• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4A
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• pp.565-571
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• 2008

Recently, the evaluation technique using NDT (Nondestructive Technique : NDT) is widely utilized because it makes little damage on RC (Reinforced Concrete : RC) structures. The techniques using electromagnetic properties (EM properties) are also attempted for the evaluation of the performance of concrete which is nonmetallic. For the economic manufacturing of concrete material, sea-sand is often used as aggregate, however, chloride ion in concrete has direct effects on steel corrosion and EM properties. In this study, OPC mortar specimens with 5 different chloride amount (0.0, 0.6, 1.2, 2.4, and $3.6kg/m^3$) and 3 different water-cement ratios (45%, 55%, and 65%) are prepared in order to investigate the EM properties corresponding to concrete properties. The EM properties of conductivity and dielectric constant are measured in the frequency range over 0.2~20 GHz. To facilitate the comparison of EM properties with chloride content, average values are taken respectively for the conductivity and dielectric constant measured over the 5~20 GHz frequency range. According to the results of this experiment, dielectric constant and conductivity are increased with lower W/C ratio and larger amount of chloride content.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.1A
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• pp.53-59
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• 2010

Recently, NDTs (Non-Destructive Techniques) using infrared camera are widely studied for detection of damage and void in RC (reinforced concrete) structures and they are also considered as an effective techniques for maintenance of infrastructures. The temperature on concrete surface depends on material and thermal properties such as specific heat, thermal conductivity, and thermal diffusion coefficient. Different porosity on cement mortar due to different mixture proportions can show different heat behavior in cooling stage. The porosity can affect physical and durability properties like strength and chloride diffusion coefficient as well. In this paper, active thermography which uses flash for heat induction is utilized and thermal characteristics on surface are evaluated. Samples of cement mortar with W/C (water to cement ratio) of 0.55 and 0.65 are prepared and physical properties like porosity, compressive strength, and chloride diffusion coefficient are evaluated. Then infrared thermography technique is carried out in a constant room condition (temperature $20{\sim}22^{\circ}C$ and relative humidity 55-60%). The mortar samples with higher porosity shows higher residual temperature at the cooling stage and also shows reduced critical time which shows constant temperature due to back wall effect. Furthermore, simple equation for critical time of back wall effect is suggested with porosity and experimental constants. These characteristics indicate the applicability of infrared thermography as an NDT for quality assessment of cement based composite like concrete. Physical properties and thermal behavior in cement mortar with different porosity are analyzed in discussed in this paper.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.27 no.3
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• pp.1-18
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• 2024

The study aims to establish a direction for forest ecological restoration by classifying forest types and understanding the ecological characteristics of the Uljin forest area damaged by a large fire in 2022. Hierarchical cluster analysis and indicator species analysis were conducted on 78 survey plots located in the forest fire-affected area, and four forest cover types were derived: P. densiflora pure forests, P. densiflora dominant forests, mixed broad-leaved forests, and Q. variabilis dominant forests. As a result of visually comparing changes in forest types before and after forest fire damage, by classifying data according to whether or not upper dead trees are included, it was confirmed that pine forests, which have a high proportion of pine trees, spread widely due to forest fire damage. However, broad-leaved mixed forests and oyster oak dominant forests showed characteristics of maintaining concentration, indicating that pine forests were severely damaged. As a result of the important value analysis, during the process of natural recovery after a forest fire, the species that appear early in the lower layer are the sprouts of existing species such as Quercus mongolica Fisch. ex Ledeb., Quercus variabilis Blume, Fraxinus sieboldiana Blume, Rhododendron mucronulatum Turcz. The distribution of diameter at breast height by forest cover type showed that among areas with extreme forest fire damage, the proportion of dead trees was relatively high and structural changes were large in P. densiflora pure forests and P. densiflora dominant forests where pine trees had a high distribution ratio. However, if continuous monitoring is carried out in the future with reference to the results of this study and plant data is collected and analyzed from a mid- to long-term perspective, it is believed that it will be used as useful data to promote forest ecological restoration projects in forest fire-affected areas.

