• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.9-20
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• 2010

In order to visualize participating media in 3D space, they usually calculate the incoming radiance by subdividing the ray path into small subintervals, and accumulating their respective light energy due to direct illumination, scattering, absorption, and emission. Among these light phenomena, scattering behaves in very complicated manner in 3D space, often requiring a great deal of simulation efforts. To effectively simulate the light scattering effect, several approximation techniques have been proposed. Volume photon mapping takes a simple approach where the light scattering phenomenon is represented in volume photon map through a stochastic simulation, and the stored information is explored in the rendering stage. While effective, this method has a problem that the number of necessary photons increases very fast when a higher variance reduction is needed. In an attempt to resolve such problem, we propose a different approach for rendering particle-based volume data where kernel smoothing, one of several density estimation methods, is explored to represent and reconstruct the light in-scattering effect. The effectiveness of the presented technique is demonstrated with several examples of volume data.

• Journal of the Korean Magnetics Society
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• v.26 no.2
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• pp.39-44
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• 2016

Determination of the structural, electronic, and magnetic properties of the magnetically doped bismuth-telluride alloys are drawing lots of interest in the fields of the thermoelectric application as well as the research on magnetic interaction and topological insulator. In this study, we performed the first-principles electronic structure calculations within the density functional theory for the Gd doped bismuth-tellurides in order to study its magnetic properties and magnetic phase stability. All-electron FLAPW (full-potential linearized augmented plane-wave) method is employed and the exchange correlation potentials of electrons are treated within the generalized gradient approximation. In order to describe the localized f-electrons of Gd properly, the Hubbard +U term and the spin-orbit coupling of the valence electrons are included in the second variational way. The results show that while the Gd bulk prefers a ferromagnetic phase, the total energy differences between the ferromagnetic and the antiferromagnetic phases of the Gd doped bismuth-telluride alloys are about ~1meV/Gd, indicating that the stable magnetic phase may be changed sensitively depending on the structural change such as defects or strains.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.155-161
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• 2020

In general, optimization problems are difficult to solve simply. The reason is that the given problem is solved as soon as it is simple, but the more complex it is, the very large number of cases. This study is about the optimization of AI neural network. What we are dealing with here is the relief method for constructing AI network. The main topics deal with non-deterministic issues such as the stability and unstability of the overall network state, cost down and energy down. For this one, we discuss associative memory models, that is, a method in which local minimum memory information does not select fake information. The simulated annealing, this is a method of estimating the direction with the lowest possible value and combining it with the previous one to modify it to a lower value. And nonlinear planning problems, it is a method of checking and correcting the input / output by applying the appropriate gradient descent method to minimize the very large number of objective functions. This research suggests a useful approach to relief method as a theoretical approach to solving optimization problems. Therefore, this research will be a good proposal to apply efficiently when constructing a new AI neural network.

• Journal of the Korean Institute of Gas
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• v.18 no.1
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• pp.46-51
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• 2014

The purpose of this paper is to study of the vehicle lamp manufacturing system composing ultrasonic waves connection process. Making lamp assembly plant, it was produced in the separate process as the injection molding, ultrasonic waves bonding, annealing in the constant temperature, lamp assembling and packing. But the improvement method producing the lamp was added with one-step process by one automation technique. As a result, welding with ultrasonic waves process, the method decreased the energy consumption and noise during ultrasonic waves welding. Therefore, this method used the mathematics modeling for checking validity, it selected the stability and suitable controller using transfer function of plant and bode chart. In this study, the $180^{\circ}$ revolution control system to turn injection part upside down was $M_{eq}\;lcos{\theta}(t)$ because of gravity influence. It effected to unstable condition a system. For solving this problem, it aimed the linearization and stabilization of system by elimination $M_{eq}\;lcos{\theta}(t)$ as applying Free-forward control technique.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.18 no.2
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• pp.217-225
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• 2020

Concrete waste accounts for approximately 70~80% of the total waste generated during the decommissioning of nuclear power plants (NPPs). Based upon the concentration of each radionuclide, the concrete waste from the decommissioning can be used in the determination of the clearance threshold used to classify waste as radioactive. To reduce the cost of radioactive concrete waste disposal, it is important to perform decontamination before self-disposal or limited recycling. Therefore, it is necessary to estimate the internal radioactivity distribution of radioactive concrete waste to ensure effective decontamination. In this study, the performance metrics of various Compton reconstruction algorithms were compared in order to identify the best strategy to estimate the internal radioactivity distribution in concrete waste during the decommissioning of NPPs. Four reconstruction algorithms, namely, simple back-projection, filtered back-projection, maximum likelihood expectation maximization (MLEM), and energy-deconvolution MLEM (E-MLEM) were used as Compton reconstruction algorithms. Subsequently, the results obtained by using these various reconstruction algorithms were compared with one another and evaluated, using quantitative evaluation methods. The MLEM and E-MLEM reconstruction algorithms exhibited the best performance in maintaining a high image resolution and signal-to-noise ratio (SNR), respectively. The results of this study demonstrate the feasibility of using Compton images in the estimation of the internal radioactive distribution of concrete during the decommissioning of NPPs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.660-667
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• 2018

