The dynamic characteristics are the key issues in the optimum design of a permanent magnetic actuator (PMA). A new approach to forecast the dynamic characteristics of the multilink PMA is proposed. By carrying out further developments of ADAMS and ANSOFT, a mathematic calculation model describing the coupling of mechanical movement, electric circuit and magnetic field considering eddy current effect, is constructed. With this model, the dynamic characteristics of the multilink PMA are calculated and compared with the experimental results. Factors that affect the opening time of the multilink PMA are analyzed with the model as well. The method is capable of providing a reference for the design of the PMA.

RFID (Radio Frequency Identification) technology is expected to be used as a localization tool. By the localization of RFID tags, a mobile robot equipped with an RFID reader can recognize the surrounding environment. In this paper, we propose a novel effective scheme called the communication range recognition (CRR) scheme for localizing RFID tags. In this scheme, an RFID reader determines the boundaries of the communication range when it is appropriately positioned by the robot. We evaluate the estimated position accuracy through numerous experiments. We show that the moving distance of the RFID reader in the proposed scheme is lower than that in conventional schemes.

We have developed a macro model, which allows us to describe precise LDMOS DC/AC characteristics. Characterization of anomalous gate input capacitance is the key issue in the LDMOS model development. We have newly employed a T-type distributed RC scheme for gate overlapped LDMOS drift region. The bias dependent resistance and capacitance are modeled independently in Verilog-A as R-model and PMOS-capacitance. The dividing factor of the distributed R is introduced to reflect the shield effect of the gate overlap capacitance. Comparison between the new model and measurement results has proven that the developed macro model reproduces accurately not only the gate input capacitance, but also DC characteristics.

Interrupt service routines are a key technology for embedded systems. In this paper, we introduce the standard approach for using Generalized Stochastic Petri Nets (GSPNs) as a high-level model for generating CTMC Continuous-Time Markov Chains (CTMCs) and then use Markov Reward Models (MRMs) to compute the performance for embedded systems. This framework is employed to analyze two embedded controllers with low cost and high performance, ARM7 and Cortex-M3. Cortex-M3 is designed with a tail-chaining mechanism to improve the performance of ARM7 when a nested interrupt occurs on an embedded controller. The Platform Independent Petri net Editor 2 (PIPE2) tool is used to model and evaluate the controllers in terms of power consumption and interrupt overhead performance. Using numerical results, in spite of the power consumption or interrupt overhead, Cortex-M3 performs better than ARM7.

In this paper, a novel feeding technique is proposed to feed a printed rectangular ring patch antenna that attains high gain in two bands simultaneously. The prototype antenna exhibits good impedance bandwidths satisfying ISM 2.45/5.8 GHz achieving maximum gain of 9.56 and 10.17 dBi, respectively, with a stable radiation pattern.

In this paper we introduce a new framework of audio processing, which is essential to achieve a trigger-free speech interface for home appliances. If the speech interface works continually in real environments, it must extract occasional voice commands and reject everything else. It is extremely important to reduce the number of false alarms because the number of irrelevant inputs is much larger than the number of voice commands even for heavy users of appliances. The framework, called Intentional Voice Command Detection, is based on voice activity detection, but enhanced by various speech/audio processing techniques such as emotion recognition. The effectiveness of the proposed framework is evaluated using a newly-collected large-scale corpus. The advantages of combining various features were tested and confirmed, and the simple LDA-based classifier demonstrated acceptable performance. The effectiveness of various methods of user adaptation is also discussed.

We investigated suitable spatial inverse filters for cortical dipole imaging from the scalp electroencephalogram (EEG). The effects of incorporating statistical information of signal and noise into inverse procedures were examined by computer simulations and experimental studies. The parametric projection filter (PPF) and parametric Wiener filter (PWF) were applied to an inhomogeneous three-sphere volume conductor head model. The noise covariance matrix was estimated by applying independent component analysis (ICA) to scalp potentials. The present simulation results suggest that the PPF and the PWF provided excellent performance when the noise covariance was estimated from the differential noise between EEG and the separated signal using ICA and the signal covariance was estimated from the separated signal. Moreover, the spatial resolution of the cortical dipole imaging was improved while the influence of noise was suppressed by including the differential noise at the instant of the imaging and by adjusting the duration of noise sample according to the signal to noise ratio. We applied the proposed imaging technique to human experimental data of visual evoked potential and obtained reasonable results that coincide to physiological knowledge.