• Korean Journal of Radiology
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• v.21 no.9
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• pp.1036-1044
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• 2020

Objective: To investigate the clinical feasibility of synthetic diffusion-weighted imaging (sDWI) at different b-values in patients with breast cancer by assessing the diagnostic image quality and the quantitative measurements compared with conventional diffusion-weighted imaging (cDWI). Materials and Methods: Fifty patients with breast cancer were assessed using cDWI at b-values of 800 and 1500 s/mm² (cDWI₈₀₀ and cDWI₁₅₀₀) and sDWI at b-values of 1000 and 1500 s/mm² (sDWI₁₀₀₀ and sDWI₁₅₀₀). Qualitative analysis (normal glandular tissue suppression, overall image quality, and lesion conspicuity) was performed using a 4-point Likert-scale for all DWI sets and the cancer detection rate (CDR) was calculated. We also evaluated cancer-to-parenchyma contrast ratios for each DWI set in 45 patients with the lesion identified on any of the DWI sets. Statistical comparisons were performed using Friedman test, one-way analysis of variance, and Cochran's Q test. Results: All parameters of qualitative analysis, cancer-to-parenchyma contrast ratios, and CDR increased with increasing b-values, regardless of the type of imaging (synthetic or conventional) (p < 0.001). Additionally, sDWI₁₅₀₀ provided better lesion conspicuity than cDWI₁₅₀₀ (3.52 ± 0.92 vs. 3.39 ± 0.90, p < 0.05). Although cDWI₁₅₀₀ showed better normal glandular tissue suppression and overall image quality than sDWI₁₅₀₀ (3.66 ± 0.78 and 3.73 ± 0.62 vs. 3.32 ± 0.90 and 3.35 ± 0.81, respectively; p < 0.05), there was no significant difference in their CDR (90.0%). Cancer-to-parenchyma contrast ratios were greater in sDWI₁₅₀₀ than in cDWI₁₅₀₀ (0.63 ± 0.17 vs. 0.55 ± 0.18, p < 0.001). Conclusion: sDWI₁₅₀₀ can be feasible for evaluating breast cancers in clinical practice. It provides higher tumor conspicuity, better cancer-to-parenchyma contrast ratio, and comparable CDR when compared with cDWI₁₅₀₀.

• Asian-Australasian Journal of Animal Sciences
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• v.21 no.1
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• pp.107-119
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• 2008

