Density ratio estimation has gathered a great deal of attention recently since it can be used for various data processing tasks. In this paper, we consider three methods of density ratio estimation: (A) the numerator and denominator densities are separately estimated and then the ratio of the estimated densities is computed, (B) a logistic regression classifier discriminating denominator samples from numerator samples is learned and then the ratio of the posterior probabilities is computed, and (C) the density ratio function is directly modeled and learned by minimizing the empirical Kullback-Leibler divergence. We first prove that when the numerator and denominator densities are known to be members of the exponential family, (A) is better than (B) and (B) is better than (C). Then we show that once the model assumption is violated, (C) is better than (A) and (B). Thus in practical situations where no exact model is available, (C) would be the most promising approach to density ratio estimation.

A multiple-peak negative differential resistance (NDR) circuit made of standard Si-based metal-oxide-semiconductor field-effect-transistor (MOS) and SiGe-based heterojunction bipolar transistor (HBT) is demonstrated. We can obtain a three-peak I-V curve by connecting three cascoded MOS-HBT-NDR circuits by suitably designing the MOS parameters. This novel three-peak NDR circuit possesses the adjustable current-voltage characteristics and high peak-to-valley current ratio (PVCR). We can adjust the PVCR values to be as high as 11.5, 6.5, and 10.3 for three peaks, respectively. Because the NDR circuit is a very strong nonlinear element, we discuss the extrinsic hysteresis phenomena in this multiple-peak NDR circuit. The effect of series resistance on hysteresis phenomena is also investigated. Our design and fabrication of the NDR circuit is based on the standard 0.35 µm SiGe BiCMOS process.

We propose requirement validation criteria and a method based on the interaction between actors in an information system. We focus on the cyclical transitions of one actor's situation against another and clarify observable stimuli and responses based on these transitions. Both actors' situations can be listed in a state transition table, which describes the observable stimuli or responses they send or receive. Examination of the interaction between both actors in the state transition tables enables us to detect missing or defective observable stimuli or responses. Typically, this method can be applied to the examination of the interaction between a resource managed by the information system and its user. As a case study, we analyzed 332 requirement defect reports of an actual system development project in Japan. We found that there were a certain amount of defects regarding missing or defective stimuli and responses, which can be detected using our proposed method if this method is used in the requirement definition phase. This means that we can reach a more complete requirement definition with our proposed method.

A continuous belief propagation (BP) decoding algorithm for a hybrid automatic repeat request (ARQ) system is proposed in this paper. The proposed continuous BP decoding algorithm utilizes the extrinsic information generated in the last iteration of the previous transmission for a continuous progression of the decoding through retransmissions. This allows the continuous BP decoding algorithm to accelerate the decoding convergence for codeword determination, especially when the number of retransmissions is large or a currently combined packet has punctured nodes. Simulation results verify the effectiveness of the proposed continuous BP decoding algorithm.

With simultaneous multi-user transmissions, spatial division multiple access (SDMA) provides substantial throughput gain over the single user transmission. However, its implementation in WLANs with contention-based IEEE 802.11 MAC remains challenging. Problems such as coordinating and synchronizing the multiple users need to be solved in a distributed way. In this paper, we propose a distributed MAC protocol for WLANs with SDMA support. A dual-mode CTS responding mechanism is designed to accomplish the channel estimation and user synchronization required for SDMA. We analytically study the throughput performance of the proposed MAC, and dynamic parameter adjustment is designed to enhance the protocol efficiency. In addition, the proposed MAC protocol does not rely on specific physical layer realizations, and can work on legacy IEEE 802.11 equipment with slight software updates. Simulation results show that the proposed MAC outperforms IEEE 802.11 significantly, and that the dynamic parameter adjustment can effectively track the load variation in the network.

Ultra wideband (UWB) on-body communication is attracting much attention in biomedical applications. In this paper, the performance of UWB on-body communication is investigated based on a statistically extracted on-body channel model, which provides detailed characteristics of the multi-path-affected channel with an emphasis on various body postures or body movement. The possible data rate, the possible communication distance, as well as the bit error rate (BER) performance are clarified via computer simulation. It is found that the conventional correlation receiver is incompetent in the multi-path-affected on-body channel, while the RAKE receiver outperforms the conventional correlation receiver at a cost of structure complexity. Different RAKE receiver structures are compared to show the improvement of the BER performance.

