• 제목/요약/키워드: Pre-verification

검색결과 322건 처리시간 0.021초

기계학습을 통한 전기화재 예측모델 연구 (Electrical fire prediction model study using machine learning)

  • 고경석;황동현;박상준;문가경
    • 한국정보전자통신기술학회논문지
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    • 제11권6호
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    • pp.703-710
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    • 2018
  • 매년 전기화재사고에 대한 사고유형 분석, 점검 등 전기적 화재사고를 줄이기 위해 다양한 노력이 있었으나, 효율적인 의사결정지원 체계 및 기존 누적 데이터 활용방안의 미비로 효과적인 대처방안이 부재한 현황이다. 본 연구는 전기안전점검데이터, 전기화재사고정보, 건축물정보, 기상청정보 등 데이터 기반의 전기화재를 예측하는 알고리즘을 개발하고 이를 활용하여 전기화재사고를 줄이는데 목적이 있다. 본 연구에서는 한국전기안전공사, 기상청, 국토교통부, 소방본부 등 기관별로 수집된 데이터를 전처리, 융합, 분석, 모델링, 검증 과정을 거쳐 전기화재에 영향을 끼치는 요인과 예측모델을 도출하였다. 주요요인으로 절연저항 값, 습도, 풍속, 건축물 노후년수, 용적율, 건폐율, 건축물용도로 나타났고, Random forest 알고리즘을 활용한 예측모델은 74.7%의 정확도를 얻었다.

QAR 데이터 분석을 통한 항공난류 조기 인지 가능성 연구 (A Study on the Precursors of Aviation Turbulence via QAR Data Analysis)

  • 김인규;장조원
    • 한국항공운항학회지
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    • 제26권4호
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    • pp.36-42
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    • 2018
  • Although continuous passenger injuries and physical damages are repeated due to the unexpected aviation turbulence encountered during operations, there is still exist the limitation for preventing recurrence of similar events because the lack of real-time information and delay in technological developments regarding various operating conditions and variable weather phenomena. The purpose of this study is to compare and analyze the meteorological data of the aviation turbulence occurred and actual flight data extracted from the Quick Access Recorder(QAR) to provide some precursors that the pilot can identify aviation turbulence early by referring thru the flight instrumentation indications. The case applied for this study was recent event, a scheduled flight from Incheon Airport, Korea to Narita Airport, Japan that suddenly encountered turbulence at an altitude of approximately 14,000 feet during approach. According to the Korea Meteorological Administration(KMA)'s Regional Data Assessment and Prediction System(RDAPS) data, it was observed that the strong amount of vorticity in the rear area of jet stream, which existed near Mount Fuji at that time. The QAR data analysis shows significant changes in the aircraft's parameters such as Pitch and Roll angle, Static Air Temperature(SAT), and wind speed and direction in tens of seconds to minutes before encounter the turbulence. If the accumulate reliability of the data in addition and verification of various parameters with continuous analysis of additional cases, it can be the precursors for the pilot's effective and pre-emptive action and conservative prevention measures against aviation turbulence to reduce subsequent passenger injuries in the aviation operations.

FEA based optimization of semi-submersible floater considering buckling and yield strength

  • Jang, Beom-Seon;Kim, Jae Dong;Park, Tae-Yoon;Jeon, Sang Bae
    • International Journal of Naval Architecture and Ocean Engineering
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    • 제11권1호
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    • pp.82-96
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    • 2019
  • A semi-submersible structure has been widely used for offshore drilling and production of oil and gas. The small water plane area makes the structure very sensitive to weight increase in terms of payload and stability. Therefore, it is necessary to lighten the substructure from the early design stage. This study aims at an optimization of hull structure based on a sophisticated yield and buckling strength in accordance with classification rules. An in-house strength assessment system is developed to automate the procedure such as a generation of buckling panels, a collection of required panel information, automatic buckling and yield check and so on. The developed system enables an automatic yield and buckling strength check of all panels composing the hull structure at each iteration of the optimization. Design variables are plate thickness and stiffener section profiles. In order to overcome the difficulty of large number of design variables and the computational burden of FE analysis, various methods are proposed. The steepest descent method is selected as the optimization algorithm for an efficient search. For a reduction of the number of design variables and a direct application to practical design, the stiffener section variable is determined by selecting one from a pre-defined standard library. Plate thickness is also discretized at 0.5t interval. The number of FE analysis is reduced by using equations to analytically estimating the stress changes in gradient calculation and line search steps. As an endeavor to robust optimization, the number of design variables to be simultaneously optimized is divided by grouping the scantling variables by the plane. A sequential optimization is performed group by group. As a verification example, a central column of a semi-submersible structure is optimized and compared with a conventional optimization of all design variables at once.

