• 한국정보통신학회논문지
• /
• 제11권8호
• /
• pp.1612-1618
• /
• 2007

유비쿼터스 환경으로 발전하면서 이종의 디바이스들을 자연스럽게 연동시킬 수 있는 기술에 대한 요구가 크게 증가하고 있으며, 이를 해결하기 위한 하나의 대안으로 웹서비스가 주목받고 있다. 최근 디바이스 연동을 선언적인 ECA(Event-Condition-Action) 룰로 정의하고 이를 이용하여 디바이스 연동을 수행할 수 있는 웹서비스 기반의 WS-ECA(Web Services-ECA) 프레임워크가 제안되었다. 본 논문에서는 WS-ECA 프레임워크에 대한 구체적인 모듈 단위의 설계 부분을 제안하고, 이를 기반으로 WS-ECA 프레임워크를 구현하였다.

• Steel and Composite Structures
• /
• 제43권5호
• /
• pp.639-660
• /
• 2022

The bending and buckling behaviours of FG-GRNC laminated sandwich plates are investigated by using novel five-variables quasi 3D higher order shear deformation plate theory by considering the modified continuum nonlocal strain gradient theory. To calculate the effective Young's modulus of the GRNC sandwich plate along the thickness direction, and Poisson's ratio and mass density, the modified Halpin-Tsai model and the rule of the mixture are employed. Based on a new field of displacement, governing equilibrium equations of the GRNC sandwich plate are solved using a developed approach of Galerkin method. A detailed parametric analysis is carried out to highlight the influences of length scale and material scale parameters, GPLs distribution pattern, the weight fraction of GPLs, geometry and size of GPLs, the geometry of the sandwich plate and the total number of layers on the stresses, deformation and critical buckling loads. Some details are studied exclusively for the first time, such as stresses and the nonlocality effect.

• 국제학술발표논문집
• /
• The 9th International Conference on Construction Engineering and Project Management
• /
• pp.1253-1253
• /
• 2022

Although the construction industry is changing from a 2D-based to a 3D BIM-based management process, 2D drawings are still used as standards for permits and construction. For this reason, 2D deliverables extracted from 3D BIM are one of the essential achievements of BIM projects. However, due to technical and institutional problems that exist in practice, the process of extracting 2D deliverables from BIM requires additional work beyond generating 3D BIM models. In addition, the consistency of data between 3D BIM models and 2D deliverables is low, which is a major factor hindering work productivity in practice. To solve this problem, it is necessary to build BIM data that meets information requirements (IRs) for extracting 2D deliverables to minimize the amount of work of users and maximize the utilization of BIM data. However, despite this, the additional work that occurs in the BIM process for drawing creation is still a burden on BIM users. To solve this problem, the purpose of this study is to increase the productivity of the BIM process by automating the process of extracting 2D deliverables from BIM and securing data consistency between the BIM model and 2D deliverables. For this, an expert interview was conducted, and the requirements for automation of the process of extracting 2D deliverables from BIM were analyzed. Based on the requirements, the types of drawings and drawing expression elements that require automation of drawing generation in the design development stage were derived. Finally, the method for developing automation technology targeting elements that require automation was classified and analyzed, and the process for automatically extracting BIM-based 2D deliverables through templates and rule-based automation modules were derived. At this time, the automation module was developed as an add-on to Revit software, a representative BIM authoring tool, and 120 rule-based automation rulesets, and the combinations of these rulesets were used to automatically generate 2D deliverables from BIM. Through this, it was possible to automatically create about 80% of drawing expression elements, and it was possible to simplify the user's work process compared to the existing work. Through the automation process proposed in this study, it is expected that the productivity of extracting 2D deliverables from BIM will increase, thereby increasing the practical value of BIM utilization.

• Journal of Electrical Engineering and Technology
• /
• 제7권4호
• /
• pp.636-645
• /
• 2012

This study introduces an information granular-based fuzzy radial basis function neural networks (FRBFNN) based on multiobjective optimization and weighted least square (WLS). An improved multiobjective space search algorithm (IMSSA) is proposed to optimize the FRBFNN. In the design of FRBFNN, the premise part of the rules is constructed with the aid of Fuzzy C-Means (FCM) clustering while the consequent part of the fuzzy rules is developed by using four types of polynomials, namely constant, linear, quadratic, and modified quadratic. Information granulation realized with C-Means clustering helps determine the initial values of the apex parameters of the membership function of the fuzzy neural network. To enhance the flexibility of neural network, we use the WLS learning to estimate the coefficients of the polynomials. In comparison with ordinary least square commonly used in the design of fuzzy radial basis function neural networks, WLS could come with a different type of the local model in each rule when dealing with the FRBFNN. Since the performance of the FRBFNN model is directly affected by some parameters such as e.g., the fuzzification coefficient used in the FCM, the number of rules and the orders of the polynomials present in the consequent parts of the rules, we carry out both structural as well as parametric optimization of the network. The proposed IMSSA that aims at the simultaneous minimization of complexity and the maximization of accuracy is exploited here to optimize the parameters of the model. Experimental results illustrate that the proposed neural network leads to better performance in comparison with some existing neurofuzzy models encountered in the literature.

