• Title/Summary/Keyword: Position Prediction

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Contact Detection based on Relative Distance Prediction using Deep Learning-based Object Detection (딥러닝 기반의 객체 검출을 이용한 상대적 거리 예측 및 접촉 감지)

  • Hong, Seok-Mi;Sun, Kyunghee;Yoo, Hyun
    • Journal of Convergence for Information Technology
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    • v.12 no.1
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    • pp.39-44
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    • 2022
  • The purpose of this study is to extract the type, location, and absolute size of an object in an image using a deep learning algorithm, predict the relative distance between objects, and use this to detect contact between objects. To analyze the size ratio of objects, YOLO, a CNN-based object detection algorithm, is used. Through the YOLO algorithm, the absolute size and position of an object are extracted in the form of coordinates. The extraction result extracts the ratio between the size in the image and the actual size from the standard object-size list having the same object name and size stored in advance, and predicts the relative distance between the camera and the object in the image. Based on the predicted value, it detects whether the objects are in contact.

Combination Analysis of Optical Tracking System Design Variables for Unknown Space Objects Using Effectiveness Analysis Simulation (효과분석 시뮬레이션을 이용한 미지 우주물체 광학 추적 시스템 설계 변수 조합 분석)

  • Hyun, Chul;Lee, Sangwook;Lee, Hojin;Park, Seung-Wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.9
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    • pp.1312-1319
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    • 2022
  • This paper defines an effectiveness index for optical continuous observation of unknown space objects and presents a range of design variables combinations that can satisfy the effectiveness index from a telescope/mount control system perspective using integrated simulation. The overall system-level simulation was implemented and the tracking performance was analyzed by considering design variables such as target position prediction and frame rate, image processing time and measurement error, target trajectory characteristics, and maneuver performance of mount gimbal. As a result of the analysis, it was confirmed that the continuous tracking performance of the optical observation system is dependent on the combination of frame rate and mount maneuver performance. In a situation where an optical observation system is designed or a similar system is implemented using COTS, an appropriate combination of parameters between design variables can be found through effectiveness analysis simulation as in this study.

Analysis of the buckling failure of bedding slope based on monitoring data - a model test study

  • Zhang, Qian;Hu, Jie;Gao, Yang;Du, Yanliang;Li, Liping;Liu, Hongliang;Sun, Shangqu
    • Geomechanics and Engineering
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    • v.28 no.4
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    • pp.335-346
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    • 2022
  • Buckling failure is a typical slope instability mode that should be paid more attention to. It is difficult to provide systematic guidance for the monitoring and management of such slopes due to unclear mechanism. Here we examine buckling failure as the potential instability mode for a slope above a railway tunnel in southwest China. A comprehensive model test system was developed that can be used to conduct buckling failure experiments. The displacement, stress, and strain of the slope were monitored to document the evolution of buckling failure during the experiment. Monitoring data reveal the deformation and stress characteristics of the slope with different slipping mass thicknesses and under different top loads. The test results show that the slipping mass is the main subject of the top load and is the key object of monitoring. Displacement and stress precede buckling failure, so maybe useful predictors of impending failure. However, the response of the stress variation is earlier than displacement variation during the failure process. It is also necessary to monitor the bedrock near the slip face because its stress evolution plays an important role in the early prediction of instability. The position near the slope foot is most prone to buckling failure, so it should be closely monitored.

Disease Prediction System based on WEB (WEB 기반 질병 예측 시스템)

  • Hong, YouSik;Han, Y.H.;Lee, W.B.
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.3
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    • pp.125-132
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    • 2022
  • The Ministry of Environment recently analyzed the output data of 10 fine dust measuring stations and, as a result, announced that about 60% had an error that the existing atmospheric measurement concentration was higher. In order to accurately predict fine dust, the wind direction and measurement position must be corrected. In this paper, in order to solve these problems, fuzzy rules are used to solve these problems. In addition, in order to calculate the fine particulate sensation index actually felt by pedestrians on the street, a computer simulation experiment was conducted to calculate the fine particulate sensation index in consideration of weather conditions, temperature conditions, humidity conditions, and wind conditions.

