• Title/Summary/Keyword: Time graph

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Prediction for Bicycle Demand using Spatial-Temporal Graph Models (시-공간 그래프 모델을 이용한 자전거 대여 예측)

  • Jangwoo Park
    • Journal of Internet of Things and Convergence
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    • v.9 no.6
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    • pp.111-117
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    • 2023
  • There is a lot of research on using a combination of graph neural networks and recurrent neural networks as a way to account for both temporal and spatial dependencies. In particular, graph neural networks are an emerging area of research. Seoul's bicycle rental service (aka Daereungi) has rental stations all over the city of Seoul, and the rental information at each station is a time series that is faithfully recorded. The rental information of each rental station has temporal characteristics that show periodicity over time, and regional characteristics are also thought to have important effects on the rental status. Regional correlations can be well understood using graph neural networks. In this study, we reconstructed the time series data of Seoul's bicycle rental service into a graph and developed a rental prediction model that combines a graph neural network and a recurrent neural network. We considered temporal characteristics such as periodicity over time, regional characteristics, and the degree importance of each rental station.

The Implementation of Graph-based SLAM Using General Graph Optimization (일반 그래프 최적화를 활용한 그래프 기반 SLAM 구현)

  • Ko, Nak-Yong;Chung, Jun-Hyuk;Jeong, Da-Bin
    • The Journal of the Korea institute of electronic communication sciences
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    • v.14 no.4
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    • pp.637-644
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    • 2019
  • This paper describes an implementation of a graph-based simultaneous localization and mapping(SLAM) method called the General Graph Optimization. The General Graph Optimization formulates the SLAM problem using nodes and edges. The nodes represent the location and attitude of a robot in time sequence, and the edge between the nodes depict the constraint between the nodes. The constraints are imposed by sensor measurements. The General Graph Optimization solves the problem by optimizing the performance index determined by the constraints. The implementation is verified using the measurement data sets which are open for test of various SLAM methods.

AN OPTIMAL PARALLEL ALGORITHM FOR SOLVING ALL-PAIRS SHORTEST PATHS PROBLEM ON CIRCULAR-ARC GRAPHS

  • SAHA ANITA;PAL MADHUMANGAL;PAL TAPAN K.
    • Journal of applied mathematics & informatics
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    • v.17 no.1_2_3
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    • pp.1-23
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    • 2005
  • The shortest-paths problem is a fundamental problem in graph theory and finds diverse applications in various fields. This is why shortest path algorithms have been designed more thoroughly than any other algorithm in graph theory. A large number of optimization problems are mathematically equivalent to the problem of finding shortest paths in a graph. The shortest-path between a pair of vertices is defined as the path with shortest length between the pair of vertices. The shortest path from one vertex to another often gives the best way to route a message between the vertices. This paper presents an $O(n^2)$ time sequential algorithm and an $O(n^2/p+logn)$ time parallel algorithm on EREW PRAM model for solving all pairs shortest paths problem on circular-arc graphs, where p and n represent respectively the number of processors and the number of vertices of the circular-arc graph.

Frequent Patterns Mining using only one-time Database Scan (한 번의 데이터베이스 탐색에 의한 빈발항목집합 탐색)

  • Chai, Duck-Jin;Jin, Long;Lee, Yong-Mi;Hwang, Bu-Hyun;Ryu, Keun-Ho
    • The KIPS Transactions:PartD
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    • v.15D no.1
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    • pp.15-22
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    • 2008
  • In this paper, we propose an efficient algorithm using only one-time database scan. The proposed algorithm creates the bipartite graph which indicates relationship of large items and transactions including the large items. And then we can find large itemsets using the bipartite graph. The bipartite graph is generated when database is scanned to find large items. We can't easily find transactions which include large items in the large database. In the bipartite graph, large items and transactions are linked each other. So, we can trace the transactions which include large items through the link information. Therefore the bipartite graph is a indexed database which indicates inclusion relationship of large items and transactions. We can fast find large itemsets because proposed method conducts only one-time database scan and scans indexed the bipartite graph. Also, it don't generate candidate itemsets.

AN EFFICIENT PRAM ALGORITHM FOR MAXIMUM-WEIGHT INDEPENDENT SET ON PERMUTATION GRAPHS

  • SAHA ANITA;PAL MADHUMANGAL;PAL TAPAN K.
    • Journal of applied mathematics & informatics
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    • v.19 no.1_2
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    • pp.77-92
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    • 2005
  • An efficient parallel algorithm is presented to find a maximum weight independent set of a permutation graph which takes O(log n) time using O($n^2$/ log n) processors on an EREW PRAM, provided the graph has at most O(n) maximal independent sets. The best known parallel algorithm takes O($log^2n$) time and O($n^3/log\;n$) processors on a CREW PRAM.

