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The history of test is looked at for IC Test to put in context the papers that are being highlighted at DATE. This paper focuses on the path that led to the adoption of structural test. ATE related historical aspects are not mentioned. [ABSTRACT FROM AUTHOR]

When performing quality inspection of recycled paper one phenomenon of concern is the appearance of macroscopic undulations on the paper sheet surface that may emerge shortly or some time after its production. In this paper we explore the detection and measurement of this defect by means of computer vision and statistical pattern recognition techniques that may allow early detection at the production site. We propose features computed from Gabor Filter Banks (GFB) and Discrete Wavelet Transforms (DWT) for the characterization of paper sheet surface bumpiness in recycled paper images. The lack of a precise definition of the defect and the great variability of the sheet deformation shapes and scales, both within each image and between images, introduce additional difficulties to the problem. We obtain, with both proposed modeling approaches (GFB and DWT), classification accuracies are comparable to the agreement between human observers. The best performance is obtained using DWT features. [ABSTRACT FROM AUTHOR]

In this paper we review two well-known citation methods to find relatedness between scientific papers: co-citation and bibliographic coupling. We propose a practical method to estimate the co-citation relatedness using the Google search engine. We call this method Web co-citation. We conducted experiments on a collection of scientific papers to compare the performances of different methods. The experimental results show that our approach, despite its simplicity, is efficient in discovering the relatedness between scientific papers. [ABSTRACT FROM AUTHOR]

MIMO systems are of interest to meet the expected demand for higher data rates and lower delays in future wireless systems. In addition, multi-carrier systems are of interest to combat frequency-selective fading experienced over the larger bandwidth these future broadband systems will use. The introduction of these spatial and frequency resources adds extra dimensions and complexity for any scheduling algorithm in a multiuser system. In this paper, we investigate scheduling through utility functions implemented via genetic algorithms in order to reduce complexity. This paper extends our prior work for a single-carrier MIMO system using dirty paper coding to the multi-carrier case. Here, the users that are scheduled, the order they are encoded in, and the subcarrier frequencies they are assigned to will all affect the performance of the scheduling algorithm. We demonstrate that the genetic algorithm is still able to achieve a similar near-optimal performance relative to an exhaustive search with the same relative reduction in complexity. Additionally, with the use of OFDM, an increase in capacity is seen relative to the single-carrier case. [ABSTRACT FROM AUTHOR]

The softened rolling contact of two paper machine rolls is considered. A regenerative excitation source can exists in the system due to the finite relaxation time of the roll cover polymer materials. The modeling of the rolls is described by multibody substructuring methodology and the polymer cover layer between the rolls in contact is modeled by contact spring reaction forces calculated according to the stiffness of the layer. The regenerative excitation is introduced to the system as a time delay term and it is calculated from the penetration history of the cover layer. The solution of the system equations is obtained by numerical time integration by utilizing the method of steps time delay equation solution procedure. Some numerical results are illustrated. [ABSTRACT FROM AUTHOR]

This paper presents the experimental aspects of a robotic system used for detection, sorting and grading of paper objects from visual features. The experimental system is used as an automated paper recycling system. The system uses simplified stereo vision to compute position estimate of unknown objects. A vector of geometrical and textural features is used for sorting the paper, according to its grade. The grading process uses additional contact sensors for refining grading from visual features. Supervised learning is used for training the decision system to separate paper from other objects. The experimental aspects of the training process are presented in detail. A special vacuum gripper was designed for gripping paper objects detected by the vision system. The experimental results prove the efficiency of the proposed techniques. [ABSTRACT FROM AUTHOR]

This paper is a study of the correlation between the humidity, density and matrix suction of non-plastic soil taken from a region located near the city of Rio de Janeiro. The study was conducted through laboratory tests, using minilysimeters and equipment that indirectly measured the humidity through soil suction: in effect, an automated tensiometer, an equivalence tensiometer (EQ2), a TDR and a specially adapted system, which measures the suction in situ, using filter paper. The electronic instruments were connected to a data logger and placed in three mini-lysimeters. Cycles of wetting and drying of the confined material were simulated. The soil was characterised. This characterisation enabled the determination of physical indexes, density, plasticity, grain size, porosity, and the characteristic curve of water retention, using the Richards pressure pan (cooker) test. The results obtained by the instruments, humidity and matrix suction, were compared with the characteristic curve. Overall, the equipment was satisfactory. The low presence of clay in this soil, around 7%, and its associated high porosity, were factors in limiting water retention. The equilibrium time of the soil humidity and the filter paper, obtained at intervals of fifteen days, presented better results than the weekly intervals (seven days). The equivalence tensiometer EQ2 compared to the filter paper presented quite efficient results for high suction values. [ABSTRACT FROM AUTHOR]

