• Title/Summary/Keyword: 3-Dimensional Network

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Characteristic Analysis using Equivalent Magnetic Circuit Network Method for Permanent Magnet Excited Transverse Flux Linear Motor with Spiral Core in a Mover (스파이럴 이동자 코어를 가지는 영구자석여자 횡자속 선형전동기의 등가자기회로망법을 이용한 특성해석)

  • Lee, Ji-Young;Kim, Ji-Won;Woo, Byung-Chul;Kang, Do-Hyun;Hoang, Trung Kien;Kim, Kwang-Woon
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.794_795
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    • 2009
  • This paper presents an analysis method for a permanent magnet excited Transverse Flux Linear Motor (TFLM) with spiral core in a mover. The spiral core is used as mover core in order to make 3-dimensional magnetic flux path at the TFLM which has 3-dimensional magnetic flux flow. Magnetic field is analyzed by three-dimensional Equivalent Magnetic Circuit Network (EMCN) method. And an imaginary part, 'flux barrier,' is introduced to consider the spiral core characteristic. The computed thrust forces is compared to the measured results to show the effect of presented analysis method.

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Deep Neural Network-Based Scene Graph Generation for 3D Simulated Indoor Environments (3차원 가상 실내 환경을 위한 심층 신경망 기반의 장면 그래프 생성)

  • Shin, Donghyeop;Kim, Incheol
    • KIPS Transactions on Software and Data Engineering
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    • v.8 no.5
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    • pp.205-212
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    • 2019
  • Scene graph is a kind of knowledge graph that represents both objects and their relationships found in a image. This paper proposes a 3D scene graph generation model for three-dimensional indoor environments. An 3D scene graph includes not only object types, their positions and attributes, but also three-dimensional spatial relationships between them, An 3D scene graph can be viewed as a prior knowledge base describing the given environment within that the agent will be deployed later. Therefore, 3D scene graphs can be used in many useful applications, such as visual question answering (VQA) and service robots. This proposed 3D scene graph generation model consists of four sub-networks: object detection network (ObjNet), attribute prediction network (AttNet), transfer network (TransNet), relationship prediction network (RelNet). Conducting several experiments with 3D simulated indoor environments provided by AI2-THOR, we confirmed that the proposed model shows high performance.

Study on Aerodynamic Optimization Design Process of Multistage Axial Turbine

  • Zhao, Honglei;Tan, Chunqing;Wang, Songtao;Han, Wanjin;Feng, Guotai
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2008.03a
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    • pp.130-135
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    • 2008
  • An aerodynamic optimization design process of multistage axial turbine is presented in this article: first, applying quasi-three dimensional(Q3D) design methods to conduct preliminary design and then adopting modern optimization design methods to implement multistage local optimization. Quasi-three dimensional(Q3D) design methods, which mainly refer to S2 flow surface direct problem calculation, adopt the S2 flow surface direct problem calculation program of Harbin Institute of Technology. Multistage local optimization adopts the software of Numeca/Design3D, which jointly adopts genetic algorithm and artificial neural network. The major principle of the methodology is that the successive design evaluation is performed by using an artificial neural network instead of a flow solver and the genetic algorithms may be used in an efficient way. Flow computation applies three-dimensional viscosity Navier Stokes(N-S) equation solver. Such optimization process has three features: (i) local optimization based on aerodynamic performance of every cascade; (ii) several times of optimizations being performed to every cascade; and (iii) alternate use of coarse grid and fine grid. Such process was applied to optimize a three-stage axial turbine. During the optimization, blade shape and meridional channel were respectively optimized. Through optimization, the total efficiency increased 1.3% and total power increased 2.4% while total flow rate only slightly changed. Therefore, the total performance was improved and the design objective was achieved. The preliminary design makes use of quasi-three dimensional(Q3D) design methods to achieve most reasonable parameter distribution so as to preliminarily enhance total performance. Then total performance will be further improved by adopting multistage local optimization design. Thus the design objective will be successfully achieved without huge expenditure of manpower and calculation time. Therefore, such optimization design process may be efficiently applied to the aerodynamic design optimization of multistage axial turbine.

