• International Journal of Aeronautical and Space Sciences
• /
• v.14 no.4
• /
• pp.297-309
• /
• 2013

Design optimization is a mathematical process to find an optimal solution through the use of formal optimization algorithms. Design plays a vital role in the engineering field; therefore, using design tools in education and research is becoming more and more important. Recently, numerical design optimization in fluid mechanics, which uses computational fluid dynamics (CFD), has numerous applications in the engineering field, because of the rapid development of high-performance computing resources. However, it is difficult to find design optimization software and contents for educational purposes in aerospace engineering. In the present study, we have developed an aerodynamic design framework specifically for an airfoil, based on the EDucation-research Integration through Simulation On the Net (EDISON) portal. The airfoil design framework is composed of three subparts: a geometry kernel, CFD flow analysis, and an optimization algorithm. Through a seamless interface among the subparts, an iterative design process is conducted. In addition, the CFD flow analysis and the design framework are provided through a web-based portal system, while the computation is taken care of by a supercomputing facility. In addition to the software development, educational contents are developed for lectures associated with design optimization in aerospace and mechanical engineering education programs. The software and content developed in this study is expected to be used as a tool for e-learning material, for education and research in universities.

• The KIPS Transactions:PartB
• /
• v.16B no.1
• /
• pp.47-54
• /
• 2009

Automatic object recognition in 3D measuring data is of great interest in many application fields e.g. computer vision, reverse engineering and digital factory. In this paper we present a software tool for a fully automatic object detection and parameter estimation in unordered and noisy point clouds with a large number of data points. The software consists of three interactive modules each for model selection, point segmentation and model fitting, in which the orthogonal distance fitting (ODF) plays an important role. The ODF algorithms estimate model parameters by minimizing the square sum of the shortest distances between model feature and measurement points. The local quadric surface fitted through ODF to a randomly touched small initial patch of the point cloud provides the necessary initial information for the overall procedures of model selection, point segmentation and model fitting. The performance of the presented software tool will be demonstrated by applying to point clouds.

• Journal of KIISE:Computing Practices and Letters
• /
• v.15 no.12
• /
• pp.1008-1012
• /
• 2009

Obfuscation is known as one of the most effective methods to protect software against malicious reverse engineering transforming the software into more complicated one with still preserving the original semantic. However, obfuscating a program can increase both code size of the program and execution time compared to the original program. In mobile devices, the increases of code size and execution time incur the waste of resources including the increase of power consumption. This paper has analyzed the effectiveness of some high-level obfuscation algorithms as well as their power consumption with implementing them under an embedded board equipped with ARM processor. The analysis results show that there is (are) an efficient obfuscation method(s) in terms of execution time or power consumption according to characteristics of a given program.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.6
• /
• pp.1225-1236
• /
• 2020

Fuzzing is an automated software testing methodology that dynamically tests the security of software by inputting randomly generated input values outside of the expected range. KISA is releasing open source for standard cryptographic algorithms, and many crypto module developers are developing crypto modules using this source code. If there is a vulnerability in the open source code, the cryptographic library referring to it has a potential vulnerability, which may lead to a security accident that causes enormous losses in the future. Therefore, in this study, an appropriate security policy was established to verify the safety of block cipher source codes such as SEED, HIGHT, and ARIA, and the safety was verified using differential fuzzing. Finally, a total of 45 vulnerabilities were found in the memory bug items and error handling items, and a vulnerability improvement plan to solve them is proposed.

• Imaging Science in Dentistry
• /
• v.52 no.3
• /
• pp.303-308
• /
• 2022

Purpose: This technical report aims to describe and detail the use of micro-computed tomography for a reliable evaluation of the bulk-fill composite/tooth interface. Materials and Methods: Bulk-fill composite restorations in tooth cavities were scanned using micro-computed tomography to obtain qualitatively and quantitatively valuable information. Two-dimensional information was processed using specific algorithms, and ultimately a 3-dimensional (3D) specimen reconstruction was generated. The 3D rendering allowed the visualization of voids inside bulk-fill composite materials and provided quantitative measurements. The 3D analysis software VG Studio MAX was used to perform image analysis and assess gap formation within the tooth-restoration interface. In particular, to evaluate internal adaptation, the Defect Analysis addon module of VG Studio Max was used. Results: The data, obtained with the processing software, highlighted the presence and the shape of gaps in different colours, representing the volume of porosity within a chromatic scale in which each colour quantitatively represents a well-defined volume. Conclusion: Micro-computed tomography makes it possible to obtain several quantitative parameters, providing fundamental information on defect shape and complexity. However, this technique has the limit of not discriminating materials without radiopacity and with low or no filler content, such as dental adhesives, and hence, they are difficult to visualise through software reconstruction.

• Annual Conference of KIPS
• /
• 2021.05a
• /
• pp.411-414
• /
• 2021

One of the elements of technology that has become extremely critical within the field of education today is Deep learning. It has been especially used in the area of natural language processing, with some word-representation vectors playing a critical role. However, some of the low-resource languages, such as Swahili, which is spoken in East and Central Africa, do not fall into this category. Natural Language Processing is a field of artificial intelligence where systems and computational algorithms are built that can automatically understand, analyze, manipulate, and potentially generate human language. After coming to discover that some African languages fail to have a proper representation within language processing, even going so far as to describe them as lower resource languages because of inadequate data for NLP, we decided to study the Swahili language. As it stands currently, language modeling using neural networks requires adequate data to guarantee quality word representation, which is important for natural language processing (NLP) tasks. Most African languages have no data for such processing. The main aim of this project is to recognize and focus on the classification of words in English, Swahili, and Korean with a particular emphasis on the low-resource Swahili language. Finally, we are going to create our own dataset and reprocess the data using Python Script, formulate the syllabic alphabet, and finally develop an English, Swahili, and Korean word analogy dataset.