In this paper, we study the servomechanism problem for positive LTI systems. In particular, we consider the robust servomechanism problem of nonnegative constant reference signals for stable SISO positive LTI systems with constant disturbances, for the case when the plant model of the system is not known. A positive LTI system is an LTI system with the imposed constraint that the state, output and/or input variables be nonnegative for all time. This type of constraint is quite natural to apply, since the property of nonnegativity occurs quite frequently in practical applications and in nature, e.g. in pharmacodynamic applications, infusion of vasoactive drugs, chemical systems. A special class of positive systems that is of significant importance and appears quite frequently in the literature is the class of compartmental systems; these systems are composed of a finite number of storage devices or reservoirs and model various gas, fluid, and solid exchange networks. Positive systems have been of great interest to numerous researchers over several decades. Interesting results obtained on positive systems span the topics of reachability and controllability, realization theory for positive systems, stability control, and control via pole-assignment. However, to date, there appears that no study has been carried out on the servomechanism problem for positive LTI systems; thus we focus our attention on this topic in the paper. Various applications of the results are applied to a number of positive system problems obtained from the literature. [ABSTRACT FROM AUTHOR]

This paper considers localization of a source or a sensor from distance measurements. We argue that linear algorithms proposed for this purpose are susceptible to poor noise performance. Instead given a set of sensors/anchors of known positions and measured distances of the source/sensor to be localized from them we propose a potentially non-convex weighted cost function whose global minimum estimates the location of the source/sensor one seeks. The contribution of this paper is to provide nontrivial ellipsoidal and polytopic regions surrounding these sensors/anchors of known positions, such that if the object to be localized is in this region, localization occurs by globally exponentially convergent gradient descent in the noise free case. Exponential convergence in the noise free case represents practical convergence as it ensures graceful performance degradation in the presence of noise. These results guide the deployment of sensors/anchors so that small subsets can be made responsible for practical localization in geographical areas determined by our approach. [ABSTRACT FROM AUTHOR]

In vision-based robotic arc welding had some degree of autonomy functions, sensors must be used to detect the position and orientation of a weld seam and determine its path in order to carry out the autonomy of welding process. This paper represented a method to recognize whole seam in complex robotic welding environment. According to the parameter we defined to judge the degree of image noise, then different size of filter windows were selected to preprocess the image. Algorithm to eliminate effect of complex changing background is proposed. Parameters are defined to judge if it is necessary to use this algorithm. The threshold and edge detect algorithms that adapt to the recognition for robotic welding environment is also addressed in this paper. The experiments give the recognition results of two different shapes and material of seams. The results showed that the recognized method was robust to the recognition of macroscopic seam for complex robotic welding environment. [ABSTRACT FROM AUTHOR]

This paper describes one aspect of our approach in developing an intelligent off-road autonomous vehicle, the Intelligent Off-road Navigator (ION), as team Desert Buckeyes from the Ohio State University for the DARPA Grand Challenge 2005. The real-time navigation is one of the critical components in an autonomous ground vehicle system. In this paper, we focus on the navigation module, whose main responsibility is to generate smooth and obstacle-free local paths with appropriate speed setpoints. For the smooth path generation, we introduce a polynomial interpolation method. To generate obstacle-free paths, a steering controller utilizing a fuzzy obstacle avoidance algorithm is presented. A speed fuzzy controller is introduced to generate the speed setpoints. These two fuzzy controllers collaborate with each other to guide our vehicle ION to the goal safely. The obstacle avoidance algorithm proposed in this paper was also tested in simulations and on small robots successfully. Other issues related to the navigation module are discussed in the paper as well, such as the vehicle's system structure and its finite state machine. As a result, ION achieved great performance in the National Qualification Event (NQE), covered about 30miles in the Nevada Desert with complete autonomous operations, and finished 10th in the Grand Challenge 2005. [ABSTRACT FROM AUTHOR]

Obstructive Sleep Apnea (OSA) is the most common type of sleep apnea. OSA is caused by an obstruction in the upper airway, which actually stops the air flow in the nose and mouth during sleep. The current gold standard of diagnosis, called polysomnography (PSG), requires a fullnight hospital stay connected to over ten channels of measurements requiring physical contact with sensors. PSG is inconvenient, expensive and unsuited for community screening. OSA is commonly accompanied by snoring, but its potential in clinical diagnosis is not fully recognized yet. In this paper, we use the snore sounds (SS) as diagnostic systems, and propose the novel technique to track the sleep state of OSA patient in the connection weight space (CWS) of neural networks (NN) after the process of supervised training. While the SS data/database of OSA patient provides an excellent medium to test our methods, we carry out experiments using two variations of the basic back-propagation (BP) algorithm: the steepest descent (SD) algorithm and the Levenberg-Marquardt (LM) algorithm. This paper compares the performance of SD with that of LM algorithm in an attempt to find an ideal artificial NN-training algorithm to model the SS. [ABSTRACT FROM AUTHOR]

