• Title/Summary/Keyword: data algorithm system

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Study on Wireless Body Area Network System Design Based on Transmission Rate (전송률을 고려한 WBAN 시스템 설계에 관한 연구)

  • Park, Joo-Hee
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.12
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    • pp.121-129
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    • 2012
  • In this paper, we proposed WBAN system model to management an application that requires low rate data transfer in IEEE 802.15.4. We have to use different wireless sensor network technology to transfer different date rate and emergency message in medical application service. A suitable system model for WBAN and a WBAN MAC protocol in order to solve these existing system problems are proposed. Firstly, the priority queuing was applied to contention access period, and the system model which could guarantee transmission of a MAC command frame was proposed. Secondly, the MAC frame was newly defined to use the system model which was proposed above. Thirdly, WBAN CSMA/CA back-off algorithm based on data transmission rate was proposed to enhance data throughput and transmission probability of the data frame which does not have priority in the proposed WBAN system. The proposed algorithm is designed to be variable CSMA/CA algorithm parameter, depending on data rate. For the evaluation of WBAN CSMA/CA algorithm, we used Castalia. As a result of the simulation, it is found that the proposed system model can not only relieve loads of data processing, but also probability of collision was decreased.

A rubber o-ring defect detection system using data augmentation based on the SinGAN and random forest algorithm (SinGAN기반 데이터 증강과 random forest알고리즘을 이용한 고무 오링 결함 검출 시스템)

  • Lee, Yong Eun;Lee, Han Sung;Kim, Dae Won;Kim, Kyung Chun
    • Journal of the Korean Society of Visualization
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    • v.19 no.3
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    • pp.63-68
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    • 2021
  • In this study, data was augmentation through the SinGAN algorithm using small image data, and defects in rubber O-rings were detected using the random forest algorithm. Unlike the commonly used data augmentation image rotation method to solve the data imbalance problem, the data imbalance problem was solved by using the SinGAN algorithm. A study was conducted to distinguish between normal products and defective products of rubber o-ring by using the random forest algorithm. A total of 20,000 image date were divided into transit and testing datasets, and an accuracy result was obtained to distinguish 97.43% defects as a result of the test.

Estimation of Smart Election System data

  • Park, Hyun-Sook;Hong, You-Sik
    • International journal of advanced smart convergence
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    • v.7 no.2
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    • pp.67-72
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    • 2018
  • On the internal based search, the big data inference, which is failed in the president's election in the United States of America in 2016, is failed, because the prediction method is used on the base of the searching numerical value of a candidate for the presidency. Also the Flu Trend service is opened by the Google in 2008. But the Google was embarrassed for the fame's failure for the killing flu prediction system in 2011 and the prediction of presidential election in 2016. In this paper, using the virtual vote algorithm for virtual election and data mining method, the election prediction algorithm is proposed and unpacked. And also the WEKA DB is unpacked. Especially in this paper, using the K means algorithm and XEDOS tools, the prediction of election results is unpacked efficiently. Also using the analysis of the WEKA DB, the smart election prediction system is proposed in this paper.

Data Quality Management: Operators and a Matching Algorithm with a CRM Example (데이터 품질 관리 : CRM을 사례로 연산자와 매칭기법 중심)

  • 심준호
    • The Journal of Society for e-Business Studies
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    • v.8 no.3
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    • pp.117-130
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    • 2003
  • It is not unusual to observe that there Is a great amount of redundant or inconsistent data even within an e-business system such as CRM(Customer Relationship Management) system. This problem becomes aggravate when we construct a system of which information are gathered from different sources. Data quality management is indeed needed to avoid any possible redundant or inconsistent data in such information system. A data quality process, in general, consists of three phases: data cleaning (scrubbing), matching, and integration phase. In this paper, we introduce and categorize data quality operators for each phase. Then, we describe our distance function used in the matching phase, and present a matching algorithm PRIMAL (a PRactical Matching Algorithm). And finally, we present a related work and future research.

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Development of a 3-D Position Measurement Algorithm using 2-D Image Information (2차원 영상 정보를 이용한 3차원 위치 측정 알고리즘 개발)

  • Lee, J.H.;Jung, S.H.;Kim, D.H.
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.12 no.5
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    • pp.141-148
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    • 2013
  • There are several problems in the conventional 2-D image processing and 3-D measurement systems. In the case of the 2-D image processing system, it is not possible to detect elevation data. In a 3-D measurement system, it requires a skillful operator and a lot of time for measuring data. Also, there exist data errors depending on operators. The limitation of detecting elevation data in the 2-D image processing system can be solved by laser diodes. In this study an algorithm that measures the accurate data in a subject face to be detected by combining laser diodes and a commercial CCD camera is developed. In the development process, a planar equation is developed using laser diodes and the equation is used to obtain a normal vector. Based on the results, an algorithm that transforms commercial CCD camera coordinates to 3-D coordinates is proposed. The completed measurement method will be applied to replace a manual measurement system for vehicle bodies and parts by an automated system.

