• Journal of Environmental Analysis, Health and Toxicology
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• v.21 no.4
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• pp.209-219
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• 2018

In the areas of RoHS, WEEE, ELV and REACH, reinforcement of environmental regulations against harmful substances is a global trend not only in EC but also in all over the world. In the fields of Korea's major export products such as material parts, electrical and electronic products and automobile parts, we are responding to these regulations consistently. To develop reference material for analyzing lead and cadmium in paints, the candidate materials were produced through the screening process which separated shapes and sizes. To secure the traceability of the candidate materials produced, the characteristics and uncertainties are estimated by ICP-AES analysis using the primary reference material. The short-term and long-term stabilities also are evaluated in parallel. In order to calculate the final certification value of the candidate material, the verification were carried out by the performance evaluation through the comparison among the KOLAS (Korea Laboratory Accreditation Scheme) laboratories, and the CRM was produced in accordance with ISO Guide 35. The certified values and uncertainties of Pb and Cd of the final paint standard, determined according to the joint analysis among laboratories, are Pb [($191.4{\pm}3.1$) mg/kg, ($944.1{\pm}5.6$) mg/kg] and Cd [($45.0{\pm}2.6$) mg/kg, ($225.5{\pm}3.5$) mg/kg]. These standard materials were developed to enhance the reliability of measurement analysis, including the validity and traceability of measurement results. Also it is expected that the CRM will be used as QCM (quality control material) for the product design and the process monitoring, so that regulation and management of hazardous heavy metals can be systematically implemented.

• Fisheries and Aquatic Sciences
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• v.26 no.2
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• pp.117-132
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• 2023

Chum salmon (Oncorhynchus keta) is a species of anadromous salmonid inhabiting coastal rivers in the North Pacific and the Arctic in the Bering and is the most widely distributed among Pacific salmon species. It is an important fish species in Korea as the salmon releasing project is being actively carried out. This study was conducted to investigate changes in the physiological activity of O. keta according to water temperature. Three experiments were conducted according to the water temperature and period, and the plasma concentrations of cortisol and glucose were analyzed from the blood samples of the experimental groups. Experiment I is a short-term water temperature experiment, in which water temperature stimulation was given for 4 hours at water temperatures of 12℃, 16℃ (control), 20℃, and 24℃, and a recovery period was given for 4 hours. Experiment II is an experiment in which water temperature stimulation was given for 24 hours, 48 hours, and 72 hours at a high temperature of 24℃, and a recovery period was given for 12 hours, respectively. Experiment III is a long-term water temperature experiment, in which the water temperature was 12℃, 16℃ (control), 20℃, and 24℃ for 8 weeks. As a result of the experiment, in Experiment I, there was no significant difference in the survival rate between the experimental groups, but the concentration of cortisol and glucose in the plasma according to the set water temperature showed a significant difference. In Experiment II, there was no significant trend according to the maintenance time of the high-temperature state, but as the temperature increased, the plasma cortisol and glucose levels significantly increased compared to the control group. In Experiment III, all of the experimental group C (24℃) died in the 1st week, and there was no significant difference in the plasma glucose at the 1st and 8th weeks among the remaining experimental groups.

• Korean Journal of Environment and Ecology
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• v.32 no.3
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• pp.313-322
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• 2018

To investigate the changing patterns of sub-alpine forest vegetation due to climate change requires accumulation of contiguous reference data and continuous monitoring. Furthermore, it is crucial to monitor short-term ecological change of lower level vegetation to understand the trend of long-term vegetation change. Therefore, this study carried out a vegetation survey and tree diameter measurement in 36 plots of Mt. Jiri inhabited by Abies koreana species from 2015 to 2017 to examine the short-term dynamics of Abies koreana seedling and the change of vegetation distribution according to altitude. We analyzed the importance value and MIV (mean importance value) of major species by each stratum as well as the importance value and species diversity index of major species and the change of seedling population by altitude. The results showed that Abies koreana had the highest importance value on tree layer, Rhododendron schlippenbachii on shrub layer and Tripterygium regelii on herb layer. MIV was high in the order of Abies koreana, Rhododendron schlippenbachii and Acer pseudosieboldianum. Regarding the species composition and species diversity index (H') along the altitudinal gradient, Sasa borealis showed high MI and low H' in the elevation less than 1,500 m, and IV of Tripterygium regelii and H' of herb layer were high in the elevation of 1,700 - 1,800 m. Abies koreana seedling decreased by 22.4% from 1,250 n/ha in 2015 to 970 n/ha in 2017 (p <0.05) throughout the investigated area. The decline rate along seedling and sapling height were 22.9% in less than 10 cm, 3.4% in 10-30 cm, 8.9% in 30-50 cm, 39.3% in 50-100 cm, and 55.1% more than 100 cm. Few of A. koreana seedlings appeared due to the dominance of Sasa borealis in the elevation of 1,500 m or less and due to the dominance and high species diversity of Tripterygium regelii in the elevation of 1,700-1,800 m. On the other hand, many of A. koreana seedlings appeared in the elevation of 1,600-1,700 m due to no distribution of S. borealis and T. regelii species in that altitude range. Therefore, we concluded that those seedlings and saplings of A. koreana could be more stable in the altitude of 1,600-1,700 m.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.14 no.1
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• pp.51-64
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• 2002