This study examined the optimal manufacturing conditions of RDF using heat-dried sludge from sewage treatment plant in Cheonan with the oil-drying method. The amounts of oil evaporation and oil drying of the heat-dried sludge were measured at different temperatures to evaluate the value of the product. The performance of the product was then measured using a calorimeter and TGA. In addition, the concentration of odor, NH3, H2S, and TVOC during drying was determined using a portable odor-meter. Ingredient analysis was performed by EDS. Considering mass-production, the oil to heat-dried sludge weight ratio was fixed to 4:1. At $130^{\circ}C$, only physical mixing occurred after the instantaneous drying of internal water. Considering the eco-friendly aspects, there was no significant difference in the drying efficiency between $160^{\circ}C$ and $190^{\circ}C$. Therefore, the optimal conditions were a drying temperature of $160^{\circ}C$ within 5 minutes. Finally, the RDF manufactured in this study and fuel used in the thermal power plants were compared. The calorific value was 4,449kcal/kg, the water content was 2% and the ash content was 34%, which is higher than the fuel of thermal power plants. Therefore, it is believed that coal energy as well as wood pellets can be replaced.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.5
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• pp.554-563
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• 2016

Ships are capable of operating on residual fuel oil. Recently, various attempts have been made to meet environmental regulations and with ships operating on residual fuel oil. One way of fulfilling these requirements is by using fuel additives. Dispersants and fuel combustion improvers will have a positive effect on improving the combustion characteristics of the residual fuel oil. As such, this study examines fuel oils blended with additives by using fuel combustion analysis (FIA/FCA) and thermogravimetric analysis (TGA). The results of FIA/FCA focuse only on the amount of work done by the fuel oil. Therefore, it is recommended in this study that a new method to evaluate the combustion efficiency via FIA/FCA processes be developed. The analysis with ROHR curve gained by FIA/FCA brought similar results with pressure trace curve therefore it can be said that new analysis method can be reliable. The TGA, analysis process is very sensitive to the evaporation of fuel, for example, which could be addressed. In the performance-related findings of this study, blended samples with additives containing iron compounds showed a greater improvement in early combustion characteristics than samples without additives.

• Journal of the Korean Wood Science and Technology
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• v.37 no.3
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• pp.192-199
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• 2009

This study was carried out to investigate the performance of a radio-frequency/vacuum dryer combined with a mechanical compressive load (RF/VC) with a scale of about $3m^3$ during drying board of Azobe (Lophira alata) and Korean red pine (Pinus densiflora). The degree of vacuum of the RF/VC system was maintained at 80~105 torr, and wood temperature was increased from $40^{\circ}C$ at the beginning of drying to $60^{\circ}C$ at the end of drying and the radiofrequency generator was operated with schedule of 7 minute-ON and 3 minute-OFF. The wood temperatures near charge plate always remained higher than those of the control during all of the drying stage, whereas the wood temperature near ground plate always remained lower than those of the controlled. As drying time proceeding, the temperature of the wood near ground plate presented lower than those of the control. Whereas the temperature of the wood near charge plate presented higher than those of the controlled. The final average moisture contents of the Azobe boards stacked near the input side of the RF generator showed slightly lower than those near the opposite side. Those of the wood stacked in the layers near the charge plate were lower than those of near the ground plate. The average length of surface checks of the Azobe boards stacked near the charge plate was very slight, whereas that toward the ground plate represented high values. The efficiency of input energy was simliar with the commercial systems.

• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.743-748
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• 2019

This study focuses on the simulation of wet flue gas desulfurization process for improving the production of gypsum by the utilization of low-grade limestone. At present, high-grade limestone with a $CaCO_3$ content of 94% is used for producing merchantable gypsum. In modeling process, a lot of reactions are considered to develop model. First, the limestone dissolution is simulated by RSTOIC model. Second, SOx absorption and crystallization is used by RCSTR model. Finally the gypsum is separated by using SEPERATORS model. Modeling steps make it easy to reflect further side reactions and physical disturbances. In optimization condition, constraints are set to 93% purity of gypsum, 94% desulfurization efficiency, and total use of limestone at 3710 kg/hr. Under these constraints, the mass flow of low-grade limestone was maximized. As a result, the maximum blending quantity of low-grade limestone for 2,100 kg of high-grade limestone that satisfies constraints is about 1,610 kg.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.519-524
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• 2023

In hashing-based image retrieval, the hash code of a manipulated image is different from the original image, making it difficult to search for the same image. This paper proposes and evaluates a self-supervised deephashing model that generates perceptual hash codes from feature information such as texture, shape, and color of images. The comparison models are autoencoder-based variational inference models, but the encoder is designed with a fully connected layer, convolutional neural network, and transformer modules. The proposed model is a variational inference model that includes a SimAM module of extracting geometric patterns and positional relationships within images. The SimAM module can learn latent vectors highlighting objects or local regions through an energy function using the activation values of neurons and surrounding neurons. The proposed method is a representation learning model that can generate low-dimensional latent vectors from high-dimensional input images, and the latent vectors are binarized into distinguishable hash code. From the experimental results on public datasets such as CIFAR-10, ImageNet, and NUS-WIDE, the proposed model is superior to the comparative model and analyzed to have equivalent performance to the supervised learning-based deephashing model. The proposed model can be used in application systems that require low-dimensional representation of images, such as image search or copyright image determination.