• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2633-2635
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• 2003

In this study, we propose a fuzzy polynomial neural networks (FPNN) and a genetically optimized fuzzy polynomial neural networks(GoFPNN) for identification of non-linear system. GoFPNN architecture is designed by a FPNN based on fuzzy set and its structure and parameters are optimized by genetic algorithms. A fuzzy neural networks(FNN) based on fuzzy set divide into two structures that is simplified inference structure and linear inference structure. The proposed FPNN is resulted from integration and extension of simplified and linear inference structure of FNN. The consequence structure of the FPNN consist of polynomials represented by networks using connection weights for rules. The networks comprehend simplified(Type 0), linear (Type 1), and quadratic(Type 3) inferences. The proposed FPNN can select polynomial type of consequence part for each rule. Therefore, proposed scheme can offer flexible structure design capability for a system characteristics. Moreover, GAs is applied to networks structure and parameters tuning of proposed FPNN, and its efficient application method is discussed, these subjects are result in GoFPNN that is optimal FPNN. To evaluate proposed model performance, a numerical experiment is carried out.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.97-106
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• 2021

Social networking platforms have become a smart way for people to interact and meet on internet. It provides a way to keep in touch with friends, families, colleagues, business partners, and many more. Among the various social networking sites, Twitter is one of the fastest-growing sites where users can read the news, share ideas, discuss issues etc. Due to its vast popularity, the accounts of legitimate users are vulnerable to the large number of threats. Spam and Malware are some of the most affecting threats found on Twitter. Therefore, in order to enjoy seamless services it is required to secure Twitter against malicious users by fixing them in advance. Various researches have used many Machine Learning (ML) based approaches to detect spammers on Twitter. This research aims to devise a secure system based on Hybrid Similarity Cosine and Soft Cosine measured in combination with Genetic Algorithm (GA) and Artificial Neural Network (ANN) to secure Twitter network against spammers. The similarity among tweets is determined using Cosine with Soft Cosine which has been applied on the Twitter dataset. GA has been utilized to enhance training with minimum training error by selecting the best suitable features according to the designed fitness function. The tweets have been classified as spammer and non-spammer based on ANN structure along with the voting rule. The True Positive Rate (TPR), False Positive Rate (FPR) and Classification Accuracy are considered as the evaluation parameter to evaluate the performance of system designed in this research. The simulation results reveals that our proposed model outperform the existing state-of-arts.

• Journal of The Korean Digital Architecture Interior Association
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• v.11 no.2
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• pp.93-102
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• 2011

Existing research for store has been localized in that of Seoul area, and research for the Japanese style store built under the rule of Japanese Imperialism has not been done properly owing to national sentiment. This research established Naju that inland pillage is available along Yeongsan River after opening of Mokpo harbor. I will compare modernization developmental process of building of Korean style store with that of Japanese Style store, so obviously try to make clear the activities of modernization by linking social and economical change with Joseon merchants' life. I will try to light up the position of korean style store in Naju area in history of architecture by analyzing two styles of stores into urban architectural element, putting process of change in order and translating it according to flow of age. The development process of Korean restaurant stores and that of Japanese counterparts are rather relative. Whereas Japanese accumulated wealth through oppression and exploitation of the people of Joseon the former dynasty of present day Korea, the people of Joseon could not but be oppressed and depressed. On the other hand, while the dynamic liberation movements of Joseon merchants managed to develop based on the vitality that was growing ever more, Japanese chose to back down to some degree by exercising appeasing policy. The efforts to take initiative by shattering off the submissive attitude can be found from the ability fostering movement, Gwangju students campaign and new construction or remodeling of hanok the traditional Korean house as commercial building in the 1920s. The changing phase of the people breaking away from subjugated relation to subjective attitude can be found in the commercial districts.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.5
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• pp.487-495
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• 2016

In the offshore project such as semi-submersible FPU and FPSO, the free fall type life boat called TEMPSC (Totally Enclosed Motor Propelled Survival Craft) has been installed for the use of an emergency evacuation of POB (People on Board) from the topside platform. For the design of life boat arrangement for semi-submersible FPU in the initial design stage, the drop height and launch angle are required fulfill with the limitation of classification society rule and Company requirement, including type of approval as applicable when intact and damage condition of the platform. In this paper, we have been performed the numerical studies to find proper arrangement for the life boats consider drop height in various environmental conditions such as wave, wind and current. In the calculations, the contributions from static and low frequency (LF) motions are considered from the hydrodynamic and mooring analysis as well as damage angle from the intact and damage stability analysis. Also, Air-gap calculation at the life boat positions has been carried out to check the effect on the life boat arrangement. The air-gap assessment is based on the extreme air-gap method includes the effect of 1st order wave frequency (WF) motions, 2nd order low frequency roll/pitch motion, static trim/heel and set down.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.111-120
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• 2005

A cost effective three-dimensional color gamut mapping architecture is described. The conventional three-dimensional reduced resolution look-up table is considered and the concept of three-dimensional reduced resolution difference look-up table is introduced for cost effective and real-time color gamut mapping. The overall architecture uses one-dimensional memory decomposition of three-dimensional gamut mapping look-up table, three-dimensional interpolation and simple addition operation for generating the final gamut mapped colors. The required computational cost is greatly reduced by look-up table resolution adjustment and further reduced by the gamut mapping rule modification. The proposed architecture greatly reduces the required memory size and hardware complexity compared to the conventional method and it is suitable for real-time applications. The proposed hardware is suitable for FPGA and ASIC implementation and could be applied to the real-time display quality enhancement purposes.

