• Title/Summary/Keyword: Data Analysis Module

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Development of a Control System for Automated Line Heating Process by an Object-Oriented Approach

  • Shin, Jong-Gye;Ryu, Cheol-Ho;Choe, Sung-Won
    • Journal of Ship and Ocean Technology
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    • v.6 no.4
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    • pp.1-12
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    • 2002
  • A control system for an automated line heating process is developed by use of object-oriented methodology. The main function of the control system is to provide real-time heating information to technicians or automated machines. The information includes heating location, torch speed, heating order, and others. The system development is achieved by following the five steps in the object-oriented procedure. First, requirements are specified and corresponding objects are determined. Then, the analysis, design, and implementation of the proposed system are sequentially carried out. The system consists of six subsystems, or modules. These are (1) the inference module with an artificial neural network algorithm, (2) the analysis module with the Finite Element Method and kinematics analysis, (3) the data access module to store and retrieve the forming information, (4) the communication module, (5) the display module, and (6) the measurement module. The system is useful, irrespective of the heating sources, i.e. flame/gas, laser, or high frequency induction heating. A newly developed automated line heating machine is connected to the proposed system. Experiments and discussions follow.

Design and Implementation of 'Sea Map' Data Importer Module ('바다지도' 데이터 입력 모듈 설계 및 구현)

  • Yeo, Jimin;Park, Daewon;Park, Suhyun
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.2
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    • pp.91-99
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    • 2014
  • This paper is about design and implementation of 'SeaMap' importer module which is for map-based application using 'SeaMap' data. 'SeaMap' data importer is a module that reads 'SeaMap' data in consistent form and offers using easily change the format and the internal data structure in the application. Design of data importer module is based on analyzing characteristic of 'SeaMap'. The comparative analysis between the data type of 'SeaMap' and standard S-57 Electronic Navigation Chart (ENC) of the International Hydrographic Organization (IHO), based on this, to be applicable of S-52 standards 'SeaMap' data is defined as a structure of data. The importer module is designed and converted to allow to use distribution type of 'SeaMap' data sets in map application, parsing 'SeaMap' data around the object defining transformation data structure. In addition, we implemented a 'SeaMap' data viewer in order to test our 'SeaMap' data importer module.

A Design of Customized Market Analysis Scheme Using SVM and Collaboration Filtering Scheme (SVM과 협업적 필터링 기법을 이용한 소비자 맞춤형 시장 분석 기법 설계)

  • Jeong, Eun-Hee;Lee, Byung-Kwan
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.6
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    • pp.609-616
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    • 2016
  • This paper is proposed a customized market analysis method using SVM and collaborative filtering. The proposed customized market analysis scheme is consists of DC(Data Classification) module, ICF(Improved Collaborative Filtering) module, and CMA(Customized Market Analysis) module. DC module classifies the characteristics of on-line and off-line shopping mall and traditional markets into price, quality, and quantity using SVM. ICF module calculates the similarity by adding age weight and job weight, and generates network using the similarity of purchased item each users, and makes a recommendation list of neighbor nodes. And CMA module provides the result of customized market analysis using the data classification result of DC module and the recommendation list of ICF module. As a result of comparing the proposed customized recommendation list with the existing user based recommendation list, the case of recommendation list using the existing collaborative filtering scheme, precision is 0.53, recall is 0.56, and F-measure is 0.57. But the case of proposed customized recommendation list, precision is 0.78, recall is 0.85, and F-measure is 0.81. That is, the proposed customized recommendation list shows more precision.

Development of a CDMA Field Engineering System (CDMA 필드 엔지니어링 시스템 개발)

  • Lee, Chan-Su;Im, Hui-Gyeong;Hong, Seong-Cheol;Im, Jae-Bong;Seong, Yeong-Rak;O, Ha-Ryeong
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.5
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    • pp.1500-1510
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    • 2000
  • In this paper, a CDMA (Code Division Multiple Access) field engineering system is designed and implemented for managing cellular telecommunication base stations. For high quality of CDMA service, optimized cell planning is crucial. For such cell planning, base stations must be managed based on analysis of CDMA field dta. The proposed system consists of two modules: a measurement module and au analysis of CDMA field dta. eh proposed system consists of tow modules; a measurement module and an analysis module. The measurement module collects various CDMA field dta and displays them on a vector map in a real-time manner. The analysis module associates measured data with various related information, e.g. base station information, and process them statistically. The proposed system can drastically reduce base station management cost.

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A Swine Management System for PLC baed on Integrated Image Processing Technique (통합 이미지 처리기법 기반의 PLF를 위한 Swine 관리 시스템)

  • Arellano, Guy;Cabacas, Regin;Balontong, Amem;Ra, In-Ho
    • Smart Media Journal
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    • v.3 no.1
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    • pp.16-21
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    • 2014
  • The demand for food rises proportionally as population grows. To be able to achieve sustainable supply of livestock products, efficient farm management is a necessity. With the advancement in technology it also brought innovations that could be harness in order to achieve better productivity in animal production and agriculture. Precision Livestock Farming (PLF) is a budding concept of making use of smart sensors or available devices to automatically and continuously monitor and manage livestock production. With this concept, this paper introduces a swine management system that integrates image processing technique for weight monitoring. This system captures pig images using camera, evaluate and estimate the weight base on the captured image. It is comprised of Pig Module, Breeding Module, Health and Medication Module, Weighr Module, Data Analysis Module and Report Module to help swine farm administrators better understand the performance and situation of the swine farm. This paper aims to improve the management in both small and big livestock raisers.