• 한국정보시스템학회지:정보시스템연구
• /
• 제26권2호
• /
• pp.1-23
• /
• 2017

Purpose Facebook is a social network service that has the highest number of Monthly Active Users around the world. Hence, marketers have selected Facebook as the most important platform to get customer engagement. With respect to the customer engagement enhancement, the most popular and engaging post type in the Facebook brand fan pages related to what was usually classified as 'sweepstakes'. Sweepstakes refer to a form of gambling where the entire prize may be awarded to the winner. Which makes customers more engaged with the brand. This study aims to explore sweepstakes-oriented social media marketing approaches based on the application of big data analytics. Design/methodology/approach we collect sweepstakes data from each company based on the data crawling from the Facebook brand fan pages. The output of this study explains how companies in each category of FCB grid can design and apply sweepstakes for their social media marketing. Findings The results show that they have one thing in common across the four quadrants of FCB grid. Regardless of the quadrants, most frequently observed type is 'Simple/Quiz or Comments/Quatrains [event type of sweepstakes] + Gifticon [type of reward prize] + Image [type of message display] + No URL [Link toother website] +Single-Gift-Offer [type of reward prize payment]'. So, if the position of the brand is hard to be defined by the FCB grid model, then this general rule can be applied to all types of brands. Also some differences between the quadrants of the FCB grid were observed. This study offers several research implications by analyzing Sweepstakes-oriented social media marketing approaches in Facebook brand fan pages. By using the FCB grid model, this study provides guidance on how companies can design their sweepstakes-oriented social media marketing approaches in the context of Facebook brand fan pages by considering their context.

• 전기학회논문지
• /
• 제59권5호
• /
• pp.981-989
• /
• 2010

In this study, we introduce a new architecture of fuzzy inference system. In the fuzzy inference system, we use Fuzzy C-Means clustering algorithm to form the premise part of the rules. The membership functions standing in the premise part of fuzzy rules do not assume any explicit functional forms, but for any input the resulting activation levels of such radial basis functions directly depend upon the distance between data points by means of the Fuzzy C-Means clustering. As the consequent part of fuzzy rules of the fuzzy inference system (being the local model representing input output relation in the corresponding sub-space), four types of polynomial are considered, namely constant, linear, quadratic and modified quadratic. This offers a significant level of design flexibility as each rule could come with a different type of the local model in its consequence. Either the Least Square Estimator (LSE) or the weighted Least Square Estimator (WLSE)-based learning is exploited to estimate the coefficients of the consequent polynomial of fuzzy rules. In fuzzy modeling, complexity and interpretability (or simplicity) as well as accuracy of the obtained model are essential design criteria. The performance of the fuzzy inference system is directly affected by some parameters such as e.g., the fuzzification coefficient used in the FCM, the number of rules(clusters) and the order of polynomial in the consequent part of the rules. Accordingly we can obtain preferred model structure through an adjustment of such parameters of the fuzzy inference system. Moreover the comparative experimental study between WLSE and LSE is analyzed according to the change of the number of clusters(rules) as well as polynomial type. The superiority of the proposed model is illustrated and also demonstrated with the use of Automobile Miles per Gallon(MPG), Boston housing called Machine Learning dataset, and Mackey-glass time series dataset.

• 한국인터넷방송통신학회논문지
• /
• 제13권2호
• /
• pp.181-189
• /
• 2013

본 논문에서는 패턴 인식기를 설계하기 위하여 개별 입력 공간을 기반으로 한 퍼지 뉴럴 네트워크를 소개한다. 제안된 퍼지 뉴럴 네트워크는 각 입력 공간을 개별적으로 분할함으로서 네트워크를 구성한다. 규칙의 전반부는 개별적 입력 공간을 퍼지 분할하여 독립적으로 구성하고, 규칙의 후반부는 다항식으로서 표현된다. 퍼지 뉴럴 네트워크의 학습은 퍼지 규칙의 후반부에 있는 뉴런의 연결가중치를 조정함으로써 실현되고, 오류 역전파 알고리즘을 이용하여 실현한다. 또한, 제안한 네트워크의 파라미터를 최적화하기 위하여 실수 코딩 유전자 알고리즘을 이용한다. 마지막으로, 패턴 인식을 위한 실험 데이터를 이용하여 최적화된 패턴 인식기를 설계한다.

