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The Study on Applying Ankle Joint Load Variable Lower-Knee Prosthesis to Development of Terrain-Adaptive Above-Knee Prosthesis (노면 적응형 대퇴 의족개발을 위한 발목 관절 부하 가변형 하퇴 의족 적용에 대한 연구)

  • Eom, Su-Hong;Na, Sun-Jong;You, Jung-Hwun;Park, Se-Hoon;Lee, Eung-Hyuk
    • Journal of IKEEE
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    • v.23 no.3
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    • pp.883-892
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    • 2019
  • This study is the method which is adapted to control ankle joint movement for resolving the problem of gait imbalance in intervals where gait environments are changed and slope walking, as applying terrain-adaptive technique to intelligent above-knee prosthesis. In this development of above-knee prosthesis, to classify the gait modes is essential. For distinguishing the stance phases and the swing phase depending on roads, a machine learning which combines decision tree and random forest from knee angle data and inertial sensor data, is proposed and adapted. By using this method, the ankle movement state of the prosthesis is controlled. This study verifies whether the problem is resolved through butterfly diagram.

Emergency vehicle priority signal system based on deep learning using acoustic data (음향 데이터를 활용한 딥러닝 기반 긴급차량 우선 신호 시스템)

  • Lee, SoYeon;Jang, Jae Won;Kim, Dae-Young
    • Journal of Platform Technology
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    • v.9 no.3
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    • pp.44-51
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    • 2021
  • In general, golden time refers to the most important time in the initial response to accidents such as saving lives or extinguishing fires. The golden time varies from disaster to disaster, but is aimed at five minutes in terms of fire and first aid. However, for the actual site, the average dispatch time for ambulances is 9 minutes and the average transfer time is 17.6 minutes, which is quite large compared to the golden time. There are various causes for this delay, but the main cause is traffic jams. In order to solve the problem, the government has established emergency car concession obligations and secured golden time to prioritize ambulances in places with the highest accident rate, but it is not a solution in rush hour when traffic is increasing rapidly. Therefore, this paper proposed a deep learning-based emergency vehicle priority signal system using collected sound data by installing sound sensors on traffic lights and conducted an experiment to classify frequency signals that differ depending on the distance of the emergency vehicle.

A Study on the Analysis Method of Technology Trend on Tactical Data Link Using Intellectual Property Information (지식재산 정보를 이용한 전술데이터링크 기술동향 분석방법 연구)

  • Noh, Giseop
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.1
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    • pp.539-544
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    • 2021
  • The tactical data link is a military data network to improve the ability to recognize battlefield situations. The ROK military is promoting the tactical data link performance improvement programs. Tactical data link is essential to combine and integrate various platforms, sensor data, and command and control (C2) systems. Therefore, the research on related technical fields is required. However, the tactical data link has not disclosed detailed technical information due to the characteristics of military operation. In this paper, we propose a data-based automated analysis methodology using intellectual property information to understand the technology trend of tactical data link. In this paper, data related to intellectual property is automatically collected and pre-processed, and analyzed in terms of time series. In addition, the current status of each institution of patent technology information was generated, and the process of identifying key-researchers through network analysis was presented with providing results of our approach in this paper.

Comparison of Search Performance of SQLite3 Database by Linux File Systems (Linux File Systems에 따른 SQLite3 데이터베이스의 검색 성능 비교)

  • Choi, Jin-Oh
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.1
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    • pp.1-6
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    • 2022
  • Recently, IoT sensors are often used to produce stream data locally and they are provided for edge computing applications. Mass-produced data are stored in the mobile device's database for real-time processing and then synchronized with the server when needed. Many mobile databases are developed to support those applications. They are CloudScape, DB2 Everyplace, ASA, PointBase Mobile, etc, and the most widely used database is SQLite3 on Linux. In this paper, we focused on the performance required for synchronization with the server. The search performance required to retrieve SQLite3 was compared and analyzed according to the type of each Linux file system in which the database is stored. Thus, performance differences were checked for each file system according to various search query types, and criteria for applying the more appropriate Linux file system according to the index use environment and table scan environment were prepared and presented.

