We model wireless local area network channel utilization over a finite interval through a finite time-horizon Markov (FTHM) model. By accurately capturing time-varying utilization, the FTHM model allows for generally distributed transmission-opportunity (TXOP) duration, which most existing models do not account for. An absorbing state is introduced to limit the lifetime of the counting process, resulting in a non-ergodic Markov chain that is solved via transient analysis. The model predictions for time-varying utilization are validated by simulation with errors of no more than 0.1% after eight beacon intervals. Moreover, we show that the FTHM model prediction error is below 4% for Poisson distributed and uniformly distributed TXOP durations.

A simplified minimum mean square error (MMSE) detector is proposed for joint detection and decoding of multiple-input multiple-output (MIMO) systems. The matrix inversion lemma and the singular value decomposition (SVD) of the channel matrix are used to simplify the computation of the coefficient of the MMSE filter. Compared to the original MMSE detector, the proposed detector has a much lower computational complexity with only a marginal performance loss. The proposed detector can also be applied to MIMO systems with high order modulations.

The most dominant error source for microwave ranging is the frequency instability of the oscillator that generates the carrier phase signal. The oscillator noise is very difficult to filter due to its extremely low frequency. A dual transponder carrier ranging method can effectively minimize the oscillator noise by combing the reference phase and the to-and-fro measurement phase from the same single oscillator. This method does not require an accurate time tagging system, since it extracts phases on the same satellite. This paper analyzes the dual transponder carrier ranging system by simulation of the phase measurements with comprehensive error models. Both frequency domain and time domain noise transfer characteristics were simulated to compare them with dual one-way ranging. The simulation results in the two domains conformed to each other and demonstrated that a high level of accuracy can also be achieved by use of the dual transponder carrier ranging system, with relatively simple instruments.

Wireless sensor networks consist of hundreds or thousands of sensor nodes that involve numerous restrictions including computation capability and battery capacity. Topology control is an important issue for achieving a balanced placement of sensor nodes. The clustering scheme is a widely known and efficient means of topology control for transmitting information to the base station in two hops. The automatic routing scheme of the self-organizing technique is another critical element of wireless sensor networks. In this paper we propose an optimal algorithm with cluster balance taken into consideration, and compare it with three well known and widely used approaches, i.e., LEACH, MEER, and VAP-E, in performance evaluation. Experimental results show that the proposed approach increases the overall network lifetime, indicating that the amount of energy required for communication to the base station will be reduced for locating an optimal cluster.

We present a bulk micromachined in-plane capacitive accelerometer fabricated with an improved process flow, by etching only one-fifth of the wafer thickness at the back of the silicon while forming the bar-structure electrode for the sensing capacitor. The improved flow greatly lowers the footing effect during deep reactive ion etching (DRIE), and increases the proof mass by 54% compared to the traditional way, resulting in both improved device quality and a higher yield rate. Acceleration in the X direction is sensed capacitively by varying the overlapped area of a differential capacitor pair, which eliminates the nonlinear behavior by fixing the parallel-plate gap. The damping coefficient of the sensing motion is low due to the slide-film damping. A large proof mass is made using DRIE, which also ensures that dimensions of the spring beams in the Y and Z directions can be made large to lower cross axis coupling and increase the pull-in voltage. The theoretical Brownian noise floor is 0.47 μg/Hz^1/2 at room temperature and atmospheric pressure. The tested frequency response of a prototype complies with the low damping design scheme. Output data for input acceleration from −1 g to 1 g are recorded by a digital multimeter and show very good linearity. The tested random bias of the prototype is 130 μg at an averaging time of around 6 s.

This paper describes the fabrication of a waveguide and the analysis of its polarization characteristics by applying light-emitting diode (LED) pumping lights to its surface. By using double tubed coaxial line (DTCL) microwave plasma chemical vapor deposition (MPCVD) equipment, an a-Si:H/SiN multilayer waveguide was fabricated whose thickness could be controlled at nanometer order. The main structural material of the waveguide sample consisted of a combination of layers of amorphous silicon hydrogen and silicon nitrate. Once the sample was ready, another major objective of the experiment was to analyze the polarization characteristics of the fabricated waveguide. The idea of the experiment was to analyze how the waveguide reacts when three types of LED (blue, yellow, and red) are radiated onto its surface. The results showed that the fabrication of the a-Si:H/SiN sample is successful. Most effective transmission results, which accord with the polarization characteristics analysis, were obtained.

