• Nuclear Engineering and Technology
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• v.25 no.1
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• pp.91-101
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• 1993

To predict accurately the thermal hydraulic behavior of light water reactors during normal or abnormal operation, the accurate estimation of the void distribution is required. Up to date, many techniques for predicting void fraction of two-phase flow systems have been suggested. Among these techniques, the drift-flux model is widely used because of its exact calculation ability and simplicity. However, to get more accurate prediction of void fraction using drift-flux model, slip and flow regime effects must be considered more properly In the drift-flux method, these two effects are accounted for by two drift-flux parameters ; $C_{o}$ and (equation omitted). At earlier stage, $C_{o}$ is measured in a circular tube. In this study, $C_{o}$ is experimentally determined by measuring local void fraction and vapor velocity distribution in a rectangular subchannel having 4 heating rods which simulates nuclear subchannels. The measurements are peformed with two-electrical conductivity probes which are known to be adequate for measuring local parameters. The experiments are performed at low flow rate and the system pressure less than 3 atmo spheric pressure. In this experiment, (equation omitted), is not measured, but quoted from well-known empirical correlation to formulate $C_{o}$. Finally, $C_{o}$ is expressed as a function of channel averaged void fraction. fraction.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.108-109
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• 2022

In this study analyzed experimental data on noise interference caused by engine operating apply surface wave communication in the engine room. For the experiment, 7 areas of the engine room on 256 ton tug boat and measured noise during engine on off using signal analyzer for effect surface wave communication. In order to construct and actual communication network based on the analysis of the noise and confirm the characteristics of surface wave communication in the area made metal bulkheads the actual communication network installed communication equipment between three metal bulkheads and conducted a comparative experiment with wireless communication. The difference was confirmed. As a result, in the case of surface wave communication, there was no significant difference in the transmission and reception rates before and after engine operation in an environment with three bulkheads, but in the case of Wi-Fi using wireless, the performance deteriorated significantly during operation. was confirmed. As a result of analyzing the experimental data, it was confirmed that noise caused by engine operation affects wireless communication but does not affect surface wave communication. Therefore, even in the area with a lot of electromagnetic wave noise in the ship, when the surface wave communication system is configured using the ship's metal structure, it is possible to replace the wireless communication and furthermore, it is possible to apply the surface wave communication in the enclosed space and the engine room in the ship.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.15-22
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• 2023

BNKT Ceramics, one of the representative Pb free based piezoelectric ceramics, constitutes a perovskite(ABO3) structure. At this time, the perovskite structure (ABO3) is in the form where the corners of the octahedrons are connected, and in the unit cell, two ions, A and B, are cations, A ion is located at the body center, B ion is located at each corner, and an anion O is located at the center of each side. Since Bi, Na, and K sources constituting the A site are highly volatile at a sintering temperature of 1100℃ or higher, it is difficult to maintain uniformity of the composition. In order to solve this problem, there should be suppression of volatilization of the A site material or additional compensation of the volatilized. In this study, the basic composition of BNKT Ceramics was set to Bi_0.5(Na_0.78K_0.22)_0.5TiO₃ (= BNKT), and volatile site (Bi, Na, and K sources) were coated in the form of a shell to compensate additionally for the A site ions. In addition, the physical and electrical properties of BNKT and its coated with shell additives(= @BNK) were compared and analyzed, respectively. As a result of analyzing the crystal structure through XRD, both BNKT(Core) and @BNK(Shell) had perovskite phases, and the crystallinity was almost similar. Although the Curie temperature of the two sintered bodies was almost the same (TC = 290 ~ 300 ℃), it was confirmed that the d33 (piezoelectric coefficient) and Pr (residual polarization) values were different. The experimental results indicated that the additional compensation for a shell additive causes the coarsening, resulting in a decrease in sintering density and Pr(remanent polarization). However, coating shell additives to compensate for A site ion is an effective way to suppress volatilization. Based on these experimental results, it would be the biggest advantage to develop an eco-friendly material (Lead-free) that replaced lead (Pb), which is harmful to the human body. This lead-free piezoelectric material can be applied to a biomedical device or products(ex. earphones (hearing aids), heart rate monitors, ultrasonic vibrators, etc.) and skin beauty improvement products (mask packs for whitening and wrinkle improvement).

