• Title/Summary/Keyword: Tracking algorithm

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A study on the design and implementation of a virus spread prevention system using digital technology (디지털 기술을 활용한 바이러스 확산 방지 시스템 설계 및 구현에 관한 연구)

  • Ji-Hyun, Yoo
    • Journal of IKEEE
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    • v.26 no.4
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    • pp.681-685
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    • 2022
  • Including the COVID-19 crisis, humanity is constantly exposed to viral infections, and efforts are being made to prevent the spread of infection by quickly isolating infected people and tracing contacts. Passive epidemiological investigations that confirm contact with an infected person through contact have limitations in terms of accuracy and speed, so automatic tracking methods using various digital technologies are being proposed. This paper verify contact by utilizing Bluetooth Low Energy (BLE) technology and present an algorithm that identifies close contact through analysis and correction of RSSI (Received Signal Strength Indicator) values. Also, propose a system that can prevent the spread of viruses in a centralized server structure.

A Study on Predicting the demand for Public Shared Bikes using linear Regression

  • HAN, Dong Hun;JUNG, Sang Woo
    • Korean Journal of Artificial Intelligence
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    • v.10 no.1
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    • pp.27-32
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    • 2022
  • As the need for eco-friendly transportation increases due to the deepening climate crisis, many local governments in Korea are introducing shared bicycles. Due to anxiety about public transportation after COVID-19, bicycles have firmly established themselves as the axis of daily transportation. The use of shared bicycles is spread, and the demand for bicycles is increasing by rental offices, but there are operational and management difficulties because the demand is managed under a limited budget. And unfortunately, user behavior results in a spatial imbalance of the bike inventory over time. So, in order to easily operate the maintenance of shared bicycles in Seoul, bicycles should be prepared in large quantities at a time of high demand and withdrawn at a low time. Therefore, in this study, by using machine learning, the linear regression algorithm and MS Azure ML are used to predict and analyze when demand is high. As a result of the analysis, the demand for bicycles in 2018 is on the rise compared to 2017, and the demand is lower in winter than in spring, summer, and fall. It can be judged that this linear regression-based prediction can reduce maintenance and management costs in a shared society and increase user convenience. In a further study, we will focus on shared bike routes by using GPS tracking systems. Through the data found, the route used by most people will be analyzed to derive the optimal route when installing a bicycle-only road.

Correction of Time and Coordinate Systems for Interoperability of Multi-GNSS

  • Kim, Lawoo;Lee, Yu Dam;Lee, Hyung Keun
    • Journal of Positioning, Navigation, and Timing
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    • v.10 no.4
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    • pp.279-289
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    • 2021
  • GNSS receivers capable of tracking multiple Global Navigation Systems (GNSSs) simultaneously are widely used. In order to estimate accurate user position and velocity, it is necessary to consider the key elements that contribute to the interoperability of the different GNSSs. Typical examples are the time system and the coordinate system. Each GNSS is operated based on its own reference time system depending on when the system was developed and whether the leap seconds are applied. In addition, each GNSS is designed based on its own coordinate system based on earth model constant values. This paper addresses the interoperability issues from the viewpoint of Single Point Positioning (SPP) users utilizing multiple GNSS signals from GPS, GLONASS, BeiDou, and Galileo. Since the broadcast ephemerides of each GNSS are based on their own time and coordinate systems, the time and the coordinate systems should be unified for any user algorithm. For this purpose, this paper proposes a method of converting each GNSS coordinate system into the reference coordinate system through Helmert transformation. The error of the broadcast ephemerides was calculated with the precise ephemerides provided by the International GNSS Service (IGS). The effectiveness of the proposed multi-GNSS correction and transformation method is verified using the Multi-GNSS Experiment (MGEX) station data.

CBDC Model with Enhanced Anonymity Using ID Certificate andBlockchain Encryption (익명인증서 및 블록체인 암호화로 익명성이 강화된 디지털화폐 모델)

  • Jae-ho Yoon;Yong-min Kim
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.33 no.2
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    • pp.139-149
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    • 2023
  • CBDC has characteristics similar to e-payments in which all records are kept by logs, so it is difficult to satisfy the anonymity level of cash. Therefore, in this study, the CBDC model that encrypts all transaction contents using the Diffie-Hellman key sharing algorithm was presented to enhance anonymity. The proposed model provides unlinkability anduntraceability. In addition, a CBDC certificate that uses pseudonym is used. Through this certificate, illegal transactions that require tracking can be tracked later by authorized institutions.