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A Matlab and Simulink Based Three-Phase Inverter Fault Diagnosis Method Using Three-Dimensional Features

  • Talha, Muhammad;Asghar, Furqan;Kim, Sung Ho
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.16 no.3
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    • pp.173-180
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    • 2016
  • Fault detection and diagnosis is a task to monitor the occurrence of faults and pinpoint the exact location of faults in the system. Fault detection and diagnosis is gaining importance in development of efficient, advanced and safe industrial systems. Three phase inverter is one of the most common and excessively used power electronic system in industries. A fault diagnosis system is essential for safe and efficient usage of these inverters. This paper presents a fault detection technique and fault classification algorithm. A new feature extraction approach is proposed by using three-phase load current in three-dimensional space and neural network is used to diagnose the fault. Neural network is responsible of pinpointing the fault location. Proposed method and experiment results are presented in detail.

Simulator for Dynamic 2/3-Dimensional Switching of Computing Resources

  • Ki, Jang-Geun;Kwon, Kee-Young
    • International Journal of Internet, Broadcasting and Communication
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    • v.12 no.3
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    • pp.9-17
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    • 2020
  • In this paper, as part of the research for the infrastructure of very high flexible and reconfigurable data center using very high speed crossbar switches, we developed a simulator that can model two and three dimensional connection structure of switches with an efficient control algorithm using software defined network and verified the functions and analyzed the performance accordingly. The simulator consists of a control module and a switch module that was coded using Python language based on the Mininet and Ryu Openflow frameworks. The control module dynamically controls the operation of switching cells using a shortest multipath algorithm to calculate efficient paths adaptively between configurable computing resources. Performance analysis by using the simulator shows that the three-dimensional switch architecture can accommodate more hosts per port and has about 1.5 times more successful 1:n connections per port with the same number of switches than the two-dimensional architecture. Also simulation results show that connection length in a 3-dimensional way is shorter than that of 2-dimensional way and the unused switch ratio in a 3-dimensional case is lower than that of 2-dimensional cases.

Recognition of the Center Position of Bolt Hole in the Stand of Insulator Using Multilayer Neural Network (다층 뉴럴네트워크를 이용한 애자 스탠드에서의 볼트 구멍의 중심위치 인식)

  • 안경관;표성만
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.4
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    • pp.304-309
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    • 2003
  • Uninterrupted power supply has become indispensable during the maintenance task of active electric power lines as a result of today's highly information-oriented society and increasing demand of electric utilities. The maintenance task has the risk of electric shock and the danger of falling from high place. Therefore it is necessary to realize an autonomous robot system. In order to realize these tasks autonomously, the three dimensional position of target object such as electric line and the stand of insulator must be recognized accurately and rapidly. The approaching of an insulator and the wrenching of a nut task is selected as the typical task of the maintenance of active electric power distribution lines in this paper. Image recognition by multilayer neural network and optimal target position calculation method are newly proposed in order to recognize the center 3 dimensional position of the bolt hole in the stand of insulator. By the proposed image recognition method, it is proved that the center 3 dimensional position of the bolt hole can be recognized rapidly and accurately without regard to the pose of the stand of insulator. Finally the approaching and wrenching task is automatically realized using 6-link electro-hydraulic manipulators.

Accelerated Monte Carlo analysis of flow-based system reliability through artificial neural network-based surrogate models

  • Yoon, Sungsik;Lee, Young-Joo;Jung, Hyung-Jo
    • Smart Structures and Systems
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    • v.26 no.2
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    • pp.175-184
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    • 2020
  • Conventional Monte Carlo simulation-based methods for seismic risk assessment of water networks often require excessive computational time costs due to the hydraulic analysis. In this study, an Artificial Neural Network-based surrogate model was proposed to efficiently evaluate the flow-based system reliability of water distribution networks. The surrogate model was constructed with appropriate training parameters through trial-and-error procedures. Furthermore, a deep neural network with hidden layers and neurons was composed for the high-dimensional network. For network training, the input of the neural network was defined as the damage states of the k-dimensional network facilities, and the output was defined as the network system performance. To generate training data, random sampling was performed between earthquake magnitudes of 5.0 and 7.5, and hydraulic analyses were conducted to evaluate network performance. For a hydraulic simulation, EPANET-based MATLAB code was developed, and a pressure-driven analysis approach was adopted to represent an unsteady-state network. To demonstrate the constructed surrogate model, the actual water distribution network of A-city, South Korea, was adopted, and the network map was reconstructed from the geographic information system data. The surrogate model was able to predict network performance within a 3% relative error at trained epicenters in drastically reduced time. In addition, the accuracy of the surrogate model was estimated to within 3% relative error (5% for network performance lower than 0.2) at different epicenters to verify the robustness of the epicenter location. Therefore, it is concluded that ANN-based surrogate model can be utilized as an alternative model for efficient seismic risk assessment to within 5% of relative error.

