• Proceedings of the Korean Information Science Society Conference
• /
• 1999.10a
• /
• pp.287-289
• /
• 1999

다등급 보안 자료기지 관리체계는 하위 등급의 자료에 대한 쓰기 연산 및 상위 등급의 자료에 대한 읽기 연산을 불허하여, 상위 등급의 자료가 하위 등급의 거래에 노출되는 것을 방지한다. 하지만, 전통적인 다등급 보안 자료기지 관리체계는 서로 상이한 등급간 거래의 공모로 생성될 수 있는 비밀 경로는 차단할 수 없다. 이러한 비밀 경로의 생성을 막기 위한 여러 연구가 다중 버전의 환경 및 제한된 버전의 환경 하에서 수행되어 왔다. 하지만 다중 버전에 기반한 기법은 상위 등급의 거래가 지나치게 오래된 버전의 자료를 읽을 뿐 아니라 버전 관리를 위하여 추가적인 부담이 요구된다는 단점이 있고, 제한된 버전에 기반한 기법은 항상 상위 등급 거래의 지연 및 철회를 강요한다는 단점이 있다. 본 논문에서는 제한된 버전 하에서 직렬화 가능성 그래프 검사 기법을 사용하여, 각 보안 등급간의 형평성을 높일 수 있는 비밀경로 생성 방지 기법을 제안한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.355-357
• /
• 2022

In this paper, as a positioning technology for predicting the movement path of a moving object using a recurrent neural network (RNN) model, which is a deep learning network, in an indoor environment, continuous location information is used to predict the path of a moving vehicle within a local path. We propose a movement path generation technique that can reduce decision errors. In the case of an indoor environment where GPS information is not available, the data set must be continuous and sequential in order to apply the RNN model. However, Wi-Fi radio fingerprint data cannot be used as RNN data because continuity is not guaranteed as characteristic information about a specific location at the time of collection. Therefore, we propose a movement path generation technique for a vehicle moving a local path in an indoor environment by giving the necessary sequential location continuity to the RNN model.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.15 no.7
• /
• pp.4482-4488
• /
• 2014

This paper proposes the creation scheme of a threat map for robot global path planning. The threat map was generated using neural network theory by analyzing the robot's armament state and the menace information of an enemy or obstacle. In addition, the performance of the suggested method was verified using the compared result of the damage amount and existing robot path data.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2017.04a
• /
• pp.598-601
• /
• 2017

소프트웨어 테스트는 시스템의 신뢰도를 판단하는 중요한 작업이지만, 많은 노력과 비용을 필요로 한다. 모델 기반 테스트는 이러한 비용을 줄이기 위한 방안으로써 제안되었다. 정형적 모델로부터 시스템의 실행 가능한 경로를 파악하고, 각 경로마다 입력 값을 생성하여 테스트를 수행한다. 이 때, 적절한 입력 값을 찾기 위해 메타-휴리스틱 기법을 사용하는데, 기존의 알고리즘은 목적 경로와 관련이 없는 변수까지 구분없이 고려하기 때문에 시스템이 복잡할수록 불필요한 연산이 많아지는 문제가 있다. 본 논문은 슬라이싱 기법과 우선순위 정책을 적용한 테스트 데이터 자동 생성 기법을 제안하며, 실험을 통해 기존의 방법보다 효과적으로 테스트 데이터를 생성함을 보인다.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.2
• /
• pp.161-167
• /
• 2012

This research deals with generating via points for autonomous navigation on a roadway for unmanned vehicles. When a vehicle plans a path from a starting point to a goal point, it should be able to map out which lane on which road it passes by. For this purpose, we should organize positional information of roads and save it as a database. This paper presents methods to save the database and to plan a shortest path to the goal by generating via points in consideration of the moving direction and the lane directions. Then we prove that the proposed algorithm can find the optimal path on the road through simulations.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.50 no.6
• /
• pp.385-391
• /
• 2022