Development of Multi Card Touch based Interactive Arcade Game System (멀티 카드 터치기반 인터랙티브 아케이드 게임 시스템 구현)

  • Lee, Dong-Hoon;Jo, Jae-Ik;Yun, Tae-Soo
    • Journal of Korea Entertainment Industry Association
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    • v.5 no.2
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    • pp.87-95
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    • 2011
  • Recently, the issue has been tangible game environment due to the various interactive interface developments. In this paper, we propose the multi card touch based interactive arcade system by using marker recognition interface and multi-touch interaction interface. For our system, the card's location and orientation information is recognized through DI-based recognition algorithm. In addition, the user's hand gesture tracking informations are provided by the various interaction metaphors. The system provides the user with a higher engagement offers a new experience. Therefore, our system will be used in the tangible arcade game machine.

A Study on AI-based Autonomous Traffic Cone Tracking Algorithm for 1/5 scale Car Platform (인공지능기반 1/5 스케일 콘 추종 자율 주행 기법에 관한 연구)

  • Tae Min KIM;Seong Bin MA;Ui Jun SONG;Yu Bin WON;Jae Hyeok LEE;Kuk Won KO
    • Annual Conference of KIPS
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    • 2023.11a
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    • pp.283-284
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    • 2023
  • 자율주행 경진대회에서 학생들의 장애물 후에 경로를 생성 능력을 검정하는 라바콘 추종 종목은 중요한 항목 중의 하나이다. 라바콘의 위치를 알기 위해서는 라이다 센서가 필요하다. 실내의 경우 저가의 2D 라이다 센서를 사용하여 콘의 위치 검출이 가능하지만, 실외의 경우에는 고가의 3D 라이다 센서 또는 고가의 3차원 카메라가 필요하다. 이러한 고가의 기자재는 실습의 대중화에 걸림돌이 되고 있으므로, 1개의 카메라와 인공지능을 이용한 라이다 콘의 검출하는 방법을 개발하였고, 이를 활용하여 경로 생성 및 제어를 수행하였다. 그 결과 0.4m 이내의 정밀도로 콘의 위치 추정과 주행을 성공적으로 수행하였다.

A study on Improving the Performance of Anti - Drone Systems using AI (인공지능(AI)을 활용한 드론방어체계 성능향상 방안에 관한 연구)

  • Hae Chul Ma;Jong Chan Moon;Jae Yong Park;Su Han Lee;Hyuk Jin Kwon
    • Journal of the Korean Society of Systems Engineering
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    • v.19 no.2
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    • pp.126-134
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    • 2023
  • Drones are emerging as a new security threat, and the world is working to reduce them. Detection and identification are the most difficult and important parts of the anti-drone systems. Existing detection and identification methods each have their strengths and weaknesses, so complementary operations are required. Detection and identification performance in anti-drone systems can be improved through the use of artificial intelligence. This is because artificial intelligence can quickly analyze differences smaller than humans. There are three ways to utilize artificial intelligence. Through reinforcement learning-based physical control, noise and blur generated when the optical camera tracks the drone may be reduced, and tracking stability may be improved. The latest NeRF algorithm can be used to solve the problem of lack of enemy drone data. It is necessary to build a data network to utilize artificial intelligence. Through this, data can be efficiently collected and managed. In addition, model performance can be improved by regularly generating artificial intelligence learning data.

A Study of Guide System for Cerebrovascular Intervention (뇌혈관 중재시술 지원 가이드 시스템에 관한 연구)

