We describe an evaluation system consisting of an evaluation and interpretation model to totally assess and interpret an end-user's computing capability. It includes four evaluation factors and eighteen items, the complex indicators, an evaluation process, and method. We verified the model construct was verified by factor analysis and reliability analysis through a pilot test. We confirmed the application of the developed system by applying the model to evaluating end-users in a computing business environment and presenting the results. This system contributes to developing a practical system for evaluating an end-user's computing capability and hence for improving computing capability of end-users.

In 3D computer graphics, mesh parameterization is a key technique for digital geometry processings such as morphing, shape blending, texture mapping, re-meshing and so on. Most of the previous approaches made use of an identical primitive domain to parameterize a mesh model. In recent works of mesh parameterization, more flexible and attractive methods that can create direct mappings between two meshes have been reported. These mappings are called "cross-parameterization" and typically preserve semantic feature correspondences between target meshes. This paper proposes a novel approach for parameterizing a mesh into another one directly. The main idea of our method is to combine a competitive learning and a least-square mesh techniques. It is enough to give some semantic feature correspondences between target meshes, even if they are in different shapes or in different poses.

In this paper, a new methodology to estimate the number of competing stations in an IEEE 802.11 network, is proposed. Due to the nonlinear nature of the measurement model, an iterative nonlinear filtering algorithm, called the Scaled Unscented Filter (SUF), is employed. The SUF can provide a superior alternative to nonlinear filtering than the conventional Extended Kalman Filter (EKF), since it avoids errors associated with linearization. This approach demonstrates both high accuracy in addition to prompt reactivity to changes in the network occupancy status. In particular, the proposed algorithm shows superior performance in non saturated conditions when compared to the EKF. Numerical results demonstrate that the proposed algorithm provides a more viable method for estimation of the number of competing stations in an IEEE 802.11 network, than estimators based on the EKF.

Design by Contract (DBC), originated in the Eiffel programming language, is generally accepted as a practical method for building reliable software. Currently, however, few languages have built-in support for it. In recent years, several methods have been proposed to support DBC in Java. We compare eleven DBC tools for Java by analyzing their impact on the developer's programming activities, which are characterized by seven quality attributes identified in this paper. It is shown that each of the existing tools fails to achieve some of the quality attributes. This motivates us to develop ezContract, an open source DBC tool for Java that achieves all of the seven quality attributes. ezContract achieves streamlined integration with the working environment. Notably, standard Java language is used and advanced IDE features that work for standard Java programs can also work for the contract-enabled programs. Such features include incremental compilation, automatic refactoring, and code assist.

An essential condition for diversity reception is that the fading distributions between individual received signals of an antenna array are uncorrelated. In this paper, a new technique to improve the performance of transmission with the correlated Rayleigh-fading signals is proposed. In conventional array systems, individual receivers start sampling the received signals at the same time with the same sampling rate. On the other hand, in the proposed scheme, the received signals are again sampled with the same rate, however the sampling points are shifted in each receiver. Numerical results through computer simulation show that with correlated received signals, by applying the proposed technique the correlation can be reduced to a sufficient level for diversity reception.

A technique that acquires documents in the same category with a given short text is introduced. Regarding the given text as a training document, the system marks up the most similar document, or sufficiently similar documents, from among the document domain (or entire Web). The system then adds the marked documents to the training set to learn the set, and this process is repeated until no more documents are marked. Setting a monotone increasing property to the similarity as it learns enables the system to 1) detect the correct timing so that no more documents remain to be marked and to 2) decide the threshold value that the classifier uses. In addition, under the condition that the normalization process is limited to what term weights are divided by a p-norm of the weights, the linear classifier in which training documents are indexed in a binary manner is the only instance that satisfies the monotone increasing property. The feasibility of the proposed technique was confirmed through an examination of binary similarity and using English and German documents randomly selected from the Web.

Amidst conflicting views about whether soft cooperative energy detection scheme (SCEDS) outperforms hard cooperative energy detection scheme (HCEDS) greatly in cognitive radio, we establish the bridge that mathematically connects SCEDS and HCEDS by closed approximations. Through this bridge, it is demonstrate that, if the number of detectors of HCEDS is 1.6 times as that of SCEDS, they have nearly the same performance which is confirmed by numerical simulations, enabling a quantitative evaluation of the relation between them and a resolution of the conflicting views.

A new structure of a waveguide-type left-handed transmission line is proposed. It is composed of two rectangular waveguides with many stubs. One waveguide is put on another waveguide symmetrically. When one mode with odd electric field distribution is excited, the stubs work as open stubs and the mode propagates with very small loss. Guided regions of the left-handed mode and a right-handed mode are discussed using an approximate equivalent circuit. Tuning the structure parameters, the band gap between the two regions can be removed, and the wave propagates continuously from the left-handed frequency regions to the right-handed frequency region. The transmission line is applied to a leaky waveguide. It is confirmed experimentally that the beam angle of the radiation wave changes from the backward to the forward directions.

