• Title/Summary/Keyword: 유사성 탐색

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Optimized Bankruptcy Prediction through Combining SVM with Fuzzy Theory (퍼지이론과 SVM 결합을 통한 기업부도예측 최적화)

  • Choi, So-Yun;Ahn, Hyun-Chul
    • Journal of Digital Convergence
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    • v.13 no.3
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    • pp.155-165
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    • 2015
  • Bankruptcy prediction has been one of the important research topics in finance since 1960s. In Korea, it has gotten attention from researchers since IMF crisis in 1998. This study aims at proposing a novel model for better bankruptcy prediction by converging three techniques - support vector machine(SVM), fuzzy theory, and genetic algorithm(GA). Our convergence model is basically based on SVM, a classification algorithm enables to predict accurately and to avoid overfitting. It also incorporates fuzzy theory to extend the dimensions of the input variables, and GA to optimize the controlling parameters and feature subset selection. To validate the usefulness of the proposed model, we applied it to H Bank's non-external auditing companies' data. We also experimented six comparative models to validate the superiority of the proposed model. As a result, our model was found to show the best prediction accuracy among the models. Our study is expected to contribute to the relevant literature and practitioners on bankruptcy prediction.

An Algorithm for Identifying the Change of the Current Traffic Congestion Using Historical Traffic Congestion Patterns (과거 교통정체 패턴을 이용한 현재의 교통정체 변화 판별 알고리즘)

  • Lee, Kyungmin;Hong, Bonghee;Jeong, Doseong;Lee, Jiwan
    • KIISE Transactions on Computing Practices
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    • v.21 no.1
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    • pp.19-28
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    • 2015
  • In this paper, we proposed an algorithm for the identification of relieving or worsening current traffic congestion using historic traffic congestion patterns. Historical congestion patterns were placed in an adjacency list. The patterns were constructed to represent spatial and temporal length for status of a congested road. Then, we found information about historical traffic congestions that were similar to today's traffic congestion and will use that information to show how to change traffic congestion in the future. The most similar pattern to current traffic status among the historical patterns corresponded to starting section of current traffic congestion. One of our experiment results had average error when we compared identified changes of the congestion for one of the sections in the congestion road by using our proposal and real traffic status. The average error was 15 minutes. Another result was for the long congestion road consisting of several sections. The average error for this result was within 10 minutes.

Integrated Simulation System for Computer-Generated Forces' Human-like Movement (가상군의 인간유사성 움직임을 위한 통합 시뮬레이션 시스템)

  • Han, Chang-Hee;Shin, Kyu-Yong;Oh, Myung-Ho
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.48 no.5
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    • pp.8-15
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    • 2011
  • The goal of this paper is to describe how to construct an integrated simulation system that integrates limited perception-based mapping with spatial reasoning, path planning, and human motion style in order for a virtual soldier to effectively communicate with other virtual solders and/or human participants in a simulation. Virtual human research often ignores or simplifies perception by using a full map (with omniscient perception). In addition, previous research used a placement node where virtual environment designers save in advance the required information. However, this paper also shows that the human-like movement behavior can be achieved by the integrated ECA system with the mapping that supports a spatial understanding and does not require the omniscient perception.

An Efficient Clustering Algorithm for Massive GPS Trajectory Data (대용량 GPS 궤적 데이터를 위한 효율적인 클러스터링)

  • Kim, Taeyong;Park, Bokuk;Park, Jinkwan;Cho, Hwan-Gue
    • Journal of KIISE
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    • v.43 no.1
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    • pp.40-46
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    • 2016
  • Digital road map generation is primarily based on artificial satellite photographing or in-site manual survey work. Therefore, these map generation procedures require a lot of time and a large budget to create and update road maps. Consequently, people have tried to develop automated map generation systems using GPS trajectory data sets obtained by public vehicles. A fundamental problem in this road generation procedure involves the extraction of representative trajectory such as main roads. Extracting a representative trajectory requires the base data set of piecewise line segments(GPS-trajectories), which have close starting and ending points. So, geometrically similar trajectories are selected for clustering before extracting one representative trajectory from among them. This paper proposes a new divide- and-conquer approach by partitioning the whole map region into regular grid sub-spaces. We then try to find similar trajectories by sweeping. Also, we applied the $Fr{\acute{e}}chet$ distance measure to compute the similarity between a pair of trajectories. We conducted experiments using a set of real GPS data with more than 500 vehicle trajectories obtained from Gangnam-gu, Seoul. The experiment shows that our grid partitioning approach is fast and stable and can be used in real applications for vehicle trajectory clustering.

