• Title/Summary/Keyword: Pattern function

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Classification and recognition of electrical tracking signal by means of LabVIEW (LabVIEW에 의한 Tracking 신호 분류 및 인식)

  • Kim, Dae-Bok;Kim, Jung-Tae;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.4
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    • pp.779-787
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    • 2010
  • In this paper, We introduce electrical tracking generated from surface activity associated with flow of leakage current on insulator under wet and contaminated conditions and design electrical tracking pattern recognition system by using LabVIEW. We measure the leaking current of contaminated wire by using LabVIEW software and the NI-c-DAQ 9172 and NI-9239 hardware. As pattern recognition algorithm and optimization algorithm for electrical tracking system, neural networks, Radial Basis Function Neural Networks(RBFNNs) and particle swarm optimization are exploited. The designed electrical tracking recognition system consists of two parts such as the hardware part of electrical tracking generator, the NI-c-DAQ 9172 and NI-9239 hardware and the software part of LabVIEW block diagram, LabVIEW front panel and pattern recognition-related application software. The electrical tracking system decides whether electrical tracking generate or not on electrical wire.

Design of Multilayer Perceptrons for Pattern Classifications (패턴인식 문제에 대한 다층퍼셉트론의 설계 방법)

  • Oh, Sang-Hoon
    • The Journal of the Korea Contents Association
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    • v.10 no.5
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    • pp.99-106
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    • 2010
  • Multilayer perceptrons(MLPs) or feed-forward neural networks are widely applied to many areas based on their function approximation capabilities. When implementing MLPs for application problems, we should determine various parameters and training methods. In this paper, we discuss the design of MLPs especially for pattern classification problems. This discussion includes how to decide the number of nodes in each layer, how to initialize the weights of MLPs, how to train MLPs among various error functions, the imbalanced data problems, and deep architecture.

The effect of elastic band based of PNF pattern on the U/E function in the spinal cord injury patient (PNF 패턴에 기초한 탄력밴드 훈련이 척수손상 환자의 상지 기능에 미치는 영향)

  • Shin Young-Il;Lee Hyoung-Soo
    • The Journal of Korean Physical Therapy
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    • v.16 no.3
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    • pp.152-160
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    • 2004
  • The purpose of this study was to investigate the effect of elastic band based of PNF pattern on the U/E function in the spinal cord injury patient. 11 subjects with spinal cord injury participated in this study. They took elastic band excercise 5 times per week for 8 weeks. One time excercise spent 35minutes. The therapeutic effect was evaluated by Cybex 6000, BTE Work Simulator, how many seconds they needed to walk 100 meters. 11 cases were examined before, after 8 week, elastic band excercise. The results of this study are as follows; 1. Isokinetic power by Cybex 6000 : The elbow flexion, shoulder flexion and extension were significant difference between test-retest(p<.05). but elbow extension were not significant difference between test-retest. 2. BTE Work Simulator : Wheelchair Propulsion and Steering Torque were significant difference between test-retest(p<.05). 3. Wheelchair Propulsion velocity : There were significant difference between test-retest(p<.05). The findings suggest that SCI patients can improve their Isokinetic power on shoulder and elbow joint, wheelchair propulsion and Steering Torque by BTE Work Simulator, Wheelchair Propulsion velocity through elastic band based of PNF pattern.

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Syntatic Pattern recognition of the ECG (심전도 신호의 신택틱 패턴인식)

  • Nam, Seung-Woo;Lee, Byung-Cha;Sin, Kun-Su;Lee, Jae-Jun;Lee, Myung-Hoo
    • Proceedings of the KOSOMBE Conference
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    • v.1991 no.11
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    • pp.129-132
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    • 1991
  • This paper describes the ECG pattern recognition using the syntatic pattern recognition algorithm. The algorithm uses the BNF rule wi th the semantic evaluation which has the structural Information of the ECG. This algorithm is constructed with (1) removing the baseline drift by the Cubic spline function and exract the significant point by the line-approximation algorithm, (2) syntatic peak recognition algorithm with the extracted significant point, (3) produce the token which is used pattern recognition, (4) pattern recognition of the ECG by the syntatic pattern recognition algorithm, (5) extract the parameter with the pattern recognized ECG signal.

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A Study On IoT Data Consistency in IoT Environment (사물인터넷 환경에서 IoT 데이터 정합성 연구)

  • Choi, Changwon
    • Journal of Internet of Things and Convergence
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    • v.8 no.5
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    • pp.127-132
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    • 2022
  • As the IoT technology is more developed, it is more important for the accuracy of IoT data. Since the IoT data supports a different formats and protocols, it is often happened that the IoT system is failed or the incorrect data is generated with the unreliable IoT devices(sensor, actuator). Because the abnormality of IoT device or the user situation is not detected correctly, this problem makes the user to be unsatisfied with the IoT system. This study proposes the decision methodology of IoT data consistency whether the IoT data is generated in normal range or not by using the mathematical functions('gradient descent function' and 'linear regression function'). It may be concluded that the gradient function method is suitable for the IoT data which the 'increasing velocity' is related with the next generated pattern(eg. sensor devices), the linear regression function method is suitable for the IoT data which the 'the difference from linear regression function' is related with the next generated pattern in case the data has a linear pattern(eg. water meter, electric meter).

