• Title/Summary/Keyword: Blackbox

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A Security-Enhanced Storing Method for the Voice Data in the Aircraft (항공기에서 보안 강화된 음성 데이터 저장 방식)

  • Cho, Seung Hoon;Suh, Jeong Bae;Moon, Yong Ho
    • IEMEK Journal of Embedded Systems and Applications
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    • v.6 no.4
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    • pp.255-261
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    • 2011
  • In this paper, we propose a security-enhanced storing method for the voice data obtained during the flight. When an emergency occurs during flight, the flight data in the storage device such as DTS or Blackbox can be exposed to antagonist or enemy. Currently, zeroize function is embedded in these devices in order to prevent this situation. However, this could not be operated if the system is malfunctioned or the pilot is wounded in the emergency. In order to solve this problem, the voice data compressed by the ADPCM is encrypted in the proposed method composed of the AES algorithm and a reordering method. The simulation results show that the security for the voice date is further enhanced due to the proposed method.

An Estimating Algorithm of Vehicle Collision Speed Through Images of Blackbox (블랙박스 영상 분석을 통한 차량 충돌 속도 연산 알고리즘에 대한 융복합 연구)

  • Ko, Kwang-Ho
    • Journal of Digital Convergence
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    • v.16 no.9
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    • pp.173-178
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    • 2018
  • The vehicle collision speed in mid and high range can be checked by EDM(Event Driven memory) data recorded when the air bag works. But it's difficult to estimate the low speed of vehicle collision. And estimating the speed is important because the injury level can be changed by the impact speed. The study proposed an estimating algorithm by analysing the images recorded in car blackbox instrument. Low speed rear collision accidents simulated with wire winding motor for various vehicle types. The study estimated the impact speed with the ratio of the distance change between two vehicles and the length change of the number plate of front vehicle. The closer the vehicles are, the larger the plate length is. You can estimate the impact speed with the ratio. The impact speed is calculated with the initial distance for a specific length of number plate in the algorithm. The results can be applied to the linear rear collision because the angle of impact was not considered in this study.

Blackbox-Based a Vehicle Emergency Situation Detection and Notification System (블랙박스 기반의 차량용 응급상황 감지 및 통보시스템)

  • Kwon, Doo-Wy;Lee, Hoon-Jae;Park, Su-Hyun;Do, Kyeong-Hoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.11
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    • pp.2423-2428
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    • 2010
  • The number of motor vehicle registrations in Korea is increasing steadily each year, driven by industry development and economic growth. The number of traffic accidents is also rapidly increasing. Korea has a relatively high number of traffic accidents among OECD member countries, and it ranks among the highest in traffic accident death rates. This death rate is higher compared to death rates as a proportion of the number of traffic accidents in each country. It is very common for drivers to lose consciousness in traffic collisions, which leads to a failure to carry out early emergency measures. In order to prevent such situations as well as hit-and-runs and people left uncared for after traffic accidents, there is a need for motor vehicle black boxes and accident report systems. This study addressed the need for an emergency evacuation system for people injured in traffic accidents and a secondary traffic accident prevention system by developing a motor vehicle emergency situation detection and report system combined with a black box, and materializing it as an actual system.

Formal Specification and Modeling Techniques of Component Workflow Variability (컴포넌트 워크플로우 가변성의 정형 명세 및 모델링 기법)

  • Lee, Jong-Kook;Cho, Eun-Sook;Kim, Soo-Dong
    • Journal of KIISE:Software and Applications
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    • v.29 no.10
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    • pp.703-725
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    • 2002
  • It is well recognized that component-based development (CBD) is an effective approach to manage the complexity of modem software development. To achieve the benefits of low-cost development and higher productivity, effective techniques to maximize component reusability should be developed. Component is a set of related concepts and objects, and provides a particular coarse-grained business service. Often, these components include various message flows among the objects in the component, called 'business workflow`. Blackbox components that include but hide business workflow provide higher reusability and productivity. A key difficulty of using blackbox components with business workflow is to let the workflow be customized by each enterprise. In this paper, we provide techniques to model the variability of family members and to customize the business workflow of components. Our approach is to provide formal specification on the component variability, and to define techniques to customize them by means of the formalism.

