• Title/Summary/Keyword: Large Scale Data

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Role-based Self-Organization Protocol of Clustering Hierarchy for Wireless Sensor Networks (무선 센서 네트워크를 위한 계층형 클러스터링의 역할 기반 자가 구성 프로토콜)

  • Go, Sung-Hyun;Kim, Hyoung-Jin
    • Journal of the Korea Society of Computer and Information
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    • v.13 no.6
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    • pp.137-145
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    • 2008
  • In general, a large-scale wireless sensor network(WSNs) is composed of hundreds of or thousands of sensor nodes. In this large-scale wireless sensor networks, it is required to maintain and manage the networks to lower management cost and obtain high energy efficiency. Users should be provided with sensing service at the level of quality for users through an efficient system. In evaluating the result data quality provided from this network to users, the number of sensors related to event detection has an important role. Accordingly, the network protocol which can provide proper QoS at the level of users demanding quality should be designed in a way such that the overall system function has not to be influenced even if some sensor nodes are in error. The energy consumption is minimized at the same time. The protocol suggested in this article is based on the LEACH protocol and is a role-based self-Organization one that is appropriate for large-scale networks which need constant monitoring.

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ABox Realization Reasoning in Distributed In-Memory System (분산 메모리 환경에서의 ABox 실체화 추론)

  • Lee, Wan-Gon;Park, Young-Tack
    • Journal of KIISE
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    • v.42 no.7
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    • pp.852-859
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    • 2015
  • As the amount of knowledge information significantly increases, a lot of progress has been made in the studies focusing on how to reason large scale ontology effectively at the level of RDFS or OWL. These reasoning methods are divided into TBox classifications and ABox realizations. A TBox classification mainly deals with integrity and dependencies in schema, whereas an ABox realization mainly handles a variety of issues in instances. Therefore, the ABox realization is very important in practical applications. In this paper, we propose a realization method for analyzing the constraint of the specified class, so that the reasoning system automatically infers the classes to which instances belong. Unlike conventional methods that take advantage of the object oriented language based distributed file system, we propose a large scale ontology reasoning method using spark, which is a functional programming-based in-memory system. To verify the effectiveness of the proposed method, we used instances created from the Wine ontology by W3C(120 to 600 million triples). The proposed system processed the largest 600 million triples and generated 951 million triples in 51 minutes (696 K triple / sec) in our largest experiment.

Factors Affecting Public Non-compliance With Large-scale Social Restrictions to Control COVID-19 Transmission in Greater Jakarta, Indonesia

  • Rosha, Bunga Christitha;Suryaputri, Indri Yunita;Irawan, Irlina Raswanti;Arfines, Prisca Petty;Triwinarto, Agus
    • Journal of Preventive Medicine and Public Health
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    • v.54 no.4
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    • pp.221-229
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    • 2021
  • Objectives: The Indonesian government issued large-scale social restrictions (called Pembatasan Sosial Berskala Besar, or PSBB) at the beginning of the coronavirus disease 2019 (COVID-19) pandemic to control the spread of COVID-19 in Jakarta, Bogor, Depok, Tangerang, and Bekasi (Greater Jakarta). Public compliance poses a challenge when implementing large-scale social restrictions, and various factors have contributed to public non-compliance with the regulation. This study aimed to determine the degree of non-compliance and identify the factors that contributed to public non-compliance with the PSBB in Greater Jakarta, Indonesia. Methods: This was a quantitative study with a cross-sectional design. A total of 839 residents of Greater Jakarta participated in this study. Data were collected online using a Google Form, and convenience sampling was undertaken. Univariate and multivariate analyses were performed to explore the relationships between public non-compliance with the PSBB regulation and socio-demographic variables, respondents' opinion of the PSBB, and social capital. Results: A total of 22.6% of subjects reported participating in activities that did not comply with the PSBB. The variables that most affected non-compliance with the PSBB were age, gender, income, opinion of the PSBB, and social capital. Conclusions: Strengthening social capital and providing information about COVID-19 prevention measures, such as washing one's hands with soap, wearing masks properly, and maintaining social distancing, is essential. Robust public understanding will foster trust and cooperation with regard to COVID-19 prevention efforts and provide a basis for mutual agreement regarding rules/penalties.

Development of Large-scale Tool Dynamometer for Measuring Three-axis Individual Force (3축 분력 측정이 가능한 대형 공구동력계 개발)

  • Kim, Joong-Seon;Wang, Duck-Hyun
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.18 no.5
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    • pp.29-36
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    • 2019
  • In modern society in which the fourth industrial revolution has come to the fore and rapid technology innovations are taking place, a phenomenon of making and selling small quantities of various products that consumers want instead of mass producing one item has emerged. As the market is moving toward the multi-item small-sized production system, there is a need for a system in which a machine independently judges and carries out machining and post-processing. In order for a machine to judge processing on its own, it is necessary to measure the force applied to a product. This study aimed to develop a large-scale dynamometer that enables three-axis measurement using octagonal ring load cells. As for the device's configuration, four octagonal ring load cells, which were previously researched, were used to enable three-axis measurement. It was reconfigured by modifying the attachment position of the octagonal ring load cells' strain gauge and the Wheatstone bridge of each axis, and a system was set up to allow the monitoring of data measured through the monitor. The configured device calculated a strain rate by an experiment, and this rate was compared with the theoretical strain rate to find a correction value. The correction value was entered into a formula, deriving a modified formula. The modified formula was entered into the device, which completed the large-scale dynamometer.

