This paper proposes new techniques to simulate a MIMO propagation channel using the ray-tracing method for the purpose of decreasing the computational complexity. These techniques simulate a MIMO propagation channel by substituting the propagation path between a particular combination of transmitter and receiver antennas for all combinations of transmitter and receiver antennas. The estimation accuracy calculated using the proposed techniques is evaluated based on comparison to the results calculated using imaging algorithms. The results show that the proposed techniques simulate a MIMO propagation channel with low computational complexity, and a high level of estimation accuracy is achieved using the proposed Vector-Rotation Approximation technique compared to that for the imaging algorithm.

In recent years, there have been many studies on integrating a number of heterogeneous wireless networks into one network by establishing standards like IEEE 802.16. For this purpose, the base station (BS) should allocate the appropriate bandwidth to each connection with a network scheduler. In wireless networks, the signal to noise ratio (SNR) changes with time due to many factors such as fading. Hence, we estimate the SNR based on the error rate reflecting wireless network condition. Using the estimated SNR, we propose a new time slot allocation algorithm so that the proposed algorithm guarantees the delay requirement and full link utilization.

In this paper, we use frequency-domain equalization (FDE) to create coherent optical single-carrier (CO-SC) transmission systems that are very tolerant of chromatic dispersion (CD) and polarization mode dispersion (PMD). The efficient transmission of a 25-Gb/s NRZ-QPSK signal by using the proposed FDE is demonstrated under severe CD and PMD conditions. We also discuss the principle of FDE and some techniques suitable for implementing CO-SC-FDE. The results show that a CO-SC-FDE system is very tolerant of CD and PMD and can achieve high transmission rates over single mode fiber without optical dispersion compensation.

Initial growth of GaP on Si substrates using metalorganic vapor phase epitaxy was studied. Si substrates were exposed to PH3 preflow for 15 s or 120 s at 830 after they were preheated at 925. Atomic force microscopy (AFM) revealed that the Si surface after preflow for 120 s was much rougher than that after preflow for 15 s. After 1.5 nm GaP deposition on the Si substrates at 830, GaP islands nucleated more uniformly on the Si substrate after preflow for 15 s than on the substrate after preflow for 120 s. After 3 nm GaP deposition, layer structures were observed on a fraction of Si surface after preflow for 15 s. Island-like structures remained on the Si surface after preflow for 120 s. After 6 nm GaP deposition, the continuity of GaP layers improved on both substrates. However, AFM shows pits that penetrated a Si substrate with preflow for 120 s. Transmission electron microscopy of a GaP layer on the Si substrate after preflow for 120 s revealed that V-shaped pits penetrated the Si substrate. The preflow for a long time roughened the Si surface, which facilitated the pit formation during GaP growth in addition to degrading the surface morphology of GaP at the initial growth stage. Even after 50 nm GaP deposition, pits with a density on the order of 107 cm-2 remained in the sample. A 50-nm-thick flat GaP surface without pits was achieved for the sample with PH3 preflow for 15 s. The PH3 short preflow is necessary to produce a flat GaP surface on a Si substrate.

An inversion method of bridge height over water by polarimetric synthetic aperture radar (SAR) is developed. A geometric ray description to illustrate scattering mechanism of a bridge over water surface is identified by polarimetric image analysis. Using the mapping and projecting algorithm, a polarimetric SAR image of a bridge model is first simulated and shows that scattering from a bridge over water can be identified by three strip lines corresponding to single-, double-, and triple-order scattering, respectively. A set of polarimetric parameters based on the de-orientation theory is applied to analysis of three types scattering, and the thinning-clustering algorithm and Hough transform are then employed to locate the image positions of these strip lines. These lines are used to invert the bridge height. Fully polarimetric image data of airborne Pi-SAR at X-band are applied to inversion of the height and width of the Naruto Bridge in Japan. Based on the same principle, this approach is also applicable to spaceborne ALOSPALSAR single-polarization data of the Eastern Ocean Bridge in China. The results show good feasibility to realize the bridge height inversion.

