• Journal of the Microelectronics and Packaging Society
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• v.29 no.1
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• pp.49-54
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• 2022

The copper plating process used to fabricate the submicron damascene pattern of Cu wiring for Si wafer was applied to the plating of a PCB pattern of several tens of microns in size using the same organic additives and current density conditions. In this case, the non-uniformity of the plating thickness inside the pattern was observed. In order to quantitatively analyze the cause, a numerical calculation considering the solution flow and electric field was carried out. The calculation confirmed that the depletion of Cu²⁺ ions in the solution occurred relatively earlier at the bottom corner than the upper part of the pattern due to the plating of the sidewall and the bottom at the corner of the pattern bottom. The diffusion coefficient of Cu²⁺ ions is 2.65 10^-10 m²/s, which means that Cu²⁺ ions move at 16.3 ㎛ per second on average. In the cases of small damascene patterns, the velocity of Cu²⁺ ions is high enough to supply sufficient ions to the inside of the patterns, while sufficient time is required to replenish the exhausted copper ions in the case of a PCB pattern having a size of several tens of microns. Therefore, it is found that the thickness uniformity can be improved by reducing the current density to supply sufficient copper ions to the target area.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.63-79
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• 2022

Recently, various studies have been conducted on stock price prediction using machine learning and deep learning techniques. Among these studies, the latest studies have attempted to predict stock prices using limit order books, which contain buy and sell order information of stocks. However, most of the studies using limit order books consider only the trend of limit order books over the most recent period of a specified length, and few studies consider both the medium and short term trends of limit order books. Therefore, in this paper, we propose a deep learning-based prediction model that predicts stock price more accurately by considering both the medium and short term trends of limit order books. Moreover, the proposed model considers news headlines during the same period to reflect the qualitative status of the company in the stock price prediction. The proposed model extracts the features of changes in limit order books with CNNs and the features of news headlines using Word2vec, and combines these information to predict whether a particular company's stock will rise or fall the next day. We conducted experiments to predict the daily stock price fluctuations of five stocks (Amazon, Apple, Facebook, Google, Tesla) with the proposed model using the real NASDAQ limit order book data and news headline data, and the proposed model improved the accuracy by up to 17.66%p and the average by 14.47%p on average. In addition, we conducted a simulated investment with the proposed model and earned a minimum of $492.46 and a maximum of $2,840.93 depending on the stock for 21 business days.

• Animal Bioscience
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• v.35 no.2
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• pp.184-195
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• 2022

Objective: In this study we aimed to evaluate the effect of dietary live yeast supplementation on ruminal pH pattern, fermentation characteristics and associated bacteria in beef cattle. Methods: This work comprised of in vitro and in vivo experiments. In vitro fermentation was conducted by incubating 0%, 0.05%, 0.075%, 0.1%, 0.125%, and 0.15% active dried yeast (Saccharomyces cerevisiae, ADY) with total mixed ration substrate to determine its dose effect. According to in vitro results, 0.1% ADY inclusion level was assigned in in vivo study for continuously monitoring ruminal fermentation characteristics and microbes. Six ruminally cannulated steers were randomly assigned to 2 treatments (Control and ADY supplementation) as two-period crossover design (30-day). Blood samples were harvested before-feeding and rumen fluid was sampled at 0, 3, 6, 9, and 12 h post-feeding on 30 d. Results: After 24 h in vitro fermentation, pH and gas production were increased at 0.1% ADY where ammonia nitrogen and microbial crude protein also displayed lowest and peak values, respectively. Acetate, butyrate and total volatile fatty acids concentrations heightened with increasing ADY doses and plateaued at high levels, while acetate to propionate ratio was decreased accordingly. In in vivo study, ruminal pH was increased with ADY supplementation that also elevated acetate and propionate. Conversely, ADY reduced lactate level by dampening Streptococcus bovis and inducing greater Selenomonas ruminantium and Megasphaera elsdenii populations involved in lactate utilization. The serum urea nitrogen decreased, whereas glucose, albumin and total protein concentrations were increased with ADY supplementation. Conclusion: The results demonstrated dietary ADY improved ruminal fermentation dose-dependently. The ruminal lactate reduction through modification of lactate metabolic bacteria could be an important reason for rumen pH stabilization induced by ADY. ADY supplementation offered a complementary probiotics strategy in improving gluconeogenesis and nitrogen metabolism of beef cattle, potentially resulted from optimized rumen pH and fermentation.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.291-298
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• 2022

