• Journal of Adhesion and Interface
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• v.24 no.4
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• pp.136-142
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• 2023

In this study, TEOS was used as a silica source, and a triblock copolymer (P123) was used as a template to produce mesoporous silica with a well-ordered hexagonal mesopore array through a self-assembly method and hydrothermal process under acidic condition. (Surfactant-extracted SBA-15). Surfactant-extracted SBA-15 showed the particle shape of a short rod with a size of approximately 980 nm. The surface area and pore diameter were 730 m²g^-1 and 70.8 Å, respectively. Meanwhile, aminosilane (3-aminopropyltriethoxysilane, APTES) was grafted into the mesopores using a post-synthesis method. Mesoporous silica (APTES-SBA-15) modified with aminosilane had a well-ordered pore structure (p6mm) and well-maintained the particle shape of short rods. The surface area and pore diameter of APTES-SBA-15 decreased to 350 m²g^-1 and 60.7 Å, respectively. APTES-modified mesoporous silica was treated with a solution of rare earth metal ions (Eu³⁺, Tb³⁺) to synthesize a mesoporous silica material in which rare earth metal complexes were introduced into the mesopores. (Eu/APTES-SBA-15, Tb/APTES-SBA-15) These materials exhibited characteristic photoluminescence spectra by λ_ex=250 nm. (⁵D₄→⁷F₅ (543.5 nm), ⁵D₄→⁷F₄ (583.5 nm), ⁵D₄→⁷F₃ (620.2 nm) transitions for Tb/APTES-SBA-15; ⁵D₀→⁷F₀ (577.7 nm), ⁵D₀→⁷F₁ (592.0 nm), ⁵D₀→⁷F₂ (614.9 nm), ⁵D₀→⁷F₃ (650.3 nm) and ⁵D₀→⁷F₄ (698.5 nm) transitions for Eu/APTES-SBA-15)

• Research in Plant Disease
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• v.29 no.4
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• pp.384-389
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• 2023

Milling can affect the distribution of mycotoxins in small grains. To investigate the effects on barley, seven hulled barley and three naked barley samples naturally contaminated with trichothecenes and zearalenone were obtained and milled at commonly used rates. Both barleys were simultaneously contaminated with deoxynivalenol and its acetyl derivatives (98.1-2,197.8 ㎍/kg), nivalenol and its acetyl derivative (468.5-3,965.1 ㎍/kg), and zearalenone (4.1-274.2 ㎍/kg). Milling hulled barleys at a rate of 67% reduced the mycotoxins in the grain by 90.9% for deoxynivalenol, 87.7% for nivalenol, and 93.2% for zearalenone. The reduction in naked barleys (milled at a rate of 70%) was slightly lower than in hulled barleys, with 88.6% for deoxynivalenol, 80.2% for nivalenol, and 70.1% for zearalenone. In both barleys, the acetyl derivatives of deoxynivalenol and nivalenol were reduced by 100%. However, barley bran had significantly higher mycotoxin concentrations than the pre-milled grains: bran from hulled barley had a 357% increase in deoxynivalenol, 252% increase in nivalenol, and 169% increase in zearalenone. Similarly, bran from naked barley had a 337% increase in deoxynivalenol, 239% increase in nivalenol, and 554% increase in zearalenone. These results show that mycotoxins present in the outer layers of barley grain can be effectively removed through the milling process. As milling redistributes mycotoxins from the grain into the bran, however, it shows that advance monitoring of barley bran is recommended when using barley bran for human or animal consumption.

