• Title/Summary/Keyword: Automate

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Development of a Tool to Automate One-Dimensional Finite Element Analysis of Machine Tool Spindles

  • Choi, Jin-Woo
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.24 no.2
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    • pp.172-176
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    • 2015
  • In this research, a tool was developed to automate one-dimensional finite element analysis (1D FEA) for design of a machine tool spindle. Based on object-oriented programing, this tool employs the objects of a CAD system to construct a geometric model and then to convert it into the FE model of 1D beams at the workbenches of the CAD system with minimum data to define the spindle such as bearing positions and cross-sections of the shaft. Graphic user interfaces were developed for users to interact with the tool. This tool is helpful in identifying a near optimal design of the spindle with the automation of the FEA process with numerous design changes in minimum time and efforts. It is also expected to allow even design engineers to perform the FEA in search of an optimal design of the machine tool spindle.

Robust Design Methodology of a Coupled System (연성 시스템의 강건설계 방법)

  • Lee, Kwon-Hee;Park, Gyung-Jin;Joo, Won-Sik
    • Proceedings of the KSME Conference
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    • 2003.11a
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    • pp.1763-1768
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    • 2003
  • Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. Based on the independence axiom of axiomatic design theory that illustrates the relationship between desired specifications and design parameters, the designs can be classified into three types: uncoupled, decoupled and coupled. To best approach the target performance with the maximum robustness is one of the main functional requirements of a mechanical system. Most engineering designs are pertaining to either coupled or decoupled ones, but these designs cannot currently accomplish a real robustness thus a trade-off between performance and robustness has to be made. In this research, the game theory will be applied to optimize the trade-off.

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Algorithm for Detecting, Indentifying, Locating and Experience to Develop the Automate Faults Location in Radial Distribution System

  • Wattanasakpubal, Choowong;Bunyagul, Teratum
    • Journal of Electrical Engineering and Technology
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    • v.5 no.1
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    • pp.36-44
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    • 2010
  • This paper presents the design of an algorithm to detect, identify, and locate faults in radial distribution feeders of Provincial Electricity Authority (PEA). The algorithm consists of three major steps. First, the adaptive algorithm is applied to track/estimate the system electrical parameter, i.e. current phasor, voltage phasor, and impedance. Next process, the impedance rule base is used to detect and identify the type of fault. Finally, the current compensation technique and a geographic information system (GIS) are applied to evaluate a possible fault location. The paper also shows the results from field tests of the automate fault location and illustrates the effectiveness of the proposed fault location scheme.

Applications of Machine Learning for Online Learning Systems towards Children with Speech Disorders

  • Jadi, Amr;Alzahrani, Ali
    • International Journal of Computer Science & Network Security
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    • v.22 no.8
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    • pp.55-60
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    • 2022
  • Specific Language Impairment is one of the serious disorders that interferes with spontaneous communication skills in children. Children suffering from this disorder may have reading, speaking, or listening impairments, and such type of disorders are also termed Autism Speech Disorder (ASD) in medical terminology. The aim of the article is to define specific language impairment in children and the problems it can cause. The different methods adopted by speech pathologists to diagnose language impairment. Finally implementing machine learning models to automate the process and help speech pathologists and pediatricians/ in diagnosing the specific language impairment.

Development of Deep Learning based waste Detection vision system (Deep Learning 기반의 폐기물 선별 Vision 시스템 개발)

  • Bong-Seok Han;Hyeok-Won Kwon;Bong-Cheol Shin
    • Design & Manufacturing
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    • v.16 no.4
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    • pp.60-66
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    • 2022
  • Recently, with the development of industry and the improvement of living standards, various wastes are generated along with the production of various products. Most of these wastes are used as containers for products, and plastic or aluminum is used. Various attempts are being made to automate the classification of these wastes due to the high labor cost, but most of them are solved by manpower due to the geometrical shape change due to the nature of the waste. In this study, in order to automate the waste sorting task, Deep Learning technology is applied to a robot system for waste sorting and a vision system for waste sorting to effectively perform sorting tasks according to the shape of waste. As a result of the experiment, a Deep Learning parameter suitable for waste sorting was selected. In addition, through various experiments, it was confirmed that 99% of wastes could be selected in individual & group image learning. It is expected that this will enable automation of the waste sorting operation.

A Study on Automation of Big Data Quality Diagnosis Using Machine Learning (머신러닝을 이용한 빅데이터 품질진단 자동화에 관한 연구)

  • Lee, Jin-Hyoung
    • The Journal of Bigdata
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    • v.2 no.2
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    • pp.75-86
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    • 2017
  • In this study, I propose a method to automate the method to diagnose the quality of big data. The reason for automating the quality diagnosis of Big Data is that as the Fourth Industrial Revolution becomes a issue, there is a growing demand for more volumes of data to be generated and utilized. Data is growing rapidly. However, if it takes a lot of time to diagnose the quality of the data, it can take a long time to utilize the data or the quality of the data may be lowered. If you make decisions or predictions from these low-quality data, then the results will also give you the wrong direction. To solve this problem, I have developed a model that can automate diagnosis for improving the quality of Big Data using machine learning which can quickly diagnose and improve the data. Machine learning is used to automate domain classification tasks to prevent errors that may occur during domain classification and reduce work time. Based on the results of the research, I can contribute to the improvement of data quality to utilize big data by continuing research on the importance of data conversion, learning methods for unlearned data, and development of classification models for each domain.

