This paper proposes a novel crest factor reduction (CFR) algorithm applicable to currently deployed W-CDMA base stations. The peak-to-average ratio (PAR) reduction of the multiple carrier mixed signal, namely CFR, has been an issue in order to convey the benefit of using low-cost power amplifiers. The simple final clipping method (SFCM) as a conventional method has been widely utilized due to its simplicity and effectiveness. However, the SFCM degrades the adjacent channel leakage ratio (ACLR) characteristic as well as the signal quality indicated by either the error vector magnitude (EVM) or the peak code domain error (PCDE). Conventionally, in order to alleviate this undesired deterioration, extra channel filtering and signal quality enhancement followed by CFR might be processed in an open-loop style. Alternatively, to perform CFR by maintaining the PAR as low as possible subject to satisfying the prescribed ACLR and EVM/PCDE performance, this paper introduces the prediction filter dependent peak reduction (PFDPR) process collaboratively working with dynamic waterfilling-based code domain compensation (DWCDC). To verify the superiority of the proposed CFR algorithm, tentative simulations are conducted while maintaining the rules of legitimate W-CDMA base station test specifications.

In the IEEE 802.11 MAC protocol, access points (APs) are given the same priority as wireless terminals in terms of acquiring the wireless link, even though they aggregate several downlink flows. This feature leads to a serious throughput degradation of downlink flows, compared with uplink flows. In this paper, we propose a dynamic contention window control scheme for the IEEE 802.11e EDCA-based wireless LANs, in order to achieve fairness between uplink and downlink TCP flows while guaranteeing QoS requirements for real-time traffic. The proposed scheme first determines the minimum contention window size in the best-effort access category at APs, based on the number of TCP flows. It then determines the minimum and maximum contention window sizes in higher priority access categories, such as voice and video, so as to guarantee QoS requirements for these real-time traffic. Note that the proposed scheme does not require any modification to the MAC protocol at wireless terminals. Through simulation experiments, we show the effectiveness of the proposed scheme.

This paper proposes an improved method that uses a K-means method to effectively reduce the ringing artifacts in a color moving picture. To apply this improved K-method, we set the number of groups for the process to two (K=2) in the three dimensional R, G, B color space. We then improved the R, G, B color value of all of the pixels by moving the current R, G, B color value of each pixel to calculated center values, which reduced the ringing artifacts. The results were verified by calculating the overshoot and the slope of the light luminance around the edges of test images that had been processed by the new algorithm. We then compared the calculated results with the overshoot and slope of the light luminance of the unprocessed image.

Gaussian rough surfaces can be characterized by two roughness parameters, the root-mean-square height and correlation length. For accurate estimation of these parameters from measured surface height-profile, data samples with sufficiently long record length are necessary. In this letter, an expression of correlation length in terms of a surface slope function is introduced in order to estimate correlation length and analytical expression of the data record length required for accurate estimation is derived. The result shows that the method using the slope function can reduce the data record length approximately 60% as compared to the commonly employed method using the correlation function. In order to check the result, a Monte Carlo simulation is also carried out and the validity of the result is confirmed.

For fast egomotion of a camera, computing feature correspondence and motion parameters by global search becomes highly time-consuming. Therefore, the complexity of the estimation needs to be reduced for real-time applications. In this paper, we propose a compound omnidirectional vision sensor and an algorithm for estimating its fast egomotion. The proposed sensor has both multi-baselines and a large field of view (FOV). Our method uses the multi-baseline stereo vision capability to classify feature points as near or far features. After the classification, we can estimate the camera rotation and translation separately by using random sample consensus (RANSAC) to reduce the computational complexity. The large FOV also improves the robustness since the translation and rotation are clearly distinguished. To date, there has been no work on combining multi-baseline stereo with large FOV characteristics for estimation, even though these characteristics are individually are important in improving egomotion estimation. Experiments showed that the proposed method is robust and produces reasonable accuracy in real time for fast motion of the sensor.

