A dispersion diagram is useful in interpreting the characteristics of a periodic structure. In particular, the fast-wave region, where the wave is radiating, and the slow-wave region, where the wave is guided, can be determined from the dispersion diagram. An electronically-controlled composite right/left-handed (CRLH) transmission line (TL) was previously proposed and utilized as a leaky-wave (LW) antenna operating in the fast-wave region. However, since a guided-wave application operates in the slow-wave region, it is meaningful to study slow-wave effects of the proposed TL. In this paper, the dispersion diagram is used to investigate the slow-wave factor (SWF), which is necessary to understand the fast/slow-wave operations. Furthermore, the frequency characteristics are measured to find the cut-off frequencies in the LH and RH regions. Based on experimental results, it is observed at a fixed frequency, 2.6-GHz, that the phase of a proposed 6-cell structure can be changed by up to 280 in the LH slow-wave region.

UHF radio frequency identification (RFID) has gathered significant interest in the field of long-distance automatic identification applications. Since UHF RFID shares the frequency band with other RFID and/or other wireless systems, it is important to determine how much interference can be applied without causing a significant degradation of anti-collision speed. In this paper, the permissible link quality for RFID anti-collision in a practical environment is discussed by considering an erroneous communication link, taking into account of bit encoding and the type of interference. We approach the quantification of permissible link quality experimentally along with protocol simulations and the mathematical analyses. An international standard protocol, employing frame slotted ALOHA, was used as the air protocol. For these investigations, the present authors developed a protocol simulator. The simulation results were compared with analytical values based on Poisson distribution. The investigation in the return (tag to reader) link, and the forward (reader to tag) link, were analyzed separately. As result of the protocol simulation, it is generally important to secure the Pulse Error Rate 10-4 or better in both return and forward links for the anti-collision of 64 or less tags. The quality of the return link may be relaxed when the application does not require fast anti-collision. The degradation of the forward link, on the other hand, may entail loss of important commands, resulting in extremely slow anti-collision. It is measured experimentally that the required link quality can be relaxed by up to 10 dB in the return links and by 5 dB in the forward link when the primary source of interference originates in the interfering readers.

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.

Obtaining the best linear unbiased estimator (BLUE) of noisy signals is a traditional but powerful approach to noise reduction. Explicitly computing the BLUE usually requires the prior knowledge of the noise covariance matrix and the subspace to which the true signal belongs. However, such prior knowledge is often unavailable in reality, which prevents us from applying the BLUE to real-world problems. To cope with this problem, we give a practical procedure for approximating the BLUE without such prior knowledge. Our additional assumption is that the true signal follows a non-Gaussian distribution while the noise is Gaussian.

In [13], we proposed new decision problems related to lattices, and proved their NP-completeness. In this paper, we present a new public-key identification scheme and a digital signature scheme based on one of the problems in [13]. We also prove the security of our schemes under certain assumptions, and analyze the efficiency of ours.

In air navigation, the rotation of aircraft results in the discontinuous tracking of GNSS signals. As the platform rotates, the GNSS signals are subject to blanking effects. To solve this problem, a ring-type antenna array is used to prevent signal discontinuity and a hypothesis-test based detection scheme is developed so that the correct antenna combination can be formed to provide uninterrupted reception of GNSS signals in the presence of blanking, noise, and interferences. A fixed threshold detection scheme is first developed by assuming that the statistics of the noise are known. It is shown that the scheme is capable of differentiating signal from noise at each antenna element. To account for the interference effect, a multiple hypothesis test scheme, together with an adaptive selection rule, is further developed. Through this detection and selection process, it is shown, through simulations, that the desired GNSS signals can be extracted and successfully tracked in the presence of blanking and co-channel interference.