Based on the molecular mechanics, this paper uses the two-body potential energy function to construct a trapezoidal cantilever nano-scale simulation measurement model of contact mode atomic force microscopy (AFM) under the constant force mode to simulate the measurement the nano-scale standard stairstep sample. This paper investigates the offset distance error occurred during scanning the cross-section curve of the standard step sample. The two probes employed in this study are of different cantilever geometry and probe material (V-shaped Si3N4 cantilever and trapezoidal Si cantilever), but have the same tip radius of 3.65 nm. It is found that the probe tip radius and the tip edge oblique angle of the probe influenced the cross-section curve during simulation measurement. Therefore, the factor influencing this cross-section curve appearance is mainly the geometry form of the probe. It can be observed that the cross-section curve under simulation measurement by using the trapezoidal Si cantilever is closer to the cross-section curve of nano-scale standard sample than under simulation measurement by using the V-shaped Si3N4 cantilever. It can be known that the probe material can influence the cross-section curve under simulated measurement. The investigation of the error analysis is referential in compensating the error of AFM measurement in the future, and can be used to further enhance the accuracy of AFM scanning and measurement. [ABSTRACT FROM AUTHOR]

In this paper, a novel algorithm of mining multidimensional association rules in relational database is proposed. First, design a particular structure including many indexes to save multidimensional itemsets, which makes time of finding itemsets decrease. Basing on statistic idea, the algorithm saves all frequent 1-itemsets and their support members at scanning the database for the first time. Frequent k-itemsets will be generated with no necessary to scan the database more times because of using these support members. Compared with some traditional algorithms of mining association rules, the algorithm presented in this paper has better executive efficiency and expansibility, which is proved in our experiments. [ABSTRACT FROM AUTHOR]

Wireless ad-hoc sensor networks have recently emerged as a premier research topic. They have great long-term economic potential, ability to transform our lives, and pose many new system-building challenges. One major challenge for its real deployment is its QoS issue. This is a rich area because sensor deaths and sensor replenishments make it difficult to specify the optimum number of sensors (this being the service quality that we address in this paper) that should be sending information at any given time. Through literature survey, we discover that current solution towards this problem remains some unreasonable assumptions in practice. So we proposed a new control schema allowing the control method to be more feasible in real environment. A distributed control schema is introduced in this paper. Every sensor node runs a control algorithm in a distributed fashion. This distributed QoS control schema can handle limitations exist in current QoS control methods. [ABSTRACT FROM AUTHOR]

This paper presents a contribution to automatic model building in quadratic polynomial environments, in the context of programming by human demonstration. A human operator moves a demonstration tool equipped with a probe, in contact with an unknown environment. The motion of the demonstration tool is sensed with a 3D camera, and the interaction with the environment is sensed with a force/torque sensor. Both measurements are uncertain, and do not give direct information about the different objects in the environment (such as cylinders, spheres, planes,...) and their geometric parameters. This paper uses a Bayesian Sequential Monte Carlo method or particle filter, to recognize the different discrete objects that form the environment, and simultaneously estimate the continuous geometric parameters of these different quadratic polynomial objects. The result is a complete geometric model of an environment, with different quadratic polynomial objects at its building blocks. The approach has been verified using real world experimental data, in which it is able to recognize three different unknown quadratic polynomial objects, and estimate their geometric parameters. [ABSTRACT FROM AUTHOR]

The paper presents T1R3-type fully-isotropic redundantly-actuated parallel manipulators (PMs) with four degrees of freedom. The mobile platform has one independent translation (T1) and three independent rotations (R3). A method is proposed for structural synthesis of fully-isotropic redundantly-actuated T1R3-type PMs based on the theory of linear transformations. A one-to-one correspondence exists between the actuated joint velocity space and the external velocity space of the moving platform. The Jacobian matrix mapping the two vector spaces of fully-isotropic T1R3- type PMs presented in this paper is 4×4 identity matrix throughout the entire workspace. The condition number and the determinant of the Jacobian matrix being equal to one, the manipulator performs very well with regard to force and motion transmission capabilities. Redundant actuation is used to obtain fully-isotropic solutions. As far as we are aware, this paper presents for the first time in the literature the use of redundancy to design fully-isotropic T1R3-type PMs. [ABSTRACT FROM AUTHOR]

