• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권4호
• /
• pp.1887-1898
• /
• 2018

In this paper, a method to classify insider threat activity is introduced. The internal threats help detecting anomalous activity in the procedure performed by the user in an organization. When an anomalous value deviating from the overall behavior is displayed, we consider it as an inside threat for classification as an inside intimidator. To solve the situation, Markov Chain Model is employed. The Markov Chain Model shows the next state value through an arbitrary variable affected by the previous event. Similarly, the current activity can also be predicted based on the previous activity for the insider threat activity. A method was studied where the change items for such state are defined by a transition probability, and classified as detection of anomaly of the inside threat through values for a probability variable. We use the properties of the Markov chains to list the behavior of the user over time and to classify which state they belong to. Sequential data sets were generated according to the influence of n occurrences of Markov attribute and classified by machine learning algorithm. In the experiment, only 15% of the Cert: insider threat dataset was applied, and the result was 97% accuracy except for NaiveBayes. As a result of our research, it was confirmed that the Markov Chain Model can classify insider threats and can be fully utilized for user behavior classification.

• 대한인간공학회지
• /
• 제15권2호
• /
• pp.157-163
• /
• 1996

A single line display menu (SDM) is widely used for the user interface of many electronic consumer products, and the designers need useful guidelines applicable to the SDM. In many studies on menus, major focus has been placed on the optimal menu structure, but only a few standard menu structures, such as $64^{1},8^{2},4^{3}$,and $2^{6}$ are usually tested for optimality. In many cases, however, ill defined or asymmetric structures are suggested as design alternatives. To determine the optimal menu structure, user performance should be obtained in terms of quantitative measures. Hence, a model is needed to provide a predicted value of user performance for a given menu structure. Altough several models have been proposed for ordinary menus, none is available for the SDM yet. To solve this problem a performance model was developed in this study using the neural network approach. This model is capable of providing quantitative measures of human performance for any menu structures without conducting additional experiments, which will save much time and reduce the design cost.

• Management Science and Financial Engineering
• /
• 제15권1호
• /
• pp.51-69
• /
• 2009

A network model and a Genetic Algorithm (GA) is proposed to solve the simultaneous estimation of the trip distribution and traffic assignment from traffic counts in the congested networks in a logit-based Stochastic User Equilibrium (SUE). The model is formulated as a problem of minimizing a non-linear objective function with the linear constraints. In the model, the flow-conservation constraints are utilized to restrict the solution space and to force the link flows become consistent to the traffic counts. The objective of the model is to minimize the discrepancies between two sets of link flows. One is the set of link flows satisfying the constraints of flow-conservation, trip production from origin, trip attraction to destination and traffic counts at observed links. The other is the set of link flows those are estimated through the trip distribution and traffic assignment using the path flow estimator in the logit-based SUE. In the proposed GA, a chromosome is defined as a real vector representing a set of Origin-Destination Matrix (ODM), link flows and route-choice dispersion coefficient. Each chromosome is evaluated by the corresponding discrepancies. The population of the chromosome is evolved by the concurrent simplex crossover and random mutation. To maintain the feasibility of solutions, a bounded vector shipment technique is used during the crossover and mutation.

• 한국전산유체공학회지
• /
• 제13권2호
• /
• pp.62-67
• /
• 2008

This study aims to investigate numerically the static stiffness characteristics of porous air bearing and to estimate appropriate permeability values of porous medium. In particular, a new roughness model is proposed and implemented into the commercial CFD code (FLUENT Ver. 6.2) by using C language based user subroutine. The predicted results are extensively compared with experimental data. The roughness model is also validated through comparison with the results from open literature. It is found that the predictions for static stiffness are in good agreement with experimental data. Therefore, the suggested model based on the roughness Reynolds number can be used in studying the stiffness characteristics of porous air bearing effectively. In addition, numerical simulations of various diameter size and conditions are conducted. According the results, it is expected that the static stiffness of porous air bearing has the non-linear characteristics.

• Journal of Multimedia Information System
• /
• 제6권4호
• /
• pp.179-184
• /
• 2019

This paper introduces a study for procedurally generating the behavior of objects in a virtual environment at runtime. This study was initiated to enable the behavioral model of objects in virtual reality applications to evolve in response to user behavior at runtime. Our approach is to describe the behavior of an object as a behavior tree, and to make a node of the behavior tree change to another type if a certain condition is satisfied. We defined four types of node changes: "parameterized", "probabilistic", "alternate", and "variant". We experimented with a virtual environment that includes a variety of simple procedural elements to explore the possibilities of our approach. As a result of the implementation, if an optimization algorithm that can select and apply the optimized procedural elements in response to the user's behavior is complemented, it is confirmed that more intelligent objects and agents can be implemented in virtual reality applications.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 1991년도 봄 학술발표회 논문집
• /
• pp.50-55
• /
• 1991

This paper presents database technique for an computer-integrated structural design system of buildings. Network database designed to support all the processes of structural design, such as, planning, modelling, analysis, member design and redesign processes etc. stores all information from user input and system results effectively and so provides centeral communication area between applications. The user interface wi th interactive and batch modes plays roles of building modeler including conventional pre-processor and post-processor. The concepts of 'Planar Surface Modeling' and 'Geometry Zoning' are defined for easy construction of building model. The concept presented in this paper will save the time and memory required for model generation and contribute to data consistency, thus leave a designer more time actually performing the analyses and interpreting the results. The formulation of automating the process of bulilding model ins and structural analysis is the key to study.

