• Journal of the Korea Computer Graphics Society
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• v.23 no.2
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• pp.29-39
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• 2017

This paper presents a unified framework to efficiently and realistically simulate surface and wave foams. The framework is designed to first project 3D water particles from an underlying water solver onto 2D screen space in order to reduce the computational complexity of determining where foam particles should be generated. Because foam effects are often created primarily in fast and complicated water flows, we analyze the acceleration and curvature values to identify the areas exhibiting such flow patterns. Foam particles are emitted from the identified areas in 3D space, and each foam particle is advected according to its type, which is classified on the basis of velocity, thereby capturing the essential characteristics of foam wave motions. We improve the realism of the resulting foam by classifying it into two types: surface foam and wave foam. Wave foam is characterized by the sharp wave patterns of torrential flow s, and surface foam is characterized by a cloudy foam shape even in water with reduced motion. Based on these features, we propose a technique to correct the velocity and position of a foam particle. In addition, we propose a kernel technique using the screen space density to efficiently reduce redundant foam particles, resulting in improved overall memory efficiency without loss of visual detail in terms of foam effects. Experiments convincingly demonstrate that the proposed approach is efficient and easy to use while delivering high-quality results.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.15 no.3
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• pp.104-107
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• 2005

[ $TiN_x$ ] powder have been fabrication by making of reaction between titanium powder and $Si_3N_4$ bowl during a planetary milling. Milling times were maintained for 1 hour, 5 hours, and 10 hours, respectively. The XRD result showed existence of non-stoichiometric compound of $TiN_{0.26}$ after 5 hours milling and coexistence of TiN with $TiN_{0.26}$ after 10 hours milling. Particle size distribution was investigated by particle size analyzer and microstructure was analyzed by FE-SEM. The size of titanium was decreased with increasing the milling time and the mean size of $TiN_x$ after 10 hours milling was increased by 200 nm.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.1
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• pp.15-22
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• 2014

This paper presents the implementation of a control system of pellet boiler using wood pellet as carbon neutral material. The system also has the additional features to provide remote controlling and monitoring based on home networking technology through either public switched telephone networks or mobile communication networks. It consists of three kinds of sub-modules; a main controller provides basic and additional features such as a setting of temperature, a supplying of wood pellet, a controlling of ignition and fire-power, and a removing of soot. The second is temperature controller of individual rooms which is connected to the main controller through RS-485 links. And interface modules with PSTN and mobile networks can support remote controlling and monitoring the functions. The test results under the heating area of $172m^2$ show a thermal efficiency of 93.6%, a heating power of 20,640kcal/hr, and a fuel consumption of 5.54kg/hr. These results are superior to those of the conventional pellet boilers. In order to obtain the such high performance, we newly applied a 3-step ignition flow, a flame detection by $C_dS$ sensor, and a fire-power control by fine controlling of shutter to our pellet boiler.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.2
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• pp.53-62
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• 2012

Demand for high resolution weather data grows in the agriculture and forestry fields. Local Analysis and Prediction System (LAPS) can be used to analyze the local weather at high spatial and temporal resolution, utilizing the data from various sources including numerical weather prediction models, wind or temperature profilers, Automated Weather Station (AWS) networks, radars, and satellites. LAPS has been set to analyze weather elements such as air temperature, relative humidity, wind speed, and wind direction every hour at the spatial resolution of $100m{\times}100m$ for Gyeonggi-do on near real-time basis. The AWS data were revised by adding the agricultural field AWS data (33 stations) in addition to the KMA data. The analysis periods were from 1 to 31 August 2009 and from 15 to 21 February 2010. The comparison of the LAPS output showed the smaller errors when using the agricultural AWS observation data together with the KMA data as its input data than using only either the agricultural or KMA AWS data. The accuracy of the current system needs improvement by further optimization of analyzing options of the system. However, the system is highly applicable to various fields in agriculture and forestry because it can provide site specific data with reasonable time intervals.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3719-3725
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• 2012