This paper presents a contribution to programming by human demonstration, in the context of compliant motion task specification for sensor-controlled robot systems that physically interact with the environment. One wants to learn about the geometric parameters of the task and segment the total motion executed by the human into subtasks for the robot that can each be executed with simple compliant motion task specifications. The motion of the human demonstration tool is sensed with a 3D camera, and the interaction with the environment is sensed with a force sensor in the human demonstration tool. Both measurements are uncertain, and do not give direct information about the geometric parameters of the contacting surfaces, or about the contact formations encountered during the human demonstration. The paper uses a Bayesian Sequential Monte Carlo method (also known as a particle filter) to do the simultaneous estimation of the contact formation (discrete information) and the geometric parameters (continuous information). The simultaneous contact formation segmentation and the geometric parameter estimation are helped by the availability of a contact state graph of all possible contact formations. The presented approach applies to all compliant motion tasks involving polyhedral objects with a known geometry, where the uncertain geometric parameters are the poses of the objects. The approach has been verified in real world experiments, in which it is able to discriminate in realtime between 245 different contact formations of the contact state graph. [ABSTRACT FROM AUTHOR]

To realize weld defects detection and measure automation based on machine vision, such as dimension, shape, displacement and numbers in a given length (area), it's necessary to build a mathematic model for the imaging system. Precision of model directly affects precision of measurement for defects. In this paper, a model was built including some nonlinear factors, i.e. the input screen shape (spherical surface) of the x-ray image intensifier and the distortion of the image in CCD at small distance. A kind of reason why the electromagnetic distortion generates is given in this paper, too. [ABSTRACT FROM AUTHOR]

This paper explains the principle and method to calibrate the image plane center of the camera by use of laser in the pre-calibrate process of the intrinsic parameters of the visual sensor. The laser facula image has been disposed properly, so the accurate position has been located by calculating the center of mass. Consequently, the image plane center can be calibrated accurately. After the calibration, the guiding experiments show that the precision of the system is quite good which proves that camera calibrated by the method presented by this paper can satisfy the requirement of the whole system. [ABSTRACT FROM AUTHOR]

This paper designs a way to model on the complex welding robot system. With analyzing the characteristic of welding robot system, a fuzzy Petri net model is designed and analyzed. In order to get the performance of designed model, this paper proves the performance of model in theory. Results of model simulation experiment illustrate that the model can depicts welding robot system accurately and right. [ABSTRACT FROM AUTHOR]

Inspired by human's remarkable capability to perform a wide variety of physical and mental tasks without any measurements and computations and dissatisfied with classical logic as a tool for modeling human reasoning in an imprecise environment, Lotfi A. Zadeh developed the theory and foundation of fuzzy logic with his 1965 paper "Fuzzy Sets" [1] and extended his work with his 2005 paper "Toward a Generalized Theory of Uncertainty (GTU)—An Outline" [2]. Fuzzy logic has at least two main sources over the past century. The first of these sources was initiated by Peirce in the form what he called a logic of vagueness in 1900s, and the second source is Lotfi's A. Zadeh work, fuzzy sets and fuzzy Logic in the 1960s and 1970s. [ABSTRACT FROM AUTHOR]

This paper shows an agent based approach to solve the Tragedy of the Commons. This game is one of the well-known problems that involve sharing limited common resources. In this paper, to control the usage of common resources, we employ Levy Based Control Strategy and extend it with Autonomous Role Selection. In this approach, what levy plan of meta-agents should be used is very important to avoid the tragedy situation. Accordingly, we apply Genetic Algorithm (GA) to each agent to obtain evolutionally suitable levy plan. As a result, we show effectiveness of this approach and it depends on a fitness function of GA. Therefore, we examine the various fitness functions considered for a social balance and the importance of agents' role by simulations. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to present a novel way to formulate control problems with partial observations of stochastic systems. Themethod is based on stochastic realization theory. The contribution of the paper is the stochastic realization approach to stochastic control with partial observations. The motivation for the paper are the weaknesses of control with partial observations based on the separation principle. The separation property holds for the stochastic control problem with a Gaussian system and a quadratic cost function (LQG), but does not hold for at least one optimal stochastic control problem, LEQG, and may not hold for most other stochastic control problems. Moreover, control of decentralized stochastic systems or control of stochastic dynamic games becomes unsolvable or unnatural in the existing approaches in the literature. Therefore a novel approach may be explored. [ABSTRACT FROM AUTHOR]

This paper presents a method of detecting camera posture from endoscopic images. In epipolar geometry, the fundamental matrix provides some geometric information including translation and rotation of cameras. Although it is well known that DLT(Direct Linear Transform) algorithm can be an efficient method to calculate the matrix, it depends upon performance of matching points. The Levenberg-Marquardt algorithm which is robust for estimation with Gaussian noise can be a good method for this reason. In this paper, the distance between matched points and epipolar lines is defined and the fundamental matrix is accurately computed by the Levenberg- Marquardt algorithm using DLT algorithm to find the initial value. Also, good translation and rotation information can be obtained by decomposing the fundamental matrix. Experimental results show the improvement of the result of the fundamental matrix that result in improvement of the camera posture also. The detection of the pose of endoscope is important for compute added diagnosis in medical applications. [ABSTRACT FROM AUTHOR]

