• Title/Summary/Keyword: 자동차 모델 인식

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Customer participatory design for mass customization(Focused on development of interactive design toolkit) (매스커스터마이제이션을 위한 소비자 참여 디자인 방법(인터랙티브 디자인 툴킷의 개발을 중심으로))

  • 변재형
    • Archives of design research
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    • v.16 no.4
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    • pp.5-14
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    • 2003
  • This study suggest the development and application of the Interactive Design Toolkit as a participatory design method for general customer who are non-expert on design activity to participate in design process of mass customization. In order to let general customers to express their design needs, we have to make a familiar and direct communication method for them. And, customer's design needs should be transformed into digital media. This study define the Interactive Design Toolkit as a design tool for customer participation by direct manipulation of computer system for simulation of design needs by customer themselves. The Interactive Design Toolkit is based on a PC-based image perception system and its application. User can make virtual models in virtual space by manipulating physical objects in real world. And, The toolkit can be used in the field of participatory design for deliverer side customization, especially in system kitchen which is manufactured and distributed in modular system. More improved design toolkit for manipulating 3 dimensional shape is needed for consumer product design and car styling.

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Research on the development of automated tools to de-identify personal information of data for AI learning - Based on video data - (인공지능 학습용 데이터의 개인정보 비식별화 자동화 도구 개발 연구 - 영상데이터기반 -)

  • Hyunju Lee;Seungyeob Lee;Byunghoon Jeon
    • Journal of Platform Technology
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    • v.11 no.3
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    • pp.56-67
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    • 2023
  • Recently, de-identification of personal information, which has been a long-cherished desire of the data-based industry, was revised and specified in August 2020. It became the foundation for activating data called crude oil[2] in the fourth industrial era in the industrial field. However, some people are concerned about the infringement of the basic rights of the data subject[3]. Accordingly, a development study was conducted on the Batch De-Identification Tool, a personal information de-identification automation tool. In this study, first, we developed an image labeling tool to label human faces (eyes, nose, mouth) and car license plates of various resolutions to build data for training. Second, an object recognition model was trained to run the object recognition module to perform de-identification of personal information. The automated personal information de-identification tool developed as a result of this research shows the possibility of proactively eliminating privacy violations through online services. These results suggest possibilities for data-based industries to maximize the value of data while balancing privacy and utilization.

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Speech Enhancement System Using a Model of Auditory Mechanism (청각기강의 모델을 이용한 음성강조 시스템)

  • 최재승
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.6
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    • pp.295-302
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    • 2004
  • On the field of speech processing the treatment of noise is still important problems for speech research. Especially, it has been noticed that the background noise causes remarkable reduction of speech recognition ratio. As the examples of the background noise, there are such various non-stationary noises existing in the real environment as driving noise of automobiles on the road or typing noise of printer. The treatment for these kinds of noises is not so simple as could be eliminated by the former Wiener filter, but needs more skillful techniques. In this paper as one of these trials, we show an algorithm which is a speech enhancement method using a model of mutual inhibition for noise reduction in speech which is contaminated by white noise or background noise mentioned above. It is confirmed that the proposed algorithm is effective for the speech degraded not only by white noise but also by colored noise, judging from the spectral distortion measurement.

Intrinsic and Extrinsic Factors Affecting Use of Sharing Economy Services and the Moderating Effect of Benefits (공유경제 서비스 사용에 영향을 미치는 사용자의 내외적 요인과 이익의 조절효과)

  • Kim, Sanghyun;Park, Hyunsun;Lim, Jeongtaek
    • The Journal of the Korea Contents Association
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    • v.20 no.12
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    • pp.482-491
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    • 2020
  • This study proposed a research model based on self-determination theory and unified theory of acceptance and use of technology to explain the factors influencing intention to use sharing economy services. A total of 392 responses were collected, and structural equation analysis was performed with AMOS 22.0. The results are summarized as follows. First, self-technological aptness and trust had a positive effect on intention to use sharing economy services. Second, access bigger market and environmental friendliness had a positive effect on intention to use sharing economy services. Third, intention to use sharing economy services had a positive effect on actual usage of sharing economy services. Finally, benefits was found to strengthen the relationship between intention to use sharing economy services and actual usage of sharing economy services. The findings of this study would provide a theoretical framework for sharing economy services and important information for understanding individuals using the sharing economy services.