The aim of this work is to develop an efficient medical image segmentation technique by fitting a nonlinear shape model with pre-segmented images. In this technique, the kernel principle component analysis (KPCA) is used to capture the shape variations and to build the nonlinear shape model. The pre-segmentation is carried out by classifying the image pixels according to the high level texture features extracted using the over-complete wavelet packet decomposition. Additionally, the model fitting is completed using the particle swarm optimization technique (PSO) to adapt the model parameters. The proposed technique is fully automated, is talented to deal with complex shape variations, can efficiently optimize the model to fit the new cases, and is robust to noise and occlusion. In this paper, we demonstrate the proposed technique by implementing it to the liver segmentation from computed tomography (CT) scans and the obtained results are very hopeful.

Thinking process development diagram is a graphical expression from which readers can easily find not only the hierarchy of a given problem but the relationship between the problem and the solution. Although that has been developed as an idea creation support tool in the field of mechanical design, we referred to the restricted version as clamshell diagram to attempt to apply to other fields. In this paper we propose the framework for drawing the diagram of the SQL statement. The basic idea is to supply the hierarchical code fragments of a given SQL statement in the left side of the diagram and to put the meaning written in a natural language in the right. To verify the usefulness of the diagram expression, we actually drew several clamshell diagrams. For three SQL statements that are derived from the same specification, the resulting diagrams enable us to understand the difference visually.

This paper proposes an efficient multiuser relay scheme in OFDMA systems. In the proposed scheme, multiple terminals transmit their data packets simultaneously in the same subband and multiple relay stations retransmit their received signals in different subbands after subband conversion. A base station (BS) extracts individual packets from received signals in the different subbands. In advance of data transmission, the BS selects appropriate terminals so that the BS can extract individual data packets successfully. Numerical results show that the proposed relay scheme achieves higher system throughput than the conventional relay scheme when scheduling is applied to a larger number of terminals than the number of relay stations.

The problem of recovering a high-resolution frame from a sequence of low-resolution frames is considered. In general, video frames cannot be related through global parametric transformation due to the arbitrary individual pixel movement between frame pairs. To overcome this problem, we propose to employ region-matching technique for motion estimation with a modified model for frame alignment. To do that, the reference frame is segmented into arbitrary-shaped regions which are further matched with that of the other frames. Then, the frame alignment is accomplished by optimizing the cost function that consists of L1-norm of the difference between the interpolated low-resolution (LR) frames and the simulated LR frames. The experimental results demonstrate that using region matching in motion estimation step with the modified alignment model works better than other motion models such as affine, block matching, and optical flow motion models.

This paper proposes a joint source-channel coding technology to transmit periodic vital information such as an electrocardiogram. There is an urgent need for a ubiquitous medical treatment space in which personalized medical treatment is automatically provided based on measured vital information. To realize such treatment and reduce the constraints on the patient, wireless transmission of vital information from a sensor device to a data aggregator is essential. However, the vital information has to be correctly conveyed through wireless channels. In addition, sensor devices are constrained by their battery power. Thus, a coding technique that provides robustness to noise, channel efficiency and low power consumption at encoding is essential. This paper presents a coding method that uses correlation of periodic vital information in the time domain, and provides a decoding scheme that uses the correlation as side information in a maximum a posteriori probability algorithm. Our results show that the proposed method provides better performance in terms of mean squared error after decoding in comparison to differential pulse-code modulation, and the uncoded case.

Nonlinear distortions in power amplifiers (PAs) generate spectral regrowth at the output, which causes interference to adjacent channels and errors in digitally modulated signals. This paper presents a novel method to evaluate adjacent channel leakage power ratio (ACPR) and error vector magnitude (EVM) from the amplitude-to-amplitude (AM/AM) and amplitude-to-phase (AM/PM) characteristics. The transmitted signal is considered to be complex Gaussian distributed in orthogonal frequency-division multiplexing (OFDM) systems. We use the Mehler formula to derive closed-form expressions of the PAs output power spectral density (PSD), ACPR and EVM for memoryless PA and memory PA respectively. We inspect the derived relationships using an OFDM signal in the IEEE 802.11a WLAN standard. Simulation results show that the proposed method is appropriate to predict the ACPR and EVM values of the nonlinear PA output in OFDM systems, when the AM/AM and AM/PM characteristics are known.

OFDMA femtocells in the macrocellular network of which frequency reuse factor is 1 cause serious interference to macrocell users, while the femtocells improve the performance of indoor users. In this letter, a novel downlink resource allocation algorithm for OFDMA femtocell networks is proposed to reduce interference between the macrocells and the femtocells. This algorithm allocates femtocell subchannels to avoid interference to macrocell users in the femtocell coverage, and minimizes the total transmission power of the femtocell to reduce the negative effect on the performance of the macrocell. Simulation results are provided to present the performance of the proposed algorithm.

