• Journal of the Korean Institute of Intelligent Systems
• /
• v.20 no.6
• /
• pp.748-754
• /
• 2010

To reduce the computational cost required for assembling vessel fragments using surface geometry, this paper proposes a fast axis estimation method. Using circular constraint of pottery and local planar patch assumption, it finds the axis of the symmetry. First, the circular constraint on each cylinder is used. A circular symmetric pot can be thought of unions of many cylinders with different radii. It selects one arbitrary point on the pot fragment surface and searches a path where a circumference exists on that point. The variance of curvature will be calculated along the path and the path with the minimum variance will be selected. The symmetric axis will pass through the center of that circle. Second, the planar patch assumption and profile curve is used. The surface of fragment is divided into small patches and each patch is assumed as plane. The surface normal of each patch will intersects the axis in 3D space since each planar patch faces the center of the pot. A histogram method and minimization of the profile curve error are utilized to find the probability distribution of the axis location. Experimental results demonstrate the improvement in speed and robustness of the algorithms.

• The Journal of the Acoustical Society of Korea
• /
• v.30 no.2
• /
• pp.63-72
• /
• 2011

Since the detection probability is critically dependent on the target strength (TS) in active sonar and on the radiated noise level (RNL) in passive sonar, the acoustic materials for echo reduction (ER) and transmission loss (TL) are widely used for the stealth of underwater targets. In this paper, a measurement system based on the small water tank, for the frequency range of greater than 30 kHz, is developed and verified using reference targets. In order to design the water tank and the geometry of test samples, a program is developed to calculate the arrival time of interfering signals due to the reflection from water tank walls and also due to the diffraction from the edge of the test samples. Considering all the interfering signals, an optimal experimental configuration for water tank and test samples is designed and used throughout the experiment. Next, the signal processing algorithms to estimate ER and TL are developed based on the measured propagation loss reflecting the geometric spreading characteristics of the transducer. Finally, a set of reference targets such as aluminium plate and perfectly reflecting plate are used in a small water tank to verify the developed measurement system.

• Journal of Intelligence and Information Systems
• /
• v.9 no.3
• /
• pp.193-205
• /
• 2003

In this paper, we suggest user authentication and authorization system for internet banking by face recognition. The system is one of Biometrics technology to verify and authorize personnel identification and is more unobtrusive than the other technologies, because they use physiological characteristics such as fingerprint, hand geometry, iris to their system that people have to touch it. Also, the face recognition system requires only a few devices such as a camera and keypad, so it is easy to apply it to the real world. The face recognition algorithms open to the public are separated by their analysis method differ from what characteristic of the human face use. There are PCA (principal Component Analysis), ICA (Independent Component Analysis), FDA (Fisher Discriminant Analysis). Among these, physiological data of encrypted form is translated utilizing PCA which is the most fundamental algorithm that analyze face feature, and we suggests design method of user authentication system that can do send-receive fast and exactly.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.5
• /
• pp.284-293
• /
• 2016

One of the most efficient procedures for the solution of partial differential equations is the method of differential quadrature. The differential quadrature method (DQM) has been applied to a large number of cases to overcome the difficulties of complex algorithms of computer programming, as well as the excessive use of storage due to the conditions of complex geometry and loading. The in-plane vibrations of curved beams with extensibility of the arch axis, including the effects of rotatory inertial and shear deformation, are analyzed by the DQM. The fundamental frequencies are calculated for members with various slenderness ratios, shearing flexibilities, boundary conditions, and opening angles. The results are compared with the numerical results obtained by other methods for cases in which they are available. The DQM gives good mathematical precision even when only a limited number of grid points is used, and new results according to diverse variations are also suggested.

• The KIPS Transactions:PartA
• /
• v.14A no.3 s.107
• /
• pp.151-158
• /
• 2007

Quadtree, which is a hierarchical data structure, is a very important data structure to represent images. The linear quadtree representation as a way to store a quadtree is efficient to save space compared with other representations. Therefore, it has been widely studied to develop efficient algorithms to execute operations related with quadtrees. The computation of block location is one of important geometry operations in image processing, which extracts a component completely including a given block. In this paper, we present a constant time algorithm to compute the block location of images represented by quadtrees, using three-dimensional $n\times n\times n$ processors on RMESH(Reconfigurable MESH). This algorithm has constant-time complexity by using efficient basic operations to deal with the locational codes of quardtree on the hierarchical structure of $n\times n\times n$ RMESH.

