Browsing by Author "Chen, JL"

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2-D discrete signal interpolation and its image resampling application using fuzzy rule-based inference
(2000-09-01)
Chen, JL
;
Chang, JY
;
Shieh, KL
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper describes an interpolation algorithm for two-dimensional (2-D) discrete signals using fuzzy rule-based inference. The original signal is estimated by the main-surface function in the interpolation region, and four sub-plane functions surrounding the interpolation region. The main-surface is a bilinearly interpolated function passing through four signal samples in the interpolation region and the four sub-planes reflect the tendencies of pixels from the left, right, up, and down of the interpolation region. Drawing fuzzy inferences about signals from these five functions, we can estimate original signals very well even when the signals are buried in noise. We verified the method by computer simulations of some assumed 2-D signals and by resampling of the actual image data. (C) 2000 Elsevier Science B.V. All rights reserved.
A concurrent 0.18-mu m CMOS self-biased dual-band driver amplifier for IEEE 802.11 a/b/g
(2004)
Jou, CF
;
Cheng, KH
;
Chen, JL
;
傳播研究所
;
Institute of Communication Studies
A 2.4 GHz / 5.2 GHz self-biased dual band CMOS driver amplifier with a 9.8-dBm output power using TSMC 0.18-mu m IP6M standard CMOS process is described. The CMOS amplifier designed on Rogers R04003 printed-circuit-board (PCB) with a single input and a single output signal chain is simultaneously optimized for wireless local area network (WLAN) 2.4 GHz / 5.2 GHz applications. Simulation results show that the driver amplifier exhibits an Output power about 9.7-dBm in both 2.4 GHz and 5.2 GHz, output interception point (OIP3) of 24dBm with power added efficiency (PAE) = 27% and PAE =24% in 2.4GHz and 5.2 GHz, respectively. The die size is 0.85x0.7 mm(2).
An efficient algorithm for form structure extraction using strip projection
(1998-09-01)
Chen, JL
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Lee, HJ
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資訊工程學系
;
Department of Computer Science
This paper presents an efficient strip-projection-based approach to extracting form structures from form documents for office automation. To locate the data, we have to extract and interpret the form structure. In this paper, a strip projection method is presented for extracting the form structure. We first segment input form images into uniform vertical and horizontal strips. Since most form lines are vertical or horizontal, we project the image of each vertical strip horizontally and that of each horizontal strip vertically. The peak positions in these projection profiles denote possible locations of lines in form images. We then extract the lines starting with the possible line positions in the source image. After all lines have been extracted, redundant lines are removed using a line-verification algorithm and broken lines are linked using a line-merging algorithm. Experimental results show that the proposed method can extract form structures from A4-sized documents in about 3 seconds which is very efficient, compared with the methods based on Hough transformation and run-based line-detection algorithms. (C) 1998 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
An inheritance flow model for class hierarchy analysis
(1998-06-30)
Chen, JL
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Wang, FJ
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資訊工程學系
;
Department of Computer Science
This paper presents an inheritance flow model, which represents the inheritance relationships among classes as a flow graph. A flow operation is associated with each attribute and method in a class to denote the defined (redefined) or inherited member. An inherited member can be deemed as being handled by a sequence of how operations along a path in the flow graph. This model provides several analyses in a class hierarchy, such as implicit inherited member and polymorphic method invocation. These analyses may be applied in various fields of software engineering, such as static analysis, maintenance, and complexity measurement. (C) 1998 Elsevier Science B.V. All rights reserved.
An object-oriented dependency graph for program slicing
(1998)
Chen, JL
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Wang, FJ
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Chen, YL
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資訊工程學系
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Department of Computer Science
Program dependency graphs (PDG's) of a program facilitate program analysis and related applications such as program slicing, a method to identify the relevant entities of the program according to data and control dependencies. In the past, PDG's and program slicing were most developed for (conventional) imperative programs. Recently, the object-oriented (OO) paradigm gained momentum and popularity. The OO paradigm introduces the features of object abstraction, encapsulation, inheritance, and polymorphism to programs, but is not considered in PDG's and program slicing. In this paper, we present an Object-Oriented Dependency Graph (ODG) to represent the structure of OO programs. The ODG is defined based on a property multi-digraph that is extended from a directed graph by augmenting multiple edge types, vertex properties, and property relations. With the extension, the ODG cart avoid the specious dependencies due to object encapsulation. Based on the ODC, a program slicing method for OO software is developed. Besides data and control dependencies, dependencies caused by OO features are taken into consideration in our slicing method. Through the ODG, the slicing method might be applied to facilitate understanding debugging, and maintaining OO software as well as traditional program slicing methods do.
