• Title/Summary/Keyword: post data processing

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Reinforcement Data Mining Method for Anomaly&Misuse Detection (침입탐지시스템의 정확도 향상을 위한 개선된 데이터마이닝 방법론)

  • Choi, Yun Jeong
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.6 no.1
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    • pp.1-12
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    • 2010
  • Recently, large amount of information in IDS(Intrusion Detection System) can be un manageable and also be mixed with false prediction error. In this paper, we propose a data mining methodology for IDS, which contains uncertainty based on training process and post-processing analysis additionally. Our system is trained to classify the existing attack for misuse detection, to detect the new attack pattern for anomaly detection, and to define border patter between attack and normal pattern. In experimental results show that our approach improve the performance against existing attacks and new attacks,from 0.62 to 0.84 about 35%.

Debiasing Technique for Numerical Weather Prediction using Artificial Neural Network

  • Kang, Boo-Sik;Ko, Ick-Hwan
    • Proceedings of the Korea Water Resources Association Conference
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    • 2006.05a
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    • pp.51-56
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    • 2006
  • Biases embedded in numerical weather precipitation forecasts by the RDAPS model was determined, quantified and corrected. The ultimate objective is to eventually enhance the reliability of reservoir operation by Korean Water Resources Corporation (KOWACO), which is based on precipitation-driven forecasts of stream flow. Statistical post-processing, so called MOS (Model Output Statistics) was applied to RDAPS to improve their performance. The Artificial Neural Nwetwork (ANN) model was applied for 4 cases of 'Probability of Precipitation (PoP) for wet and dry season' and 'Quantitative Precipitation Forecasts (QPF) for wet and dry season'. The reduction on the large systematic bias was especially remarkable. The performance of both networks may be improved by retraining, probably every month. In addition, it is expected that performance of the networks will improve once atmospheric profile data are incorporated in the analysis. The key to the optimal performance of ANN is to have a large data set relevant to the predictand variable. The more complex the process to be modeled by the ANN, the larger the data set needs to be.

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A Work-related Musculoskeletal Disorder Risk Assessment Platform using Smart Sensor (스마트센서를 활용한 근골격계 질환 위험 평가 플랫폼)

  • Loh, Byoung Gook
    • Journal of the Korean Society of Safety
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    • v.30 no.3
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    • pp.93-99
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    • 2015
  • Economic burden of work-related musculoskeletal disorder(WMDs) is increasing. Known causes of WMDs include improper posture, repetition, load, and temperature of workplace. Among them, improper postures play an important role. A smart sensor called SensorTag is employed to estimate the trunk postures including flexion-extension, lateral bend, and the trunk rotational speeds. Measuring gravitational acceleration vector in the smart sensor along the tri-orthogonal axes offers an orientation of the object with the smart sensor attached to. The smart sensor is light in weight and has small form factor, making it an ideal wearable sensor for body posture measurement. Measured data from the smart senor is wirelessly transferred for analysis to a smartphone which has enough computing power, data storage and internet-connectivity, removing need for additional hardware for data post-processing. Based on the estimated body postures, WMDs risks can be conviently gauged by using existing WMDs risk assesment methods such as OWAS, RULA, REBA, etc.

Measuring hull girder deformations on a 9300 TEU containership

  • Koning, Jos;Schiere, Marcus
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.6 no.4
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    • pp.1111-1129
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    • 2014
  • A 9300 TEU container carrier was equipped in 2006 with instrumentation aimed at wave induced accelerations, and motions. In 2010 the system was extended with strain sensors to include structural loads. Section loads for vertical bending could be readily obtained but the originally intended derivation of horizontal bending and torsion from the measured strains was found to be unreliable. This paper addresses an alternative approach that was adopted in the post processing of results. In particular the concept to use acceleration sensors to capture global hull deformations along the length of the hull, and the use of a data fusion procedure to obtain section loads from combined sensor data and finite element calculations. The approach is illustrated by comparison of actually measured accelerations and local strains with values obtained from the data fusion model. It is concluded that the approach is promising but in need of further validation and development. In particular the number and shapes of the modes used may not have been sufficient to represent the true deflection and thus strain distributions along the high loaded areas.

Development of a Measurement System Development for On-Line Testing of High Speed Railway (고속철도 시운전시험 계측시스템 개발에 관한 연구)

  • 김석원;김영국;한영재;박찬경;김진환;백광선
    • Journal of the Korean Society for Railway
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    • v.5 no.3
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    • pp.158-166
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    • 2002
  • In this paper, we introduce the software and hardware of the measurement system for on-line testing and evaluation of high speed railway. The test items focus on the verification of the performance and acquirement of the technical data of the high speed railway system. The software controls the hardware of the measurement system, perform the analysis and calculation of measurement data and acts as interface between users and the system hardware. For this purpose, three programs a measuring program, a monitoring program and post-processing program are developed. The detailed test scenario is in the process of development to closely follow the process of development and design of the system.

