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Implementation of a Crowding Measurement System Based on High Frequency Signal

  • Myoungbeom Chung
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.5
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    • pp.67-74
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    • 2024
  • As the number of coffee shops increases, many people are studying or working at coffee shops. Coffee shop operators have been required to analyze customer visits due to customer turnover and profit problems. Methods such as image analysis, QR code authentication, and Bluetooth beacon have been proposed for these statistics and analysis. However, it is difficult to use due to problems such as invasion of privacy and low accuracy. Therefore, in this study, to solve these problem and provide more accurate in-store congestion information, we propose a crowding measurement method of coffee shop using high frequency signal. There is an advantage in that a high frequency signal replaces the Bluetooth signal, and the transmission range of the signal is limited to the store, thereby increasing the accuracy of the method. To verify the performance of the proposed system, we conducted a comparative experiment with a Bluetooth based system, and as a result, the proposed method showed lower misrecognition rate. Thus, the proposed method will be an effective useful service for providing information on crowding at coffee shops and processing statistics.

A Ubiquitous Home Network System for Managing Environment-Information Sensors using Image Processing (영상 처리를 이용하여 주변 환경 센서를 관리하기 위한 유비쿼터스 홈 네트워크 시스템)

  • Hong, Sung-Hwa;Jung, Suk-Yong
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.3
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    • pp.931-942
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    • 2010
  • A home network provides users with a variety of information services. The kind and quality of the services can be substantially enhanced by utilizing a variety of data from sensors. However, home networks currently limit their potential by focusing on providing multimedia services rather than services utilizing sensor data. Outdoor electronics are frequently made in a form that emphasizes only certain limited functions in contrast to home appliances. Thus, sensors with one or two functions rather than many can be used in outdoor systems and their use will be more economical than using sensor nodes indoors with more complex home appliances. In this study, we chose to work with motion sensors as they have many potential uses, and we selected a parking lot control system with to use the motion sensors. This parking lot control system was implemented and applied as part of a home network. For this purpose, we defined and implemented a protocol to manage the network in a ubiquitous sensor network environment for the wireless home network in this study. Although a network management system in a Ubiquitous Sensor Network (USN) related to this study is being advanced for other projects, the protocol interface and message system have not yet been clearly defined for use in a general purpose network or in an extension into heterogeneous kinds of networks, communication support, etc. Therefore, USN network management should be conducted for management of faults, composition, power, and applications. To verify the performance of the protocol interface designed in this study, we designed and implemented the necessary units (sensor nodes, sensor gateway, and server) for each network section and, with them, proved the validity of this study.

A Study on the Implementation of the Multi-Process Structured ISDN Terminal Adaptor for Sending the Ultra Sound Medical Images (다중처리 구조를 갖는 초음파 의료영상 전송용 ISDN(Integrated Services Digital Network) TA(Terminal Adaptor) 구현에 관한 연구)

  • 남상규;이영후
    • Journal of Biomedical Engineering Research
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    • v.15 no.3
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    • pp.317-324
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    • 1994
  • This paper proposed a new method in the implementation of ISDN (integrated services digital network) LAPD (link access procedure on the D-channel) and LAPB (link access procedure on the B-channel) protocols. The proposed method in this paper implement ISDW LAPD protocol through multi-tasking operating system and adopt a kernel part that is changed operating system to target board. The features of implemented system are (1) the para.llel processing of the events generated at each layer, as follows (2) the supporting necessary timers for the implementation of ISDW LAPD protocol from the kernel part by using software, (3) the recommanded SAP (Service Access Point) from CCITT was composed by using port function in the operating system. With the proposed method, the protocols of ISDH layerl, layer2 and layer3 (call control) were implemented by using the kernel part and related tests were carried out by connecting the ISDH terminal simulator to ISDN S-interface system using the ISDN LAPD protocol The results showed that ISDW S-interface terminals could be discriminated by TEI (Terminal Equipment Identifier) assignment in layer 2 (LAPD) and the message transmission of layer 3 was verified by establishing the multi-frame transmission and then through the path established by the LAPD protocol, a user data was tranfered and received on B-channel with LAPB protocol Thererfore, as new efficient ISDN S-interface environment was implemented in the thesis, it was verified that the implemented system can be utilized by connecting ISDW in the future to transfer a medical image data.

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Restoration of Missing Data in Satellite-Observed Sea Surface Temperature using Deep Learning Techniques (딥러닝 기법을 활용한 위성 관측 해수면 온도 자료의 결측부 복원에 관한 연구)

  • Won-Been Park;Heung-Bae Choi;Myeong-Soo Han;Ho-Sik Um;Yong-Sik Song
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.6
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    • pp.536-542
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    • 2023
  • Satellites represent cutting-edge technology, of ering significant advantages in spatial and temporal observations. National agencies worldwide harness satellite data to respond to marine accidents and analyze ocean fluctuations effectively. However, challenges arise with high-resolution satellite-based sea surface temperature data (Operational Sea Surface Temperature and Sea Ice Analysis, OSTIA), where gaps or empty areas may occur due to satellite instrumentation, geographical errors, and cloud cover. These issues can take several hours to rectify. This study addressed the issue of missing OSTIA data by employing LaMa, the latest deep learning-based algorithm. We evaluated its performance by comparing it to three existing image processing techniques. The results of this evaluation, using the coefficient of determination (R2) and mean absolute error (MAE) values, demonstrated the superior performance of the LaMa algorithm. It consistently achieved R2 values of 0.9 or higher and kept MAE values under 0.5 ℃ or less. This outperformed the traditional methods, including bilinear interpolation, bicubic interpolation, and DeepFill v1 techniques. We plan to evaluate the feasibility of integrating the LaMa technique into an operational satellite data provision system.

