• 제목/요약/키워드: hybrid tree

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Quality Enhancement for Hybrid 3DTV with Mixed Resolution Using Conditional Replenishment Algorithm

  • Jung, Kyeong-Hoon;Bang, Min-Suk;Kim, Sung-Hoon;Choo, Hyon-Gon;Kang, Dong-Wook
    • ETRI Journal
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    • 제36권5호
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    • pp.752-760
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    • 2014
  • This paper proposes a conditional replenishment algorithm (CRA) to improve the visual quality (where spatial resolutions of the left and right views are mismatched) of a hybrid stereoscopic 3DTV that is based on the ATSC-M/H standard. So as to generate an enhanced view, the CRA is to choose the better substitute among a disparity-compensated view with high quality and a simply interpolated view. The CRA generates a disparity map that includes modes and disparity vectors as additional information. It also employs a quad-tree structure with variable block size by considering the spatial correlation of disparity vectors. In addition, it takes advantage of the disparity map used in a previous frame to keep the amount of additional information as small as possible. The simulation results show that the proposed CRA can successfully improve the peak signal-to-noise ratio of a poor-quality view and consequently have a positive effect on the subjective quality of the resulting 3D view.

자바 원시 코드에서 논리적인 오류를 찾는 복합 디버깅 기술의 설계 (Design of Hybrid Debugging Technique for Locating Logical Errors in Java Source Codes)

  • 고훈준
    • 한국콘텐츠학회논문지
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    • 제6권10호
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    • pp.114-125
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    • 2006
  • 이전 논문은 자바 프로그램에서 논리적인 오류를 찾기 위한 기술로 HDT를 제안했었다. HDT는 알고리즈믹 프로그램 디버깅 기술을 이용하여 실행트리에서 오류를 포함하고 있는 메소드를 찾고, 단계적 프로그램 디버깅 기술을 이용하여 오류를 포함하고 있는 메소드에서 오류가 있는 문장을 찾아낸다. 이 기술은 전통적인 디버깅 기술보다 자바 프로그램에서 프로그래머가 디버깅하는 횟수를 줄였다. 그러나 최근에는 프로그램 크기가 증가하고 메소드의 수가 증가하고 있기 때문에 아직까지 HDT는 디버깅하는 횟수가 많다. 이 논문은 HDT에 프로그램 분할 기술을 적용하는 HDTS를 제안한다. 이 방법은 자바 프로그램을 디버깅할 때, HDT보다 프로그래머가 디버깅하는 횟수를 줄여 줄 수 있다. 특히, HDTS는 메소드와 문장의 수가 증가할수록 효율성이 증가한다.

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Motion Planning and Control for Mobile Robot with SOFM

  • Yun, Seok-Min;Choi, Jin-Young
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1039-1043
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    • 2005
  • Despite the many significant advances made in robot architecture, the basic approaches are deliberative and reactive methods. They are quite different in recognizing outer environment and inner operating mechanism. For this reason, they have almost opposite characteristics. Later, researchers integrate these two approaches into hybrid architecture. In such architecture, Reactive module also called low-level motion control module have advantage in real-time reacting and sensing outer environment; Deliberative module also called high-level task planning module is good at planning task using world knowledge, reasoning and intelligent computing. This paper presents a framework of the integrated planning and control for mobile robot navigation. Unlike the existing hybrid architecture, it learns topological map from the world map by using MST (Minimum Spanning Tree)-based SOFM (Self-Organizing Feature Map) algorithm. High-level planning module plans simple tasks to low-level control module and low-level control module feedbacks the environment information to high-level planning module. This method allows for a tight integration between high-level and low-level modules, which provide real-time performance and strong adaptability and reactivity to outer environment and its unforeseen changes. This proposed framework is verified by simulation.