• Korean Journal of Construction Engineering and Management
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• v.23 no.5
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• pp.3-14
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• 2022

Construction projects have high potentials of claims among a variety of stakeholders. Claims on their own are not disputes but they have high potentials leading to disputes if agreements are not made between parties due to conflicting opinions. In the event of the construction disputes between clients and contractors, it could give negative impacts to both parties and, to minimize or pro-actively manage construction disputes, the role of clients is more significant. The objective of the study is to analyze a level of associations between the types of disputes and causes of construction projects based on the association rule analysis, and to identify and discuss key characteristics and implications from client's perspectives. The study analyzes associations between the types of disputes and causes, and also identifies those with a high level of associations. It also presents the outcomes of more systematic analysis compared to descriptive statistics just based on frequencies. Through the analysis of the data cases, the study proposes the directions to resolve the causes of disputes from client's perspectives. It can assist to improve understandings of the relationships between the types of disputes and causes and to pro-actively manage the disputes of construction projects.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.11
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• pp.2108-2116
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• 2008

The paper concerns Fuzzy C-Means clustering based Radial Basis Function neural networks (FCM-RBFNN) and the optimization of the network is carried out by means of Particle Swarm Optimization(PSO). FCM-RBFNN is the extended architecture of Radial Basis Function Neural Network(RBFNN). In the proposed network, the membership functions of the premise part of fuzzy rules do not assume any explicit functional forms such as Gaussian, ellipsoidal, triangular, etc., so its resulting fitness values directly rely on the computation of the relevant distance between data points by means of FCM. Also, as the consequent part of fuzzy rules extracted by the FCM - RBFNN model, the order of four types of polynomials can be considered such as constant, linear, quadratic and modified quadratic. Weighted Least Square Estimator(WLSE) are used to estimates the coefficients of polynomial. Since the performance of FCM-RBFNN is affected by some parameters of FCM-RBFNN such as a specific subset of input variables, fuzzification coefficient of FCM, the number of rules and the order of polynomials of consequent part of fuzzy rule, we need the structural as well as parametric optimization of the network. In this study, the PSO is exploited to carry out the structural as well as parametric optimization of FCM-RBFNN. Moreover The proposed model is demonstrated with the use of numerical example and gas furnace data set.

• Journal of Information Technology Services
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• v.10 no.2
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• pp.223-234
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• 2011

Loosely coupled properties of SOA(Service Oriented Architecture) services do not guarantee that service applications always work properly. Service errors may also influence other services of SOA. These characteristics adversely affect software reliability. Therefore, it is a challenge to effectively manage system change and errors for operating services normally. In this study, we propose a SOA based framework using AOP(Aspect Oriented Programming) for reliable service applications. AOP provides a way to manipulate cross-cutting concerns such as logging, security and reliability and these concerns can be added to applications through weaving process. We define a service specification and an aspect specification for this framework. This framework also includes service provider, requester, repository, platform, manager, and aspect weaver to handle changes and exceptions of applications. Independent Exception Handler is stored to exhibited external Aspect Service Repository. When exception happened, Exception Handler is linked dynamically according to aspect rule that is defined in aspect specification and offer function that handle exception alternate suitable service in systematic error situation. By separating cross-cutting concerns independently, we expect that developer can concentrate on core service implementation and reusability, understanding, maintainability increase. Finally, we have implemented a prototype system to demonstrate the feasibility of our framework in case study.

• Journal of the Earthquake Engineering Society of Korea
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• v.24 no.3
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• pp.129-139
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• 2020

An approximate analysis method is proposed to predict the dynamic amplification of shear forces in ordinary reinforced concrete shear walls as a preliminary study. First, a seismic design for three groups of ordinary reinforced concrete shear walls higher than 60 m was created on the basis of nonlinear dynamic analysis. Causes for the dynamic amplification effect of shear forces were investigated through a detailed evaluation of the nonlinear dynamic analysis result. A new modal combination rule was proposed on the basis of that observation, in which fundamental mode response and combined higher mode response were summed directly. The fundamental mode response was approximated by nonlinear static analysis result, while higher mode response was computed using response spectrum analysis for equivalent linear structural models with the effective stiffness based on the nonlinear dynamic analysis result. The proposed approximate analysis generally predicted vertical distribution of story shear and shear forces of individual walls from the nonlinear dynamic analysis with comparable accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.372-372
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• 2000

In this paper, we propose Neuro Fuzzy Polynomial Networks(NFPN) based on Polynomial Neural Network(PNN) and Neuro-Fuzzy(NF) for model identification of complex and nonlinear systems. The proposed NFPN is generated from the mutually combined structure of both NF and PNN. The one and the other are considered as the premise part and consequence part of NFPN structure respectively. As the premise part of NFPN, NF uses both the simplified fuzzy inference as fuzzy inference method and error back-propagation algorithm as learning rule. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using genetic algorithms. As the consequence part of NFPN, PNN is based on Group Method of Data Handling(GMDH) method and its structure is similar to Neural Networks. But the structure of PNN is not fixed like in conventional Neural Networks and self-organizing networks that can be generated. NFPN is available effectively for multi-input variables and high-order polynomial according to the combination of NF with PNN. Accordingly it is possible to consider the nonlinearity characteristics of process and to get better output performance with superb predictive ability. In order to evaluate the performance of proposed models, we use the nonlinear function. The results show that the proposed FPNN can produce the model with higher accuracy and more robustness than any other method presented previously.