based cryptosystems, which have not been constructed efficiently without the pairing. The processing speed of the pairing based cryptosystems is relatively slow compared with the other conventional public key cryptosystems. However, several efficient algorithms for computing the pairing have been proposed, namely Duursma-Lee algorithm and its variant ηT pairing. In this paper, we present an efficient implementation of the pairing over some mobilephones. Moreover, we compare the processing speed of the pairing with that of the other standard public key cryptosystems, i.e. RSA cryptosystem and elliptic curve cryptosystem. Indeed the processing speed of our implementation in ARM9 processors on BREW achieves under 100 milliseconds using the supersingular curve over F397. In addition, the pairing is more efficient than the other public key cryptosystems, and the pairing can be achieved enough also on BREW mobilephones. It has become efficient enough to implement security applications, such as short signature, ID-based cryptosystems or broadcast encryption, using the pairing on BREW mobilephones.

This paper considers the problem of contention resolution algorithm for multi-class with quality of service (QoS) constrained for wireless communication. Five different channel reservation schemes are proposed, namely, UNI+MLA, UNI+DS, UNI+DS+MLA, Partial UNI and Partial UNI+MLA schemes for multimedia traffic, all are extensions of our recently proposed UNI scheme for single-class traffic. The goal is to achieve the highest system performance and enable each traffic type to meet its QoS requirements. We evaluate the performance of each scheme by mathematical analysis. The numerical results show that our proposed schemes are effective in enabling each traffic type to achieve the best successful rate possible in this kind of environment. Finally when comparing between our proposed schemes and conventional technique in terms of both throughput performance and QoS requirements it is found that the UNI+MLA, UNI+DS+MLA and Partial UNI+MLA schemes are relatively efficient and suitable for practical applications.

In this paper, we design a new coded cooperation protocol utilizing superposition modulation together with iterative decoding/detection algorithms. The aim of the proposed system is to apply "dirty paper coding" theory in the context of half-duplex relay systems. In the proposed system, the node transmits a superposed signal which consists of its own coded information and other node's re-coded information. The destination node detects and decodes the signal using the received signals at two continuous time-slots with iterative decoding algorithm. Moreover, the destination node detects the received signal using the results of decoding, iteratively. This paper provides the outage probability of the proposed system under the assumption that the proposed system can ideally perform dirty paper coding, and it is shown from the comparison between outage probabilities and simulated results that the proposed system can get close to the dirty paper coding theory.

Spectrum and Bit Error Rate (BER) performance of a coded π/2 phase shift Non-Square (NS) 8 Quadrature Amplitude Modulation (QAM) system are studied in this letter. The modulation process of this scheme removes all 180 phase shift between adjacent constellation points and contains inherent memory which can be treated as a type of inner coding in coded system. Simulation results show that this modulation scheme has much lower spectrum regrowth and better BER performance when passing through nonlinear channel compared with conventional mode.

Based on cyclic difference sets, sequences with two-valued autocorrelation can be constructed. Using these constructed sequences, two classes of binary constant weight codes are presented. Some codes proposed in this paper are proven to be optimal.

In this paper, we propose a new model of automatically constructing an acronym dictionary. The proposed model generates possible acronym candidates from a definition, and then verifies each acronym-definition pair with a Naive Bayes classifier based on web documents. In order to achieve high dictionary quality, the proposed model utilizes the characteristics of acronym generation types: a syllable-based generation type, a word-based generation type, and a mixed generation type. Compared with a previous model recognizing an acronym-definition pair in a document, the proposed model verifying a pair in web documents improves approximately 50% recall on obtaining acronym-definition pairs from 314 Korean definitions. Also, the proposed model improves 7.25% F-measure on verifying acronym-definition candidate pairs by utilizing specialized classifiers with the characteristics of acronym generation types.

Very high-speed data services are demanded in the next generation wireless systems. However, the available bandwidth is limited. The use of multi-input multi-output (MIMO) multiplexing can increase the transmission rate without bandwidth expansion. For high-speed data transmission, however, the channel becomes severely frequency-selective and the achievable bit error rate (BER) performance degrades. In our previous work, we proposed the joint use of iterative frequency-domain parallel interference cancellation (PIC) and two-dimensional (2D) MMSE-FDE for the non-spread single-carrier (SC) transmission in a frequency-selective fading channel. The joint use of PIC and 2D MMSE-FDE can effectively suppress the inter-path interference (IPI) and the inter-code interference (ICI), resulting from the channel frequency-selectivity, and the interference from other antennas simultaneously. An iterative PIC with 2D MMSE-FDE has a high computational complexity. In this paper, to well suppress the interference from other antennas while reducing the computational complexity, we propose to replace 2D MMSE-FDE by 1D MMSE-FDE except for the initial iteration stage and to use multicode spread-spectrum (SS) transmission instead of the non-spread SC transmission. The BER performance of the proposed scheme in a frequency-selective Rayleigh fading channel is evaluated by computer simulation to show that the proposed scheme can basically match the BER performance of 2D MMSE-FDE with lower complexity.

