• Title/Summary/Keyword: Binary Tree algorithm

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Learning Assembly Strategies for Chamferless Parts (학습적 방법에 의한 챔퍼없는 부품의 조립에 관한 연구)

  • Ahn, D.S.;Kim, S.Y.;Cho, H.S.
    • Journal of the Korean Society for Precision Engineering
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    • v.10 no.3
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    • pp.175-181
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    • 1993
  • In this paper, a practical method to generate task strategies applicable to chamferless and high-precision assembly, is proposed. The difficulties in devising reliable assembly strategies result from various forms of uncertainty such as imperfect knowledge on the parts being assembled and functional limitations of the assembly devices. In approach to cope with these problems, the robot is provided with the capability of learning the corrective motion in response to the force signal trrough iterative task execution. The strategy is realized by adopting a learning algorithm and represented in a binary tree type database. To verify the effectiveness of the proposed algorithm, a series of simulations and experiments are carried out under assimilated real production environments. The results show that the sensory signal-to-robot action mapping can be acquired effectively and, consequently, the chamferless assembly can be performed successfully.

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An Improvement of Bin-slotted Anti-collision Algorithm for Ubiquitous ID System

  • Kim Ji-Yoon;Kang Bong-Soo;Yang Doo-Yeong
    • International Journal of Contents
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    • v.2 no.1
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    • pp.34-38
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    • 2006
  • In this paper, an overview of anti-collision algorithm for RFID system of a standard EPC Class1 protocol is presented, and the binslotted dynamic search algorithm (BDS) based upon the slotted ALOHA and binary tree procedure is proposed and analyzed. Also, the performance is evaluated as comparing the BDS algorithm with the standard bin-slotted algorithm (BSA) through the simulation program. The performance of the proposed BDS algorithm is improved by dynamically identifying the collided-bit position and the collided bins stored in the stack of the reader. As the results, the number of request command that a reader send to tags in the reader s interrogation zone and the total recognition time are decreased to 59% as compared with BSA algorithm. Therefore, the tag identification performance is fairly improved by resolving a collision problem using the proposed BDS algorithm.

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Evaluation of Machine Learning Algorithm Utilization for Lung Cancer Classification Based on Gene Expression Levels

  • Podolsky, Maxim D;Barchuk, Anton A;Kuznetcov, Vladimir I;Gusarova, Natalia F;Gaidukov, Vadim S;Tarakanov, Segrey A
    • Asian Pacific Journal of Cancer Prevention
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    • v.17 no.2
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    • pp.835-838
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    • 2016
  • Background: Lung cancer remains one of the most common cancers in the world, both in terms of new cases (about 13% of total per year) and deaths (nearly one cancer death in five), because of the high case fatality. Errors in lung cancer type or malignant growth determination lead to degraded treatment efficacy, because anticancer strategy depends on tumor morphology. Materials and Methods: We have made an attempt to evaluate effectiveness of machine learning algorithms in the task of lung cancer classification based on gene expression levels. We processed four publicly available data sets. The Dana-Farber Cancer Institute data set contains 203 samples and the task was to classify four cancer types and sound tissue samples. With the University of Michigan data set of 96 samples, the task was to execute a binary classification of adenocarcinoma and non-neoplastic tissues. The University of Toronto data set contains 39 samples and the task was to detect recurrence, while with the Brigham and Women's Hospital data set of 181 samples it was to make a binary classification of malignant pleural mesothelioma and adenocarcinoma. We used the k-nearest neighbor algorithm (k=1, k=5, k=10), naive Bayes classifier with assumption of both a normal distribution of attributes and a distribution through histograms, support vector machine and C4.5 decision tree. Effectiveness of machine learning algorithms was evaluated with the Matthews correlation coefficient. Results: The support vector machine method showed best results among data sets from the Dana-Farber Cancer Institute and Brigham and Women's Hospital. All algorithms with the exception of the C4.5 decision tree showed maximum potential effectiveness in the University of Michigan data set. However, the C4.5 decision tree showed best results for the University of Toronto data set. Conclusions: Machine learning algorithms can be used for lung cancer morphology classification and similar tasks based on gene expression level evaluation.

A Fast Decision Method of Quadtree plus Binary Tree (QTBT) Depth in JEM (차세대 비디오 코덱(JEM)의 고속 QTBT 분할 깊이 결정 기법)

  • Yoon, Yong-Uk;Park, Do-Hyun;Kim, Jae-Gon
    • Journal of Broadcast Engineering
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    • v.22 no.5
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    • pp.541-547
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    • 2017
  • The Joint Exploration Model (JEM), which is a reference SW codec of the Joint Video Exploration Team (JVET) exploring the future video standard technology, provides a recursive Quadtree plus Binary Tree (QTBT) block structure. QTBT can achieve enhanced coding efficiency by adding new block structures at the expense of largely increased computational complexity. In this paper, we propose a fast decision algorithm of QTBT block partitioning depth that uses the rate-distortion (RD) cost of the upper and current depth to reduce the complexity of the JEM encoder. Experimental results showed that the computational complexity of JEM 5.0 can be reduced up to 21.6% and 11.0% with BD-rate increase of 0.7% and 1.2% in AI (All Intra) and RA (Random Access), respectively.

