• Title/Summary/Keyword: Network analysis method

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An Efficient Analysis Model for Process Quality Information in Manufacturing Process of Automobile Safety Belt Parts (자동차 안전벨트 부품 제조공정에서의 효율적 공정품질정보 분석 모형)

  • Kong, Myung Dal
    • Journal of the Korean Institute of Plant Engineering
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    • v.23 no.4
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    • pp.29-38
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    • 2018
  • Through process quality information, the time required for process quality analysis has been drastically shortened, the process defect rate has been reduced, and the manufacturing lead time has been shortened and the on-time delivery rate has been improved. Therefore, The purpose of this study is to develop a quality information analysis system model that effectively shortens the time required for process quality analysis in automobile safety belt parts manufacturing process. As a result of experiments on communication operation between manufacturing execution system (MES) quality server, injection machine control computer, injection machine programmable logic controller (PLC) and terminal, in analyzing quality information, the conventional handwriting input method took an average of 20 minutes, but the new multi-network method took about 2 minutes on average. In addition, the process defect rate was reduced by 13% and the manufacturing lead time was shortened from 28 hours to 20 hours. The delivery compliance rate improved from 96 to 99%.

The Effect of the Sentence Location on Arabic Sentiment Analysis

  • Alotaibi, Saud S.
    • International Journal of Computer Science & Network Security
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    • v.22 no.5
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    • pp.317-319
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    • 2022
  • Rich morphology language such as Arabic needs more investigation and method to improve the sentiment analysis task. Using all document parts in the process of the sentiment analysis may add some unnecessary information to the classifier. Therefore, this paper shows the ongoing work to use sentence location as a feature with Arabic sentiment analysis. Our proposed method employs a supervised sentiment classification method by enriching the feature space model with some information from the document. The experiments and evaluations that were conducted in this work show that our proposed feature in the sentiment analysis for Arabic improves the performance of the classifier compared to the baseline model.

Train voltage analysis of railroad system using supply network method (급전회로망 해석기법을 활용한 전철계통 해석)

  • 윤재영;최흥관
    • Proceedings of the KSR Conference
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    • 2000.05a
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    • pp.108-115
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    • 2000
  • This paper presents the new simulation algorithms using network methods to analysis the steady-state train voltage distribution characteristics in ac auto-transformer fed railroads. In general, the supply system of railroads is composed of non-symmetrical and unbalance transmission line. Therefore, the general method using simplified old algorithms have the self-contradictory errors because the supply line of train railroads is completely unbalanced. In this paper, the simulation results of new developed algorithms is compared with those of EMTP to confirm the effectiveness.

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Network Reduction Method for Power System Transient Analysis ; Time-Domain Formulation Based On The Network Function (과도 상태 해석을 위한 계통 축약법 ; 계통 함수를 이용한 시간 영역 해석법)

  • Hong, J.H.;Kang, Y.C.;Cho, K.R.;Park, J.K.
    • Proceedings of the KIEE Conference
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    • 1991.07a
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    • pp.417-421
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    • 1991
  • In electromagnetic transient analysis, complex transmission system should be modelled in detail. But in large system, this full representation of power transmission system has a big burden in many sides such as computation time, modelling efforts, etc. It is very required, therefore, in electromagnetic transients studies to represent parts of a complete system in a reduced or an equivalent form. This paper develops the method from which system equivalents may be derived. The suggested method is of an essentially transient form, and allows travelling wave interaction between the equivalent and explicit transmission network to be modelled.

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Inverse Analysis Approach to Flow Stress Evaluation by Small Punch Test (소형펀치 시험과 역해석에 의한 재료의 유동응력 결정)

  • Cheon, Jin-Sik
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.24 no.7 s.178
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    • pp.1753-1762
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    • 2000
  • An inverse method is presented to obtain material's flow properties by using small punch test. This procedure employs, as the objective function of inverse analysis, the balance of measured load-di splacement response and calculated one during deformation. In order to guarantee convergence to global minimum, simulated annealing method was adopted to optimize the current objective function. In addition, artificial neural network was used to predict the load-displacement response under given material parameters which is the most time consuming and limits applications of global optimization methods to these kinds of problems. By implementing the simulated annealing for optimization along with calculating load-displacement curve by neural network, material parameters were identified irrespective of initial values within very short time for simulated test data. We also tested the present method for error-containing experimental data and showed that the flow properties of material were well predicted.

Fuzzy Regression Analysis Using Fuzzy Neural Networks (퍼지 신경망에 의한 퍼지 회귀분석)

  • Kwon, Ki-Taek
    • Journal of Korean Institute of Industrial Engineers
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    • v.23 no.2
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    • pp.371-383
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    • 1997
  • This paper propose a fuzzy regression method using fuzzy neural networks when a membership value is attached to each input-output pair. First, a method of linear fuzzy regression analysis is described by interpreting the reliability of each input-output pair as its membership values. Next, an architecture of fuzzy neural networks with fuzzy weights and fuzzy biases is shown. The fuzzy neural network maps a crisp input vector to a fuzzy output. A cost function is defined using the fuzzy output from the fuzzy neural network and the corresponding target output with a membership value. A learning algorithm is derived from the cost function. The derived learning algorithm trains the fuzzy neural network so that the level set of the fuzzy output includes the target output. Last, the proposed method is illustrated by computer simulations on numerical examples.

