• Journal of Korea Multimedia Society
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• v.23 no.3
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• pp.468-475
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• 2020

In this paper, we proposed a three-dimensional visualization system for medical images in augmented reality based on deep learning. In the proposed system, the artificial neural network model performed fully automatic segmentation of the region of lung and pulmonary nodule from chest CT images. After applying the three-dimensional volume rendering method to the segmented images, it was visualized in augmented reality devices. As a result of the experiment, when nodules were present in the region of lung, it could be easily distinguished with the naked eye. Also, the location and shape of the lesions were intuitively confirmed. The evaluation was accomplished by comparing automated segmentation results of the test dataset to the manual segmented image. Through the evaluation of the segmentation model, we obtained the region of lung DSC (Dice Similarity Coefficient) of 98.77%, precision of 98.45%, recall of 99.10%. And the region of pulmonary nodule DSC of 91.88%, precision of 93.05%, recall of 90.94%. If this proposed system will be applied in medical fields such as medical practice and medical education, it is expected that it can contribute to custom organ modeling, lesion analysis, and surgical education and training of patients.

• Atmosphere
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• v.25 no.2
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• pp.339-351
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• 2015

The purpose of this study is for the fundamental understandings about building morphological parameters and aerodynamic roughness parameters of Seoul, Korea using the detailed urban geographic information datasets. Applied roughness parameter calculations are based on a digital map of buildings with lot area polygons. The quality of the developed roughness length ($z_0$) of Seoul was evaluated with densely installed 107 automatic weather stations. The correlation coefficient results between averaged wind speeds of AWS data and averaged $z_0$ is -0.303 in night and -0.398 in day (200 m radii circles case). Further $z_0$ enhancement should follow by considering other surface features such as high tree and orography of Seoul. However, this study would meet the needs to for local- or meso-scale meteorological modeling applications of Seoul. However, further studies would require for enhancing the $z_0$ applications of Seoul.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.1-10
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• 2001

In the reverse engineering, surfaces are modeled for new products by interpolating the digitized data points obtained by measuring the existing shapes. However, many measuring or deviation errors are happened during the measuring process. If these errors are ignored, designers could get undesirable results. Therefore, it is important to handle such errors and fairing procedure with the esthetics criteria is needed during surface modeling process. This paper presents algorithms for the fairing of B-spline surfaces. The algorithms are based on automatic repositioning of control points for B-spline surfaces. New positions of the control points are determined by solving a non-linear programming of which the objective functions are derived variously using derived surfaces and constraints are established by distance measures between the original and the modified control points. Changes in surface shapes are analyzed by illustrations of their shapes and continuous plotting of gaussian and mean curvatures.

• Journal of KIISE:Software and Applications
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• v.35 no.9
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• pp.529-537
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• 2008

Since concurrent software is hard to debug, the verification of such systems inevitably needs automatic tools which support exhaustive searching. Bounded Model Checking (BMC) is one of them. Within a bound k, BMC exhaustively check some errors in execution traces of the given system. In this paper, we introduce the tool that performs BMC for LTS, modeling language for concurrent programs. In this tool, a property is described by a FLTL formula, which is suitable to present the property with actions in a LTS model. To experiment with existential model checkers and out tool, we compare and analysis the performance of the developed tool and others.

• Journal of the Korean Society of Systems Engineering
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• v.12 no.1
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• pp.113-120
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• 2016

Steel in a continuous reheat furnace is heated to higher temperature to be treated in the rolling steel process. Due to this reason the continuous reheat furnace system requires an optimal control system to adjust the temperature inside the furnace. Level 2 control systems for continuous reheat furnaces generate automatic heating set points for the level 1 system of the furnace based on the mathematical thermal model which can give a good estimation of steel heating inside the furnace and is used to adjust heating requirements to optimize furnace combustion. For the current study the analytic methodology based on the design procedure from the systems engineering to develop new level 2 control system of a continuous reheat furnace was proposed. The system analysis and the requirements of the level 2 control system were derived using the unified modeling language (UML) 2.0, and the design of database and the graphic user interface (GUI) for the level 2 control system were conducted.