4축 이적재 로봇의 주요 부품 선정을 위한 동적 해석 (Dynamic Analysis to Select Main Parts of Four-Axis Palletizing Robots)

  • 박일환;전용재;고아라;설상석;홍대선
    • 한국기계가공학회지
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    • 제19권12호
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    • pp.62-69
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    • 2020
  • The demand for industrial robots is proliferating with production automation. Industrial robots are used in various fields, such as logistics, welding, and assembly. Generally, six degrees of freedom are required to move freely in space. However, the palletizing robot used for material management and logistics systems typically has four degrees of freedom. In designing such robots, their main parts, such as motors and reducers, need to be adequately selected while satisfying payload requirements and speed. Hence, this study proposes a practical method for selecting the major parts based on dynamic analysis using ADAMS. First, the acceleration torques for the robot motion were found from the analysis, and then the friction torques were evaluated. This study introduces a constant-speed torque constant instead of friction coefficient. The RMS torque and maximum power of each motor were found considering the above torques. After that, this study recommends the major specifications of all motors and reducers. The proposed method was applied to a palletizing robot to verify the suitability of the pre-selected main parts. The verification result shows that the proposed method can be successfully applied to the early design stage of industrial robots.

DoS 공격에 강한 무선 랜 인증 프로토콜 (DoS-Resistance Authentication Protocol for Wreless LAN)

  • 김민현;이재욱;최영근;김순자
    • 정보보호학회논문지
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    • 제14권5호
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    • pp.3-10
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    • 2004
  • 무선 랜은 액세스 포인트를 경유하여 인터넷을 사용할 수 있기 때문에 접근 제어의 중요성을 가지고 있다. 또한 무선 랜을 이용하기 위해서는 EAP의 인증과정을 거치게 된다. 이러한 액세스 포인트 접근과 인증 과정에 대한 치명적인 공격 중의 하나가 DoS(Denial of Service) 공격이다. 즉 악의적인 공격자가 액세스 포인트의 접근을 막거나 또는 인증 과정에서 서버의 메모리 및 중앙처리장치의 계산 능력 등을 강제적으로 소비시킴으로써 합법적인 사용자가 서비스를 받지 못하게 한다. 본 논문에서는 무선 랜에 대한 DoS 공격을 접근 제어, 자원의 할당, 인증프로토콜 상에서의 공격으로 나누어 각 공격에 대한 방어법을 제시하였다. 액세스 포인트 접근에 대한 문제는 사전 검증 단계 및 보안 수준 변수에 의해, 자원의 할당에 대한 공격은 부분적인 stateless 프로토콜에 의해, 프로토콜상의 약점은 타임스템프와 접근 제한 변수에 의해 개선하였다.

딥러닝을 이용한 자율 이륙 드론 알고리즘 제안 (Proposal of autonomous take-off drone algorithm using deep learning)

  • 이종구;장민석;이연식
    • 한국정보통신학회논문지
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    • 제25권2호
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    • pp.187-192
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    • 2021
  • 본 연구는 객체 검출기를 이용하여 숲 혹은 그에 준하는 복잡한 환경에서의 이륙에 대한 시스템을 제안한다. 시뮬레이터에서 대각선상의 모터간 550mm의 길이를 갖는 쿼드콥터에 라즈베리파이를 장착하여 엣지 컴퓨팅 기반으로 실험을 진행한다. 학습에 사용될 이미지는 군산대학교 내부의 세 지점을 선정하여 640⁎480 사이즈의 이미지를 150장 내외 정도 획득하였으며, 이들을 흑백으로 변환한 다음, 127의 경계값을 두어 이진화 전처리를 하였다. 이후 SSD_Inception 모델을 학습 하였다. 시뮬레이션상에서 검증용 영상을 입력으로 학습한 모델을 통해 드론을 이륙시키는 실험 결과, 라벨을 이용하여 이륙했을 때와 유사한 궤적을 그려내었다.

머신러닝 기반 신체 계측정보를 이용한 CT 피폭선량 예측모델 비교 (Comparison of CT Exposure Dose Prediction Models Using Machine Learning-based Body Measurement Information)

  • 홍동희
    • 대한방사선기술학회지:방사선기술과학
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    • 제43권6호
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    • pp.503-509
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    • 2020
  • This study aims to develop a patient-specific radiation exposure dose prediction model based on anthropometric data that can be easily measurable during CT examination, and to be used as basic data for DRL setting and radiation dose management system in the future. In addition, among the machine learning algorithms, the most suitable model for predicting exposure doses is presented. The data used in this study were chest CT scan data, and a data set was constructed based on the data including the patient's anthropometric data. In the pre-processing and sample selection of the data, out of the total number of samples of 250 samples, only chest CT scans were performed without using a contrast agent, and 110 samples including height and weight variables were extracted. Of the 110 samples extracted, 66% was used as a training set, and the remaining 44% were used as a test set for verification. The exposure dose was predicted through random forest, linear regression analysis, and SVM algorithm using Orange version 3.26.0, an open software as a machine learning algorithm. Results Algorithm model prediction accuracy was R^2 0.840 for random forest, R^2 0.969 for linear regression analysis, and R^2 0.189 for SVM. As a result of verifying the prediction rate of the algorithm model, the random forest is the highest with R^2 0.986 of the random forest, R^2 0.973 of the linear regression analysis, and R^2 of 0.204 of the SVM, indicating that the model has the best predictive power.