A Study on the Implementation of Small Capacity Dictionary for Mobile Equipments Using a CBDS tree (CBDS 트리를 이용한 모바일 기기용 저용량 사전 구현에 관한 연구)

  • Jung Kyu-Cheol;Lee Jin-Hwan;Jang Hye-Suk;Park Ki-hong
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.5 s.37
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    • pp.33-40
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    • 2005
  • Recently So far Many low-cost mobile machinery have been produced. Those are being used for study and business. But those are some weak Points which are small-capacity storage and quite low-speed system. If we use general database programs or key-searching algorithm, It could decrease in performance of system. To solve those Problems, we applied CBDS(Compact Binary Digital Search) trie to mobile environment. As a result we could accomplish our goal which are quick searching and low-capacity indexing. We compared with some Java classes such as TreeSet to evaluation. As a result, the velocity of searching was a little slow than B-tree based TreeSet. But the storage space have been decreased by 29 percent. So I think that it would be practical use.

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Path Level Reliability in Overlay Multicast Tree for Realtime Service

  • Lee, Chae-Y.;Lee, Jung-H.
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.11a
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    • pp.312-315
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    • 2006
  • Overlay Multicast is a promising approach to overcome the implementation problem of IP multicast. Real time services like internet broadcasting are provided by overlay multicast technology due to the complex nature of IP multicast and the high cost to support multicast function. Since multicast members can dynamically join or leave their multicast group, it is necessary to keep a reliable overlay multicast tree to support real time service without delay. In this paper, we consider path level reliability that connects each member node. The problem is formulated as a binary integer programming which maximizes the reliability of multicast tree. Tabu search based algorithm is presented to solve the NP-hard problem.

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Design of a Booth's Multiplier Suitable for Embedded Systems (임베디드 시스템에 적용이 용이한 Booth 알고리즘 방식의 곱셈기 설계)

  • Moon, San-Gook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2007.10a
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    • pp.838-841
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    • 2007
  • In this study, we implemented a $17^*17b$ binary digital multiplier using radix-4 Booth's algorithm. Two stage pipeline architecture was applied to achieve higher throughput and 4:2 adders were used for regular layout structure in the Wallace tree partition. To evaluate the circuit, several MPW chips were fabricated using Hynix 0.6-um 3M N-well CMOS technology. Also we proposed an efficient test methodology and did fault simulations. The chip contains 9115 transistors and the core area occupies about $1135^*1545$ mm2. The functional tests using ATS-2 tester showed that it can operate with 24 MHz clock at 5.0 V at room temperature.

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Constraint Algorithm in Double-Base Number System for High Speed A/D Converters

  • Nguyen, Minh Son;Kim, Man-Ho;Kim, Jong-Soo
    • Journal of Electrical Engineering and Technology
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    • v.3 no.3
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    • pp.430-435
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    • 2008
  • In the paper, an algorithm called a Constraint algorithm is proposed to solve the fan-in problem occurred in ADC encoding circuits. The Flash ADC architecture uses a double-base number system (DBNS). The DBNS has known to represent the multi-dimensional logarithmic number system (MDLNS) used for implementing the multiplier accumulator architecture of FIR filter in digital signal processing (DSP) applications. The authors use the DBNS with the base 2 and 3 to represent binary output of ADC. A symmetric map is analyzed first, and then asymmetric map is followed to provide addition read DBNS to DSP circuitry. The simulation results are shown for the Double-Base Integer Encoder (DBIE) of the 6-bit ADC to demonstrate an effectiveness of the Constraint algorithm, using $0.18{\mu}\;m$ CMOS technology. The DBIE’s processing speed of the ADC is fast compared to the FAT tree encoder circuit by 0.95 GHz.

Effective Diagnostic Method Of Breast Cancer Data Using Decision Tree (Decision Tree를 이용한 효과적인 유방암 진단)

  • Jung, Yong-Gyu;Lee, Seung-Ho;Sung, Ho-Joong
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.10 no.5
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    • pp.57-62
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    • 2010
  • Recently, decision tree techniques have been studied in terms of quick searching and extracting of massive data in medical fields. Although many different techniques have been developed such as CART, C4.5 and CHAID which are belong to a pie in Clermont decision tree classification algorithm, those methods can jeopardize remained data by the binary method during procedures. In brief, C4.5 method composes a decision tree by entropy levels. In contrast, CART method does by entropy matrix in categorical or continuous data. Therefore, we compared C4.5 and CART methods which were belong to a same pie using breast cancer data to evaluate their performance respectively. To convince data accuracy, we performed cross-validation of results in this paper.

An Efficient Processor Allocation Scheme for Hypercube (하이퍼큐브에서의 효과적인 프로세서할당 기법)

  • Son, Yoo-Ek;Nam, Jae-Yeal
    • The Transactions of the Korea Information Processing Society
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    • v.3 no.4
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    • pp.781-790
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    • 1996
  • processors must be allocated to incoming tasks in a way that will maximize the processor utilization and minimize the system fragmentation. Thus, an efficient method of allocating processors in a hypercube is a key to system performance. In order to achieve this goal, it is necessary to detect the availability of a subcube of required size and merge the released small cubes to form a larger ones. This paper presents the tree-exchange algorithm which detemines the levels and partners of the binary tree representation of a hypercube, and an efficient allocation strategy using the algorithm. The complexity for search time of the algorithm is $O\ulcorner$n/2$\lrcorner$$\times$2n)and it shows good performance in comparison with other strategies.

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