• Title/Summary/Keyword: graph structure

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ON FINITE GROUPS WITH THE SAME ORDER TYPE AS SIMPLE GROUPS F4(q) WITH q EVEN

  • Daneshkhah, Ashraf;Moameri, Fatemeh;Mosaed, Hosein Parvizi
    • Bulletin of the Korean Mathematical Society
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    • v.58 no.4
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    • pp.1031-1038
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    • 2021
  • The main aim of this article is to study quantitative structure of finite simple exceptional groups F4(2n) with n > 1. Here, we prove that the finite simple exceptional groups F4(2n), where 24n + 1 is a prime number with n > 1 a power of 2, can be uniquely determined by their orders and the set of the number of elements with the same order. In conclusion, we give a positive answer to J. G. Thompson's problem for finite simple exceptional groups F4(2n).

On-Line Recongnition of Handwritten Hangeul by Structure Analysis (구조해석에 의한 필기체 한글의 온라인 인식)

  • Hong, Sung Min;Kim, Eun Won;Park, Chong Kug;Cho, Won Kyung
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.23 no.1
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    • pp.114-119
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    • 1986
  • In this paper, an algorithm for the on-line recognition of handwritten Hangeul is proposed. The strokes are recognized by the minimum distance parser. The phonemes are separated by the finite-state automata resulted from the state graph of phonemes which are produced by the order of strokes. By simulation result for 3,000 characteristics in practical sentences, the recognition rate of strokes is obtained to be 98.5% and the separation rate of phonemes is obtained to be 92.5%.

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Locally weighted linear regression prefetching method for hybrid memory system (하이브리드 메모리 시스템의 지역 가중 선형회귀 프리페치 방법)

  • Tang, Qian;Kim, Jeong-Geun;Kim, Shin-Dug
    • Proceedings of the Korea Information Processing Society Conference
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    • 2020.11a
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    • pp.12-15
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    • 2020
  • Data access characteristics can directly affect the efficiency of the system execution. This research is to design an accurate predictor by using historical memory access information, where highly accessible data can be migrated from low-speed storage (SSD/HHD) to high-speed memory (Memory/CPU Cache) in advance, thereby reducing data access latency and further improving overall performance. For this goal, we design a locally weighted linear regression prefetch scheme to cope with irregular access patterns in large graph processing applications for a DARM-PCM hybrid memory structure. By analyzing the testing result, the appropriate structural parameters can be selected, which greatly improves the cache prefetching performance, resulting in overall performance improvement.

Reconstruction of Collagen Using Tensor-Voting & Graph-Cuts

  • Park, Doyoung
    • Journal of Advanced Information Technology and Convergence
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    • v.9 no.1
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    • pp.89-102
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    • 2019
  • Collagen can be used in building artificial skin replacements for treatment of burns and towards the reconstruction of bone as well as researching cell behavior and cellular interaction. The strength of collagen in connective tissue rests on the characteristics of collagen fibers. 3D confocal imaging of collagen fibers enables the characterization of their spatial distribution as related to their function. However, the image stacks acquired with confocal laser-scanning microscope does not clearly show the collagen architecture in 3D. Therefore, we developed a new method to reconstruct, visualize and characterize collagen fibers from fluorescence confocal images. First, we exploit the tensor voting framework to extract sparse reliable information about collagen structure in a 3D image and therefore denoise and filter the acquired image stack. We then propose to segment the collagen fibers by defining an energy term based on the Hessian matrix. This energy term is minimized by a min cut-max flow algorithm that allows adaptive regularization. We demonstrate the efficacy of our methods by visualizing reconstructed collagen from specific 3D image stack.

FPGA Mapping Incorporated with Multiplexer Tree Synthesis (멀티플렉서 트리 합성이 통합된 FPGA 매핑)

  • Kim, Kyosun
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.4
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    • pp.37-47
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    • 2016
  • The practical constraints on the commercial FPGAs which contain dedicated wide function multiplexers in their slice structure are incorporated with one of the most advanced FPGA mapping algorithms based on the AIG (And-Inverter Graph), one of the best logic representations in academia. As the first step of the mapping process, cuts are enumerated as intermediate structures. And then, the cuts which can be mapped to the multiplexers are recognized. Without any increased complexity, the delay and area of multiplexers as well as LUTs are calculated after checking the requirements for the tree construction such as symmetry and depth limit against dynamically changing mapping of neighboring nodes. Besides, the root positions of multiplexer trees are identified from the RTL code, and annotated to the AIG as AOs (Auxiliary Outputs). A new AIG embedding the multiplexer tree structures which are intentionally synthesized by Shannon expansion at the AOs, is overlapped with the optimized AIG. The lossless synthesis technique which employs FRAIG (Functionally Reduced AIG) is applied to this approach. The proposed approach and techniques are validated by implementing and applying them to two RISC processor examples, which yielded 13~30% area reduction, and up to 32% delay reduction. The research will be extended to take into account the constraints on the dedicated hardware for carry chains.