To determine the true digestible phosphorus (TDP) requirement of growing pigs, two experiments were designed with the experimental diets containing five true digestible P levels (0.16%, 0.20%, 0.23%, 0.26% and 0.39%) and the ratio of total calcium to true digestible P (TDP) kept at 2:1. In Experiment 1, five barrows (Duroc${\times}$Landrace${\times}$Yorkshire) with an average initial body weight of 27.9 kg were used in a $5{\times}5$ Latin-square design to evaluate the effect of different dietary P levels on the digestibility and output of P and nitrogen. In Experiment 2, sixty healthy growing pigs (Duroc${\times}$Landrace${\times}$Yorkshire) with an average body weight (BW) of 21.4 kg were assigned randomly to one of the five dietary treatments (12 pigs/diet), and were used to determine the true digestible phosphorus (TDP) requirement of growing pigs on the basis of growth performance and serum biochemical indices. The results indicated that the true digestibility of P increased (p<0.05) linearly with increasing dietary TDP level below 0.26%. The true P digestibility was highest (56.6%) when dietary TDP was 0.34%. Expressed as g/kg dry matter intake (DMI), fecal P output increased (p<0.05) linearly with increasing P input. On the basis of g/kg fecal dry matter (DM), fecal P output was lowest for Diet 4 and highest (p<0.05) for Diet 5. The apparent digestibility of crude protein (CP) did not differ (p>0.05) among the five diets, with the average nitrogen output of 12.14 g/d and nitrogen retention of 66% to 74% (p>0.05), which suggested that there was no interaction between dietary P and CP protein levels. During the 28-d experimental period of Experiment 2, the average daily gain (ADG) of pigs was affected by dietary TDP levels as described by Eq. (1): $y=-809,532x^4+788,079x^3-276,250x^2+42,114x-1,759$; ($R^2=0.99$; p<0.01; y = ADG, g/d; x = dietary TDP, %), F/G for pigs by Eq. (2): $y=3,651.1x^4-3,480.4x^3+1,183.8x^2-172.5x+10.9$ ($R^2=0.99$; p<0.01; y = F/G; x = dietary TDP, %), and Total P concentrations in serum by Eq. (3): $y=-3,311.7x^4+3,342.7x^3-1,224.6x^2+195.6x-8.7$ (R2 = 0.99; p<0.01; y = total serum P concentration and x = dietary TDP, %). The highest ADG (782 g/d), the lowest F/G (1.07) and the highest total serum P concentration (3.1 mmol/L) were obtained when dietary TDP level was 0.34%. Collectively, these results indicate that the optimal TDP requirement of growing pigs is 0.34% of the diet at a total Ca to TDP ratio of 2:1.

• Economic and Environmental Geology
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• v.15 no.3
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• pp.123-154
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• 1982

Petrochemical, K-Ar dating, Sand Rb/Sr isotopes, metallogenic zoning, paleomagnetic and geotectonic studies of the Gyongsang basin were carried out to examine applicability of plate tectonics to the post-late Cretaceous igneous activity and metallogeny in the southeastern part of Korean Peninsula. The results obtained are as follows: 1. Bulgugsa granitic rocks range from granite to adamellite, whose Q-Ab-Or triangular diagram indicates that the depth and pressure at which the magma consolidated increase from coast to inland varying from 6 km, 0.5-3.3 kb in the coastal area to 17 km, 0.5-10 kb in the inland area. 2. The volcanic rocks in Gyongsang basin range from andesitic to basaltic rocks, and the basaltic rocks are generally tholeiitic in the coastal area and alkali basalt in the inland area. 3. The volcanic rocks of the area have the initial ratio of Sr^{87}/Sr^{86} varying from 0.706 to 0.707 which suggests a continental origin; the ratio of Rb/Sr changing from 0.079-0.157 in the coastal area to 0.021-0.034 in the inland area suggests that the volcanism is getting younger toward coastal side, which may indicate a retreat in stage of differentiation if they were derived from a same magma. The K_2O/SiO_2 (60%) increases from about 1.0 in the coastal area to about 3.0 in the inland area, which may suggest an increase indepth of the Benioff zone, if existed, toward inland side. 4. The K-Ar ages of volcanic rocks were measured to be 79.4 m.y. near Daegu, and 61.7 m.y. near Busan indicating a southeastward decrease in age. The ages of plutonic rocks also decrease toward the same direction with 73 m.y. near Daegu, and 58 m.y. near Busan, so that the volcanism predated the plutonism by 6 m.y. in the continental interior and 4 m.y. along the coast. Such igneous activities provide a positive evidence for an applicability of plate tectonics to this area. 5. Sulfur isotope analyses of sulfide minerals from 8 mines revealed that these deposits were genetically connected with the spacially associated ingeous rocks showing relatively narrow range of ${\delta}^{34}S$ values (-0.9‰ to +7.5‰ except for +13.3 from Mulgum Mine). A sequence of metallogenic zones from the coast to the inland is delineated to be in the order of Fe-Cu zone, Cu-Pb-Zn zone, and W-Mo zone. A few porphyry type copper deposits are found in the Fe-Cu zone. These two facts enable the sequence to be comparable with that of Andean type in South America. 6. The VGP's of Cretaceous and post Cretaceous rocks from Korea are located near the ones($71^{\circ}N$, $180^{\circ}E$ and $90^{\circ}N$, $110^{\circ}E$) obtained from continents of northern hemisphere. This suggests that the Korean peninsula has been stable tectonically since Cretaceous, belonging to the Eurasian continent. 7. Different polar wandering path between Korean peninsula and Japanese islands delineates that there has been some relative movement between them. 8. The variational feature of declination of NRM toward northwestern inland side from southeastern extremity of Korean peninsula suggests that the age of rocks becomes older toward inland side. 9. The geological structure(mainly faults) and trends of lineaments interpreted from the Landsat imagery reveal that NNE-, NWW- and NEE-trends are predominant in the decreasing order of intensity. 10. The NNE-trending structures were originated by tensional and/or compressional forces, the directions of which were parallel and perpendicular respectively to the subduction boundary of the Kula plate during about 90 m.y. B.P. The NWW-trending structures were originated as shear fractures by the same compressional forces. The NEE-trending structures are considered to be priginated as tension fractures parallel to the subduction boundary of the Kula plate during about 70 m.y. B.P. when Japanese islands had drifted toward southeast leaving the Sea of Japan behind. It was clearly demonstrated by many authors that the drifting of Japanese islands was accompanied with a rotational movement of a clock-wise direction, so that it is inferred that subduction boundary had changed from NNE- to NEE-direction. A number of facts and features mentioned above provide a suite of positive evidences enabling application of plate tectonics to the late Cretaceous-early Tertiary igneous activity and metallogeny in the area. Synthesizing these facts, an arc-trench system of continental margin-type is adopted by reconstructing paleogeographic models for the evolution of Korean peninsula and Japan islands. The models involve an extention mechanism behind the are(proto-Japan), by which proto-Japan as of northeastern continuation of Gyongsang zone has been drifted rotationally toward southeast. The zone of igneous activity has also been migrated from the inland in late-Cretaceous to the peninsula margin and southwestern Japan in Tertiary.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.39-55
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• 2019