When galaxies align: intrinsic alignments of the progenitors of elliptical galaxies in the Horizon-AGN simulation

  • James Bate;Nora Elisa Chisari;Sandrine Codis;Garreth Martin;Yohan Dubois;Julien Devriendt;Christophe Pichon;Adrianne Slyz
    • Monthly Notices of the Royal Astronomical Society
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    • v.491 no.3
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    • pp.4057-4068
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    • 2020
  • Elliptical galaxies today appear aligned with the large-scale structure of the Universe, but it is still an open question when they acquire this alignment. Observational data are currently insufficient to provide constraints on the time evolution of intrinsic alignments, and hence existing models range from assuming that galaxies gain some primordial alignment at formation, to suggesting that they react instantaneously to tidal interactions with the large-scale structure. Using the cosmological hydrodynamical simulation Horizon-AGN, we measure the relative alignments between the major axes of galaxies and eigenvectors of the tidal field as a function of redshift. We focus on constraining the time evolution of the alignment of the main progenitors of massive z = 0 elliptical galaxies, the main weak-lensing contaminant at low redshift. We show that this population, which at z = 0 has a stellar mass above 1010.4 M, transitions from having no alignment with the tidal field at z = 3, to a significant alignment by z = 1. From z = 0.5, they preserve their alignment at an approximately constant level until z = 0. We find a mass dependence of the alignment signal of elliptical progenitors, whereby ellipticals that are less massive today (1010.4 < M/M < 1010.7) do not become aligned till later redshifts (z < 2), compared to more massive counterparts. We also present an extended study of progenitor alignments in the parameter space of stellar mass and galaxy dynamics, the impact of shape definition, and tidal field smoothing.

Sample Size Determination for the Estimation of Population Density of Marine Benthos on a Tidal Flat and a Subtidal Area, Korea

  • Koh, Chul-Hwan;Kang, Seong-Gil
    • Journal of the korean society of oceanography
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    • v.33 no.3
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    • pp.113-122
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    • 1998
  • The requisite numbers of sample replicates for the population study of soft-bottom benthos were estimated from survey data on the Songdo tidal flat and subtidal zone in Youngil Bay, Korea. Large numbers of samples were taken; two-hundred-fifty 0.02 m$^2$ box corers and fifty 0.1m$^2$ van Veen grabs were taken on the Songdo tidal flat and in Youngil Bay, respectively. The effect of sampler size on sampling efforts was investigated by pooling the unit samples in pairs, fours, eights, etc. The requisite number of sample replicates (n$_r$) was determined by sample variance (s$^2$) and mean (m) function (n$_r$:s$^2$/P$^2$m$^2$), at P=0.2 level, in which s$^2$ and m were calculated from the counts of individuals collected. For example, seven samples of 0.02 m$^2$ corer for the intertidal and two samples of 0.1 m$^2$ van Veen grab for subtidal fauna were required to estimate the total density of community. The smaller sampler size was more efficient than larger ones when sampling costs were compared on the basis of the total sampling area. The requisite number of sample replicates was also predicted ($\^{n}$n$_r$) by substituting $\^{s}$$^2$ obtained from the regression of s$^2$ against m using the Taylor's power law ($\^{s}$$^2$:am$^b$). The regression line of survey data on s$^2$ and m plotted on log scale was well fitted to the Taylor's power law (r$^2$${\geq}$0.95, p<;0.001) over the whole range of m. The exponent b was, however, varied when it was estimated from m which was categorized into classes by its scale. The fitted exponent b was large when both density class and the sampler size were large. The number of sample replicates, therefore, could be more significantly estimated, if regression coefficients (a and b) would be calculated from sample variance and mean categorized into density classes.

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Field measurements of wind pressure on an open roof during Typhoons HaiKui and SuLi

