• Wind and Structures
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• v.16 no.6
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• pp.617-627
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• 2013

In wind load calculations based on pressure measurements, the concept of 'tributary area' is usually used. The literature has less guidance for a systematic computational methodology for calculating tributary areas, in general, and for scattered pressure taps, in particular. To the best of the author's knowledge, there is no generic mathematical equation that helps calculate the tributary areas for irregular pressure taps. Traditionally, the drawing of tributary boundaries for scattered and intensively distributed taps may not be feasible (a time and resource consuming task). To alleviate this problem, this paper presents a proposed numerical approach for tributary area calculations on rectangular surfaces. The approach makes use of the available coordinates of the pressure taps and the dimensions of the surface. The proposed technique is illustrated by two application examples: first, quasi-regularly distributed pressure taps, and second, taps that have scattered distribution on a rectangular surface. The accuracy and the efficacy of the approach are assessed, and a comparison with a traditional method is presented.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.1279-1282
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• 2004

계층적인 Mobile IPv6 구조에서 실시간 서비스의 확대와 노드의 이동성 증가에 따라 Mobility Anchor Point(MAP)의 부하가 늘어나는 문제가 발생할 수 있다. 본 논문에서는 IETF(internet Engineering Task Force)의 중요한 마이크로 이동성 프로토콜인 HMIPv6의 기본동작을 설명하고 MAP에서 발생할 수 있는 부하를 하위에 있는 라우터에게 분산시키기 위하여 Passive Approach와 Active Approach 두 가지 방법을 제안하였다. Passive Approach는 MAP가 분산 시점을 결정하여 하위의 라우터에게 부하를 분산해주는 방법이고 Active Approach는 임의의 MAP하위에 있는 라우터가 스스로 분산 시점을 결정하여 MAP로 동작하여 MAP에서 발생할 수 있는 부하를 줄이는 방법이다.

• Structural Engineering and Mechanics
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• v.70 no.1
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• pp.43-54
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• 2019

Due to various numerical problems, crack analysis of reinforced concrete members using the finite element method is confronting with substantial difficulties, rendering the prediction of crack patterns and crack widths a formidable task. The root cause is that the conventional analysis methods are not capable of tracking the crack sequence and accounting for the stress relief and re-distribution during cracking. To address this deficiency, the crack queuing algorithm has been proposed. Basically, at each load increment, iterations are carried out and within each iteration step, only the most critical concrete element is allowed to crack and the stress re-distribution is captured in subsequent iteration by re-formulating the cracked concrete element and re-analysing the whole concrete structure. To demonstrate the effectiveness of the crack queuing algorithm, crack analysis of concrete members tested in the literature is performed with and without the crack queuing algorithm incorporated.

• Journal of information and communication convergence engineering
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• v.16 no.4
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• pp.264-270
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• 2018

In our research study, we aim at optimizing multiple load in cloud, effective resource allocation and lesser response time for the job assigned. Using Hadoop on datacenter is the best and most efficient analytical service for any corporates. To provide effective and reliable performance analytical computing interface to the client, various cloud service providers host Hadoop clusters. The previous works done by many scholars were aimed at execution of workflows on Hadoop platform which also minimizes the cost of virtual machines and other computing resources. Earlier stochastic hill climbing technique was applied for single parameter and now we are working to optimize multiple parameters in the cloud data centers with proposed heuristic hill climbing. As many users try to priorities their job simultaneously in the cluster, resource optimized workflow scheduling technique should be very reliable to complete the task assigned before the deadlines and also to optimize the usage of the resources in cloud.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.525-526
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• 2009

Due to the limitation of battery life time, energy is one of the most crucial issues for wireless sensor networks. Thus this paper proposes an energy efficient duty cycle scheme to conserve energy mostly. To handle the large varieties of data (i.e., both low and high traffic load) the proposed duty cycle scheme ensures a fair access period (FAP) and a prioritized access period (PAP). The idea presented in this paper able to reduce the collision probability and energy consumption. Finally simulation outputs have demonstrated the effectiveness of the proposed duty cycle task and showed a noticeable performance in terms of energy usage.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.05a
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• pp.74-77
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• 2022

