• Title/Summary/Keyword: Depth-First Search

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Android Application for Connecting Cycling Routes on Strava Segments

  • Mulasastra, Intiraporn;Kao-ian, Wichpong
    • Journal of information and communication convergence engineering
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    • v.17 no.2
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    • pp.142-148
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    • 2019
  • Relatively few countries provide separate bicycle lanes for cyclists. Hence, tools for suggesting cycling routes are essential for a safe and pleasant cycling experience. This study aims to develop a mobile application to build cycling routes based on user preferences, specifically location, search radius, ride distance, and number of optimal routes. Our application calls the Strava API to retrieve Strava cycling segments crowdsourced from the cycling community. Then, it creates a graph consisting of the start and end points of these segments. Beginning from a user-specified location, the depth-first search algorithm (DFS) is applied to find routes that conform to the user's preferences. Next, a set of optimal routes is obtained by computing a trade-off ratio for every discovered route. This ratio is calculated from the lengths of all segments and the lengths of all connecting paths. The connected routes can be displayed on a map on an Android device or exported as a GPX file to a bike computer. Future work must be performed to improve the design of the user interface and user experience.

Location Estimation for Multiple Targets Using Expanded DFS Algorithm (확장된 깊이-우선 탐색 알고리듬을 적용한 다중표적 위치 좌표 추정 기법)

  • Park, So Ryoung;Noh, Sanguk
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38C no.12
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    • pp.1207-1215
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    • 2013
  • This paper proposes the location estimation techniques of distributed targets with the multi-sensor data perceived through IR sensors of the military robots in consideration of obstacles. In order to match up targets with measured azimuths, to add to the depth-first search (DFS) algorithms in free-obstacle environment, we suggest the expanded DFS (EDS) algorithm including bypass path search, partial path search, middle level ending, and the supplementation of decision metric. After matching up targets with azimuths, we estimate the coordinate of each target by obtaining the intersection point of the azimuths with the least square error (LSE) algorithm. The experimental results show the error rate of estimated location, mean number of calculating nodes, and mean distance between real coordinates and estimated coordinates of the proposed algorithms.

Study on Inference and Search for Development of Diagnostic Ontology in Oriental Medicine (한의진단 Ontology 구축을 위한 추론과 탐색에 관한 연구)

  • Park, Jong-Hyun
    • Journal of Physiology & Pathology in Korean Medicine
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    • v.23 no.4
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    • pp.745-750
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    • 2009
  • The goal of this study is to examine on reasoning and search for construction of diagnosis ontology as a knowledge base of diagnosis expert system in oriental medicine. Expert system is a field of artificial intelligence. It is a system to acquire information with diverse reasoning methods after putting expert's knowledge in computer systematically. A typical model of expert system consists of knowledge base and reasoning & explanatory structure offering conclusion with the knowledge. To apply ontology as knowledge base to expert system practically, consideration on reasoning and search should be together. Therefore, this study compared and examined reasoning, search with diagnosis process in oriental medicine. Reasoning is divided into Rule-based reasoning and Case-based reasoning. The former is divided into Forward chaining and Backward chaining. Because of characteristics of diagnosis, sometimes Forward chaining or backward chaining are required. Therefore, there are a lot of cases that Hybrid chaining is effective. Case-based reasoning is a method to settle a problem in the present by comparing with the past cases. Therefore, it is suitable to diagnosis fields with abundant cases. Search is sorted into Breadth-first search, Depth-first search and Best-first search, which have respectively merits and demerits. To construct diagnosis ontology to be applied to practical expert system, reasoning and search to reflect diagnosis process and characteristics should be considered.