The Prediction of Brake Corner Module Squeal Noise Using Participation Factor Analysis (기여도 분석법을 이용한 자동차 브레이크 시스템의 스퀼 소음 예측)

  • Lee, Jong-Ghi;Lim, Hyun-Seok;Kim, Hee-Yong;Baek, Jae-Wook
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.33 no.10
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    • pp.1074-1080
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    • 2009
  • A method for determining the geometric stability characteristics of a brake corner module (BCM) is presented. Since disc brake "squeal" noise typically occurs at unstable resonant frequencies of a system, the likelihood of disc brake squeal for a particular design can be determined. Finite element methods are used to derive complex eigenvalue for a brake corner module. Some unstable modes calculated by finite element methods correspond to squeal noise data. Through kinetic energy participation analysis for each part of BCM, we can efficiently predict squeal noise data.

A New Anchor Shot Detection System for News Video Indexing

  • Lee, Han-Sung;Im, Young-Hee;Park, Joo-Young;Park, Dai-Hee
    • Journal of the Korean Institute of Intelligent Systems
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    • v.18 no.1
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    • pp.133-138
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    • 2008
  • In this paper, we propose a novel anchor shot detection system, named to MASD (Multi-phase Anchor Shot Detection), which is a core step of the preprocessing process for the news video analysis. The proposed system is composed of four modules and operates sequentially: 1) skin color detection module for reducing the candidate face regions; 2) face detection module for finding the key-frames with a facial data; 3) vector representation module for the key-frame images using a non-negative matrix factorization; 4) one class SVM module for determining the anchor shots using a support vector data description. Besides the qualitative analysis, our experiments validate that the proposed system shows not only the comparable accuracy to the recently developed methods, but also more faster detection rate than those of others.

Design and Implementation of Intelligent IP Switch with Packet FEC for Ensuring Reliability of ATSC 3.0 Broadcast Streams

  • Lee, Song Yeon;Paik, Jong Ho;Dan, Hyun Seok
    • Journal of Internet Computing and Services
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    • v.20 no.2
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    • pp.21-27
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    • 2019
  • The terrestrial ATSC 3.0 broadcasting system, which is capable of converging broadcast and communication services, uses IP based technology for data transmission between broadcasting equipment. In addition, data transmission between broadcasting equipment uses IP-based technology like existing wired communication network, which has advantageous in terms of equipment construction and maintenance In case IP based data transmission technology is used, however, it may inevitably cause an error that a packet is lost during transmission depending on the network environments. In order to cope with a broadcasting accident caused by such a transmission error or a malfunction of a broadcasting apparatus, a broadcasting system is generally configured as a duplication, which can transmit a normal packet when various types of error may occur. By this reason, correction method of error packets and intelligent switching technology are essential. Therefore, in this paper, we propose a design and implementation of intelligent IP switch for Ensuring Reliability of ATSC 3.0 Broadcast Streams. The proposed intelligent IP consists of IP Stream Analysis Module, ALP Stream Analysis Module, STL Stream Analysis Module and SMPTE 2022-1 based FEC Encoding/Decoding Module.

An Optimal Driving Support Strategy(ODSS) for Autonomous Vehicles based on an Genetic Algorithm

  • Son, SuRak;Jeong, YiNa;Lee, ByungKwan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.12
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    • pp.5842-5861
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    • 2019
  • A current autonomous vehicle determines its driving strategy by considering only external factors (Pedestrians, road conditions, etc.) without considering the interior condition of the vehicle. To solve the problem, this paper proposes "An Optimal Driving Support Strategy(ODSS) based on an Genetic Algorithm for Autonomous Vehicles" which determines the optimal strategy of an autonomous vehicle by analyzing not only the external factors, but also the internal factors of the vehicle(consumable conditions, RPM levels etc.). The proposed ODSS consists of 4 modules. The first module is a Data Communication Module (DCM) which converts CAN, FlexRay, and HSCAN messages of vehicles into WAVE messages and sends the converted messages to the Cloud and receives the analyzed result from the Cloud using V2X. The second module is a Data Management Module (DMM) that classifies the converted WAVE messages and stores the classified messages in a road state table, a sensor message table, and a vehicle state table. The third module is a Data Analysis Module (DAM) which learns a genetic algorithm using sensor data from vehicles stored in the cloud and determines the optimal driving strategy of an autonomous vehicle. The fourth module is a Data Visualization Module (DVM) which displays the optimal driving strategy and the current driving conditions on a vehicle monitor. This paper compared the DCM with existing vehicle gateways and the DAM with the MLP and RF neural network models to validate the ODSS. In the experiment, the DCM improved a loss rate approximately by 5%, compared with existing vehicle gateways. In addition, because the DAM improved computation time by 40% and 20% separately, compared with the MLP and RF, it determined RPM, speed, steering angle and lane changes faster than them.

Ambiguity Analysis of Defectiveness in NASA MDP Data Sets (NASA MDP 데이터 집합의 결함도 모호성 분석)

  • Hong, Euyseok
    • Journal of Information Technology Services
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    • v.12 no.2
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    • pp.361-371
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    • 2013
  • Public domain defect data sets, such as NASA data sets which are available from the NASA MDP and PROMISE repositories, make it possible to compare the results of different defect prediction models by using the same data sets. This means that repeatable and general prediction models can be built. However, some recent studies have raised questions about the quality of two versions of NASA data set, and made new cleaned data sets by applying their data cleaning processes. We find that there are two ways in the NASA MDP versions to determine the defectiveness of a module, 0 or 1, and the two results are different in some cases. This serious problem, to our knowledge, has not been addressed in previous studies. To handle this ambiguity problem, we define two kinds of module defectiveness and two conditions that can be used to determine the ambiguous cases. We meticulously analyze 5 projects among the 13 NASA projects by using our ambiguity analysis method. The results show that JM1 and PC4 are the best projects with few ambiguous cases.