Since an FFT-based speech encryption system retains a considerable residual intelligibility, such as talk spurts and the original intonation in the encrypted speech, this makes it easy for eavesdroppers to deduce the information contents from the encrypted speech. In this letter, we propose a new technique based on the combination of an orthogonal frequency division multiplexing (OFDM) scheme and an appropriate QAM mapping method to remove the residual intelligibility from the encrypted speech by permuting several frequency components. In addition, the proposed OFDM-based speech encryption system needs only two FFT operations instead of the four required by the FFT-based speech encryption system. Simulation results are presented to show the effectiveness of this proposed technique.

The complexity of Finite Impulse Response (FIR) filters is mainly dominated by the number of adders (subtractors) used to implement the coefficient multipliers. It is well known that Common Subexpression Elimination (CSE) method based on Canonic Signed Digit (CSD) representation considerably reduces the number of adders in coefficient multipliers. Recently, a binary-based CSE (BSE) technique was proposed, which produced better reduction of adders compared to the CSD-based CSE. In this paper, we propose a new 4-bit binary representation-based CSE (BCSE-4) method which employs 4-bit Common Subexpressions (CSs) for implementing higher order low-power FIR filters. The proposed BCSE-4 offers better reduction of adders by eliminating the redundant 4-bit CSs that exist in the binary representation of filter coefficients. The reduction of adders is achieved with a small increase in critical path length of filter coefficient multipliers. Design examples show that our BCSE-4 gives an average power consumption reduction of 5.2% and 6.1% over the best known CSE method (BSE, NR-SCSE) respectively, when synthesized with TSMC-0.18 µm technology. We show that our BCSE-4 offers an overall adder reduction of 6.5% compared to BSE without any increase in critical path length of filter coefficient multipliers.

This paper represents a novel second harmonic power combining oscillator using mutually synchronized Gunn diodes embedded on slot line resonators. A both-sided MIC technology is adopted in the oscillator. The oscillator consists of Gunn diodes, slot line resonators and microstrip lines. By embedding Gunn diodes on the slot line resonators, the harmonic RF signal can be generated very easily. The microstrip lines are used for the power combining output circuit. This oscillator has advantages such as easy circuit design, simple circuit configuration and miniaturization of the circuit size. The second harmonic oscillator is designed and fabricated in K-Band. The output power is +5.75 dBm at the design frequency of 19.0 GHz (2f0) with the phase noise of -111.7 dBc/Hz at the offset frequency of 1 MHz. Excellent suppression of the undesired fundamental frequency signal (f0) of -39 dBc is achieved.

RFID event filtering is an important issue of RFID data management. Tag read events from readers have some problems like unreliability, redundancy, and disordering of tag readings. Duplicated events lead to performance degradation of RFID systems with a flood of similar tag information. Therefore, this paper proposes a fuzzy logic-based quantized event filter. In order to reduce duplicated tag readings and solve disordering of tag readings, the filter applies a fuzzy logic system to control a filtering threshold by the change in circumstances of readers. Continuous tag readings are converted into discrete values for event generation by the filtering threshold. And, the filter generates as many events as the discrete values at a point of event generation time. Experimental results comparing the proposed filter with existing RFID event filters, such as the primitive event filter and the smoothing event filter, verify effectiveness and efficiency of the fuzzy logic-based quantized event filter.

This paper suggests word voiceprint models to verify the recognition results obtained from a speech recognition system. Word voiceprint models have word-dependent information based on the distributions of phone-level log-likelihood ratio and duration. Thus, we can obtain a more reliable confidence score for a recognized word by using its word voiceprint models that represent the more proper characteristics of utterance verification for the word. Additionally, when obtaining a log-likelihood ratio-based word voiceprint score, this paper proposes a new log-scale normalization function using the distribution of the phone-level log-likelihood ratio, instead of the sigmoid function widely used in obtaining a phone-level log-likelihood ratio. This function plays a role of emphasizing a mis-recognized phone in a word. This individual information of a word is used to help achieve a more discriminative score against out-of-vocabulary words. The proposed method requires additional memory, but it shows that the relative reduction in equal error rate is 16.9% compared to the baseline system using simple phone log-likelihood ratios.

This paper discusses an on-line Tasks Assignment and Routing Problem (TARP) for Autonomous Transportation Systems (ATSs) in manufacturing systems. The TARP is a constrained version of the Pickup and Delivery Problem with Time Windows (PDPTW). In our former study, a cooperative algorithm, called the triple loop method, with autonomous distributed agents has been proposed. The Improving initial Task Assignment and Avoiding Deadlock method (ITAAD) is a faster algorithm than the triple loop method. In this paper, we propose a new vehicle routing method for the ITAAD. Results of computational experiments show effectiveness of the proposed routing method.

