• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.1
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• pp.54-63
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• 2019

As a part of the national marine ecosystem monitoring program, the temporal and spatial variation of sedimentary environment and pollution of organic matters and trace metals from four major tidal flats, i.e., Ganghwa Is., Garolim bay, Jeung Is., Suncheon bay, was investigated for 3 yerars from 2015 to 2017. The mean grain size of the sediment was $5.0-5.3{\varnothing}$ at Ganghwa Is, $4.5-4.8{\varnothing}$ at Garolim bay, $6.1-6.5{\varnothing}$ at Jeung Is, and $8.6-8.7{\varnothing}$ at Suncheon bay. The mean grain size (Mz) tended to decrease from the north (Ganghwa Is.) to the south (Suncheon bay). The ignition loss (IL) was 15.5% in Suncheon bay in 2015, which was relatively high compared to other sites, but gradually decreased over time from 8.3% in 2016 to 7.0% in 2017. In Jeung Is. and Suncheon bay, the concentration of Zn and As exceeded the threshold effect level (TEL) at some stations, but the range of trace metals in the other sites was below the level. In Jeung Is., the Mz and concentration of trace metals except Hg was positively correlated (r= 0.40-0.88, P<0.05). On the other hand, Mz was negatively correlated with trace metals (P<0.05) in Suncheon bay. The geoaccumulation index ($I_{geo}$) to evaluate contamination status of sediments for trace metal was less than 1(not contaminated) for Cu, Zn, Pb, Cd and Hg, and 2-3 (moderately to strongly polluted) for As at several stations in Suncheon bay and Jeung Is.

• Land and Housing Review
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• v.12 no.3
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• pp.11-26
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• 2021

With the increasing demand for office space, there have been questions on how office rent distribution produces a change in the urban spatial structure in Seoul. The purpose of this paper is to investigate a relative price gradient and to present a time-series model that can quantitatively explain the dynamic changes in the urban spatial structure. The analysis was dealt with office rent above 3,306 m² for the past 10 years from 1Q 2010 to 4Q 2019 within Seoul. A modified repeat sales model was employed. The main findings are briefly summarized as follows. First, according to the estimates of the office price gradient in the three major urban centers of Seoul, the CBD remained at a certain level with little change, while those in the GBD and the YBD continued to increase. This result reveals that the urban form of Seoul has shifted from monocentric to polycentric. This shows that the spatial distribution of companies has gradually accelerated decentralized concentration implying that the business networks have become significant. Second, contrary to small and medium-sized office buildings that have undertaken no change in the gradient, large office buildings have seen an increase in the gradient. The relative price gradients in small and medium-sized buildings were inversely proportional among the CBD, the GBD, and the YBD, implying their heterogeneous submarkets by office rent movements. Presumably, those differences in the submarkets were attributed to investment attraction, industrial competition, and the credit and preference of tenants. The findings are consistent with the hierarchical system identified in the Seoul 2030 Plan as well as the literature about Seoul's urban form. This research claims that the proposed method, based on the modified repeat sales model, is useful in understanding temporal dynamic changes. Moreover, the findings can provide implications for urban growth strategies under rapidly changing market conditions.

• Journal of agriculture & life science
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• v.53 no.5
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• pp.137-143
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• 2019

To manufacturing of solid fuel by reuse of the wastes, the drying unit which have 500 kg/hr of drying capacity was developed and experimentally evaluate the performance. The spinach grown in Nam-hae island were used for the experiments and investigated of the heated-air drying characteristics as the inlet amount of raw materials, raw material stirring status, conveying type and drying time. The drying air heated by the energy derived from the steam which is supplied from the incineration plant. The moisture contents of raw materials were measured 85.65%. The inlet flow rate of drying air made a difference as the depth of the raw materials loaded on the drying unit and temperature has showed 108~144℃. The drying speed of the mixed drying more than doubled as that of non mixed drying under the same drying type, inlet amount, drying time and drying air temperature. In each experiment, the drying capacity have showed over 500 kg/hr. A drying efficiency of the ratio of drying consumption energy to input energy was 33.46%, lower than the average of 57.76% for the 157 conventional dryers. Because developed dryer must have a drying time of less than one hour, it is considered that the dry efficiency has been reduced due to the loss of wind volume during drying. If waste heat from incineration plant is used as a direct heat source, the dry air temperature is expected to be at least 160℃, greatly improving the drying capacity.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.1
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• pp.13-34
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• 2022