A Study on Fire Dynamics Simulation on the Arrangement of Aero System in the Residential (주거공간 에어로 시스템 배치에 관한 화재시뮬레이션 연구)

  • Choi, Doo Chan;Ko, Min Hyeok;Lee, Doo Hee;Park, Kye Won;Choi, Jeong Min;Lee, Yong Kwon;Kim, Gil Nam;Sun, Kyoung Soo
    • Journal of the Society of Disaster Information
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    • v.17 no.4
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    • pp.890-896
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    • 2021
  • Purpose: The called Aero System is important to find the well detected place in the livingroom or bedroom so, it needs to the confirmation through the Fire Dynamics Simulation Method: A fire simulation of a residential space of 59 m2 was performed, and in order to find the point where the fire environment was exposed quickly, measuring points were installed at 0.6 m and 1.5 m in height for each bedroom and living room, and the point where the fire was quickly detected was confirmed. Result: It was confirmed that the temperature and carbon monoxide sensor set at a point of 1.5 m was quickly detected at the reference value. Conclusion: The Fire detection would be relatively quick if the product in which the fire extinguishing module and the AQI module were separated was installed on the wall.

Smart Closet based on Arduino MEGA (아두이노 메가 기반의 스마트 옷장)

  • Mun, Se-Hun;Lee, Ju-Hyon;Lee, Ji-Min;Park, Gun-Hee;Han, Young-Oh
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.5
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    • pp.949-958
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    • 2022
  • Modern people have many kinds of clothes for individuals, and not just for storing clothes, but also for managing the condition of the closet, and users of smart closets created smart closets that provide daily convenience and optimal closet conditions, suggesting the possibility of developing smart furniture for various environments. In this developed system, smart closet is controlled using app inventor and touch LCD through bluetooth wireless communication, based on Arduino MEGA and user's clothes is recommended depending on the weather. In addition, this smart closet is designed with real-time weather status checking and easy ventilation function. It was implemented through the Arduino and app inventor program so that the weather can be printed on the LCD screen and the user's suitable clothes can be recommended to the application.

Daily Behavior Pattern Extraction using Time-Series Behavioral Data of Dairy Cows and k-Means Clustering (행동 시계열 데이터와 k-평균 군집화를 통한 젖소의 일일 행동패턴 검출)

  • Lee, Seonghun;Park, Gicheol;Park, Jaehwa
    • Journal of Software Assessment and Valuation
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    • v.17 no.1
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    • pp.83-92
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    • 2021
  • There are continuous and tremendous attempts to apply various sensor systems and ICTs into the dairy science for data accumulation and improvement of dairy productivity. However, these only concerns the fields which directly affect to the dairy productivity such as the number of individuals and the milk production amount, while researches on the physiology aspects of dairy cows are not enough which are fundamentally involved in the dairy productivity. This paper proposes the basic approach for extraction of daily behavior pattern from hourly behavioral data of dairy cows to identify the health status and stress. Total four clusters were grouped by k-means clustering and the reasonability was proved by visualization of the data in each groups and the representatives of each groups. We hope that provided results should lead to the further researches on catching abnormalities and disease signs of dairy cows.

Sound PSD Image based Tool Condition Monitoring using CNN in Machining Process (생산 공정에서 CNN을 이용한 음향 PSD 영상 기반 공구 상태 진단 기법)

  • Lee, Kyeong-Min
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.7
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    • pp.981-988
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    • 2022
  • The intelligent production plant called smart factories that apply information and communication technology (ICT) are collecting data in real time through various sensors. Recently, researches that effectively applying to these collected data have gained a lot of attention. This paper proposes a method for the tool condition monitoring based on the sound signal generated in machining process. First, it not only detects a fault tool, but also presents various tool states according to idle and active operation. The second, it's to represent the power spectrum of the sounds as images and apply some transformations on them in order to reveal, expose, and emphasize the health patterns that are hidden inside them. Finally, the contrast-enhanced PSD image obtained is diagnosed by using CNN. The results of the experiments demonstrate the high discrimination potential afforded by the proposed sound PSD image + CNN and show high diagnostic results according to the tool status.