To investigate long-period wave responses in Sokcho Harbor and Cheongcho lagoon, field measurements were made for long-and short-period waves and current velocities using a Directional Waverider, a ultrasonic-type wave gauge, four pressure-type wave gauges, and a current meter. From the data analysis, it was found that the Helmholtz resonant periods of Sokcho Harbor and Cheongcho lagoon are about 13.6 and 54.5 minutes, respectively, and the dominant period of wave induced current in the passage between Sokcho Harbor and Cheongcho lagoon is about 55.2 minutes which depends on Helmholtz resonant condition of the Cheongcho lagoon. It was also found that the energy level of the far-infra-gravity waves during storm conditions is very high compared with that during calm sea conditions. To investigate relationships between far-infra-gravity waves and short-period waves at offshore station, regression analyses were carried out especially for 1) heights, 2) periods, 3) direction and height, 4) height and period between short-and far-infra-gravity waves, respectively. The results showed that the long-period wave height is highly correlated with the short-period wave height. However, no special trend was found for the other relations. In the future far-infra-gravity wave heights on return period around Sokcho Harbor region can be suggested by using extreme value analyses of long term measured data.

• Korean Journal of Head & Neck Oncology
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• v.17 no.1
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• pp.32-37
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• 2001

Objectives: We performed this study to compare the short term results of induction chemotherapy and radiotherapy versus concurrent chemoradiotherapy in patients with locally advanced head and neck cancer. Materials and Methods: From Oct. 1985 to May 1998, 121 patients with locally advanced head and neck cancer were treated with induction chemotherapy and radiotherapy (induction group) or concurrent chemoradiotherapy (concurrent group), and a retrospective analysis was done. Induction chemotherapy was done for 97 patients, and concurrent chemotherapy for 24 patients. Age, sex, performance status, and pathologic types were evenly distributed between two groups. Primary site showed nasopharynx(72.2%), oropharynx(27.8%) in induction group, and nasopharynx(50%), oropharynx(50%) in concurrent group. Chemotherapy regimen was CF(cisplatin and 5-fluorouracil) for 67 patients and CVB (cisplatin, vincristine, bleomycin) for 30 patients in induction group, and CF for all of 24 patients in concurrent group. Proportion of patients treated with more than 2 cycles of planned chemotherapy was 94.8% in induction group and 87.5% in concurrent group. Conventionally fractionated radiotherapy with daily fraction size of 1.8-2.0Gy and 5 fractions/week was done. Total dose was 61-95Gy (median 73.4Gy) for induction group, and 69.4-75.4Gy (median 69.4Gy) for concurrent group. Follow-up time was 4-161 months (median 38 months) for induction group, 7-35 months (median 21.5 months) for concurrent group, respectively. Results: According to treatment modality, overall 2-year survival rates were 68.0% for induction group, 74.3% for concurrent group (p>0.05). two-year disease-free survival rates were 51 % and 74% (p=0.05). Complete response rates were 67.4% for induction group and 83.3% for concurrent group (p=0.09). The incidence of grade 3-4 hematologic toxicity (2.1% vs. 25%, p=0.001) and grade 3-4 mucositis (9.3% vs. 37.5%, p=0.002) during radiotherapy was higher in concurrent group. Conclusion: Concurrent chemoradiotherapy showed a trend of improvement in short-term survival and treatment response when compared with induction chemotherapy and radiotherapy in locally advanced head and neck cancer. A more controlled randomized trial is needed.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.30 no.4
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• pp.331-341
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• 2020