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데이터마이닝 기법을 활용한 국민건강보험 상해상병 관리모형 개발 (Developing the administrative model using the data mining technique for injury in National Health Insurance)

  • 박일수;한준태;손혜숙;강석복
    • Journal of the Korean Data and Information Science Society
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    • 제22권3호
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    • pp.467-476
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    • 2011
  • 우리나라의 건강보험제도권 내 해당되지 않은 상해상병 진료건 중 국민건강보험으로 부당 잘못 청구되는 진료건을 적발하여, 환수조치하기 위해서는 정확한 상해상병 조사대상자 선정이 필요하다. 그러나, 국민건강보험공단의 한정된 인력으로 증가하는 상해조사관련 업무량을 보다 효율적으로 대처하고, 수행하기 위해서는 상해요인조사 업무 효율화 및 환수 결정율 제고를 위한 조사대상자 발췌기준의 고도화 방안을 마련해야 한다. 이에 본 연구에서는 상해상병 유형에 대해 일정금액 이상 진료건의 발췌 등과 같은 과거의 발췌기준에서 데이터마이닝 기법과 같은 통계적 모형과 업무규칙을 함께 적용한 하이브리드 모형으로서 상해상병 조사대상자 선정기준을 제시하고자하였다.

Traffic Flow Estimation System using a Hybrid Approach

  • Aung, Swe Sw;Nagayama, Itaru;Tamaki, Shiro
    • IEIE Transactions on Smart Processing and Computing
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    • 제6권4호
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    • pp.281-291
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    • 2017
  • Nowadays, as traffic jams are a daily elementary problem in both developed and developing countries, systems to monitor, predict, and detect traffic conditions are playing an important role in research fields. Comparing them, researchers have been trying to solve problems by applying many kinds of technologies, especially roadside sensors, which still have some issues, and for that reason, any one particular method by itself could not generate sufficient traffic prediction results. However, these sensors have some issues that are not useful for research. Therefore, it may not be best to use them as stand-alone methods for a traffic prediction system. On that note, this paper mainly focuses on predicting traffic conditions based on a hybrid prediction approach, which stands on accuracy comparison of three prediction models: multinomial logistic regression, decision trees, and support vector machine (SVM) classifiers. This is aimed at selecting the most suitable approach by means of integrating proficiencies from these approaches. It was also experimentally confirmed, with test cases and simulations that showed the performance of this hybrid method is more effective than individual methods.

Relevancy contemplation in medical data analytics and ranking of feature selection algorithms

  • P. Antony Seba;J. V. Bibal Benifa
    • ETRI Journal
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    • 제45권3호
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    • pp.448-461
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    • 2023
  • This article performs a detailed data scrutiny on a chronic kidney disease (CKD) dataset to select efficient instances and relevant features. Data relevancy is investigated using feature extraction, hybrid outlier detection, and handling of missing values. Data instances that do not influence the target are removed using data envelopment analysis to enable reduction of rows. Column reduction is achieved by ranking the attributes through feature selection methodologies, namely, extra-trees classifier, recursive feature elimination, chi-squared test, analysis of variance, and mutual information. These methodologies are ranked via Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) using weight optimization to identify the optimal features for model building from the CKD dataset to facilitate better prediction while diagnosing the severity of the disease. An efficient hybrid ensemble and novel similarity-based classifiers are built using the pruned dataset, and the results are thereafter compared with random forest, AdaBoost, naive Bayes, k-nearest neighbors, and support vector machines. The hybrid ensemble classifier yields a better prediction accuracy of 98.31% for the features selected by extra tree classifier (ETC), which is ranked as the best by TOPSIS.