Recently banks and large financial institutions have introduced lots of Robo-Advisor products. Robo-Advisor is a Robot to produce the optimal asset allocation portfolio for investors by using the financial engineering algorithms without any human intervention. Since the first introduction in Wall Street in 2008, the market size has grown to 60 billion dollars and is expected to expand to 2,000 billion dollars by 2020. Since Robo-Advisor algorithms suggest asset allocation output to investors, mathematical or statistical asset allocation strategies are applied. Mean variance optimization model developed by Markowitz is the typical asset allocation model. The model is a simple but quite intuitive portfolio strategy. For example, assets are allocated in order to minimize the risk on the portfolio while maximizing the expected return on the portfolio using optimization techniques. Despite its theoretical background, both academics and practitioners find that the standard mean variance optimization portfolio is very sensitive to the expected returns calculated by past price data. Corner solutions are often found to be allocated only to a few assets. The Black-Litterman Optimization model overcomes these problems by choosing a neutral Capital Asset Pricing Model equilibrium point. Implied equilibrium returns of each asset are derived from equilibrium market portfolio through reverse optimization. The Black-Litterman model uses a Bayesian approach to combine the subjective views on the price forecast of one or more assets with implied equilibrium returns, resulting a new estimates of risk and expected returns. These new estimates can produce optimal portfolio by the well-known Markowitz mean-variance optimization algorithm. If the investor does not have any views on his asset classes, the Black-Litterman optimization model produce the same portfolio as the market portfolio. What if the subjective views are incorrect? A survey on reports of stocks performance recommended by securities analysts show very poor results. Therefore the incorrect views combined with implied equilibrium returns may produce very poor portfolio output to the Black-Litterman model users. This paper suggests an objective investor views model based on Support Vector Machines(SVM), which have showed good performance results in stock price forecasting. SVM is a discriminative classifier defined by a separating hyper plane. The linear, radial basis and polynomial kernel functions are used to learn the hyper planes. Input variables for the SVM are returns, standard deviations, Stochastics %K and price parity degree for each asset class. SVM output returns expected stock price movements and their probabilities, which are used as input variables in the intelligent views model. The stock price movements are categorized by three phases; down, neutral and up. The expected stock returns make P matrix and their probability results are used in Q matrix. Implied equilibrium returns vector is combined with the intelligent views matrix, resulting the Black-Litterman optimal portfolio. For comparisons, Markowitz mean-variance optimization model and risk parity model are used. The value weighted market portfolio and equal weighted market portfolio are used as benchmark indexes. We collect the 8 KOSPI 200 sector indexes from January 2008 to December 2018 including 132 monthly index values. Training period is from 2008 to 2015 and testing period is from 2016 to 2018. Our suggested intelligent view model combined with implied equilibrium returns produced the optimal Black-Litterman portfolio. The out of sample period portfolio showed better performance compared with the well-known Markowitz mean-variance optimization portfolio, risk parity portfolio and market portfolio. The total return from 3 year-period Black-Litterman portfolio records 6.4%, which is the highest value. The maximum draw down is -20.8%, which is also the lowest value. Sharpe Ratio shows the highest value, 0.17. It measures the return to risk ratio. Overall, our suggested view model shows the possibility of replacing subjective analysts's views with objective view model for practitioners to apply the Robo-Advisor asset allocation algorithms in the real trading fields.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.139-157
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• 2016

