• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.1932-1950
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• 2018

The paper proposes a code-clone detection method that gives the highest possible precision and recall, without giving much attention to efficiency and scalability. The goal is to automatically create a reliable reference corpus that can be used as a basis for evaluating the precision and recall of clone detection tools. The algorithm takes an abstract-syntax-tree representation of source code and thoroughly examines every possible pair of all duplicate tree patterns in the tree, while avoiding unnecessary and duplicated comparisons wherever possible. The largest possible duplicate patterns are then collected in the set of pattern clusters that are used to identify code clones. The method is implemented and evaluated for a standard set of open-source Java applications. The experimental result shows very high precision and recall. False-negative clones missed by our method are all non-contiguous clones. Finally, the concept of neighbor patterns, which can be used to improve recall by detecting non-contiguous clones and intertwined clones, is proposed.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1705-1711
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• 1991

On-line fault detection and diagnosis has an increasing interest in a chemical process industry, especially for a process control and automation. The chemical process needs an intelligent operation-aided workstation which can do such tasks as process monitoring, fault detection, fault diagnosis and action guidance in semiautomatic mode. These tasks can increase the performance of a process operation and give merits in economics, safety and reliability. Aiming these tasks, series of researches have been done in our lab. Main results from these researches are building appropriate knowledge representation models and a diagnosis mechanism for fault detection and diagnosis in a chemical process. The knowledge representation schemes developed in our previous research, the symptom tree model and the fault-consequence digraph, showed the effectiveness and the usefulness in a real-time application, of the process diagnosis, especially in large and complex plants. However in our previous approach, the diagnosis speed is its demerit in spite of its merits of high resolution, mainly due to using two knowledge models complementarily. In our current study, new knowledge representation scheme is developed which integrates the previous two knowledge models, the symptom tree and the fault-consequence digraph, into one. This new model is constructed using a material balance, energy balance, momentum balance and equipment constraints. Controller related constraints are included in this new model, which possesses merits of the two previous models. This new integrated model will be tested and verified by the real-time application in a BTX process or a crude unit process. The reliability and flexibility will be greatly enhanced compared to the previous model in spite of the low diagnosis speed. Nexpert Object for the expert system shell and SUN4 workstation for the hardware platform are used. TCP/IP for a communication protocol and interfacing to a dynamic simulator, SPEEDUP, for a dynamic data generation are being studied.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.133-140
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• 2018

Accurate sentiment classification is an important research topic in sentiment analysis. This study suggests an efficient classification method of Korean sentiment using word2vec and ensemble methods which have been recently studied variously. For the 200,000 Korean movie review texts, we generate a POS-based BOW feature and a feature using word2vec, and integrated features of two feature representation. We used a single classifier of Logistic Regression, Decision Tree, Naive Bayes, and Support Vector Machine and an ensemble classifier of Adaptive Boost, Bagging, Gradient Boosting, and Random Forest for sentiment classification. As a result of this study, the integrated feature representation composed of BOW feature including adjective and adverb and word2vec feature showed the highest sentiment classification accuracy. Empirical results show that SVM, a single classifier, has the highest performance but ensemble classifiers show similar or slightly lower performance than the single classifier.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.05a
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• pp.185-191
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• 1999

Mathematical morphology based on set theory has been applied to various areas in image processing. Pitas proposed a object recognition algorithm using Morphological Shape Decomposition(MSD), and a new representation scheme called Morphological Shape Representation(MSR). The Pitas's algorithm is a simple and adequate approach to recognize objects that are rotated 45 degree-units with respect to the model object. However, this recognition scheme fails in case of random rotation. This disadvantage may be compensated by defining small angle increments. However, this solution may greatly increase computational complexity because the smaller the step makes more number of rotations to be necessary. In this paper, we propose a new method for object recognition based on MSD. The first step of our method decomposes a binary shape into a union of simple binary shapes, and then a new tree structure is constructed which ran represent the relations of binary shapes in an object. finally, we obtain the feature informations invariant to the rotation, translation, and scaling from the tree and calculate matching scores using efficient matching measure. Because our method does not need to rotate the object to be tested, it could be more efficient than Pitas's one. MSR has an intricate structure so that it might be difficult to calculate matching scores even for a little complex object. But our tree has simpler structure than MSR, and easier to calculated the matchng score. We experimented 20 test images scaled, rotated, and translated versions of five kinds of automobile images. The simulation result using octagonal structure elements shows 95% correct recognition rate. The experimental results using approximated circular structure elements are examined. Also, the effect of noise on MSR scheme is considered.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.10
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• pp.59-68
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• 1998

The goal of data mining is to develop the automatic and intelligent tools and technologies that can find useful knowledge from databases. To meet this goal, we propose an efficient data mining algorithm based on the fuzzy decision tree. The proposed method combines comprehensibility of decision tree such as ID3 and C4.5 and representation power of fuzzy set theory. So, it can generate simple and comprehensive rules describing data. The proposed algorithm consists of two stages: the first stage generates the fuzzy membership functions using histogram analysis, and the second stage constructs a fuzzy decision tree using the fuzzy membership functions. From the testing of the proposed algorithm on the IRIS data and the Wisconsin Breast Cancer data, we found that the proposed method can generate a set of fuzzy rules from data efficiently.