Image Clustering using Improved Neural Network Algorithm (개선된 신경망 알고리즘을 이용한 영상 클러스터링)

  • 박상성;이만희;유헌우;문호석;장동식
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.7
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    • pp.597-603
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    • 2004
  • In retrieving large database of image data, the clustering is essential for fast retrieval. However, it is difficult to cluster a number of image data adequately. Moreover, current retrieval methods using similarities are uncertain of retrieval accuracy and take much retrieving time. In this paper, a suggested image retrieval system combines Fuzzy ART neural network algorithm to reinforce defects and to support them efficiently. This image retrieval system takes color and texture as specific feature required in retrieval system and normalizes each of them. We adapt Fuzzy ART algorithm as neural network which receive normalized input-vector and propose improved Fuzzy ART algorithm. The result of implementation with 200 image data shows approximately retrieval ratio of 83%.

Parameter Estimation of Shallow Arch Using Quantum-Inspired Evolution Algorithm (양자진화 알고리즘을 이용한 얕은 아치의 파라미터 추정)

  • Shon, Sudeok;Ha, Junhong
    • Journal of Korean Association for Spatial Structures
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    • v.20 no.1
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    • pp.95-102
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    • 2020
  • The structural design of arch roofs or bridges requires the analysis of their unstable behaviors depending on certain parameters defined in the arch shape. Their maintenance should estimate the parameters from observed data. However, since the critical parameters exist in the equilibrium paths of the arch, and a small change in such the parameters causes a significant change in their behaviors. Thus, estimation to find the critical ones should be carried out using a global search algorithm. In this paper we study the parameter estimation for a shallow arch by a quantum-inspired evolution algorithm. A cost functional to estimate the system parameters included in the arch consists of the difference between the observed signal and the estimated signal of the arch system. The design variables are shape, external load and damping constant in the arch system. We provide theoretical and numerical examples for estimation of the parameters from both contaminated data and pure data.

Optimal Fuzzy Models with the Aid of SAHN-based Algorithm

  • Lee Jong-Seok;Jang Kyung-Won;Ahn Tae-Chon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.6 no.2
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    • pp.138-143
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    • 2006
  • In this paper, we have presented a Sequential Agglomerative Hierarchical Nested (SAHN) algorithm-based data clustering method in fuzzy inference system to achieve optimal performance of fuzzy model. SAHN-based algorithm is used to give possible range of number of clusters with cluster centers for the system identification. The axes of membership functions of this fuzzy model are optimized by using cluster centers obtained from clustering method and the consequence parameters of the fuzzy model are identified by standard least square method. Finally, in this paper, we have observed our model's output performance using the Box and Jenkins's gas furnace data and Sugeno's non-linear process data.

Single-channel Demodulation Algorithm for Non-cooperative PCMA Signals Based on Neural Network

  • Wei, Chi;Peng, Hua;Fan, Junhui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.7
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    • pp.3433-3446
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    • 2019
  • Aiming at the high complexity of traditional single-channel demodulation algorithm for PCMA signals, a new demodulation algorithm based on neural network is proposed to reduce the complexity of demodulation in the system of non-cooperative PCMA communication. The demodulation network is trained in this paper, which combines the preprocessing module and decision module. Firstly, the preprocessing module is used to estimate the initial parameters, and the auxiliary signals are obtained by using the information of frequency offset estimation. Then, the time-frequency characteristic data of auxiliary signals are obtained, which is taken as the input data of the neural network to be trained. Finally, the decision module is used to output the demodulated bit sequence. Compared with traditional single-channel demodulation algorithms, the proposed algorithm does not need to go through all the possible values of transmit symbol pairs, which greatly reduces the complexity of demodulation. The simulation results show that the trained neural network can greatly extract the time-frequency characteristics of PCMA signals. The performance of the proposed algorithm is similar to that of PSP algorithm, but the complexity of demodulation can be greatly reduced through the proposed algorithm.

Design of C-EPS (Column type - Electric Power Steering) Simulator and Development of Control Algorithm (C-EPS (C-type Electric Power Steering) 시뮬레이터 설계 및 제어 알고리즘 개발)

  • Park, Myung-Wook;Moon, Hee-Chang;Kim, Jung-Ha;Crane III, Carl D.
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.6
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    • pp.566-571
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    • 2010
  • EPS (Electric Power Steering) is important device for improving vehicle's dynamics and static performances. This paper deals with simulator design for C-EPS (Colum type-EPS), development assist and returnability control algorithm. First, C-EPS system model was simply designed because EPS system is complex control system that has many unknown variables. These parameters were simplified through assumptions. Second, C-EPS simulator was designed for development of control algorithm. This simulator has SAS (Steering Angle Sensor), dual torque sensor, dual load cell for measuring rack force, dual linear actuator for generating tire force and Data Acquisition System. Using this simulator, control methods ware tested. Third, control algorithm was designed for torque assist and returnability. Assist torque map and returnability torque map were found by lots of simulation test. These torque maps were tuned for EPS actuator control. The simulation result was compared with non-EPS system result. In this research, the C-EPS simulator was designed for development of control algorithm about torque assistant and returnability. Using this simulator, control algorithm was improved.