A Comparative Study on the Welfare Assistive Devices In Korea and Japan (한국과 일본의 복지용구 품목 비교 연구)

  • Jeong, Hyun-Woo;Yeom, Hojun;Park, Sangsoo
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.6
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    • pp.405-411
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    • 2022
  • Korea's long-term care insurance for the elderly, which started in 2008, is a borrowed one from gaeho insurance, which started eight years earlier. Both countries have a policy of welfare equipment benefit systems to support the lives of the elderly who are intellectually and mentally weakened. In this study, we attempted to compare and examine the welfare equipment items in Korea with those in Japan and find out the characteristics of the items in Korea and Japan. In Korea, loitering-detection device, posture changing devices, and incontinence underwears were registered as welfare devices before Japan, and in Japan, automatic urine disposal systems, wheelchair electric assist device, position converters, and lifts for handicapped person were designated as welfare devices before Korea. In addition, the Japanese Ministry of Health, Labor and Welfare has announced the designation of the excretion prediction support device as a welfare device. If Korea and Japan cooperate to develop welfare equipment items together, it will be of great help in improving the quality of life of the elderly in both countries in a super-aged society.

On the Development of Spot and ARC Welding Dual-Purpose Robot System (스포트 및 아크 용접 겸용 로보트 시스템의 개발)

  • Ryuh, B.S.;Lee, Y.J.;Lee, Y.B.
    • Journal of the Korean Society for Precision Engineering
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    • v.12 no.6
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    • pp.13-19
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    • 1995
  • A dual purpose robot automation system is developed for both arc welding and spot welding by one robot within a cell. The need for automation of both arc welding and spot welding processes is urgent while the production volume is not so big as to accommodate separate stations for the two processes. Also, space is too narrow for separate stations to be settled down in the factory. A spot welding robot is chosen and the functions for arc welding are implemented in-house at cost of advanced functions. For the spot welding, a single pole type gun is used and the robot has to push down the plate to be wolded, which causes the robot positioning error. Therefore, position error compensation algorithm is developed. The basic functions for the arc welding processes are implemented using the digital I/O board of robot controller, PLC, and A/D conversion PCB. The weaving pattern is taught in meticulously by manual teach. A fixture unit is also developed for dual purpose. The main aspects of the system is presented in this paper especially in the design and implementation procedure. The signal diagrams and sequence logic diagrams are also included. The outcome of the dual purpose welding cell is the increased productivity and good production stability which is indispensable for production volume prediction. Also, it leads to reduction of manufacturing lead time.

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The relationship of E-selectin single-nucleotide polymorphisms with breast cancer in Iraqi Arab women

  • Bilal Fadil Zakariya;Asmaa M. Salih Almohaidi;Secil Akilli Simsek;Safaa A. Al-Waysi;Wijdan H. Al-Dabbagh;Areege Mustafa Kamal
    • Genomics & Informatics
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    • v.20 no.4
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    • pp.42.1-42.11
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    • 2022
  • Breast cancer (BC) is a significant threat to female health, with both modifiable and non-modifiable risk factors. It is essential to monitor patients regularly and to raise population awareness. Increasing research also suggests that E-selectin (SELE) may increase tumor angiogenesis and the development of cancer. This study investigated SELE single-nucleotide polymorphisms (SNPs) in the following positions: rs5367T/C, rs5368C/T, rs5362T/G, and rs5362T/C. Using polymerase chain reaction, significant differences in allele and genotype frequencies were found between BC patients and controls. Position rs5368 was associated with an increased risk of BC for the CT and TT genotypes, with odds ratios (ORs) of 16.3 and 6.90 (Fisher probability = 0.0001, p = 0.005). Women with the T allele had a 19.3-fold higher incidence of BC, while allele C may be a protective allele against BC (OR, 0.05). Heterozygous genotypes at rs5367, rs5362, and rs5362 were significantly more common in BC patients, with ORs of 5.70, 4.50, and 3.80, respectively. These SNPs may be associated with the risk of BC, because the frequency of mutant alleles was significantly higher in patients (OR: 4.26, 3.83, and 4.30, respectively) than in controls (OR: 0.23, 0.30, and 0.20, respectively). These SNPs may be considered a common genotype in the Iraqi population, with the wild-type allele having a protective fraction and the mutant allele having an environmental fraction. The results also revealed a 2-fold increase in gene expression in BC patients compared to controls, with a significant effect (p = 0.017). This study's findings confirm the importance of SELE polymorphisms in cancer risk prediction.