  • Feng, Ruoqiang;Liu, Fengcheng;Cai, Qi;Yan, Guirong;Leng, Jiabing
    • Wind and Structures
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    • v.26 no.1
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    • pp.11-24
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    • 2018
  • Full-scale measurements of wind action on the open roof structure of the WuXi grand theater, which is composed of eight large-span free-form leaf-shaped space trusses with the largest span of 76.79 m, were conducted during the passage of Typhoons HaiKui and SuLi. The wind pressure field data were continuously and simultaneously monitored using a wind pressure monitoring system installed on the roof structure during the typhoons. A detailed analysis of the field data was performed to investigate the characteristics of the fluctuating wind pressure on the open roof, such as the wind pressure spectrum, spatial correlation coefficients, peak wind pressures and non-Gaussian wind pressure characteristics, under typhoon conditions. Three classical methods were used to calculate the peak factors of the wind pressure on the open roof, and the suggested design method and peak factors were given. The non-Gaussianity of the wind pressure was discussed in terms of the third and fourth statistical moments of the measured wind pressure, and the corresponding indication of the non-Gaussianity on the open roof was proposed. The result shows that there were large pulses in the time-histories of the measured wind pressure on Roof A2 in the field. The spatial correlation of the wind pressures on roof A2 between the upper surface and lower surface is very weak. When the skewness is larger than 0.3 and the kurtosis is larger than 3.7, the wind pressure time series on roof A2 can be taken as a non-Gaussian distribution, and the other series can be taken as a Gaussian distribution.

Synchronized sensing for wireless monitoring of large structures

  • Kim, Robin E.;Li, Jian;Spencer, Billie F. Jr;Nagayama, Tomonori;Mechitov, Kirill A.
    • Smart Structures and Systems
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    • v.18 no.5
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    • pp.885-909
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    • 2016
  • Advances in low-cost wireless sensing have made instrumentation of large civil infrastructure systems with dense arrays of wireless sensors possible. A critical issue with regard to effective use of the information harvested from these sensors is synchronized sensing. Although a number of synchronization methods have been developed, most provide only clock synchronization. Synchronized sensing requires not only clock synchronization among wireless nodes, but also synchronization of the data. Existing synchronization protocols are generally limited to networks of modest size in which all sensor nodes are within a limited distance from a central base station. The scale of civil infrastructure is often too large to be covered by a single wireless sensor network. Multiple independent networks have been installed, and post-facto synchronization schemes have been developed and applied with some success. In this paper, we present a new approach to achieving synchronized sensing among multiple networks using the Pulse-Per-Second signals from low-cost GPS receivers. The method is implemented and verified on the Imote2 sensor platform using TinyOS to achieve $50{\mu}s$ synchronization accuracy of the measured data for multiple networks. These results demonstrate that the proposed approach is highly-scalable, realizing precise synchronized sensing that is necessary for effective structural health monitoring.

Reinforcement Learning for Node-disjoint Path Problem in Wireless Ad-hoc Networks (무선 애드혹 네트워크에서 노드분리 경로문제를 위한 강화학습)

  • Jang, Kil-woong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.8
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    • pp.1011-1017
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    • 2019
  • This paper proposes reinforcement learning to solve the node-disjoint path problem which establishes multipath for reliable data transmission in wireless ad-hoc networks. The node-disjoint path problem is a problem of determining a plurality of paths so that the intermediate nodes do not overlap between the source and the destination. In this paper, we propose an optimization method considering transmission distance in a large-scale wireless ad-hoc network using Q-learning in reinforcement learning, one of machine learning. Especially, in order to solve the node-disjoint path problem in a large-scale wireless ad-hoc network, a large amount of computation is required, but the proposed reinforcement learning efficiently obtains appropriate results by learning the path. The performance of the proposed reinforcement learning is evaluated from the viewpoint of transmission distance to establish two node-disjoint paths. From the evaluation results, it showed better performance in the transmission distance compared with the conventional simulated annealing.

A Study on the Changes in the Physical Environment of Resources in Rural Areas Using UAV -Focusing on Resources in Galsan-Myeon, Hongseong-gun- (무인항공기를 활용한 농촌 지역자원의 물리적 환경변화 분석연구 - 홍성군 갈산면 지역자원을 중심으로 -)

  • An, Phil-Gyun;Kim, Sang-Bum;Cho, Suk-Yeong;Eom, Seong-Jun;Kim, Young-Gyun;Cho, Han-Sol
    • Journal of the Korean Institute of Rural Architecture
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    • v.23 no.4
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    • pp.1-12
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    • 2021
  • Recently, the use of unmanned aerial vehicles (UAVs) is increasing in the field of land information acquisition and terrain exploration through high-altitude aerial photography. High-altitude aerial photography is suitable for large-scale geographic information collection, but has the disadvantage that it is difficult to accurately collect small-scale geographic information. Therefore, this study used low-altitude UAV to monitor changes in small rural spaces around rural resources, and the results are as follows. First, the low-altitude aerial imagery had a very high spatial resolution, so it was effective in reading and analyzing topographic features. Second, an area with a large number of aerial images and a complex topography had a large amount of point clouds to be extracted, and the number of point clouds affects the three-dimensional quality of rural space. Third, 3D mapping technology using point cloud is effective for monitoring rural space and rural resources because it enables observation and comparison of parts that cannot be read from general aerial images. In this study, the possibility of rural space analysis of low-altitude UAV was verified through aerial photography and analysis, and the effect of 3D mapping on rural space monitoring was visually analyzed. If data acquired by low-altitude UAV are used in various forms such as GIS analysis and topographic map production it is expected to be used as basic data for rural planning to maintain and preserve the rural environment.