Due to the recent shortage of well-graded river sand resulting from a rapid growth of concrete construction, sea sand, crushed sand, and etc. are increasingly used instead. It is, however, well noted that non-washed sea sand leads to corrosion of the reinforcing steel in concrete, and thus eventually results in damage to concrete. Also, the crushed sand is not being widely used, since it is difficult to maintain the allowable amount of passing 0.08mm sieve and to adjust grading. On the other hand, because the fine sand of Nakdong-River has a poor grading but good quality as a fine aggregate for concrete, it is strongly needed to investigate the fine sand as an alternative fine aggregate. Thus, the purpose of this research is to evaluate the physical properties of the fine sand of Nakdong-River to utilize it actively as a fine aggregate. For this purpose, after the sand samples were collected according to typical location of main stream of Nakdong-River, the physical properties such as density in oven-dry condition, grading, unit volume mass, and etc. of them were estimated. It was observed from the test results that physical properties of the fine sand of Nakdong-River except grading were found to be excellent.

• Journal of Korean Neurosurgical Society
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• v.30 no.sup1
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• pp.85-90
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• 2001

Objective : DREZotomy is effective for the treatment of deafferentation pain as a consequence of root avulsion, postparaplegic pain, posttraumatic syrinx, postherpetic neuralgia, spinal cord injury, and peripheral nerve injury. We performed microsurgical DREZotomy to the patients with deafferentation pain and relieved pain without any serious complication. The purpose of this study is to evaluate the usefulness of the microsurgical DREZotomy for deafferentation pain. Methods : We evaluated 4 patients with deafferntation pain who were intractable to medical therapy. Two of them were brachial plexus injury with root avulsion owing to trauma, one was axillary metastasis of the squamous cell carcinoma of the left forearm, and the last was anesthesia dolorosa after surgical treatment(MVD and rhizotomy) of trigeminal neuralgia. Preoperative evaluation was based on the neurologic examination, radiologic imaging, and electrophysiological study. In the case of anesthesia dolorosa, we produced two parallel lesions in cephalocaudal direction, 2mm in distance, from the C2 dorsal rootlet to the 5mm superior to the obex including nucleus caudalis, after suboccipital craniectomy and C1-2 laminectomy, with use of microelectrode. In the others, we confirmed lesion site with identification of the nerve root after hemilaminectomy. We performed arachnoid dissection along the posterolateral sulcus and made lesion with microsurgical knife and microelectrocoagulation, 2mm in depth, 2mm in distance, to the direction of 30-45 degrees in the medial portion of the Lissauer's tract and the most dorsal layers of the posterior horn at the one root level above and below the lesion. Results : Compared with preoperative state, microsurgical DREZotomy significantly diminished dosage of the drugs and relieved pain meaningfully. One patient showed tansient ipsilateral ataxia, but recovered soon. There was not any serious complication. Conclusion : It may be concluded that microsurgical DREZotomy is very useful and safe therapeutic modality for deafferentation pain, especially segmentally distributed intermittent or evoke pain. Complete preoperative evaluation and proper selection of the patients and lesion making device are needed to improve the result.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.7-14
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• 2021

Tomato crops are highly affected by tomato diseases, and if not prevented, a disease can cause severe losses for the agricultural economy. Therefore, there is a need for a system that quickly and accurately diagnoses various tomato diseases. In this paper, we propose a system that classifies nine diseases as well as healthy tomato plants by applying various pretrained deep learning-based CNN models trained on an ImageNet dataset. The tomato leaf image dataset obtained from PlantVillage is provided as input to ResNet, Xception, and DenseNet, which have deep learning-based CNN architectures. The proposed models were constructed by adding a top-level classifier to the basic CNN model, and they were trained by applying a 5-fold cross-validation strategy. All three of the proposed models were trained in two stages: transfer learning (which freezes the layers of the basic CNN model and then trains only the top-level classifiers), and fine-tuned learning (which sets the learning rate to a very small number and trains after unfreezing basic CNN layers). SGD, RMSprop, and Adam were applied as optimization algorithms. The experimental results show that the DenseNet CNN model to which the RMSprop algorithm was applied output the best results, with 98.63% accuracy.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.2
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• pp.117-124
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• 2019