Bankruptcy involves considerable costs, so it can have significant effects on a country's economy. Thus, bankruptcy prediction is an important issue. Over the past several decades, many researchers have addressed topics associated with bankruptcy prediction. Early research on bankruptcy prediction employed conventional statistical methods such as univariate analysis, discriminant analysis, multiple regression, and logistic regression. Later on, many studies began utilizing artificial intelligence techniques such as inductive learning, neural networks, and case-based reasoning. Currently, ensemble models are being utilized to enhance the accuracy of bankruptcy prediction. Ensemble classification involves combining multiple classifiers to obtain more accurate predictions than those obtained using individual models. Ensemble learning techniques are known to be very useful for improving the generalization ability of the classifier. Base classifiers in the ensemble must be as accurate and diverse as possible in order to enhance the generalization ability of an ensemble model. Commonly used methods for constructing ensemble classifiers include bagging, boosting, and random subspace. The random subspace method selects a random feature subset for each classifier from the original feature space to diversify the base classifiers of an ensemble. Each ensemble member is trained by a randomly chosen feature subspace from the original feature set, and predictions from each ensemble member are combined by an aggregation method. The k-nearest neighbors (KNN) classifier is robust with respect to variations in the dataset but is very sensitive to changes in the feature space. For this reason, KNN is a good classifier for the random subspace method. The KNN random subspace ensemble model has been shown to be very effective for improving an individual KNN model. The k parameter of KNN base classifiers and selected feature subsets for base classifiers play an important role in determining the performance of the KNN ensemble model. However, few studies have focused on optimizing the k parameter and feature subsets of base classifiers in the ensemble. This study proposed a new ensemble method that improves upon the performance KNN ensemble model by optimizing both k parameters and feature subsets of base classifiers. A genetic algorithm was used to optimize the KNN ensemble model and improve the prediction accuracy of the ensemble model. The proposed model was applied to a bankruptcy prediction problem by using a real dataset from Korean companies. The research data included 1800 externally non-audited firms that filed for bankruptcy (900 cases) or non-bankruptcy (900 cases). Initially, the dataset consisted of 134 financial ratios. Prior to the experiments, 75 financial ratios were selected based on an independent sample t-test of each financial ratio as an input variable and bankruptcy or non-bankruptcy as an output variable. Of these, 24 financial ratios were selected by using a logistic regression backward feature selection method. The complete dataset was separated into two parts: training and validation. The training dataset was further divided into two portions: one for the training model and the other to avoid overfitting. The prediction accuracy against this dataset was used to determine the fitness value in order to avoid overfitting. The validation dataset was used to evaluate the effectiveness of the final model. A 10-fold cross-validation was implemented to compare the performances of the proposed model and other models. To evaluate the effectiveness of the proposed model, the classification accuracy of the proposed model was compared with that of other models. The Q-statistic values and average classification accuracies of base classifiers were investigated. The experimental results showed that the proposed model outperformed other models, such as the single model and random subspace ensemble model.