A Study on the Trigger Technology for Vehicle Occupant Detection (차량 탑승 인원 감지를 위한 트리거 기술에 관한 연구)

  • Lee, Dongjin;Lee, Jiwon;Jang, Jongwook;Jang, Sungjin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.05a
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    • pp.120-122
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    • 2021
  • Currently, as demand for cars at home and abroad increases, the number of vehicles is decreasing and the number of vehicles is increasing. This is the main cause of the traffic jam. To solve this problem, it operates a high-ocompancy vehicle (HOV) lane, a multi-passenger vehicle, but many people ignore the conditions of use and use it illegally. Since the police visually judge and crack down on such illegal activities, the accuracy of the crackdown is low and inefficient. In this paper, we propose a system design that enables more efficient detection using imaging techniques using computer vision to solve such problems. By improving the existing vehicle detection method that was studied, the trigger was set in the image so that the detection object can be selected and the image analysis can be conducted intensively on the target. Using the YOLO model, a deep learning object recognition model, we propose a method to utilize the shift amount of the center point rather than judging by the bounding box in the image to obtain real-time object detection and accurate signals.

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Voice Activity Detection Method Using Psycho-Acoustic Model Based on Speech Energy Maximization in Noisy Environments (잡음 환경에서 심리음향모델 기반 음성 에너지 최대화를 이용한 음성 검출 방법)

  • Choi, Gab-Keun;Kim, Soon-Hyob
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.5
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    • pp.447-453
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    • 2009
  • This paper introduces the method for detect voices and exact end point at low SNR by maximizing voice energy. Conventional VAD (Voice Activity Detection) algorithm estimates noise level so it tends to detect the end point inaccurately. Moreover, because it uses relatively long analysis range for reflecting temporal change of noise, computing load too high for application. In this paper, the SEM-VAD (Speech Energy Maximization-Voice Activity Detection) method which uses psycho-acoustical bark scale filter banks to maximize voice energy within frames is introduced. Stable threshold values are obtained at various noise environments (SNR 15 dB, 10 dB, 5 dB, 0 dB). At the test for voice detection in car noisy environment, PHR (Pause Hit Rate) was 100%accurate at every noise environment, and FAR (False Alarm Rate) shows 0% at SNR15 dB and 10 dB, 5.6% at SNR5 dB and 9.5% at SNR0 dB.

Estimating Car-sharing Demand of Young People for Parking-Free Apartment House in the Future (미래형 공동주택의 청년계층 카셰어링 이용수요 분석)

  • Shin, Doh Kyoum;Kee, Hoyoung;Byun, Wanhee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.19 no.5
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    • pp.119-137
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    • 2020
  • Over the last two decades, the attitudes to cars have changed from buying a car to sharing a car, especially among young people. Shared transport services and autonomous vehicles together can resolve the accessibility issue of shared transport services. Furthermore, they will make it possible to develop a new model of apartments without car parking. Therefore, the study estimated the demand for car sharing by young people and the running efficiency of car-sharing dealing with their car-based trip demand. The study chose nine apartment complexes for study sites where a majority of the residents were young people. The questionnaire survey was conducted to collect data on the trip demands of young people. The results showed that there are significant differences in the car-sharing use patterns and demand between the apartment houses located in the Capital region and non-capital region. Young people living in apartments in the Capital region used car sharing once per day per person for approximately 80 minutes per trip and tended to hire that between 8 AM and 10 AM. On the other hand, the young people living in apartments in the non-capital region used car sharing twice per day per person for approximately 200 minutes per trip. They tended to hire that frequently in the afternoon and evening as well as in the morning. The results also showed that a single car-sharing vehicle could deal with 3~4 trips per day in the Capital region and around 2 trips per day in the non-capital region.