A filter integrated antenna configuration that suppresses the coupling signal from the transmitter (Tx) to receiver (Rx) base station antenna is investigated. We propose an aperture coupled patch antenna with multiple trapezoidal elements installed on the substrate of the Rx antenna between the radiation and feed layers in order to increase the bandwidth in the Rx band while maintaining low mutual coupling in the Tx band. The mutual coupling characteristics and the fractional bandwidth of the Rx antenna are presented as functions of the shape and width of the trapezoidal elements.

Toponyms and other named entities are main issues in unknown word processing problem. Our purpose is to salvage unknown toponyms, not only for avoiding noises but also providing them information of area candidates to where they may belong. Most of previous toponym resolution methods were targeting disambiguation among area candidates, which is caused by the multiple existence of a toponym. These approaches were mostly based on gazetteers and contexts. When it comes to the documents which may contain toponyms worldwide, like newspaper articles, toponym resolution is not just an ambiguity resolution, but an area candidate selection from all the areas on Earth. Thus we propose an automatic toponym resolution method which enables to identify its area candidates based only on their surface statistics, in place of dictionary-lookup approaches. Our method combines two modules, area candidate reduction and area candidate examination which uses block-unit data, to obtain high accuracy without reducing recall rate. Our empirical result showed 85.54% precision rate, 91.92% recall rate and .89 F-measure value on average. This method is a flexible and robust approach for toponym resolution targeting unrestricted number of areas.

Spectrum sensing is a key technology within Cognitive Radio (CR) systems. Cooperative spectrum sensing using a distributed model provides improved detection for the primary user, which opens the CR system to a new security threat. This threat is the decrease of the cooperative sensing performance due to the spectrum sensing data falsification which is generated from malicious users. Our proposed scheme, based on robust statistics, utilizes only available past sensing nodes' received power data for estimating the distribution parameters of the primary signal presence and absence hypotheses. These estimated parameters are used to perform the Dempster-Shafer theory of evidence data fusion which causes the elimination of malicious users. Furthermore, in order to enhance performance, a node's reliability weight is supplemented along with the data fusion scheme. Simulation results indicate that our proposed scheme can provide a powerful capability in eliminating malicious users as well as a high gain of data fusion under various cases of channel condition.

A variety of ZnO belt-like structures were synthesized by the heat treatment of ZnS substrates with Ga droplets in the air, and their morphological and structural properties were investigated. Three types of ZnO belts with flat surfaces of (20), (100) and (23) were obtained. As comparison, the ZnO crystal growth was examined by the thermal oxidation of ZnS only. These results highlight the promise of the heat treatment with Ga in the synthesis of oxide nanostructures.

Traditional TCP has a good congestion control strategy that adapts its sending rate in accordance with network congestion. In addition, a fast recovery algorithm can help TCP achieve better throughput by responding to temporary network congestion well. However, if multiple packet losses occur, the time to enter congestion avoidance phase would be delayed due to the long recovery time. Moreover, during the recovery phase, TCP freezes congestion window size until all lost packets are recovered, and this can make recovery time much longer resulting in performance degradation. To mitigate such recovery overhead, we propose Momentary recovery algorithm that recovers packet loss without an extra recovery phase. As other TCP and variants, our algorithm also halves the congestion window size when packet drop is detected, but it performs congestion avoidance phase immediately as if loss recovery is completed. For lost packets, TCP sender transmits them along with normal packets as long as congestion window permits rather than performs fast retransmission. In this manner, we can eliminate recovery overhead efficiently and reach steady state momentarily after network congestion. Finally, we provide a simulation based study on TCP recovery behaviors and confirm that our Momentary recovery algorithm always shows better performance compared with NewReno, SACK, and FACK.

When cognitive radio (CR) systems dynamically use the frequency band, a control signal is necessary to indicate which carrier frequencies are currently available in the network. In order to keep efficient spectrum utilization, this control signal also should be transmitted based on the channel conditions. If transmitters dynamically select carrier frequencies, receivers have to receive control signals without knowledge of their carrier frequencies. To enable such transmission and reception, this paper proposes a novel scheme called DCPT (Differential Code Parallel Transmission). With DCPT, receivers can receive low-rate information with no knowledge of the carrier frequencies. The transmitter transmits two signals whose carrier frequencies are spaced by a predefined value. The absolute values of the carrier frequencies can be varied. When the receiver acquires the DCPT signal, it multiplies the signal by a frequency-shifted version of the signal; this yields a DC component that represents the data signal which is then demodulated. The performance was evaluated by means of numerical analysis and computer simulation. We confirmed that DCPT operates successfully even under severe interference if its parameters are appropriately configured.