In this paper, we present a method for dependency parsing with chunking in Korean. Dependency parsing is a task of determining a governor of every word in a sentence. In general, we used to determine the syntactic governor in Korean and should transform the syntactic structure into semantic structure for further processing like semantic analysis in natural language processing. There is a notorious problem to determine whether syntactic or semantic governor. For example, the syntactic governor of the word "먹고 (eat)" in the sentence "밥을 먹고 싶다 (would like to eat)" is "싶다 (would like to)", which is an auxiliary verb and therefore can not be a semantic governor. In order to mitigate this somewhat, we propose a Korean dependency parsing after chunking, which is a process of segmenting a sentence into constituents. A constituent is a word or a group of words that function as a single unit within a dependency structure and is called a chunk in this paper. Compared to traditional dependency parsing, there are some advantage of the proposed method: (1) The number of input units in parsing can be reduced and then the parsing speed could be faster. (2) The effectiveness of parsing can be improved by considering the relation between two head words in chunks. Through experiments for Sejong dependency corpus, we have shown that the USA and LAS of the proposed method are 86.48% and 84.56%, respectively and the number of input units is reduced by about 22%p.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.155-163
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• 2022

The optimization of long-range ensemble climate prediction for rice phenology model with advanced bias correction method is conducted. The daily long-range forecast(6-month) of mean/ minimum/maximum temperature and observation of January to October during 1991-2021 is collected for rice phenology prediction. In this study, the concept of "buffer period" is newly introduced to reduce the problem after bias correction by quantile mapping with constructing the transfer function by month, which evokes the discontinuity at the borders of each month. The four experiments with different lengths of buffer periods(5, 10, 15, 20 days) are implemented, and the best combinations of buffer periods are selected per month and variable. As a result, it is found that root mean square error(RMSE) of temperatures decreases in the range of 4.51 to 15.37%. Furthermore, this improvement of climatic variables quality is linked to the performance of the rice phenology model, thereby reducing RMSE in every rice phenology step at more than 75~100% of Automated Synoptic Observing System stations. Our results indicate the possibility and added values of interdisciplinary study between atmospheric and agriculture sciences.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.367-372
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• 2022

With the recent advent of the New Normal era, realistic technologies and non-contact technologies are receiving social attention. However, the hair styling field focuses on the direction of the hair itself, individual movements, and modeling, focusing on hair simulation. In order to create an improved practice environment and demand of the times, this study proposed a non-contact hair styling VR system. In the theoretical review, we studied the existing cases of hair cut research. Existing haircut-related research tend to be mainly focused on force-based feedback. Research on the interactive haircut work in the virtual environment as addressed in this paper has not been done yet. VR controllers capable of finger tracking the movements necessary for beauty enable selection, cutting, and rotation of beauty tools, and built a non-contact collaboration environment. As a result, we conducted two experiments for interactive hair cutting in VR. First, it is a haircut operation for synchronization using finger tracking and holding hook animation. We made position correction for accurate motion. Second, it is a real-time interactive cutting operation in a multi-user virtual collaboration environment. This made it possible for instructors and learners to communicate with each other through VR HMD built-in microphones and Photon Voice in non-contact situations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.393-399
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• 2021

In this study, experiments were conducted to estimate the PM concentrations by learning the nighttime CCTV images of various PM concentrations environments. In the case of daytime images, there have been many related studies, and the various texture and brightness information of images is well expressed, so the information affecting learning is clear. However, nighttime images contain less information than daytime images, and studies using only nighttime images are rare. Therefore, we conducted an experiment combining nighttime images with non-uniform characteristics due to light sources such as vehicles and streetlights and building roofs, building walls, and streetlights with relatively constant light sources as an ROI (Region of Interest). After that, the correlation was analyzed compared to the daytime experiment to see if deep learning-based PM concentrations estimation was possible with nighttime images. As a result of the experiment, the result of roof ROI learning was the highest, and the combined learning model with the entire image showed more improved results. Overall, R² exceeded 0.9, indicating that PM estimation is possible from nighttime CCTV images, and it was calculated that additional combined learning of weather data did not significantly affect the experimental results.

