• Title/Summary/Keyword: multi-net

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Design and Implementation of Multi-mode Mobile Device for supporting License Shared Access (면허기반 주파수 공동 사용을 위한 멀티모드 단말기 설계 및 구현)

  • Jin, Yong;Choi, Seungwon
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.12 no.4
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    • pp.81-87
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    • 2016
  • Recently, as the heterogeneous network (HetNet) has been deployed widely to support various kinds of Radio Access Networks(RANs) with a combination of Macro, Pico, and/or Femto cells, research and standardization efforts have been very active regarding the concept of Licensed Shared Access (LSA) for supporting spectrum sharing. In order for a mobile device to efficiently support the spectrum sharing, the mobile device shall be reconfigurable, meaning that its radio application code has to be adaptively changed in accordance with the hopping of desired spectral band. Especially, Working Group 2 (WG2) of Technical Committee (TC) Reconfigurable Radio System (RRS) of European Telecommunications Standards Institute (ETSI) has been a main driving force for developing standard architecture for Multi-mode Mobile Device (MD) that can be applied to the LSA system. In this paper, we introduce the Multi-mode MD architecture for supporting LSA-based spectrum sharing. An implementation of a test-bed of Multi-mode MD is presented in order to verify the feasibility of the standard MD architecture for the purpose of LSA-based spectrum sharing through various experimental tests.

Performance characteristics of a multi-directional underwater CCTV camera system to use in the artificial reef survey (인공어초 조사용 다방향 수중 CCTV 카메라 시스템의 성능 특성)

  • Lee, Dae-Jae
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.47 no.2
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    • pp.146-152
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    • 2011
  • Underwater CCTV camera systems are increasingly replaced the traditional net approach of assessing the species, numbers and aggregation patterns of marine animals distributing around the artificial reefs installed in the inshore fishing grounds, in particular, in relation to the biological investigation of behavior and distribution patterns of target fishes. In relation to these needs, we developed a multi-directional underwater CCTV camera system to use in detecting and tracking marine animals in the artificial reef ground. The marine targets to be investigated were independently tracked by using a camera module toward the bottom and four camera modules installed in the interval of $90^{\circ}$ in horizontal plane and inclination of $45^{\circ}$ in vertical plane of the CCTV system without the overlap of video frames by each camera module. From the results of several field tests at sea, we believe that the developed multi-directional underwater CCTV camera system will contribute to a better understanding in evaluating the effect of artificial reefs installed in the inshore fishing grounds.

DEVELOPMENT OF THE MULTI-DIMENSIONAL HYDRAULIC COMPONENT FOR THE BEST ESTIMATE SYSTEM ANALYSIS CODE MARS

  • Bae, Sung-Won;Chung, Bub-Dong
    • Nuclear Engineering and Technology
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    • v.41 no.10
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    • pp.1347-1360
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    • 2009
  • A multi-dimensional component for the thermal-hydraulic system analysis code, MARS, was developed for a more realistic three-dimensional analysis of nuclear systems. A three-dimensional and two-fluid model for a two-phase flow in Cartesian and cylindrical coordinates was employed. The governing equations and physical constitutive relationships were extended from those of a one-dimensional version. The numerical solution method adopted a semi-implicit and finite-difference method based on a staggered-grid mesh and a donor-cell scheme. The relevant length scale was very coarse compared to commercial computational fluid dynamics tools. Thus a simple Prandtl's mixing length turbulence model was applied to interpret the turbulent induced momentum and energy diffusivity. Non drag interfacial forces were not considered as in the general nuclear system codes. Several conceptual cases with analytic solutions were chosen and analyzed to assess the fundamental terms. RPI air-water and UPTF 7 tests were simulated and compared to the experimental data. The simulation results for the RPI air-water two-phase flow experiment showed good agreement with the measured void fraction. The simulation results for the UPTF downcomer test 7 were compared to the experiment data and the results from other multi-dimensional system codes for the ECC delivery flow.