This paper presents to develop a path planning algorithm combining gradient descent-based path planning (GBPP) and particle swarm optimization (PSO) for considering prohibited flight areas, terrain information, and characteristics of fixed-wing unmmaned aerial vehicle (UAV) in 3D space. Path can be generated fast using GBPP, but it is often happened that an unsafe path can be generated by converging to a local minimum depending on the initial path. Bio-inspired swarm intelligence algorithms, such as Genetic algorithm (GA) and PSO, can avoid the local minima problem by sampling several paths. However, if the number of optimal variable increases due to an increase in the number of UAVs and waypoints, it requires heavy computation time and efforts due to increasing the number of particles accordingly. To solve the disadvantages of the two algorithms, hierarchical path planning algorithm associated with hierarchical particle swarm optimization (HPSO) is developed by defining the initial path, which is the input of GBPP, as two variables including particles variables. Feasibility of the proposed algorithm is verified by software-in-the-loop simulation (SILS) of flight control computer (FCC) for UAVs.

• Journal of KIISE:Software and Applications
• /
• v.34 no.4
• /
• pp.368-376
• /
• 2007

How to represent the search space is as important as which search algorithm to use for finding natural-looking paths for moving NPC (non-player character) in computer games. Recently, various state space representation methods which have been developed for computer games are being used while A* algorithm dominates as the preferred search algorithm. These representation methods show some drawbacks such as the size of state space is too large, there is no guarantee for optimality, the path found is not natural-looking, and the generation of nodes and links is not automatic by depending on a level designer. In this paper the requirements for natural-looking paths are introduced and to find paths satisfying these requirements, the use of the generalized visibility graphs which is the extended version of the visibility graph in Robotics is proposed.

• Journal of KIISE:Software and Applications
• /
• v.30 no.9
• /
• pp.862-866
• /
• 2003

Traveling Salesman Problem(TSP) is a combinational optimization problem, Genetic Algorithm(GA) and Lin-Kernighan(LK) Heuristic［1］that is Local Search Heuristic are one of the most commonly used methods to resolve TSP. In this paper, we introduce ACS(Ant Colony System) Algorithm as another approach to solve TSP and propose a new pheromone updating method. ACS uses pheromone information between cities in the Process where many ants make a tour, and is a method to find a optimal solution through recursive tour creation process. At the stage of Global Updating of ACS method, it updates pheromone of edges belonging to global best tour of created all edge. But we perform once more pheromone update about created all edges before global updating rule of original ACS is applied. At this process, we use the frequency of occurrence of each edges to update pheromone. We could offer stochastic value by pheromone about each edges, giving all edges' occurrence frequency as weight about Pheromone. This finds an optimal solution faster than existing ACS algorithm and prevent a local optima using more edges in next time search.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.3
• /
• pp.125-134
• /
• 2017

The SOA (Service Oriented Architecture) based softwares are escalated because of quickly coping with business requirement. SOA can not apply to existing test method because of loosely coupled service and massage exchange architecture. In this paper, we suggest a method of test case generation using BPMN (Business Process Model and Notation). First we model processes, then make Business Flow Graph (BFG). After searching the euler path through symmetrized BFG about input and output degrees, we generate test cases. A method of test case generation using BPMN can apply at SOA-based system, and reduce the number of test cases.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2000.10b
• /
• pp.1207-1210
• /
• 2000

프로토콜을 설계하고 이를 구현하면 IUT가 프로토콜 규격과 일치하는지를 검증하는 적합성 시험을 수행한다. 기존의 시험열 생성 방법은 오일러 경로에 의한 방법을 사용하였으나 이 방법은 전체 경로를 다 포함하지 못한다는 단점이 있다. 이 단점을 개선하여 TPT(Transition Possibility Tree)를 생성하여 확장된 테스트 커버리지를 갖는 서브투어 생성방법이 제안되었다. 이 논문에서 기존에 제안된 TPT 서브투어 생성 방법에서 시험열의 갯수가 많아진다는 단점을 보안하여 TPT 서브투어 생성 방법에서의 효과적인 시험열 선택 방법을 제안하였다. 제안 방법에 의해서 생성된 시험열도 완전한 시험 목적에 부합하지 않는다는 단점은 있으나 시험자가 선택해야 하는 시험열의 양을 최소화하는 데 그 의미가 있다.