MUSIC-based estimation of direction of arrival (DOA) using universal steering vector (USV) is experimentally studied. A four-element array antenna and a four-channel receiver are employed for the experiment. In order to improve the accuracy of DOA estimation, USV which has already included the effect of mutual coupling between array elements and effect of array elements themselves is compensated to further include the electric delay and loss of four channels in the receiver. The compensated USV (C-USV) approach proposed in this paper does not need the time-consuming measurement of array element pattern because the compensating matrix for USV is obtained by measuring the S parameters between RF input ports of the feeding cables and IF output ports of the receiver. The experimental results of MUSIC-based DOA estimation show that C-USV approach is an accurate, effective and practical method for the MUSIC-based DOA estimation.

In this paper, we propose a reduced-complexity radial basis function (RBF)-assisted decision-feedback equalizer (DFE)-based turbo equalization (TEQ) scheme using a novel extended fuzzy c-means (FCM) algorithm, which not only is comparable in performance to the Jacobian RBF DFE-based TEQ but also is low-complexity. Previous TEQ research has shown that the Jacobian RBF DFE TEQ considerably reduces the computational complexity with similar performance, when compared to the logarithmic maximum a posteriori (Log-MAP) TEQ. In this study, the proposed reduced-complexity RBF DFE TEQ further greatly reduces the computational complexity and is capable of attaining a similar performance in contrast to the Jacobian RBF DFE TEQ in the context of both binary phase-shift keying (BPSK) modulation and 4 quadrature amplitude modulation (QAM). With this proposal, the materialization of the RBF-assisted TEQ scheme becomes more feasible.

Multiply-stacked structures of Si quantum dots (Si-QDs) in gate oxide are attracting much attention because of their potential importance to improve retention characteristics in a high density charge storage. In this work, we have fabricated 6-fold stacked Si-QDs with 2 nm-thick SiO2 interlayers, whose areal dot density and average dot size were 5.71011 cm-2 in each dot layer and 5 nm in height, and studied progress on electron distribution in 6-fold stacked Si-QDs with 2 nm-thick SiO2 interlayers from the measurements of temporal changes in the surface potential after electron charging and discharging locally at room temperature using an AFM/Kelvin probe technique in clean room air. First, by scanning an area of 22 µm2 with the AFM tip biased at +3 V with respect to the substrate in a tapping mode, the area was negatively charged due to electron injection from the substrate to the dot through the bottom tunnel oxide and subsequently, the central part of 100100 nm2 in the pre-charged area was scanned with the tip biased at -3 V to emit the electrons from the Si-QDs to the substrate. As a result, the negative charging level was markedly reduced in the central part in comparison to its peripheral region. And then, the surface potential of the negatively-charged peripheral region was decay monotonously with time as a result of progressive electron tunneling to the substrate. In contrast to this, the temporal change in the surface potential of the central part shows that the electron charging proceeds with time until the surface potential becomes almost the same as that in the peripheral region. This result can be interpreted in terms of lateral spreading of electrons stored in the Si-QDs layer due to the potential difference between the central part and its peripheral region more negatively charged.

Previously proposed batch signature schemes do not allow a signer to generate a signature immediately for sequentially asked signing queries. In this letter, we propose flexible batch signatures which do not need any waiting period and have very light computational overhead. Therefore our schemes are well suited for low power devices.

Code acquisition performance in the Direct-Sequence Code-Division Multiple-Access (DS/CDMA) communication system is strongly related to the quality of the communication systems. The performance is assessed by (i) code acquisition time; (ii) precision; and (iii) complexity for implementation. This paper applies the method of maximum likelihood (ML) to estimation of propagation delay in DS/CDMA communications, and proposes a low-complexity method for code acquisition. First, a DS/CDMA system model and properties of outputs with a passive matched-filter receiver are reviewed, and a statistical problem in code acquisition is mentioned. Second, an error-controllable code acquisition method based on the maximum likelihood is discussed. Third, a low-complexity ML code acquisition method is proposed. It is shown that the code acquisition time with the low-complexity method is about 1.5 times longer than that with the original ML method, e.g. 13 data periods under 4.96 dB.