Soil moisture data have been collected at 11 agrometeorological stations operated by The Korea Meteorological Administration (KMA). This study aimed to verify the accuracy of soil moisture data of KMA and develop a correction formula to be applied to improve their quality. The soil of the observation field was sampled to analyze its physical properties that affect soil water content. Soil texture was classified to be sandy loam and loamy sand at most sites. The bulk density of the soil samples was about 1.5 g/cm³ on average. The content of silt and clay was also closely related to bulk density and water holding capacity. The EnviroSCAN model, which was used as a reference sensor, was calibrated using the self-manufactured "reference soil moisture observation system". Comparison between the calibrated reference sensor and the field sensor of KMA was conducted at least three times at each of the 11 sites. Overall, the trend of fluctuations over time in the measured values of the two sensors appeared similar. Still, there were sites where the latter had relatively lower soil moisture values than the former. A linear correction formula was derived for each site and depth using the range and average of the observed data for the given period. This correction formula resulted in an improvement in agreement between sensor values at the Suwon site. In addition, the detailed approach was developed to estimate the correction value for the period in which a correction formula was not calculated. In summary, the correction of soil moisture data at a regular time interval, e.g., twice a year, would be recommended for all observation sites to improve the quality of soil moisture observation data.

• Korean Journal of Poultry Science
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• v.49 no.4
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• pp.211-220
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• 2022

Poultry are exposed to extremely high levels of oxidative stress as a consequence of the excessive production of reactive oxygen species (ROS) induced by endogenous and exogenous stressors, such as high-stocking densities, thermal stress, environmental and feed contamination, along with factors associated with intensive breeding systems. Oxidative stress promotes lipid peroxidation, DNA damage, and inflammation, which can have detrimental effects on the health of birds. During the course of evolution, birds have developed antioxidant defense mechanisms that contribute to maintaining homeostasis when exposed to endogenous and exogenous stressors. The primary antioxidant defense systems are enzymatic and non-enzymatic in nature and play roles in protecting cells from ROS attack. Recently, plant flavonoids, which have been established to reduce oxidative stress, have been attracting considerable attention as potential feed additives. Flavonoids are a group of polyphenolic compounds that can be stabilized by binding structural compounds with ROS, and can promote the elimination of ROS by inducing the expression of antioxidant enzymes. However, although flavonoids can contribute to reducing lipid peroxidation and thereby enhance the antioxidant capacity of birds, they have low solubility in the gastrointestinal tract, and consequently, it is necessary to develop a delivery technology that can facilitate the effect intestinal absorption of these compounds. Furthermore, it is important to determine the dietary levels of flavonoids by assessing the exact antioxidant effects in the gastrointestinal tract wherein the concentrations of dietary flavonoids are highest. It is also necessary to examine the expression of transcriptional factors and vitagenes associated with the efficient antioxidant effects induced by flavonoids. It is anticipated that the application of flavonoids as natural antioxidants will become a particularly important field in the poultry industry.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.253-264
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• 2022

In this study, we investigated the occurrence of viral diseases in the early growth stage of soybean to establish management practices. We collected 83 soybean samples showing abnormal symptoms, approximately 3-4 weeks after seeding in the breeding field of the National Institute of Crop Science. Viruses were detected in the collected samples using reverse transcription polymerase chain reaction (RT-PCR) and metatranscriptome analysis of all those samples. The incidence of viral diseases in the field was less than 1% overall and up to 50% in certain cultivars and lines. RT-PCR and metatranscriptome analysis detected Soybean yellow mottle mosaic virus (SYMMV), Soybean mosaic virus (SMV), Soybean yellow common mosaic virus, Peanut stunt virus, and soybean geminivirus A (SGVA). Among these detected viruses, SYMMV and SMV were identified as major viruses causing infection in the early growth stage of soybean, with detection rates of 53.7% and 42.6%, respectively. Soybeans infected with SYMMV showed typical mosaic symptoms, whereas those infected with SMV showed a variety of symptoms such as mosaic, mottle, stunt, and chlorotic spots. Transmission characteristics of these viruses are variable, such that SMV is primarily transmitted by seeds, whereas SYMMV could be transmitted by insects, soil, and seeds. In this study, SGVA was detected in the early growth stage of soybean, and research on the current status and its effects on soybean after the early growth stage should be conducted.