This paper presents a measurement method for determining effective conductivity of copper-clad dielectric laminate substrates in the millimeter-wave region. The conductivity is indirectly evaluated from measured resonant frequencies and unloaded Q values of a number of Whispering Gallery modes excited in a circular disk sample, which consists of a copper-clad dielectric substrate with a large diameter of 20-30 wavelengths. We can, therefore, obtain easily the frequency dependence of the effective conductivity of the sample under test in a wide range of frequency at once. Almost identical conductivity is predicted for two kinds of WG resonators (the copper-clad type and the sandwich type) with different field distribution; it is self-consistent and provides the important foundation for the method if not for the alternative method at this moment. We measure three kinds of copper foils in 55-65 GHz band, where the conductivity of electrodeposited copper foil is smaller than that of rolled copper foil and shiny-both-sides copper foil. The measured conductivity for the electrodeposited copper foil decreases with an increase in the frequency. The transmission losses measured for microstrip lines which are fabricated from these substrates are accurately predicted with the conductivity evaluated by this method.

This paper addresses problems appearing in restoration algorithms based on utilizing both Tikhonov and bilateral total variation (BTV) regularization. The former regularization assumes that prior information has Gaussian distribution which indeed fails at edges, while the later regularization highly depends on the selected bilateral filter's parameters. To overcome these problems, we propose a locally adaptive regularization. In the proposed algorithm, we use general directional regularization functions with adaptive weights. The adaptive weights are estimated from local patches based on the property of the partially restored image. Unlike Tikhonov regularization, it can avoid smoothness across edges by using adaptive weights. In addition, unlike BTV regularization, the proposed regularization function doesn't depend on parameters' selection. The convexity conditions as well as the convergence conditions are derived for the proposed algorithm.

Active Shape Model (ASM) is a powerful statistical tool for image interpretation, especially in face alignment. In the standard ASM, local appearances are described by intensity profiles, and the model parameter estimation is based on the assumption that the profiles follow a Gaussian distribution. It suffers from variations of poses, illumination, expressions and obstacles. In this paper, an improved ASM framework, GentleBoost based SIFT-ASM is proposed. Local appearances of landmarks are originally represented by SIFT (Scale-Invariant Feature Transform) descriptors, which are gradient orientation histograms based representations of image neighborhood. They can provide more robust and accurate guidance for search than grey-level profiles. Moreover, GentleBoost classifiers are applied to model and search the SIFT features instead of the unnecessary assumption of Gaussian distribution. Experimental results show that SIFT-ASM significantly outperforms the original ASM in aligning and localizing facial features.

This paper presents an extended Relief-F algorithm for nominal attribute estimation, for application to small-document classification. Relief algorithms are general and successful instance-based feature-filtering algorithms for data classification and regression. Many improved Relief algorithms have been introduced as solutions to problems of redundancy and irrelevant noisy features and to the limitations of the algorithms for multiclass datasets. However, these algorithms have only rarely been applied to text classification, because the numerous features in multiclass datasets lead to great time complexity. Therefore, in considering their application to text feature filtering and classification, we presented an extended Relief-F algorithm for numerical attribute estimation (E-Relief-F) in 2007. However, we found limitations and some problems with it. Therefore, in this paper, we introduce additional problems with Relief algorithms for text feature filtering, including the negative influence of computation similarities and weights caused by a small number of features in an instance, the absence of nearest hits and misses for some instances, and great time complexity. We then suggest a new extended Relief-F algorithm for nominal attribute estimation (E-Relief-Fd) to solve these problems, and we apply it to small text-document classification. We used the algorithm in experiments to estimate feature quality for various datasets, its application to classification, and its performance in comparison with existing Relief algorithms. The experimental results show that the new E-Relief-Fd algorithm offers better performance than previous Relief algorithms, including E-Relief-F.