• Steel and Composite Structures
• /
• v.25 no.6
• /
• pp.663-670
• /
• 2017

The problem of layup optimization of the composite laminates involves a very complex multidimensional solution space which is usually non-exhaustively explored using different heuristic computational methods such as genetic algorithms (GA). To ensure the convergence to the global optimum of the applied heuristic during the optimization process it is necessary to evaluate a lot of layup configurations. As a consequence the analysis of an individual layup configuration should be fast enough to maintain the convergence time range to an acceptable level. On the other hand the mechanical behavior analysis of composite laminates for any geometry and boundary condition is very convoluted and is performed by computational expensive numerical tools such as finite element analysis (FEA). In this respect some studies propose very fast FEA models used in layup optimization. However, the lower bound of the execution time of FEA models is determined by the global linear system solving which in some complex applications can be unacceptable. Moreover, in some situation it may be highly preferred to decrease the optimization time with the cost of a small reduction in the analysis accuracy. In this paper we explore some machine learning techniques in order to estimate the failure of a layup configuration. The estimated response can be qualitative (the configuration fails or not) or quantitative (the value of the failure factor). The procedure consists of generating a population of random observations (configurations) spread across solution space and evaluating using a FEA model. The machine learning method is then trained using this population and the trained model is then used to estimate failure in the optimization process. The results obtained are very promising as illustrated with an example where the misclassification rate of the qualitative response is smaller than 2%.

• Journal of the Korean Society of Mechanical Technology
• /
• v.13 no.1
• /
• pp.17-22
• /
• 2011

As the quality of a weld joint is strongly influenced by process parameters the welding process, an intelligent algorithms that can predict the bead geometry and shape to accomplish the desired mechanical properties of the weldment should be developed. In this study, prepared by ${\Phi}1.6mm$ GMA welding of metal wire nose Advice jowelui 350A 600A grade level inverter welder and DAIHEN SCR's were carried out using welding. Welding conditions were 5.5m/min wire feed rate the welding current is rapidly transmit approximately 260A, welding voltage was about 30V. CTWD a 22mm, shielding gas was Ar 20L/min and the welding speed was a 240mm/min. Using data collected during welding equipment welding current and welding voltage waveform was analyzed by measuring the volume of the transition mode. Addition of $CaCO_3$ as a loss of the spread of the weld bead dilution rate decreased, suggesting that, GMA in the overlay welding bead shape control, dilution control and may be used as a welding flux is considered. Stabilizing effect of the arc by the Ca-containing $CaF_2$, $CaCO_3$, $CaMg(CO_3)_2$, respectively, welding flux 0.1wt.% added GMA welding and weld overlay were evaluated with dilution, $CaF_2$, and $CaMg(CO_3)_2$ added to the dilution of Seemed to increase.

• Korean Journal of Remote Sensing
• /
• v.19 no.6
• /
• pp.421-430
• /
• 2003

The extraction technique for Doppler information(Doppler centroid frequency(f$_{dc}$) and it's rate(f$_{r}$) is very important to make an image from the radar echo signal data. Clutterlock and auto-focusing techniques have been widely used to extract accurate Doppler information. But both techniques are not easy to implement in SAR processor and need quite lots of time to calculate accurate f$_{dc}$ and f$_{r}$ because they are generally based on echo signal data only. In this paper we suggest hybrid method for Doppler extraction using both of echo signal data and orbital and attitude information of satellite. In this method CDE(Correlation Doppler Estimation) technique is only used to estimate exact modular f$_{dc}$ using received echo signal data and rest of other algorithms are based on simple mathematical model of geometry between satellite and ground targets as well as the Doppler frequency ambiguity resolving problem. The experimental results using Radarsat-1 signal data shows that the proposed method can be effectively used for the extraction of Doppler information.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.41 no.3
• /
• pp.277-288
• /
• 2021

Building information modeling (BIM) element to industry foundation classes (IFC) entity mappings need to be checked to ensure the semantic integrity of BIM models. Existing studies have demonstrated that machine learning algorithms trained on geometric features are able to classify BIM elements, thereby enabling the checking of these mappings. However, reliance on geometry is limited, especially for elements with similar geometric features. This study investigated the employment of relational data between elements, with the assumption that such additions provide higher classification performance. Neural structured learning, a novel approach for combining structured graph data as features to machine learning input, was used to realize the experiment. Results demonstrated that a significant improvement was attained when trained and tested on eight BIM element types with their relational semantics explicitly represented.

• International Journal of Computer Science & Network Security
• /
• v.22 no.9
• /
• pp.195-207
• /
• 2022

COVID-19 has remained one of the most serious health crises in recent history, resulting in the tragic loss of lives and significant economic impacts on the entire world. The difficulty of controlling COVID-19 poses a threat to the global health sector. Considering that Artificial Intelligence (AI) has contributed to improving research methods and solving problems facing diverse fields of study, AI algorithms have also proven effective in disease detection and early diagnosis. Specifically, acoustic features offer a promising prospect for the early detection of respiratory diseases. Motivated by these observations, this study conceptualized a speech-based diagnostic model to aid in COVID-19 diagnosis. The proposed methodology uses speech signals from confirmed positive and negative cases of COVID-19 to extract features through the pre-trained Visual Geometry Group (VGG-16) model based on Mel spectrogram images. This is used in addition to the K-means algorithm that determines effective features, followed by a Genetic Algorithm-Support Vector Machine (GA-SVM) classifier to classify cases. The experimental findings indicate the proposed methodology's capability to classify COVID-19 and NOT COVID-19 of varying ages and speaking different languages, as demonstrated in the simulations. The proposed methodology depends on deep features, followed by the dimension reduction technique for features to detect COVID-19. As a result, it produces better and more consistent performance than handcrafted features used in previous studies.