A Polarization-based Frequency Scanning Interferometer and the Measurement Processing Acceleration based on Parallel Programing (편광 기반 주파수 스캐닝 간섭 시스템 및 병렬 프로그래밍 기반 측정 고속화)

  • Lee, Seung Hyun;Kim, Min Young
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.8
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    • pp.253-263
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    • 2013
  • Frequency Scanning Interferometry(FSI) system, one of the most promising optical surface measurement techniques, generally results in superior optical performance comparing with other 3-dimensional measuring methods as its hardware structure is fixed in operation and only the light frequency is scanned in a specific spectral band without vertical scanning of the target surface or the objective lens. FSI system collects a set of images of interference fringe by changing the frequency of light source. After that, it transforms intensity data of acquired image into frequency information, and calculates the height profile of target objects with the help of frequency analysis based on Fast Fourier Transform(FFT). However, it still suffers from optical noise on target surfaces and relatively long processing time due to the number of images acquired in frequency scanning phase. 1) a Polarization-based Frequency Scanning Interferometry(PFSI) is proposed for optical noise robustness. It consists of tunable laser for light source, ${\lambda}/4$ plate in front of reference mirror, ${\lambda}/4$ plate in front of target object, polarizing beam splitter, polarizer in front of image sensor, polarizer in front of the fiber coupled light source, ${\lambda}/2$ plate between PBS and polarizer of the light source. Using the proposed system, we can solve the problem of fringe image with low contrast by using polarization technique. Also, we can control light distribution of object beam and reference beam. 2) the signal processing acceleration method is proposed for PFSI, based on parallel processing architecture, which consists of parallel processing hardware and software such as Graphic Processing Unit(GPU) and Compute Unified Device Architecture(CUDA). As a result, the processing time reaches into tact time level of real-time processing. Finally, the proposed system is evaluated in terms of accuracy and processing speed through a series of experiment and the obtained results show the effectiveness of the proposed system and method.

Development of an abnormal road object recognition model based on deep learning (딥러닝 기반 불량노면 객체 인식 모델 개발)

  • Choi, Mi-Hyeong;Woo, Je-Seung;Hong, Sun-Gi;Park, Jun-Mo
    • Journal of the Institute of Convergence Signal Processing
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    • v.22 no.4
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    • pp.149-155
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    • 2021
  • In this study, we intend to develop a defective road surface object recognition model that automatically detects road surface defects that restrict the movement of the transportation handicapped using electric mobile devices with deep learning. For this purpose, road surface information was collected from the pedestrian and running routes where the electric mobility aid device is expected to move in five areas within the city of Busan. For data, images were collected by dividing the road surface and surroundings into objects constituting the surroundings. A series of recognition items such as the detection of breakage levels of sidewalk blocks were defined by classifying according to the degree of impeding the movement of the transportation handicapped in traffic from the collected data. A road surface object recognition deep learning model was implemented. In the final stage of the study, the performance verification process of a deep learning model that automatically detects defective road surface objects through model learning and validation after processing, refining, and annotation of image data separated and collected in units of objects through actual driving. proceeded.

Study of multi-stacked InAs quantum dot infrared photodetector grown by metal organic chemical vapor deposition

