• Title/Summary/Keyword: Dijkstra

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An Energy Efficient Intelligent Method for Sensor Node Selection to Improve the Data Reliability in Internet of Things Networks

  • Remesh Babu, KR;Preetha, KG;Saritha, S;Rinil, KR
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.9
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    • pp.3151-3168
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    • 2021
  • Internet of Things (IoT) connects several objects with embedded sensors and they are capable of exchanging information between devices to create a smart environment. IoT smart devices have limited resources, such as batteries, computing power, and bandwidth, but comprehensive sensing causes severe energy restrictions, lowering data quality. The main objective of the proposal is to build a hybrid protocol which provides high data quality and reduced energy consumption in IoT sensor network. The hybrid protocol gives a flexible and complete solution for sensor selection problem. It selects a subset of active sensor nodes in the network which will increase the data quality and optimize the energy consumption. Since the unused sensor nodes switch off during the sensing phase, the energy consumption is greatly reduced. The hybrid protocol uses Dijkstra's algorithm for determining the shortest path for sensing data and Ant colony inspired variable path selection algorithm for selecting active nodes in the network. The missing data due to inactive sensor nodes is reconstructed using enhanced belief propagation algorithm. The proposed hybrid method is evaluated using real sensor data and the demonstrated results show significant improvement in energy consumption, data utility and data reconstruction rate compared to other existing methods.

A study on ITZ percolation threshold in mortar with ellipsoidal aggregate particles

  • Pan, Zichao;Wang, Dalei;Ma, Rujin;Chen, Airong
    • Computers and Concrete
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    • v.22 no.6
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    • pp.551-561
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    • 2018
  • The percolation of interfacial transition zone (ITZ) in cementitious materials is of great importance to the transport properties and durability issues. This paper presents numerical simulation research on the ITZ percolation threshold of mortar specimens at meso-scale. To simulate the meso-scale model of mortar as realistically as possible, the aggregates are simplified as ellipsoids with arbitrary orientations. Major and minor aspect ratios are defined to represent the global shape characteristics of aggregates. Some algorithms such as the burning algorithm, Dijkstra's algorithm and Connected-Component Labeling (CCL) algorithm are adopted for identification of connected ITZ clusters and percolation detection. The effects of gradation and aspect ratios of aggregates on ITZ percolation threshold are quantitatively studied. The results show that (1) the ITZ percolation threshold is mainly affected by the specific surface area (SSA) of aggregates and shows a global decreasing tendency with an increasing SSA; (2) elongated ellipsoidal particles can effectively bridge isolated ITZ clusters and thus lower the ITZ percolation threshold; (3) as ITZ volume fraction increases, the bridging effect of elongated particles will be less significant, and has only a minor effect on ITZ percolation threshold; (4) it is the ITZ connectivity that is essentially responsible for ITZ percolation threshold, while other factors such as SSA and ITZ volume fraction are only the superficial reasons.

A Development of Optimal Travel Course Recommendation System based on Altered TSP and Elasticsearch Algorithm (변형된 TSP 및 엘라스틱서치 알고리즘 기반의 최적 여행지 코스 추천 시스템 개발)

  • Kim, Jun-Yeong;Jo, Kyeong-Ho;Park, Jun;Jung, Se-Hoon;Sim, Chun-Bo
    • Journal of Korea Multimedia Society
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    • v.22 no.9
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    • pp.1108-1121
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    • 2019
  • As the quality and level of life rise, many people are doing search for various pieces of information about tourism. In addition, users prefer the search methods reflecting individual opinions such as SNS and blogs to the official websites of tourist destination. Many of previous studies focused on a recommendation system for tourist courses based on the GPS information and past travel records of users, but such a system was not capable of recommending the latest tourist trends. This study thus set out to collect and analyze the latest SNS data to recommend tourist destination of high interest among users. It also aimed to propose an altered TSP algorithm to recommend the optimal routes to the recommended destination within an area and a system to recommend the optimal tourist courses by applying the Elasticsearch engine. The altered TSP algorithm proposed in the study used the location information of users instead of Dijkstra's algorithm technique used in previous studies to select a certain tourist destination and allowed users to check the recommended courses for the entire tourist destination within an area, thus offering more diverse tourist destination recommendations than previous studies.