This paper presents a novel interactive system for establishing compatible meshes for articulated shapes. Given two mesh surfaces, our system automatically generates both the global level component correspondence and the local level feature correspondence. Users can use some sketch-based tools to specify the correspondence in an intuitive and easy way. Then all the other vertex correspondences could be generated automatically. The cross parameterization preserves both high level and low level features of the shapes. The technique showed in the system benefits various applications in graphics including mesh interpolation, deformation transfer, and texture transfer.

This paper presents an approach for recognizing both isolated and intersecting geometric features of freeform surface models of parts, for the purpose of automating the process planning of sheet metal forming. The developed methodology has three major steps: subdivision of B-spline surfaces, detection of protrusions and depressions, and recognition of geometric features for sheet metal forming domain. The input geometry data format of the part is based on an IGES CAD surface model represented in the form of trimmed B-spline surfaces. Each surface is classified or subdivided into different curvature regions with the aid of curvature property surfaces obtained by using symbolic computation of B-spline surfaces. Those regions satisfying a particular geometry and topology relation are recognized as protrusion and depression (DP) shapes. The DP shapes are then classified into different geometric features using a rule-based approach. A verified feasibility study of the developed method is also presented.

Labeling information in a complex irregular region is a useful procedure occurring frequently in sheet metal and the furniture industry which will be beneficial in parts management. A fast code-based labeler (FCBL) is proposed to accomplish this objective in this paper. The region is first discretized, and then encoded by the Freeman encoding technique for providing the 2D regional information by 1D codes with redundancies omitted. We enhance the encoding scheme to make it more suitable for our complex problem. Based on the codes, searching algorithms are designed and can be extended with customized constraints. In addition, by introducing a smart optimal direction estimation, the labeling speed and accuracy of FCBL are significantly improved. Experiments with a large range of real data gained from industrial factories demonstrate the stability and millisecond-level speed of FCBL. The proposed method has been integrated into a shipbuilding CAD system, and plays a very important role in ship parts labeling process.

Speaker variability is an important source of speech variations which makes continuous speech recognition a difficult task. Adapting automatic speech recognition (ASR) models to the speaker variations is a well-known strategy to cope with the challenge. Almost all such techniques focus on developing adaptation solutions within the acoustic models of the ASR systems. Although variations of the acoustic features constitute an important portion of the inter-speaker variations, they do not cover variations at the phonetic level. Phonetic variations are known to form an important part of variations which are influenced by both micro-segmental and suprasegmental factors. Inter-speaker phonetic variations are influenced by the structure and anatomy of a speaker’s articulatory system and also his/her speaking style which is driven by many speaker background characteristics such as accent, gender, age, socioeconomic and educational class. The effect of inter-speaker variations in the feature space may cause explicit phone recognition errors. These errors can be compensated later by having appropriate pronunciation variants for the lexicon entries which consider likely phone misclassifications besides pronunciation. In this paper, we introduce speaker adaptive dynamic pronunciation models, which generate different lexicons for various speaker clusters and different ranges of speech rate. The models are hybrids of speaker adapted contextual rules and dynamic generalized decision trees, which take into account word phonological structures, rate of speech, unigram probabilities and stress to generate pronunciation variants of words. Employing the set of speaker adapted dynamic lexicons in a Farsi (Persian) continuous speech recognition task results in word error rate reductions of as much as 10.1% in a speaker-dependent scenario and 7.4% in a speaker-independent scenario.

We propose an algorithm of embedding ensemble tracking in a stochastic framework to achieve robust tracking performance under partial occlusion, illumination changes, and abrupt motion. It operates on likelihood images generated by the ensemble method, and combines mean shift and particle filtering in a principled way, where a better proposal distribution is designed by first propagating particles via a motion model, and then running mean shift to move towards their local peaks in the likelihood image. An observation model in the particle filter incorporates global and local information within a region, and an adaptive motion model is adopted to depict the evolution of the object state. The algorithm needs fewer particles to manage the tracking task compared with the general particle filter, and recaptures the object quickly after occlusion occurs. Experiments on two image sequences demonstrate the effectiveness and robustness of the proposed algorithm.

