• Title/Summary/Keyword: 구조적 조인 알고리즘

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Development of Robot Performance Platform Interoperating with an Industrial Robot Arm and a Humanoid Robot Actor (산업용 로봇 Arm과 휴머노이드 로봇 액터를 연동한 로봇 공연 플랫폼 개발)

  • Cho, Jayang;Kim, Jinyoung;Lee, Sulhee;Lee, Sang-won;Kim, Hyungtae
    • Journal of Broadcast Engineering
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    • v.25 no.4
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    • pp.487-496
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    • 2020
  • For the purpose of next generation technology for robot perfomances, a RAoRA (Robot Actor on Robot Arm) structure was proposed using a robot arm joined with a humanoid robot actor. Mechanical analysis, machine design and fabrication were performed for motions combined with the robot arm and the humanoid robot actor. Kinematical analysis for 3D model, spline interpolation of positions, motion control algorithm and control devices were developed for movements of the robot actor. Preliminary visualization, simulation tools and integrated operation of consoles were constructed for the non-professionals to produce intuitive and safe contents. Air walk was applied to test the developed platform. The air walk is a natural walk close to a floor or slow ascension to the air. The RAoRA also executed a performance with 5 minute-running time. Finally, the proposed platform of robot performance presented intensive and live motions which was impossible in conventional robot performances.

Development of AAB (Algorithm-Aided BIM) Based 3D Design Bases Management System in Nuclear Power Plant (Algorithm-Aided BIM 기반 원전 3차원 설계기준 관리시스템 개발)

  • Shin, Jaeseop
    • Korean Journal of Construction Engineering and Management
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    • v.20 no.2
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    • pp.28-36
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    • 2019
  • The APR1400 (Advanced Power Reactor 1400MW) nuclear power plant is a large-scale national infrastructure facility with a total project cost of 8.6 trillion won and a project period of 10 years or more. The total project area is about 2.17 million square meters and consists of more than 20 buildings and structures. And the total number of drawings required for construction is about 65,000. In order to design such a large facility, it is important to establish a design standard that reflects the design intent and can increase conformity between documents (drawings). To this end, a design bases document (DBD) reflecting the design bases that extracted in regulatory requirements (e.g. 10CFR50, Korean Law, etc.) is created. However, although the design bases are important concepts that are a big framework for the whole design of the nuclear power plant, they are managed in 2-dimensional by the experts in each field fragmentarily. Therefore, in order to improve the usability of building information, we developed BIM(Building Information Model) based 3-dimensional design bases management system. For this purpose, the concept of design bases information layer (DBIL) was introduced. Through the simulation of developed system, design bases attribute and element data extraction for each DBIL was confirmed, and walls, floors, doors, and penetrations with DBIL were successfully extracted.

Evaluating Reverse Logistics Networks with Centralized Centers : Hybrid Genetic Algorithm Approach (집중형센터를 가진 역물류네트워크 평가 : 혼합형 유전알고리즘 접근법)

