• International journal of advanced smart convergence
• /
• v.12 no.4
• /
• pp.361-369
• /
• 2023

Achieving realistic visual quality while maintaining optimal real-time rendering performance is a major challenge in evolving computer graphics and interactive 3D applications. Normal mapping, as a core technology in 3D, has matured through continuous optimization and iteration. Hybrid normal mapping as a new mapping model has also made significant progress and has been applied in the 3D asset production pipeline. This study comprehensively explores the hybrid normal techniques, analyzing Linear Blending, Overlay Blending, Whiteout Blending, UDN Blending, and Reoriented Normal Mapping, and focuses on how the various hybrid normal techniques can be used to achieve rendering performance and visual fidelity. performance and visual fidelity. Under the consideration of computational efficiency, visual coherence, and adaptability in different 3D production scenes, we design comparative experiments to explore the optimal solutions of the hybrid normal techniques by analyzing and researching the code, the performance of different hybrid normal mapping in the engine, and analyzing and comparing the data. The purpose of the research and summary of the hybrid normal technology is to find out the most suitable choice for the mainstream workflow based on the objective reality. Provide an understanding of the hybrid normal mapping technique, so that practitioners can choose how to apply different hybrid normal techniques to the corresponding projects. The purpose of our research and summary of mixed normal technology is to find the most suitable choice for mainstream workflows based on objective reality. We summarized the hybrid normal mapping technology and experimentally obtained the advantages and disadvantages of different technologies, so that practitioners can choose to apply different hybrid normal mapping technologies to corresponding projects in a reasonable manner.

• Journal of Platform Technology
• /
• v.11 no.6
• /
• pp.89-105
• /
• 2023

With the development of information technology, most of the information has been converted into digital information, leading to the Big Data era. The demand for search platform has increased to enhance accessibility and usability of information in the databases. Big data search software platforms consist of two main components: (1) an indexing component to generate and store data indices for a fast and efficient data search and (2) a searching component to look up the given data fast. As an amount of data has explosively increased, data indexing performance has become a key performance bottleneck of big data search platforms. Though many companies adopted big data search platforms, relatively little research has been made to improve indexing performance. This research study employs Elasticsearch platform, one of the most famous enterprise big data search platforms, and builds physical clusters of 3 nodes to investigate optimal indexing performance configurations. Our comprehensive experiments and studies demonstrate that the proposed optimal Elasticsearch configuration achieves high indexing performance by an average of 3.13 times.

• Proceedings of the Korean Society for Technology of Plasticity Conference
• /
• 2007.05a
• /
• pp.401-404
• /
• 2007

Inertia welding is a solid-state welding process in which butt welds in materials are made in bar and in ring form at the joint face, and energy required for welding is obtained from a rotating flywheel. The stored energy is converted to frictional heat at the interface under axial load. The quality of the welded joint depends on many parameters, including axial force, initial revolution speed and energy, amount of upset, working time, and residual stresses in the joint. Inertia welding was conducted to make the large rotor shaft for low speed marine diesel engine, alloy steel for shaft of 140mm. Due to different material characteristics, such as, thermal conductivity and flow stress, on the two sides of the weld interface, modeling is crucial in determining the optimal weld geometry and parameters. FE simulation was performed by the commercial code DEFORM-2D. A good agreement between the predicted and actual welded shape is observed. It is expected that modeling will significantly reduce the number of experimental trials needed to determine the weld parameters.

• Computers and Concrete
• /
• v.6 no.3
• /
• pp.253-268
• /
• 2009

This study aims to develop a cost-based high-performance concrete (HPC) mix optimization system based on an integrated approach using artificial neural networks (ANNs) and genetic algorithms (GA). ANNs are used to predict the three main properties of HPC, namely workability, strength and durability, which are used to evaluate fitness and constraint violations in the GA process. Multilayer back-propagation neural networks are trained using the results obtained from experiments and previous research. The correlation between concrete components and its properties is established. GA is employed to arrive at an optimal mix proportion of HPC by minimizing its total cost. A system prototype, called High Performance Concrete Mix-Design System using Genetic Algorithm and Neural Networks (HPCGANN), was developed in MATLAB. The architecture of the proposed system consists of three main parts: 1) User interface; 2) ANNs prediction models software; and 3) GA engine software. The validation of the proposed system is carried out by comparing the results obtained from the system with the trial batches. The results indicate that the proposed system can be used to enable the design of HPC mix which corresponds to its required performance. Furthermore, the proposed system takes into account the influence of the fluctuating unit price of materials in order to achieve the lowest cost of concrete, which cannot be easily obtained by traditional methods or trial-and-error techniques.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.11
• /
• pp.5140-5147
• /
• 2012

