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2022 개정 교육과정이 고시된 과정에서 소프트웨어 교육이 현실 세계의 문제를 해결하는 데 직접적으로 연결되 지 않는 학습 개념 수준에 그치는 것이 아닐지에 대한 우려가 있다. 이에 대응하는 방법론 가운데 최근에는 ‘학습 자 중심의 교육 방법론’이 강조되고 있으며 알고리즘에 대한 교육 또한 지속적인 교육적 가치를 가지기 때문에 초 등교육에서 반드시 학습되어야 하는 개념이다. 본 연구에서는 컴퓨팅 교육을 초등학교 교육과정에 효과적으로 통 합하고, 학생들이 현실 세계의 문제를 해결하는 경험을 실제 체험할 수 있도록 Living Lab의 프로세스를 언플러그 드 활동과 결합하여 알고리즘 교육에 적용하였다. 그 결과 학생들의 문제해결력과 협력적 의사소통 역량이 향상됨 을 확인할 수 있었다. 본 연구 결과를 토대로 어려운 컴퓨팅 개념에 대해 다양한 언플러그드 활동이 개발되어 교 육 현장에서도 Living Lab이 정착되기를 기대한다.

In the 2022 revised curriculum, there's concern about software education remaining disconnected from real- world problem-solving. To address this, 'learner-centered methodologies' are emphasized, and algorithm education is promoted in elementary schooling. This study effectively integrated computing education within elementary curriculum, applying Living Lab processes alongside unplugged activities for algorithm education, enhancing students' problem-solving and collaborative communication skills. The study anticipates the development of varied unplugged activities for challenging computing concepts, establishing Living Lab within educational settings.

미래 사회로 갈수록 대중교통을 연계하기 위한 환승센터의 기능 및 규모가 확대됨에 따라 환승센터 내에서 이용자를 대상으로 경로를 안내하는 시스템의 필요성이 제기되고 있다. 그러나 도로에서의 차량을 대상으로 한 최적경로에 관한 모형은 많이 제시되고 있는 반면 건물 내에서 보행자를 위한 최적경로에 대한 연구는 미미하다. 따라서 본 연구는 복합환승센터 내에서 승용차를 이용하는 개인이 지하주차장에서 환승센터 내 대중교통 수단 이용을 위한 승강장이나 상가 시설로 이동하는 최적의 경로를 제시할 수 있는 모형개발을 주요내용으로 하였다. 건물 내 최적경로 모형은 다익스트라(Dijkstra) 알고리즘을 기본으로 하여 거리의 최소비용을 산정하고, 여기에 이동시간, 피로감, 쾌적도와 대기시간 등의 요소를 순위합, 산술합 방법 등을 통해 적용하여 객관성을 부가하였다. 또한 대중교통 수단의 이용자들의 성향이 반영된 Neuro-Fuzzy 모형을 통하여 환승센터 내 환승하는 이용자에게 최적의 교통수단을 제시하고, 그 해당 수단의 승강장까지 최적경로를 제시함으로써 모형의 효율성을 높였다. 마지막으로 가상의 시나리오들를 통하여 개발 모형의 효율성 검증하였다. 검증결과 개발모형을 통했을 경우 그렇지 않을 경우보다, 수직이동 경로차이의 시나리오에서 약 75%, 수평이동 경로차이의 시나리오에서 약 더 효율적으로 나타났다.

As function and scale of the transit center get larger, the efficient guidance system in the transit center is essential for transit users in order to find their efficient routes. Although there are several studies concerning optimal path for the road, but insufficient studies are executed about optimal path inside the building. Thus, this study is to develop the algorithm about optimal path for car owner from the basement parking lot to user's destination in the transfer station. Based on Dijkstra algorithm which calculate horizontal distance, several factors such as fatigue, freshness, preference, and required time in using moving devices are objectively computed through rank-sum and arithmetic-sum method. Moreover, optimal public transportation is provided for transferrer in the transfer station by Neuro-Fuzzy model which is reflected on people's tendency about public transportation mode choice. Lastly, some scenarios demonstrate the efficiency of optimal path algorithm for pedestrian in this study. As a result of verification the case through the model developed in this study is 75 % more effective in the scenario reflected on different vertical distance, and more effective in the scenario considering different horizontal distance, respectively.