Measurement of Travel Time Using Sequence Pattern of Vehicles (차종 시퀀스 패턴을 이용한 구간통행시간 계측)

  • Lim, Joong-Seon;Choi, Gyung-Hyun;Oh, Kyu-Sam;Park, Jong-Hun
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.7 no.5
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    • pp.53-63
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    • 2008
  • In this paper, we propose the regional travel time measurement algorithm using the sequence pattern matching to the type of vehicles between the origin of the region and the end of the region, that could be able to overcome the limit of conventional method such as Probe Car Method or AVI Method by License Plate Recognition. This algorithm recognizes the vehicles as a sequence group with a definite length, and measures the regional travel time by searching the sequence of the origin which is the most highly similar to the sequence of the end. According to the assumption of similarity cost function, there are proposed three types of algorithm, and it will be able to estimate the average travel time that is the most adequate to the information providing period by eliminating the abnormal value caused by inflow and outflow of vehicles. In the result of computer simulation by the length of region, the number of passing cars, the length of sequence, and the average maximum error rate are measured within 3.46%, which means that this algorithm is verified for its superior performance.

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An Exploration of the Improvement Direction for Decimal Fractional Multiplication Unit in Textbooks (소수 곱셈 단원의 교과서 개선 방향 탐색)

  • Kim, Sukyoung;Kim, Jinsook;Kwon, Sungyong
    • Journal of Elementary Mathematics Education in Korea
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    • v.22 no.4
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    • pp.475-496
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    • 2018
  • Although the multiplication of decimal fractions is expected to be easy for students to understand because of the similarity to natural numbers multiplication in computing methods, students show many errors in the multiplication of decimal fractions. This is a result of the instruction focused more on skill mastery than conceptual understanding. This study is a basic study for effectively developing a unit of multiplication of decimal fractions. For this purpose, we analyzed the curriculums' performance standards, significance in teaching-learning and evaluation, contents and methods for teaching multiplication of decimal fractions from the 7th curriculum to the revised curriculum of 2015 and the textbooks' activities and lessons. Further, we analyzed preceding studies and introductory books to suggest effective directions for developing teaching unit. As a result of the analysis, three implications were obtained: First, a meaningful instruction for estimation is needed. Second, it is necessary to present a visual model suitable for understanding the meaning of decimal multiplication. Third, the process of formalizing an algorithms for multiplying decimal fractions needs to be diversified.

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Establishment of an In Vitro TCD (Testosterone Compound Detection) System (테스토스테론 물질 검출을 위한 in vitro TCD 시스템 구축)

  • Lee, Dong-Geun;Jo, Jung-Kwon;Lee, Sang-Hyeon
    • Journal of Life Science
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    • v.29 no.10
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    • pp.1159-1163
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    • 2019
  • Although there is a growing interest in male menopause, a phenomenon associated with male hormone depletion, current kits using antibodies to quantify male hormones are expensive. In this study, we constructed an in vitro system for verifying the activity or concentration of male steroid hormones using a transcriptional activity test. A reporter plasmid, pGL2-Neo-ARE-AdE1BTATA, which reacts to testosterone, was constructed. In this plasmid, the ARE-AdE1bTATA sequences can be bounded by the testosterone - androgen receptor complex to express luciferase as a reporter. Then, a stable transfection was performed on the human prostate cancer cell line, LNcap-LN3. The constructed LNcap-LN3/pGL2-Neo-ARE-AdE1BTATA testosterone compound detection (TCD) system showed quantitatively proportional luciferase activities to concentrations of $10^{-13}$ to $10^{-8}M$ of standard testosterone. The established in vitro TCD system will contribute to the development of materials for health/functional foods and drugs as it will be possible to search en masse for testosterone-like or testosterone-inhibiting substances derived from natural materials.

