• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2003년도 하계학술대회 논문집 D
• /
• pp.2633-2635
• /
• 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
• /
• 제21권1호
• /
• pp.97-106
• /
• 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.

• 한국디지털건축인테리어학회논문집
• /
• 제11권2호
• /
• pp.93-102
• /
• 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
• /
• 제8권5호
• /
• pp.487-495
• /
• 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.

• 대한전자공학회논문지SP
• /
• 제42권6호
• /
• pp.111-120
• /
• 2005

본 논문에서는 실시간 색역 사상을 위한 3차원 룩업 테이블을 좀더 효과적으로 구현하기 위한 하드웨어 구조를 제시하였다. 기존의 해상도 절감 3차원 룩업 테이블에 대해서 기술하고 하드웨어의 구조를 간소화시킨 해상도 절감 3차원 차분 룩업 테이블의 개념을 소개한다. 새로 제안하는 3차원 차분 룩업 테이블의 경우 기존의 방법과 같이 3차원 룩업 테이블을 8개의 1차원 룩업 테이블로 분해하여 구성하며 색역 사상 규칙은 현재 입력 영상 값과 색역 사상된 출력 값과의 차분 값만을 저장시키고 삼차원 보간 이후에 최종적으로 덧셈기를 추가함으로써 구성한다. 이를 통하여 필요로 하는 하드웨어의 양을 더욱 감축시킬 수 있으며 기존의 방법에 비해서 좀 더 고속으로 구현이 가능하다. 새로 제안된 하드웨어 구조는 FPGA나 ASIC으로 쉽게 구성이 가능하며 실시간 화질 개선의 용도로 쉽게 적용이 가능하다.

• 한국건설관리학회논문집
• /
• 제23권5호
• /
• pp.3-14
• /
• 2022

건설공사는 이해관계자들 간에 클레임(claim)이 발생할 가능성이 높은 특징을 지니고 있다. 클레임 그 자체가 분쟁은 아니지만, 당사간에 이견이나 갈등으로 인해 상호간 합의가 이루어지지 않으면 이는 분쟁으로 발전하게 될 가능성이 높다. 발주자와 건설사 간에 분쟁이 발생하게 되면 양측 모두에게 부정적인 영향을 끼치며, 건설분쟁을 최소화 하거나 선제적으로 대응하기 위해서는 발주자의 역할이 더욱 중요하다. 본 연구의 목적은 연관규칙 분석(Association Rules Analysis)을 바탕으로 분쟁유형과 분쟁원인의 연관성을 도출하고 주요 특징 및 발주자 관점의 시사점을 제시하는데 있다. 본 연구를 통해 분쟁유형과 분쟁원인간의 연관성을 파악할 수 있었으며 연관성이 높은 규칙을 도출할 수 있었다. 또한 연관규칙 분석을 통해 분쟁유형과 분쟁원인의 연관성을 도출함으로서 단순한 기술통계(빈도수)에 의존하는 것과 비교하여 보다 체계적인 분석을 실시하였다. 사례 분석을 통해 발주자 관점의 시사점으로 분쟁원인을 해소하기 위한 방향도 제시하였다. 본 연구의 결과를 통해 분쟁유형과 분쟁원인의 연관성에 대한 이해를 높일 수 있으며 건설공사의 분쟁을 선제적으로 대응하는데 유용하게 활용될 수 있다.

• 전기학회논문지
• /
• 제57권11호
• /
• pp.2108-2116
• /
• 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.

• 한국IT서비스학회지
• /
• 제10권2호
• /
• pp.223-234
• /
• 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.

• 한국지진공학회논문집
• /
• 제24권3호
• /
• pp.129-139
• /
• 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
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.372-372
• /
• 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.