• Nuclear Engineering and Technology
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• v.31 no.2
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• pp.157-171
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• 1999

In this work, an automatic software verification method for Nuclear Power Plant (NPP) protection system is developed. This method utilizes Colored Petri Net (CPN) for system modeling and Prototype Verification System (PVS) for mathematical verification. In order to help flow-through from modeling by CPN to mathematical proof by PVS, an information extractor from CPN models has been developed in this work. In order to convert the extracted information to the PVS specification language, a translator also has been developed. ML that is a higher-order functional language programs the information extractor and translator. This combined method has been applied to a protection system function of Wolsong NPP SDS2(Steam Generator Low Level Trip). As a result of this application, we could prove completeness and consistency of the requirement logically. Through this work, in short, an axiom or lemma based-analysis method for CPN models is newly suggested in order to complement CPN analysis methods and a guideline for the use of formal methods is proposed in order to apply them to NPP Software Verification and Validation.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.2
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• pp.58-65
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• 2008

The finite element programs have been developed for structure, collision, flow, dynamics, heat transfer, acoustics, electromagnetism, MEMS (Micro Electro Mechanical Systems), and etc. These programs can be classified as either "package" program or "single purpose" program. Single purpose programs usually have convenient and powerful functions, but these programs have limited expandability to different fields of analysis. Therefore, the method to converter the analysis results of single purpose program to other programs is needed. In the research, multi-body data conversion methods of 1) finite element model and 2) solid model were created to convert fluid analysis result of CFD-ACE+ to ANSYS data structure. Automatic boundary condition algorithms were developed for blade, and finite element model was compared with solid model. It is expected that, by sealess data transfer, the Multi-body Data Conversion Program could reduce the development period of torque converters.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.43-48
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• 2002

This paper discusses the application of fuzzy-ARTMAP neural network to compensate the nonlinearity of satellite communication channel. The fuzzy-ARTMAP is the class of ART(adaptive resonance theory) architectures designed fur supervised loaming. It has capabilities not fecund in other neural network approaches, that includes a small number of parameters, no requirements fur the choice of initial weights, automatic increase of hidden units, and capability of adding new data without retraining previously trained data. By a match tracking process with vigilance parameter, fuzzy-ARTMAP neural network achieves a minimax teaming rule that minimizes predictive error and maximizes generalization. Thus, the system automatically leans a minimal number of recognition categories, or hidden units, to meet accuracy criteria. As a input-converting process for implementing fuzzy-ARTMAP equalizer, the sigmoid function is chosen to convert actual channel output to the proper input values of fuzzy-ARTMAP. Simulation studies are performed over satellite nonlinear channels. QPSK signals with Gaussian noise are generated at random from Volterra model. The performance of proposed fuzzy-ARTMAP equalizer is compared with MLP equalizer.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.57-62
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• 2003

Among the procedure of automatic fingerprint recognition, binary code is important for the optimum thinning and singular point extraction while reserving the fingerprint image data. Binarization is to convert gray scale images into 0s and 255s values. For this conversion, you should set up the proper threshold value not to lose fingerprint image data. In this paper, we suggest the method to extract the standard threshold in real-time from fingerprint images entered by applying artificial intelligent methods in the binary code procedure. We show improved features while comparing the experiment results with the existing methods.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.5-8
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• 2001

We propose a realtime numeric caption recognition algorithm that automatically recognizes the numeric caption generated by computer graphics (CG) and displays the modified caption using the recognized resource only when a valuable numeric caption appears in the aimed specific region of the live sportscast scene produced by other broadcasting stations. We extract the mesh feature from the enhanced binary image as a feature vector after acquiring the sports broadcast scenes using a frame grabber in realtime and then recover the valuable resource from just a numeric image by perceiving the character using the neural network. Finally, the result is verified by the knowledge-based rule set designed for more stable and reliable output and is displayed on a screen as the converted CC caption serving our purpose. At present, we have actually provided the realtime automatic mile-to-kilometer caption conversion system taking up our algorithm f3r the regular Major League Baseball (MLB) program being broadcasted live throughout Korea over our nationwide network. This caption conversion system is able to automatically convert the caption in mile universally used in the United States into that in kilometer in realtime, which is familiar to almost Koreans, and makes us get a favorable criticism from the TV audience.