• The Korean Journal of Quaternary Research
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• v.17 no.2
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• pp.157-159
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• 2003

Much of northern Asia is lacking in high-resolution palaeoclimatic data coverage. This vast region thus represents a sizeable gap in data sets used to reconstruct hemispheric-scale temperature trends for the past millennium. To improve coverage, we present a regional-scale composite of four tree-ring width records of Siberian pine and Siberian larch from temperature-sensitive alpine timber-line sites in Mongolia. The chronologies load closely in principal components analysis (PCA) with the first eigenvector accounting for over 53% of the variance from ad 1450 to 1998. The 20-year interval from 1974 to 1993 is the highest such growth period in this composite record, and 17 of the 20 highest growth years have occurred since 1946. Thus these trees, unlike those recently described at some northern sites, do not appear to have lost their temperature sensitivity, and suggest that recent decades have been some of the warmest in the past 500 years for this region. There are, however, comparable periods of inferred, local warmth for individual sites, e.g., in 1520-1580 and 1760-1790. The percent common variance between chronologies has increased through time and is highest (66.1%) in the present century. Although there are obvious differences among the individual chronologies, this result suggests a coherent signal which we consider to be related to temperature. The PCA scores show trends which strongly resemble those seen in recent temperature reconstructions for the Northern Hemisphere, very few of which included representation from Eurasia east of the Ural Mountains. The Mongolia series therefore provides independent corroboration for these reconstructions and their indications of unusual wanning during the twentieth century.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.10A
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• pp.1546-1554
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• 1999

In this paper, Dynamic Fault Tree algorithm(DFT algorithm) is presented. This algorithm provides a concise representation of dynamic fault tolerance system including fault recovery techniques with fault detection, mask and switching function. And this algorithm define FDEP, CSP, SEQ, PAG gate which captures the dynamic characteristics of system. It show that this algorithm solved the constraints to satisfy the dynamic characteristics of system which there are in Markov and also this is able to satisfy the dynamic characteristics of system which there are in Markov and also this is able to covered the disadvantage of Fault tree methods. To show the key advantage of this algorithm, a traditional method, that is, Markov and Fault Tree, applies to TMR and Dual-Duplex systems with the dynamic characteristic and a presented method applies to those. He results proved that the DFT algorithm for solving the problems of the system is more effective than the Markov and Fault tree analysis model..

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.141-150
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• 2008

In this mobile computing environment, data broadcasting is widely used to resolve the problem of limited power and bandwidth of mobile equipments. Most previous broadcast indexing methods concentrate on flat data. However. with the growing popularity of XML, an increasing amount of information is being stored and exchanged in the XML format. We propose a novel indexing method. called TOP tree(Tree Ordering based Path summary tree), for indexing XML document on mobile broadcast environments. TOP tree is a path summary tree which provides a concise structure summary at group level using global IDs and element information at local level using local IDs. Based on the TOP tree representation, we suggest a broadcast stream generation and query Processing method that efficiently handles not only simple Path queries but also multiple path queries. We have compared our indexing method with other indexing methods. Evaluation results show that our approaches can effectively improve the access time and tune-in time in a wireless broadcasting environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.1
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• pp.122-128
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• 2003

In this paper, a 16${\times}$16-bit Multiplier and Accumulator (MAC) is designed using a Redundant Binary Adder (RBA) circuit so that it can make a fast addition of the Redundant Binary Partial Products (RB_PP's) by using Wallace-tree structure. Because a RBA adds two RB numbers, it acts as a 4-2 compressor, which reduces four inputs to two output signals. We propose a method to convert the Redundant Binary (RB) representation into the 2's complement binary representation. Instead of using the conventional full adders, a more efficient RB number to binary number converter can be designed with new conversion method.

• Korean Journal of Computational Design and Engineering
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• v.10 no.4
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• pp.262-273
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• 2005

For CAD data users, few things are as frustrating as receiving CAD data that is unusable due to poor data quality. Users waste time trying to get better data, fixing the data, or even rebuilding the data from scratch from paper drawings or other sources. Most related works and commercial tools handle the boundary representation (B-Rep) shape of CAD models. However, we propose a design history?based approach for healing CAD model errors. Because the design history, which covers the features, the history tree, the parameterization data and constraints, reflects the design intent, CAD model errors can be healed by an interdependency analysis of the feature commands or of the parametric data of each feature command, and by the reconstruction of these feature commands through the rule-based reasoning of an expert system. Unlike other B Rep correction methods, our method automatically heals parametric feature models without translating them to a B-Rep shape, and it also preserves engineering information.