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Optimal Allocation Method of Hybrid Active Power Filters in Active Distribution Networks Based on Differential Evolution Algorithm

  • Chen, Yougen;Chen, Weiwei;Yang, Renli;Li, Zhiyong
    • Journal of Power Electronics
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    • v.19 no.5
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    • pp.1289-1302
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    • 2019
  • In this paper, an optimal allocation method of a hybrid active power filter in an active distribution network is designed based on the differential evolution algorithm to resolve the harmonic generation problem when a distributed generation system is connected to the grid. A distributed generation system model in the calculation of power flow is established. An improved back/forward sweep algorithm and a decoupling algorithm are proposed for fundamental power flow and harmonic power flow. On this basis, a multi-objective optimization allocation model of the location and capacity of a hybrid filter in an active distribution network is built, and an optimal allocation scheme of the hybrid active power filter based on the differential evolution algorithm is proposed. To verify the effect of the harmonic suppression of the designed scheme, simulation analysis in an IEEE-33 nodes model and an experimental analysis on a test platform of a microgrid are adopted.

Network Structure of Professional Volleyball Players and Resource Exchange (프로배구 선수의 사회연결망 구조와 자원교환)

  • Lee, Se-Ho
    • The Journal of the Korea Contents Association
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    • v.12 no.6
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    • pp.438-447
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    • 2012
  • This study was to explore the social network structure of professional volleyball players and analyze network variables and resource exchange. This study selected 127 players of Korean professional volleyball in ten team of male and female using the purposive sampling method. The research method utilized general social survey of NGQ(Name Generator Question) and interview. To analyze data, NetMiner 3.0 and SNA(social network analysis) were used. The conclusion based on above study method and the result of material analysis are here below. First, social network of professional volleyball players is scale-free network following power law. Centrality and herb of club members' network show up richer-get-richer and poor-get-poor by collecting links of back of beyond. Second, social network structure of professional volleyball players influence resource exchange.

Performance test method analysis of wired network (유선 네트워크 성능시험 방법 분석)

  • Lee, Jae-Jeong;Ryu, Han-yang;Nam, Ki-dong;Rhee, Woo-Seop
    • Journal of Digital Contents Society
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    • v.19 no.4
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    • pp.801-808
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    • 2018
  • The performance test methodology for switch, router or integrated networks that make up the wired network is not clearly defined. Due to smart phones and multimedia traffic, the speed of the network is rapidly increasing to 100Gbps. However, there is no formalized test method, and performance test related parts are still being tested based on old data. Telecommunication companies and companies are testing their requirements in their own BMT, and government or public institutions are requesting performance tests from external organizations. As the demand for the performance test of next generation network equipments and the integrated network increases, analysis of the performance test method should be done as soon as possible. Therefore, in this paper, we analyze the performance test method performed by the institute and propose guidelines that can be applied to all wired network equipment.

Monitoring of Chemical Processes Using Modified Scale Space Filtering and Functional-Link-Associative Neural Network (개선된 스케일 스페이스 필터링과 함수연결연상 신경망을 이용한 화학공정 감시)

  • Park, Jung-Hwan;Kim, Yoon-Sik;Chang, Tae-Suk;Yoon, En-Sup
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.12
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    • pp.1113-1119
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    • 2000
  • To operate a process plant safely and economically, process monitoring is very important. Process monitoring is the task to identify the state of the system from sensor data. Process monitoring includes data acquisition, regulatory control, data reconciliation, fault detection, etc. This research focuses on the data recon-ciliation using scale-space filtering and fault detection using functional-link associative neural networks. Scale-space filtering is a multi-resolution signal analysis method. Scale-space filtering can extract highest frequency factors(noise) effectively. But scale-space filtering has too large calculation costs and end effect problems. This research reduces the calculation cost of scale-space filtering by applying the minimum limit to the gaussian kernel. And the end-effect that occurs at the end of the signal of the scale-space filtering is overcome by using extrapolation related with the clustering change detection method. Nonlinear principal component analysis methods using neural network have been reviewed and the separately expanded functional-link associative neural network is proposed for chemical process monitoring. The separately expanded functional-link associative neural network has better learning capabilities, generalization abilities and short learning time than the exiting-neural networks. Separately expanded functional-link associative neural network can express a statistical model similar to real process by expanding the input data separately. Combining the proposed methods-modified scale-space filtering and fault detection method using the separately expanded functional-link associative neural network-a process monitoring system is proposed in this research. the usefulness of the proposed method is proven by its application a boiler water supply unit.

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