The increase in the advanced location based services such as traffic coordination and management necessitates the need for advanced models tracking the positions of Moving Objects (MOs) like vehicles. Due to computer processing limitations, it is impossible for MOs to continuously update their locations. This results in the uncertainty nature of a MO's location between any two reported positions. Efficiently managing and quantifying the uncertainty regions of MOs are needed in order to support different types of queries and to improve query response time. This challenging problem of modeling uncertainty regions associated with MO was recently addressed by researchers and resulted in models that ranged from linear which require few properties of MOs as input to the models, to non-linear that are able to more accurately represent uncertainty regions by considering higher degree input. This paper summarizes and discusses approaches in modeling uncertainty regions associated with MOs. It further illustrates the need for appropriate approximations especially in the case of non-linear models as the uncertainty regions become rather irregularly shaped and difficult to manage. Finally, we demonstrate through several experimental sets the advantage of non-linear models over linear models when the uncertainty regions of MOs are approximated by two different approximations; the Minimum Bounding Box (MBB) and the Tilted Minimum Bounding Box (TMBB).

We developed a novel movement-imagery-based brain-computer interface (BCI) for untrained subjects without employing machine learning techniques. The development of BCI consisted of several steps. First, spline Laplacian analysis was performed. Next, time-frequency analysis was applied to determine the optimal frequency range and latencies of the electroencephalograms (EEGs). Finally, trials were classified as right or left based on β-band event-related synchronization using the cumulative distribution function of pretrigger EEG noise. To test the performance of the BCI, EEGs during the execution and imagination of right/left wrist-bending movements were measured from 63 locations over the entire scalp using eight healthy subjects. The highest classification accuracies were 84.4% and 77.8% for real movements and their imageries, respectively. The accuracy is significantly higher than that of previously reported machine-learning-based BCIs in the movement imagery task (paired t-test, p < 0.05). It has also been demonstrated that the highest accuracy was achieved even though subjects had never participated in movement imageries.

In this paper, we propose a quantitative metric of measuring the degree of the visual fatigue in a stereoscopy. To the best of our knowledge, this is the first simplified relative quantitative approach describing visual fatigue value of a stereoscopy. Our experimental result shows that the correlation index of more than 98% is obtained between our Simplified Relative Visual Fatigue (SRVF) model and Mean Opinion Score (MOS).

We describe an efficient algorithm that extracts a connected component of an isosurface, or a contour, from a 3D rectilinear volume data. The efficiency of the algorithm is achieved by three factors: (i) directly working with rectilinear grids, (ii) parallel utilization of a multi-core CPU for extracting active cells, the cells containing the contour, and (iii) parallel utilization of a many-core GPU for computing the geometries of a contour surface in each active cell using CUDA. Experimental results show that our hybrid parallel implementation achieved up to 20x speedup over existing methods on an ordinary PC. Our work coupled with the Contour Tree framework is useful for quickly segmenting, displaying, and analyzing a feature of interest in 3D rectilinear volume data without being distracted by other features.

The accurate and fast estimation of link price is the key component of network-based congestion control schemes. A fast estimation method A2DPM is presented. Multiple hashes on IP identifier of packet header are adopted to accelerate the side information transmission, so accurate estimation of maximum price on the flow forwarding path can be realized after the receipt of just a few probe packets, and the sender is capable of reacting to congestion more quickly, making it suitable to meet the demands of dynamic networks.

In this paper, the performance of a low duty factor (DF) hybrid direct sequence (DS) multiband (MB)-pulsed ultra wideband (UWB) system is evaluated over realistic propagation channels to highlight its capability of interference mitigation. The interference mitigation techniques incorporated in the DS-MB-UWB system is a novel design that includes the utilization of the frequency-agile multiple sub-band configuration and the coexistence-friendly low DF signaling. The system design consists of a Rake type receiver over multipath and multi-user channel in the presence of a coexisting narrowband interferer. The propagation channels are modeled based on actual measurement data. Firstly, by suppressing the power in the particular sub-band coexisting with the narrowband signal, performance degradation due to narrowband interference can be improved. It is observed that by fully suppressing the sub-band affected by the narrowband signal, a typical 1-digit performance improvement (e.g. BER improves from 10-3 to 10-4) can be achieved. Secondly, by employing lower DF signaling, self interference (SI) and multi-user interference (MUI) can be mitigated. It is found that a typical 3 dB improvement is achieved by reducing the DF from 0.5 to 0.04. Together, the sub-band power suppression and low DF signaling are shown to be effective mitigation techniques against environment with the presence of SI, MUI and narrowband interference.

In this review, we introduce a variety of surface sensitive techniques for the study of organic thin films, and applications to organic devices. These studies include surface plasmon emission light, organic thin film transistors, combination of quartz crystal microbalance and optical waveguide spectroscopy, evaluation of alignment of liquid crystal molecules at surfaces, and biosensor applications.

