• Title/Summary/Keyword: 사물 검출

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Analysis of Detection Ability Impact of Clang Static Analysis Tool by Source Code Obfuscation Technique (소스 코드 난독화 기법에 의한 Clang 정적 분석 도구의 성능 영향 분석)

  • Jin, Hongjoo;Park, Moon Chan;Lee, Dong Hoon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.28 no.3
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    • pp.605-615
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    • 2018
  • Due to the rapid growth of the Internet of Things market, the use of the C/C++ language, which is the most widely used language in embedded systems, is also increasing. To improve the quality of code in the C/C++ language and reduce development costs, it is better to use static analysis, a software verification technique that can be performed in the first half of the software development life cycle. Many programs use static analysis to verify software safety and many static analysis tools are being used and studied. In this paper, we use Clang static analysis tool to check security weakness detection performance of verified test code. In addition, we compared the static analysis results of the test codes applied with the source obfuscation techniques, layout obfuscation, data obfuscation, and control flow obfuscation techniques, and the static analysis results of the original test codes, Analyze the detection ability impact of the Clang static analysis tool.

Active Object Tracking System for Intelligent Video Surveillance (지능형 비디오 감시를 위한 능동적 객체 추적 시스템)

  • Park, Ho-Sik
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.7 no.2
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    • pp.82-85
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    • 2014
  • It is helpful to use Intelligent Video Surveillance to replace and supplement the demerit which can possibly occur due to the mistake that can be made by human management. To accomplish this, it is essential that the system should digitalize image information from surveillance camera so that the system, itself, can be able to locate a object and to analyze the pattern of the object. Also, it is imperative that the system should have ability to operate a alarm and a entrance blocking system and to notify a situation to a security manager. Zooming a small object form a screen, however, requires a exact zooming ratio of the object and a shift of centric coordinate. In this paper, It is able to locate and observe closely a object from flexible background, regardless of the distance, by calculating a zooming ratio according to object moment, pan coordinate, and tilt coordinate.

M2M Technology based Global Heathcare Platform (M2M 기반의 글로벌 헬스케어 시스템 플랫폼)

  • Jung, Sang-Joong;Chung, Wan-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.11
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    • pp.2435-2441
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    • 2010
  • A global healthcare system based on M2M technology is proposed to support a good mobility, flexibility and scalability to the patients in 6LoWPAN. Sensor nodes integrated with wearable sensors are linked to gateway with IEEE 802.15.4 protocol and 6LoWPAN protocol for data acquisition and transmission purpose via external network. In the server, heart rate variability signals are obtained by signal processing and used for time and frequency domain performance analysis to evaluate the patient's health status. Our approach for global healthcare system with non-invasive and continuous IP-based communication is managed to process large amount of biomedical signals in the large scale of service range accurately.

Weakly-supervised Semantic Segmentation using Exclusive Multi-Classifier Deep Learning Model (독점 멀티 분류기의 심층 학습 모델을 사용한 약지도 시맨틱 분할)

  • Choi, Hyeon-Joon;Kang, Dong-Joong
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.6
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    • pp.227-233
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    • 2019
  • Recently, along with the recent development of deep learning technique, neural networks are achieving success in computer vision filed. Convolutional neural network have shown outstanding performance in not only for a simple image classification task, but also for tasks with high difficulty such as object segmentation and detection. However many such deep learning models are based on supervised-learning, which requires more annotation labels than image-level label. Especially image semantic segmentation model requires pixel-level annotations for training, which is very. To solve these problems, this paper proposes a weakly-supervised semantic segmentation method which requires only image level label to train network. Existing weakly-supervised learning methods have limitations in detecting only specific area of object. In this paper, on the other hand, we use multi-classifier deep learning architecture so that our model recognizes more different parts of objects. The proposed method is evaluated using VOC 2012 validation dataset.

Implementation of Incoming Panel Monitoring System using Open Source Platform and Wi-Fi Networks (오픈소스 플랫폼 및 Wi-Fi를 이용한 수배전반 모니터링 시스템 구현)

  • Kang, Jin-Young;Kang, Hag-Seong;Jeong, Sung-Hak;Park, Mi-Young;Lee, Young-Dong
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.886-887
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    • 2015
  • There is a growing interest in and demand for power industry acceleration and energy efficiency due to the increased energy consumption, environmental issues. Electronic power IT convergence industries such as intelligent power system has attract attention as new growth engine industry. A large number of sensors and motors are being installed following unmanned, automated in existing incoming panel management system. Observe the operating conditions and rapid response is essential. Despite the need for immediate action to be taken in the event of various later failed to recognize the emergency power can lead to accidents. In this paper, we propose a new architecture of the implementation of incoming panel monitoring system for power monitoring, fault detection, maintenance and system control using open source hardware platform and Wi-Fi networks.