AN EFFICIENT ALGORITHM TO SOLVE CONNECTIVITY PROBLEM ON TRAPEZOID GRAPHS

  • Ghosh, Prabir K.;Pal, Madhumangal
    • Journal of applied mathematics & informatics
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    • v.24 no.1_2
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    • pp.141-154
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    • 2007
  • The connectivity problem is a fundamental problem in graph theory. The best known algorithm to solve the connectivity problem on general graphs with n vertices and m edges takes $O(K(G)mn^{1.5})$ time, where K(G) is the vertex connectivity of G. In this paper, an efficient algorithm is designed to solve vertex connectivity problem, which takes $O(n^2)$ time and O(n) space for a trapezoid graph.

Path Planning for Mobile Robots using Visibility Graph and Genetic Algorithms (가시도 그래프와 유전 알고리즘에 기초한 이동로봇의 경로계획)

  • 정연부;이민중;전향식;최영규
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.418-418
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    • 2000
  • This paper proposes a path planning algorithm for mobile robot. To generate an optimal path and minimum time path for a mobile robot, we use the Genetic Algorithm(GA) and Visibility Graph. After finding a minimum-distance between start and goal point, the path is revised to find the minimum time path by path-smoothing algorithm. Simulation results show that the proposed algorithms are more effective.

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A Study on the Mitigation of the Exposure Dose Applying Bolus Tracking in Brain Perfusion CT Scan (뇌 관류 CT검사에서 BolusTracking기법을 적용한 피폭선량 저감화에 관한 연구)

  • Kim, Ki-Jeong;Jung, Hong-Ryang;Lim, Cheong-Hwan;Hong, Dong-Hee;Shim, Jae-Goo;You, In-Gyu
    • Journal of Digital Convergence
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    • v.12 no.3
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    • pp.353-358
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    • 2014
  • This study was conducted to analyze the patient's exposed dose targeting the patients who had acute ischemic stroke symptoms and CT brain perfusion scan, by comparing fixed time technique and bolus tracking technique which was provided by the manufacturer and to identify the Time graph to implement the usability of contrast medium's tracking technique the best contrast enhancement intervals. $CTDI_{VOL}$ of PCT in patient appeared to be 431.72mGy in fixed scan delay protocol, whereas 323.61mGy in Bolus tracking technique. The value of DLP appeared to be $1243.47mGy{\cdot}cm$ in fixed scan delay protocol, whereas $932mGy{\cdot}cm$ in Bolus tracking technique. Time graph appeared to be various in fixed scan delay protocol, whereas the optimal time graph could be obtained in Bolus tracking. The exposure dose could be reduced by 25% applying Bolus tracking technique when taking brain perfusion CT scan.

Automatic decomposition of unstructured meshes employing genetic algorithms for parallel FEM computations

  • Rama Mohan Rao, A.;Appa Rao, T.V.S.R.;Dattaguru, B.
    • Structural Engineering and Mechanics
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    • v.14 no.6
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    • pp.625-647
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    • 2002
  • Parallel execution of computational mechanics codes requires efficient mesh-partitioning techniques. These mesh-partitioning techniques divide the mesh into specified number of submeshes of approximately the same size and at the same time, minimise the interface nodes of the submeshes. This paper describes a new mesh partitioning technique, employing Genetic Algorithms. The proposed algorithm operates on the deduced graph (dual or nodal graph) of the given finite element mesh rather than directly on the mesh itself. The algorithm works by first constructing a coarse graph approximation using an automatic graph coarsening method. The coarse graph is partitioned and the results are interpolated onto the original graph to initialise an optimisation of the graph partition problem. In practice, hierarchy of (usually more than two) graphs are used to obtain the final graph partition. The proposed partitioning algorithm is applied to graphs derived from unstructured finite element meshes describing practical engineering problems and also several example graphs related to finite element meshes given in the literature. The test results indicate that the proposed GA based graph partitioning algorithm generates high quality partitions and are superior to spectral and multilevel graph partitioning algorithms.

Modeling and Scheduling of Cyclic Shops with Time Window Constraints

  • Seo, Jeong-Won;Lee, Tae-Eog
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2000.10a
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    • pp.161-164
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    • 2000
  • A cyclic shop is a production system that repeatedly produces identical sets of jobs, called minimal part sets, in the same loading and processing sequence. We consider a version of cyclic shop where the operations are processed and unloaded within time limits, so called a time window. We model the shop using an event graph model, a class of Petri nets. To represent the time window constraint, we introduce places with negative time delays. From the shop modeling graph, we develop a linear system model based on the max- plus algebra and characterize the conditions on the existence of a stable schedule.

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