Objectives: This study was conducted to evaluate perceptions of safety and risk among Korean industrial hygienists and the change between before and after the Sewol Ferry Disaster in 2014. Two surveys with questionnaires composed of 51 questions were completed by attendees of the Korea Industrial Hygiene Association(KIHA) conference. Methods: One was conducted at the 2013 KIHA Fall Conference(N=181) and the other was from the 2014 KIHA Summer Conference(N=123). Between these two surveys was the Sewol Ferry Disaster on April 14, 2014, which was believed to seriously affect safety and risk perceptions in Korea. Results: It was revealed that industrial hygienists' awareness of safety rules strengthened after the Sewol Ferry Disaster(p<0.05). It was apparent that people over the age of 30 were more sensitive to social safety. There was no significant difference in the evaluation and attitude regarding governmental safety policy between the years of 2013 and 2014. The credibility of public organizations responsible for the disaster management system decreased. The self-evaluation of respondents' safety level also decreased. This trend shows mainly in the younger generation. It was evaluated that the overall social safety level decreased and the anxiety level increased. The score on social safety on a ±5 Likert scale was 0.68 in the 2013 survey and -0.33 in the 2014 survey(p<0.05). It was reported that the most serious threat factors for accident or disaster were 'building collapse > illegalities and corruption > side effects of radiation therapy >accidents in normal activity > occupational disease,' in order. They picked 'safety ignorance > hurry-up habits and culture > focusing on short-term benefit > easy-going attitude > insufficient safety education' for the causes of low social safety levels in 2013. In 2014, they were 'safety ignorance > easy-going attitude > focusing on short-term benefit > insufficient safety education > hurry-up habits and culture'. Conclusions: This study has some limitations because it was originally not designed to survey attitudes prior to the Sewol Ferry disaster in 2013. In addition, the survey targets are industrial hygienists who are familiar with occupational disease and injury.

• 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.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.99-107
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• 2021

We live in a myriad of data. Various data are created in all situations in which we work, and we discover the meaning of data through big data technology. Many efforts are underway to find meaningful data. This paper introduces an analysis technique that enables humans to make better choices through the trend and prediction of time series data as a principal component analysis technique. Principal component analysis constructs covariance through the input data and presents eigenvectors and eigenvalues that can infer the direction of the data. The proposed method computes a reference axis in a time series data set having a similar directionality. It predicts the directionality of data in the next section through the angle between the directionality of each time series data constituting the data set and the reference axis. In this paper, we compare and verify the accuracy of the proposed algorithm with LSTM (Long Short-Term Memory) through cryptocurrency trends. As a result of comparative verification, the proposed method recorded relatively few transactions and high returns(112%) compared to LSTM in data with high volatility. It can mean that the signal was analyzed and predicted relatively accurately, and it is expected that better results can be derived through a more accurate threshold setting.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.14 no.2
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• pp.118-126
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• 2009

Benthic diatoms are very important primary producers in understanding estuary ecosystems and their productions are largely varied by their photo-physiological characteristics. The short-term effects of increased temperature on the photosynthetic and photo-physiological characteristics of cultured different species of benthic diatoms (Navicula sp., Nitzschia sp., Cylindrotheca closterium, and Pleurosigma elongatum) were investigated by measuring their PSII-fluorescence kinetics using a Diving-PAM. Photosynthesis versus irradiance curves were measured every two hours at six different temperatures (10, 15, 20, 25, 30, and $35^{\circ}C$) for twenty-four hour. The effective quantum yield of PSII ($\Phi_{PSII}$) for most of the species showed a decreasing trend with increased temperature. The relative maximum electron transport rate (rETRmax) was significantly increased up to the optimum temperature level and then sharply decreased. Relative to the values of other parameters, the maximum light use coefficient ($\alpha$) was not substantially changed at lower temperature levels (<$30^{\circ}C$) but significantly decreased only at higher temperatures (30 and $35^{\circ}C$). The light saturation coefficient ($E_K$) mirrored the rETRmax temperature response. In regards to the temperature acclimation abilities of the four species with time, Navicula sp. and C. closterium acclimated to short-term changes in temperature through their photo-physiological adjustments.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.187-201
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• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.