Obstructive Sleep Apnea (OSA) is a disease in which airways involuntarily collapse during sleep, leading to serious consequences. The current standard of diagnosis for OSA, polysomnography (PSG), requires that the patients spend one full day in a hospital, wired to a multitude of instruments. PSG is complicated, expensive, and unsuitable for mass screening of the population. Since OSA is commonly accompanied by snoring, the analysis of snoring sounds plays important role in the diagnosis of OSA. Conventional methods use the signal amplitude, power, pitch, zero-cross rate, etc. in the diagnosis. In this paper, we propose a new feature, which is the parameter vector of the autoregressive moving average (ARMA) process. Since the snoring signal is nonstationary, we propose to use Kalman smoother in the estimation of ARMA parameter vector. Simulation results show that the proposed method is robust to the variation of the input signal power as well as the setting of the analysis systems. [ABSTRACT FROM AUTHOR]

This paper presents a tracking method for an in vivo robotic capsule whose power is supplied from one of the multiple power transmission coils. The proposed method is aiming at selecting the best coupled one among the arrayed power transmission coils. It utilizes the fact that the driving current of the power transmitter is increased when the receiver coil inside the capsule is inductively coupled with the transmitter coil. By investigating the current increase characteristic according to its location relative to the transmission coils, we can draw the strategy on tracing the in vivo robotic capsules. This paper shows some promising results with two transmission coils and a two-dimensional power receiver. Experimental results gave the possibility of selecting the best coils by estimating the relative location of the capsule. [ABSTRACT FROM AUTHOR]

In this paper we propose a novel biological reasoning technique to find genetic palindrome using the resolution- based ATP (automated theorem proving) computing strategy. To retrieve the palindromic sequence, we apply automated deduction software with some resolution strategies to increase program performance. While the conventional reasoning or logic programming oriented method is basically top-down process, our method is bottom-up, resolution-based and also enhanced by direction and restriction reasoning strategies. Proposal method is divided into two steps. First, each element of sequence is represented as one state clause. Second, biological reasoning program resolve these states to retrieve palindrome motif from genetic sequence. Besides, to make this resolution process faster, we apply a reasoning strategy called resonance restriction. This resolution strategy blocks the biological reasoning by avoiding expression that do not mach the patterns set by researchers. This pattern is called "resonator" which is expressed by symbol patterns in automated reasoning. In our model, researcher assigns resonators to the gap between repeated regions which prevent his program from redundant search related non-symmetric parts of genetic sequence. Resonators restrict discovery process by discarding clauses generated around the gap between palindromic motifs, which enhance sharply the performance of reasoning program. In experiment, we translate whole genome sequence of Escherichia coli into clausal representation. Numerical results are presented about the retrieval of palindrome in Escherichia coli to valid the effectiveness of proposal technique. We validate that resonance restriction makes reasoning process faster with experimental output of generated clauses, CPU time. [ABSTRACT FROM AUTHOR]

This paper is devoted to discussion case-deletion methodologies of influence assessments in linear mixed models (LMM) for longitudinal data. The paper presents two case-deletion influence measures to detect the influential individuals in the context of LMM with unknown covariance structures. These two measures can be easily used to real data analysis. [ABSTRACT FROM AUTHOR]

In this paper, we propose an image identification system employing MPEG-7 as feature and using neural network as the main methodology. The proposed system properly identifies whether a given image belongs to particular sports images or not. The simulation results show that the proposed system successfully identifies images with the rate of over 85%. [ABSTRACT FROM AUTHOR]

Data association, one of the key and difficult problems for multi-target tracking, is the decision process of linking the measurements or the tracks deemed to be of common origin under certain criteria. All typical data association algorithms can be deducted into special Multidimensional Assignment Problem. However, present S-D assignment algorithm only associates the synchronous measurements from different sensors, which only generate the static result. In this paper, the static assignment algorithm(S-D) has been generalized to the dynamic Multidimensional Assignment Problem by means of combining the measurements set and the tracks set. The main challenge in the assignment problem is that it is NP-hard. The solution using Hopfield neural network (HNN) is presented in this paper. The simulation results illustrate that this method can decrease the computing burden greatly. [ABSTRACT FROM AUTHOR]