Vehicle Dynamic Simulation Using the Neural Network Bushing Model (인공신경망 부싱모델을 사용한 전차량 동역학 시뮬레이션)

  • 손정현;강태호;백운경
    • Transactions of the Korean Society of Automotive Engineers
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    • v.12 no.4
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    • pp.110-118
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    • 2004
  • In this paper, a blackbox approach is carried out to model the nonlinear dynamic bushing model. One-axis durability test is performed to describe the mechanical behavior of typical vehicle elastomeric components. The results of the tests are used to develop an empirical bushing model with an artificial neural network. The back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra's algorithm of ‘NARMAX’ form is employed in the neural network bushing module. A numerical example is carried out to verify the developed bushing model.

Empirical Bushing Model For Vehicle Dynamic Analysis (차량동역학해석을 위한 실험적 부싱모델 개발)

  • Sohn, Jeong-Hyun;Kang, Tae-Ho;Baek, Woon-Kyung;Park, Dong-Woon;Yoo, Wan-Suk
    • Proceedings of the KSME Conference
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    • 2004.04a
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    • pp.864-869
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    • 2004
  • In this paper, a blackbox approach is carried out to model the nonlinear dynamic bushing model. One-axis durability test is performed to describe the mechanical behavior of typical vehicle elastomeric components. The results of the tests are used to develop an empirical bushing model with an artificial neural network. The back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra's algorithm of 'NARMAX' form is employed in the neural network bushing module. A numerical example is carried out to verify the developed bushing model.

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Empirical Bushing Model using Artificial Neural Network (인공신경망을 이용한 실험적 부싱모델링)

  • 손정현;유완석;박동운
    • Transactions of the Korean Society of Automotive Engineers
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    • v.11 no.4
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    • pp.151-157
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    • 2003
  • In this paper, a blackbox approach is carried out to model the nonlinear dynamic bushing model. One-axis durability test is performed to describe the mechanical behavior of typical vehicle elastomeric components. The results of the tests are used to develop an empirical bushing model with an artificial neural network. The back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra algorithm of 'NARMAX' form is employed to consider these effects. A numerical example is carried out to verify the developed bushing model.

Video Blackbox Modeling For Car Accident Reconstruction (자동차 사고재현을 위한 영상블랙박스 모델링)

  • Bak, Chang-Gyu;Choi, Yo-Han;Han, Seong-Deok;Lee, Jun-Hee;Moon, Ho-Sun;Kim, Yong-Deuk;Lee, Jung-Won
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.10b
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    • pp.308-312
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    • 2007
  • 최근 차량용 블랙박스는 단순히 차속 및 주행 거리를 기록하는 차량 운행 기록기의 기능을 넘어, 각종 센서 및 영상 처리, GPS 장치 등을 통하여 수집된 정보를 토대로 자동차 사고 분석이나 부품 결함을 발견할 수 있는 기능을 추가 하는 것을 목표로 하고 있다. 본 논문은 자동차로부터 얻을 수 있는 정보를 다각도로 분류해 보고 자동차 사고 중 가장 놓은 비율을 차지하고 있는 차대차 사고재현을 위한 필수적인 파라미터를 선정함으로써 제한된 프로세싱 자원 하에서 사고 재현 효과를 극대화 할 수 있는 영상 블랙박스 모델을 제안하고 수집된 파라미터의 분석 절차를 제시한다.

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Deep Learning Method for Identification and Selection of Relevant Features

  • Vejendla Lakshman
    • International Journal of Computer Science & Network Security
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    • v.24 no.5
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    • pp.212-216
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    • 2024
  • Feature Selection have turned into the main point of investigations particularly in bioinformatics where there are numerous applications. Deep learning technique is a useful asset to choose features, anyway not all calculations are on an equivalent balance with regards to selection of relevant features. To be sure, numerous techniques have been proposed to select multiple features using deep learning techniques. Because of the deep learning, neural systems have profited a gigantic top recovery in the previous couple of years. Anyway neural systems are blackbox models and not many endeavors have been made so as to examine the fundamental procedure. In this proposed work a new calculations so as to do feature selection with deep learning systems is introduced. To evaluate our outcomes, we create relapse and grouping issues which enable us to think about every calculation on various fronts: exhibitions, calculation time and limitations. The outcomes acquired are truly encouraging since we figure out how to accomplish our objective by outperforming irregular backwoods exhibitions for each situation. The results prove that the proposed method exhibits better performance than the traditional methods.