• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.147-154
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• 2024

This study focuses on the path planning algorithm for large-scale autonomous delivery using drones and robots in urban environments. When generating delivery routes in urban environments, it is essential that avoid obstacles such as buildings, parking lots, or any other obstacles that could cause property damage. A commonly used method for obstacle avoidance is the grid-based A* algorithm. However, in large-scale urban environments, it is not feasible to set the resolution of the grid too high. If the grid cells are not sufficiently small during path planning, inefficient paths might be generated when avoiding obstacles, and smaller obstacles might be overlooked. To solve these issues, this study proposes a method that initially creates a low-resolution wide-area grid and then progressively reduces the grid cell size in areas containing registered obstacles to maintain real-time efficiency in generating paths. To implement this, obstacles in the operational area must first be registered on the map. When obstacle information is updated, the cells containing obstacles are processed as a primary subdivision, and cells closer to the obstacles are processed as a secondary subdivision. This approach is validated in a simulation environment and compared with the previous research according to the computing time and the path distance.

• Coupled systems mechanics
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• v.8 no.2
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• pp.99-109
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• 2019

This work investigates the accuracy and performance of a $FE^2$ multi-scale implementation used to predict the behavior of composite materials. The equations are formulated assuming the small deformations solid mechanics approach in non-linear material models with hardening plasticity. The uniform strain boundary conditions are applied for the macro-to-micro transitions. A parallel algorithm was implemented in order to solve large engineering problems. The scheme proposed takes advantage of the domain decomposition method at the macro-scale and the coupling between each subdomain with a micro-scale model. The precision of the method is validated with a composite material problem and scalability tests are performed for showing the efficiency.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1646-1648
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• 1991

new system of a two dimensional large scale laser digitizer with a cordless cursor is proposed-it provides an easiness of setting devices and a high accuracy of measurement.

• Electronics and Telecommunications Trends
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• v.9 no.3
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• pp.69-96
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• 1994

본고에서는 캐시 동일성 유지 기법들을 분류하여 그 특성들을 개략적으로 살펴본 후 대규모 다중프로세서를 위해 제안된 것 중 몇몇 특색있는 것들을 살펴본다.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.110.3-110
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• 2002

$\textbullet$ Lane detection by TFALDA $\textbullet$ SVM for large scale data and multiclass classification problem $\textbullet$ TLC Classification $\textbullet$ Lateral offset estimation by IPT $\textbullet$ Lane departure warning by a fuzzy system $\textbullet$ Experimental results by HiLS $\textbullet$ Conclusion

• Journal of The Korean Astronomical Society
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• v.29 no.spc1
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• pp.27-29
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• 1996

We describe the formation of large-scale inhomogeneous structure of expa-nding Universe on the basic of two components system-usual nonrelativistic particles and dark matter, with taking into account their interaction.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.8
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• pp.333-340
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• 1986

This paper presents an approach for determining the discrete reduced-order models for largescale system by using matrix sign function. We define projection operators based on the matrix sign function and develop the algorithm for model-reduction by using them. Simulation studies show that the proposed altgorithm is very useful.

• IE interfaces
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• v.15 no.2
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• pp.159-171
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• 2002

Data Warehouses integrate data from multiple heterogeneous information sources and transform them into a multidimensional representation for decision support applications. Data warehousing has emerged as one of the most powerful tools in delivering information to users. Most previous researches have focused on marketing, customer service, financing, and insurance industry. Further, relatively less research has been done on data warehouse systems in the complex manufacturing industry such as ship production, which is characterized complex product structures and production processes. In the ship production, data warehouse systems is a requisite for effective cost analysis because collecting and analysis of diverse and large of cost-related(material/production cost, productivity) data in its operational systems, was becoming increasingly cumbersome and time consuming. This paper proposes architecture of the data warehouse systems to support cost analysis in the ship production. Also, in order to illustrate the usefulness of the proposed architecture, the prototype system is designed and implemented with the object of the enterprise of producing a large-scale ship.

• Smart Structures and Systems
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• v.7 no.5
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• pp.329-348
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• 2011

Large-scale earthquakes pose serious threats to infrastructure causing substantial damage and large residual deformations. Superelastic (SE) Shape-Memory-Alloys (SMAs) are unique alloys with the ability to undergo large deformations, but can recover its original shape upon stress removal. The purpose of this research is to exploit this characteristic of SMAs such that concrete Beam-Column Joints (BCJs) reinforced with SMA bars at the plastic hinge region experience reduced residual deformation at the end of earthquakes. Another objective is to evaluate the seismic performance of SMA Reinforced Concrete BCJs repaired with flowable Structural-Repair-Concrete (SRC). A $\frac{3}{4}$-scale BCJ reinforced with SMA rebars in the plastic-hinge zone was tested under reversed cyclic loading, and subsequently repaired and retested. The joint was selected from an RC building located in the seismic region of western Canada. It was designed and detailed according to the NBCC 2005 and CSA A23.3-04 recommendations. The behaviour under reversed cyclic loading of the original and repaired joints, their load-storey drift, and energy dissipation ability were compared. The results demonstrate that SMA-RC BCJs are able to recover nearly all of their post-yield deformation, requiring a minimum amount of repair, even after a large earthquake, proving to be smart structural elements. It was also shown that the use of SRC to repair damaged BCJs can restore its full capacity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.3942-3961
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• 2019

Recently, the models of deep super-resolution networks can successfully learn the non-linear mapping from the low-resolution inputs to high-resolution outputs. However, for large scaling factors, this approach has difficulties in learning the relation of low-resolution to high-resolution images, which lead to the poor restoration. In this paper, we propose Stage Generative Adversarial Networks (Stage-GAN) with semantic maps for image super-resolution (SR) in large scaling factors. We decompose the task of image super-resolution into a novel semantic map based reconstruction and refinement process. In the initial stage, the semantic maps based on the given low-resolution images can be generated by Stage-0 GAN. In the next stage, the generated semantic maps from Stage-0 and corresponding low-resolution images can be used to yield high-resolution images by Stage-1 GAN. In order to remove the reconstruction artifacts and blurs for high-resolution images, Stage-2 GAN based post-processing module is proposed in the last stage, which can reconstruct high-resolution images with photo-realistic details. Extensive experiments and comparisons with other SR methods demonstrate that our proposed method can restore photo-realistic images with visual improvements. For scale factor ${\times}8$, our method performs favorably against other methods in terms of gradients similarity.