Classification rule mining is an important function of data mining, and is applied in many data analysis tasks. The classification rule mining algorithm based-on ant colony optimization (ACO) is researched in this paper. Some improvements are implemented based on existing research to enhance classification predictive accuracy and simplicity of rules. Multi-population parallel strategy is proposed, the cost-based discretization method is adopted, and parameters in the algorithm are adjusted step by step. With these improvements, performance of the algorithm is advanced, and classification predictive accuracy is enhanced. Finally, SIMiner, a self-development data mining software system based on swarm intelligence, is applied to experiment on six data sets taken from UCI Repository on Machine Learning. The results illuminate the algorithm proposed in this paper has better performance in predictive accuracy and simplicity of rules. [ABSTRACT FROM AUTHOR]

This paper proposes a fuzzy sliding mode controller with radial basis function neural network (RBFNN) for trajectory tracking of robot manipulator. The main problem of sliding mode controllers is that a whole knowledge of the system dynamics and system parameters is required to compute the equivalent control. In this paper, a RBFNN is proposed to compute the equivalent control. Computer simulations of three link robot manipulator for trajectory tracking indicate that the proposed method is a good candidate for trajectory control applications. [ABSTRACT FROM AUTHOR]

In this paper, discrete sliding mode controller (DSMC) with sliding-like condition is evaluated experimentally the robustness point of view. DSMC was modified to use a pseudo-sliding methodology and a variable sliding gain methodology. DSMC with a pseudo-sliding methodology and a variable sliding gain methodology perfectly eliminate a chattering problem and can control the system use a small control action. The usefulness of the designed DSMC in this paper is demonstrated by the control of an inverted pendulum system and the robustness of DSMC experimentally evaluated for model error. To provide a performance benchmark with respect to robustness, a direct comparison was made against linear quadratic control. [ABSTRACT FROM AUTHOR]

Review and analysis of continuous EEG recordings may be impeded by physiological artifacts such as blinks, eye movements, or cardiac activity. Many methods have been proposed to remove artifacts from EEG recordings, especially arising from eye movements and blinks. Often regression in the time or frequency domain is performed on EEG recordings to derive parameters characterizing the appearance and spread of eye artifacts in the EEG channels. Because EEG and ocular activity mix bidirectionally, regressing eye artifacts inevitably involves subtracting relevant EEG signals from each record as well. This paper presents noise can filter using an artificial neural network for removal of blink interference from EEG signals. The input to the neural network, used in this work, is not a raw sampled signal. We used a simple EEG model expressed by the sinusoidal waves with the Markov process amplitude as the training data of NN. This EEG model in both a frequency domain and a time domain can be applied to quantitatively express the features of the EEG. After training, input to the neural network EEG signals containing blink as the test data. Results of computer simulations indicate that blink artifact is eliminated by this method. Removing artifacts from EEG signal may aid the work of medical doctors, because artifacts disturb their attention. Removing artifacts is also important in analysis of EEG signal. It may be used as a preprocessing in diagnostic system. [ABSTRACT FROM AUTHOR]

This paper proposes a switched visual feedback control method for a micro helicopter under occlusions. Two stationary cameras are placed on the ground. They track four black balls attached to rods connected to the bottom of the helicopter. The control input is computed by using the errors between the positions of the tracked objects and pre-specified reference values for them. The multi-camera configuration enables us to design a switched controller which is robust against occlusions. The proposed controller selects a camera which correctly measures all of the tracked object positions at each time. If a camera loses a tracked object, then the camera searches for the four tracked objects by using an image data captured from the other camera. The proposed controller can keep the helicopter in a stable hover even when one of the cameras loses tracked objects due to occlusions. [ABSTRACT FROM AUTHOR]

Consider a large group of agents chasing a small group of moving targets. Assume each agent moves at constant speed toward the closest target. This paper studies the problem of controlling the agents indirectly by specifying the motion of the targets. In particular, it considers the problem of maintaining a minimum separation distance between each pair of agents, something that is impossible to do with only one target. This paper shows that only two targets are necessary to maintain separation between four agents. It also shows results in simulation to support the conjecture that only two targets are necessary to maintain separation between any number of agents, given suitable initial conditions. [ABSTRACT FROM AUTHOR]

Due to their compliance and high dexterity, biologically-inspired continuum robots have attracted much interest for applications such as medical surgery, urban search and rescue, de-mining etc. In this paper, we will present an application to medical surgery-colonoscopy by designing a pneumatic-driven flexible robotic manipulator, called ColoBot. The focus of this paper lies in the sensor-based guidance control of the ColoBot in a tubular, compliant and slippery environment of human colon. The kinematic model related the position and orientation of distal end of ColoBot to the actuator inputs is firstly developed and formulated for orientation control of ColoBot. For the autonomous guidance inside the colon, a method based on a circumscribed circle is utilized to calculate the real-time reference paths from the measurement of three sensors for orientation control of the Colobot. This proposed approach can be extended to the control of continuum robots in the conditions of a dynamically confined space. The experimental results on an emulation platform will be presented in order to validate the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper presents a hybrid formation controller approach for non-holonomic mobile robots. This approach is based on the stable switching between a leader-following formation controller and an orientation controller. The switching attempts to maintain low values of formation errors during specific leader movements that otherwise will produce a significant increment on such errors. Experimental results on commercial unicycle-like mobile robots are provided to show the feasibility and performance of the proposed control strategy. [ABSTRACT FROM AUTHOR]