The Effect of External Knowledge Search on Innovation Speed: Focusing on the Moderation Effect of Export Performance (외부지식탐색이 혁신속도에 미치는 영향: 수출성과의 조절효과를 중심으로)

  • Roh, Taewoo
    • Journal of Digital Convergence
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    • v.16 no.2
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    • pp.93-102
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    • 2018
  • This study suggests external knowledge search as a way of creating knowledge and efforts for reaching out to the innovation and examines the relationship between innovation speed and the breadth and depth of external knowledge search. As a part of efforts to overcome the limitations of the routines of external knowledge search in the domestic market, the efforts of a firm to enter the foreign market have been examined with a moderate effect. Although previous research focused on exploration of external knowledge that is mostly effected in single country or similar industry, this study expands it by introducing the concept of market expansion and empirically inspect the interaction effect. 818 valid samples used in this study are based on the innovation survey published by STEPI and empirical results are as follows. First, the breadth and depth of external knowledge search have a positive impact on innovation speed. Second, export performance as the effect of expanding the market has a moderating effect on the speed of innovation. Third, younger companies prefer various networks while older companies prefer depth networks in order to increase the speed.

Configurations of Knowledge Search in Knowledge-Intensive Industries (지식기반산업에서 기업의 지식탐색 유형: 구성형태적 접근)

  • Huh, Moon-Goo;Lee, Jaegun
    • Journal of Technology Innovation
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    • v.25 no.3
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    • pp.299-331
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    • 2017
  • This research details firm knowledge search types based on the locus and features for Korean firms in the knowledge-based industry, and then analyzes differences in innovation performance according to the types from the view of a configurational approach. Existing research has mainly concentrated on establishing a relation between knowledge search and outcome variables. Consequently, firms have relatively insufficient understanding of how to systematize knowledge search. Hence, this research classifies knowledge search into four dimensions-external search breadth, external search depth, internal search breadth, and internal search depth-by the locus and features of search. Furthermore, the research draws actual types of knowledge search of firms and analyzes differences in innovation performance. The main result of the research is as follows. First, the research reasons out six clusters of firms which have a dissimilar knowledge search type. Each cluster shows differences while participating in every dimension of knowledge search or few dimensions. Second, as for innovation performance, each cluster shows different exploitative and exploratory innovation performance according to their knowledge search type. This research applies a configurational approach while existing research applied a reductionistic approach, thereby establishing the major contribution which enables us to study a phenomenon as it comes, not to analyze variables and relationships of variables. Lastly, the research suggests a future direction of research based on the result of this research.

A New merging Algorithm for Constructing suffix Trees for Integer Alphabets (정수 문자집합상의 접미사트리 구축을 위한 새로운 합병 알고리즘)

  • Kim, Dong-Kyu;Sim, Jeong-Seop;Park, Kun-Soo
    • Journal of KIISE:Computer Systems and Theory
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    • v.29 no.2
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    • pp.87-93
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    • 2002
  • A new approach of constructing a suffix tree $T_s$for the given string S is to construct recursively a suffix tree $ T_0$ for odd positions construct a suffix tree $T_e$ for even positions from $ T_o$ and then merge $ T_o$ and $T_e$ into $T_s$ To construct suffix trees for integer alphabets in linear time had been a major open problem on index data structures. Farach used this approach and gave the first linear-time algorithm for integer alphabets The hardest part of Farachs algorithm is the merging step. In this paper we present a new and simpler merging algorithm based on a coupled BFS (breadth-first search) Our merging algorithm is more intuitive than Farachs coupled DFS (depth-first search ) merging and thus it can be easily extended to other applications.

Real-time Graph Search for Space Exploration (공간 탐사를 위한 실시간 그래프 탐색)

  • Choi, Eun-Mi;Kim, In-Cheol
    • Journal of Intelligence and Information Systems
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    • v.11 no.1
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    • pp.153-167
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    • 2005
  • In this paper, we consider the problem of exploring unknown environments with a mobile robot or an autonomous character agent. Traditionally, research efforts to address the space exploration problem havefocused on the graph-based space representations and the graph search algorithms. Recently EXPLORE, one of the most efficient search algorithms, has been discovered. It traverses at most min$min(mn, d^2+m)$ edges where d is the deficiency of a edges and n is the number of edges and n is the number of vertices. In this paper, we propose DFS-RTA* and DFS-PHA*, two real-time graph search algorithms for directing an autonomous agent to explore in an unknown space. These algorithms are all built upon the simple depth-first search (DFS) like EXPLORE. However, they adopt different real-time shortest path-finding methods for fast backtracking to the latest node, RTA* and PHA*, respectively. Through some experiments using Unreal Tournament, a 3D online game environment, and KGBot, an intelligent character agent, we analyze completeness and efficiency of two algorithms.