The cooperative relay network exploits the space diversity gain by allowing cooperation among users to improve transmission quality. It is an important issue to identify the cluster-head (or relay node) and its members who are to cooperate. The cluster-head consumes more battery power than an ordinary node since it has extra responsibilities, i.e., ensuring the cooperation of its members' transmissions; thereby the cluster-head has a lower throughput than the average. Since users are joining or departing the clusters from time to time, the network topology is changing and the network may not be stable. How to balance the fairness among users and the network stability is a very interesting topic. This paper proposes an adaptive weighted clustering algorithm (AWCA), in which the weight factors are introduced to adaptively control both the stability and fairness according to the number of arrival users. It is shown that when the number of arrival users is large, AWCA has the life time longer than FWCA and similar to SWCA and that when the number of arrival users is small, AWCA provides fairness higher than SWCA and close to FWCA.

Device-parameter estimation sensors inside a chip are gaining its importance as the post-fabrication tuning is becoming of a practical use. In estimation of variational parameters using on-chip sensors, it is often assumed that the outputs of variation sensors are not affected by random variations. However, random variations can deteriorate the accuracy of the estimation result. In this paper, we propose a device-parameter estimation method with on-chip variation sensors explicitly considering random variability. The proposed method derives the global variation parameters and the standard deviation of the random variability using the maximum likelihood estimation. We experimentally verified that the proposed method improves the accuracy of device-parameter estimation by 11.1 to 73.4% compared to the conventional method that neglects random variations.

In this paper, a geometric source separation system using nonnegative matrix factorization (NMF) is proposed. The adaptive beamformer is the best method for geometric source separation, but it suffers from a “target signal cancellation” problem in multi-path situations. We modified the HALS-NMF algorithm for decomposition into bases, and developed an interference suppression module in order to cancel the interference bases. A performance comparison between the proposed and subband GSC-RLS algorithm using a MATLAB® simulation was executed; the results show that the proposed system is robust in multi-path situations.

We have been developing low power cryogenic readout electronics for space borne large format far-infrared image sensors. As the circuit elements, a fully-depleted-silicon-on-insulator (FD-SOI) CMOS process was adopted because they keep good static performance even at 4.2 K where where various anomalous behaviors are seen for other types of CMOS transistors. We have designed and fabricated several test circuits with the FD-SOI CMOS process and confirmed that an operational amplifier successfully works with an open loop gain over 1000 and with a power consumption around 1.3 µW as designed, and the basic digital circuits worked well. These results prove that the FD-SOI CMOS process is a promising candidate of the ideal cryogenic readout electronics for far-infrared astronomical focal plane array sensors.

IEEE 802.11 Wireless LANs (WLANs) support multiple transmission rates. When some stations transmit at low transmission rates, the performance of the high transmission rate stations degrades heavily, and this phenomenon is known as the performance anomaly. As a solution to the performance anomaly, airtime fairness was proposed. However, the distributed coordination function (DCF) of IEEE 802.11 cannot provide airtime fairness to all competing stations because the protocol is designed to ensure fair attempt probability. In this paper, we propose a new medium access control, successful transmission time fair MAC (STF-MAC), which is fair in terms of successful transmission time and also provides the maximum aggregate throughput of a basic service set (BSS) in distributed manner. STF-MAC can be easily applied to solve the uplink/downlink fairness problem in infrastructure mode. Through simulations, we demonstrate that STF-MAC not only remedies the performance anomaly but also maximizes the aggregate throughput under the fairness constraint.

In this letter, we propose a power allocation scheme to optimize the ergodic secrecy rate of multiple-input single-output (MISO) fading wiretap channels with a probabilistic constraint, using the statistical channel state information (CSI) of the eavesdropper (CSI-E). The analytical expressions of the false secrecy probability are derived and used as constraints in the rate maximization problem. Moreover, we obtain a suboptimal solution by formulating the power allocation problem as a Rayleigh quotient problem.

TCP Friendly Rate Control (TFRC) has been widely used in the Internet multimedia streaming applications. However, performance of traditional TFRC algorithm degrades significantly when deployed over wireless networks. Although numerous TFRC variants have been proposed to improve the performance of TFRC over wireless networks, designing a TFRC algorithm with graceful performance both in throughput and fairness still remains a great challenge. In this paper, a novel TFRC algorithm, named TFRC-FIT, is proposed to improve the performance of TFRC over wireless environments. In the proposed approach, the behavior of multiple TFRC flows is simulated in single connection, while the number of simulated flows is adjusted by the network queuing delay. Through this mechanism, TFRC-FIT can fully utilize the capacity of wireless networks, while maintaining good fairness and TCP friendliness. Both theoretical analysis and extensive experiments over hardware network emulator, Planetlab test bed as well as commercial 3G wireless networks are carried out to characterize and validate the performance of our proposed approach.