Parallel sparse solvers are essential for solving large-scale finite element models. This paper introduces the combination of iterative and direct solver that can be applied efficiently to problems that require continuous solution for a subtly changing sequence of systems of equations. The iterative-direct sparse solver combination technique, proposed and implemented in the parallel sparse solver package, PARDISO, means that iterative sparse solver is applied for the newly updated linear system, but it uses the direct sparse solver's factorization of previous system matrix as a preconditioner. If the solution does not converge until the preset iterations, the solution will be sought by the direct sparse solver, and the last factorization results will be used as a preconditioner for subsequent updated system of equations. In this study, an improved method that sets the maximum number of iterations dynamically at the first Krylov iteration step is proposed and verified thereby enhancing calculation efficiency by the frequency domain analysis.

• International Area Studies Review
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• v.22 no.3
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• pp.255-292
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• 2018

This paper evaluates the new food policy adopted by the European Union to enhance the food safety after the mad cow crisis occurred in 1990's. Newly introduced rules at the EU level are characterized by two features. Firstly, an important part of them have the form of Regulation which is a binding legislative to all member countries. Secondly, most of them are horizontally applied to the whole food industry, irrespective of their kinds of performance, hygiene or labelling. According to theoretical studies on this topic, any food safety regulation for solving adverse selection problem or reducing negative externality in food consumption should be fine-tuning depending on the concrete demand and costs conditions of the food sector concerned. In this theoretical perspective, the food safety laws introduced at EU level after mad cow crisis have been over-regulated for improving social welfare. The true motivation for the transfer of the policy competence on food safety to the Union level is political rather than economic. Our analysis with a political economic perspective shows that how the EU food regulations have been embraced not only by the governments of member countries, but also by diverse interest groups like food processor & distributors, consumers and agro-livestock groups, and that they have been used as protectionist purpose specially against non-member developing countries. Taking into account the fact that the basic aim to form the Union is to establish a single market to enhance economic efficiency at the Union level, the EU is required to adopt some policy actions to reduce negative effects of too restrictive food safety regulations.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.133-140
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• 2022

We investigate the performance of deep learning-based Korean language models on a task of predicting the score range of Korean essays written by foreign students. We construct a data set containing a total of 304 essays, which include essays discussing the criteria for choosing a job ('job'), conditions of a happy life ('happ'), relationship between money and happiness ('econ'), and definition of success ('succ'). These essays were labeled according to four letter grades (A, B, C, and D), and a total of eleven essay score range prediction experiments were conducted (i.e., five for predicting the score range of 'job' essays, five for predicting the score range of 'happiness' essays, and one for predicting the score range of mixed topic essays). Three deep learning-based Korean language models, KoBERT, KcBERT, and KR-BERT, were fine-tuned using various training data. Moreover, two traditional probabilistic machine learning classifiers, naive Bayes and logistic regression, were also evaluated. Experiment results show that deep learning-based Korean language models performed better than the two traditional classifiers, with KR-BERT performing the best with 55.83% overall average prediction accuracy. A close second was KcBERT (55.77%) followed by KoBERT (54.91%). The performances of naive Bayes and logistic regression classifiers were 52.52% and 50.28% respectively. Due to the scarcity of training data and the imbalance in class distribution, the overall prediction performance was not high for all classifiers. Moreover, the classifiers' vocabulary did not explicitly capture the error features that were helpful in correctly grading the Korean essay. By overcoming these two limitations, we expect the score range prediction performance to improve.