Applying fuzzy logic in the modified single-layer perceptron image segmentation network
(2000-03-01)
Chang, JY
;
Chen, JL
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電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper, we propose a fuzzy-logic-based modified single layer perceptron (MSLP) image segmentation network for object extraction. We select a sigmoid gray level transfer function with the aid of the input image histogram and map the input gray levels into the interval [0,1]. Then we adopt the linear index of fuzziness of the output nodes as the error function of the image segmentation system to incorporate the learning capability of a neural network. Our scheme can successfully extract objects from the background. To further enhance the capability of the segmentation system, the proposed network is incorporated with fuzzy if-then rules to adaptively adjust the threshold of the activation function of the MSLP output neuron for best matching the local characteristics of the image. Fuzzy if-then rules involving the edge intensities and vertical positions of pixels are reasoned to determine the threshold adaptively. From the results of segmenting forward looking infrared (FLIR) images, better segmentation images have been obtained by incorporating fuzzy if-then rules with the MSLP segmentation technique. As demonstrated by this study, it is promising and worthy of study that incorporating human knowledge in terms of Fuzzy rules into a designed numerical algorithm can further improve performance, not only in the segmentation problem we present.
Automated facial expression recognition system using neural networks
(2001-05-01)
Chang, JY
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Chen, JL
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電控工程研究所
;
Institute of Electrical and Control Engineering
This paper proposes an automated facial expression recognition system using neural network classifiers. First, we use the rough contour. estimation routine, mathematical morphology, and point contour detection method to extract the precise contours of the eyebrows, eyes, and mouth of a face image. Then we define 30 facial characteristic points to describe the position and shape of these three facial features. Facial expressions can be described by combining different action units, which are specified by the basic muscle movements of a human face. We choose six main action units, composed of facial characteristic point movements, as the input vectors of two different neural network-based expression classifiers including a radial basis function network and a multilayer perceptron network. Using these two networks, we have obtained recognition rates as high as 92.1 % in categorizing the facial expressions neutral, anger, or happiness. Simulation results by the computer demonstrate that computers are capable of extracting high-level or abstract information like humans.
Bearing contact analysis of the involute spur planetary gear train
(2001)
Chen, JL
;
Tseng, CH
;
Tsay, CB
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機械工程學系
;
Department of Mechanical Engineering
The goal of this study is to determine the dimensions and orientations of instant contact ellipses of gear surfaces in the meshing of the planetary gear train in order to recommend the proper amount of the crowning radii. The mathematical model for the surface profiles of the simple planetary gear train with the crowned planet gear is developed to simulate gear-meshing conditions and obtain the contact points. Principal curvatures and directions of the planetary gear train are derived and investigated based on the theory of gearing. The dimensions and orientations of the contact ellipses of the planetary gear train due to the assembly errors of different kinds of axial misalignments in different crowning radii can further be developed from the principal curvatures and directions of gear surfaces. Examples are presented to illustrate the above-mentioned investigations.
Chinese handwritten character segmentation in form documents
(1999)
Chen, JL
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Wu, CH
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Lee, HJ
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資訊工程學系
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Department of Computer Science
This paper presents a projection based method for segmenting handwritten Chinese characters in form documents with known structures. In the preprocessing phase, a noise removal method is proposed that preserves stroke connections and character edge points. In the character segmentation phase, the projection profile analysis method is used to segment a text line image into projection blocks. In addition, projection blocks are classified into one of four types: mark, half-word, single-word, and two-word. Large blocks are then split and small blocks are merged. In addition, an OCR system is adopted to eliminate errors resulting from the inappropriate merging of Chinese numerical characters with other characters. As for 1319 Chinese characters are tested during our experiments, the correct segmentation rates of 92.34% and 91.76% are obtained with and without the OCR module.
Classifier-augmented median filters for image restoration
(2004-04-01)
Chang, JY
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Chen, JL
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電控工程研究所
;
Institute of Electrical and Control Engineering
Developed in this paper is a new approach that augments a fuzzy classifier to determine whether or not the operating pixel, centered in the sliding window, should be involved with the impulse noise filtering process. Owing to the inclusion of the fuzzy K-nearest neighbor (K-NN) scheme, any central operating pixel that is not noise corrupted can be effectively detected and then left unchanged. Thus, the unnecessary pixel replacement can be avoided and the details and signal structure of the image will be best retained. If the center point is found to be noise corrupted, the proposed classifier-augmented median filter facilitates the filtering action only on a subset of pixels, which are not noise contaminated in the window. Due to this impulse pixel exclusion, the biased estimation caused from impulses can be eliminated and, thus, obtains a better estimation of the center pixel. Experimental results showed that this new approach largely outperformed several existing schemes for image noise removal.