This paper presents a wireless burst modulation/ demodulation method for narrowband ubiquitous communication systems. This method especially suits those systems, whose traffic is especially dominated by short frame bursts. The proposed modulation method provides a preamble-less frame structure with training symbols, which improves both transmission efficiency and burst synchronization performance. Moreover, the proposed demodulation method achieves superior burst synchronization performance in low carrier-to-noise power ratio (CNR) environments by applying a synchronization method that includes symbol timing recovery, slot synchronization, carrier frequency correction and channel tracking. In addition, this paper presents the result of experiments on hardware prototypes of the proposed modulator and demodulator. The basic operation and practical performance of the proposed method is confirmed through testbed studies.

Broadcasting is an elementary operation in wireless multi-hop networks. Flooding is a simple broadcast protocol but it frequently causes serious redundancy, contention and collisions. Probability based methods are promising because they can reduce broadcast messages without additional hardware and control packets. In this paper, the counter-based scheme which is one of the probability based methods is focused on as a broadcast protocol, and the RAD (Random Assessment Delay) Extension is proposed to improve the original counter-based scheme. The RAD Extension can be implemented without additional hardware, so that the strength of the counter-based scheme can be preserved. In addition, we propose the additional algorithm called Hop Count Aware RAD Extension to establish shorter path from the source node. Simulation results show that both of the RAD Extension and the Hop Count Aware RAD Extension reduce the number of retransmitting nodes by about 10% compared with the original scheme. Furthermore, the Hop Count Aware RAD Extension can establish almost the same path length as the counter-based scheme.

UWB (Ultra Wide-Band) pulse radar is a promising candidate for surveillance systems designed to prevent crimes and terror-related activities. The high-speed SEABED (Shape Estimation Algorithm based on BST and Extraction of Directly scattered waves) imaging algorithm, is used in the application of UWB pulse radar in fields that require realtime operations. The SEABED algorithm assumes that omni-directional antennas are scanned to observe the scattered electric field in each location. However, for surveillance systems, antenna scanning is impractical because it restricts the setting places of the devices. In this paper, movement of a body is used to replace antenna scanning. The instantaneous velocity of any given motion is an unknown variable that changes as a function of time. A pair of antennas is used to analyze delay time to estimate the unknown motion. We propose a new algorithm to estimate the shape of a human body using data obtained from a human body passing stationary antennas.

In this article, we propose a vehicle positioning method that can estimate positions of cars even in areas where the GPS is not available. For the estimation, each car measures the relative distance to a car running in front, communicates the measurements with other cars, and uses the received measurements for estimating its position. In order to estimate the position even if the measurements are received with time-delay, we employed the time-delay tolerant Kalman filtering. For sharing the measurements, it is assumed that a car-to-car communication system is used. Then, the measurements sent from farther cars are received with larger time-delay. It follows that the accuracy of the estimates of farther cars become worse. Hence, the proposed method manages only the states of nearby cars to reduce computing effort. The authors simulated the proposed filtering method and found that the proposed method estimates the positions of nearby cars as accurate as the distributed Kalman filtering.

Even though weighted frequent pattern (WFP) mining is more effective than traditional frequent pattern mining because it can consider different semantic significances (weights) of items, existing WFP algorithms assume that each item has a fixed weight. But in real world scenarios, the weight (price or significance) of an item can vary with time. Reflecting these changes in item weight is necessary in several mining applications, such as retail market data analysis and web click stream analysis. In this paper, we introduce the concept of a dynamic weight for each item, and propose an algorithm, DWFPM (dynamic weighted frequent pattern mining), that makes use of this concept. Our algorithm can address situations where the weight (price or significance) of an item varies dynamically. It exploits a pattern growth mining technique to avoid the level-wise candidate set generation-and-test methodology. Furthermore, it requires only one database scan, so it is eligible for use in stream data mining. An extensive performance analysis shows that our algorithm is efficient and scalable for WFP mining using dynamic weights.

This paper introduces a theory for fast optimization of the circuit topology and parameters in sinusoidal oscillators. The theory starts from a system model composed of standard active and passive elements. We then include even the output load in the circuit, so that there is no longer any interaction with the outside of the system through the port. This model is thus called no-input-no-output (NINO) oscillator. The circuit is cut at an arbitrary branch, and is characterized in terms of the scalar impedance from the cut point. This is called active impedance because it is a function of not only the stimulating frequency but also the active device gain. The oscillation frequency and necessary device gain are estimated by solving impedance-domain Barkhausen equilibrium equations. This estimation works for the adjustment of circuit elements to meet the specified oscillation frequency. The estimation of necessary device gain enables us to maximize the oscillation amplitude, thanks to the inherent negative-slope nonlinearity of active devices. The active impedance is also used to derive the oscillation Q (quality) factor, which serves as a key criterion for sideband noise minimization i.e. frequency spectrum purification. As an alternative measure to active impedance, we also introduce branch admittance matrix determinant. This has the same numerical effect as the scalar impedance but can be used to formulate oscillator characteristics in a more elegant fashion, and provides a lucent picture of the physical behavior of each element in the circuit. Based on the proposed theory, we provide the tabled formulas of oscillation frequency, necessary device gain, active Q factor for a variety of typical Colpitts, Hartley, and cross-coupled twin-FET (field-effect transistor) oscillators.