• Korean Journal of Poultry Science
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• v.33 no.3
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• pp.225-231
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• 2006

To investigate the effect of feeding rare earth (RE) on the performance of breeder hens a feeding trial with sixteen thousands of 158 day old Ross broiler breeder hens was conducted for thirty weeks. A mixture of RE- chlorides containing mainly La, Ce, and Pr was mixed into corn-soy based diet at two levels, 300 and 600 mg/kg, All the hens were housed in flat layer houses and the ratio of male to female was maintained at one to ten. Dietary supplementation of the of RE at a level of 300 mg/kg made the hens reach egg production peak higher by about 6% and earlier by about two weeks. As a result, it made higher hatchable egg production by 3.5%. It also reduced dramatically the mortality of both male and female breeders(P<0.05). Egg weight was slightly increased but egg qualify was not much influenced by dietary supplementation of RE. Egg albumin hight and Haugh unit were significantly improved while egg shell thickness, egg breaking strength and yolk color were similar to those of the control. Experimental results appeared to show a good possibility that egg fertility and hatchability were improved by feeding RE. Dietary supplementation of RE at a level of 300 mg/kg should be acceptable but not the 600 mg/kg level for breeder hens. Further studies on the effect of RE on egg fertility and hatchability appears to be necessary.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.8
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• pp.866-871
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• 2006

The nutrient recovery in phosphate crystallization process was investigated by using laboratory scale uptlow reactors, adopting sequencing batch type configuration. The industrial waste lime was used as potential cation source with magnesium salt($MgCl_2$) as control. The research was focused on its successful application in a novel integrated sludge treatment process, which is comprised of a high performance fermenter followed by a crystallization reactor. In the struvite precipitation test using synthetic wastewater first, which has the similar characteristics with the real fermentation effluent, the considerable nutrient removal(about 60%) in both ammonia and phosphate was observed within $0.5{\sim}1$ hr of retention time. The results also revealed that a minor amount(<5%) of ammonia stripping naturally occurred due to the alkaline(pH 9) characteristic in feed substrate. Stripping of $CO_2$ by air did not increase the struvite precipitation rate but it led to increased ammonia removal. In the second experiment using the fermentation effluent, the optimal dosage of magnesium salt for struvite precipitation was 0.86 g Mg $g^{-1}$ P, similar to the mass ratio of the struvite. The optimal dosage of waste lime was 0.3 g $L^{-1}$, resulting in 80% of $NH_4-N$ and 41% of $PO_4-P$ removal, at about 3 hrs of retention time. In the microscopic analysis, amorphous crystals were mainly observed in the settled solids with waste lime but prism-like crystals were observed with magnesium salt. Based on mass balance analysis for an integrated sludge treatment process(fermenter followed by crystallization reactor) for full-scale application(treatment capacity Q=158,880 $m^3\;d^{-1}$), nutrient recycle loading from the crystallization reactor effluent to the main liquid stream would be significantly reduced(0.13 g N and 0.19 g P per $m^3$ of wastewater, respectively). The results of the experiment reveal therefore that the reuse of waste lime, already an industrial waste, in a nutrient recovery system has various advantages such as higher economical benefits and sustainable treatment of the industrial waste.