The architecture of ZigBee networks focuses on developing low-cost, low-speed ubiquitous communication between devices. The ZigBee technique is based on IEEE 802.15.4, which specifies the physical layer and medium access control (MAC) for a low rate wireless personal area network (LR-WPAN). Currently, numerous wireless sensor networks have adapted the ZigBee open standard to develop various services to promote improved communication quality in our daily lives. The problem of system and network reliability in providing stable services has become more important because these services will be stopped if the system and network reliability is unstable. The ZigBee standard has three kinds of networks; star, tree and mesh. The paper models the ZigBee protocol stack from the physical layer to the application layer and analyzes these layer reliability and mean time to failure (MTTF). Channel resource usage, device role, network topology and application objects are used to evaluate reliability in the physical, medium access control, network, and application layers, respectively. In the star or tree networks, a series system and the reliability block diagram (RBD) technique can be used to solve their reliability problem. However, a division technology is applied here to overcome the problem because the network complexity is higher than that of the others. A mesh network using division technology is classified into several non-reducible series systems and edge parallel systems. Hence, the reliability of mesh networks is easily solved using series-parallel systems through our proposed scheme. The numerical results demonstrate that the reliability will increase for mesh networks when the number of edges in parallel systems increases while the reliability quickly drops when the number of edges and the number of nodes increase for all three networks. More use of resources is another factor impact on reliability decreasing. However, lower network reliability will occur due to network complexity, more resource usage and complex object relationship.

This paper proposes a novel robust audio watermarking algorithm to embed data and extract it in a bit-exact manner based on changing the magnitudes of the FFT spectrum. The key point is selecting a frequency band for embedding based on the comparison between the original and the MP3 compressed/decompressed signal and on a suitable scaling factor. The experimental results show that the method has a very high capacity (about 5 kbps), without significant perceptual distortion (ODG about -0.25) and provides robustness against common audio signal processing such as added noise, filtering and MPEG compression (MP3). Furthermore, the proposed method has a larger capacity (number of embedded bits to number of host bits rate) than recent image data hiding methods.

Visual adaptation is a universal phenomenon associated with human visual system. This adaptation affects not only the perception of low-level visual systems processing color, motion, and orientation, but also the perception of high-level visual systems processing complex visual patterns, such as facial identity and expression. Although it remains unclear for the mutual interaction mechanism between systems at different levels, this issue is the key to understand the hierarchical neural coding and computation mechanism. Thus, we examined whether the low-level adaptation influences on the high-level aftereffect by means of cross-level adaptation paradigm (i.e. color, figure adaptation versus facial identity adaptation). We measured the identity aftereffects within the real face test images on real face, color chip and figure adapting conditions. The cross-level mutual influence was evaluated by the aftereffect size among different adapting conditions. The results suggest that the adaptation to color and figure contributes to the high-level facial identity aftereffect. Besides, the real face adaptation obtained the significantly stronger aftereffect than the color chip or the figure adaptation. Our results reveal the possibility of cross-level adaptation propagation and implicitly indicate a high-level holistic facial neural representation. Based on these results, we discussed the theoretical implication of cross-level adaptation propagation for understanding the hierarchical sensory neural systems.

With DCT coding, block artifact and mosquito noise degradations appear in decoded pictures. The control of post filtering is important to reduce degradations without causing side effects. Decoding information is useful, if the filter is inside or close to the encoder; however, it is difficult to control with independent post filtering, such as in a display. In this case, control requires the estimation of the artifact from only the decoded picture. In this work, we describe an estimation method that determines the mosquito noise block and level. In this method, the ratio of spatial activity is taken between the mosquito block and the neighboring flat block. We test the proposed method using the reconstructed pictures which are coded with different quantization scales. We recognize that the results are mostly reasonable with the different quantizations.

To realize dynamic spectrum access (DSA), spectrum sensing is performed to detect the presence or absence of primary users (PUs). This paper proposes a sensing architecture. This architecture enables use cases such as DSA with PU detection using a single spectrum sensor and DSA with distributed sensing, such as cooperative sensing, collaborative sensing, and selective sensing. In this paper we focus on distributed sensing. These sensing schemes employ distributed spectrum sensors (DSSs) where each sensor uses energy detection (ED) in Rayleigh fading environment. To theoretically analyze the performance of the three sensing schemes, a closed-form expression for the probability of detection by ED with selective combining (SC) in Rayleigh fading environment is derived. Applying this expression to the PU detection problem, we obtain analytical models of the three sensing schemes. Analysis shows that at 5-dB signal-to-noise ratio (SNR) and with a false alarm rate of 0.004, the probability of detection is increased from 0.02 to 0.3 and 0.4, respectively, by cooperative sensing and collaborative sensing schemes using using three DSSs. Results also show that the selected sensing scheme matches the performance of the collaborative sensing scheme. Moreover, it provides a low false alarm rate.