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A Development of Effective Object Detection System Using Multi-Device LiDAR Sensor in Vehicle Driving Environment (차량주행 환경에서 다중라이다센서를 이용한 효과적인 검출 시스템 개발)

  • Kwon, Jin-San;Kim, Dong-Sun;Hwang, Tae-Ho;Park, Hyun-Moon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.2
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    • pp.313-320
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    • 2018
  • The importance of sensors on a self-driving vehicle has rising since it act as eyes for the vehicle. Lidar sensors based on laser technology tend to yield better image quality with more laser channels, thus, it has higher detection accuracy for obstacles, pedistrians, terrain, and other vechicles. However, incorporating more laser channels results higher unit price more than ten times, and this is a major drawback for using high channel lidar sensors on a vehicle for actual consumer market. To come up with this drawback, we propose a method of integrating multiple low channel, low cost lidar sensors acting as one high channel sensor. The result uses four 16 channels lidar sensors with small form factor acting as one bulky 64 channels sensor, which in turn, improves vehicles cosmetic aspects and helps widespread of using the lidar technology for the market.

Development of EDAM2 program for ENC Quality Assurance (전자해도 품질향상을 위한 검사프로그램(EDAM2)개발)

  • 심우성;서상현
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2001.05a
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    • pp.542-545
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    • 2001
  • ENC(Electronic Navigational Chart) development of all coast of our country have been finished by Hydrographic Office in last years. Quality assurance of ENC will be more important because it may be focused in a sense of utilization and application of data. Two things of ENC quality are spatial and attribute. These should be made and edited by HO, but some instances are not correct because of various production tools, disagreement of S-57 adaptation, and etc. This paper presents which point of data quality in attitude of data users should be considered and corrected in detail. Especially, error of AGEN attribute, Meta information and Korean Language are investigated. Finally, The program of EDAM2, ENC quality assurance program, will be presented. It is expected for EDAM2 to devote advanced ENC quality assurance.

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The Design of IoT Device System for Disaster Prevention using Sound Source Detection and Location Estimation Algorithm (음원탐지 및 위치 추정 알고리즘을 이용한 방재용 IoT 디바이스 시스템 설계)

  • Ghil, Min-Sik;Kwak, Dong-Kurl
    • Journal of Convergence for Information Technology
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    • v.10 no.8
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    • pp.53-59
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    • 2020
  • This paper relates to an IoT device system that detects sound source and estimates the sound source location. More specifically, it is a system using a sound source direction detection device that can accurately detect the direction of a sound source by analyzing the difference of arrival time of a sound source signal collected from microphone sensors, and track the generation direction of a sound source using an IoT sensor. As a result of a performance test by generating a sound source, it was confirmed that it operates very accurately within 140dB of the acoustic detection area, within 1 second of response time, and within 1° of directional angle resolution. In the future, based on this design plan, we plan to commercialize it by improving the reliability by reflecting the artificial intelligence algorithm through big data analysis.

Secure Routing Mechanism to Defend Multiple Attacks in Sensor Networks (무선 센서 네트워크에서 다중 공격 방어를 위한 보안 라우팅 기법)

  • Moon, Soo-Young;Cho, Tae-Ho
    • Journal of Intelligence and Information Systems
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    • v.16 no.1
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    • pp.45-56
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    • 2010
  • Sensor Networks are composed of many sensor nodes, which are capable of sensing, computing, and communicating with each other, and one or more sink node(s). Sensor networks collect information of various objects' identification and surrounding environment. Due to the limited resources of sensor nodes, use of wireless channel, and the lack of infrastructure, sensor networks are vulnerable to security threats. Most research of sensor networks have focused on how to detect and counter one type of attack. However, in real sensor networks, it is impractical to predict the attack to occur. Additionally, it is possible for multiple attacks to occur in sensor networks. In this paper, we propose the Secure Routing Mechanism to Defend Multiple Attacks in Sensor Networks. The proposed mechanism improves and combines existing security mechanisms, and achieves higher detection rates for single and multiple attacks.

IoT Platform System for Electric Fire Prediction and Prevention (전기화재 예측 및 예방을 위한 IoT 플랫폼 시스템)

  • Yang, Seungeui;Lee, Sungock;Jung, Hoekyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.2
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    • pp.223-229
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    • 2022
  • During the winter season, when the weather gets colder every year, electricity consumption increases rapidly. The occurrence of fires is increasing due to a short circuit in electrical facilities of buildings such as markets, bathrooms, and apartments with high population density while using a lot of electricity. The cause of these short circuit fires is mostly due to the aging of the wires, the usage increases, and the excessive load cannot be endured, and the wire sheath is melted and caused by nearby ignition materials. In this paper, the load and overheat generated in the electric wire are measured through a complex sensor composed of an overload sensor, a VoC sensor, and an overheat sensor. Based on this, big data analysis is carried out to develop a platform capable of predicting, alerting, and blocking electric fires in real time, and a simulator capable of simulated fire experiments.