• Title/Summary/Keyword: Cloud Modeling

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Applying the Cloud Computing Technology for Mobile BIM based Project Management Information System (모바일 BIM 공사관리시스템을 위한 클라우드 컴퓨팅 기술 활용 방안)

  • Lee, Jong-Ho;Eom, Shin-Jo
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2011.05a
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    • pp.145-148
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    • 2011
  • As a futuristic construction model, building information model(BIM) based project management system(PMIS) and mobile PMIS have been showing visible sign. However, researches on the 3D BIM based PMIS using mobile device are hard to find, result from limitation of mobile device application(slow speed at huge BIM file, display size, and etc.) and undefined standard of business processes. Therefore, this research aims at studying feasibility of mobile BIM PMIS based on cloud computing as a business model. In case of applying mobile BIM PMIS, 3D drawings and integrated building informations are possible on mobile devices in real time. it would support increasing the productivity of project participants as designer, engineer, supervisor, and etc. Globally, BIM based PMIS and Mobile BIM system, cloud computing based mobile BIM simulator are in the concept or experimental phase, therefore it is possible to secure global leading technology of IT and construction merger in the mobile BIM.

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Reconstruction of Canal Surfaces (캐널곡면의 복원)

  • Lee In-Kwon;Kim Ku-Jin
    • Journal of KIISE:Computer Systems and Theory
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    • v.32 no.8
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    • pp.411-417
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    • 2005
  • We present a method to reconstruct a canal surface from a point cloud (a set of unorganized points). A canal surface is defined as a swept surface of a moving sphere with varying radii. By using the shrinking and moving least-squares methods, we reduce a point cloud to a thin curve-like point set which can be approximated to the spine curve of a canal surface. The distance between a point in the thin point cloud and a corresponding point in the original point set represents the radius of the canal surface.

Climate Influences of Galactic Cosmic Rays (GCR): Review and Implications for Research Policy (우주기원의 고에너지 입자가 기후에 미치는 영향: 연구 현황과 정책적 시사점)

  • Kim, Jiyoung;Jang, Kun-Il
    • Atmosphere
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    • v.27 no.4
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    • pp.499-509
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    • 2017
  • Possible links among cosmic ray, cloud, and climate have scientific uncertainties. The reputed topics have been highly controversial during several decades. A link between the atmospheric ionization by galactic cosmic rays (GCR), which is modulated by solar activities, and global cloud cover was firstly proposed in 1997. Some researchers suggested that the GCR can stimulate the formation of cloud condensation nuclei (CCN) in the atmosphere, and then the higher CCN concentrations may lead to an increase of cloud cover, resulting in a cooling of the Earth's climate, and vise versa. The CLOUD (Cosmic leaving outdoor droplets) experiment was designed to study the effect of GCR on the formation of atmospheric aerosols and clouds under precisely controlled laboratory conditions. A state-of-the-art chamber experiment has greatly advanced our scientific understanding of the aerosol formation in early stage and its nucleation processes if the GCR effect is considered or not. Many studies on the climate-GCR (or space weather) connection including the CLOUD experiment have been carried out during the several decades. Although it may not be easy to clarify the physical connection, the recent scientific approaches such as the laboratory experiments or modeling studies give some implications that the research definitively contributed to reduce the scientific uncertainties of natural and anthropogenic aerosol radiative forcing as well as to better understand the formation processes of fine particulate matters as an important parameter of air quality forecast.

CTaG: An Innovative Approach for Optimizing Recovery Time in Cloud Environment

  • Hung, Pham Phuoc;Aazam, Mohammad;Huh, Eui-Nam
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.4
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    • pp.1282-1301
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    • 2015
  • Traditional infrastructure has been superseded by cloud computing, due to its cost-effective and ubiquitous computing model. Cloud computing not only brings multitude of opportunities, but it also bears some challenges. One of the key challenges it faces is recovery of computing nodes, when an Information Technology (IT) failure occurs. Since cloud computing mainly depends upon its nodes, physical servers, that makes it very crucial to recover a failed node in time and seamlessly, so that the customer gets an expected level of service. Work has already been done in this regard, but it has still proved to be trivial. In this study, we present a Cost-Time aware Genetic scheduling algorithm, referred to as CTaG, not only to globally optimize the performance of the cloud system, but also perform recovery of failed nodes efficiently. While modeling our work, we have particularly taken into account the factors of network bandwidth and customer's monetary cost. We have implemented our algorithm and justify it through extensive simulations and comparison with similar existing studies. The results show performance gain of our work over the others, in some particular scenarios.

PCIA Cloud Service Modeling and Performance Analysis of Physical & Logical Resource Provisioning (PCIA 클라우드 서비스 모델링 및 자원 구성에 따른 성능 영향도 분석)

  • Yin, Binfeng;Kwak, Jong Wook
    • Journal of the Korea Society of Computer and Information
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    • v.19 no.2
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    • pp.1-10
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    • 2014
  • Cloud computing provides flexible and efficient mass data analysis platform. In this paper, we define a new resource provisioning architecture in the public cloud, named PCIA. In addition, we provide a service model of PCIA and its new naming scheme. Our model selects the proper number of physical or virtual resources based on the requirements of clients. By the analysis of performance variation in the PCIA, we evaluate the relationship between performance variation and resource provisioning, and we present key standards for cloud system constructions, which can be an important resource provisioning criteria for both cloud service providers and clients.