Faster pipe auto-routing using improved jump point search

  • Min, Jwa-Geun;Ruy, Won-Sun;Park, Chul Su
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.12 no.1
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    • pp.596-604
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    • 2020
  • Previous studies on pipe auto-routing algorithms generally used such algorithms as A*, Dijkstra, Genetic Algorithm, Particle Swarm Optimization, and Ant Colony Optimization, to satisfy the relevant constraints of its own field and improve the output quality. On the other hand, this study aimed to significantly improve path-finding speed by applying the Jump Point Search (JPS) algorithm, which requires lower search cost than the abovementioned algorithms, for pipe routing. The existing JPS, however, is limited to two-dimensional spaces and can only find the shortest path. Thus, it requires several improvements to be applied to pipe routing. Pipe routing is performed in a three-dimensional space, and the path of piping must be parallel to the axis to minimize its interference with other facilities. In addition, the number of elbows must be reduced to the maximum from an economic perspective, and preferred spaces in the path must also be included. The existing JPS was improved for the pipe routing problem such that it can consider the above-mentioned problem. The fast path-finding speed of the proposed algorithm was verified by comparing it with the conventional A* algorithm in terms of resolution.

RFID-based Shortest Time Algorithm Line Tracer (RFID 기반 최단시간 알고리즘 라인트레이서)

  • Cheol-Min, Kim;Hee-Young, Cho;Tae-Sung, Yun;Ho-Jun, Shin;Hyoung-Keun, Park
    • The Journal of the Korea institute of electronic communication sciences
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    • v.17 no.6
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    • pp.1221-1228
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    • 2022
  • With the development of modern technology, the use of unmanned automation equipment that can replace humans in logistics and industrial sites is increasing. The technology of one such automation facility, the Unmanned Carrier (AGV), includes Line Tracing, which allows you to recognize a line through infrared sensors and drive a predetermined route. In this paper, the shortest time algorithm using Arduino is configured in the line tracing technology to enable efficient driving. It is also designed to collect location and time information using RFID tags.

Optimal route generation method for ships using reinforcement learning (강화학습을 이용한 선박의 최적항로 생성기법)

  • Min-Kyu Kim;Jong-Hwa Kim;Ik-Soon Choi;Hyeong-Tak Lee;Hyun Yang
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.167-168
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    • 2022
  • 선박을 운항함에 있어 최적항로를 결정하는 것은 항해시간과 연료 소모를 줄이는 중요한 요인 중의 하나이다. 기존에는 항로를 결정하기 위해 항해사의 전문적인 지식이 요구되지만 이러한 방법은 최적의 항로라고 판단하기 어렵다. 따라서 연료비 절감과 선박의 안전을 고려한 최적의 항로를 생성할 필요가 있다. 연료 소모량 혹은 항해시간을 최소화하기 위해서 에이스타 알고리즘, Dijkstra 알고리즘을 적용한 연구가 있다. 하지만 이러한 연구들은 최단거리만 구할 뿐 선박의 안전, 해상상태 등을 고려하지 못한다. 이를 보완하기 위해 본 연구에서는 강화학습 알고리즘을 적용하고자한다. 강화학습 알고리즘은 앞으로 누적 될 보상을 최대화 하는 행동으로 정책을 찾는 방법으로, 본 연구에서는 강화학습 알고리즘의 하나인 Q-learning을 사용하여 선박의 안전을 고려한 최적의 항로를 생성하는 기법을 제안 하고자 한다.

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Optimal Route Generation of Ships using Navigation Chart Information (해도 정보를 이용한 선박의 최적 항로 생성)