A Parameter-Free Approach for Clustering and Outlier Detection in Image Databases (이미지 데이터베이스에서 매개변수를 필요로 하지 않는 클러스터링 및 아웃라이어 검출 방법)

  • Oh, Hyun-Kyo;Yoon, Seok-Ho;Kim, Sang-Wook
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.1
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    • pp.80-91
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    • 2010
  • As the volume of image data increases dramatically, its good organization of image data is crucial for efficient image retrieval. Clustering is a typical way of organizing image data. However, traditional clustering methods have a difficulty of requiring a user to provide the number of clusters as a parameter before clustering. In this paper, we discuss an approach for clustering image data that does not require the parameter. Basically, the proposed approach is based on Cross-Association that finds a structure or patterns hidden in data using the relationship between individual objects. In order to apply Cross-Association to clustering of image data, we convert the image data into a graph first. Then, we perform Cross-Association on the graph thus obtained and interpret the results in the clustering perspective. We also propose the method of hierarchical clustering and the method of outlier detection based on Cross-Association. By performing a series of experiments, we verify the effectiveness of the proposed approach. Finally, we discuss the finding of a good value of k used in k-nearest neighbor search and also compare the clustering results with symmetric and asymmetric ways used in building a graph.

A Study on Optimal Location Selection and Analytic Method of Landmark Element in terms of Visual Perception (시각적 측면에서 랜드마크 요소의 최적입지선정 분석방법에 관한 연구)

  • Kim, Suk-Tae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.16 no.9
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    • pp.6360-6367
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    • 2015
  • The location selection of the element that should guarantee easy visual perception, like the landmark, is the a topic that appears much in the design process. Recently, a graph analysis technique using computers has been applied in order to evaluate the visibility of the visual element, but the analytic frame is flat and the setting of the visual pont and the matrix are fixed so there were great limitations in obtaining the results of the practical analysis. Thus, this study presented Nondirectional Multi-Dimensional Calculation (MDVC-N), an analytic methodology available for the analysis of the dynamic visual point in the 3D environment. It thus attempted to establish the analytic application using the 3D computer graphics technology and designed a script structure to set the visual point and the matrix. In addition to that, this study tried to verify the analytic methodology by applying the complex land as an example model, where buildings in various heights of terrains with a high-differences are located, verifying the same analytic methodology. It thus tried to identify the visual characteristics of each alternative location. The following results were gained from the study. 1) The visibility can be measured quantitatively trough the application of the 6-alternatives. 2) Using the 3dimensional graph, intuitive analysis was possible. 3) It attempted to improve the analytic applicability by calculating the results corrected as a variable behavior from the local integration variable of the space syntax.

An Effective Method for Comparing Control Flow Graphs through Edge Extension (에지 확장을 통한 제어 흐름 그래프의 효과적인 비교 방법)

  • Lim, Hyun-Il
    • KIPS Transactions on Computer and Communication Systems
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    • v.2 no.8
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    • pp.317-326
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    • 2013
  • In this paper, we present an effective method for comparing control flow graphs which represent static structures of binary programs. To compare control flow graphs, we measure similarities by comparing instructions and syntactic information contained in basic blocks. In addition, we also consider similarities of edges, which represent control flows between basic blocks, by edge extension. Based on the comparison results of basic blocks and edges, we match most similar basic blocks in two control flow graphs, and then calculate the similarity between control flow graphs. We evaluate the proposed edge extension method in real world Java programs with respect to structural similarities of their control flow graphs. To compare the performance of the proposed method, we also performed experiments with a previous structural comparison for control flow graphs. From the experimental results, the proposed method is evaluated to have enough distinction ability between control flow graphs which have different structural characteristics. Although the method takes more time than previous method, it is evaluated to be more resilient than previous method in comparing control flow graphs which have similar structural characteristics. Control flow graph can be effectively used in program analysis and understanding, and the proposed method is expected to be applied to various areas, such as code optimization, detection of similar code, and detection of code plagiarism.

Auto Exposure Control System using Variable Time Constants (가변 시상수를 이용한 자동 노출제어 시스템)

  • Kim, Hyun-Sik;Lee, Sung-Mok;Jang, Won-Woo;Ha, Joo-Young;Kim, Joo-Hyun;Kang, Bong-Soon;Lee, Gi-Dong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.2
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    • pp.257-264
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    • 2007
  • In order to obtain a fine picture, a camera has many convenient functions. Its representative functions are Auto Focus(AF), Auto White Balance(AWB) and Auto Exposure(AE). In this paper, we present the new algorithm of Auto Exposure control system, one of its useful functions The proposed algorithm of Auto Exposure control system is based on IIR Filter with Variable Time Constant. First, in order to establish the standards of exposure control, we compare change of the picture luminance with luminance of an object in the Zone system. Second, we make an ideal characteristic graph of luminance by using the results. Finally, we can find the value of the right exposure by comparing an ideal characteristic graph of the luminance with the value of the current expose of a scene. We can find an appropriate exposure as comparing the ideal characteristic graph of the luminance with current exposure of a scene. In order to find a suitable exposure state, we make use of IIR Filter instead of a conventional method using micro-controller. In this paper, the proposed system has therefore simple structure, we use it for compact image sensor module used in the handheld device.

A Ranking Algorithm for Semantic Web Resources: A Class-oriented Approach (시맨틱 웹 자원의 랭킹을 위한 알고리즘: 클래스중심 접근방법)

  • Rho, Sang-Kyu;Park, Hyun-Jung;Park, Jin-Soo
    • Asia pacific journal of information systems
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    • v.17 no.4
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    • pp.31-59
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    • 2007
  • We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.