• Journal of Korea Multimedia Society
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• v.24 no.9
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• pp.1203-1210
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• 2021

In this paper, we developed the inspection system of electric vehicle pouch battery using image processing. Line scan cameras are used for acquiring the all parts of the pouch battery, and several steps of image processing for extracting significant dimensions(User Required Position) of the battery. In image processing, edge lines, node points, dimension lines, etc. were extracted using Preprocessor, Square Edge Detection, and Size Detection algorithms. This is used to measure the dimensions of the location requested by the user on the pouch battery. For verification of the inspection system, the dimensions of three pouch batteries produced in the same process were measured, and the mean and standard deviation were obtained to confirm the precision.

• Journal of Korea Multimedia Society
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• v.24 no.12
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• pp.1663-1672
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• 2021

There are various typing practice applications. In addition, research cases on learning applications that support typing practice have been reported. These services are usually provided in a way that utilizes their own built-in text. Learners collect various contents through web services and use them a lot for learning. Therefore, this paper proposes a learning application to increase the learning effect by collecting vast amounts of web content and applying it to typing practice. The proposed application is implemented using Tkinter, a GUI module of Python. BeautifulSoup module of Python is used to extract information from the web. In order to process the extracted data, the NLTK module, which is an English data preprocessor, and the KoNLPy module, which is a Korean language processing module, are used. The operation of the proposed function is verified in the implementation and experimental results.

• The KIPS Transactions:PartA
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• v.17A no.1
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• pp.9-18
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• 2010

Races that occur in shared-memory parallel programs such as OpenMP programs must be detected for debugging because of causing unintended non-deterministic results. Previous works which verify the existence of these races on-the-fly are limited to the programs without internal non-determinism. But in the programs with internal non-determinism, such works need at least N! execution instances for each critical section to verify the existence of races, where N is the degree of maximum parallelism. This paper presents a preprocessor that statically analyzes the locations of non-deterministic accesses using program slicing and can detect apparent races as well as potential races through single execution using the analyzed information. The suggested tool can deterministically monitor non-deterministic accesses to occur in OpenMP programs so that this tool can verify the existence of races even if it is used any race detection protocol which can apply to programs with critical section. To prove empirically this tool, we have experimented using a set of benchmark programs such as synthetic programs that involve non-deterministic accesses, OpenMP Microbenchmark, NAS Parallel Benchmark, and OpenMP application programs.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.2875-2888
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• 1999

In this paper we present compiler-based active rule system to efficiently maintain spatial integrity constraints in a heterogeneous, distributed environment. Specially, the prototype active rule system presented has been developed as a component of a whole middleware system called SDBC(Spatile DataBase Connectivity). Due to this reason, our active rule system is provided for heterogeneous ODBMSs in a distributed environment and used to define spatial integrity constraints using the active rules in E-C-A(Event-Condition-Action) type. Using this active rule system, an application programmer can free himself from a heavier burden on the integrity maintenance of application objects. In the compiler-based approach, active rules applicable to events raised by a database program are directly inserted into the program in a function type by the preprocessor, and then they are compiled with the application program source codes. One advantage of this approach is that there is no run-time overhead accompanied by monitoring all the database transitions when preprocessed program is executed. This active rule system also provides facilities to manage changed rules and dynamically interpret those rules at run-tuime.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.702-723
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• 2020

The application of machine learning (ML) in intrusion detection has attracted much attention with the rapid growth of information security threat. As an efficient multi-label classifier, kernel extreme learning machine (KELM) has been gradually used in intrusion detection system. However, the performance of KELM heavily relies on the kernel selection. In this paper, a novel multiple kernel extreme learning machine (MKELM) model combining the ReliefF with nature-inspired methods is proposed for intrusion detection. The MKELM is designed to estimate whether the attack is carried out and the ReliefF is used as a preprocessor of MKELM to select appropriate features. In addition, the nature-inspired methods whose fitness functions are defined based on the kernel alignment are employed to build the optimal composite kernel in the MKELM. The KDD99, NSL and Kyoto datasets are used to evaluate the performance of the model. The experimental results indicate that the optimal composite kernel function can be determined by using any heuristic optimization method, including PSO, GA, GWO, BA and DE. Since the filter-based feature selection method is combined with the multiple kernel learning approach independent of the classifier, the proposed model can have a good performance while saving a lot of training time.

