• Title/Summary/Keyword: Sequential Tree

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Ecological Examinations of the Radial Growth of Pine Trees (Pinus densiflora S. et Z.) on Mt. Namsan and the Potential Effects of Current Level of Air Pollutants to the Growth of the Trees in Central Seoul, Korea.

  • Kim, Eun-Shik
    • Journal of Korean Society for Atmospheric Environment
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    • v.10 no.E
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    • pp.371-386
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    • 1994
  • Ecological examinations of the radial growth Patterns of pine trees(Pinus densiflora Sieb. et Zucc) growing on Mt. Namsan in central Seoul were made to test a Proposition that the pine trees decline due to the influence of air pollution and acid rain, which was proposed by some researchers in Korea, and the potential effects of current level of air pollutants to the growth of the Pine trees in central Seoul have been speculated. Tree-rings of 40 trees sampled at 3 sites of Mt. Namsan were prepared and examined using a Computer-aided Tree-Ring Measuring System at Kookmin University, Korea. Air Pollutant data collected by the Ministry of Environment( MOE ) and the Forestry Research Institute(FRI) were used to infer the general conditions of the environment. Correlation analysis was applied to the data set of tree growth and the other environmental factors. General information derived from the close examination of the tree-rings and the data on air pollution, drought and the other biological conditions suggested that the growth of the pine trees was severely affected by the occurrence of drought(climatic variation), the prevalence of the pine leaf gall midges(insects), and the suppression by the black locust trees(Robinia pseudo-acacia L.) (competition among trees). While the current condition of air pollution in Seoul cannot be categorized as good, the concentrations of air pollutants are not so high as to cause acute damages to the trees. In addition, while the data of rain acidity showed episodic low PHs of under 4.0, the average of them is far less acidic than those which were observed in either northeastern United States or central Europe, where the decline of trees were not solely attributed to any of the air pollutants. Considering the sequential facts that one of the most important environmental factors that affect the growth of trees is weather condition of the forest that the proposition of the decline of the pine trees was made without careful examination of the growth patterns and past growth history of them as well as the complex influences of many other factors including the weather conditions to the growth of trees, and that no objective explanation has been made on the causal relationships between the current condition of air pollution and the growth of the trees, such a proposition should be evaluated as invalid for the explanation of tree growth on Mt. Namsan in central Seoul, Korea. The author evaluates the factors of air pollution (including acid rain) as the predisposing factors, which may have the Potentials to chronically affect the tree growth at the forest ecosystem on Mt. Namsan for a long period of time. Ecosystem ecological studies should be further carried out to carefully explain both the functional and the structural aspects of the ecosystem processes, which include the biogeochemistry and the long-term changes of soil conditions as well as the growth of the other tree species on the mountain.

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Effective Normalization Method for Fraud Detection Using a Decision Tree (의사결정나무를 이용한 이상금융거래 탐지 정규화 방법에 관한 연구)

  • Park, Jae Hoon;Kim, Huy Kang;Kim, Eunjin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.1
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    • pp.133-146
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    • 2015
  • Ever sophisticated e-finance fraud techniques have led to an increasing number of reported phishing incidents. Financial authorities, in response, have recommended that we enhance existing Fraud Detection Systems (FDS) of banks and other financial institutions. FDSs are systems designed to prevent e-finance accidents through real-time access and validity checks on client transactions. The effectiveness of an FDS depends largely on how fast it can analyze and detect abnormalities in large amounts of customer transaction data. In this study we detect fraudulent transaction patterns and establish detection rules through e-finance accident data analyses. Abnormalities are flagged by comparing individual client transaction patterns with client profiles, using the ruleset. We propose an effective flagging method that uses decision trees to normalize detection rules. In demonstration, we extracted customer usage patterns, customer profile informations and detection rules from the e-finance accident data of an actual domestic(Korean) bank. We then compared the results of our decision tree-normalized detection rules with the results of a sequential detection and confirmed the efficiency of our methods.