In this paper, we propose a novel target acoustic signal detection approach which is based on non-negative matrix factorization (NMF). Target basis vectors are trained from the target signal database through NMF, and input vectors are projected onto the subspace spanned by these target basis vectors. By analyzing the distribution of time-varying normalized projection error, the optimal threshold can be calculated to detect the target signal intervals during the entire input signal. Experimental results show that the proposed algorithm can detect the target signal successfully under various signal environments.

In this paper, we propose a novel Web service composition framework which dynamically accommodates various failure recovery requirements. In the proposed framework called Adaptive Failure-handling Framework (AdaFF), failure-handling submodules are prepared during the design of a composite service, and some of them are systematically selected and automatically combined with the composite Web service at service instantiation in accordance with the requirement of individual users. In contrast, existing frameworks cannot adapt the failure-handling behaviors to user's requirements. AdaFF rapidly delivers a composite service supporting the requirement-matched failure handling without manual development, and contributes to a flexible composite Web service design in that service architects never care about failure handling or variable requirements of users. For proof of concept, we implement a prototype system of the AdaFF, which automatically generates a composite service instance with Web Services Business Process Execution Language (WS-BPEL) according to the users' requirement specified in XML format and executes the generated instance on the ActiveBPEL engine.

In this letter, a statistical uncorrelated near class discriminant (SUNCD) approach is proposed for face recognition. The optimal discriminant vector obtained by this approach can differentiate one class and its near classes, i.e., its nearest neighbor classes, by constructing the specific between-class and within-class scatter matrices and using the Fisher criterion. In this manner, SUNCD acquires all discriminant vectors class by class. Furthermore, SUNCD makes every discriminant vector satisfy locally statistical uncorrelated constraints by using the corresponding class and part of its most neighboring classes. Experiments on the public AR face database demonstrate that the proposed approach outperforms several representative discriminant methods.

We present analytical expression for inductance of a superconducting stripline, a strip sandwiched by two superconducting ground planes. In our method, we utilize the analytical formula for a perfect-conducting stripline derived by Chang in 1976. To utilize Chang's formula, we first transform the structure of a superconducting stripline into that of a perfect-conducting stripline by reducing the thicknesses of the superconducting layers. The thickness reduction is "λ coth (t/λ)" for each (upper or lower) side, where λ and t are the field penetration depth and the layer thickness, respectively. Then, we apply Chang's formula to the transformed stripline model. The calculated results are in good agreement with the numerical and experimental results.

We consider a single-link multi-source network with FAST TCP sources. We adopt a continuous-time dynamic model for FAST TCP sources, and propose a static model to adequately describe the queuing delay dynamics at the link. The proposed model turns out to have a structure that reveals the time-varying network feedback delay, which allows us to analyze FAST TCP with due consideration of the time-varying network feedback delay. Based on the proposed model, we establish sufficient conditions for the boundedness of congestion window of each source and for the global asymptotic stability. The asymptotic stability condition shows that the stability property of each source is affected by all other sources sharing the link. Simulation results illustrate the validity of the sufficient condition for the global asymptotic stability.

A cooperative relaying system with transmission scheduling is investigated. Cooperative relaying is composed of multiple links because the source sends the data to more than one receiver, and the destination receives multiple data transmitted by more than one transmitter. Therefore, if the source can transmit the data when the channel gains of the links are high, it is not clear which channel gains should be high in order to achieve high spectral efficiency. In the present letter, the spectral efficiency of a cooperative relaying system is theoretically derived under the assumption that the source transmits the data only when the channel gains of links are above certain threshold values. Numerical results reveal that a high spectral efficiency can be achieved by assuring a high channel gain for the link with the highest average received power among links to the destination.

This paper evaluates impact of self-heating in wire interconnection on signal propagation delay in an upcoming 32 nm process technology, using practical physical parameters. This paper examines a 64-bit data transmission model as one of the most heating cases. Experimental results show that the maximum wire temperature increase due to the self-heating appears in the case where the ratio of interconnect delay becomes largest compared to the driver delay. However, even in the most significant case which induces the maximum temperature rise of 11.0, the corresponding increase in the wire resistance is 1.99% and the resulting delay increase is only 1.15%, as for the assumed 32 nm process. A part of the impact reduction of wire self-heating on timing comes from the size-effect of nano-scale wires.