• Journal of IKEEE
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• v.27 no.4
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• pp.486-493
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• 2023

In this paper, we propose an automatic hand gesture area extraction and recognition technique using FMCW radar-based point cloud and LSTM. The proposed technique has the following originality compared to existing methods. First, unlike methods that use 2D images as input vectors such as existing range-dopplers, point cloud input vectors in the form of time series are intuitive input data that can recognize movement over time that occurs in front of the radar in the form of a coordinate system. Second, because the size of the input vector is small, the deep learning model used for recognition can also be designed lightly. The implementation process of the proposed technique is as follows. Using the distance, speed, and angle information measured by the FMCW radar, a point cloud containing x, y, z coordinate format and Doppler velocity information is utilized. For the gesture area, the hand gesture area is automatically extracted by identifying the start and end points of the gesture using the Doppler point obtained through speed information. The point cloud in the form of a time series corresponding to the viewpoint of the extracted gesture area is ultimately used for learning and recognition of the LSTM deep learning model used in this paper. To evaluate the objective reliability of the proposed technique, an experiment calculating MAE with other deep learning models and an experiment calculating recognition rate with existing techniques were performed and compared. As a result of the experiment, the MAE value of the time series point cloud input vector + LSTM deep learning model was calculated to be 0.262 and the recognition rate was 97.5%. The lower the MAE and the higher the recognition rate, the better the results, proving the efficiency of the technique proposed in this paper.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.165-184
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• 2023

Recently, Deep learning analysis of unstructured text data using language models, such as Google's BERT and OpenAI's GPT has shown remarkable results in various applications. Most language models are used to learn generalized linguistic information from pre-training data and then update their weights for downstream tasks through a fine-tuning process. However, some concerns have been raised that privacy may be violated in the process of using these language models, i.e., data privacy may be violated when data owner provides large amounts of data to the model owner to perform fine-tuning of the language model. Conversely, when the model owner discloses the entire model to the data owner, the structure and weights of the model are disclosed, which may violate the privacy of the model. The concept of offsite tuning has been recently proposed to perform fine-tuning of language models while protecting privacy in such situations. But the study has a limitation that it does not provide a concrete way to apply the proposed methodology to text classification models. In this study, we propose a concrete method to apply offsite tuning with an additional classifier to protect the privacy of the model and data when performing multi-classification fine-tuning on Korean documents. To evaluate the performance of the proposed methodology, we conducted experiments on about 200,000 Korean documents from five major fields, ICT, electrical, electronic, mechanical, and medical, provided by AIHub, and found that the proposed plug-in model outperforms the zero-shot model and the offsite model in terms of classification accuracy.

• Journal of IKEEE
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• v.28 no.2
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• pp.150-157
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• 2024

In this paper, we propose a novel algorithm for predicting the number of apples on an apple tree using a deep learning-based object detection model and a polynomial regression model. Measuring the number of apples on an apple tree can be used to predict apple yield and to assess losses for determining agricultural disaster insurance payouts. To measure apple fruit load, we photographed the front and back sides of apple trees. We manually labeled the apples in the captured images to construct a dataset, which was then used to train a one-stage object detection CNN model. However, when apples on an apple tree are obscured by leaves, branches, or other parts of the tree, they may not be captured in images. Consequently, it becomes difficult for image recognition-based deep learning models to detect or infer the presence of these apples. To address this issue, we propose a two-stage inference process. In the first stage, we utilize an image-based deep learning model to count the number of apples in photos taken from both sides of the apple tree. In the second stage, we conduct a polynomial regression analysis, using the total apple count from the deep learning model as the independent variable, and the actual number of apples manually counted during an on-site visit to the orchard as the dependent variable. The performance evaluation of the two-stage inference system proposed in this paper showed an average accuracy of 90.98% in counting the number of apples on each apple tree. Therefore, the proposed method can significantly reduce the time and cost associated with manually counting apples. Furthermore, this approach has the potential to be widely adopted as a new foundational technology for fruit load estimation in related fields using deep learning.

