• Title/Summary/Keyword: 개체 기반

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Real-time Laying Hens Sound Analysis System using MFCC Feature Vectors

  • Jeon, Heung Seok;Na, Deayoung
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.3
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    • pp.127-135
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    • 2021
  • Raising large numbers of animals in very narrow environments such as laying hens house can be very damaged from small environmental change. Previously researched about laying hens sound analysis system has a problem for applying to the laying hens house because considering only the limited situation of laying hens house. In this paper, to solve the problem, we propose a new laying hens sound analysis model using MFCC feature vector. This model can detect 7 situations that occur in actual laying hens house through 9 kinds of laying hens sound analysis. As a result of the performance evaluation of the proposed laying hens sound analysis model, the average AUC was 0.93, which is about 43% higher than that of the frequency feature analysis method.

Implementation of a Classification System for Dog Behaviors using YOLI-based Object Detection and a Node.js Server (YOLO 기반 개체 검출과 Node.js 서버를 이용한 반려견 행동 분류 시스템 구현)

  • Jo, Yong-Hwa;Lee, Hyuek-Jae;Kim, Young-Hun
    • Journal of the Institute of Convergence Signal Processing
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    • v.21 no.1
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    • pp.29-37
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    • 2020
  • This paper implements a method of extracting an object about a dog through real-time image analysis and classifying dog behaviors from the extracted images. The Darknet YOLO was used to detect dog objects, and the Teachable Machine provided by Google was used to classify behavior patterns from the extracted images. The trained Teachable Machine is saved in Google Drive and can be used by ml5.js implemented on a node.js server. By implementing an interactive web server using a socket.io module on the node.js server, the classified results are transmitted to the user's smart phone or PC in real time so that it can be checked anytime, anywhere.

Virtual-Constructive Simulation Interoperation for Aircombat Battle Experiment (Virtual-Constructive 시뮬레이션 연동을 활용한 공중전 전투 실험)

  • Kim, Dongjun;Shin, Yongjin;An, Kyeong-Soo;Kim, Young-Gon;Moon, Il-Chul;Bae, Jang Won
    • Journal of the Korea Society for Simulation
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    • v.30 no.1
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    • pp.139-152
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    • 2021
  • Simulations enable virtually experiencing rare events as well as analytically analyzing such events. Defense modeling and simulation research and develops the virtual and the constructive simulations to support these utilizations. These virtual and constructive(VC) simulations can interoperate to simultaneously virtual combat experience as well as evaluations on tactics and intelligence of combat entities. Moreover, recently, for artificial intelligence researches, it is necessary to retrieve human behavior data to proceed the imitation learning and the inverse reinforcement learning. The presented work illustrates a case study of VC interoperations in the aircombat scenario, and the work analyze the collected human behavior data from the VC interoperations. Through this case study, we discuss how to build the VC simulation in the aircombat area and how to utilize the collected human behavior data.

Big Data Analysis Method for Recommendations of Educational Video Contents (사용자 추천을 위한 교육용 동영상의 빅데이터 분석 기법 비교)

  • Lee, Hyoun-Sup;Kim, JinDeog
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.12
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    • pp.1716-1722
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    • 2021
  • Recently, the capacity of video content delivery services has been increasing significantly. Therefore, the importance of user recommendation is increasing. In addition, these contents contain a variety of characteristics, making it difficult to express the characteristics of the content properly only with a few keywords(Elements used in the search, such as titles, tags, topics, words, etc.) specified by the user. Consequently, existing recommendation systems that use user-defined keywords have limitations that do not properly reflect the characteristics of objects. In this paper, we compare the efficiency of between a method using voice data-based subtitles and an image comparison method using keyframes of images in recommendation module of educational video service systems. Furthermore, we propose the types and environments of video content in which each analysis technique can be efficiently utilized through experimental results.

Multi-UAV Formation Algorithm Based on Distributed Control Using Swarm Intelligence (군집 지능을 이용한 분산 제어 기반 대형 형성 알고리즘)

  • Kim, Moon-Jung;Kim, Jeong-Hun;Kim, Hyo-Jung;Ryoo, Chang-Kyung
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.50 no.8
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    • pp.523-530
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    • 2022
  • Since the Multi-UAV system for various missions is more complex than a single UAV, an efficient formation control method is required. In wide-area search mission, there is a need for a distributed control for flexible formation that has a low burden of communication and computation and enables autonomous formation between UAVs. This paper proposes a flexible formation operation method that considers the swarm formation, the bank alignment formation, and the formation movement to expand the scan area and improve search performance. The algorithm has a vibration characteristic of the second-order system for a relative distance and can design an algorithm through parameter tuning. In addition, we converted control commands to suit conventional UAV systems and demonstrated the performance of algorithms for a formation and movement of a formation through simulation.

Exon Capture - Principle and Applications to Phylogenomics and Population Genomics of Fishes (엑손 포획 - 원리와 어류의 계통유전체학 및 집단유전체학으로의 응용)

  • Li, Chenhong
    • Korean Journal of Ichthyology
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    • v.33 no.4
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    • pp.205-216
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    • 2021
  • Phylogenetic reconstruction based on one locus or a few loci can be misleading due to gene-tree/species-tree discordance. Species delimitation and intraspecific studies also often suffered from low resolution because of insufficient statistic power when few loci were used. Exon capture method is one of the most efficient way to collect genome-scale data, which can significantly augment studies that aimed to investigate patterns and histories of organisms at both intraspecific and high level. Here, I showed the advancement of shifting from single-gene method to genomic approach and the benefit of applying exon capture method comparing to alternative genomic techniques. Then, I explained the principle of exon capture method as well as providing detailed recommendations for applying this method. Finally, I demonstrated exon capture method using two applications and discussed future perspectives of this technology.