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Infant Retinal Images Optic Disk Detection Using Active Contours

  • Charmjuree, Thammanoon;Uyyanonvara, Bunyarit;Makhanov, Stanislav S.
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.312-316
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    • 2004
  • The paper presents a technique to identify the boundary of the optic disc in infant retinal digital images using an approach based on active contours (snakes). The technique can be used to be develop a automate system in order to help the ophthalmologist's diagnosis the retinopathy of prematurity (ROP) disease which may occurred on preterm infant,. The optic disc detection is one of the fundamental step which could help to create an automate diagnose system for the doctors we use a new kind of active contour (snake) method has been developed by Chenyang et. al. [1], based on a new type of external force field, called gradient vector flow, or GVF. GVF is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. The testing results on a set of infant retinal ROP images verify the effectiveness of the proposed methods. We show that GVF has a large capture range and it's able to move snakes into boundary concavities of optic disc and finally the optic disk boundary was determined.

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인터넷을 이용한 글로벌 제조환경의 구축

  • 김태운;김홍배;현재명
    • Proceedings of the Korea Association of Information Systems Conference
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    • 1997.10a
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    • pp.113-125
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    • 1997
  • The objective of this research is to construct and build a software platform to enable collaboration among enterprise headquarters, product designers, software engineers, manufacturing plants, and suppliers which are located at different remote locations via internet. In specific, agent technology is adopted as a software vehicle to automate demand as a software vehicle to automate demand and supply process in the internet environment. Agents are programs that act an behalf of their human users to perform laborious tasks such as information locating, accessing, filtering, integrating, adapting and resolving inconsistencies. Global competition is forcing the present day industry to produce high quality product more fast and inexpensively. In Korea, most labor-intensive industries have moved to China and other Asian countries for cost reduction. The need for fast information exchange has increased among the remote locations for the cooperation and coordination. In this research, a virtual global manufacturing system will be constructed that distributes production schedule among remote places, acts as a bridge between the headquarters and manufacturing plants, distributes tasks and collates different solutions between demand and supply using agent. The external communication protocol takes HTML format, internal message handling requires SGML for document exchange, and KQML for agent implementation. The expected benefits will be : reduced cost of real-time information exchange, realization of global manufacturing environment, the maximum utilization of internet for the enterprise data exchange.

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An Orthologous Group Clustering Technique based on the Grid Computing

  • Oh, J.S.;Kim, T.K.;Kim, S.S.;Kwon, H.R.;Kim, Y.C.;Yoo, J.S.;Cho, W.S.
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2005.09a
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    • pp.72-77
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    • 2005
  • Orthologs are genes having the same function across different species that specialize from a single gene in the last common ancestor of these species. Orthologous groups are useful in the genome annotation, studies on gene evolution, and comparative genomics. However, the construction of an orthologous group is difficult to automate and it takes so much time. It is also hard to guarantee the accuracy of the constructed orthologous groups. We propose a system to construct orthologous groups on many genomes automatically and rapidly. We utilize the grid computing to reduce the sequence alignment time, and we use clustering algorithm in the application of database to automate whole processes. We have generated orthologous groups for 20 complete prokaryotes genomes just in a day because of the grid computing. Furthermore, new genomes can be accommodated easily by the clustering algorithm and grid computing. We compared the generated orthologous groups with COGs (Clusters of orthologous Group of proteins) and KO (KEGG Ortholog). The comparison shows about 85 percent similarity compared with previous well-known orthologous databases.

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A Study on the Software Development to Automate the Calculation for the Landscape Architecture Construction Cost Estimation. (조경 공사 내역서 계산 자동화를 위한 소프트웨어 개발에 관한 연구)

  • 이규석;황국웅
    • Journal of the Korean Institute of Landscape Architecture
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    • v.20 no.2
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    • pp.106-118
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    • 1992
  • The landscape architecture construction cost estimation includes the repeated calculation and updating. Thus, it is time-consuming, and one of the jobs which needs to be automated first. In Korea, the IBM compatible personal computer(PC) is the most widely used one in the landscape architecture firms. However, the software for landscape architecture construction cost estimation is not being used in the PC environment. Therefore, the purpose of this study is to develop the software which can be used to automate the calculation for the landscape architecture construction cost estimation, and runs in the IBM compatible personal computers(PC). The clipper '88 summer is one of the DBMS software packages, and it has many commands and functions and functions which reduces program lines and makes the programing efficient, especially in the programing work whose total source code lines do not exceed over 10,000 lines. So, it was used in this study. The software developed in the this study was tested using the real data, and it was found that it can be efficiently used in the following jobs. They are: (1) to calculate exactly and rapidly. (2) to use resources repeatedly. (3) to print out the results. (4) to store data files for the future use. The software, as discussed in this paper, reduces the time and efforts to be spent in the calculation for the landscape architecture construction cost estimation compared with the traditional approach using the pocket calculator.

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