• Journal of the Korean Society of Radiology
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• v.84 no.5
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• pp.1066-1079
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• 2023

Purpose Distinguishing intradural extramedullary (IDEM) spinal ependymoma from myxopapillary ependymoma is challenging due to the location of IDEM spinal ependymoma. This study aimed to investigate the utility of clinical and MR imaging features for differentiating between IDEM spinal and myxopapillary ependymomas. Materials and Methods We compared tumor size, longitudinal/axial location, enhancement degree/pattern, tumor margin, signal intensity (SI) of the tumor on T2-weighted images and T1-weighted image (T1WI), increased cerebrospinal fluid (CSF) SI caudal to the tumor on T1WI, and CSF dissemination of pathologically confirmed 12 IDEM spinal and 10 myxopapillary ependymomas. Furthermore, classification and regression tree (CART) was performed to identify the clinical and MR features for differentiating between IDEM spinal and myxopapillary ependymomas. Results Patients with IDEM spinal ependymomas were older than those with myxopapillary ependymomas (48 years vs. 29.5 years, p < 0.05). A high SI of the tumor on T1W1 was more frequently observed in IDEM spinal ependymomas than in myxopapillary ependymomas (p = 0.02). Conversely, myxopapillary ependymomas show CSF dissemination. Increased CSF SI caudal to the tumor on T1WI was observed more frequently in myxopapillary ependymomas than in IDEM spinal ependymomas (p < 0.05). Dissemination to the CSF space and increased CSF SI caudal to the tumor on T1WI were the most important variables in CART analysis. Conclusion Clinical and radiological variables may help differentiate between IDEM spinal and myxopapillary ependymomas.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.151-164
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• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.2
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• pp.313-320
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• 2014

Purpose : The purpose of the study is to evaluate the efficiency of Coaxial MLC VMAT plan (Using $273^{\circ}$ and $350^{\circ}$ collimator angle) That the leaf motion direction aligned with axis of OAR (Organ at risk, It means spinal cord or cauda equine in this study.) compare to Universal MLC VMAT plan (using $30^{\circ}$ and $330^{\circ}$ collimator angle) for spine SBRT. Materials and Methods : The 10 cases of spine SBRT that treated with VMAT planned by Coaxial MLC and Varian TBX were enrolled. Those cases were planned by Eclipse (Ver. 10.0.42, Varian, USA), PRO3 (Progressive Resolution Optimizer 10.0.28) and AAA (Anisotropic Analytic Algorithm Ver. 10.0.28) with coplanar $360^{\circ}$ arcs and 10MV FFF (Flattening filter free). Each arc has $273^{\circ}$ and $350^{\circ}$ collimator angle, respectively. The Universal MLC VMAT plans are based on existing treatment plans. Those plans have the same parameters of existing treatment plans but collimator angle. To minimize the dose difference that shows up randomly on optimizing, all plans were optimized and calculated twice respectively. The calculation grid is 0.2 cm and all plans were normalized to the target V100%=90%. The indexes of evaluation are V10Gy, D0.03cc, Dmean of OAR (Organ at risk, It means spinal cord or cauda equine in this study.), H.I (Homogeneity index) of the target and total MU. All Coaxial VMAT plans were verified by gamma test with Mapcheck2 (Sun Nuclear Co., USA), Mapphan (Sun Nuclear Co., USA) and SNC patient (Sun Nuclear Co., USA Ver 6.1.2.18513). Results : The difference between the coaxial and the universal VMAT plans are follow. The coaxial VMAT plan is better in the V10Gy of OAR, Up to 4.1%, at least 0.4%, the average difference was 1.9% and In the D0.03cc of OAR, Up to 83.6 cGy, at least 2.2 cGy, the average difference was 33.3 cGy. In Dmean, Up to 34.8 cGy, at least -13.0 cGy, the average difference was 9.6 cGy that say the coaxial VMAT plans are better except few cases. H.I difference Up to 0.04, at least 0.01, the average difference was 0.02 and the difference of average total MU is 74.1 MU. The coaxial MLC VMAT plan is average 74.1 MU lesser then another. All IMRT verification gamma test results for the coaxial MLC VMAT plan passed over 90.0% at 1mm / 2%. Conclusion : Coaxial MLC VMAT treatment plan appeared to be favorable in most cases than the Universal MLC VMAT treatment planning. It is efficient in lowering the dose of the OAR V10Gy especially. As a result, the Coaxial MLC VMAT plan could be better than the Universal MLC VMAT plan in same MU.