This paper proposes an efficient scheme for concurrent error detection for hardware implementations of the block cipher AES. In the proposed scheme, the circuit component for the round function is divided into two stages, which are used alternately for encryption (or decryption) and error checking in a pipeline. The proposed scheme has a limited overhead with respect to size and speed for the following reasons. Firstly, the need for a double number of clock cycles is eliminated by virtue of the reduced critical path. Secondly, the scheme only requires minimal additional circuitry for error detection since the detection is performed by the remaining encryption (or decryption) components within the pipeline. AES hardware with the proposed scheme was designed and synthesized by using 90-nm CMOS standard cell library with various constraints. As a result, the proposed circuit achieved 1.66 Gbps @ 12.9 Kgates for the compact version and 4.22 Gbps @ 30.7 Kgates for the high-speed version. These performance characteristics are comparable to those of a basic AES circuit without error detection, where the overhead of the proposed scheme is estimated to be 14.5% at maximum. The proposed circuit was fabricated in the form of a chip, and its error detection performance was evaluated through experiments. The chip was tested with respect to fault injection by using clock glitch, and the proposed scheme successfully detected and reacted to all introduced errors.

In this paper, we propose a novel feeding structure for a coaxial-excited compact waveguide filter, which is composed of planar resonators called frequency-selective surfaces (FSSs). In our proposed feeding structure, new FSSs located at the input and output ports are directly excited by the coaxial line. By using the FSSs, the transition from the TEM mode to the TE10 mode is realized by the resonance of the FSSs. Therefore, the backshort length from the coaxial probe to the shorted waveguide end can be made much shorter than one-quarter of the guided wavelength. Additionally, the coaxial-excited FSS provides one transmission zero at each stopband. As a design example, a three-stage bandpass filter with 4% bandwidth at the X band is demonstrated. The designed filter has a very compact size of one cavity and has high skirt selectivity with six transmission zeros. The effectiveness of the design is confirmed by the comparison of frequency characteristics obtained by the simulation and measurement.

In this study, we demonstrate an acceleration of flexible generalized minimal residual algorithm (FGMRES) implemented with the method of moments and the fast multipole method (FMM), based on a combined tangential formulation. For the implementation of the FGMRES incorporated with the FMM concept, we propose a new definition of the truncation number for the FMM operator within the inner solver. The proposed truncation number provides an optimal variable preconditioner by controlling the accuracy and computational cost of the inner iteration. Moreover, to further accelerate the convergence, we introduce the concept of a multistage preconditioner. Numerical experiments reveal that our new version of FGMRES, based on the proposed truncation number for the inner solver and the multistage preconditioner, achieves outstanding acceleration of the convergence for large-scale and practical electromagnetic scattering and radiation problems with several levels of geometrical complexity.

Although unavailability and failure frequency are important reliability measures for designing telecommunications networks, having two different reliability measures causes difficulties when their evaluation results contradict each other. To overcome this difficulty, for determining a single reliability measure is proposed. Market share, which is an important management index, was used and the effect of each reliability measure on this index was studied. If we the effect of one of the reliability measures is small enough to be ignored, then the other one is chosen as the single reliability measure. The procedure of the proposed statistical analysis method and test results suggesting that failure frequency is promising as a single reliability measure are discussed.

To reduce the error of channel estimation caused by noise, a novel noise suppression method based on the degree of confidence is proposed in this paper. The false alarm and false dismissal probabilities, corresponding to noise being taken as part of channel impulse response (CIR) and part of the CIR being mis-detected as noise, respectively, are also investigated. A false alarm reduction method is therefore presented to reduce the false alarms in the estimated CIR while the mis-detection ratio still remains low. Simulation results show the effectiveness of the proposed method.

Histogram-based image features such as HoG, SIFT and histogram of visual words are generally represented as high-dimensional, non-negative vectors. We propose a supervised method of reducing the dimensionality of histogram-based features by using non-negative matrix factorization (NMF). We define a cost function for supervised NMF that consists of two terms. The first term is the generalized divergence term between an input matrix and a product of factorized matrices. The second term is the penalty term that reflects prior knowledge on a training set by assigning predefined constants to cannot-links and must-links in pairs of training data. A multiplicative update rule for minimizing the newly-defined cost function is also proposed. We tested our method on a task of scene classification using histograms of visual words. The experimental results revealed that each of the low-dimensional basis vectors obtained from the proposed method only appeared in a single specific category in most cases. This interesting characteristic not only makes it easy to interpret the meaning of each basis but also improves the power of classification.