Mining Frequent Trajectory Patterns in RFID Data Streams (RFID 데이터 스트림에서 이동궤적 패턴의 탐사)

  • Seo, Sung-Bo;Lee, Yong-Mi;Lee, Jun-Wook;Nam, Kwang-Woo;Ryu, Keun-Ho;Park, Jin-Soo
    • Journal of Korea Spatial Information System Society
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    • v.11 no.1
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    • pp.127-136
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    • 2009
  • This paper proposes an on-line mining algorithm of moving trajectory patterns in RFID data streams considering changing characteristics over time and constraints of single-pass data scan. Since RFID, sensor, and mobile network technology have been rapidly developed, many researchers have been recently focused on the study of real-time data gathering from real-world and mining the useful patterns from them. Previous researches for sequential patterns or moving trajectory patterns based on stream data have an extremely time-consum ing problem because of multi-pass database scan and tree traversal, and they also did not consider the time-changing characteristics of stream data. The proposed method preserves the sequential strength of 2-lengths frequent patterns in binary relationship table using the time-evolving graph to exactly reflect changes of RFID data stream from time to time. In addition, in order to solve the problem of the repetitive data scans, the proposed algorithm infers candidate k-lengths moving trajectory patterns beforehand at a time point t, and then extracts the patterns after screening the candidate patterns by only one-pass at a time point t+1. Through the experiment, the proposed method shows the superior performance in respect of time and space complexity than the Apriori-like method according as the reduction ratio of candidate sets is about 7 percent.

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Efficient Collaboration Method Between CPU and GPU for Generating All Possible Cases in Combination (조합에서 모든 경우의 수를 만들기 위한 CPU와 GPU의 효율적 협업 방법)

  • Son, Ki-Bong;Son, Min-Young;Kim, Young-Hak
    • KIPS Transactions on Computer and Communication Systems
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    • v.7 no.9
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    • pp.219-226
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    • 2018
  • One of the systematic ways to generate the number of all cases is a combination to construct a combination tree, and its time complexity is O($2^n$). A combination tree is used for various purposes such as the graph homogeneity problem, the initial model for calculating frequent item sets, and so on. However, algorithms that must search the number of all cases of a combination are difficult to use realistically due to high time complexity. Nevertheless, as the amount of data becomes large and various studies are being carried out to utilize the data, the number of cases of searching all cases is increasing. Recently, as the GPU environment becomes popular and can be easily accessed, various attempts have been made to reduce time by parallelizing algorithms having high time complexity in a serial environment. Because the method of generating the number of all cases in combination is sequential and the size of sub-task is biased, it is not suitable for parallel implementation. The efficiency of parallel algorithms can be maximized when all threads have tasks with similar size. In this paper, we propose a method to efficiently collaborate between CPU and GPU to parallelize the problem of finding the number of all cases. In order to evaluate the performance of the proposed algorithm, we analyze the time complexity in the theoretical aspect, and compare the experimental time of the proposed algorithm with other algorithms in CPU and GPU environment. Experimental results show that the proposed CPU and GPU collaboration algorithm maintains a balance between the execution time of the CPU and GPU compared to the previous algorithms, and the execution time is improved remarkable as the number of elements increases.

Prediction of Dormancy Release and Bud Burst in Korean Grapevine Cultivars Using Daily Temperature Data (기온자료에 근거한 주요 포도품종의 휴면해제 및 발아시기 추정)