Design considerations for assembly in planetary gear trains
(2000)
Chen, JL
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Tseng, CH
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機械工程學系
;
Department of Mechanical Engineering
Relative phase angles between planetary gears in the multi-stage planetary gear trains are the important design consideration for assembling. Different gear sizes require different relative phase angles. This study investigated the design considerations for planetary gear trains for assembling, especially for planetary gear sets. Two methods for determining the relative phase angles for single-stage and multiple-stage planetary gear trains with evenly spaced planetary gears are proposed. Numerical examples are used to demonstrate these methods.
Determination of 1-hydroxypyrene in children urine using column-switching liquid chromatography and fluorescence detection
(2004-06-15)
Kuo, CT
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Chen, HW
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Chen, JL
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環境工程研究所
;
Institute of Environmental Engineering
This study developed an acid hydrolysis method instead of using enzyme extraction, equipped with column-switching system for the pretreatment of samples, in the determination of 1-hydroxypyrene in the urine from children and pyrene in airborne particulates. We collected both types of samples from areas near a petrochemical industry and rural areas as reference. Samples were first treated with acid hydrolysis and followed by solvent extraction prior to being injected into the separation system for the determination with high performance liquid chromatography and fluorescence. A column-switching system was on-line with a C-18 separation column to remove matrix interference and obtain a stable baseline of the chromatogram. The eluent used to separate the 1-hydroxypyrene was 60% (v/v) aqueous acetonitrile solution. A fluorescence detector was used to monitor 1-hydroxypyrene at lambda(ex) = 348 nm and lambda(em) = 388nm, and pyrene at lambda(ex) = 331 nm and lambda(em) = 390 nm. Both calibration graphs were linear with very good correlation coefficients (r > 0.999) and the detection limits were ca. 2 pg (5 ng/l). Results showed that there was a significant association between 1-hydroxypyrene levels in urine specimens and pyrene levels in airborne particulate samples (r = 0.68, P < 0.05). The average levels of pyrene in the particulates (0.18 versus 0.09 ng/m(3)) and of 1-hydroxypyrene in urine specimens (155.9 versus 110.2 ng/g creatinine) were higher for the petrochemical area than for the rural area. This method is stable and sensitive for measuring polycyclic aromatic hydrocarbons in environmental samples. (C) 2003 Elsevier B.V. All rights reserved.
Dual band CMOS power amplifier for WLAN applications
(2003)
Jou, CF
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Cheng, KH
;
Lin, CM
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Chen, JL
;
傳播研究所
A 2.4 GHz / 5.2 GHz dual band CMOS power amplifier (PA) with a 21-dBm output power using 0.25 - mu m 1P5M standard CMOs process is described. In this paper, we present a CMOs PA with a single input and a single output signal chain which simultaneously optimized for wireless local area network (WLAN) 2.4 GHz / 5.2 GHz applications designed on Rogers RO4003 printed-circuit-board (PCB). The simulated dual-band PA biased at Class-A exhibiting P-1dB = 21dBm in both 2.4 GHz and 5.2 GHz with power added efficiency (PAE) = 26% and PAE = 18% separately. The performances of the designed PA presents the standard CMOs process has the potential for the PAs of 2.4 GHz / 5.2 GHz WLAN applications.
Encapsulation in object-oriented programs
(1996-07-01)
Chen, JL
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Wang, FJ
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交大名義發表
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資訊科學與工程研究所
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National Chiao Tung University
Epoxy-polycarbonate blends catalyzed by a tertiary amine .1. Mechanism of transesterification and cyclization
(1996-01-15)
Li, MS
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Ma, CCM
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Chen, JL
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Lin, ML
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Chang, FC
In the Bisphenol A base polycarbonate-Bisphenol A base epoxy blend system, the carbonate group can react with epoxide in the presence of a tertiary amine. The transesterification reactions convert the original aromatic/aromatic carbonate of PC to aromatic/aliphatic and aliphatic/aliphatic carbonates. IR spectroscopy shows an unknown major structure formed during the later stages of the transesterification reaction. The unknown structure was investigated by a model reaction using diphenyl carbonate and phenyl glycidyl ether leading to the formation of 4-(phenoxymethyl)-1,3-dioxolan-2-one (PMD), which has been identified by IR, UV, H-1 NMR, C-13 NMR, and mass spectroscopy. The mechanism of forming the cyclic carbonate is proposed to proceed through a zwitterion and a nucleophile attack of the aromatic/aliphatic or the aliphatic/aliphatic carbonate group.