• 한국전산구조공학회논문집
• /
• 제31권4호
• /
• pp.191-197
• /
• 2018

폴리머 폼은 다공성을 가장 큰 특징으로 하는 재료이기 때문에, 본 연구에서 비가역 열역학 관점을 기반으로 폴리머 폼의 기공 성장 및 합체를 고려한 손상 탄성 구성방정식을 개발하였으며, 개발된 구성방정식은 unilateral 손상의 효과를 고려하였다. 유한요소해석의 적용을 위해 상용 유한요소해석 프로그램인 ABAQUS의 사용자 서브루틴 UMAT을 이용하여 제안된 구성방정식을 수치적으로 구현하였다. 비선형 유한요소해석 결과와 폴리머 폼의 인장 시험 결과와 비교를 통해 제안된 손상 모델의 유효성을 검증하였으며, 제안된 구성방정식의 재료모델상수가 손상에 미치는 영향에 대해 분석하였다.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
• /
• 제14권6호
• /
• pp.614-618
• /
• 2008

인터넷 서비스의 급속한 발전으로 멀티미디어 데이타의 양이 크게 증가함에 따라, 이를 분석하여 유용한 정보를 얻기 위해 사용자 개개인에 초점을 맞춘 효율적인 검색기술이 필요하게 되었다. 하지만 최근 웹사이트에서 제공하는 사용자 모델링 서비스는 텍스트 기반 페이지 구성이나 추천 검색 등에만 국한되어 있는 단점이 있다. 본 논문에서는 사용자 모델링 기법을 동영상 검색에 적용하기 위해 사용자의 선호도를 베이지안 네트워크로 모델링하고, 추론된 확률 값을 검색에 반영하는 방법을 제안한다. 이를 위해 실제 연구실 환경 내에 존재하는 컨텍스트 정보를 정의하였고, 설치된 카메라로부터 얻어진 동영상이 포함하는 컨텍스트 정보를 텍스트의 형태로 주석을 달았다. 사용자로부터 입력받은 사용자 개인의 정보는 설계된 베이지안 네트워크 모델의 증거 값으로 사용되어, 그로부터 사용자의 선호도를 추론하도록 하였다. 베이지안 네트워크의 추론 결과로 얻어진 확률 값은 검색에 반영되어 각 사용자의 선호도에 맞는 검색 결과를 보여준다. 사용자 평가 결과, 제안하는 모델을 사용하여 선택된 결과의 만족도가 일반적인 검색의 결과에 비해 높음을 확인하였다.

• 전자공학회논문지B
• /
• 제32B권5호
• /
• pp.671-682
• /
• 1995

In this paper, we propose a multimedia query language MQL which defines and manipulates multimedia data as integration of monomedia data in time and space. The MQL is designed for a multimedia data model, called the object-relationship model, and based on the multimedia object calculus which formally describes operations on multimedia data. The SQL- like syntax for class definition and object manipulation, such as retrieval, insert, update, and delete, is defined. We show how the MQL can represent the user queries using composite temporal-spatial class structures and various relationships, such as equivalence and sequence.

• Journal of Communications and Networks
• /
• 제18권3호
• /
• pp.411-419
• /
• 2016

This article investigates the problem of distributed channel selection in opportunistic spectrum access networks from a perspective of interference minimization. The traditional physical (PHY)-layer interference model is for information theoretic analysis. When practical multiple access mechanisms are considered, the recently developed binary medium access control (MAC)-layer interference model in the previous work is more useful, in which the experienced interference of a user is defined as the number of competing users. However, the binary model is not accurate in mathematics analysis with poor achievable performance. Therefore, we propose a real-valued one called stochastic MAC-layer interference model, where the utility of a player is defined as a function of the aggregate weight of the stochastic interference of competing neighbors. Then, the distributed channel selection problem in the stochastic MAC-layer interference model is formulated as a weighted stochastic MAC-layer interference minimization game and we proved that the game is an exact potential game which exists one pure strategy Nash equilibrium point at least. By using the proposed stochastic learning-automata based uncoupled algorithm with heterogeneous learning parameter (SLA-H), we can achieve suboptimal convergence averagely and this result can be verified in the simulation. Moreover, the simulated results also prove that the proposed stochastic model can achieve higher throughput performance and faster convergence behavior than the binary one.