• 정보보호학회논문지
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• 제33권6호
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• pp.1111-1123
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• 2023

최근 생성 모델이 발전함에 따라 생성 모델을 위협하는 연구도 활발히 진행되고 있다. 본 논문은 Text-to-Image 모델에 대한 멤버십 추론 공격을 위한 새로운 제안 방법을 소개한다. 기존의 Text-to-Image 모델에 대한 멤버십 추론 공격은 쿼리 이미지의 caption으로 단일 이미지를 생성하여 멤버십을 추론하였다. 반면, 본 논문은 Textual Inversion을 통해 쿼리 이미지에 personalization된 임베딩을 사용하고, Adversarial Prompt 생성 방법으로 여러 장의 이미지를 효과적으로 생성하는 멤버십 추론 공격을 제안한다. 또한, Text-to-Image 모델 중 주목받고 있는 Stable Diffusion 모델에 대한 멤버십 추론 공격을 최초로 진행하였으며, 최대 1.00의 Accuracy를 달성한다.

• 산업융합연구
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• 제13권1호
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• pp.11-23
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• 2015

Organizations use multiple team membership to enhance individual and team productivity and learning, but this structure creates competing pressures on attention and information, which make in difficult to increase both productivity and learning. My model describes how the number and variety of multiple team memberships drive different mechanisms, yielding distinct effects.

• 한국지능시스템학회논문지
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• 제13권6호
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• pp.722-728
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• 2003

In this paper, we propose a fuzzy traffic controller of Sugeno`s fuzzy model so as to model the nonlinear characteristics of controlling the traffic light. It use a degree of the traffic congestion of the preceding roads as an input so that it can cope with traffic congestion appropriately, which causes the loss of fuel and our discomfort. First, in order to construct fuzzy traffic controller of Sugeno`s fuzzy model, we model the control process of the traffic light by using Mamdani`s fuzzy model, which has the uniform membership functions of the same size and shape. Second, we make Mamdani`s fuzzy model with the non-uniform membership functions so that it can exactly reflect the knowledge of experts and operators. Last, we construct the fuzzy traffic controller of Sugeno`s fuzzy model by learning from the input/output data, which is retrieved from Mamdani`s fuzzy model with the non-uniform membership functions. We compared and analyzed the fixed traffic light controller, the fuzzy traffic controller of Mamdani`s fuzzy model and the fuzzy traffic controller of Sugeno`s fuzzy model by using the delay time and the proportion of the entered vehicles to the occurred vehicles. As a result of comparison, the fuzzy traffic controller of Sugeno`s fuzzy model showed the best performance.

• Industrial Engineering and Management Systems
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• 제12권1호
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• pp.36-40
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• 2013

The paper discusses the problem of how to allocate the fund to a large number of individuals in a higher school so as to bring a higher utility return based on the theory of uncertain set. Suppose that experts can assign each invested individual a corresponding nondecreasing membership function on a close interval I according to its actual level and developmental foreground. The membership degree at the fund $x{\in}I$ is called utility degree from fund x, and product (minimum) of utility degrees of distributed funds for all invested individuals is called united utility degree from the fund. Based on the above concepts, we present an uncertain optimization model, called Maximal United Utility Degree (or Maximal Membership Degree) model for fund distribution. Furthermore, we use nondecreasing polygonal functions defined on close intervals to structure a mathematical maximal united utility degree model. Finally, we design a genetic algorithm to solve these models.

• 한국정보시스템학회지:정보시스템연구
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• 제33권1호
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• pp.133-157
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• 2024

Purpose The purpose of this study is to identify the utility and sacrifice factors of paid membership in domestic e-commerce based on the value-based acceptance model, and to determine its impact on perceived value and intention to continue using e-commerce. Design/methodology/approach This study confirmed the perceived benefits and sacrifice factors of e-commerce paid membership through in-depth interviews, and verified the research model through an online survey. Findings The study identifies seven perceived benefit factors(differentiation, enjoyment, sharing, point benefit, discount benefit, contents benefit, and delivery benefit) and three perceived sacrifice factors(fee, opportunity loss, complexity). Structural model verification reveals that discount benefit, delivery benefit, and opportunity loss significantly impact the perceived value in Coupang Rocket Wow, while discount benefit, point benefit, and fee significantly influence the perceived value in Naver Plus membership. The perceived value of both memberships positively influences the intention to continue using the respective e-commerce platforms. A comparison highlights a significant difference in the impact of opportunity loss on perceived value between Coupang Rocket Wow and Naver Plus memberships.