The Estimation of Incomplete Information in Electricity Markets by Using Load Pattern Changes (부하패턴을 이용한 전력시장 정보의 불완비성 추정에 관한 연구)

  • Shin, Jae-Hong;Lee, Kwang-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.5
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    • pp.848-853
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    • 2007
  • This paper presents a methodology of estimating incomplete information in electricity markets for analyzing the gaming behavior of Generating Companies (GENCOs). Each GENCO needs to model its opponents' unknown information of strategic biddings and cost functions. In electricity markets with complete information, each GENCO knows its rivals' payoff functions and tries to maximize its own profit at Nash equilibriurnl Nli) by acknowledging the rivals' cost function. On the other hand, in the incomplete information markets, each GENCO lacks information about its rivals. Load patterns can change continuously due to many factors such as weather, price, contingency, etc. In this paper, we propose the method of the estimation of the opponents' cost function using market price, transaction quantities. and customer load patterns. A numerical example with two GENCOs is illustrated to show the basic idea and effectiveness of the proposed methodology.

Development of Intelligent Gear-Shifting Map Based on Radial Basis Function Neural Networks

  • Ha, Sang-Hyung;Jeon, Hong-Tae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.13 no.2
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    • pp.116-123
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    • 2013
  • Currently, most automobiles have automatic transmission systems. The gear-shifting strategy used to generate shift patterns in transmission systems plays an important role in improving the performance of vehicles. However, conventional transmission systems have a fixed type of shift map, so it may not be enough to provide an efficient gear-shifting pattern to satisfy the demands of driver. In this study, we developed an intelligent strategy to handle these problems. This approach is based on a normalized radial basis function neural network, which can generate a flexible gear-shift pattern to satisfy the demands of drivers, including comfortable travel and fuel consumption. The method was verified through simulations.

New Similarity Measures of Simplified Neutrosophic Sets and Their Applications

  • Liu, Chunfang
    • Journal of Information Processing Systems
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    • v.14 no.3
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    • pp.790-800
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    • 2018
  • The simplified neutrosophic set (SNS) is a generalization of fuzzy set that is designed for some practical situations in which each element has truth membership function, indeterminacy membership function and falsity membership function. In this paper, we propose a new method to construct similarity measures of single valued neutrosophic sets (SVNSs) and interval valued neutrosophic sets (IVNSs), respectively. Then we prove that the proposed formulas satisfy the axiomatic definition of the similarity measure. At last, we apply them to pattern recognition under the single valued neutrosophic environment and multi-criteria decision-making problems under the interval valued neutrosophic environment. The results show that our methods are effective and reasonable.

APPLICATIONS OF SIMILARITY MEASURES FOR PYTHAGOREAN FUZZY SETS BASED ON SINE FUNCTION IN DECISION-MAKING PROBLEMS

  • ARORA, H.D.;NAITHANI, ANJALI
    • Journal of applied mathematics & informatics
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    • v.40 no.5_6
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    • pp.897-914
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    • 2022
  • Pythagorean fuzzy sets (PFSs) are capable of modelling information with more uncertainties in decision-making problems. The essential feature of PFSs is that they are described by three parameters: membership function, non-membership function and hesitant margin, with the total of the squares of each parameter equal to one. The purpose of this article is to suggest some new similarity measures and weighted similarity measures for PFSs. Numerical computations have been carried out to validate our proposed measures. Applications of these measures have been applied to some real-life decision-making problems of pattern detection and medicinal investigations. Moreover, a descriptive illustration is employed to compare the results of the proposed measures with the existing analogous similarity measures to show their effectiveness.

Mathematical Creativity and Mathematics Curriculum: Focusing on Patterns and Functions (창의성 관점에서 본 제 7차 초등 수학과 교육과정: 규칙성과 함수를 중심으로)

  • 서경혜;유솔아;정진영
    • Education of Primary School Mathematics
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    • v.7 no.1
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    • pp.15-29
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    • 2003
  • The present study examined the 7th national elementary school mathematics curriculum from a perspective of mathematical creativity. The study investigated to what extent the activities in the Pattern and Function lessons in the national elementary school mathematics textbooks promoted the development of mathematical creativity. The results indicated that the current elementary school mathematics curriculum was limited in many ways to promote the development of mathematical creativity. Regarding the activities in Pattern lessons, for example, most activities presented closed tasks involving finding and extending patterns. The lesson provided little opportunities to explore the relationships among various patterns, apply patterns to different situations, or create ones own patterns. In regard to the Function lessons, the majority of activities were about computing the rate. This showed that the function was taught from an operational perspective, not a relational perspective. It was unlikely that students would develop the basic understanding of function through the activities involving the computing the rate. Further, the lessons had students use exclusively the numbers in representing the function. Students were provided little opportunities to use various representation methods involving pictures or graphs, explore the strengths and limitations of various representation methods, or to choose more effective representation methods in particular contexts. In conclusion, the lesson activities in the current elementary school mathematics textbooks were unlikely to promote the development of mathematical creativity.

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