• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.27-36
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• 1998

This paper suggests an integrated method based on rough sets for discovering useful knowledge from a large databse. Our approach applies attribute-oriented concept hierarchy ascension technique to extract generalized data from actual data in database, induction of decision trees to measure the information gain, and knowledge reduction method of rough set theory to remove superfluous attributes and attribute values. The integrated algorithm first reduces the size of database through the concept generalization, reduces the number of attributes by means of eliminating condition attributes which have little influence on decision attribute, and finally induces simplified decision rules by removing the superfluous attribute values by analyzing the dependency relationships among the attributes.

• Computers and Concrete
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• v.16 no.1
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• pp.141-161
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• 2015

A significant portion of residential areas of Turkey is located in active earthquake zones. In Turkey occurred major earthquakes in last twenty years, such as Erzincan (1992), Kocaeli and $D{\ddot{u}}zce$ (1999), $Bing{\ddot{o}}l$ (2003), Van (2011). These earthquakes have demonstrated that reinforced concrete (RC) buildings having horizontal and vertical irregularities are significantly damaged, which in turn most of them are collapsed. Architectural design and arrangement of load-bearing system have important effect on RC building since architectural design criteria in design process provide opportunity to make this type of buildings safer and economical under earthquake loads. This study aims to investigate comparatively the effects of weak story irregularity on earthquake behavior and rough construction costs of RC buildings by considering different soil-conditions given in the Turkish Earthquake Code. With this aim, Sta4-CAD program based on matrix displacement method is utilized. Considering that different story height and compressive strength of concrete, and infill walls or their locations are the variables, a set of structural models are developed to determine the effect of them on earthquake behavior and rough construction costs of RC buildings. In conclusion, some recommendations and results related to making RC buildings safer and more economical are presented by comparing results obtained from structural analyses.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.5
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• pp.69-74
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• 2015

In this paper the patterns of information system is reduced so that control rules can guarantee fast response of queries in database. Generally an information system includes many kinds of necessary and unnecessary attribute. In particular, inconsistent information system is less likely to acquire the accuracy of response. Hence we are interested in the simple and understandable rules that can represent useful patterns by means of rough entropy and Bayesian posterior probability. We propose an algorithm which can reduce control rules to a minimum without inadequate patterns such that the implication between condition attributes and decision attributes is measured through the framework of rough entropy. Subsequently the validation of the proposed algorithm is showed through test information system of new employees appointment.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.11
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• pp.1958-1966
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• 2003

Three-axis CNC surface machining entails a series of processes including rough cutting, intermediate cutting and finish cutting for a reference surface defined in CAD/CAM. This study is targeting development of an integrated NURBS surface interpolator that can incorporate rough, intermediate and finish cutting processes. In each process, volume to be removed and cutting condition are different according to the shape of a part to be machined and the reference surface. Accordingly, the proposed NURBS surface interpolator controls motion in real-time optimized for the machining conditions of each process. In this paper, a newly defined set of G-codes is proposed such that NURBS surface machining through CNC is feasible with minimal information on the surface composition. To verify the usefulness of the proposed interpolator, through computer simulations on NURBS surface machining, total machining time, size of required NC data and cutting force variations are compared with the existing method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3B
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• pp.244-250
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• 2002

In this paper, rile scattered field from a random rough perfectly conducting surface by method of moment(MoM) was computed. A one-dimensional random rough surface predetermined statistical properties was generated by a digital computer. The number of surface realization for the computed field and the width of surface realization are set to be 100, 80 λ, respectively. To eliminate the scattering from the ends of the surface, the Gaussian taper function is used. Using Monte Carlo technique, we calculated hi-static scattering and back scattering coefficient. In order to verify the result by MoM we compare the MoM results with those of Kirchhoff approximations, which show good agreement between them.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.315-326
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• 2007

The rapid proliferation of wireless networks and mobile computing applications has changed the landscape of network security. Anomaly detection is a pattern recognition task whose goal is to report the occurrence of abnormal or unknown behavior in a given system being monitored. This paper presents a dynamic anomaly detection scheme that can effectively identify a group of especially harmful internal masqueraders in cellular mobile networks. Our scheme uses the trace data of wireless application layer by a user as feature value. Based on the feature values, the use pattern of a mobile's user can be captured by rough sets, and the abnormal behavior of the mobile can be also detected effectively by applying a roughness membership function with both the age of the user profile and weighted feature values. The performance of our scheme is evaluated by a simulation. Simulation results demonstrate that the anomalies are well detected by the proposed dynamic scheme that considers the age of user profiles.

• Communications of the Korean Mathematical Society
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• v.22 no.2
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• pp.277-287
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• 2007

We prove that if a graph G of bounded degree has finitely many p-hyperbolic ends($1) in which every bounded energy finite p-harmonic function is asymptotically constant for almost every path, then the set $\mathcal{HBD}_p(G)$ of all bounded energy finite p-harmonic functions on G is in one to one corresponding to $\mathbf{R}^l$, where $l$ is the number of p-hyperbolic ends of G. Furthermore, we prove that if a graph G' is roughly isometric to G, then $\mathcal{HBD}_p(G')$ is also in an one to one correspondence with $\mathbf{R}^l$.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.6
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• pp.583-590
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• 1999

We propose the reusability decision model of the object-oriented components, which can decide the potentiality of reusability of the object-oriented components actively. Fisrt, we select attributes for the reusability decision of the object-oriented components. Then, we acquire information from the reused components based on the quality measures and criteria proposed by many researches. Lastly, we generate algorithm for the reusability decision of the object-oriented components from the acquired information employing rough set.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.142-148
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• 2004

In this paper, we propose the color fuzzy decision algorithm to face segmentation in a color image. Our algorithm can segment without the user's interaction by fuzzy decision marking. And it removes small parts such as a noise using wavelet morphology in the image obtained by applying the fuzzy decision algorithm. Also, it merges and chooses the face region in each quantization image through rough sets. This video object division algorithm is shown to be superior to a conventional algorithm.

• ETRI Journal
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• v.36 no.6
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• pp.1023-1031
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• 2014

Failure analysis is necessary to clarify the root cause of a failure, predict the next time a failure may occur, and improve the performance and reliability of a system. However, it is not an easy task to analyze and interpret failure data, especially for complex systems. Usually, these data are represented using many attributes, and sometimes they are inconsistent and ambiguous. In this paper, we present a scalable approach for the analysis and interpretation of failure data of high-performance computing systems. The approach employs rough sets theory (RST) for this task. The application of RST to a large publicly available set of failure data highlights the main attributes responsible for the root cause of a failure. In addition, it is used to analyze other failure characteristics, such as time between failures, repair times, workload running on a failed node, and failure category. Experimental results show the scalability of the presented approach and its ability to reveal dependencies among different failure characteristics.