• The Journal of the Acoustical Society of Korea
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• v.41 no.5
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• pp.507-517
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• 2022

The PhotoAcoustic Microscopy (PAM) has been proved to be a useful tool for biological and medical applications due to its high spatial and contrast resolution. PAM is based on transmission of laser pulses and reception of PA signals. Since the strength of PA signals is generally low, not only are high-performance optical and acoustic modules required, but high-performance electronics for imaging are also particularly needed for high-quality PAM imaging. Most PAM systems are implemented with a combination of several pieces of equipment commercially available to receive, amplify, enhance, and digitize PA signals. To this end, PAM systems are inevitably bulky and not optimal because general purpose equipment is used. This paper reports a PA signal receiving system recently developed to attain the capability of improved Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR) of PAM images; the main module of this system is a low noise, wideband signal receiver that consists of two low-noise amplifiers, two variable gain amplifiers, analog filters, an Analog to Digital Converter (ADC), and control logic. From phantom imaging experiments, it was found that the developed system can improve SNR by 6.7 dB and CNR by 3 dB, compared to a combination of several pieces of commercially available equipment.

• The Korea Journal of Herbology
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• v.37 no.3
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• pp.29-39
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• 2022

Objective : This study is aimed to evaluate the protective effects of Rehmanniae Radix, Mori Folium, and Liriopie Tuber mixture (RML) on lung injury of Particulate matter less than 10 um in diameter and diesel exhaust particles (PM10D) mice model. Methods : To investigate the anti-inflammatory activity of RML, PM10D was diluted in aluminum hydroxide (Alum) in 7-week-old male mice and induced by Intra-Nazal-Tracheal (INT) injection method. Animal experiments were divided into 5 groups. Nor (normal mice), CTL (PM10D-induced mice with the administration of distilled water), DEXA (PM10D-induced mice with the administration of 3 mg/kg Dexamethasone), RML 100 (PM10D-induced mice treated with RML 100 mg/kg weight), and RML 200 (PM10D-induced mice treated with RML 200 mg/kg body weight). After 11 days administration, mice were sacrificed and inflammation-related immune cells in broncho-alveolar lavage fluid (BALF) were analyzed. Inflammation-related biomarkers were also analyzed in blood and lungs. Lung tissue was observed through histological examination. Results : In the PM10D induced model, the PML showed decreases in CXCL-1 and IL-17A in BALF. Expression of inflammatory cytokines and cough-related mRNA genes was significantly decreased in serum and lung tissue. The mixture treatment of RML significantly improved the immune related cells in the serum. In addition, histological observations showed a tendency to decrease the severity of lung injury. Conclusions : Overall, these results confirmed the respiratory protective effect of the RML mixture in a model of lung injury induced by air pollution (PM10+DEP), suggesting that it is a potential treatment for respiratory damage.

• The Korea Journal of Herbology
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• v.33 no.5
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• pp.89-103
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• 2018

Objectives : This study is aimed to compare the changes in Antioxidative capacity of Liriopis Tuber by steaming process and to compare the effects in hyperlipidemia induced rats fed high cholesterol diet between Simvastatin and Liriopis Tuber by steaming process. Methods : The SD rats were divided into six groups: normal diet (Nor), high cholesterol diet (Veh), high cholesterol diet plus Simvastatin 5 mg/kg (Sim), high cholesterol diet plus LT0 extract 200 mg/kg (LT0), high cholesterol diet plus LT6 extract 200 mg/kg (LT6) and high cholesterol diet plus LT9 extract 200 mg/kg (LT9). We compared the total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL), low density lipoprotein cholesterol (LDL) contents and reactive oxygen species (ROS) from each serums. Protein expression in liver tissues related to antioxidant and cholesterol was analyzed. Results : The Antioxidant activity of Liriopis Tuber increased by steaming process. In vivo, TC, TG, LDL-c, atherogenic index (AI) and cardiac risk factor (CRF) decreased and HDL-c increased with increasing steaming frequency. aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine, and blood urea nitrogen (BUN) decreased with increasing steaming frequency. ROS decreased only in LT9, and SOD, catalase and glutathione peroxidase (GPx) increased with increasing steaming frequency. phospho-AMP-activated protein kinase (p-AMPK) increased and sterol regulatory element-binding protein 2 (SREBP-2), Phospho-Acetyl-CoA Carboxylase (p-ACC) and HMG-CoA reductase (HMGCR) decreased with increasing steaming frequency. Liver staining showed a decrease in hepatic fat accumulation of LT9. LT9 showed significant results in all experiments. Conclusions : LT9 showed significance of anti-lipid effect and improved fatty liver of hyperlipemia induced rats fed on high cholesterol diet, In conclusion, LP9 can be effectively used for the treatment of hyperlipidemia.