Performance Evaluation for ECG Signal Prediction Using Digital IIR Filter and Deep Learning (디지털 IIR Filter와 Deep Learning을 이용한 ECG 신호 예측을 위한 성능 평가)

  • Uei-Joong Yoon
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.4
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    • pp.611-616
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    • 2023
  • ECG(electrocardiogram) is a test used to measure the rate and regularity of heartbeats, as well as the size and position of the chambers, the presence of any damage to the heart, and the cause of all heart diseases can be found. Because the ECG signal obtained using the ECG-KIT includes noise in the ECG signal, noise must be removed from the ECG signal to apply to the deep learning. In this paper, the noise of the ECG signal was removed using the digital IIR Butterworth low-pass filter. When the performance evaluation of the three activation functions, sigmoid(), ReLU(), and tanh() functions, was compared using the deep learning model of LSTM, it was confirmed that the activation function with the smallest error was the tanh() function. Also, When the performance evaluation and elapsed time were compared for LSTM and GRU models, it was confirmed that the GRU model was superior to the LSTM model.

A Prediction and Distribution of Wetland Based on an E-GIS (E-GIS 기반의 습지분포 및 규모예측)

  • Jang, Yong Gu;Kim, Sang Seok
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.6D
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    • pp.1011-1017
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    • 2006
  • It is so sensitive that the wetland ecosystem very weak in artificial interference and environment change. wetlands are a transitional zone between aquatic and terrestrial ecosystems. This natural property is important to people and life. It is necessary to preservation and protection of the wetland with a countermeasure. we really need to Environment-GIS (E-GIS) and digital map which is included correct position, attribute data and range of the wetland. In this study, we take priority of making a database of wetland management. Moreover, we standardize a digital map production of wetland in our research and we improve accuracy of control survey using GPS surveying. The main purpose of this study is to suggest a pre-estimated wetland that have not yet been discovered. by analysing terrain, geological feature, a geographical distribution of plants and animals using GIS.

Geometric and Semantic Improvement for Unbiased Scene Graph Generation

  • Ruhui Zhang;Pengcheng Xu;Kang Kang;You Yang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.10
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    • pp.2643-2657
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    • 2023
  • Scene graphs are structured representations that can clearly convey objects and the relationships between them, but are often heavily biased due to the highly skewed, long-tailed relational labeling in the dataset. Indeed, the visual world itself and its descriptions are biased. Therefore, Unbiased Scene Graph Generation (USGG) prefers to train models to eliminate long-tail effects as much as possible, rather than altering the dataset directly. To this end, we propose Geometric and Semantic Improvement (GSI) for USGG to mitigate this issue. First, to fully exploit the feature information in the images, geometric dimension and semantic dimension enhancement modules are designed. The geometric module is designed from the perspective that the position information between neighboring object pairs will affect each other, which can improve the recall rate of the overall relationship in the dataset. The semantic module further processes the embedded word vector, which can enhance the acquisition of semantic information. Then, to improve the recall rate of the tail data, the Class Balanced Seesaw Loss (CBSLoss) is designed for the tail data. The recall rate of the prediction is improved by penalizing the body or tail relations that are judged incorrectly in the dataset. The experimental findings demonstrate that the GSI method performs better than mainstream models in terms of the mean Recall@K (mR@K) metric in three tasks. The long-tailed imbalance in the Visual Genome 150 (VG150) dataset is addressed better using the GSI method than by most of the existing methods.