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Search for the Efficient Hierarchical Data Structure in Mobile Screen (모바일 화면에서의 효율적인 메뉴구조 - 유목의 명확성, 깊이수준, 아이템의 수, 공간단서를 중심으로)

  • Cho, Kyung-Ja;Choi, Hyang;Han, Kwang-Hee
    • Korean Journal of Cognitive Science
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    • v.18 no.2
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    • pp.193-221
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    • 2007
  • This study explored the efficient hierarchical data structure of mobile interfaces. The first experiment demonstrated the effects of grouping(clear/unclear), depth level(2/3/5), and the number of items(32/64/128) on the search time and the number of errors. The results indicated that participants spent less time and made fewer errors to perform the task when the clear mobile interfaces, low depth level, and fewer items were provided. In addition, the results indicated that there were no effects of the depth level and the number of items on the search time and number of errors in clear mobile interfaces conditions. As depth level and the number of items changed, on the other hand, participants spent longer time to complete the task and made more mistakes in unclear mobile interfaces conditions. The second experiment investigated the effects of grouping(clear/unclear), the number of items(32/64/128), and spacial cues(colors/ windows/ number of cues) on search time and the number of errors in hierarchical data structures which had five depth levels. The results indicated that participants spent less time to complete the task and made less errors in a mobile interface when grouping is clear and the number of items are fewer. The results were identical with the first experiments. In addition, the main effect of spacial cues indicated that providing spacial cues via pictures and numbers can be helpful to reduce errors in search behaviors.

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MOTION VECTOR DETECTION ALGORITHM USING THE STEEPEST DESCENT METHOD EFFECTIVE FOR AVOIDING LOCAL SOLUTIONS

  • Konno, Yoshinori;Kasezawa, Tadashi
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.460-465
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    • 2009
  • This paper presents a new algorithm that includes a mechanism to avoid local solutions in a motion vector detection method that uses the steepest descent method. Two different implementations of the algorithm are demonstrated using two major search methods for tree structures, depth first search and breadth first search. Furthermore, it is shown that by avoiding local solutions, both of these implementations are able to obtain smaller prediction errors compared to conventional motion vector detection methods using the steepest descent method, and are able to perform motion vector detection within an arbitrary upper limit on the number of computations. The effects that differences in the search order have on the effectiveness of avoiding local solutions are also presented.

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A Flexible Branch and Bound Method for the Job Shop Scheduling Problem

  • Morikawa, Katsumi;Takahashi, Katsuhiko
    • Industrial Engineering and Management Systems
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    • v.8 no.4
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    • pp.239-246
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    • 2009
  • This paper deals with the makespan minimization problem of job shops. The problem is known as one of hard problems to optimize, and therefore, many heuristic methods have been proposed by many researchers. The aim of this study is also to propose a heuristic scheduling method for the problem. However, the difference between the proposed method and many other heuristics is that the proposed method is based on depth-first branch and bound, and thus it is possible to find an optimal solution at least in principle. To accelerate the search, when a node is judged hopeless in the search tree, the proposed flexible branch and bound method can indicate a higher backtracking node. The unexplored nodes are stored and may be explored later to realize the strict optimization. Two methods are proposed to generate the backtracking point based on the critical path of the current best feasible schedule, and the minimum lower bound for the makespan in the unexplored sub-problems. Schedules are generated based on Giffler and Thompson's active schedule generation algorithm. Acceleration of the search by the flexible branch and bound is confirmed by numerical experiment.