Vertical handoff is a new type of handoff that is triggered when a mobile node moves over heterogeneous wireless networks with each proving different access bandwidth, transmission latency, and coverage. A mobile node can achieve higher throughput by accessing a higher bandwidth providing wireless network. However, TCP has to experience drastic changes of the bandwidth and the latency due to the vertical handoff which must be recognized as a network congestion, and this degrades end-to-end performance. In this paper, we propose a TCP context switching scheme, named Context-Switching TCP, that maintains TCP variables separately for different types of wireless networks. Through simulations, Context-Switching TCP shows higher performance than TCP SACK for vertical handoff. Especially, it shows much higher performance gain when vertical handoff occurs frequently.

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 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.

In multiple-input multiple-output (MIMO) cellular networks, certain schedulers have two independent phases: the first selects a group of users based on the scheduler criterion, and the second assigns the selected users to the transmit antennas by using an assignment scheme taking into consideration capacity maximization. Other schedulers directly select among the available channels between users and the base station in a centralized way. The schedulers of the first category can be implemented with lower complexity compared with the schedulers of the second category. For the first category, we propose three near-optimal assignment schemes with low complexities. We conducted a simulation in which the mobility of users was considered that demonstrated the superior performance of our assignment schemes. Furthermore, we analytically demonstrate their efficiency.

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.).

Recently, cyber attacks have become a serious hindrance to the stability of Internet. These attacks exploit interconnectivity of networks, propagate in an instant, and have become more sophisticated and evolutionary. Traditional Internet security systems such as firewalls, IDS and IPS are limited in terms of detecting recent cyber attacks in advance as these systems respond to Internet attacks only after the attacks inflict serious damage. In this paper, we propose a hybrid intrusion forecasting system framework for an early warning system. The proposed system utilizes three types of forecasting methods: time-series analysis, probabilistic modeling, and data mining method. By combining these methods, it is possible to take advantage of the forecasting technique of each while overcoming their drawbacks. Experimental results show that the hybrid intrusion forecasting method outperforms each of three forecasting methods.

Yeh and Tsai recently proposed an enhanced mobile commerce security mechanism. They modified the lightweight security mechanism due to Lam, Chung, Gu, and Sun to relieve the burden of mobile clients. However, this article shows that a malicious WAP gateway can successfully obtain the mobile client's PIN by sending a fake public key of a mobile commerce server and exploiting information leakage caused by addition operation. We also present a countermeasure against the proposed attack.

In this paper, we present a novel approach to recognize motion styles and identify people using the Multi Factor Tensor (MFT) model. We apply a musical information analysis method in segmenting the motion sequence relevant to the keyposes and the musical rhythm. We define a task model by considering the repeated motion segments, where the motion is decomposed into a person-invariant factor task and a person-dependent factor style. Given the motion data set, we formulate the MFT model, factorize it efficiently in different modes, and use it in recognizing the tasks and the identities of the persons performing the tasks. We capture the motion data of different people for a few cycles, segment it using the musical analysis approach, normalize the segments using a vectorization method, and realize our MFT model. In our experiments, Japanese traditional dance sequences performed by several people are used. Provided with an unknown motion segment which is to be probed and which was performed at a different time in the time space, we first normalize the motion segment and flatten our MFT model appropriately, then recognize the task and the identity of the person. We follow two approaches in conducting our experiments. In one experiment, we recognize the tasks and the styles by maximizing a function in the tensor subdomain, and in the next experiment, we use a function value in the tensorial subdomain with a threshold for recognition. Interestingly, unlike the first experiment, we are capable of recognizing tasks and human identities that were not known beforehand. We conducted various experiments to evaluate the potential of the recognition ability of our proposed approaches, and the results demonstrate the high accuracy of our model.

This letter presents the performance of ultra-wideband multi-band orthogonal frequency division multiplexing (UWB MB-OFDM) systems with an extra diversity. To fully obtain diversity gain in the current MB-OFDM system when a time-domain spreading (TDS) is adopted, two consecutive OFDM symbols are designed to be cyclic shifted against each other. Simulation results indicate that the MB-OFDM system using additional frequency diversity outperforms conventional MB-OFDM system.