  • Kim, Jeong-Seop;Ha, Seung-Gyu;Yang, Chang-Jae;Lee, Jae-Yeol;Park, Se-Hun;Choe, Won-Jun;Yun, Ui-Jun
    • Proceedings of the Korean Vacuum Society Conference
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    • 2010.02a
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    • pp.129-129
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    • 2010
  • 적외선 검출소자(Infrared Photodetector)는 근적외선에서 원적외선 영역에 이르는 광범위한 파장 범위의 적외선을 이용하는 기기로서 대상물이 방사하는 적외선 영역의 에너지를 흡수하여 이를 영상화할 수 있는 장비이다. 적외선 관련 기술은 2차 세계대전 기간에 태동하였으며, 현재에는 원거리 감지기술 등과 접목되면서 그 활용 분야가 다양해지고 있다. 특히 능동형 정밀 타격무기를 비롯한 감시 정찰 장비 및 지능형 전투 장비 시스템 등에 대한 요구를 바탕으로 보다 정밀하고 신속한 표적 감지 및 정보처리 기술에 관한 연구가 선진국을 통해서 활발히 진행되고 있다. 기존의 Bolometer 형식의 열 감지 소자는 반응 속도가 느리고 측정 감도가 낮은 단점이 있으며, MCT(HgCdTe)를 이용한 적외선 검출기의 경우 높은 기계적 결함과 77K 저온에서 동작해야하기 때문에 발생하는 추가 비용 등이 문제점으로 지적되고 있다[1]. 이에 반해 화합물 반도체 자기조립 양자점(self-assembled quantum dot)을 이용한 적외선 수광소자는 양자점이 가지는 불연속적인 내부 에너지 준위로 인하여, 높은 내부 양자 효율과 온도 안정성을 기대할 수 있으며, 고성능, 고속처리, 저소비전력 및 저소음의 실현이 가능하다. 본 연구에서는 적층 InAs/InGaAs dot-in-a-well 구조를 유기금속화학기상증착법을 이용하여 성장하고 이를 소자에 응용하였다. 균일한 적층 양자점의 성장을 위해서 원자현미경(atomic force microscopy)을 이용하여, 각 층의 양자점의 크기와 밀도를 관찰하였고, photoluminescence (PL)를 이용하여 발광특성을 연구하였다. 각 층간의 GaAs space layer의 두께와 온도 조절 과정을 조절함으로써 균일한 적층 양자점 구조를 얻을 수 있었다. 이를 이용하여 양자점의 전도대 내부의 에너지 준위간 천이(intersubband transition)를 이용하는 n-type GaAs/intrinsic InAs 양자점/n-type GaAs 구조의 양자점 적외선수광소자 구조를 성장하였다. 이 과정에서 상부 n-type GaAs의 성장 온도가 600도 이상이 되는 경우 발광효율이 급격히 감소하고, 암전류가 크게 증가하는 것을 관찰하였다. 이는 InAs 양자점과 주변 GaAs 간의 열에 의한 상호 확산에 의하여 양자점의 전자 구속 효과를 저해하는 것으로 설명된다.

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Development of IoT Device Management System Using Blockchain DPoS Consensus Algorithm (블록체인 DPoS 합의 알고리즘을 활용한 IoT 장치 관리 시스템 개발)

  • Kim, Mihui;Kim, Youngmin
    • Journal of IKEEE
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    • v.23 no.2
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    • pp.508-516
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    • 2019
  • Smart home with various IoT devices provides convenient and efficient services. However, security is important because sensitive information such as private video and audio can be collected and processed, as well as shared over the Internet. To manage such smart home IoT devices, we use blockchain technology that provides data integrity and secure management. In this paper, we utilize a PoS(Proof of Stake) method that verifies the block through the accumulated stake in the network rather than the computation power, out of the PoW(Proof of Work) block chain, in which the computation for the existing verification must be continuously performed. Among them, we propose a blockchain based system with DPoS(Delegated Proof of Stake) method to actively solve the scalability part, for security that is suitable for smart home IoT environment. We implement the proposed system with DPoS based EOSIO to show realization, and we show performance improvement in terms of transaction processing speed.

Design and manufacture of eyeball protrusion measuring device using white light scanning interferometer (백색광 간섭계를 이용한 안구 돌출 측정 장치 설계 및 제작)

  • Chang, Jung-soo;Kim, Young-kil
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.1
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    • pp.63-69
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    • 2019
  • The relative position of the orbital eye can be a criterion for evaluating several pathological conditions. It is especially useful to diagnose orbital fractures, thyroid eye disease, orbital tumors and to evaluate the outcome of medication and surgical treatment. Hertel and Naugle are representative measurement tools used to measure eyeball protrusion values, and have different measurement results, such as fixed orbits, every time they are inspected, even if the same inspector repeatedly measures them. Even with the same calibrator, it is inevitable that different manufacturers will change the design of the stationary part of the orbit, causing the surveyor to make a measurement error. In this paper, we designed and fabricated a protrusion measuring device using a white light interferometer and measured the protrusion of the human eye and found that the precision and repeatability were significantly higher than the manual measurement method.

Camera Model Identification Using Modified DenseNet and HPF (변형된 DenseNet과 HPF를 이용한 카메라 모델 판별 알고리즘)

  • Lee, Soo-Hyeon;Kim, Dong-Hyun;Lee, Hae-Yeoun
    • The Journal of Korean Institute of Information Technology
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    • v.17 no.8
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    • pp.11-19
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    • 2019
  • Against advanced image-related crimes, a high level of digital forensic methods is required. However, feature-based methods are difficult to respond to new device features by utilizing human-designed features, and deep learning-based methods should improve accuracy. This paper proposes a deep learning model to identify camera models based on DenseNet, the recent technology in the deep learning model field. To extract camera sensor features, a HPF feature extraction filter was applied. For camera model identification, we modified the number of hierarchical iterations and eliminated the Bottleneck layer and compression processing used to reduce computation. The proposed model was analyzed using the Dresden database and achieved an accuracy of 99.65% for 14 camera models. We achieved higher accuracy than previous studies and overcome their disadvantages with low accuracy for the same manufacturer.