• 한국멀티미디어학회논문지
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• 제22권9호
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• pp.1069-1079
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• 2019

In this study, we developed a $PM_{10}$ forecasting model using DNN and Membership Function, and improved the forecasting performance. The model predicts the $PM_{10}$ concentrations of the next 3 days in the Seoul area by using the weather and air quality observation data and forecast data. The best model(RM14)'s accuracy (82%, 76%, 69%) and false alarm rate(FAR:14%,33%,44%) are good. Probability of detection (POD: 79%, 50%, 53%), however, are not good performance. These are due to the lack of training data for high concentration $PM_{10}$ compared to low concentration. In addition, the model dose not reflect seasonal factors closely related to the generation of high concentration $PM_{10}$. To improve this, we propose Julian date membership function as inputs of the $PM_{10}$ forecasting model. The function express a given date in 12 factors to reflect seasonal characteristics closely related to high concentration $PM_{10}$. As a result, the accuracy (79%, 70%, 66%) and FAR (24%, 48%, 46%) are slightly reduced in performance, but the POD (79%, 75%, 71%) are up to 25% improved compared with those of the RM14 model. Hence, this shows that the proposed Julian forecast model is effective for high concentration $PM_{10}$ forecasts.

• 한국경영공학회지
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• 제23권4호
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• pp.87-103
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• 2018

This paper introduces the method to develop two main types of the fuzzy OEE (Overall Equipment Effectiveness) models via triangular membership function for measuring uncertainty. The fuzzy OEE includes model type 1 and model type 2. The model type 1 is used when the theoretical machine speed only reflects the time loss whereas model type 2 is used when the actual machine speed reflects both time and speed loss. Model type 2 has shown to perform a lower availability rate and a higher performance rate compared to model type 1. In addition, the fuzzy UPH (Unit Per Hour) which is derived from using the fuzzy OEE is presented to satisfy demand uncertainty. The fuzzy UPH can easily measure the fuzzy tact time and cycle time by reciprocating itself. Finally, this study demonstrates the fuzzy OEE models using IVIFS (Interval-Valued Intuitionistic Fuzzy Set) based on the characterization via membership function, non-membership function and hesitant function. For the purpose of analyzing the fuzzy system OEE, the OEE for each machine of plant structure is considered triangular interval-valued intuitionistic fuzzy number. Regardless of plant structure, the validity degree of fuzzy membership function of system OEE decreases when the number of machine with worst value of the validity degree increases. Corresponding examples are presented in this paper for practitioner to understand the applicability and practicability of the proposed fuzzy OEE methods.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제4권2호
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• pp.211-216
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• 2004

Fuzzy neural networks have been successfully applied to analyze/generate predictive rules for medical or diagnostic data. However, most approaches proposed so far have not considered the weights for the membership functions much. This paper presents a neural network with weighted fuzzy membership functions. In our approach, the membership functions can capture the concentrated and essential information that affects the classification of the input patterns. To verify the performance of the proposed model, well-known Iris data set is performed. According to the results, the weighted membership functions enhance the prediction accuracy. The architecture of the proposed neural network with weighted fuzzy membership functions and the details of experimental results for the data set is discussed in this paper.

• International Journal of Control, Automation, and Systems
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• 제2권3호
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• pp.298-309
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• 2004

In this paper, a new evolutionary scheme to design a TSK fuzzy model from relevant data is proposed. The identification of the antecedent rule parameters is performed via the evolutionary algorithm with the unique fitness function and the various evolutionary operators, while the identification of the consequent parameters is done using the least square method. The occurrence of the multiple overlapping membership functions, which is a typical feature of unconstrained optimization, is resolved with the help of the proposed fitness function. The proposed algorithm can generate a fuzzy model with transparent membership functions. Through simulations on various problems, the proposed algorithm found a TSK fuzzy model with better accuracy than those found in previous works with transparent partition of input space.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.372-377
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• 1993

In this paper, we investigate a set-membership identification approach to the quantification of an upper bound of model uncertainty in frequency domain, which is required in the H$_{\infty}$ robust control system design. First we formulate this problem as a set-membership identification of a nominal model error in the presence f unknown noise input with unknown bound, while the ordinary set-membership approaches assume that an upper bound of the uncertain input is known. For this purpose, the proposed algorithm includes the estimation of the bound of the uncertain input. thus the proposed method can obtain the hard bound of the model error in frequency domain as well as a parametric lower-order nominal model. Finally numerical simulation results are shown to confirm the validity of the presented algorithm..