지난 10년간 우리나라에서 발생한 화재 사건 중 건물 화재가 가장 많고 재산과 인명 피해가 가장 많다. 하지 만 기존 소방 시스템은 비상구 위치만 알려주고 안전한 경로를 안내해 사상자들이 원활하게 대피할 수 있도록 도와 주지는 않는다. 공간적 특성을 이용하여 수직적 특성과 수평적 특성을 구분하여 성공적인 대피를 돕는 시스템을 제안 하였다. 본 연구에서는 온도 감지 센서와 연기 센서 값을 이용하여 화재를 예측하고, Dijkstra 알고리즘을 통해 최적 의 대피 경로를 계산하여 효과적인 대피 시스템을 제안하였다.

Among the fire incidents in Korea over the past decade, building fires are the most common, and property and human casualties are the most common. However, the existing fire fighting system does not only inform the location of emergency exits and guide safe routes to help casualties evacuate smoothly. A system was proposed to help successful evacuation by distinguishing vertical and horizontal characteristics using spatial characteristics. In this study, an effective evacuation system was proposed by predicting fires using temperature detection sensors and smoke sensor values, and calculating the optimal evacuation path through the Dijkstra algorithm.

To have an efficient and successful communication in ad hoc networks, the use of Cognitive Radios (CR) has gained popularity in the recent past. These radios have spectrum sensing capabilities and thus can easily switch to free spectrum band. The use of such type of radios not only improves the routing performance but at the same time improves the overall throughput of the network. To show the same, we implement shortest path routing strategy in MATLAB-7.01. The routing scheme uses two types of radios one with spectrum sensing capability such as cognitive radios and the other which doesn’t. The following performance metrics such as Packet Delivery Ratio (PDR), Delay, Success Ratio and Hop count are taken into consideration for measuring the efficiency. The result shows that a node having spectrum sensing capability outperforms the other one.

Path planning algorithm is a key issue among robot control areas. In practical engineering applications, traditional methods have some limitations to a certain degrees in key aspects of cost, efficiency, security, flexibility, portability, etc. Through the analysis and comparison of A-star algorithm and Dijkstra algorithm, path planning problem supporting multiple cars run parallely (PPSMC for short) in a static and dynamic obstacles co-existing environment is studied. An A-STAR-Dijkstra-integrated algorithm is promoted to make multiple cars moving parallely without collision or deadlock. Both two algorithms are optimized too. The algorithm has applied in smart park.

This paper first represent the basic conceptions of anonymous communication, then introduce the fundamentals in Anonymous Communication. Afterwards, we went deep to the classification of anonymous network topological, therefore we could get a better understanding on P2P anonymous communication system. We also systematically analyzes the existing node-select algorithms. Furthermore, we propose and implement a new node selection algorithm based on Dijkstra algorithm, named NSDA algorithm. We give a belief description about the backgrounds and design of NSDA Algorithm. The algorithm can combine the node properties with link properties to select node, which can adjust the system performancing and anonymity. In order to evaluate the NSDA algorithm, we have done experiments in Network Simulator 3, and we also explain the reason why we choose Network Simulator 3 as the simulate tool. In the end, we analyze the characteristics of NSDA algorithm according to the results of experiments.

Dynamic optimization scheduling strategy is carried out based on a comprehensive objective function which is constructed for reservoirs. Corresponding constraints and conditions are generally designed, and then the solution of the objective function is worked out based on those constraints and finally an optimal scheduling scheme suitable for reservoirs is acquired in combination with actual conditions. Focusing on the problems above, this study combines Dijkstra algorithm with genetic algorithm (GA) effectively and makes full use of their advantages. Consequently, an optimized Dijkstra - genetic algorithm (D – GA) is obtained and applied in the scheduling scheme. First of all, the thesis preliminarily introduces relevant algorithms on water conservancy project and sets up a data model consistent with the actual situation. Secondly, this work analyzes the two algorithms, improves the Dijkstra algorithm and applies D – GA to solution optimization. Thirdly, this study compares the results obtained by using D – GA and GA respectively and finally completes the simulation of water conservancy scheduling system.

본 논문에서는 보행로봇의 일종인 TITAN-VIII라 불리는 로봇을 이용하여 가장 짧은 경로를 탐색하여 이동하는 방법에 관한 연구를 나타낸다. 보행로봇의 경우 바퀴구동 로봇에 비해 불규칙한 지면 위를 자유로이 이동 가능한 장점 등을 가지고 있는데 반해 이동속도는 바퀴구동 로봇에 비해 느린 편이다. 따라서 본 논문에서는 목적지에 도달하기까지 시간을 최소화하는 최적경로 탐색 제어방법을 제시하였다. 경로를 탐색하기 위해 Dijkstra's algorithm라 불리는 알고리즘을 기반으로 하여 적용하였다. 또한 로봇이 항상 정적인 자세를 유지하는 로봇의 다양한 자세에 대해서도 다루었다. 로봇의 자세제어와 알고리즘을 통하여 로봇의 관절각 결정에 필요한 여러 수학방정식을 제시하였다. 그 후 원하는 궤적으로 로봇이 이동하고 탐색하는 알고리즘을 고안하였고, 제안한 방법의 결과를 실험으로 확인하였다.