A Study on Verification of the effectiveness of Mutually Recognizable Traffic Safety Facilities (상호인식 교통안전시설물 현장적용에 따른 효과검증 연구)

  • Kim, Ki-Nam;Jeong, Yong-Ho;Lee, Min-jae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.12
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    • pp.468-474
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    • 2019
  • Korea had the highest accident rate among OECD countries in 2018, with 8.4 per 100,000 population, ranking 4th among 35 countries. In addition, the accident rate of traffic with children and the elderly was also high. This study reviewed the relevant literature and analyzed the traffic-accident analysis system. Customized traffic safety facilities were developed. In addition, by measuring the visibility of the traffic safety facilities by installing a test bed, this study measured the forward driving frequency and vehicle driving speed while driving. As a result of applying the "pedestrian pedestrian model" collision test model, the possibility of serious injury after installing the facility was reduced greatly to 4.6%. In this study, the visibility of traffic safety facilities and the effect of reducing the traffic speed were verified through test beds. Recognizing traffic safety facilities will reduce traffic accidents.

Design of a designated lane enforcement system based on deep learning (딥러닝 기반 지정차로제 단속 시스템 설계)

  • Bae, Ga-hyeong;Jang, Jong-wook;Jang, Sung-jin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.236-238
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    • 2022
  • According to the current Road Traffic Act, the 2020 amendment bill is currently in effect as a system that designates vehicle types for each lane for the purpose of securing road use efficiency and traffic safety. When comparing the number of traffic accident fatalities per 10,000 vehicles in Germany and Korea, the number of traffic accident deaths in Germany is significantly lower than in Korea. The representative case of the German autobahn, which did not impose a speed limit, suggests that Korea's speeding laws are not the only answer to reducing the accident rate. The designated lane system, which is observed in accordance with the keep right principle of the Autobahn Expressway, plays a major role in reducing traffic accidents. Based on this fact, we propose a traffic enforcement system to crack down on vehicles violating the designated lane system and improve the compliance rate. We develop a designated lane enforcement system that recognizes vehicle types using Yolo5, a deep learning object recognition model, recognizes license plates and lanes using OpenCV, and stores the extracted data in the server to determine whether or not laws are violated.Accordingly, it is expected that there will be an effect of reducing the traffic accident rate through the improvement of driver's awareness and compliance rate.

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A basic study on explosion pressure of hydrogen tank for hydrogen fueled vehicles in road tunnels (도로터널에서 수소 연료차 수소탱크 폭발시 폭발압력에 대한 기초적 연구)

  • Ryu, Ji-Oh;Ahn, Sang-Ho;Lee, Hu-Yeong
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.23 no.6
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    • pp.517-534
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    • 2021
  • Hydrogen fuel is emerging as an new energy source to replace fossil fuels in that it can solve environmental pollution problems and reduce energy imbalance and cost. Since hydrogen is eco-friendly but highly explosive, there is a high concern about fire and explosion accidents of hydrogen fueled vehicles. In particular, in semi-enclosed spaces such as tunnels, the risk is predicted to increase. Therefore, this study was conducted on the applicability of the equivalent TNT model and the numerical analysis method to evaluate the hydrogen explosion pressure in the tunnel. In comparison and review of the explosion pressure of 6 equivalent TNT models and Weyandt's experimental results, the Henrych equation was found to be the closest with a deviation of 13.6%. As a result of examining the effect of hydrogen tank capacity (52, 72, 156 L) and tunnel cross-section (40.5, 54, 72, 95 m2) on the explosion pressure using numerical analysis, the explosion pressure wave in the tunnel initially it propagates in a hemispherical shape as in open space. Furthermore, when it passes the certain distance it is transformed a plane wave and propagates at a very gradual decay rate. The Henrych equation agrees well with the numerical analysis results in the section where the explosion pressure is rapidly decreasing, but it is significantly underestimated after the explosion pressure wave is transformed into a plane wave. In case of same hydrogen tank capacity, an explosion pressure decreases as the tunnel cross-sectional area increases, and in case of the same cross-sectional area, the explosion pressure increases by about 2.5 times if the hydrogen tank capacity increases from 52 L to 156 L. As a result of the evaluation of the limiting distance affecting the human body, when a 52 L hydrogen tank explodes, the limiting distance to death was estimated to be about 3 m, and the limiting distance to serious injury was estimated to be 28.5~35.8 m.