Development of Multi-Crop Smart Farm Management System for User Convenience based on Lab-View (Lab-View 기반의 사용자 편의성을 위한 다작물 스마트팜 관리 시스템 개발)

  • Hwang, Jung-Tae;Kim, Young-Gon
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.1
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    • pp.15-20
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    • 2022
  • With the arrival of the fourth industrial era, demand for agriculture is increasing day by day, and smart farm technology, in which computers manage agriculture in line with the current situation, is developing. However, agricultural workers who use it find it difficult to set up and use a management system for smart farms. This paper aims to establish a Lab-View smart farm management system to facilitate the use of a control program for ICT technology farms (hereinafter referred to as smart farms), one of the promising projects of the next industrial revolution. Based on Lab-View, users simply set the type of crops they want to grow, set appropriate temperature/humidity data for each set crop, and collect data in real time through sensors and store it in DB. This functionality maximizes convenience and usability in terms of users.

Spatiotemporal patterns of the extreme 2022 drought event in Southern region using remote sensing based drought index (위성영상 기반 가뭄지수를 활용한 2022년 남부지역의 가뭄 분석)

  • Gwang-Su Park;Won-Ho Nam;Hee-Jin Lee;Young-Sik Mun;Min-Gi Jeon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.202-202
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    • 2023
  • 전 세계적으로 지구 온난화로 인해 발생한 가뭄은 사회적, 경제적, 환경적으로 막대한 피해를 야기하고 있다. 국내의 경우, 2022년부터 현재까지 지속되고 있는 가뭄 상황은 강수의 지역적 편차로 인해 남부 지역 중심으로 극심한 피해가 발생하였다. 남부 지역의 주요 용수공급원인 영산강, 섬진강권역의 용수 공급율은 예년의 57%(3.8억 톤)에 불과하며, 일부 도서·산간 지역은 용수공급이 제한되는 현상까지 발생하였다. 이러한 가뭄 피해를 대비하기 위해 초기에 모니터링을 통한 선제적 대응 방안을 구축해야 한다. 가뭄 모니터링의 경우 미계측 지역에 대한 모니터링 방법으로 주기적이고 균질한 자료를 제공 받을 수 있는 위성영상을 활용한 연구가 수행되고 있다. 가뭄을 정량적으로 분석하고 판단하기 위해 가뭄지수를 활용하고 있으며, 대표적인 가뭄지수는 지상 관측강수량자료를 활용한 확률분포 기반의 표준강수지수 (Standardized Precipitation Index, SPI)와 강수 및 기온의 변동성이 포함된 표준강수증발산지수 (Standardized Precipitation Evapotranspiration Index, SPEI)가 있으며, 위성영상 자료를 활용한 가뭄지수인 증발스트레스지수(Evaporative Stress Index, ESI) 등이 있다. 본 연구에서는 강수와 기온을 고려한 가뭄지수인SPEI와 위성영상 기반의 가뭄지수인 ESI를 활용하여 2022년 남부 지역의 가뭄 사상을 중심으로 지표별 시공간적 변화를 분석하고자 한다. SPEI의 경우 기상관측소 지점자료의 기온과 강수량을 활용하였으며, Terra 위성의 MODIS (Moderate Resolution Imaging Spectroradiometer) 센서에서 제공되는 위성영상자료를 활용한 ESI는 미계측 지역에 대한 가뭄 판단을 위해 시·군별로 세분화하여 산정하였다.

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