In this paper, the optimizing path finding control method is studied for a Legged-robot. It's named TITAN-VIII. It has a lot of advantages over the wheeled robot in the ability to walk freely on an irregular ground. However, the moving speed on the ground of the Legged-robot is slower than the Wheeled-robot's. Consequently, the purpose of the method is presented in this paper to minimize its time when it walks to a goal. It find the path, our approach is based on an algorithm which is called Dijkstra's algorithm. In the rest of paper, the various posture of the robot is discussed to keep the robot always in the statically stable. Based on above works, the math formulas are presented to determine the joint angles of the robot. After that an algorithm is designed to find and keep robot on the desired trajectory. Experimental results of the proposed method are demonstrated in the last of paper.

In this paper, we develop the path planning algorithm using the improved Dijkstra algorithm and the particle swarm optimization. To get the optimal path, at first we construct the MAKLINK on the world environment and then make a graph associated with the MAKLINK. From the graph, we obtain the Dijkstra path between the starting point and the destination point. From the optimal path, we search the improved Dijkstra path using the graph. Finally, applying the particle swarm optimization to the improved Dijkstra path, we obtain the optimal path for the mobile robot. It turns out that the proposed method has better performance than the result in [1].

This paper presents a fast and effective methodology for service restoration in large-scale distribution systems. The service restoration problem is formulated as a constrained optimization problem and requires the fast computation time and superior solution because the more unfaulted out-of-service area should be restored as soon as possible. The proposed methodology is designed to consider the fast computation time and priority service restoration by dijkstra algorithm and fuzzy theory in large-scale distribution systems. Simulation results demonstrate the validity and effectiveness of the proposed on a 26-bus and 140-bus system.

본 논문에서는 비등방성 특징 기반의 다익스트라 알고리즘(Dijkstra algorithm)을 이용한 효율적인 감성 완화 프레임워크를 제안한다. 감성을 완화시키는 것은 감성 분석만큼이나 중요하며, 사람의 우울함이나 외로움을 자동으로 완화시켜줄 수 있는 프레임워크로써 인간과 컴퓨터의 상호작용(HCI, Human-Computer Interaction)측면에서도 매우 중요한 의미를 갖는다. 본 논문에서는 1) 마이크로소프트의 Emotion API를 이용하여 얼굴 표정으로부터 변화하는 감정값을 계산하고, 2) 이 감정값의 차이를 이용하여 우울이나 외로움 같은 이상 감정을 인지한다. 3) 마지막으로, 감성 히스토그램과 비등방성 특성을 고려한 감정 메시 기반의 매칭 과정을 거침으로써 사용자에게 완화된 감성이 내포된 이미지들을 제시해준다. 본 논문에서 제안하는 기법은 얼굴 영상을 이용하여 사용자가 쉽게 감성의 변화를 인지하고, 완화된 감성으로 감정을 트레이닝 할 수 있는 시스템이다.

In this paper, we propose an efficient emotional relaxation framework using Dijkstra algorithm based on anisotropic features. Emotional relaxation is as important as emotional analysis. This is a framework that can automatically alleviate the person's depression or loneliness. This is very important for HCI (Human-Computer Interaction). In this paper, 1) Emotion value changing from facial expression is calculated using Microsoft's Emotion API, 2) Using these differences in emotion values, we recognize abnormal feelings such as depression or loneliness. 3) Finally, emotional mesh based matching process considering the emotional histogram and anisotropic characteristics is proposed, which suggests emotional relaxation to the user. In this paper, we propose a system which can recognize the change of emotion easily by using face image and train personal emotion by emotion relaxation.

There are a variety of apps that are finding their way. And in car navigation, we launched a product that reflects Augmented Reality technology this year. However, existing apps have problems. It is implemented in 2D or 3D, has a large error range because it has been modified in most vehicles, is not updated in real time, and car augmented reality navigation is a vehicle, and a separate device is required, etc. In this study, we implemented a smartphone app for walking directions using augmented reality, and made it possible to intuitively use a route service from a user 's location to a destination. The Dijkstra algorithm is applied to calculate the shortest path to solve the problem of finding the route with the least cost. By using this application, it is possible to use the route search service even in a data-free environment, to solve the inconvenience of the language barrier, and to update in real time, so that the latest information can be always maintained. In the future, we want to develop an app that can be commercialized by using a character in the path to promote it.