• The Journal of Korean Society for Radiation Therapy
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• v.27 no.2
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• pp.145-156
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• 2015

Purpose : The purpose of this study is to evaluate the efficiency of Split VMAT planning(Contouring rectum divided into an upper and a lower for reduce rectum dose) compare to Conventional VMAT planning(Contouring whole rectum) for prostate cancer radiotherapy involving pelvic lymph nodes. Materials and Methods : A total of 9 cases were enrolled. Each case received radiotherapy with Split VMAT planning to the prostate involving pelvic lymph nodes. Treatment was delivered using TrueBeam STX(Varian Medical Systems, USA) and planned on Eclipse(Ver. 10.0.42, Varian, USA), PRO3(Progressive Resolution Optimizer 10.0.28), AAA(Anisotropic Analytic Algorithm Ver. 10.0.28). Lower rectum contour was defined as starting 1cm superior and ending 1cm inferior to the prostate PTV, upper rectum is a part, except lower rectum from the whole rectum. Split VMAT plan parameters consisted of 10MV coplanar $360^{\circ}$ arcs. Each arc had $30^{\circ}$ and $30^{\circ}$ collimator angle, respectively. An SIB(Simultaneous Integrated Boost) treatment prescription was employed delivering 50.4Gy to pelvic lymph nodes and 63~70Gy to the prostate in 28 fractions. $D_{mean}$ of whole rectum on Split VMAT plan was applied for DVC(Dose Volume Constraint) of the whole rectum for Conventional VMAT plan. In addition, all parameters were set to be the same of existing treatment plans. To minimize the dose difference that shows up randomly on optimizing, all plans were optimized and calculated twice respectively using a 0.2cm grid. All plans were normalized to the prostate $PTV_{100%}$ = 90% or 95%. A comparison of $D_{mean}$ of whole rectum, upperr ectum, lower rectum, and bladder, $V_{50%}$ of upper rectum, total MU and H.I.(Homogeneity Index) and C.I.(Conformity Index) of the PTV was used for technique evaluation. All Split VMAT plans were verified by gamma test with portal dosimetry using EPID. Results : Using DVH analysis, a difference between the Conventional and the Split VMAT plans was demonstrated. The Split VMAT plan demonstrated better in the $D_{mean}$ of whole rectum, Up to 134.4 cGy, at least 43.5 cGy, the average difference was 75.6 cGy and in the $D_{mean}$ of upper rectum, Up to 1113.5 cGy, at least 87.2 cGy, the average difference was 550.5 cGy and in the $D_{mean}$ of lower rectum, Up to 100.5 cGy, at least -34.6 cGy, the average difference was 34.3 cGy and in the $D_{mean}$ of bladder, Up to 271 cGy, at least -55.5 cGy, the average difference was 117.8 cGy and in $V_{50%}$ of upper rectum, Up to 63.4%, at least 3.2%, the average difference was 23.2%. There was no significant difference on H.I., and C.I. of the PTV among two plans. The Split VMAT plan is average 77 MU more than another. All IMRT verification gamma test results for the Split VMAT plan passed over 90.0% at 2 mm / 2%. Conclusion : As a result, the Split VMAT plan appeared to be more favorable in most cases than the Conventional VMAT plan for prostate cancer radiotherapy involving pelvic lymph nodes. By using the split VMAT planning technique it was possible to reduce the upper rectum dose, thus reducing whole rectal dose when compared to conventional VMAT planning. Also using the split VMAT planning technique increase the treatment efficiency.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.63-77
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• 2011