최근 사물 인터넷(IoT)의 발전으로 계산 집약적이거나 지연시간에 민감한 태스크가 증가하면서, 모바일 엣지 컴퓨팅 기술이 주목받고 있지만 지상에 고정되어 있는 MEC 서버는 사용자의 요구사항 변화에 따라 서버의 위치를 변경하거나 유연하게 대처할 수 없다. 이 문제를 해결하기 위해 UAV(Unmanned Aerial Vehicle)를 추가로 이용해 엣지 서비스를 제공하는 기법이 연구되고 있다. 그러나 UAV는 지상 MEC와는 달리 배터리 용량이 제한되어 있어 태스크 마이그레이션을 통해 에너지 사용량을 최소화하는 것이 필요하다. 본 논문에서는 MEC 서버들 사이의 로드 밸런싱과 UAV MEC 서버의 에너지 효율성을 최적화하기 위해 강화학습 기법인 Q-learning을 이용한 태스크 마이그레이션 기법을 제안한다. 제안 시스템의 성능을 평가하기 위해 UAV의 개수에 따라 실험을 진행하여 잔여 에너지와 로드 밸런싱 측면에서 성능을 분석한다.

• Journal of Practical Agriculture & Fisheries Research
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• v.20 no.1
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• pp.55-66
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• 2018

Judicious control of high temperature is the most important task for the successful intensive-cultivation of vegetables in glasshouses during the hot summer. Estimation of cooling load and wise selection of suitable equipments and facilities based upon the environmental conditions are essential for the efficient temperature control. A series of experiments were carried out to investigate VETH(ventilation, evapotranspiration, temperature and humidity) plot was prepared for the possible practical application in designing some evaporated cooling methods for the following 9 locations; Seoul, Seosan, Taejeon, Pusan, Cheju, Kwangju, Taegu, Chonju, and Chinju.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.126-133
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• 2023

Recent advancements in cloud service virtualization technologies have witnessed a shift from a Virtual Machine-centric approach to a container-centric paradigm, offering advantages such as faster deployment and enhanced portability. Container orchestration has emerged as a key technology for efficient management and scheduling of these containers. However, with the increasing complexity and diversity of heterogeneous workloads and service types, resource scheduling has become a challenging task. Various research endeavors are underway to address the challenges posed by diverse workloads and services. Yet, a systematic approach to container orchestration for effective cloud management has not been clearly defined. This paper proposes the DRA-Engine (Dynamic Resource Allocation Engine) for resource scheduling in container orchestration. The proposed engine comprises the Request Load Procedure, Required Resource Measurement Procedure, and Resource Provision Decision Procedure. Through these components, the DRA-Engine dynamically allocates resources according to the application's requirements, presenting a solution to the challenges of resource scheduling in container orchestration.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.161-171
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• 2019

Varied methods have been researched continuously because the past as the daily maximum electricity demand expectation has been a crucial task in the nation's electrical supply and demand. Forecasting the daily peak electricity demand accurately can prepare the daily operating program about the generating unit, and contribute the reduction of the consumption of the unnecessary energy source through efficient operating facilities. This method also has the advantage that can prepare anticipatively in the reserve margin reduced problem due to the power consumption superabundant by heating and air conditioning that can estimate the daily peak load. This paper researched a model that can forecast the next day's daily peak load when considering the influence of temperature and weekday, weekend, and holidays in the Seasonal ARIMA, TBATS, Seasonal Reg-ARIMA, and NNETAR model. The results of the forecasting performance test on the model of this paper for a Seasonal Reg-ARIMA model and NNETAR model that can consider the day of the week, and temperature showed better forecasting performance than a model that cannot consider these factors. The forecasting performance of the NNETAR model that utilized the artificial neural network was most outstanding.

• Journal of Information Processing Systems
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• v.12 no.2
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• pp.275-294
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• 2016

A primary task in wireless sensor networks (WSNs) is data collection. The main objective of this task is to collect sensor readings from sensor fields at predetermined sinks using routing protocols without conducting network processing at intermediate nodes, which have been proved as being inefficient in many research studies using a static sink. The major drawback is that sensor nodes near a data sink are prone to dissipate more energy power than those far away due to their role as relay nodes. Recently, novel WSN architectures based on mobile sinks and mobile relay nodes, which are able to move inside the region of a deployed WSN, which has been developed in most research works related to mobile WSN mainly exploit mobility to reduce and balance energy consumption to enhance communication reliability among sensor nodes. Our main purpose in this paper is to propose a solution to the problem of deploying mobile data collectors for alleviating the high traffic load and resulting bottleneck in a sink's vicinity, which are caused by static approaches. For this reason, several WSNs based on mobile elements have been proposed. We studied two key issues in WSN mobility: the impact of the mobile element (sink or relay nodes) and the impact of the mobility model on WSN based on its performance expressed in terms of energy efficiency and reliability. We conducted an extensive set of simulation experiments. The results obtained reveal that the collection approach based on relay nodes and the mobility model based on stochastic perform better.