The Distribution System consist of many tie-line switches and sectionalizing switches, operated a radial type. When an outage occurs in Distribution System, outage areas are isolated by system switches, has to restored as soon as possible. At this time, system operator have to get a information about network topology for service restoration of outage areas. Therefore, the searching result of restorative topology has to fast computation time and reliable result topology for to restore a electric service to outage areas, equal to optimal switching operation problem. So, the problem can be defined as combinatorial optimization problem. The service restoration problem is so important problem which have outage area minimization, outage loss minimization. Many researcher is applying to the service restoration problem with various techniques. In this paper, advanced Dijkstra algorithm is applied to searching a restoration topology, is so efficient to searching a shortest path in graph type network. Additionally, fuzzy rules and operator are applied to overcome a fuzziness of correlation with input data. The present technique has superior results which are fast computation time and searching results than previous researches, demonstrated by example distribution model system which has 3 feeders, 26 buses. For a application capability to real distribution system, additionally demonstrated by real distribution system of KEPCO(Korea Electric Power Corporation) which has 8 feeders and 140 buses.

This paper presents a restoration method by using Dijkstra algorithm for outage restoration problems in distribution system that considering load capacity constraints and operation constraints. Restoration problem in distribution system is difficult to solve problem in a short times, because of a distribution system that supplies power for customers combined with many tie-line switches and sectionalizing switches and have to satisfy plenty of operation conditions. Therefore, this paper applied Dijkstra algorithm which is satisfy radial operation conditions in distribution system. This proposed method used Kruskal algorithm include to Dijkstra algorithm Therefore, proposed method is restored to a outage sections in a short times and just then to satisfied with a operation conditions in distribution system. A 26-bus, 31-branch model system is used to demonstrate the effectiveness of the proposed method.

According to recent advances in technology, major robot technologies that have been developed and commercialized for industrial use are being applied to various fields in our everyday life such as guide robots and cleaning robots. Among them, the navigation based on the self localization has become an essential element technology of the robot. In the case of indoor environment, many high-priced sensors are used, which makes it difficult to activate the robot industry. In this paper, we propose a robotic platform and a moving algorithm that can travel by using Dijkstra algorithm. The proposed system can find a short route to the destination with its own position. Also, its performance is discussed through the experimentation of an actual robot.

본 연구는 산업현장에서 사용되는 이동로봇이 익숙하지 못한 환경에서 목적지에 도착할 수 있는 항법 알고리즘을 개발하고자 한다. 이를 위해 동적창 접근(DWA)과 Dijkstra 경로설정 알고리즘을 결합하여 항법 알고리즘을 제안한다. 이를 성능 비교하기 위해 로컬 동적창 접근(LDWA), 글로벌 동적창 접근(GDWA), 고속 탐색 랜덤 트리 (RRT) 알고리즘을 비교 분석한다. LDWA과 GDWA을 적용한 Dijkstra 알고리즘을 활용한 항법 알고리즘을 구현하여 제한된 정보를 이용하여 이동로봇이 목적지에 도달할 수 있도록 한다. 이 알고리즘들의 목적지에 도착할 때까지 걸리는 시간, 장애물 회피와 계산복잡도에 대한 비교 분석한다. 위 알고리즘의 한계를 극복하기 위한 새로운 항법 알고리즘을 제안하고 제시된 최적화된 항법 알고리즘의 산업현장에서의 활용 방안을 모색한다.

In this paper, we develop a new navigation algorithm for industrial mobile robots to arrive at the destination in unknown environment. To achieve this, we suggest a navigation algorithm that combines Dynamic Window Approach (DWA) and Dijkstra path planning algorithm. We compare Local Dynamic Window Approach (LDWA), Global Dynamic Window Approach(GDWA), Rapidly-exploring Random Tree (RRT) Algorithm. The navigation algorithm using Dijkstra algorithm combined with LDWA and GDWA makes mobile robots to reach the destination. and obstacles faced during the path planning process of LDWA and GDWA. Then, we compare on time taken to arrive at the destination, obstacle avoidance and computation complexity of each algorithm. To overcome the limitation, we seek ways to use the optimized navigation algorithm for industrial use.