• Journal of the Korea Organic Resources Recycling Association
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• v.18 no.1
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• pp.110-118
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• 2010

Supercritical treatment of liquefaction technology for rice hull was investigated the biomass conversion rate and evaluated its crude oil in respect to feasibility of burner in order to heat the green house. The reaction was carried out in a 5,000 mL liquefaction system with dispenser and external electrical furnace. Raw materials (160 g) of rice hull and 3,000 mL of different solvents were fed into the reactor. It was observed that the maximum crude oil yield was about 84.4 % with 1-butanol. The calorific value of crude oil from ethanol solvent were 7,752 kcal/kg. Furthermore, in case study of co-solvent with ethanol and bulk-glycerol, it observed that more than 80 % of rice hull was decomposed and liquefied in its solvent at $315{\sim}326^{\circ}C$ for 30 min. For the development of applicable bio-fuel from rice hull, it was considered that its feasibility is necessary to be carried out for co-solvent soluble portions. Regarding to utilize the crude oil into burner as fuel, it was observed that its calorific value was lower at approximately 24 % than the diesel. Also, flame length from crude oil at lower temperature was decreasing due to incomplete incineration. The temperature of warm wind on the burner was maintained between 63 and $65^{\circ}C$, and the temperature of emission line was appeared at $350{\sim}380^{\circ}C$.

• Journal of the Korea Organic Resources Recycling Association
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• v.18 no.1
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• pp.104-109
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• 2010

Hydro-thermal liquefaction technology for rapeseed straws was investigated the biomass conversion rate with different catalysts and reaction temperatures. NaOH and KOH were used for catalysts, and the reaction temperature were ranged from 180 to $320^{\circ}C$ at every $20^{\circ}C$ of intervals for 10 minutes. The reaction was carried out in a 5,000 mL liquefaction system with dispenser and external electrical furnace. Raw materials (160g), 2,000 mL of distilled water and 10% (wt/wt) of catalyst to plant residue were fed into the reactor. It was observed that the maximum crude oil yield was about 36% at temperature range, $260{\sim}280^{\circ}C$ with KOH and at $300^{\circ}C$ with NaOH, respectively. It was observed that the more calorific values of crude oil, the higher reaction temperature with KOH, but it had the reverse pattern in NaOH.

• Journal of Acupuncture Research
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• v.20 no.5
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• pp.118-132
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• 2003