This paper proposes a new minimum BER (MBER) criterion precoding method that is robust to imperfect channel state information (CSI) for MIMO-OFDM mobile communications. The proposed MBER precoding aims to minimize BER of the maximum likelihood detection (MLD), on the condition that the transmitter can obtain only imperfect CSI owing to channel estimation and quantization errors of the feedback CSI. The proposed scheme controls its precoding parameters under a transmit power constraint by minimizing an upper bound of BER which is derived from the pairwise error probability and averaged with respect to the CSI error. In contrast with a conventional power allocation MBER precoding method that is also robust to the CSI error, the proposed scheme does not make any assumption on the precoding parameters so as to reduce complexity. Thus, it is expected to outperform the conventional scheme at the cost of higher complexity. Computer simulations demonstrate that the proposed precoding method outperforms a conventional nonrobust MBER precoder and the conventional robust power allocation MBER precoding method when the amount of the CSI error is not considerable.

In this paper, we present a multiple capture approach to reducing the peak power as well as average power consumption during testing. The basic idea behind is to divide a scan chain into two sub-scan chains, and only one sub-scan chain will be enabled at a time during the scan shift or capture operations. We develop a pattern insertion technique to efficiently deal with the capture violation problem during the capture cycle. In order to alleviate the timing cost due to the insertion of redundant patterns, a scan chain partitioning method incorporated with test pattern reordering is developed to reduce the testing time. Experimental results for large ISCAS'89 benchmark circuits show that the proposed approach can efficiently reduce peak and average power with little timing overhead.

In this paper, we present an efficient fingerprint classification algorithm which is an essential component in many critical security application systems e.g. systems in the e-government and e-finance domains. Fingerprint identification is one of the most important security requirements in homeland security systems such as personnel screening and anti-money laundering. The problem of fingerprint identification involves searching (matching) the fingerprint of a person against each of the fingerprints of all registered persons. To enhance performance and reliability, a common approach is to reduce the search space by firstly classifying the fingerprints and then performing the search in the respective class. Jain et al. proposed a fingerprint classification algorithm based on a two-stage classifier, which uses a K-nearest neighbor classifier in its first stage. The fingerprint classification algorithm is based on the fingercode representation which is an encoding of fingerprints that has been demonstrated to be an effective fingerprint biometric scheme because of its ability to capture both local and global details in a fingerprint image. We enhance this approach by improving the efficiency of the K-nearest neighbor classifier for fingercode-based fingerprint classification. Our research firstly investigates the various fast search algorithms in vector quantization (VQ) and the potential application in fingerprint classification, and then proposes two efficient algorithms based on the pyramid-based search algorithms in VQ. Experimental results on DB1 of FVC 2004 demonstrate that our algorithms can outperform the full search algorithm and the original pyramid-based search algorithms in terms of computational efficiency without sacrificing accuracy.

This paper proposes a closed form solution to L2-sensitivity minimization of second-order state-space digital filters. Restricting ourselves to the second-order case of state-space digital filters, we can express the L2-sensitivity by a simple linear combination of exponential functions and formulate the L2-sensitivity minimization problem by a simple polynomial equation. As a result, the L2-sensitivity minimization problem can be converted into a problem to find the solution to a fourth-degree polynomial equation of constant coefficients, which can be algebraically solved in closed form without iterative calculations.

A motion refinement algorithm is proposed to enhance motion compensated noise reduction (MCNR) efficiency. Instead of the vector with minimum distortion, the vector with minimum distance from motion vectors of neighboring blocks is selected as the best motion vector among vectors which have distortion values within the range set by noise level. This motion refinement finds more accurate motion vectors in the noisy sequences. The MCNR with the proposed algorithm maintains the details of an image sequence very well without blurring and joggling. And it achieves 10% bit-usage reduction or 0.5 dB objective quality enhancement in subsequent video coding.

Due to the computational complexity of the optimum maximum likelihood detector (OMD) growing exponentially with the number of users, suboptimum techniques have received significant attention. We have proposed the particle swarm optimization (PSO) for the multiuser detection (MUD) in asynchronous multicarrier code division multiple access (MC-CDMA) system. The performance of PSO based MUD is near optimum, while its computational complexity is far less than OMD. Performance of PSO-MUD has also been shown to be better than that of genetic algorithm based MUD (GA-MUD) at practical SNR.

In this letter, a robust pilot-assisted synchronization scheme is proposed for estimation of residual frequency offset (RFO) in OFDM-based digital radio mondiale (DRM) system. The RFO estimator uses the gain reference pilots mainly reserved for the channel tracking in the DRM standard. To demonstrate the efficiency of the proposed RFO estimator, comparisons are made with the conventional RFO estimator using the frequency reference pilots in terms of mean square error (MSE) performance.