• Annual Conference on Human and Language Technology
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• 1997.10a
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• pp.249-254
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• 1997

영어 웹 문서를 한국어로 기계번역을 하기 위해서는 HTML 태그를 번역 대상 문장과 분리하는 처리가 필요하다. HTML 태그를 단순히 제거하는 것이 아니라 대상 문장의 기계번역이 종료된 후에 같은 형태의 한국어 웹 문서로 복원하기 위한 방안이 마련 되어야 한다. 또한 문서 전처리기에서는 영어 형태소해석기의 성능을 높이기 위하여 번역 단위가 되는 문장의 인식 및 분리, 타이틀의 처리, 나열된 단어의 처리, 하이픈 처리, 고유명사 인식, 특수 문자 처리, 대소문자 정규화, 날짜 인식 등을 처리하여 문서의 정규화를 수행한다.

• The KSFM Journal of Fluid Machinery
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• v.1 no.1 s.1
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• pp.7-16
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• 1998

An interactive mode of grid generation system has been developed for a Navier-Stokes design procedure of axial flow compressors. The present grid generator adopts the multiblock H-grid structure, which simplifies the creation of computational grids about complex turbomachinery geometries and facilitate the manipulation of multiple grid blocks for multirow flow fields. The numerical algorithm adopts the combination of the algebraic and elliptic method to create the internal grids efficiently and quickly. The system consists of four separated modules, which are linked together with a common graphical user interface. The system input is made of the results of the preliminary design. The final grids generated from each module of the system are used as the preprocessor for the performance prediction of the two-or three-dimensional flow simulation inside the blade passage. Application to the blade design of the LP compressor was demonstrated to be very reliable and practical in support of design activities. This customized system are coupled strongly with the design procedure of the turbomachinery cascades using the Navier-Stokes technique.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.1
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• pp.205-213
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• 2003

The fiber reinforced composite material is widely used in the multi-industrial field where the weight reduction of the infrastructure is demanded because of their high specific modulus and specific strength. It has two main merits which are to cut down energy by reducing weight and to prevent explosive damage preceding to the sudden bursting which is generated by the pressure leakage condition. Therefore, Pressure vessels using this composite material in comparison with conventional metal vessels can be applied in the field such as defense industry, aerospace industry and rocket motor case where lightweight and the high pressure are demanded. In this paper, for nonlinear finite element analysis of E-glass/epoxy filament winding composite pressure vessel receiving an internal pressure, the standard interpretation model is developed by using the ANSYS, general commercial software, which is verified as the accuracy and useful characteristic of the solution based on Auto LISP and ANSYS APDL. Both the preprocessor for doing exclusive analysis of filament winding composite pressure vessel and postprocessor that simplifies result of analysis have been developed to help the design engineers.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2166-2176
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• 2017

Electricity price prediction plays a crucial part in making the schedule and managing the risk to the competitive electricity market participants. However, it is a difficult and challenging task owing to the characteristics of the nonlinearity, non-stationarity and uncertainty of the price series. This study proposes a hybrid improved strategy which incorporates data preprocessor components and a forecasting engine component to enhance the forecasting accuracy of the electricity price. In the developed forecasting procedure, the Seasonal Adjustment (SA) method and the Ensemble Empirical Mode Decomposition (EEMD) technique are synthesized as the data preprocessing component; the Coupled Simulated Annealing (CSA) optimization method and the Least Square Support Vector Regression (LSSVR) algorithm construct the prediction engine. The proposed hybrid approach is verified with electricity price data sampled from the power market of New South Wales in Australia. The simulation outcome manifests that the proposed hybrid approach obtains the observable improvement in the forecasting accuracy compared with other approaches, which suggests that the proposed combinational approach occupies preferable predication ability and enough precision.

• Journal of Advanced Navigation Technology
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• v.10 no.1
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• pp.48-56
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• 2006

This paper proposes an efficient preprocessing technique for a binary centroid tracker in correlated image sequences. It is known that the following factors determine the performance of the binary centroid target tracker: (1) an efficient real-time preprocessing technique, (2) an exact target segmentation from cluttered background images and (3) an intelligent tracking window sizing, and etc. The proposed centroid tracker consists of an adaptive segmentation method based on novel distance features and an efficient real-time preprocessing technique in order to enhance the distinction between the objects of interest and their local background. Various tracking experiments using synthetic images as well as real Forward-Looking InfraRed (FLIR) images are performed to show the usefulness of the proposed methods.