한국어 기계독해 기반 법률계약서 리스크 예측 모델 (Risk Prediction Model of Legal Contract Based on Korean Machine Reading Comprehension)

  • 이치훈;노지우;정재훈;주경식;이동희
    • 한국IT서비스학회지
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    • 제20권1호
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    • pp.131-143
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    • 2021
  • Commercial transactions, one of the pillars of the capitalist economy, are occurring countless times every day, especially small and medium-sized businesses. However, small and medium-sized enterprises are bound to be the legal underdogs in contracts for commercial transactions and do not receive legal support for contracts for fair and legitimate commercial transactions. When subcontracting contracts are concluded among small and medium-sized enterprises, 58.2% of them do not apply standard contracts and sign contracts that have not undergone legal review. In order to support small and medium-sized enterprises' fair and legitimate contracts, small and medium-sized enterprises can be protected from legal threats if they can reduce the risk of signing contracts by analyzing various risks in the contract and analyzing and informing them of toxic clauses and omitted contracts in advance. We propose a risk prediction model for the machine reading-based legal contract to minimize legal damage to small and medium-sized business owners in the legal blind spots. We have established our own set of legal questions and answers based on the legal data disclosed for the purpose of building a model specialized in legal contracts. Quantitative verification was carried out through indicators such as EM and F1 Score by applying pine tuning and hostile learning to pre-learned machine reading models. The highest F1 score was 87.93, with an EM value of 72.41.

Development of the Contents of AI Convergence Education Method Subjects and Verification of Teaching Efficacy Effectiveness for Elementary and Secondary Teachers

  • Kim, Jeong-Rang
    • 한국컴퓨터정보학회논문지
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    • 제27권3호
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    • pp.217-223
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    • 2022
  • 본 논문에서는 초중등 교사를 대상으로 AI융합교육 전공 교과목 중 'AI융합교육방법' 수강자의 요구와 환경을 분석하고 이를 바탕으로 교과목을 개발 및 적용하여 정보교육 교수효능감에 대한 효과성을 검증하였다. 연구를 위해 'AI융합교육방법' 과목을 수강하는 초중등 교사를 연구 대상으로 선정하여 대상의 일반적인 특성과 사전 지식 수준, 교육내용 요구를 조사·분석한 결과를 바탕으로 'AI융합교육방법' 교과목의 영역, 15주의 교수·학습 내용을 개발하였다. 개발된 'AI융합교육방법' 과목을 15주간 대상에게 적용하여 정보교육 교수효능감에 대한 효과성을 검사하고 분석한 결과, 정보교육 교수효능감은 적용 전에 비해 통계적으로 유의미하게 향상된 것으로 나타났다. 정보교육 교수효능감의 하위요소 중 정보 수업 가치관, 정보 교수 전략에서 유의미한 차이가 나타났다. 향후 학교 현장과의 연계, 타 교과와의 융합 등 교사 전문성 확보를 위한 후속 연구 진행이 필요하며, 교수학습 자료, 인공지능 교육용 플랫폼 등 다양한 자료와 교수학습 방법이 체계적으로 마련될 필요가 있다.

지면환경이 크로스핏 선수의 프론트 스쿼트에 미치는 영향 (Effect of Surface Environment on Front Squat of Crossfit Athletes)

  • Jang, Yootae;Yoon, Sukhoon
    • 한국운동역학회지
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    • 제32권2호
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    • pp.49-55
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    • 2022
  • Objective: This study aims to verify the front squat motions using by two different surfaces, thereby elucidating the grounds for effective training environment that can minimize the risk of injury. Method: Total of 10 healthy male crossfit athletes were recruited for this study (age: 32.30 ± 3.05 yrs., height: 173.70 ± 5.12 cm, body mass: 82.40 ± 6.31 kg, 1RM: 160 ± 13.80 kg). All participants are those who know how to do front squats well with more than five years of crossfit athlete experience. All participants have sufficient experience in front squats on two types of surface which are soft surface (SS) and hard surface (HS). In each surface, participant perform 10reps of the front squat with 80% of the pre-measured 1RM. A 3-dimensional motion analysis with 8 infrared cameras and 2 channels of EMG was performed in this study. Paired sample t-test was used for statistical verification between two surfaces. The significant level was set at α=.05. Results: The significantly decreased rectus femoris muscle activation was found in SS compared with that of HS on phase 1 (p<.05). Also, ROM of ankle joint was significantly increased in the SS compare with that of HS on phase 1 (p<.05). The muscle activity ratio of gluteus maximus/rectus femoris showed a significant difference only in SS compared with that of HS on phase 1 (p<.05). Conclusion: In conclusion, Korean crossfit boxes should consider the use of hard surface, which has a relatively less risk of injury than soft surface, in selecting flooring materials. For the Crossfit athletes, they are also considered appropriate to train on a relatively hard surface.