• Journal of Ship and Ocean Technology
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• v.10 no.2
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• pp.11-23
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• 2006

The model exchange from CAD system to CAE system in valid and effective manner is the major issue of automatic analysis modelling of ship structure. However, model exchange approaches based on the neutral CAD file have resulted in invalid model exchange that could not properly reflect the characteristics of CAD model and CAE model of ship structure. This paper presents the new approach of n-to-n mapping to exchange ship structure model in heterogeneous CAD/CAE environments. In this study, the common model called 'unified ship model for analysis' to directly extract proper information from different CAD systems for ship structural analysis is proposed. Moreover, a command language based model interfacing technique to construct an idealized model for analysis job is also proposed. The proposed approach has been actually implemented in DSME CAD/CAE environment of ship structure such as TRIBON system, PATRAN system and FLUENT system. The applicability and effectiveness of the proposed approach was verified by applying it to the real analysis project for fore-body of ship and block lifting. This application results show that the proposed approach can be effectively used for heterogeneous CAD/CAE environment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.118-124
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• 2010

We proposed a goods load simulator for optimum RFID distribution, which includes experiment process modeling guidelines for stable RFID scan rate, efficient cost-reduction of RFID application or even speedy management of RFID field. We show verification of this simulator using field test of distribution, and the proposed simulator has better performance than the classic method, and demonstrate the proposed is efficient method of draw up guidelines on RFID distribution.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.89-89
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• 2014

While the current consensus view holds that galaxy mergers are commonplace, it is sometimes speculated that Globular Clusters (GCs) may also have undergone merging events, possibly resulting in massive objects with a strong metallicity spread such as Omega Centauri. Galaxies are mostly far, unresolved systems whose mergers are most likely wet, resulting in observational as well as modeling difficulties, but GCs are resolved into stars that can be used as discrete dynamical tracers, and their mergers might have been dry, therefore easily simulated with an N-body code. It is however difficult to determine the observational parameters best suited to reveal a history of merging based on the positions and kinematics of GC stars, if evidence of merging is at all observable. To overcome this difficulty, we investigate the applicability of supervised and unsupervised machine learning to the automatic reconstruction of the dynamical history of a stellar system. In particular we test whether statistical clustering methods can classify simulated systems into monolithic versus merger products. We run direct N-body simulations of two identical King-model clusters undergoing a head-on collision resulting in a merged system, and other simulations of isolated King models with the same total number of particles as the merged system. After several relaxation times elapse, we extract a sample of snapshots of the sky-projected positions of particles from each simulation at different dynamical times, and we run a variety of clustering and classification algorithms to classify the snapshots into two subsets in a relevant feature space.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.1
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• pp.1-9
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• 2001

The development of flexible automation in the manufacturing industry is concerned with production activities performed by unmanned machining system A major topic relevant to metal-cutting operations is monitoring toll wear, which affects process efficiency and product quality, and implementing automatic toll replacements. In this paper, the measurement of the cutting force components has been found to provide a method for an in-process detection of tool wear. The static com-ponents of cutting force have been used to detect flank wear. To eliminate the influence of variations in cutting conditions, tools, and workpiece materials, the force modeling is performed for various cutting conditions. The normalized force dis-parities are defined in this paper, and the relationships between normalized disparity and flank were are established. Final-ly, artificial neural network is used to learn these relationships and detect tool wear. According to proposed method, the static force components could provide the effective means to detect flank wear for varying cutting conditions in turning operation.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.4
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• pp.439-449
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• 2018

In this paper, multi-objective optimization of a multi-bubble pressure cabin in the underwater glider with Blended-Wing-Body (BWB) is carried out using Kriging and the Non-dominated Sorting Genetic Algorithm (NSGA-II). Two objective functions are considered: buoyancy-weight ratio and internal volume. Multi-bubble pressure cabin has a strong compressive capacity, and makes full use of the fuselage space. Parametric modeling of the multi-bubble pressure cabin structure is automatic generated using UG secondary development. Finite Element Analysis (FEA) is employed to study the structural performance using the commercial software ANSYS. The weight of the primary structure is determined from the volume of the Finite Element Structure (FES). The stress limit is taken into account as the constraint condition. Finally, Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) method is used to find some trade-off optimum design points from all non-dominated optimum design points represented by the Pareto fronts. The best solution is compared with the initial design results to prove the efficiency and applicability of this optimization method.