The World Wide Web is a very large distributed digital information space. From its origins in 1991, the web has grown to encompass diverse information resources as personal home pasges, online digital libraries and virtual museums. Some estimates suggest that the web currently includes over 500 billion pages in the deep web. The ability to search and retrieve information from the web efficiently and effectively is an enabling technology for realizing its full potential. With powerful workstations and parallel processing technology, efficiency is not a bottleneck. In fact, some existing search tools sift through gigabyte.syze precompiled web indexes in a fraction of a second. But retrieval effectiveness is a different matter. Current search tools retrieve too many documents, of which only a small fraction are relevant to the user query. Furthermore, the most relevant documents do not nessarily appear at the top of the query output order. Also, current search tools can not retrieve the documents related with retrieved document from gigantic amount of documents. The most important problem for lots of current searching systems is to increase the quality of search. It means to provide related documents or decrease the number of unrelated documents as low as possible in the results of search. For this problem, CiteSeer proposed the ACI (Autonomous Citation Indexing) of the articles on the World Wide Web. A "citation index" indexes the links between articles that researchers make when they cite other articles. Citation indexes are very useful for a number of purposes, including literature search and analysis of the academic literature. For details of this work, references contained in academic articles are used to give credit to previous work in the literature and provide a link between the "citing" and "cited" articles. A citation index indexes the citations that an article makes, linking the articleswith the cited works. Citation indexes were originally designed mainly for information retrieval. The citation links allow navigating the literature in unique ways. Papers can be located independent of language, and words in thetitle, keywords or document. A citation index allows navigation backward in time (the list of cited articles) and forwardin time (which subsequent articles cite the current article?) But CiteSeer can not indexes the links between articles that researchers doesn't make. Because it indexes the links between articles that only researchers make when they cite other articles. Also, CiteSeer is not easy to scalability. Because CiteSeer can not indexes the links between articles that researchers doesn't make. All these problems make us orient for designing more effective search system. This paper shows a method that extracts subject and predicate per each sentence in documents. A document will be changed into the tabular form that extracted predicate checked value of possible subject and object. We make a hierarchical graph of a document using the table and then integrate graphs of documents. The graph of entire documents calculates the area of document as compared with integrated documents. We mark relation among the documents as compared with the area of documents. Also it proposes a method for structural integration of documents that retrieves documents from the graph. It makes that the user can find information easier. We compared the performance of the proposed approaches with lucene search engine using the formulas for ranking. As a result, the F.measure is about 60% and it is better as about 15%.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Journal of Animal Science and Technology
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• v.51 no.5
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• pp.369-378
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• 2009

Protein fractionation was evaluated from whole crop silages of rye (RS), wheat (WS), triticale (TS), oat (OS), barley (BS), and rice straw silage (RSS), and in vitro trial was carried out to examine the effect of silage and extraction of soluble protein on fermentation characteristics, total gas production and degradation. Soluble protein of silages was extracted with borate-phosphate buffer, and fermentation characteristics, gas production and degradation of silages were estimated by incubating anaerobically the mixed solution of strained rumen fluid and artificial saliva (1:1, v/v) containing dried and ground silages placed in nylon bag at $39^{\circ}C$ up to 48h. Soluble protein (SP) content was lowest for RSS as 2.11% in total CP compared to those for other silages. Highest A fraction (NPN) was observed from RS (74.33% of total CP) while those from TS and RSS were relatively low (48%). B2 fraction was relatively higher for RS, RSS and WS than for TS and BS. $B_3$ fraction was lowest in WS among silages. C fraction (27.07) in RSS was higher than in other silages (1.40~9.93%). pH in incubation solution was increased (P<0.01~P<0.001) for extracted silages up to 12h but decreased (P<0.01) at 48h for non-extracted ones. Contents of ammonia-N (P<0.001) and total VFA (P<0.01~P<0.001) were higher for non-extracted silages than for extracted ones. Acetate proportion was increased (P<0.001) in buffer extracted silages while those of propionate and butyrate were decreased (P<0.001) up to 24h incubation. Increased (P<0.001) total gas production was obtained from non-extracted silages up to 12h while gas production was increased (P<0.01) in extracted ones thereafter. In vitro degradation of dry matter and CP was increased (P<0.001) in non-extracted silages but that of neutral detergent fiber was increased (P<0.001) in extracted ones without difference among silages. Difference in mean values of degradability for each silage prior to- and post extraction with borate buffer, however, was not found among silages. It may be concluded that high NPN content of silages may reduce the protein availability in silages and borate buffer soluble components in silages can stimulate the early stage of fermentation.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."