It is difficult for systematic and flexible control reflecting regional characteristics with only public policies that control the landscape. Also, in the event that there is no preceding quantitative index calculation, it is impossible for the public society to come to an agreement. Therefore, the development of a shielding analysis simulation methodology that makes data processing modeling that can be interlinked with the urban information system is a very meaningful study. Thus, this study presents urban space shielding simulation technologies and quantitative analysis methodologies using 3D graphic engines and deduces the optimal design by integrating the data of the geographic information system (GIS) in order to suggest the potential as an analysis model that can be used in future urban information systems.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• v.y2005m4
• /
• pp.291-298
• /
• 2005

Linear acoustic analysis has been performed to elucidate damping characteristics of acoustic cavities. Results have shown that resonant frequencies of acoustic cavity obtained by classical theoretic approach and present linear analysis are somewhat different from each other. This difference is due to the limitation of classical theory. To quantify the damping characteristics, acoustic impedance has been introduced and resultant absorption and conductance have been evaluated. Satisfactory agreement has been achieved with previous experiment. Finally the design procedure for optimal tuning of acoustic cavity has been established

• Journal of the Korean Society for Precision Engineering
• /
• v.27 no.1
• /
• pp.25-32
• /
• 2010

With the latest automobile technology, though the third generation common rail system requires high injection pressures up to 1,800bar, the next generation diesel engine is expected to require more higher pressures than the third generation. The common rail pipe requires higher strength because it is one of the parts in the common rail system, which is influenced directly by fuel under high pressure. Preform design is very important for preventing head of the common rail pipe from folding in the heading process. In this study, die angle, curvature, outer diameter of die and length of trapped part are selected as main parameters to obtain best preform shape minimizing radius of folding. Therefore optimal design is carried out by finite element analysis and Taguchi method through main parameters. Results of the finite element analysis have good agreements with those of the experiments in the actual field.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1995.10a
• /
• pp.124-140
• /
• 1995

The merit of fuzzy rule based systems stems from their capability of encoding qualitative knowledge of experts into quantitative rules. Recent advancement in automatic tuning or self-organization of fuzzy rules from experimental data further enhances their power, allowing the integration of the top-down encoding of knowledge with the bottom-up learning of rules. In this paper, methods of self-organizing fuzzy rules and of performing defuzzification and inference is presented based on a multi-resolution radial basis function network. The network learns an arbitrary input-output mapping from sample distribution as the union of hyper-ellipsoidal clusters of various locations, sizes and shapes. The hyper-ellipsoidal clusters, representing fuzzy rules, are self-organized based of global competition in such a way as to ensute uniform mapping errors. The cooperative interpolation among the multiple clusters associated with a mapping allows the network to perform a bidirectional many-to-many mapping, representing a particular from of defuzzification. Finally, an inference engine is constructed for the network to search for an optimal chain of rules or situation transitions under the constraint of transition feasibilities imposed by the learned mapping. Applications of the proposed network to skill acquisition are shown.

• Aerospace Engineering and Technology
• /
• v.9 no.2
• /
• pp.168-175
• /
• 2010

During feeding oxidizer to the engine, vortices are occurred at lower dome of oxidizer tank inside by various working environments and external forces for liquid propellant feeding system of space launch vehicle. To eliminate the vortices or swirls Anti-Vortex Devices(AVD) shall be installed at inside lower oxidizer tank. Using the numerical analysis, we have confirmed the performance of AVD and analyzed the mass flow rate by feeding time and magnitudes of swirls on the free surface of oxidizer or exit surface according to the AVD number and length. Then we could derive the optimal design of the AVD number and length.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.4
• /
• pp.1579-1602
• /
• 2020

In the design of production system, buffer capacity allocation is a major step. Through polymorphism analysis of production capacity and production capability, this paper investigates a buffer allocation optimization problem aiming at the multi-stage production line including unreliable machines, which is concerned with maximizing the system theoretical production rate and minimizing the system state entropy for a certain amount of buffers simultaneously. Stochastic process analysis is employed to establish Markov models for repairable modular machines. Considering the complex structure, an improved vector UGF (Universal Generating Function) technique and composition operators are introduced to construct the system model. Then the measures to assess the system's multi-state reliability and structural complexity are given. Based on system theoretical production rate and system state entropy, mathematical model for buffer capacity optimization is built and optimized by a specific genetic algorithm. The feasibility and effectiveness of the proposed method is verified by an application of an engine head production line.