Objective: The aim of this study was to investigate the effects of Joksamni(ST36) combination on NAD PH-diaphorase, neuronal nitric oxide synthase(nNOS), neuropeptide Y(NPY) and vasoactive intestinal peptide (VIP) in the cerebral cortex of spontaneously hypertensive rat. Methods: The experimental groups were divided into four groups: Normal, Joksamni(ST36), Joksamni(ST36)+Eumneungcheon(SP9), and Joksamni(ST36)+Gokji(LI11). Needles were inserted into acupoints at the depth of 0.5cm with basic insertion method. Electroacupuncture was done under the condition of 2Hz electrical biphasic pulses with continuous rectangular wave lasting for 0.2ms until the muscles produced visible contractions. Such stimulation was applied continuously for 10 minutes, 1 time every 2 days for 10 sessions of treatments. Thereafter we evaluated changes in NADPH-d positive neurons histochemically and changes in nNOS, NPY and VIP positive neurons immunohistochemically. Results: The optical densities of NADPH-d positive neurons of the Joksamni(ST36)+Eumneungcheon(SP9) group in all areas of cerebral cortex and Joksamni(ST36)+Gokji(LI11) group in primary somatosensory cortex, visual cortex, auditory cortex, perirhinal cortex were significantly increased as compared to the Joksamni(ST36) group. The optical densities of NADPH-d positive neurons of the Joksamni(ST36)+Gokji(LI11) group were significantly decreased as compared to the Joksamni(ST36)+Eumneungcheon(SP9) group with the exception of primary somatosensory cortex. The optical densities of nNOS positive neurons of the Joksamni(ST36)+Eumneungcheon(SP9) group in all areas of cerebral cortex and Joksamni(ST36)+Gokji(LI11) group in auditory cortex, perirhinal cortex, insular cortex were significantly increased as compared to the Joksamni(ST36) group. The optical densities of nNOS positive neurons of the Joksamni(ST36)+Gokji(LI11) group were significantly decreased in all areas of cerebral cortex as compared to the Joksamni(ST36)+Eumneungcheon(SP9) group. The optical densities of NPY positive neurons of the Joksamni(ST36)+Gokji(LI11) group were significantly decreased in primary motor cortex, primary somatosensory cortex, cingulate cortex as compared to the Joksamni (ST36) and Joksamni(ST36)+Eumneungcheon(SP9) groups. The optical densities of VIP positive neurons of the Joksamni(ST36)+Eumneungcheon(SP9) group were significantly increased in all areas of cerebral cortex except for cingulate cortex as compared to the Joksamni(ST36) group. The optical densities of VIP positive neurons of the Joksamni(ST36)+Gokji(LI11) group were significantly decreased in auditory cortex, cingulate cortex, perirhinal cortex as compared to the Joksamni(ST36) group. The optical densities of VIP positive neurons of the Joksamni(ST36)+Gokji(LI11) group were significantly decreased in all areas of cerebral cortex as compared to the Joksamni(ST36)+Eumneungcheon(SP9) group. Conclusions: The result demonstrated that electroacupuncture on Joksamni(ST36) and its combination change the activities of the NO system and peptidergic system in the cerebral cortex of SHR and that acupoint combination is one of the important parameters for the effects.

• Journal of Soil and Groundwater Environment
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• v.11 no.1
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• pp.54-64
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• 2006

Chromated copper arsenate (CCA), a wood preservative, has been widely used to protect wood products from attacks by bacteria, fungi and insects. However, the use of CCA is currently forbidden or limited to some applications in many countries because the toxic elements (Cr, Cu, and As) of CCA are released into the environments during outdoor uses, which may cause adverse health effects on humans and ecological systems. This study was conducted to investigate the distributions of chromium, copper and arsenic in soils adjacent to two CCA-treated wood structures. In a 7 month old pond entry structure, ten surface soil samples (0-2.5 cm) were collected at lateral distances of 0, 0.5, and 1 m from the stairway, and nine surface soil samples were collected beneath the deck. Nine top soil samples were taken from a 2 year old sound barrier structure at lateral distances of 0, 1, and 2 m. Background surface soil samples were also collected from each structure. Samples were analyzed for some physicochemical properties such as pH, electrical conductivity, organic matter content, and soil texture. Following the extraction of the elements with a microwave digestion system, samples were analyzed for Cr, Cu, and As. The concentrations of the three elements in soils adjacent to the structures were significantly elevated compared to the background levels, indicating that the elements have been leached out of the structures. Released e1ements showed lateral concentration gradients within 1 m. The elevations of the three elements in soils underneath the deck did not seem different (background-corrected concentrations: Cr, 5.01 mg/kg; Cu, 5.50 mg/kg; As, 4.91 mg/kg), while the elements in soils near the sound barrier were elevated in the order of As>Cu>Cr with measured concentrations of 49.7, 44.7 and 52.5 mg/kg, respectively. Background As, Cu, and Cr concentrations near the sound barrier were 9.88, 30.8, and 46.5 mg/kg, respectively. These results showed that CCA constituents are released into the environment and it is suggested that risk assessment need to be conducted to investigate harmful effects of the released elements on humans and ecological systems.