Field data extraction for form document processing using a gravitation-based algorithm
(2001-09-01)
Chen, JL
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Lee, HJ
;
資訊工程學系
;
Department of Computer Science
This paper presents a novel approach to grouping Chinese handwritten field data filled in form documents using a gravitation-based algorithm. An algorithm is developed to extract handwritten field data which may be written out of form fields. First, form lines are extracted and removed from input form images. Connected-components are then detected from remaining data, and the gravitation for each connected-component is computed by using the black pixel counts as their mass. Next, we move connected-components according to their gravitation. As generally known, filled-in data have the locality property, i.e., data of the same field are normally written in a local area consecutively. Therefore, the relationship of these connected-components can be determined by this property. Repeatedly moving these connected-components according to their neighbor components allows us to determine which connected-components should be extracted for a particular field. Experimental results demonstrate the effectiveness of the proposed method in grouping field data, (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
Field-data grouping for form document processing using a gravitation-based algorithm
(1998)
Chen, JL
;
Lee, HJ
;
資訊工程學系
;
Department of Computer Science
This paper presents a novel approach tc, grouping Chinese handwritten field-data of form documents using a gravitation-based algorithm. We develop an algorithm to extract handwritten field data which may be written out of the fields. We first extract and remove form lines for input form images. Next, we detect connected-components from remaining data, and compute the gravitation for each connected-component by using the black pixel counts as their mass. Then, we move connected-components to their field center according to their gravitation, since filled-in data have the locality property, that is, data of the same field are usually written in a local area consecutively. After moving these connected-components for a certain times, we can assign most components to the fields they should be. Thus, we can determine which connected-components should be extracted for a particular field. Experimental results show that this proposed method can group field-data effectively.
Flow analysis of class relationships for object-oriented programs
(2000-07-01)
Chen, JL
;
Wang, FJ
;
資訊工程學系
;
Department of Computer Science
Program analysis techniques have been widely applied in various fields of software engineering, such as debugging, testing, and proof of simple correctness properties. In object-oriented (OO) programs, inheritance, association, and aggregation relationships may introduce complicated dependencies concealed within classes that might obstruct program analysis. This paper proposes a class relationship flow models to provide analysis for inheritance, association, and aggregation of class relationships. The flow model consists of three flows, inheritance, association, and aggregation flows, corresponding to these relationships. A sequence of class relationships is represented as a flow path from one class to another. Along a flow path, each member within a class is associated with an operation, define or use, to represent whether its status is changed or referenced. Thereby, the concealed dependencies introduced by class relationships can be analyzed according to the flow operations. The analysis might be used as a technique for program understanding, anomaly detection, and program testing.
Fuzzy perceptron learning and its application to classifiers with numerical data and linguistic knowledge
(1995)
Chen, JL
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Chang, JY
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電控工程研究所
;
Institute of Electrical and Control Engineering
Fuzzy perceptron neural networks for classifiers with numerical data and linguistic rules as inputs
(2000-12-01)
Chen, JL
;
Chang, JY
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents a novel learning algorithm of fuzzy perceptron neural networks (FPNNs) for classifiers that utilize expert knowledge represented by fuzzy IF-THEN rules as well as numerical data as inputs. The conventional linear perceptron network is extended to a second-order one, which is much more flexible for defining a discriminant function. In order to handle fuzzy numbers in neural networks, level sets of fuzzy input vectors are incorporated into perceptron neural learning, At different levels of the input fuzzy numbers, updating the weight vector depends on the minimum of the output of the fuzzy perceptron neural network and the corresponding nonfuzzy target output that indicates the correct class of the fuzzy input vector, This minimum is computed efficiently by employing the modified vertex method to lessen the computational load and the training time required. Moreover, the; pocket algorithm, called fuzzy pocket algorithm, is introduced into our fuzzy perceptron learning scheme to solve the nonseparable problems, Simulation results demonstrate the effectiveness of the proposed FPNN model.