• Journal of IKEEE
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• v.27 no.1
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• pp.122-126
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• 2023

In this paper, a control system for a complex microbial incubator was proposed. The proposed control system consists of a control unit, a communication unit, a power supply unit, and a control system of the complex microbial incubator. The controller of the complex microbial incubator is designed and manufactured to convert analog signals and digital signals, and control signals of sensors such as displays using LCD panels, water level sensors, temperature sensors, and pH concentration sensors. The water level sensor used is designed and manufactured to enable accurate water level measurement by using the IR laser method with excellent linearity in order to solve the problem that existing water level sensors are difficult to measure due to foreign substances such as bubbles. The temperature sensor is designed and used so that it has high accuracy and no cumulative resistance error by measuring using the thermal resistance principle. The communication unit consists of two LAN ports and one RS-232 port, and is designed and manufactured to transmit signals such as LCD panel, PCT panel, and load cell controller used in the complex microbial incubator to the control unit. The power supply unit is designed and manufactured to supply power by configuring it with three voltage supply terminals such as 24V, 12V and 5V so that the control unit and communication unit can operate smoothly. The control system of the complex microbial incubator uses PLC to control sensor values such as pH concentration sensor, temperature sensor, and water level sensor, and the operation of circulation pump, circulation valve, rotary pump, and inverter load cell used for cultivation. In order to evaluate the performance of the control system of the proposed complex microbial incubator, the result of the experiment conducted by the accredited certification body showed that the range of water level measurement sensitivity was -0.41mm~1.59mm, and the range of change in water temperature was ±0.41℃, which is currently commercially available. It was confirmed that the product operates with better performance than the performance of the products. Therefore, the effectiveness of the control system of the complex microbial incubator proposed in this paper was demonstrated.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.491-501
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• 2022

Bentonite has been proposed as a buffer and backfill material for high-level radioactive waste repository. Under such repository environment conditions, bentonite is subjected to combined thermal, hydrological, mechanical, and chemical processes. This study evaluates the feasibility of applying X-ray CT technology on the characterization of bentonite under hydration conditions using a newly developed testing cell. The cylindrical cell is made of platic material, with a removable cap to place the sample, enabling to apply vertical pressure on the sample and to measure swelling pressure. The hydration test was carried out with a sample made of Gyeonju bentonite, with a dry density of 1.4 g/cm³, and a water content of 20%. The sample had a diameter of 27.5 mm and a height of 34 mm. During the test, water was injected at a constant pressure of 0.207 MPa, and lasted for 7 days. After one day of hydration, bentonite swelled and filled out the space inside the cell. Moreover, CT histograms showed how the hydration process induced an initial increase and later progressive decrease on the density of the sample. Detailed profiles of the mean CT value, CT standard deviation, and CT gradient provided more details on the hydration process of the sample and showed how the bottom and top regions exhibited a decrease on density while the middle region showed an increase, especially during the first two days of hydration. Later, the differences in CT values with respect to the initial state decreased, and were small at the end of testing. The formation and later reduction of cracks was also characterized through CT scanning.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1031-1042
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• 2023

In this study, a deep learning model was developed to predict the yield of cabbage and radish, one of the five major supply and demand management vegetables, using satellite images of Landsat 8. To predict the yield of cabbage and radish in Gangwon-do from 2015 to 2020, satellite images from June to September, the growing period of cabbage and radish, were used. Normalized difference vegetation index, enhanced vegetation index, lead area index, and land surface temperature were employed in this study as input data for the yield model. Crop yields can be effectively predicted using satellite images because satellites collect continuous spatiotemporal data on the global environment. Based on the model developed previous study, a model designed for input data was proposed in this study. Using time series satellite images, convolutional neural network, a deep learning model, was used to predict crop yield. Landsat 8 provides images every 16 days, but it is difficult to acquire images especially in summer due to the influence of weather such as clouds. As a result, yield prediction was conducted by splitting June to July into one part and August to September into two. Yield prediction was performed using a machine learning approach and reference models , and modeling performance was compared. The model's performance and early predictability were assessed using year-by-year cross-validation and early prediction. The findings of this study could be applied as basic studies to predict the yield of field crops in Korea.