A Study On The Co-survival And Collaboration Of Organization And Its Environments (조직과 환경의 상생과 협력에 관한 연구)

  • Lee, Kyung-Hwan
    • Journal of Korea Society of Industrial Information Systems
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    • v.14 no.5
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    • pp.239-256
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    • 2009
  • The major issues of managing an organization and its environments are on how to establish a community for their co-survival and collaboration. This study is on the principles and management practices for establishing the community of organization and its environments based on the power circulatory approach, so that it contributes to creation of the social orders for co-survival and collaboration. In order to do this I discussed the theories and practices of the power circulatory approach, and then suggest their application to establishment of the co-survival community for organization and its environment. According to results the power circulatory approach offers theoretical and managerial tools which establish the co-survival community for organization and its environments, so that it increases likelihood of their co-survival and collaboration. Furthermore I discussed the position of the power circulatory approach to co-survival and collaboration in a manner that displays similarities and differences with exiting approaches such as the contingency and population ecology model.

A study on an artificial intelligence model for measuring object speed using road markers that can respond to external forces (외부력에 대응할 수 있는 도로 마커 활용 개체 속도 측정 인공지능 모델 연구)

  • Lim, Dong Hyun;Park, Dae-woo
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.05a
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    • pp.228-231
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    • 2022
  • Most CCTVs operated by public institutions for crime prevention and parking enforcement are located on roads. The angle of these CCTV's view is often changed for various reasons, such as bolt loosening by vibration or shocking by vehicles and workers, etc. In order to effectively provide AI services based on the collected images, the service target area(ROI, Region Of Interest) must be provided without interruption within the image. This is also related to the viewpoint of effective operation of computing power for image analysis. This study explains how to maximize the application of artificial intelligence technology by setting the ROI based on the marker on the road, setting the image analysis to be possible only within the area, and studying the process of finding the ROI.

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Estimation of Habitat Suitability Index for Water Quality of Z acco platypus by Region (권역단위 피라미 수질 서식처적합도지수 산정)

  • Hong, Rok Gi;Park, Jin Seok;Jang, Seong Ju;Hong, Joo Pyo;Song, In Hong
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.458-458
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    • 2021
  • 하천의 환경기능과 생태에 관한 관심이 증가하며 생태를 고려한 하천 유지 유량의 산정이 필요하다. 수문 특성의 물리적 서식처에 관한 연구는 PHABSIM, River2D 등의 소프트웨어 적용을 통한 유지유량증분법(IFIM), 수문 인자별 서식처적합도지수(HSI)를 기반으로 연구되고 있지만, 하천의 수질을 고려한 서식처 연구는 각 수질 인자별 서식처적합도지수 자료의 부족으로 하천유지유량 산정에 반영이 어려운 실정이다. 본 연구는 국내 하천의 수질·생태 모니터링 자료를 바탕으로 수온, DO 등의 수질 인자에 대한 피라미의 서식처적합도지수를 권역 단위로 산정했다. 수질 및 어류조사 자료는 물환경정보시스템의 최근 10년 수질측정망, 생물측정망 조사자료를 이용해 구축하였다. 피라미의 수질별 서식 적합도는 일반화가법모형(GAM)을 적용하여 수질 인자별 어류 개체 밀도 분포의 상관관계를 분석하여 지수화하였다. 특히, 어류의 서식 특성은 수계별로 상이할 수 있어 가용 데이터의 범위를 고려하여 권역별 수질 인자에 따른 피라미의 서식 특성을 분석하였다. 본 연구로 제시된 권역단위 피라미의 수질 서식처 적합도 지수는 생태를 고려한 하천사업의 계획, 평가의 기초자료를 제시할 수 있을 것이다. 또한, 피라미 외 각 하천의 주요 생태 어종 평가를 위한 수질 서식처 적합도지수 산정의 자동화를 위한 알고리즘 개발에 적용가능할 것으로 예상된다.

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A Study on Automatic Vehicle Extraction within Drone Image Bounding Box Using Unsupervised SVM Classification Technique (무감독 SVM 분류 기법을 통한 드론 영상 경계 박스 내 차량 자동 추출 연구)

  • Junho Yeom
    • Land and Housing Review
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    • v.14 no.4
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    • pp.95-102
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    • 2023
  • Numerous investigations have explored the integration of machine leaning algorithms with high-resolution drone image for object detection in urban settings. However, a prevalent limitation in vehicle extraction studies involves the reliance on bounding boxes rather than instance segmentation. This limitation hinders the precise determination of vehicle direction and exact boundaries. Instance segmentation, while providing detailed object boundaries, necessitates labour intensive labelling for individual objects, prompting the need for research on automating unsupervised instance segmentation in vehicle extraction. In this study, a novel approach was proposed for vehicle extraction utilizing unsupervised SVM classification applied to vehicle bounding boxes in drone images. The method aims to address the challenges associated with bounding box-based approaches and provide a more accurate representation of vehicle boundaries. The study showed promising results, demonstrating an 89% accuracy in vehicle extraction. Notably, the proposed technique proved effective even when dealing with significant variations in spectral characteristics within the vehicles. This research contributes to advancing the field by offering a viable solution for automatic and unsupervised instance segmentation in the context of vehicle extraction from image.