In this paper, a new powerful technique, denoted as pack-based strategy is introduced in the context of statistical learning theory. This strategy allows us to derive bounds on the number of required samples that are manageable for "reasonable" values of probabilistic confidence and accuracy. Using this technique for feasibility and optimization problems involving Boolean expressions consisting of polynomials, we prove that the number of required samples grows with the accuracy parameter ε as $\frac{1}{\epsilon}\ln\,\frac{1}{\epsilon}$. This is a significant improvement when compared to the existing bounds which depend on $\frac{1}{\epsilon^2}\ln\,\frac{1}{\epsilon^2}$. We also apply this strategy to convex optimization problems. In this case, we show that the required sample size is inversely proportional to the accuracy for fixed confidence. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for motion planning in outdoor environments that takes into account specific characteristics of the terrain. Instead of decomposing the robot configuration space into "free" and "occupied", we consider the existence of several regions with different navigation costs. Costs are determined experimentally by navigating the robot through the regions and measuring the influence of the terrain on its motion. In this paper we measure the robot vertical acceleration, which reflects the terrain roughness. A path planning algorithm is used to determine a sequence of triangles that minimize the navigation cost. Robot control is accomplished by a piecewise continuous vector field that drives the robot through those regions. This vector field allows the robot velocity to change according to the characteristics of the terrain. Experimental results with a differential driven, all terrain mobile robot illustrate the proposed approach. [ABSTRACT FROM AUTHOR]

We provide a comprehensive and updated survey on applications of Kohonen's self-organizing map (SOM) to time series prediction (TSP). The main goal of the paper is to show that, despite being originally designed as an unsupervised learning algorithm, the SOM is flexible enough to give rise to a number of efficient supervised neural architectures devoted to TSP tasks. For each SOM-based architecture to be presented, we report its algorithm implementation in detail. Similarities and differences of such SOM-based TSP models with respect to standard linear and nonlinear TSP techniques are also highlighted. We conclude the paper with indications of possible directions for further research on this field. [ABSTRACT FROM AUTHOR]

Fuzzy classification is one of the most important applications of fuzzy logic. Its goal is to find a set of fuzzy rules which describe classification problems. Most of the existing fuzzy rule induction methods (e.g., the fuzzy decision trees induction method) focus on searching rules consisting of t-norms (i.e., AND) only, but not t-conorms (OR) explicitly. This may lead to the omission of generating important rules which involve t-conorms explicitly. This paper proposes a type of tree termed pattern trees which make use of different aggregations including both t-norms and t-conorms. Like decision trees, pattern trees are an effective machine learning tool for classification applications. This paper discusses the difference between decision trees and pattern trees, and also shows that the subsethood based method (SBM) and the weighted subsethood based method (WSBM) are two specific cases of pattern trees, with each having a fixed pattern tree structure. A novel pattern tree induction method is proposed. The comparison to other classification methods including SBM, WSBM and fuzzy decision tree induction over datasets obtained from UCI dataset repository shows that pattern trees can obtain higher accuracy rates in classifications. In addition, pattern trees are capable of generating classifiers with good generality, while decision trees can easily fall into the trap of over-fitting. According to two different configurations, simple pattern trees and pattern trees have been distinguished. The former not only produce high prediction accuracy, but also preserve compact tree structures, while the latter can produce even better accuracy, but as a compromise produce more complex tree structures. Subject to the particular demands (comprehensibility or performance), simple pattern trees and pattern trees provide an effective methodology for real world applications. Weighted pattern trees have been proposed in which certain weights are assigned to different trees, to reflect the nature that different trees may have different confidences. The experiments on British Telecom (BT) customer satisfaction dataset show that weighted pattern trees can slightly outperform pattern trees, and both are slightly better than fuzzy decision trees in terms of prediction accuracy. In addition, the experiments show that both weighted and unweighted pattern trees are robust to over-fitting. Finally, a limitation of pattern trees as revealed via BT dataset analysis is discussed and the research direction is outlined. [ABSTRACT FROM AUTHOR]