  • Min-Kyu Kim;Jong-Hwa Kim;Hyun Yang
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.11a
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    • pp.369-370
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    • 2022
  • 최근 자율 운항 선박에 대한 관심이 높아지고 있다. 특히, MUNIN (Maritime Unmanned Navigation through Intelligence in Networks) 프로젝트를 계기로 자율 운항 선박에 대한 개발과 연구가 활발히 진행되고 있다. 또한 국제해사기구 IMO는 자율 운항 선박 시대에 대응하기 위해 자율 선박을 MASS (Maritime Autonomous Surface Ship)라 정의하고 선박 자율화 정도에 따라 4단계 등급을 제시하고 있다. 완전한 자율 운항 선박에 대한 요구조건을 만족하기 위해서는 항로 결정과 제어기술이 필수적이다. 본 연구에서는 여러 가지 기술 중 선박의 최적경로를 생성하는 기법을 다룬다. 기존에 최적항로를 생성하기 위한 방법으로는 A*, Dijkstra와 같은 알고리즘들이 주로 사용되었다. 그러나 이와 같은 알고리즘은 섬이나 육지에 대한 충돌 회피는 고려하고 있지만 수심 및 연안 선박에 대한 규정들은 고려하지 않고 있어 실제로 적용하기에는 한계점이 있다. 따라서 본 연구에서는 안전을 위해 선박의 선저 여유 수심과, 해도에 규정되어 있는 선박 운항에 대한 여러 규정들을 반영하여 최적 항로를 생성하고자 한다. 최적 항로를 생성하기 위한 알고리즘으로는 강화학습 기반의 Q-learning 알고리즘을 적용하였다.

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Route Optimization for Energy-Efficient Path Planning in Smart Factory Autonomous Mobile Robot (스마트 팩토리 모빌리티 에너지 효율을 위한 경로 최적화에 관한 연구)

  • Dong Hui Eom;Dong Wook Cho;Seong Ju Kim;Sang Hyeon Park;Sung Ho Hwang
    • Journal of Drive and Control
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    • v.21 no.1
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    • pp.46-52
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    • 2024
  • The advancement of autonomous driving technology has heightened the importance of Autonomous Mobile Robotics (AMR) within smart factories. Notably, in tasks involving the transportation of heavy objects, the consideration of weight in route optimization and path planning has become crucial. There is ongoing research on local path planning, such as Dijkstra, A*, and RRT*, focusing on minimizing travel time and distance within smart factory warehouses. Additionally, there are ongoing simultaneous studies on route optimization, including TSP algorithms for various path explorations and on minimizing energy consumption in mobile robotics operations. However, previous studies have often overlooked the weight of the objects being transported, emphasizing only minimal travel time or distance. Therefore, this research proposes route planning that accounts for the maximum payload capacity of mobile robotics and offers load-optimized path planning for multi-destination transportation. Considering the load, a genetic algorithm with the objectives of minimizing both travel time and distance, as well as energy consumption is employed. This approach is expected to enhance the efficiency of mobility within smart factories.

An Implementation of Method to Determine Search Space of Hierarchical Path Algorithm for Finding Optimal Path (최적 경로 탐색을 위한 계층 경로 알고리즘의 탐색 영역 결정 기법의 구현)

  • Lee, Hyoun-Sup;Yun, Sang-Du;Kim, Jin-Deog
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.05a
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    • pp.835-838
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    • 2008
  • Many researches on hierarchical path search have been studied so far. Even though partitioning regions is essential part, the researches are not enough. This paper proposes two efficient methods to partition regions: 1)a method based on voronoi algorithm in which a major node is central point of a region, 2) a method based on fired grid that partitions regions into major and minor. The performances of the proposed methods are compared with the conventional hierarchical path search method in which a region is formed by the boundary line of nearest 4 points of a major node in terms of the path search time and the accuracy. The results obtained from the experiments show that the method based on voronoi achieves short execution time and the method based grid achieves high accuracy.

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Development and Evaluation of Real-time Travel Time Forecasting Model: Nonparametric Regression Analysis for the Seoul Transit System (비모수 회귀분석을 이용한 실시간 통행시간 예측 기법 개발 및 평가 (서울시 버스를 중심으로))

  • Park, Sin-Hyeong;Jeong, Yeon-Jeong;Kim, Chang-Ho
    • Journal of Korean Society of Transportation
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    • v.24 no.1 s.87
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    • pp.109-120
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    • 2006
  • Since the 1st of July, 2004, the public transport system of the Seoul metropolitan area has been rearranged. In the new system, bus lines are divided into 4 classes-wide area, arterial road, branch, and rotation lines with renewed fare system based on the total distance travelled. Since central control center known as the Bus Management System (BMS) integrates the entire system operation. it now becomes feasible to collect travel information and provide it to the users scientifically and systematically. The Purpose of this study is to forecast transit travel time using real-time traffic data coming from both buses and subway. This is significant contribution since provision of real-time transit information and easy access to it would most likely boost the use of mass transit system, alleviating roadway congestion in the metropolitan area.