  • Kwon Eun-Young;Song Gi-Cheol;Yun Jin I.
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.7 no.3
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    • pp.185-191
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    • 2005
  • An accurate prediction of dormancy release and bud burst in temperate zone fruit trees is indispensable for farmers to plan heating time under partially controlled environments as well as to reduce the risk of frost damage in open fields. A thermal time-based two-step phenological model that originated in Italy was applied to two important grapevine cultivars in Korea for predicting bud-burst dates. The model consists of two sequential periods: a rest period described by chilling requirement and a forcing period described by heating requirement. It requires daily maximum and minimum temperature as an input and calculates daily chill units (chill days in negative sign) until a pre-determined chilling requirement for rest release is met. After the projected rest release date, it adds daily heat units (anti-chill days in positive sign) to the chilling requirement. The date when the sum reaches zero isregarded as the bud-burst in the model. Controlled environment experiments using field sampled twigs of 'Campbell Early' and 'Kyoho' cultivars were carried out in the vineyard at the National Horticultural Research Institute (NHRI) in Suwon during 2004-2005 to derive the model parameters: threshold temperature for chilling and chilling requirement for breaking dormancy. The model adjusted with the selected parameters was applied to the 1994-2004 daily temperature data obtained from the automated weather station in the NHRI vineyard to estimate bud burst dates of two cultivars and the results were compared with the observed data. The model showed a consistently good performance in predicting the bud burst of 'Campbell Early' and 'Kyoho' cultivars with 2.6 and 2.5 days of root mean squared error, respectively.

Representation of Three-dimensional Polygonal Mesh Models Using Hierarchical Partitioning and View dependent Progressive Transmission (계층적 분할을 이용한 삼차원 다각형 메쉬 모델의 표현 및 인간 시점에 따른 점진적 전송 방법)

  • 김성열;호요성
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.6
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    • pp.132-140
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    • 2003
  • In this paper, we propose a new scheme for view-dependent transmission of three-dimensional (3-D) polygonal mesh models with hierarchial partitioning. In order to make a view-dependent representation of 3-D mesh models, we combine sequential and progressive mesh transmission techniques. By setting higher priorities to visible parts than invisible parts, we can obtain good qualify of 3-D models in a limited transmission bandwidth. In this paper, we use a multi -layer representation of 3-D mesh models based on hierarchical partitioning. After representing the 3-D mesh model in a hierarchical tree, we determine resolutions of partitioned submeshes in the last level. Then, we send 3-D model data by view-dependent selection using mesh merging and mesh splitting operations. By the partitioned mesh merging operation, we can reduce the joint boundary information coded redundantly in the partitioned submeshes. We may transmit additional mesh information adaptively through the mesh spritting operation.

An Efficient CPLD Technology Mapping considering Area and the Time Constraint (시간 제약 조건과 면적을 고려한 효율적인 CPLD 기술 매핑)

  • Kim Jae-Jin;Lee Kwan-Houng
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.3 s.35
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    • pp.11-18
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    • 2005
  • In this paper, we propose a new technology mapping algorithm for CPLD consider area under time constraint. This algorithm detect feedbacks from boolean networks, then variables that have feedback are replaced to temporary variables. Creating the temporary variables transform sequential circuit to combinational circuit. The transformed circuits are represented to DAG. After traversing all nodes in DAG, the nodes that have output edges more than two are replicated and reconstructed to fanout free tree. Using time constraints and delay time of device, the number of graph partitionable multi-level is decided. Several nodes in partitioned clusters are merged by collapsing, and are fitted to the number of OR-terms in a given CLB by bin packing. Proposed algorithm have been applied to MCNC logic synthesis benchmark circuits, and have reduced the number of CLBs by $62.2\%$ than those of DDMAP. And reduced the number of CLBs by $17.6\%$ than those of TEMPLA.

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A deisgn of VHDL compiler front-end for the VHDL-to-C mapping (VHDL-to-C 사상을 위한 VHDL 컴파일러 전반부의 설계)

  • 공진흥;고형일
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.12
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    • pp.2834-2851
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    • 1997
  • In this paper, a design and implementation of VHDL compiler front-end, aims at supporting the full-set of VHDL '87 & '93 LRM and carring out the preprocessing of VHDL-to-C, is described. The VHDL compiler front-end includes 1)the symbol tree of analyzed data to represent the hierarchy, the scope and visibility, the overloading and homograph, the concurrent multiple stacks in VHDL, 2)the data structure and supportig routies to deal with the objects, the type and subtype, the attribute and operation in VHDL, 3)the analysis of the concurrent/sequential statements, the behavior/structural descriptions, of semantic token and the propagation of symbol & type to improve the registration and retrieval procedure of analyzed data. In the experiments with Validation Suite, the VHDL compiler front-end could support the full-set specification of VHDL LRM '87 & '93; and in the experiments to asses the performance of symantic token for the VHDL hierachy/visibility/concurrency/semantic checking, the improvement of about 20-30% could be achieved.