Design of Browser for The Harbor BIM Service Based on Cloud Computing (클라우드 컴퓨팅 기반 항만 BIM 서비스를 위한 브라우저 설계)

  • Chang, Jae-Yeol;Moon, Hyoun-Seok
    • Journal of KIBIM
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    • v.8 no.4
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    • pp.60-71
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    • 2018
  • The port BIM technology has many problems such as lack of relevant system, high cost of BIM infrastructure construction, and process difference of existing domestic inter-industry. Since the port facilities as national key industries are managed and operated by public organizations, it is necessary to integrate IT resources and have a system that needs collective construction and joint utilization management. In this paper, we proposed the convergence of cloud computing technology and BIM as a way to reduce the infrastructure cost required for port BIM operation and to provide various BIM services for domestic process. To do this, we collected system requirements based on demand surveys of port staff and designed a BIM browser that provides IFC-based BIM server and customized services to reduce infrastructure cost in cloud computing environment. In terms of infrastructure, we designed cloud-based IaaS to support cost reduction, which is an essential component, and designed SaaS to support customized services in terms of services. We will perform performance verification with focus on whether port BIM servers and browsers have reached a level where they can manage four BIM models with different types and capacities.

Flexible deployment of component-based distributed applications on the Cloud and beyond

  • Pham, Linh Manh;Nguyen, Truong-Thang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.3
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    • pp.1141-1163
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    • 2019
  • In an effort to minimize operational expenses and supply users with more scalable services, distributed applications are actually going towards the Cloud. These applications, sent out over multiple environments and machines, are composed by inter-connecting independently developed services and components. The implementation of such programs on the Cloud is difficult and generally carried out either by hand or perhaps by composing personalized scripts. This is extremely error prone plus it has been found that misconfiguration may be the root of huge mistakes. We introduce AutoBot, a flexible platform for modeling, installing and (re)configuring complex distributed cloud-based applications which evolve dynamically in time. AutoBot includes three modules: A simple and new model describing the configuration properties and interdependencies of components; a dynamic protocol for the deployment and configuration ensuring appropriate resolution of these interdependencies; a runtime system that guarantee the proper configuration of the program on many virtual machines and, if necessary, the reconfiguration of the deployed system. This reduces the manual application deployment process that is monotonous and prone to errors. Some validation experiments were conducted on AutoBot in order to ensure that the proposed system works as expected. We also discuss the opportunity of reusing the platform in the transition of applications from Cloud to Fog computing.

Cloud Computing Adoption Decision-Making Modeling Using CART (CART 방법론을 사용한 클라우드 컴퓨팅 도입 의사 결정 모델링)

  • Baek, Seung Hyun;Chang, Byeong-Yun
    • Journal of the Korea Society for Simulation
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    • v.23 no.4
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    • pp.189-195
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    • 2014
  • In this paper, we conducted a study on place-free and time-free cloud computing (CC) adoption decision-making model. Panel survey data which is collected from 65 people and CART (classification and regression tree) which is one of data mining approaches are used to construct decision-making model. In this modeling, there are 2 steps: In the first step, significant questions (variables) are selected. After that, the CART decision-making model is constructed using the selected variables. In the variable selection stage, the 25 questions are reduced to 5 ones. The benefits of question reduction are quick response from respondent and reducing model-construction time.

A SEM-ANN Two-step Approach for Predicting Determinants of Cloud Service Use Intention (SEM-Artificial Neural Network 2단계 접근법에 의한 클라우드 스토리지 서비스 이용의도 영향요인에 관한 연구)

  • Guangbo Jiang;Sundong Kwon
    • Journal of Information Technology Applications and Management
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    • v.30 no.6
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    • pp.91-111
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    • 2023
  • This study aims to identify the influencing factors of intention to use cloud services using the SEM-ANN two-step approach. In previous studies of SEM-ANN, SEM presented R2 and ANN presented MSE(mean squared error), so analysis performance could not be compared. In this study, R2 and MSE were calculated and presented by SEM and ANN, respectively. Then, analysis performance was compared and feature importances were compared by sensitivity analysis. As a result, the ANN default model improved R2 by 2.87 compared to the PLS model, showing a small Cohen's effect size. The ANN optimization model improved R2 by 7.86 compared to the PLS model, showing a medium Cohen effect size. In normalized feature importances, the order of importances was the same for PLS and ANN. The contribution of this study, which links structural equation modeling to artificial intelligence, is that it verified the effect of improving the explanatory power of the research model while maintaining the order of importance of independent variables.

Role of Supercomputers in Numerical Prediction of Weather and Climate (기상 및 기후의 수치예측에 대한 슈퍼컴퓨터의 역할)

  • Park, Seon-Ki
    • Atmosphere
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    • v.14 no.4
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    • pp.19-23
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    • 2004
  • Progresses in numerical prediction of weather and climate have been in parallel with those of computing resources, especially the development of supercomputers. Advanced techniques in numerical modeling, computational schemes, and data assimilation cloud not have been practically achieved without the aid of supercomputers. With such techniques and computing powers, the accuracy of numerical forecasts has been tremendously improved. Supercomputers are also indispensible in constructing and executing the synthetic Earth system models. In this study, a brief overview on numerical weather / climate prediction, Earth system modeling, and the values of supercomputing is provided.