Obtaining an electrocorticograms (ECoG) signal requires an invasive procedure in which brain activity is recorded from the cortical surface. In contrast, obtaining electroencephalograms (EEG) recordings requires the non-invasive procedure of recording the brain activity from the scalp surface, which allows EEG recordings to be performed more easily on healthy humans. In this work, a technique previously used to study spatial-temporal patterns of brain activity on animal ECoG was adapted for use on EEG. The main issues are centered on solving the problems introduced by the increment on the interelectrode distance and the procedure to detect stable frames. The results showed that spatial patterns of beta and gamma activity can also be extracted from the EEG signal by using stable frames as time markers for feature extraction. This adapted technique makes it possible to take advantage of the cognitive and phenomenological awareness of a normal healthy subject.

We present novel vector permutation and branch reduction methods to minimize the number of execution cycles for bit reversal algorithms. The new methods are applied to single instruction multiple data (SIMD) parallel implementation of complex data floating-point fast Fourier transform (FFT). The number of operational clock cycles can be reduced by an average factor of 3.5 by using our vector permutation methods and by 1.1 by using our branch reduction methods, compared with conventional implementations. Experiments on MPC7448 (a well-known SIMD reduced instruction set computing processor) demonstrate that our optimal bit-reversal algorithm consistently takes fewer than two cycles per element in complex array operations.

A generalized controller based on stability theory of singularly perturbed systems is proposed, to deal with the problem of bounded actuator inputs in robot trajectory tracking control. The saturation function with error-gain matrix is applied in the torque control law, which ensures the upper bound of torque inputs in any given limited range. Through appropriately setting the entries of the error-gain matrix, the tracking performance can be improved. Moreover, a pseudo signal is generated from a linear filter to substitute for the actual velocity error, eliminating the need for velocity measurements. Finally, to verify the effectiveness of the generalized controller, a new saturated controller with error-gain-contained arc tangent function is designed. Comparison experiments show that the proposed controller can strictly guarantee the bound of the torque inputs in situations with non-zero initial tracking errors, and gives a better tracking result than other controllers.

The objective of this study was to obtain spatial distribution maps of paddy rice fields using multi-date moderate-resolution imaging spectroradiometer (MODIS) data in China. Paddy rice fields were extracted by identifying the unique characteristic of high soil moisture in the flooding and transplanting period with improved algorithms based on rice growth calendar regionalization. The characteristic could be reflected by the enhanced vegetation index (EVI) and the land surface water index (LSWI) derived from MODIS sensor data. Algorithms for single, early, and late rice identification were obtained from selected typical test sites. The algorithms could not only separate early rice and late rice planted in the same fields, but also reduce the uncertainties. The areal accuracy of the MODIS-derived results was validated by comparison with agricultural statistics, and the spatial matching was examined by ETM+ (enhanced thematic mapper plus) images in a test region. Major factors that might cause errors, such as the coarse spatial resolution and noises in the MODIS data, were discussed. Although not suitable for monitoring the inter-annual variations due to some inevitable factors, the MODIS-derived results were useful for obtaining spatial distribution maps of paddy rice on a large scale, and they might provide reference for further studies.

The major aim of power quality (PQ) enhancing techniques is to maintain a specified voltage magnitude at a desired frequency for sensitive loads irrespective of faults on the power distribution network. The dynamic voltage restorer (DVR) is a device used to mitigate voltage sags to regulate load voltage. This paper presents a mathematical model for leading series voltage injection to mitigate sags thereby achieving the improvement of the utility power factor as well as power sharing between the DVR and utility. The power sharing will be as per requirement to compensate the sags considering the available distributed generation (DG). The approach of mitigating voltage sags using the concept of leading series voltage injection is suitable for those locations where phase shift in the voltage will not cause any problem. The MATLAB/SIMULINK SimPowerSystem toolbox has been used to obtain simulation results to verify the proposed mathematical model.

This paper proposes a current control scheme for a grid-connected pulse width modulator (PWM) voltage source converter (GC-VSC) under imbalanced and distorted supply voltage conditions. The control scheme is implemented in the positive synchronously rotating reference frame and composed of a single proportional integral (PI) regulator and multi-frequency resonant controllers tuned at the frequencies of 2ω and 6ω, respectively. The experimental results, with the target of eliminating the active power oscillations and current harmonics on a prototype GC-VSC system, validate the feasibility of the proposed current control scheme during supply voltage imbalance and distortion.