In this paper we clarify for the boost and the buck-boost converter that the ripple effect is not ignorable for the frequency response, and reveal that it causes the unexpected characteristics where either the phase lag or the phase lead appears depending on the shape of waveform of the ramp generator in the PWM circuit. Eventually the phase margin for the stability drastically changes depending on the slope direction (normal or reverse) of the sawtooth waveform of the ramp generator even in the same circuit configuration. For the ripple effects we propose the general analysis model and analyze them of the boost and the buck-boost converters. As the result we identify that the ripple effects are caused mainly by the variation of the slope and the average of the ripple, and reveal that the both converters have the asymmetric characteristics for the slope direction of the sawtooth waveform of the ramp generator and there is more advantage for the stability in case of the reverse slope direction than in case of the normal one. It also clarified that the effect of ESR of the output capacitor of the converter on the frequency response is different according to the shape of the sawtooth waveforms. The proposed analysis method is validated by the experiments and simulations.

This study examined the performance improvement of a photovoltaic (PV) array and inverter as well as their design, construction, and post-operation and management, which will become the key elements in future PV systems. In addition, it evaluated the performance characteristics of a 50 kW grid-connection PV system in Korea. According to the result of the evaluation, the PV array showed approximately 10% efficiency. The inverter was indicated to operate at > 90% efficiency regularly at > 400 W/m2 irradiation. The capture losses (Lc), system losses (Ls) and performance ratio were approximately 0.9 h/d, 0.3 h/d, and > 70%, respectively, indicating that the system was operating stably. In addition, while the Ls decreased rapidly due to the efficiency of the inverter, the performance ratio decreased markedly with increasing Lc due to the increase in temperature when the reference yield was > 5.0 h/d.

The performance of the least-mean-square (LMS) beamformer is heavily dependent on the choice of the step-size, for it governs the convergence rate and steady-state excess mean squared error. To meet the conflicting requirement of low misadjustment, especially for the beamformer being modified in response to the multipath environmental changes, it needs to be controlled in a proper way. In this letter, we present an efficient adaptive step-size subarray LMS to achieve good performance. Simulation results are provided for illustrating the effectiveness of the proposed scheme.

This paper proposes an adaptive resource allocation for multi-tier computing systems to guarantee a fair QoS level under resource constraints of tiers. We introduce a multi-tier computing architecture which consists of a group of resource managers and an arbiter. Resource allocation of each client is managed by a dedicated resource manager. Each resource manager updates resources allocated to subtasks of its client by locally exchanging QoS levels with other resource managers. An arbiter compensates the updated resources to avoid overload conditions in tiers. Based on the compensation by the arbiter, the subtasks of each client are executed in corresponding tiers. We derive sufficient conditions for the proposed resource allocation to achieve a fair QoS level avoiding overload conditions in all tiers with some assumptions on a QoS function and a resource consumption function of each client. We conduct a simulation to demonstrate that the proposed resource allocation can adaptively achieve a fair QoS level without causing any overload condition.

In this letter, we present a real-time orientation estimation and motion tracking scheme using interacting multiple model (IMM) based Kalman filtering method. Two nonlinear filters, quaternion-based extended Kalman filter (QBEKF) and gyroscope-based extended Kalman filter (GBEKF) are utilized in the proposed IMM-based orientation estimator for sensor motion state estimation. In the QBEKF, measurements from gyroscope, accelerometer and magnetometer are processed; while in the GBEKF, sole measurements from gyroscope are processed. The interacting multiple model algorithm is used for fusing the estimated states via adaptive model weighting. Simulation results validate the proposed design concept, and the scheme is capable of reducing overall estimation errors in sensor motion tracking.

In this paper, we propose a novel filtering method for processing continuous skyline queries in wireless sensor network environments. The existing filtering methods on such environments use filters that are based on router paths. However, these methods do not have a major effect on reducing data for sensor nodes to transmit to the base station, because the filters are applied to not the whole area but a partial area. Therefore, we propose a novel and efficient method to dramatically reduce the data transmissions of sensors through applying an effective filter with low costs to all sensor nodes. The proposed effective filter is generated by using characteristics such as the data locality and the clustering of sensors. An extensive performance study verifies the merits of our new method.