Effective classification and analysis of semantic contents are very important for the content-based indexing and retrieval of video database. Our research attempts to classify movie clips into three groups of commonly elicited emotions, namely excitement, joy and sadness, based on a set of abstract-level semantic features extracted from the film sequence. In particular, these features consist of six visual and audio measures grounded on the artistic film theories. A unique sieving-structured neural network is proposed to be the classifying model due to its robustness. The performance of the proposed model is tested with 101 movie clips excerpted from 24 award-winning and well-known Hollywood feature films. The experimental result of 97.8% correct classification rate, measured against the collected human-judges, indicates the great potential of using abstract-level semantic features as an engineered tool for the application of video-content retrieval/indexing.

Facial skin detection is an important step in facial surgical planning like as many other applications. There are many problems in facial skin detection. One of them is that the image features can be severely corrupted due to illumination, noise, and occlusion, where, shadows can cause numerous strong edges. Hence, in this paper, we present an automatic Expectation-Maximization (EM) algorithm for facial skin color segmentation that uses knowledge of chromatic space and varying illumination conditions to correct and segment frontal and lateral facial color images, simultaneously. The proposed EM algorithm leads to a method that allows for more robust and accurate segmentation of facial images. The initialization of the model parameters is very important in convergence of algorithm. For this purpose, we use a method for robust parameter estimation of Gaussian mixture components. Also, we use an additional class, which includes all pixels not modeled explicitly by Gaussian with small variance, by a uniform probability density, and amending the EM algorithm appropriately, in order to obtain significantly better results. Experimental results on facial color images show that accurate estimates of the Gaussian mixture parameters are computed. Also, other results on images presenting a wide range of variations in lighting conditions, demonstrate the efficiency of the proposed color skin segmentation algorithm compared to conventional EM algorithm.

In order to overcome the drawback of TVQI and to utilize the property of dimensionality increasing techniques, a novel model for Kernel TV-based Quotient Image employing Gabor analysis is proposed and applied to face recognition with only one sample per subject. To deal with illumination outliers, an enhanced TV-based quotient image (ETVQI) model is first adopted. Then for preprocessed images by ETVQI, a bank of Gabor filters is built to extract features at specified scales and orientations. Lastly, KPCA is introduced to extract final high-order and nonlinear features of extracted Gabor features. According to experiments on the CAS-PEAL face database, our model could outperform Gabor-based KPCA, TVQI and Gabor-based TVQI when they face most outliers (illumination, expression, masking etc.).

We studied planar graded-gap injector GaAs Gunn diodes designed for operation at 94 GHz. Two types of planar Gunn diodes were designed and fabricated. In the first diode, a cathode was situated inside a circular anode with a diameter of 190 µm. The distance between the anode and cathode varied from 60 µm to 68 µm depending on the cathode size. Also, we designed a structure with a constant distance between the anode and cathode of 10 µm. In the second diode, the anode was situated inside the cathode for the flip-chip mounting on the oscillator circuits. The fabrication of the Gunn diode was based on ohmic contact metallization, mesa etching, and air-bridge and overlay metallization. DC measurements were carried out, and the nature of the negative differential resistance, the operating voltage, and the peak current in the graded-gap injector GaAs Gunn diodes are discussed for different device structures. It is shown that the structure with the shorter distance between the cathode and anode has a higher peak current, higher breakdown voltage, and lower threshold voltage than those of the structure with the larger distance between the cathode and anode.

Efforts have been devoted to maximizing memory array densities. However, as the devices are scaled down in dimension and getting closer to each other, electrical interference phenomena among devices become more prominent. Various features of 3-D memory devices are proposed for the enhancement of memory array density. In this study, we mention 3-D NAND flash memory device having pillar structure as the representative, and investigate the paired cell interference (PCI) which inevitably occurs in the read operation for 3-D memory devices in this feature. Furthermore, criteria for setting up the read operation bias schemes are also examined in existence with PCI.

This paper presents an asynchronous design technique, an enabler for the emerging technology of flexible microelectronics that feature low-temperature processed polysilicon (LTPS) thin-film transistors (TFT) and surface-free technology by laser annealing/ablation (SUFTLA®). The first design instance chosen is an 8-bit microprocessor. LTPS TFTs are good for realizing displays having integrated VLSI circuit at lower costs. However, LTPS TFTs have drawbacks, including substantial deviations in characteristics and the self-heating phenomenon. To solve these problems, the authors adopted the asynchronous circuit design technique and developed an asynchronous design language called Verilog+, which is based on a subset of Verilog HDL® and includes minimal primitives used for describing the communications between modules, and the dedicated tools including a translator called xlator and a synthesizer called ctrlsyn. The flexible 8-bit microprocessor stably operates at 500 kHz, drawing 180 µA from a 5 V power source. The microprocessor's electromagnetic emissions are 21 dB less than those of the synchronous counterpart.