Fabrication of Porous Reaction Bonded Silicon Carbide with Multi-Layered Pore Structures (다층 기공구조를 갖는 다공성 반응소결 탄화규소 다공체 제조)

  • Cho, Gyoung-Sun;Kim, Gyu-Mi;Park, Sang-Whan
    • Journal of the Korean Ceramic Society
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    • v.46 no.5
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    • pp.534-539
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    • 2009
  • Reaction Bonded Silicon Carbide(RBSC) has been used for engineering ceramics due to low-temperature fabrication and near-net shape products with excellent structural properties such as thermal shock resistance, corrosion resistance and mechanical strength. Recently, attempts have been made to develop hot gas filter with gradient pore structure by RBSC to overcome weakness of commercial clay-bonded SiC filter such as low fracture toughness and low reliability. In this study a fabrication process of porous RBSC with multi-layer pore structure with gradient pore size was developed. The support layer of the RBSC with multi-layer pore structure was fabricated by conventional Si infiltration process. The intermediate and filter layers consisted of phenolic resin and fine SiC powder were prepared by dip-coating of the support RBSC in slurry of SiC and phenol resin. The temperature of $1550^{\circ}C$ to make Si left in RBSC support layer infiltrate into dip-coated layer to produce SiC by reacting with pyro-carbon from phenol resin.

A Multi-Stage Convolution Machine with Scaling and Dilation for Human Pose Estimation

  • Nie, Yali;Lee, Jaehwan;Yoon, Sook;Park, Dong Sun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.6
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    • pp.3182-3198
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    • 2019
  • Vision-based Human Pose Estimation has been considered as one of challenging research subjects due to problems including confounding background clutter, diversity of human appearances and illumination changes in scenes. To tackle these problems, we propose to use a new multi-stage convolution machine for estimating human pose. To provide better heatmap prediction of body joints, the proposed machine repeatedly produces multiple predictions according to stages with receptive field large enough for learning the long-range spatial relationship. And stages are composed of various modules according to their strategic purposes. Pyramid stacking module and dilation module are used to handle problem of human pose at multiple scales. Their multi-scale information from different receptive fields are fused with concatenation, which can catch more contextual information from different features. And spatial and channel information of a given input are converted to gating factors by squeezing the feature maps to a single numeric value based on its importance in order to give each of the network channels different weights. Compared with other ConvNet-based architectures, we demonstrated that our proposed architecture achieved higher accuracy on experiments using standard benchmarks of LSP and MPII pose datasets.

Learning-Based Multiple Pooling Fusion in Multi-View Convolutional Neural Network for 3D Model Classification and Retrieval

  • Zeng, Hui;Wang, Qi;Li, Chen;Song, Wei
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1179-1191
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    • 2019
  • We design an ingenious view-pooling method named learning-based multiple pooling fusion (LMPF), and apply it to multi-view convolutional neural network (MVCNN) for 3D model classification or retrieval. By this means, multi-view feature maps projected from a 3D model can be compiled as a simple and effective feature descriptor. The LMPF method fuses the max pooling method and the mean pooling method by learning a set of optimal weights. Compared with the hand-crafted approaches such as max pooling and mean pooling, the LMPF method can decrease the information loss effectively because of its "learning" ability. Experiments on ModelNet40 dataset and McGill dataset are presented and the results verify that LMPF can outperform those previous methods to a great extent.

Automatic assessment of post-earthquake buildings based on multi-task deep learning with auxiliary tasks

  • Zhihang Li;Huamei Zhu;Mengqi Huang;Pengxuan Ji;Hongyu Huang;Qianbing Zhang
    • Smart Structures and Systems
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    • v.31 no.4
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    • pp.383-392
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    • 2023
  • Post-earthquake building condition assessment is crucial for subsequent rescue and remediation and can be automated by emerging computer vision and deep learning technologies. This study is based on an endeavour for the 2nd International Competition of Structural Health Monitoring (IC-SHM 2021). The task package includes five image segmentation objectives - defects (crack/spall/rebar exposure), structural component, and damage state. The structural component and damage state tasks are identified as the priority that can form actionable decisions. A multi-task Convolutional Neural Network (CNN) is proposed to conduct the two major tasks simultaneously. The rest 3 sub-tasks (spall/crack/rebar exposure) were incorporated as auxiliary tasks. By synchronously learning defect information (spall/crack/rebar exposure), the multi-task CNN model outperforms the counterpart single-task models in recognizing structural components and estimating damage states. Particularly, the pixel-level damage state estimation witnesses a mIoU (mean intersection over union) improvement from 0.5855 to 0.6374. For the defect detection tasks, rebar exposure is omitted due to the extremely biased sample distribution. The segmentations of crack and spall are automated by single-task U-Net but with extra efforts to resample the provided data. The segmentation of small objects (spall and crack) benefits from the resampling method, with a substantial IoU increment of nearly 10%.