  • Lee, Sung-Gwon;Jeong, Chang-Won;Yoon, Kwon-Ha;Joo, Su-Chong
    • Journal of Internet Computing and Services
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    • v.17 no.1
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    • pp.101-107
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    • 2016
  • Due to the recent advancement in digital imaging technology, development of intervention equipment has become generalize. Video arbitration procedure is a process to insert a tiny catheter and a guide wire in the body, so in order to enhance the effectiveness and safety of this treatment, the high-quality of x-ray of image should be used. However, the increasing of radiation has become the problem. Therefore, the studies to improve the performance of x-ray detectors are being actively processed. Moreover, this intervention is based on the reference of the angiographic imaging and 3D medical image processing. In this paper, we propose a guidance system to support this intervention. Through this intervention, it can solve the problem of the existing 2D medical images based vessel that has a formation of cerebrovascular disease, and guide the real-time tracking and optimal route to the target lesion by intervention catheter and guide wire tool. As a result, the system was completely composed for medical image acquisition unit and image processing unit as well as a display device. The experimental environment, guide services which are provided by the proposed system Brain Phantom (complete intracranial model with aneurysms, ref H+N-S-A-010) was taken with x-ray and testing. To generate a reference image based on the Laplacian algorithm for the image processing which derived from the cerebral blood vessel model was applied to DICOM by Volume ray casting technique. $A^*$ algorithm was used to provide the catheter with a guide wire tracking path. Finally, the result does show the location of the catheter and guide wire providing in the proposed system especially, it is expected to provide a useful guide for future intervention service.

A Study on Evaluating the Possibility of Monitoring Ships of CAS500-1 Images Based on YOLO Algorithm: A Case Study of a Busan New Port and an Oakland Port in California (YOLO 알고리즘 기반 국토위성영상의 선박 모니터링 가능성 평가 연구: 부산 신항과 캘리포니아 오클랜드항을 대상으로)

  • Park, Sangchul;Park, Yeongbin;Jang, Soyeong;Kim, Tae-Ho
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1463-1478
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    • 2022
  • Maritime transport accounts for 99.7% of the exports and imports of the Republic of Korea; therefore, developing a vessel monitoring system for efficient operation is of significant interest. Several studies have focused on tracking and monitoring vessel movements based on automatic identification system (AIS) data; however, ships without AIS have limited monitoring and tracking ability. High-resolution optical satellite images can provide the missing layer of information in AIS-based monitoring systems because they can identify non-AIS vessels and small ships over a wide range. Therefore, it is necessary to investigate vessel monitoring and small vessel classification systems using high-resolution optical satellite images. This study examined the possibility of developing ship monitoring systems using Compact Advanced Satellite 500-1 (CAS500-1) satellite images by first training a deep learning model using satellite image data and then performing detection in other images. To determine the effectiveness of the proposed method, the learning data was acquired from ships in the Yellow Sea and its major ports, and the detection model was established using the You Only Look Once (YOLO) algorithm. The ship detection performance was evaluated for a domestic and an international port. The results obtained using the detection model in ships in the anchorage and berth areas were compared with the ship classification information obtained using AIS, and an accuracy of 85.5% and 70% was achieved using domestic and international classification models, respectively. The results indicate that high-resolution satellite images can be used in mooring ships for vessel monitoring. The developed approach can potentially be used in vessel tracking and monitoring systems at major ports around the world if the accuracy of the detection model is improved through continuous learning data construction.

Postprocessing of Inter-Frame Coded Images Based on Convex Projection and Regularization (POCS와 정규화를 기반으로한 프레임간 압출 영사의 후처리)

  • Kim, Seong-Jin;Jeong, Si-Chang;Hwang, In-Gyeong;Baek, Jun-Gi
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.3
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    • pp.58-65
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    • 2002
  • In order to reduce blocking artifacts in inter-frame coded images, we propose a new image restoration algorithm, which directly processes differential images before reconstruction. We note that blocking artifact in inter-frame coded images is caused by both 8$\times$8 DCT and 16$\times$16 macroblock based motion compensation, while that of intra-coded images is caused by 8$\times$8 DCT only. According to the observation, we Propose a new degradation model for differential images and the corresponding restoration algorithm that utilizes additional constraints and convex sets for discontinuity inside blocks. The proposed restoration algorithm is a modified version of standard regularization that incorporate!; spatially adaptive lowpass filtering with consideration of edge directions by utilizing a part of DCT coefficients. Most of video coding standard adopt a hybrid structure of block-based motion compensation and block discrete cosine transform (BDCT). By this reason, blocking artifacts are occurred on both block boundary and block interior For more complete removal of both kinds of blocking artifacts, the restored differential image must satisfy two constraints, such as, directional discontinuities on block boundary and block interior Those constraints have been used for defining convex sets for restoring differential images.