• Journal of KIISE:Software and Applications
• /
• v.31 no.9
• /
• pp.1233-1245
• /
• 2004

Though biometrics to authenticate a person is a good tool in terms of security and convenience, typical authentication algorithms using biometrics may not be executed on resource-constrained devices such as smart cards. Thus, to execute biometric processing on resource-constrained devices, it is desirable to develop lightweight authentication algorithm that requires only small amount of memory and computation. Also, among biological features, face is one of the most acceptable biometrics, because humans use it in their visual interactions and acquiring face images is non-intrusive. We present a new face authentication algorithm in this paper. Our achievement is two-fold. One is to present a face authentication algorithm with low memory requirement, which uses support vector machines (SVM) with the feature set extracted by genetic algorithms (GA). The other contribution is to suggest a method to reduce further, if needed, the amount of memory required in the authentication at the expense of verification rate by changing a controllable system parameter for a feature set size. Given a pre-defined amount of memory, this capability is quite effective to mount our algorithm on memory-constrained devices. The experimental results on various databases show that our face authentication algorithm with SVM whose input vectors consist of discriminating features extracted by GA has much better performance than the algorithm without feature selection process by GA has, in terms of accuracy and memory requirement. Experiment also shows that the number of the feature ttl be selected is controllable by a system parameter.

• Journal of KIISE:Software and Applications
• /
• v.35 no.12
• /
• pp.789-799
• /
• 2008

For the communication between human and computer in an interactive computing environment, the gesture recognition has been studied vigorously. The algorithms which use the 2D features for the feature extraction and the feature comparison are faster, but there are some environmental limitations for the accurate recognition. The algorithms which use the 2.5D features provide higher accuracy than 2D features, but these are influenced by rotation of objects. And the algorithms which use the 3D features are slow for the recognition, because these algorithms need the 3d object reconstruction as the preprocessing for the feature extraction. In this paper, we propose a method to extract the 3D features combined with the 3D object reconstruction in real-time. This method generates three kinds of 3D projection maps using the modified GPU-based visual hull generation algorithm. This process only executes data generation parts only for the gesture recognition and calculates the Hu-moment which is corresponding to each projection map. In the section of experimental results, we compare the computational time of the proposed method with the previous methods. And the result shows that the proposed method can apply to real time gesture recognition environment.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.3
• /
• pp.1-12
• /
• 2011

Large-sized multi-touch screen is usually made using infrared rays. That is because it has technical constraints or cost problems to make the screen with the other ways using such as existing resistive overlays, capacitive overlay, or acoustic wave. Using infrared rays to make multi-touch screen is easy, but is likely to have technical limits to be implemented. To make up for these technical problems, two other methods were suggested through Surface project, which is a next generation user-interface concept of Microsoft. One is Frustrated Total Internal Reflection (FTIR) which uses infrared cameras, the other is Diffuse Illumination (DI). FTIR and DI are easy to be implemented in large screens and are not influenced by the number of touch points. Although FTIR method has an advantage in detecting touch-points, it also has lots of disadvantages such as screen size limit, quality of the materials, the module for infrared LED arrays, and high consuming power. On the other hand, DI method has difficulty in detecting touch-points because of it's structural problems but makes it possible to solve the problem of FTIR. In this thesis, we study the algorithms for effectively correcting the distort phenomenon of optical lens, and image processing algorithms in order to solve the touch detecting problem of the original DI method. Moreover, we suggest calibration algorithms for improving the accuracy of multi-touch, and a new tracking technique for accurate movement and gesture of the touch device. To verify our approaches, we implemented a table-based multi touch screen.

• The Journal of Information Technology
• /
• v.3 no.2
• /
• pp.73-85
• /
• 2000

The efficient algorithms are suggested in this study for solving the multicommodity network flow problems applied to Communications Systems. These problems are typical NP-complete optimization problems that require integer solution and in which the computational complexity increases numerically in appropriate with the problem size. Although the suggested algorithms are not absolutely optimal, they are developed for computationally efficient and produce near-optimal and primal integral solutions. We supplement the traditional Lagrangian method with a price-directive decomposition. It proceeded as follows. First, A primal heuristic from which good initial feasible solutions can be obtained is developed. Second, the dual is initialized using marginal values from the primal heuristic. Generally, the Lagrangian optimization is conducted from a naive dual solution which is set as ${\lambda}=0$. The dual optimization converged very slowly because these values have sort of gaps from the optimum. Better dual solutions improve the primal solution, and better primal bounds improve the step size used by the dual optimization. Third, a limitation that the Lagrangian decomposition approach has Is dealt with. Because this method is dual based, the solution need not converge to the optimal solution in the multicommodity network problem. So as to adjust relaxed solution to a feasible one, we made efficient re-allocation heuristic. In addition, the computational performances of various versions of the developed algorithms are compared and evaluated. First, commercial LP software, LINGO 4.0 extended version for LINDO system is utilized for the purpose of implementation that is robust and efficient. Tested problem sets are generated randomly Numerical results on randomly generated examples demonstrate that our algorithm is near-optimal (< 2% from the optimum) and has a quite computational efficiency.