Restoring Motion Capture Data for Pose Estimation (자세 추정을 위한 모션 캡처 데이터 복원)

  • Youn, Yeo-su;Park, Hyun-jun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.5-7
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    • 2021
  • Motion capture data files for pose estimation may have inaccurate data depending on the surrounding environment and the degree of movement, so it is necessary to correct it. In the past, inaccurate data was restored with post-processing by people, but recently various kind of neural networks such as LSTM and R-CNN are used as automated method. However, since neural network-based data restoration methods require a lot of computing resource, this paper proposes a method that reduces computing resource and maintains data restoration rate compared to neural network-based method. The proposed method automatically restores inaccurate motion capture data by using posture measurement data (c3d). As a result of the experiment, data restoration rates ranged from 89% to 99% depending on the degree of inaccuracy of the data.

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Development of an Automated Operational Orbit Processing System (자동 궤도운용 시스템 개발)

  • Kim, Hae-Dong;Jung, Ok-Chul;Kim, Eun-Kyou;Bang, Hyo-Choong
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.35 no.9
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    • pp.836-842
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    • 2007
  • This paper describes the development of an automated operational orbit processing system (KGS automated Operational Orbit Processing System, KOOPS), which can determine, evaluate, update, and generate the orbit data automatically. Developed system can be applied to the multi satellite mission operations as a generic satellite orbit processing system in that the KOOPS has a capability to process various kinds of tracking data and assign pre and post processes according to the satellite system respectively. Results of applying the KOOPS to the KOMPSAT-1 and KOMPSAT-2 mission operations show that man power is greatly reduced and the efficiency and stability of the mission operations are significantly increased. The experiences to develop the KOOPS and operate multi satellite missions using this system can be applied to enhance the multi and generic flight dynamics system further.

Design and Implementation of a RESTful SOAP-based Slip Data Processing System (RESTful SOAP 기반 전표 데이터 처리 시스템 설계 및 구현)

  • Hwang Eui-Chul
    • The Journal of the Korea Contents Association
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    • v.5 no.1
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    • pp.101-108
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    • 2005
  • In this paper, we propose a design methodology of RESTful SOAP-based web services which try to solve extensibility problem of SOAP-based Web service by adopting REST concept into SOAP. And, we apply the proposed RESTful SOAP-based web services design methodology in constructing slip data processing web services, compare it with simple SOAP-based slip data web services, and try to propose a model for building Web Services in the future. REST is a model about architecture type of web distributed computing , the biggest distributed application in the world. In REST, identification of resources are made by URI, states(resources) are represented by document described by XML and transferred through HTTP our proposed RESTful SOAP-based web services are expected to contribute to constructing useful world wide web services which are essential in building E-Commerce society.

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A Study on the Intelligent 3D Foot Scanning System (인공지능형 삼차원 Foot Scanning 시스템에 관한 연구)

  • Kim, Young-Tak;Park, Ju-Won;Tack, Han-Ho;Lee, Sang-Bae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.7
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    • pp.871-877
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    • 2004
  • In this paper, for manufacturing a custom-made shoes, shape of foot acquired three-dimensional measurement device which makes shoe-last data for needing a custom-made shoes is founded on artificial intelligence technique and it shows method restoring to the original shape in optimized state. the developed system for this study is based on PC which uses existing three dimensional measurement method. And it gains shoe-last and data of foot shape going through 8 CCD(Charge Coupled Device) Which equipped top and bottom, right and left sides and 4 lasers which also equipped both sides and upper and lower sides. The acquired data are processed image processing algorithm using artificial intelligence technique. And result of data management is better quality of removing noise than other system not using artificial intelligence technique and it can simplify post-processing. So, this paper is constituted hardware and software system and it used neural network for determining threshold value, when input image on pre-processing step is being stage of image binarization and present that results.

A Study on GNSS Data Pre-processing for Analyzing Geodetic Effects on Crustal Deformation due to the Earthquake (지진에 의한 측지학적 지각변동 분석을 위한 GNSS 자료 전처리 연구)

  • Sohn, Dong Hyo;Kim, Du Sik;Park, Kwan Dong
    • Journal of Korean Society for Geospatial Information Science
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    • v.23 no.1
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    • pp.47-54
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    • 2015
  • In this study, we developed strategies for pre-processing GNSS data for the purpose of separating geodetic factors from crustal deformation due to the earthquakes. Before interpreting GNSS data analysis results, we removed false signals from GNSS coordinate time series. Because permanent GNSS stations are located on a large tectonic plate, GNSS position estimates should be affected by the tectonic velocity of the plate. Also, stations with surrounding trees have seasonal signals in their three-dimensional coordinate estimates. Thus, we have estimated the location of an Euler pole and angular velocities to deduce the plate tectonic velocity and verified with geological models. Also, annual amplitudes and initial phases were estimated to get rid of those false annual signals showing up in the time series. By considering the two effects, truly geodetic analysis was possible and the result was used as preliminary data for analyzing post-seismic deformation of the Korean peninsula due to the Tohoku-oki earthquake.