• Title/Summary/Keyword: Convergence pattern

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Organic thin-film transistors and transistor diodes with transfer-printed Au electrodes

  • Cho, Hyun-Duck;Lee, Min-Jung;Yoon, Hyun-Sik;Char, Kook-Heon;Kim, Yeon-Sang;Lee, Chang-Hee
    • 한국정보디스플레이학회:학술대회논문집
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    • 2009.10a
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    • pp.1122-1124
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    • 2009
  • Organic thin-film transistors (OTFTs) were fabricated by using the transfer patterning method. In order to remove Au pattern easily, UV-curable polymer mold was surface treated. Au source/drain (S/D) pattern was transferred to insulator-coated substrate surface. Fabricated OTFTs were compared to OTFTs using vacuum-deposited Au S/D. Additionally, transistor diodes were characterized.

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A Design of Parallel Module Neural Network for Robot Manipulators having a fast Learning Speed (빠른 학습 속도를 갖는 로보트 매니퓰레이터의 병렬 모듈 신경제어기 설계)

  • 김정도;이택종
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.9
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    • pp.1137-1153
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    • 1995
  • It is not yet possible to solve the optimal number of neurons in hidden layer at neural networks. However, it has been proposed and proved by experiments that there is a limit in increasing the number of neuron in hidden layer, because too much incrememt will cause instability,local minima and large error. This paper proposes a module neural controller with pattern recognition ability to solve the above trade-off problems and to obtain fast learning convergence speed. The proposed neural controller is composed of several module having Multi-layer Perrceptron(MLP). Each module have the less neurons in hidden layer, because it learns only input patterns having a similar learning directions. Experiments with six joint robot manipulator have shown the effectiveness and the feasibility of the proposed the parallel module neural controller with pattern recognition perceptron.

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Roll-to-Roll (R2R) Fabrication of Micro Pillar Array for Biomimetic Functionalization of Surface

  • Jeon, Deok-Jin;Lee, Jun-Young;Yeo, Jong-Souk
    • Applied Science and Convergence Technology
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    • v.23 no.1
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    • pp.54-59
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    • 2014
  • The roll-to-roll (R2R) fabrication method to make micro-scale pillar arrays for biomimetic functionalization of surfaces is presented. Inspired by the micro-structure of plants in nature, a surface with a synthetic micro-scale pillar array is fabricated via maskless photolithography. After the surface is SAM (self-assembled monolayer) coated with trichlorosilane in a vacuum desiccator, it displays a hydrophobic property even in R2R replicas of original substrate, whose properties are further characterized using various pitches and diameters. In order to perform a comparison between the original micro-pattern and its replicas, surface morphology was analyzed using scanning electron microscopy and wetting characteristics were measured via a contact angle measurement tool with a $10{\mu}L$ water droplet. Efficient roll-to-roll imprinting for a biomimetic functionalized surface has the potential for use in many fields ranging from water repelling and self-cleaning to microfluidic chips.

A Study on the Fractal Attractor Creation and Analysis of the Printed Korean Characters

  • Shon, Young-Woo
    • Journal of information and communication convergence engineering
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    • v.1 no.1
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    • pp.53-57
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    • 2003
  • Chaos theory is a study researching the irregular, unpredictable behavior of deterministic and non-linear dynamical system. The interpretation using Chaos makes us evaluate characteristic existing in status space of system by tine series, so that the extraction of Chaos characteristic understanding and those characteristics enables us to do high precision interpretation. Therefore, This paper propose the new method which is adopted in extracting character features and recognizing characters using the Chaos Theory. Firstly, it gets features of mesh feature, projection feature and cross distance feature from input character images. And their feature is converted into time series data. Then using the modified Henon system suggested in this paper, it gets last features of character image after calculating Box-counting dimension, Natural Measure, information bit and information dimension which are meant fractal dimension. Finally, character recognition is performed by statistically finding out the each information bit showing the minimum difference against the normalized pattern database. An experimental result shows 99% character classification rates for 2,350 Korean characters (Hangul) using proposed method in this paper.

Humidity Induced Defect Generation and Its Control during Organic Bottom Anti-reflective Coating in the Photo Lithography Process of Semiconductors

  • Mun, Seong-Yeol;Kang, Seong-Jun;Joung, Yang-Hee
    • Journal of information and communication convergence engineering
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    • v.10 no.3
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    • pp.295-299
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    • 2012
  • Defect generation during organic bottom anti-reflective coating (BARC) in the photo lithography process is closely related to humidity control in the BARC coating unit. Defects are related to the water component due to the humidity and act as a blocking material for the etching process, resulting in an extreme pattern bridging in the subsequent BARC etching process of the poly etch step. In this paper, the lower limit for the humidity that should be stringently controlled for to prevent defect generation during BARC coating is proposed. Various images of defects are inspected using various inspection tools utilizing optical and electron beams. The mechanism for defect generation only in the specific BARC coating step is analyzed and explained. The BARC defect-induced gate pattern bridging mechanism in the lithography process is also well explained in this paper.