Android Botnet Detection Using Hybrid Analysis

  • Mamoona Arhsad;Ahmad Karim
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제18권3호
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    • pp.704-719
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    • 2024
  • Botnet pandemics are becoming more prevalent with the growing use of mobile phone technologies. Mobile phone technologies provide a wide range of applications, including entertainment, commerce, education, and finance. In addition, botnet refers to the collection of compromised devices managed by a botmaster and engaging with each other via a command server to initiate an attack including phishing email, ad-click fraud, blockchain, and much more. As the number of botnet attacks rises, detecting harmful activities is becoming more challenging in handheld devices. Therefore, it is crucial to evaluate mobile botnet assaults to find the security vulnerabilities that occur through coordinated command servers causing major financial and ethical harm. For this purpose, we propose a hybrid analysis approach that integrates permissions and API and experiments on the machine-learning classifiers to detect mobile botnet applications. In this paper, the experiment employed benign, botnet, and malware applications for validation of the performance and accuracy of classifiers. The results conclude that a classifier model based on a simple decision tree obtained 99% accuracy with a low 0.003 false-positive rate than other machine learning classifiers for botnet applications detection. As an outcome of this paper, a hybrid approach enhances the accuracy of mobile botnet detection as compared to static and dynamic features when both are taken separately.

복합 실시간 계통의 요구사항 명세와 안전성 분석을 위한 정성적 정형기법 (A Qualitative Formal Method for Requirements Specification and Safety Analysis of Hybrid Real-Time Systems)

  • 이장수;차성덕
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제27권2호
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    • pp.120-133
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    • 2000
  • 산업현장에서 복합 실시간 계통(HRTS: Hybrid Real-Time Systems) 개발을 위한 정형기법 사용의 주된 장벽은 인지적 어려움이며 이는 또 다른 위험을 초래할 수 있다. 이러한 문제를 극복하기 위해 HRTS 요구분석과 안전성 분석 시 사용자의 인지적 부담을 줄여줄 수 있는 정성적 요구분석 체계를 제안한다. 이 체계는 요구사항 명세를 위한 정성적 정형기법(QFM: Qualitative Formal Method)과 인과정보에 의한 요구사항 안전성 분석기법(CRSA: Causal Requirements Safety Analysis)으로 구성되어 있다. QFM에서는 인공지능 분야에서 연구된 정성추론 이론을 정형명세에 도입하여 요구사항 설계자와 분석자의 인지적 부담을 줄일 수 있도록 하였다. CRSA는 QFM에서 도출한 HRTS 동작의 인과 정보에 따라 체계적으로 위험 원인을 추적할 수 있도록 하여, 기존 결함 트리 분석(FTA: Fault Tree Analysis) 기법의 단점인 분석자의 주관에 의존하는 문제를 해결한다. 월성 원자력 발전소 자동정지계통(Shutdown System 2) 소프트웨어 요구사항 명세와 안전성 분석에 QFM과 CRSA를 적용하여 그 실효성을 입증하고자 하였다.

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프레임간 및 양갈래 탐색 벡터 양자화기를 혼합한 영상 부호화 시스템 (A Hybrid Interframe/BTVQ Image Coding System)

  • 금낙연;최종수
    • 한국통신학회:학술대회논문집
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    • 한국통신학회 1987년도 춘계학술발표회 논문집
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    • pp.31-34
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    • 1987
  • A new efficientcoding system which can transmit video conferenceof viedeophone signals at a 64kbps is proposed. In addition to the interframe and CRC (Conditional Repleni shment Coding) system, BTVQ (Binary Tree searched Vector Quantizer)and RLC (Run Length Coding) methods are incorporated. Couble buffer memory is used for simple comtrol of channel symbol transmission and memory underflow And also buffer memory onerfolw is easily controlled by the thresholds of a MAD (Moving Area Betector)

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호스트 이동성 보장을 위한 멀티캐스트 라우팅 프로토콜 (Multicast Routing Protocol for Guaranting Host Mobility)

  • 양승제;박성한
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 I
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    • pp.133-136
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    • 2003
  • In this paper, we propose a multicast routing protocol for the seamless delivery of multicast data to mobile hosts through the optimal route in IP based mobile networks. The proposed multicast routing protocol is a hybrid method employing the merits of the bi-directional tunneling and the remote subscription by considering the mobility of mobile hosts. The proposed protocol satisfies the bound of end-to-end delay and supports the seamless handoff. The simulation results show that the proposed protocol has better performance in the number of multicast tree reconstruction and tunneling length and packet loss time than the previous protocols.

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