• 한국산학기술학회논문지
• /
• 제18권2호
• /
• pp.23-30
• /
• 2017

건설산업 분야에서 빌딩정보모델링(BIM)은 단지 설계를 보다 쉽게 지원하고, 3차원 모델을 구현하기 위한 도구만은 아니다. 왜냐하면, 설계, 시공, 유지관리 및 철거에 이르는 건설 생애주기 동안의 다양한 데이터를 입력하고 관리가 가능하도록 구조화 되어 있기 때문이다. 이렇게 구조화된 모델을 가지고 다양한 분석 및 해석이 가능해지기 때문에 BIM의 역할은 점점 더 증대되어 가고 있다. 노르웨이 베스트바넨의 국립예술박물관 현상설계 경기를 시작으로 국내외적으로 BIM을 설계 경기 및 평가에 적용하려는 노력이 다각적으로 발생하고 있다. 이때, 기존 방식의 설계경기와는 다르게 BIM기반으로 전사적인 시뮬레이션을 통한 자동적이며, 신뢰성이 높고 효율적인 평가가 가능하게 된다. 이를 위하여 각 BIM 도구를 대상으로 하는 모델링 가이드가 필요하며 이를 검증할 수 있는 평가시스템의 요구가 생기게 되었다. 본 논문은 건설산업 분야에 새로운 패러다임을 이끌고 있는 BIM 기술을 이용한 새로운 방식의 설계평가 및 절차의 방향에 대해, 전력거래소 본사사옥 등의 이전 설계경기 사례를 비교분석하고 이에 대한 개선방안을 설명함으로써 향후 발주될 BIM기반 건축설계경기 평가의 방향을 제시하고자 한다.

• 정보처리학회논문지C
• /
• 제11C권4호
• /
• pp.455-462
• /
• 2004

네트워크 공격은 인터넷의 발달과 함께 유형도 다양하고 새로워지고 있다. 기존의 침입탐지 시스템들은 알려진 공격의 시그네처를 기반으로 탐지하기 때문에 알려지지 않거나 변형된 공격을 탐지하고, 대응하기 위해서는 많은 노력과 비용이 필요하다. 본 논문에서는 네트워크 프로토콜 속성 분석을 통해 알려지지 않거나 변형된 네트워크 공격을 예측할 수 있는 마이닝 프로토타입 시스템을 설계 하고 구현 하였다. 네트워크 프로토콜 속성을 분석하기 위해서 연관규칙과 빈발에피소드 기법을 사용하였으며, 수집된 네트워크 프로토콜은 TCP, UDP, ICMP와 통합된 형태의 스키마로 저장한다. 본 실험을 통해서 각 프로토콜별로 발생 가능한 네트워크 공격 유형을 예측할 수 있는 규칙들을 생성한다. 마이닝 프로토타입은 침입탐지 시스템에서 새로운 공격에 대응하기 위한 보조적인 .도구로서 유용하게 사용될 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권3호
• /
• pp.1204-1227
• /
• 2020

The tradeoff between energy conservation and traffic balancing is a dilemma problem in Wireless Sensor Networks (WSNs). By analyzing the intrinsic relationship between cluster properties and long distance transmission energy consumption, we characterize three node sets of the cluster as a theoretical foundation to enhance high performance of WSNs, and propose optimal solutions by introducing rendezvous and Mobile Elements (MEs) to optimize energy consumption for prolonging the lifetime of WSNs. First, we exploit an approximate method based on the transmission distance from the different node to an ME to select suboptimal Rendezvous Point (RP) on the trajectory for ME to collect data. Then, we define data transmission routing sequence and model rendezvous planning for the cluster. In order to achieve optimization of energy consumption, we specifically apply the economic theory called Diminishing Marginal Utility Rule (DMUR) and create the utility function with regard to energy to develop an adaptive energy consumption optimization framework to achieve energy efficiency for data collection. At last, Rendezvous Transmission Algorithm (RTA) is proposed to better tradeoff between energy conservation and traffic balancing. Furthermore, via collaborations among multiple MEs, we design Two-Orbit Back-Propagation Algorithm (TOBPA) which concurrently handles load imbalance phenomenon to improve the efficiency of data collection. The simulation results show that our solutions can improve energy efficiency of the whole network and reduce the energy consumption of sensor nodes, which in turn prolong the lifetime of WSNs.