  • Yun, YoungSu
    • Journal of Intelligence and Information Systems
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    • v.19 no.4
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    • pp.55-79
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    • 2013
  • In this paper, we propose a hybrid genetic algorithm (HGA) approach to effectively solve the reverse logistics network with centralized centers (RLNCC). For the proposed HGA approach, genetic algorithm (GA) is used as a main algorithm. For implementing GA, a new bit-string representation scheme using 0 and 1 values is suggested, which can easily make initial population of GA. As genetic operators, the elitist strategy in enlarged sampling space developed by Gen and Chang (1997), a new two-point crossover operator, and a new random mutation operator are used for selection, crossover and mutation, respectively. For hybrid concept of GA, an iterative hill climbing method (IHCM) developed by Michalewicz (1994) is inserted into HGA search loop. The IHCM is one of local search techniques and precisely explores the space converged by GA search. The RLNCC is composed of collection centers, remanufacturing centers, redistribution centers, and secondary markets in reverse logistics networks. Of the centers and secondary markets, only one collection center, remanufacturing center, redistribution center, and secondary market should be opened in reverse logistics networks. Some assumptions are considered for effectively implementing the RLNCC The RLNCC is represented by a mixed integer programming (MIP) model using indexes, parameters and decision variables. The objective function of the MIP model is to minimize the total cost which is consisted of transportation cost, fixed cost, and handling cost. The transportation cost is obtained by transporting the returned products between each centers and secondary markets. The fixed cost is calculated by opening or closing decision at each center and secondary markets. That is, if there are three collection centers (the opening costs of collection center 1 2, and 3 are 10.5, 12.1, 8.9, respectively), and the collection center 1 is opened and the remainders are all closed, then the fixed cost is 10.5. The handling cost means the cost of treating the products returned from customers at each center and secondary markets which are opened at each RLNCC stage. The RLNCC is solved by the proposed HGA approach. In numerical experiment, the proposed HGA and a conventional competing approach is compared with each other using various measures of performance. For the conventional competing approach, the GA approach by Yun (2013) is used. The GA approach has not any local search technique such as the IHCM proposed the HGA approach. As measures of performance, CPU time, optimal solution, and optimal setting are used. Two types of the RLNCC with different numbers of customers, collection centers, remanufacturing centers, redistribution centers and secondary markets are presented for comparing the performances of the HGA and GA approaches. The MIP models using the two types of the RLNCC are programmed by Visual Basic Version 6.0, and the computer implementing environment is the IBM compatible PC with 3.06Ghz CPU speed and 1GB RAM on Windows XP. The parameters used in the HGA and GA approaches are that the total number of generations is 10,000, population size 20, crossover rate 0.5, mutation rate 0.1, and the search range for the IHCM is 2.0. Total 20 iterations are made for eliminating the randomness of the searches of the HGA and GA approaches. With performance comparisons, network representations by opening/closing decision, and convergence processes using two types of the RLNCCs, the experimental result shows that the HGA has significantly better performance in terms of the optimal solution than the GA, though the GA is slightly quicker than the HGA in terms of the CPU time. Finally, it has been proved that the proposed HGA approach is more efficient than conventional GA approach in two types of the RLNCC since the former has a GA search process as well as a local search process for additional search scheme, while the latter has a GA search process alone. For a future study, much more large-sized RLNCCs will be tested for robustness of our approach.

A Study on the Comparison of Detected Vein Images by NIR LED Quantity of Vein Detector (정맥검출기의 NIR LED 수량에 따른 검출된 정맥 이미지 비교에 관한 연구)

  • Jae-Hyun, Jo;Jin-Hyoung, Jeong;Seung-Hun, Kim;Sang-Sik, Lee
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.15 no.6
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    • pp.485-491
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    • 2022
  • Intravenous injection is the most frequent invasive treatment for inpatients and is widely used for parenteral nutrition administration and blood products, and more than 1 billion procedures are used for peripheral catheter insertion, blood collection, and other IV therapy per year. Intravenous injection is one of the difficult procedures to be performed only by trained nurses with intravenous injection training, and failure can lead to thrombosis and hematoma or nerve damage to the vein. Accordingly, studies on auxiliary equipment capable of visualizing the vein structure of the back of the hand or arm are being published to reduce errors during intravenous injection. This study is a study on the performance difference according to the number of LEDs irradiating the 850nm wavelength band on a vein detector that visualizes the vein during intravenous injection. Four LED PCBs were produced by attaching NIR filters to CCD and CMOS camera lenses irradiated on the skin to acquire images, sharpen the acquired images using image processing algorithms, and project the sharpened images onto the skin. After that, each PCB was attached to the front end of the vein detector to detect the vein image and create a performance comparison questionnaire based on the vein image obtained for performance evaluation. The survey was conducted on 20 nurses working at K Hospital.