Voltage Optimization of Power Delivery Networks through Power Bump and TSV Placement in 3D ICs

  • Jang, Cheoljon;Chong, Jong-Wha
    • ETRI Journal
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    • v.36 no.4
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    • pp.643-653
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    • 2014
  • To reduce interconnect delay and power consumption while improving chip performance, a three-dimensional integrated circuit (3D IC) has been developed with die-stacking and through-silicon via (TSV) techniques. The power supply problem is one of the essential challenges in 3D IC design because IR-drop caused by insufficient supply voltage in a 3D chip reduces the chip performance. In particular, power bumps and TSVs are placed to minimize IR-drop in a 3D power delivery network. In this paper, we propose a design methodology for 3D power delivery networks to minimize the number of power bumps and TSVs with optimum mesh structure and distribute voltage variation more uniformly by shifting the locations of power bumps and TSVs while satisfying IR-drop constraint. Simulation results show that our method can reduce the voltage variation by 29.7% on average while reducing the number of power bumps and TSVs by 76.2% and 15.4%, respectively.

Solution Structure of the Cytoplasmic Domain of Syndecan-3 by Two-dimensional NMR Spectroscopy

  • Yeo, In-Young;Koo, Bon-Kyung;Oh, Eok-Soo;Han, Inn-Oc;Lee, Weon-Tae
    • Bulletin of the Korean Chemical Society
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    • v.29 no.5
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    • pp.1013-1017
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    • 2008
  • Syndecan-3 is a cell-surface heparan sulfate proteoglycan, which performs a variety of functions during cell adhension process. It is also a coreceptor for growth factor, mediating cell-cell and cell-matrix interaction. Syndecan-3 contains a cytoplasmic domain potentially associated with the cytoskeleton. Syndecan-3 is specifically expressed in neuron cell and has related to neuron cell differentiation and development of actin filament in cell migration. Syndecans each have a unique, central, and variable (V) region in their cytoplasmic domains. And that region of syndecan-3 may modulate the interactions of the conserved C1 regions of the cytoplasmic domains by tyrosine phosphorylation. Cytoplasmic domain of syndecan-3 has been synthesized for NMR structural studies. The solution structure of syndecan-3 cytoplasmic domain has been determined by two-dimensional NMR spectroscopy and simulated-annealing calculation. The cytoplasmic domain of the syndecan proteins has a tendency to form a dimmer conformation with a central cavity, however, that of syndecan-3 demonstrated a monomer conformation with a flexible region near C-terminus. The structural information might add knowledge about the structure-function relationships among syndecan proteins.

The 3 Dimensional Triangulation Scheme based on the Space Segmentation in WPAN

  • Lee, Dong Myung;Lee, Ho Chul
    • Journal of Engineering Education Research
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    • v.15 no.5
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    • pp.93-97
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    • 2012
  • Most of ubiquitous computing devices such as stereo camera, ultrasonic sensor based MIT cricket system and other wireless sensor network devices are widely applied to the 2 Dimensional(2D) localization system in today. Because stereo camera cannot estimate the optimal location between moving node and beacon node in Wireless Personal Area Network(WPAN) under Non Line Of Sight(NLOS) environment, it is a great weakness point to the design of the 2D localization system in indoor environment. But the conventional 2D triangulation scheme that is adapted to the MIT cricket system cannot estimate the 3 Dimensional(3D) coordinate values for estimation of the optimal location of the moving node generally. Therefore, the 3D triangulation scheme based on the space segmentation in WPAN is suggested in this paper. The measuring data in the suggested scheme by computer simulation is compared with that of the geographic measuring data in the AutoCAD software system. The average error of coordinates values(x,y,z) of the moving node is calculated to 0.008m by the suggested scheme. From the results, it can be seen that the location correctness of the suggested scheme is very excellent for using the localization system in WPAN.