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Phenological Characteristics of Rhododendron Species in Temperate Mixed Broad-leaved Forests of Arunachal Himalaya, India

  • Paul, Ashish;Khan, Mohamed Latif;Das, Ashesh Kumar
    • Journal of Forest and Environmental Science
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    • v.34 no.6
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    • pp.435-450
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    • 2018
  • Phenological events of four Rhododendron tree species (viz. R. arboreum, R. arboreum ssp. delavayi var. delavayi, R. barbatum and R. kesangiae) was monitored in temperate mixed broad-leaved forests of Arunachal Pradesh, India. Phenological events like flower bud formation, flowering, fruit setting, fruit maturing, seed dispersal, leaf bud formation, leaf flushing, and leaf shedding were recorded. Indices i.e., phenophase sequence index (PSI), active phenophasic period of the species (APS) and index of reproductive/vegetative activity (RVA) were also calculated. Present study revealed that bark consistency, growth form and leaf pattern of the studied species have showed variations among the species. Rhododendron species exhibited the phenological events overlapping with other phenophases. The peak flower bud formation was observed during the winter; R. arboreum ssp. delavayi var. delavayi start flowering from December, while the flowering in rest three species exhibited during February to April. Fruit setting occurred during summer to autumn while fruit maturation revealed peak during November. Leaf bud formation illustrated two peaks in April and May, leaf flushing exhibited peak in June, while leaf shedding peaked during October to November. Active phenophasic period of the species were found 12 months, which revealed that species engage in various phenophase activities throughout the year. Phenophase sequence index ranged between 0.8 to 0.9 (PSI ${\geq}0.6$), signifies that species have a sequential arrangement of phenophases. Index of reproductive/vegetative activity of the species exemplified >1, indicate that the reproductive phenophases were dominance over vegetative phenophases. The study have provided substantial insight on the life cycle events of Rhododendron species and ecological approaches for further scientific study with recent climate change and effective management and conservation.

Dynamic quantitative risk assessment of accidents induced by leakage on offshore platforms using DEMATEL-BN

  • Meng, Xiangkun;Chen, Guoming;Zhu, Gaogeng;Zhu, Yuan
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.11 no.1
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    • pp.22-32
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    • 2019
  • On offshore platforms, oil and gas leaks are apt to be the initial events of major accidents that may result in significant loss of life and property damage. To prevent accidents induced by leakage, it is vital to perform a case-specific and accurate risk assessment. This paper presents an integrated method of Ddynamic Qquantitative Rrisk Aassessment (DQRA)-using the Decision Making Trial and Evaluation Laboratory (DEMATEL)-Bayesian Network (BN)-for evaluation of the system vulnerabilities and prediction of the occurrence probabilities of accidents induced by leakage. In the method, three-level indicators are established to identify factors, events, and subsystems that may lead to leakage, fire, and explosion. The critical indicators that directly influence the evolution of risk are identified using DEMATEL. Then, a sequential model is developed to describe the escalation of initial events using an Event Tree (ET), which is converted into a BN to calculate the posterior probabilities of indicators. Using the newly introduced accident precursor data, the failure probabilities of safety barriers and basic factors, and the occurrence probabilities of different consequences can be updated using the BN. The proposed method overcomes the limitations of traditional methods that cannot effectively utilize the operational data of platforms. This work shows trends of accident risks over time and provides useful information for risk control of floating marine platforms.