FakedBits- Detecting Fake Information on Social Platforms using Multi-Modal Features

  • Dilip Kumar, Sharma;Bhuvanesh, Singh;Saurabh, Agarwal;Hyunsung, Kim;Raj, Sharma
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.1
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    • pp.51-73
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    • 2023
  • Social media play a significant role in communicating information across the globe, connecting with loved ones, getting the news, communicating ideas, etc. However, a group of people uses social media to spread fake information, which has a bad impact on society. Therefore, minimizing fake news and its detection are the two primary challenges that need to be addressed. This paper presents a multi-modal deep learning technique to address the above challenges. The proposed modal can use and process visual and textual features. Therefore, it has the ability to detect fake information from visual and textual data. We used EfficientNetB0 and a sentence transformer, respectively, for detecting counterfeit images and for textural learning. Feature embedding is performed at individual channels, whilst fusion is done at the last classification layer. The late fusion is applied intentionally to mitigate the noisy data that are generated by multi-modalities. Extensive experiments are conducted, and performance is evaluated against state-of-the-art methods. Three real-world benchmark datasets, such as MediaEval (Twitter), Weibo, and Fakeddit, are used for experimentation. Result reveals that the proposed modal outperformed the state-of-the-art methods and achieved an accuracy of 86.48%, 82.50%, and 88.80%, respectively, for MediaEval (Twitter), Weibo, and Fakeddit datasets.

Condensation oscillation characteristic of steam with non-condensable gas through multi-hole sparger at low mass flux

  • Dandi Zhang;Lili Tong;Xuewu Cao
    • Nuclear Engineering and Technology
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    • v.55 no.2
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    • pp.780-791
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    • 2023
  • To study oscillation characteristic of steam and non-condensable gas direct contact condensation through multi-hole sparger at low mass flux, a series of experiments of pure steam and mixture gas condensation have been carried out under the conditions of steam mass flux of 20-120kg/m2s, water temperature of 20-95 ℃ and mass fraction of non-condensable gas of 0-5%. The regime map of pure steam condensation through multi-hole sparger is divided into steam chugging, separated bubble, aggregated bubble and escaping aggregated bubble. The bubbles behavior of synchronization in the same hole columns and desynchronized excitation between different hole columns can be found. The coalescence effect of mixture bubbles increases with water temperature and non-condensable gas content increasing. Pressure oscillation intensity of pure steam condensation first increases and then decreases with water temperature increasing, and increases with steam mass flux increasing. Pressure oscillation intensity of mixture gas condensation decreases with water temperature and non-condensable gas content increasing, which is significantly weaker than that of pure steam condensation. The oscillation dominant frequency decreases with the rise of water temperature and non-condensable gas content. The correlations for oscillation intensity and dominant frequency respectively are developed in pure steam and mixture gas condensation at low mass flux.

Multi-objective optimization of printed circuit heat exchanger with airfoil fins based on the improved PSO-BP neural network and the NSGA-II algorithm

  • Jiabing Wang;Linlang Zeng;Kun Yang
    • Nuclear Engineering and Technology
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    • v.55 no.6
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    • pp.2125-2138
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    • 2023
  • The printed circuit heat exchanger (PCHE) with airfoil fins has the benefits of high compactness, high efficiency and superior heat transfer performance. A novel multi-objective optimization approach is presented to design the airfoil fin PCHE in this paper. Three optimization design variables (the vertical number, the horizontal number and the staggered number) are obtained by means of dimensionless airfoil fin arrangement parameters. And the optimization objective is to maximize the Nusselt number (Nu) and minimize the Fanning friction factor (f). Firstly, in order to investigate the impact of design variables on the thermal-hydraulic performance, a parametric study via the design of experiments is proposed. Subsequently, the relationships between three optimization design variables and two objective functions (Nu and f) are characterized by an improved particle swarm optimization-backpropagation artificial neural network. Finally, a multi-objective optimization is used to construct the Pareto optimal front, in which the non-dominated sorting genetic algorithm II is used. The comprehensive performance is found to be the best when the airfoil fins are completely staggered arrangement. And the best compromise solution based on the TOPSIS method is identified as the optimal solution, which can achieve the requirement of high heat transfer performance and low flow resistance.