Interface state density was estimated from diode factor n of SiC MIS Schottky diode. The interface state density was the order of 1012 cm-2eV-1, and was same order to the value for the sample carefully prepared by oxidation and post oxidation annealing. The interface state density determined from n was consistent to the value calculated from the capacitance voltage curve of SiO2/nitride/SiC MIS diode by Terman method. High temperature nitridation was effective to reduce the interface state density.

This letter proposes a nonlinear DCT discriminant feature extraction approach for face recognition. The proposed approach first selects appropriate DCT frequency bands according to their levels of nonlinear discrimination. Then, this approach extracts nonlinear discriminant features from the selected DCT bands by presenting a new kernel discriminant method, i.e. the improved kernel discriminative common vector (KDCV) method. Experiments on the public FERET database show that this new approach is more effective than several related methods.

This paper proposes a novel delay-locked loop (DLL) with fast-locking property. The improved fast-locking successive approximation register-controlled (IFSAR) scheme can decrease the locking time to n+4 periods and be harmonic-free, where n is the bits' number of the control code for a delay line. According to the simulation result in 180 nm CMOS technology, the DLL can cover the operating range from 70 MHz to 500 MHz and dissipate 10.44 mW at 500 MHz.

Trapdoor commitment schemes are widely used for adding valuable properties to ordinary signatures or enhancing the security of weakly secure signatures. In this letter, we propose a trapdoor commitment scheme based on RSA function, and prove its security under the hardness of the integer factoring. Our scheme is very efficient in computing a commitment. Especially, it requires only three multiplications for evaluating a commitment when e=3 is used as a public exponent of RSA function. Moreover, our scheme has two useful properties, key exposure freeness and strong trapdoor opening, which are useful for designing secure chameleon signature schemes and converting a weakly secure signature to a strongly secure signature, respectively.

Traditional algorithms for dynamic OFDMA resource allocation have relatively deterministic system capacity and user fairness. Thus, in this letter, an efficient scheme is proposed to flexibly adjust quality-of-service for users, which is achieved by appropriately setting minimum data-rate of each user.

Scalable video coding (SVC) was standardized as an extension of H.264/AVC by the JVT (Joint Video Team) in Nov. 2007. The biggest feature of SVC is multi-layered coding where two or more video sequences are compressed into a single bit-stream. This letter proposes a fast block mode decision algorithm in spatial enhancement layer of SVC. The proposed algorithm achieves early decision by limiting the number of candidate modes for block with certain characteristic called same motion vector block (SMVB). Our proposed method reduces the complexity, in terms of encoding time by up to 66.17%. Nevertheless, it shows negligible PSNR degradation by only up to 0.16 dB and increases the bit-rate by only up to 0.64%, respectively.

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.

As the integrated circuit technology has undergone continuous downscaling to improve the LSI performance and reduce chip size, design for manufacturability (DFM) and design for yield (DFY) have become very important. As one of the DFM/DFY methods, a redundant via insertion technique uses as many vias as possible to connect the metal wires between different layers. In this paper, we focus on redundant vias and propose an effective redundant via insertion method for practical use to address the manufacturing variability and reliability concerns. First, the results of statistical analysis for via resistance and via capacitance in some real physical layouts are shown, and the impact on circuit delay of the resistance variation of vias caused by manufacturing variability is clarified. Then, the valuation functions of delay variation, electro-migration (EM), and stress-migration (SM) are defined and a practical method concerning redundant via insertion is proposed. Experimental results show that LSI with redundant vias inserted by our method robust against manufacturing variability and reliability problems.

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.

Since multiview video coding (MVC) based on H.264/AVC uses a prediction scheme exploiting inter-view correlation among multiview video, MVC encoder compresses multiple views more efficiently than simulcast H.264/AVC encoder. However, in case that the number of views to be encoded increases in MVC, the total encoding time will be greatly increased. To reduce computational complexity in MVC, a fast mode decision using both Macroblock-based region segmentation information and global disparity vector among views is proposed to reduce the encoding time. The proposed method achieves on the average 1.5 2.9 reduction of the total encoding time with the PSNR (Peak Signal-to-Noise Ratio) degradation of about 0.05 dB.