A High-Frequency Signal Test Method for Embedded CMOS Op-amps

  • Kim Kang Chul;Han Seok Bung
    • Journal of information and communication convergence engineering
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    • v.3 no.1
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    • pp.28-32
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    • 2005
  • In this paper, we propose a novel test method to effectively detect hard and soft faults in CMOS 2-stage op-amps. The proposed method uses a very high frequency sinusoidal signal that exceeds unit gain bandwidth to maximize the fault effects. Since the proposed test method doesn't require any complex algorithms to generate the test pattern and uses only a single test pattern to detect all target faults, therefore test costs can be much reduced. The area overhead is also very small because the CUT is converted to a unit gain amplifier. Using HSPICE simulation, the results indicated a high degree of fault coverage for hard and soft faults in CMOS 2-stage op-amps. To verify this proposed method, we fabricated a CMOS op-amp that contained various short and open faults through the Hyundai 0.65-um 2-poly 2-metal CMOS process. Experimental results for the fabricated chip have shown that the proposed test method can effectively detect hard and soft faults in CMOS op-amps.

Query Processing based Branch Node Stream for XML Message Broker

  • Ko, Hye-Kyeong
    • International journal of advanced smart convergence
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    • v.10 no.2
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    • pp.64-72
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    • 2021
  • XML message brokers have a lot of importance because XML has become a practical standard for data exchange in many applications. Message brokers covered in this document store many users. This paper is a study of the processing of twig pattern queries in XML documents using branching node streams in XML message broker structures. This work is about query processing in XML documents, especially for query processing with XML twig patterns in the XML message broker structure and proposed a method to reduce query processing time when parsing documents with XML twig patterns by processing information. In this paper, the twig pattern query processing method of documents using the branching node stream removes the twigging value of the branch node that does not include the labeling value of the branch node stream when it receives a twig query from the client. In this paper, the leaf node discovery time can be reduced by reducing the navigation time of nodes in XML documents that are matched to leaf nodes in twig queries for client twig queries. Overall, the overall processing time to respond to queries is reduced, allowing for rapid question-answer processing.

Topology Optimization of Reinforcement Pattern for Pressure-Explosion Proof Enclosure Door in Semiconductor Manufacturing Process (위상최적화 기법을 이용한 반도체 공정용 압력방폭형 외함 도어의 보강 패턴 최적화)

  • Yeong Sang Kim;Dong Seok Shin;Euy Sik Jeon
    • Journal of the Semiconductor & Display Technology
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    • v.22 no.2
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    • pp.56-63
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    • 2023
  • This paper presents a method using finite element analysis and topology optimization to address the issue of overdesign in pressure-explosion proof enclosure doors for semiconductor manufacturing processes. The design conducted in this paper focuses on the pattern design of the enclosure door and its fixation components. The process consists of a solid-filled model, a topology optimization model, and a post-processing model. By applying environmental conditions to each model and comparing the maximum displacement, maximum equivalent stress, and weight values, it was confirmed that a reduction of about 13% in weight is achievable.

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Scale Invariant Auto-context for Object Segmentation and Labeling

  • Ji, Hongwei;He, Jiangping;Yang, Xin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.8
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    • pp.2881-2894
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    • 2014
  • In complicated environment, context information plays an important role in image segmentation/labeling. The recently proposed auto-context algorithm is one of the effective context-based methods. However, the standard auto-context approach samples the context locations utilizing a fixed radius sequence, which is sensitive to large scale-change of objects. In this paper, we present a scale invariant auto-context (SIAC) algorithm which is an improved version of the auto-context algorithm. In order to achieve scale-invariance, we try to approximate the optimal scale for the image in an iterative way and adopt the corresponding optimal radius sequence for context location sampling, both in training and testing. In each iteration of the proposed SIAC algorithm, we use the current classification map to estimate the image scale, and the corresponding radius sequence is then used for choosing context locations. The algorithm iteratively updates the classification maps, as well as the image scales, until convergence. We demonstrate the SIAC algorithm on several image segmentation/labeling tasks. The results demonstrate improvement over the standard auto-context algorithm when large scale-change of objects exists.

Wind Power Pattern Forecasting Based on Projected Clustering and Classification Methods

  • Lee, Heon Gyu;Piao, Minghao;Shin, Yong Ho
    • ETRI Journal
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    • v.37 no.2
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    • pp.283-294
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    • 2015
  • A model that precisely forecasts how much wind power is generated is critical for making decisions on power generation and infrastructure updates. Existing studies have estimated wind power from wind speed using forecasting models such as ANFIS, SMO, k-NN, and ANN. This study applies a projected clustering technique to identify wind power patterns of wind turbines; profiles the resulting characteristics; and defines hourly and daily power patterns using wind power data collected over a year-long period. A wind power pattern prediction stage uses a time interval feature that is essential for producing representative patterns through a projected clustering technique along with the existing temperature and wind direction from the classifier input. During this stage, this feature is applied to the wind speed, which is the most significant input of a forecasting model. As the test results show, nine hourly power patterns and seven daily power patterns are produced with respect to the Korean wind turbines used in this study. As a result of forecasting the hourly and daily power patterns using the temperature, wind direction, and time interval features for the wind speed, the ANFIS and SMO models show an excellent performance.