Exploring the Research Topic Networks in the Technology Management Field Using Association Rule-based Co-word Analysis (연관규칙 기반 동시출현단어 분석을 활용한 기술경영 연구 주제 네트워크 분석)

  • Jeon, Ikjin;Lee, Hakyeon
    • Journal of Technology Innovation
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    • v.24 no.4
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    • pp.101-126
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    • 2016
  • This paper identifies core research topics and their relationships by deriving the research topic networks in the technology management field using co-word analysis. Contrary to the conventional approach in which undirected networks are constructed based on normalized co-occurrence frequency, this study analyzes directed networks of keywords by employing the confidence index of association rule mining for pairs of keywords. Author keywords included in 2,456 articles published in nine international journals of technology management in 2011~2014 are extracted and categorized into three types: THEME, METHOD, and FIELD. One-mode networks for each type of keywords are constructed to identify core research keywords and their interrelationships with each type. We then derive the two-mode networks composed of different two types of keywords, THEME-METHOD and THEME-FIELD, to explore which methods or fields are frequently employed or studied for each theme. The findings of this study are expected to be fruitfully referred for researchers in the field of technology management to grasp research trends and set the future research directions.

A Semantic-Based Mashup Development Tool Supporting Various Open API Types (다양한 Open API 타입들을 지원하는 시맨틱 기반 매쉬업 개발 툴)

  • Lee, Yong-Ju
    • Journal of Internet Computing and Services
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    • v.13 no.3
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    • pp.115-126
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    • 2012
  • Mashups have become very popular over the last few years, and their use also varies for IT convergency services. In spite of their popularity, there are several challenging issues when combining Open APIs into mashups, First, since portal sites may have a large number of APIs available for mashups, manually searching and finding compatible APIs can be a tedious and time-consuming task. Second, none of the existing portal sites provides a way to leverage semantic techniques that have been developed to assist users in locating and integrating APIs like those seen in traditional SOAP-based web services. Third, although suitable APIs have been discovered, the integration of these APIs is required for in-depth programming knowledge. To solve these issues, we first show that existing techniques and algorithms used for finding and matching SOAP-based web services can be reused, with only minor changes. Next, we show how the characteristics of APIs can be syntactically defined and semantically described, and how to use the syntactic and semantic descriptions to aid the easy discovery and composition of Open APIs. Finally, we propose a goal-directed interactive approach for the dynamic composition of APIs, where the final mashup is gradually generated by a forward chaining of APIs. At each step, a new API is added to the composition.

Object Detection Based on Hellinger Distance IoU and Objectron Application (Hellinger 거리 IoU와 Objectron 적용을 기반으로 하는 객체 감지)

  • Kim, Yong-Gil;Moon, Kyung-Il
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.2
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    • pp.63-70
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    • 2022
  • Although 2D Object detection has been largely improved in the past years with the advance of deep learning methods and the use of large labeled image datasets, 3D object detection from 2D imagery is a challenging problem in a variety of applications such as robotics, due to the lack of data and diversity of appearances and shapes of objects within a category. Google has just announced the launch of Objectron that has a novel data pipeline using mobile augmented reality session data. However, it also is corresponding to 2D-driven 3D object detection technique. This study explores more mature 2D object detection method, and applies its 2D projection to Objectron 3D lifting system. Most object detection methods use bounding boxes to encode and represent the object shape and location. In this work, we explore a stochastic representation of object regions using Gaussian distributions. We also present a similarity measure for the Gaussian distributions based on the Hellinger Distance, which can be viewed as a stochastic Intersection-over-Union. Our experimental results show that the proposed Gaussian representations are closer to annotated segmentation masks in available datasets. Thus, less accuracy problem that is one of several limitations of Objectron can be relaxed.