Statistical Method and Deep Learning Model for Sea Surface Temperature Prediction (수온 데이터 예측 연구를 위한 통계적 방법과 딥러닝 모델 적용 연구)

  • Moon-Won Cho;Heung-Bae Choi;Myeong-Soo Han;Eun-Song Jung;Tae-Soon Kang
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.6
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    • pp.543-551
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    • 2023
  • As climate change continues to prompt an increasing demand for advancements in disaster and safety management technologies to address abnormal high water temperatures, typhoons, floods, and droughts, sea surface temperature has emerged as a pivotal factor for swiftly assessing the impacts of summer harmful algal blooms in the seas surrounding Korean Peninsula and the formation and dissipation of cold water along the East Coast of Korea. Therefore, this study sought to gauge predictive performance by leveraging statistical methods and deep learning algorithms to harness sea surface temperature data effectively for marine anomaly research. The sea surface temperature data employed in the predictions spans from 2018 to 2022 and originates from the Heuksando Tidal Observatory. Both traditional statistical ARIMA methods and advanced deep learning models, including long short-term memory (LSTM) and gated recurrent unit (GRU), were employed. Furthermore, prediction performance was evaluated using the attention LSTM technique. The technique integrated an attention mechanism into the sequence-to-sequence (s2s), further augmenting the performance of LSTM. The results showed that the attention LSTM model outperformed the other models, signifying its superior predictive performance. Additionally, fine-tuning hyperparameters can improve sea surface temperature performance.

Visualization and Localization of Fusion Image Using VRML for Three-dimensional Modeling of Epileptic Seizure Focus (VRML을 이용한 융합 영상에서 간질환자 발작 진원지의 3차원적 가시화와 위치 측정 구현)

  • 이상호;김동현;유선국;정해조;윤미진;손혜경;강원석;이종두;김희중
    • Progress in Medical Physics
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    • v.14 no.1
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    • pp.34-42
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    • 2003
  • In medical imaging, three-dimensional (3D) display using Virtual Reality Modeling Language (VRML) as a portable file format can give intuitive information more efficiently on the World Wide Web (WWW). The web-based 3D visualization of functional images combined with anatomical images has not studied much in systematic ways. The goal of this study was to achieve a simultaneous observation of 3D anatomic and functional models with planar images on the WWW, providing their locational information in 3D space with a measuring implement using VRML. MRI and ictal-interictal SPECT images were obtained from one epileptic patient. Subtraction ictal SPECT co-registered to MRI (SISCOM) was performed to improve identification of a seizure focus. SISCOM image volumes were held by thresholds above one standard deviation (1-SD) and two standard deviations (2-SD). SISCOM foci and boundaries of gray matter, white matter, and cerebrospinal fluid (CSF) in the MRI volume were segmented and rendered to VRML polygonal surfaces by marching cube algorithm. Line profiles of x and y-axis that represent real lengths on an image were acquired and their maximum lengths were the same as 211.67 mm. The real size vs. the rendered VRML surface size was approximately the ratio of 1 to 605.9. A VRML measuring tool was made and merged with previous VRML surfaces. User interface tools were embedded with Java Script routines to display MRI planar images as cross sections of 3D surface models and to set transparencies of 3D surface models. When transparencies of 3D surface models were properly controlled, a fused display of the brain geometry with 3D distributions of focal activated regions provided intuitively spatial correlations among three 3D surface models. The epileptic seizure focus was in the right temporal lobe of the brain. The real position of the seizure focus could be verified by the VRML measuring tool and the anatomy corresponding to the seizure focus could be confirmed by MRI planar images crossing 3D surface models. The VRML application developed in this study may have several advantages. Firstly, 3D fused display and control of anatomic and functional image were achieved on the m. Secondly, the vector analysis of a 3D surface model was defined by the VRML measuring tool based on the real size. Finally, the anatomy corresponding to the seizure focus was intuitively detected by correlations with MRI images. Our web based visualization of 3-D fusion image and its localization will be a help to online research and education in diagnostic radiology, therapeutic radiology, and surgery applications.

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