Window-shaped obstacle avoidance for a redundant manipulator.

The window-shaped obstacle avoidance problem is studied in this paper. Several research papers regarding obstacle avoidance including the method proposed by Zghal et al., which we believe is the most suitable for three-dimensional (3-D) window-shaped obstacle avoidance are studied.

A parallel fuzzy inference model with distributed prediction scheme for reinforcement learning.

This paper proposes a three-layered parallel fuzzy inference model called reinforcement fuzzy neural network with distributed prediction scheme (RFNN-DPS), which performs reinforcement learning with a novel distributed prediction scheme. In RFNN-DPS, an additional predictor for predicting the external reinforcement signal is not necessary, and the internal reinforcement information is distributed into fuzzy rules (rule nodes). Therefore, using RFNN-DPS, only one network is needed to construct a fuzzy logic system with the abilities of parallel inference and reinforcement learning.

Modeling and analysis of equipment managers in manufacturing execution systems for semiconductor packaging.

Equipment Managers (EMs) play a major role in a Manufacturing Execution System (MES). They serve as the communication bridge between the components of an MES and the equipment. The purpose of this paper is to propose a novel methodology for developing analytical and simulation models for the EM such that the validity and performance of the EM can be evaluated.

Robust radial basis function neural networks.

Function approximation has been found in many applications. The radial basis function (RBF) network is one approach which has shown a great promise in this sort of problems because of its faster learning capacity. A traditional RBF network takes Gaussian functions as its basis functions and adopts the least-squares criterion as the objective function, However, it still suffers from two major problems.

Scheduling multiprocessor job with resource and timing constraints using neural networks.

The Hopfield neural network is extensively applied to obtaining an optimal/feasible solution in many different applications such as the traveling salesman problem (TSP), a typical discrete combinatorial problem. Although providing rapid convergence to the solution, TSP frequently converges to a local minimum. Stochastic simulated annealing is a highly effective means of obtaining an optimal solution capable of preventing the local minimum.

Design of adaptive fuzzy logic controller based on linguistic-hedge concepts and genetic algorithms.

In this paper, we propose a novel fuzzy logic controller, called linguistic hedge fuzzy logic controller, to simplify the membership function constructions and the rule developments. The design methodology of linguistic hedge fuzzy logic controller is a hybrid model based on the concepts of the linguistic hedges and the genetic algorithms. The linguistic hedge operators are used to adjust the shape of the system membership functions dynamically, and ran speed up the control result to fit the system demand.

A class of physical modeling recurrent networks for analysis/synthesis of plucked string instruments.

A new approach is proposed that closely synthesizes tones of plucked string instruments by using a class of physical modeling recurrent networks. The strategies employed consist of a fast training algorithm and a multistage training procedure that are able to obtain the synthesis parameters for a specific instrument automatically. The training vector can be recorded tones of most target plucked instruments with ordinary microphones.

Reconstruction of medical images under different image acquisition angles.

Compared to object-based registration, feature-based registration is much less complex. However, in order for feature-based registration to work, the two image stacks under consideration must have the same acquisition tilt angle and the same anatomical location - two requirements that are not always fulfilled. In this paper, we propose a technique that reconstructs two sets of medical images acquired with different acquisition angles and anatomical cross sections into one set of images of identical scanning orientation and positions.

New approach to intelligent control systems with self-exploring process.

This paper proposes an intelligent control system called self-exploring-based intelligent control system (SEICS). The SEICS is comprised of three basic mechanisms, namely, controller, performance evaluator (PE), and adaptor. The controller is constructed by a fuzzy neural network (FNN) to carry out the control tasks.

Nerve cell segmentation via multi-scale gradient watershed hierarchies.

Automated segmentation of nerve cell in microscopic image is an important task in neural researches. We proposed a multi-scale watershed-based approach to cope with this microscopic image analysis problem. There are three stages in the proposed segmentation algorithm: (1) a multi-scale watershed scheme is used to estimate an initial location of nerve cell nuclei; (2) we can identity nerve cell nuclei according to properties of nerve cell and watershed results in different scale; (3) Once the possible nerve cell is identified as a true one, a fuzzy rule based active contour model (ACM) is applied to find the optimal outer contour.

The simulation of current generator design for multi-frequency electrical impedance tomograph.

In the development of new generation EIT systems, the design of a steady current generator with broad bandwidth is an important consideration. In this paper, the current generator is constructed by enhanced Howland circuit with high-speed operational amplifier. The electronic models of current generator built on Orcad PSpice 9.

Tissue image interpolation based on fractional Brownian motion.