This paper introduces a mathematical model of a hint as a body of imprecise and uncertain information. Hints are used to judge hypotheses: the degree to which a hint supports a hypothesis and the degree to which a hypothesis appears as plausible in the light of a hint are defined. This leads in turn to support- and plausibility functions. Those functions are characterized as set functions which are normalized and monotone or alternating of order ∞. This relates the present work to G. Shafer's mathematical theory of evidence. However, whereas Shafer starts out with an axiomatic definition of belief functions, the notion of a hint is considered here as the basic element of the theory. It is shown that a hint contains more information than is conveyed by its support function alone. Also hints allow for a straightforward and logical derivation of Dempster's rule for combining independent and dependent bodies of information. This paper presents the mathematical theory of evidence for general, infinite frames of discernment from the point of view of a theory of hints. [ABSTRACT FROM AUTHOR]

Scan technology increases the switching activity well beyond that of the functional operation of an IC. In this paper, we first discuss the issues of excessive peak power during scan testing and highlight the importance of reducing peak power particularly during the test cycle (i.e. between launch and capture) so as to avoid noise phenomena such as IR-drop or Ground Bounce. Next, we propose a scan cell reordering solution to minimize peak power during all test cycles of a scan testing process. The problem of scan cell reordering is formulated as a constrained global optimization problem and is solved by using a simulated annealing algorithm. Experimental evidence and practical implications of the proposed solution are given at the end of the paper. For ISCAS'89 and ITC'99 benchmark circuits, this approach reduces peak power during TC up to 51% compared to an ordering provided by an industrial synthesis tool. Fault coverage and test time are left unchanged by the proposed solution. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to propose a design technique for improving the resistance of the Quasi Delay Insensitive (QDI) Asynchronous logic against Differential Power Analysis Attacks. This countermeasure exploits the properties of the QDI circuit acknowledgement signals to introduce temporal variations so as to randomly desynchronize the data processing times. The efficiency of the countermeasure, in terms of DPA resistance, is formally presented and analyzed. Electrical simulations performed on a DES crypto-processor confirm the relevancy of the approach, showing a drastic reduction of the DPA peaks, thus increasing the complexity of a DPA attack on QDI asynchronous circuits. [ABSTRACT FROM AUTHOR]

This paper describes the high-level system modeling and functional verification of a novel 3D vertically integrated Adaptive Computing Systemon- Chip (ACSoC), which we term 3D-SoftChip. The 3D-SoftChip comprises two vertically integrated chips (a Configurable Array Processor and an Intelligent Configurable Switch) through an Indium Bump Interconnection Array (IBIA). This paper also describes an advanced HW/SW co-design and verification methodology using SystemC, which has been used to verify the functionality of the system and to allow architectural exploration in the early design stage. An implementation of the MPEG-4 full search block matching motion estimation algorithm has been applied to demonstrate the architectural superiority of the proposed novel 3D-ACSoC. [ABSTRACT FROM AUTHOR]

Quasi delay insensitive circuits are functionally independent of delays in gates and wires (except for some particular wires). Such asynchronous circuits offer high robustness but do not perform well to automatically synthesize and optimize. This paper presents a new methodology to model and synthesize data path QDI circuits. The model used to represent circuits is based on Multi-valued Decision Diagrams and allows obtaining QDI circuits with two-input gates. Optimization is achieved by applying a technology mapping algorithm with a library of asynchronous standard cells called TAL. This work is a part of the back-end of our synthesis flow from high level language. Throughout the paper, a digit-slice radix 4 ALU is used as an example to illustrate the methodology and show the results. [ABSTRACT FROM AUTHOR]

This paper presents performance comparisons between two multipliers architectures. The first architecture consists of a pure array multiplier that was modified to handle the sign bits in 2's complement and uses a radix-4 encoding to reduce the partial product lines. The second architecture implemented was the widely used Modified Booth multiplier. We describe a design methodology to physically implement these architectures in a pipelined and non-pipelined form, obtaining area, power consumption and delay results. Up to now only results at the logic level were presented in previous work. The performance of pipelined array architecture is compared with the pipelined Modified Booth. We compare the physical implementations in terms of area, power and delay. The results show that the new pipelined array multiplier can be significantly more efficient, with close to 16% power savings and 55% power savings when considering non-pipelined architectures. [ABSTRACT FROM AUTHOR]

This paper introduces some intelligent control strategies for marine craft. By looking at some existing problems in this area, e.g. the uncertainties and nonlinearities in ship dynamic model and time delay in ship actuator system, three types of control strategies are studied, namely, robust PID control for ship steering, adaptive fuzzy robust tracking control (AFRTC) for ship steering, and adaptive fuzzy Hinf control for ship roll stabilization. The effectiveness of the three control strategies are demonstrated by ship simulation. This paper is dedicated to the memory of Professor YS Yang for his pioneer work on robust adaptive fuzzy control of marine craft. [ABSTRACT FROM AUTHOR]