• Journal of Ecology and Environment
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• v.41 no.5
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• pp.142-144
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• 2017

In recent decades, as it becomes increasingly important to monitor and research long-term ecological changes, worldwide attempts are being conducted to integrate and manage ecological data in a unified framework. Especially domestic ecological data in South Korea should be first standardized based on predefined common protocols for data integration, since they are often scattered over many different systems in various forms. Additionally, foreign ecological data should be converted into a proper unified format to be used along with domestic data for association studies. In this study, our interest is to integrate ECN data with Korean domestic ecological data under our unified framework. For this purpose, we employed our semi-automatic data conversion tool to standardize foreign data and utilized ground beetle (Carabidae) datasets collected from 12 different observatory sites of ECN. We believe that our attempt to convert domestic and foreign ecological data into a standardized format in a systematic way will be quite useful for data integration and association analysis in many ecological and environmental studies.

• The Transactions of the Korea Information Processing Society
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• v.1 no.1
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• pp.38-49
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• 1994

One of the most common problems encountered in the automatic translation of FORTRAN source code to VECTRAN is the occurrence of conditional transfer of control within loops. Transfers of control create control dependencies, in which the execution of a statement is dependent on the value of a variable in another statement. In this paper I propose algorithms involve an attempt to convert statements in the loop into conditional assignment statements that can be easily analyzed for data dependency, and this paper presents a simplification method for conditional assignment statement. Especially, I propose not only a method for simplifying boolean functions but extended method for n-state functions.

• Korean Journal of Construction Engineering and Management
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• v.5 no.5 s.21
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• pp.151-162
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• 2004

Current methods for construction site modeling employ large, expensive laser range scanners that produce dense range point clouds of a scene from different perspectives. Days of skilled interpretation and of automatic segmentation may be required to convert the clouds to a finished CAD model. The dynamic nature of the construction environment requires that a real-time local area modeling system be capable of handling a rapidly changing and uncertain work environment. However, in practice, large, simple, and reasonably accurate embodying volumes are adequate feedback to an operator who, for instance, is attempting to place materials in the midst of obstacles with an occluded view. For real-time obstacle avoidance and automated equipment control functions, such volumes also facilitate computational tractability. In this research, a human operator's ability to quickly evaluate and associate objects in a scene is exploited. The operator directs a laser range finder mounted on a pan and tilt unit to collect range points on objects throughout the workspace. These groups of points form sparse range point clouds. These sparse clouds are then used to create geometric primitives for visualization and modeling purposes. Experimental results indicate that these models can be created rapidly and with sufficient accuracy for automated obstacle avoidance and equipment control functions.

• Journal of Information Processing Systems
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• v.4 no.4
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• pp.121-132
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• 2008

VLSI chips have been tested using various automatic test equipment (ATE). Although each ATE has a similar structure, the language for ATE is proprietary and it is not easy to convert a test program for use among different ATE vendors. To address this difficulty we propose a tester structure expression language, a tester language with a novel format. The developed language is called the general tester language (GTL). Developing an interpreter for each tester, the GTL program can be directly applied to the ATE without conversion. It is also possible to select a cost-effective ATE from the test program, because the program expresses the required ATE resources, such as pin counts, measurement accuracy, and memory capacity. We describe the prototype environment for the GTL and the tester selection tool. The software size of the prototype is approximately 27,800 steps and 15 manmonths were required. Using the tester selection tool, the number of man-hours required in order to select an ATE could be reduced to 1/10. A GTL program was successfully executed on actual ATE.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.49-62
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• 2023

There has been a rapid increase in the creation and alteration of new malware samples which is a huge financial risk for many organizations. There is a huge demand for improvement in classification and detection mechanisms available today, as some of the old strategies like classification using mac learning algorithms were proved to be useful but cannot perform well in the scalable auto feature extraction scenario. To overcome this there must be a mechanism to automatically analyze malware based on the automatic feature extraction process. For this purpose, the dynamic analysis of real malware executable files has been done to extract useful features like API call sequence and opcode sequence. The use of different hashing techniques has been analyzed to further generate images and convert them into image representable form which will allow us to use more advanced classification approaches to classify huge amounts of images using deep learning approaches. The use of deep learning algorithms like convolutional neural networks enables the classification of malware by converting it into images. These images when fed into the CNN after being converted into the grayscale image will perform comparatively well in case of dynamic changes in malware code as image samples will be changed by few pixels when classified based on a greyscale image. In this work, we used VGG-16 architecture of CNN for experimentation.