The error diffusion filter in this paper is optimized with respect to the ideal blue noise pattern corresponding to a single tone level. The filter coefficients are optimized by the minimization of the squared error norm between the Fourier power spectra of the resulting halftone and the blue noise pattern. During the process of optimization, the binary pattern power spectrum matching algorithm is applied with the aid of a new blue noise model. The number of the optimum filters is equal to that of different tones. The visual fidelity of the bilevel halftones generated by the error diffusion filters is evaluated in terms of a weighted signal-to-noise ratio, Fourier power spectra, and others. Experimental results have demonstrated that the proposed filter set generates satisfactory bilevel halftones of grayscale images.

A scheme for designing a hierarchical fuzzy classification system with a different number of fuzzy partitions based on statistical characteristics of the data is proposed. To minimize the number of misclassified patterns in intermediate layers, a method of fuzzy partitioning from the defuzzified outputs of previous layers is also presented. The effectiveness of the proposed scheme is demonstrated by comparing the results from five datasets in the UCI Machine Learning Repository.

We proposed a new motion vector (MV) smoothing using fuzzy weighting and vector median filtering for frame rate up-conversion. A fuzzy reasoning system adjusts the weighting values based on the local characteristics of MV field including block difference and block boundary distortion. The fuzzy weighting removes the affect of outliers and irregular MVs from the MV smoothing process. The simulation results show that the proposed algorithm can efficiently correct wrong MVs and thus improve visual quality of the interpolated frames better than conventional methods.

A high-throughput on-chip monitoring circuit with a digital output is proposed for the variations of the NMOS and PMOS threshold voltages. A voltage-controlled delay line (VCDL) and a time-to-digital converter (TDC) are used to convert a small difference in analog voltage into a large difference in time delay. This circuit was applied to the transistors of W = 10 µm and L = 0.18 µm in a 1616 array matrix fabricated with a 0.18-µm process. The measurement of the threshold voltage shows that the maximum peak-to-peak intra-chip variation of NMOS and PMOS transistors are about 31.7 mV and 32.2 mV, respectively, for the temperature range from -25 to 75. The voltage resolutions of NMOS and PMOS transistors are measured to be 1.10 mV/bit and 3.53 mV/bit at 25, respectively. The 8-bit digital code is generated for the threshold voltage of a transistor in every 125 ns, which corresponds to the 8-MHz throughput.

This paper proposes a constant-power adder based on multiple-valued logic and its application to cryptographic processors being resistant to side-channel attacks. The proposed adder is implemented in Multiple-Valued Current-Mode Logic (MV-CML). The important feature of MV-CML is that the power consumption can be constant regardless of input values, which makes it possible to prevent power-analysis attacks using dependencies between power consumption and intermediate values or operations of the executed cryptographic algorithms. In this paper, we focus on a multiple-valued Binary Carry-Save adder based on the Positive-Digit (PD) number system and its application to RSA processors. The power characteristic of the proposed design is evaluated with HSPICE simulation using 90 nm process technology. The result shows that the proposed design can achieve constant power consumption with lower performance overhead in comparison with the conventional binary design.

Motivated by the needs of modern agriculture, in this paper we present CropNET, a wireless multimedia sensor network system for agriculture monitoring. Both hardware and software designs of CropNET are tailored for sensing in wide farmland without human supervision. We have carried out multiple rounds of deployments. The evaluation results show that CropNET performs well and facilitates modern agriculture.

This paper describes the circuit design and measured performance of a high-speed digital-to-analog converter (DAC) for the next generation of coherent optical communications systems. To achieve high-speed and low-power operation, we used an R-2R current-steering architecture and devised timing alignment and waveform improvement techniques. A 6-bit DAC test chip was fabricated with InP HBT technology, which yields a peak ft of 175 GHz and a peak fmax of 260 GHz. The measured differential and integral non-linearity (DNL and INL) are within +0.61/-0.07 LSB and +0.27/-0.52 LSB, respectively. The measured spurious-free dynamic range (SFDR) is 44.7 dB for a sinusoidal output of 72.5 MHz at a sampling rate of 13.5 GS/s, which was the limit of our measurement setup. The expected ramp-wave outputs at a sampling rate of 24 GS/s are also obtained. The total power consumption is as low as 0.88 W with a supply voltage of -4.0 V. This DAC can provide low-power operation and a higher sampling rate than any other previously reported DAC with a resolution of 5 bits or more.