In this paper, a highly parallel deblocking filter architecture for H.264/AVC is proposed to process one macroblock in 48 clock cycles and give real-time support to QFHD@60 fps sequences at less than 100 MHz. 4 edge filters organized in 2 groups for simultaneously processing vertical and horizontal edges are applied in this architecture to enhance its throughput. While parallelism increases, pipeline hazards arise owing to the latency of edge filters and data dependency of deblocking algorithm. To solve this problem, a zig-zag processing schedule is proposed to eliminate the pipeline bubbles. Data path of the architecture is then derived according to the processing schedule and optimized through data flow merging, so as to minimize the cost of logic and internal buffer. Meanwhile, the architecture's data input rate is designed to be identical to its throughput, while the transmission order of input data can also match the zig-zag processing schedule. Therefore no intercommunication buffer is required between the deblocking filter and its previous component for speed matching or data reordering. As a result, only one 2464 two-port SRAM as internal buffer is required in this design. When synthesized with SMIC 130 nm process, the architecture costs a gate count of 30.2 k, which is competitive considering its high performance.

We investigated the relationship between ambient illumination and psychological effect by applying a modified color harmony model. We verified the proposed model by analyzing correlation between psychological value and modified color harmony score. Experimental results showed the possibility to obtain the best color for illumination using this model.

Multitude parameters in the design process of a reconfigurable instruction-set processor (RISP) may lead to a large design space and remarkable complexity. Quantitative design approach uses the data collected from applications to satisfy design constraints and optimize the design goals while considering the applications' characteristics; however it highly depends on designer observations and analyses. Exploring design space can be considered as an effective technique to find a proper balance among various design parameters. Indeed, this approach would be computationally expensive when the performance evaluation of the design points is accomplished based on the synthesis-and-simulation technique. A combined analytical and simulation-based model (CAnSO**) is proposed and validated for performance evaluation of a typical RISP. The proposed model consists of an analytical core that incorporates statistics collected from cycle-accurate simulation to make a reasonable evaluation and provide a valuable insight. CAnSO has clear speed advantages and therefore it can be used for easing a cumbersome design space exploration of a reconfigurable RISP processor and quick performance evaluation of slightly modified architectures.

As device feature size decreases, interconnection delay becomes the dominating factor of circuit total delay. Distributed-register architectures can reduce the influence of interconnection delay. They may, however, increase circuit area because they require many local registers. Moreover original distributed-register architectures do not consider control signal delay, which may be the bottleneck in a circuit. In this paper, we propose a high-level synthesis method targeting generalized distributed-register architecture in which we introduce shared/local registers and global/local controllers. Our method is based on iterative improvement of scheduling/binding and floorplanning. First, we prepare shared-register groups with global controllers, each of which corresponds to a single functional unit. As iterations proceed, we use local registers and local controllers for functional units on a critical path. Shared-register groups physically located close to each other are merged into a single group. Accordingly, global controllers are merged. Finally, our method obtains a generalized distributed-register architecture where its scheduling/binding as well as floorplanning are simultaneously optimized. Experimental results show that the area is decreased by 4.7% while maintaining the performance of the circuit equal with that using original distributed-register architectures.

Many signal processing systems, particularly in the multimedia and telecommunication domains, are synthesized to execute data-intensive applications: their cost related aspects -- namely power consumption and chip area -- are heavily influenced, if not dominated, by the data access and storage aspects. This paper presents an energy-aware memory allocation methodology. Starting from the high-level behavioral specification of a given application, this framework performs the assignment of the multidimensional signals to the memory layers -- the on-chip scratch-pad memory and the off-chip main memory -- the goal being the reduction of the dynamic energy consumption in the memory subsystem. Based on the assignment results, the framework subsequently performs the mapping of signals into both memory layers such that the overall amount of data storage be reduced. This software system yields a complete allocation solution: the exact storage amount on each memory layer, the mapping functions that determine the exact locations for any array element (scalar signal) in the specification, and an estimation of the dynamic energy consumption in the memory subsystem.