Fractal Brownian Motion (fBm) has been proven in a viewpoint of irregularity characterization for quantifying the structure of the tissue images. Breast masses were selected as the target sample because breast-associated diseases have become prevalent in Taiwan. In this paper, the ability of fractal dimension in fractal interpolation schemes is investigated and compared with the traditional interpolation schemes including bilinear and bicubic methods.

The quantization of chinese deep pulse.

Clinic Chinese pulse diagnosis is done by using fingers to touch the radial artery on the wrist to get the floating, middle, and deep pulses. However, the pressure of deep pulse is not an absolute value. It depends on many individual factors, such as age, height, weight, sex, and flexibility of blood vessel.

Quantification of pre-parturition restlessness in crated sows using ultrasonic measurement.

This study presents the non-video, noninvasive, automatic, and on-site monitoring system employing ultrasonic transducers to detect the behavior in sows before, during and after parturition. An ultrasonic transmitting/receiving (T/R) circuit of 40kHz is mounted above a conventional parturition bed. The T/R units use ultrasonic time-of-flight (TOP) ranging technology to measure the height of the confined sows at 8 predetermined locations.

Design and implementation of the tree-based fuzzy logic controller.

In this paper, a tree-based approach is proposed to design the fuzzy logic controller. Based on the proposed methodology, the fuzzy logic controller has the following merits: the fuzzy control rule can be extracted automatically from the input-output data of the system and the extraction process can be done in one-pass; owing to the fuzzy tree inference structure, the search spaces of the fuzzy inference process are largely reduced; the operation of the inference process can be simplified as a one-dimensional matrix operation because of the fuzzy tree approach; and the controller has regular and modular properties, so it is easy to be implemented by hardware. Furthermore, the proposed fuzzy tree approach has been applied to design the color reproduction system for verifying the proposed methodology.

Study and resolution of singularities for a 6-DOF PUMA manipulator.

Upon solving the inverse kinematics problem of robot manipulators, the inherent singularity problem should always be considered. When a manipulator is approaching a singular configuration, a certain degree of freedom will be lost such that there are no feasible solutions of the manipulator to move into this singular direction. In this paper, the singularities of a 6-DOF PUMA manipulator are analyzed in detail and all the corresponding singular directions in task space are clearly identified.

An efficient method for obtaining the general solution for the force balance equations with hard point contacts.

A compact formulation which is more efficient than the traditional pseudoinverse formulation for obtaining the general solution for the force balance equations has been presented (Cheng and Orin, 1991). With hard point contacts considered, the force balance equations can be decomposed into two sets of rank 3, smaller linear equations if proper coordinate frames of the reference member and at the contact points are chosen. This decomposition, together with the compact formulation, can reduce the steps of the Gaussian elimination process, increase parallelism of the algorithm, and therefore, keep the computation time for obtaining the general solution for the force balance equations to a minimum.

Combined techniques of singular value decomposition and vector quantization for image coding.

The combination of singular value decomposition (SVD) and vector quantization (VQ) is proposed as a compression technique to achieve low bit rate and high quality image coding. Given a codebook consisting of singular vectors, two algorithms, which find the best-fit candidates without involving the complicated SVD computation, are described. Simulation results show that the proposed methods are better than the discrete cosine transform (DCT) in terms of energy compaction, data rate, image quality, and decoding complexity.

Multiscale corner detection by using wavelet transform.

A multiscale corner detection algorithm based on the wavelet transform of contour orientation is proposed. It can utilize both the information of the local extrema and modulus of transform results to detect corners and arcs effectively. The ramp-width of contour orientation profile, which can be computed using the transformed modulus of two scales, reveals the difference between corner and arc and is utilized in the determination of corner points.

Reliability characteristics of quadratic Hebbian-type associative memories in optical and electronic network implementations.

The performance capability of quadratic Hebbian type associative memories (QHAM's) in the presence of interconnection faults is examined, and equations for predicting the probability of direct convergence P(dc) given a fraction of interconnection faults are developed. The interconnection faults considered are the equivalent of open circuit and short circuit synaptic interconnections in electronic implementations. Our results show that a network with open circuit interconnection faults has a higher probability of direct convergence P (dc) than a network with short circuit interconnection faults, when the fraction of failed interconnections p is small and the short circuit signal G is large.

A general mean-based iterative winner-take-all neural network.

In this paper, a new iterative winner-take-all (WTA) neural network is developed and analyzed. The proposed WTA neural net with one-layer structure is established under the concept of the statistical mean. For three typical distributions of initial activations, the convergence behaviors of the existing and the proposed WTA neural nets are evaluated by theoretical analyses and Monte Carlo simulations.