• Journal of Bio-Environment Control
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• v.22 no.2
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• pp.182-187
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• 2013

In closed plant production system like plant factory, changes in environmental factors should be identified for conducting efficient environmental control as well as predicting energy consumption. Since high relative humidity (RH) is essential for crop production in the plant factory, transpiration is closely related with RH and should be quantified. In this study, four varieties of lettuces (Lactuca sativa L.) were grown in a plant factory, and the leaf areas and transpiration rates of the plants according to DAT (day after transplanting) were measured. The coefficients of the simplified Penman-Monteith equation were calibrated in order to calculate the transpiration rate in the plant factory and the total amount of transpiration during cultivation period was predicted by simulation. The following model was used: $E_d=a*(1-e^{-k*LAI})*RAD_{in}+b*LAI*VPD_d$ (at daytime) and $E_n=b*LAI*VPD_n$ (at nighttime) for estimating transpiration of the lettuce in the plant factory. Leaf area and transpiration rate increased with DAT as exponential growth. Proportional relationship was obtained between leaf area and transpiration rate. Total amounts of transpiration of lettuces grown in plant factory could be obtained by the models with high $r^2$ values. The results indicated the simplified Penman-Monteith equation could be used to predict water requirements as well as heating and cooling loads required in plant factory system.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.117-137
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• 2009

Recently, intelligent traffic information systems have enabled people to forecast traffic conditions before hitting the road. These convenient systems operate on the basis of data reflecting current road and traffic conditions as well as distance-based data between locations. Thanks to the rapid development of ubiquitous computing, tremendous context data have become readily available making vehicle route planning easier than ever. Previous research in relation to optimization of vehicle route planning merely focused on finding the optimal distance between locations. Contexts reflecting the road and traffic conditions were then not seriously treated as a way to resolve the optimal routing problems based on distance-based route planning, because this kind of information does not have much significant impact on traffic routing until a a complex traffic situation arises. Further, it was also not easy to take into full account the traffic contexts for resolving optimal routing problems because predicting the dynamic traffic situations was regarded a daunting task. However, with rapid increase in traffic complexity the importance of developing contexts reflecting data related to moving costs has emerged. Hence, this research proposes a framework designed to resolve an optimal route planning problem by taking full account of additional moving cost such as road traffic cost and weather cost, among others. Recent technological development particularly in the ubiquitous computing environment has facilitated the collection of such data. This framework is based on the contexts of time, traffic, and environment, which addresses the following issues. First, we clarify and classify the diverse contexts that affect a vehicle's velocity and estimates the optimization of moving cost based on dynamic programming that accounts for the context cost according to the variance of contexts. Second, the velocity reduction rate is applied to find the optimal route (shortest path) using the context data on the current traffic condition. The velocity reduction rate infers to the degree of possible velocity including moving vehicles' considerable road and traffic contexts, indicating the statistical or experimental data. Knowledge generated in this papercan be referenced by several organizations which deal with road and traffic data. Third, in experimentation, we evaluate the effectiveness of the proposed context-based optimal route (shortest path) between locations by comparing it to the previously used distance-based shortest path. A vehicles' optimal route might change due to its diverse velocity caused by unexpected but potential dynamic situations depending on the road condition. This study includes such context variables as 'road congestion', 'work', 'accident', and 'weather' which can alter the traffic condition. The contexts can affect moving vehicle's velocity on the road. Since these context variables except for 'weather' are related to road conditions, relevant data were provided by the Korea Expressway Corporation. The 'weather'-related data were attained from the Korea Meteorological Administration. The aware contexts are classified contexts causing reduction of vehicles' velocity which determines the velocity reduction rate. To find the optimal route (shortest path), we introduced the velocity reduction rate in the context for calculating a vehicle's velocity reflecting composite contexts when one event synchronizes with another. We then proposed a context-based optimal route (shortest path) algorithm based on the dynamic programming. The algorithm is composed of three steps. In the first initialization step, departure and destination locations are given, and the path step is initialized as 0. In the second step, moving costs including composite contexts into account between locations on path are estimated using the velocity reduction rate by context as increasing path steps. In the third step, the optimal route (shortest path) is retrieved through back-tracking. In the provided research model, we designed a framework to account for context awareness, moving cost estimation (taking both composite and single contexts into account), and optimal route (shortest path) algorithm (based on dynamic programming). Through illustrative experimentation using the Wilcoxon signed rank test, we proved that context-based route planning is much more effective than distance-based route planning., In addition, we found that the optimal solution (shortest paths) through the distance-based route planning might not be optimized in real situation because road condition is very dynamic and unpredictable while affecting most vehicles' moving costs. For further study, while more information is needed for a more accurate estimation of moving vehicles' costs, this study still stands viable in the applications to reduce moving costs by effective route planning. For instance, it could be applied to deliverers' decision making to enhance their decision satisfaction when they meet unpredictable dynamic situations in moving vehicles on the road. Overall, we conclude that taking into account the contexts as a part of costs is a meaningful and sensible approach to in resolving the optimal route problem.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Journal of the Korean Applied Science and Technology
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• v.37 no.5
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• pp.1208-1221
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• 2020

The purpose of this study was to provide basic data for predicting the sports consumption market that Generation Z will lead by applying data mining based decision tree analysis to explore Generation Z sports consumption style. Therefore, the survey was conducted by selecting males and females aged 19 or older as a sample among Generation Z, and data of 429 people were used for the final analysis. For data processing, frequency analysis, exploratory factor analysis, retest and reliability analysis, and decision tree analysis were performed using the SPSS statistics (ver. 21.0) program. The main results of this study are as follows. First, if the rational efficiency index is high and the aesthetic consumption index is low, the probability of being classified as a group of female was 96.8%. On the other hand, if the rational efficiency and perception of price index were low, the probability of being classified as a male group was 100%. Second, if the brand orientation, perception of price, and rational efficiency index were high, the probability of being classified as a capital area group was 97.3%. Contrary to the results presented above, the probability of being classified as a other area group was 82.1% when the brand orientation, commemoration rites, and status symbol index were low. Third, the status symbol and trend oriented index were high, and if the functionality index was low, the probability of being classified into daily life and fashion groups was 77.6%. On the contrary, if the status symbol index is low, the retention of membership and enjoy consumption index is high, the probability of being classified into exercise and competition groups was 81.0%.

• Clinical and Experimental Pediatrics
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• v.53 no.2
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• pp.210-214
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• 2010

Purpose : Cisplatin is highly effective for the treatment of solid tumors in children. However, the clinical use of cisplatin is limited by its ototoxicity. The aim of this study was to evaluate the ototoxicity in children treated with cisplatin. Method : We performed a single institution retrospective analysis of pediatric oncology patients who received cisplatin therapy between January 2001 and January 2008. Thirty-seven patients with sufficient medical and audiologic data were included in this study. Results : The median age at the time of diagnosis was 10.7 (range 3.8-6.7) years. There were 16 males and 21 females. The underlying diseases were osteosarcoma (15 cases), medulloblastoma (14 cases), germ cell tumors (7 cases), and hepatoblastoma (1 case). The median individual dose was $100mg/m^2$/cycle (56-200). The median cumulative dose was $480mg/m^2$ (200-1,490). Sixteen patients (43%) received cranial radiotherapy. Of the 37 patients, 17 developed hearing loss, leading to an overall incidence of 46%. Logistic regression showed that age at treatment (P =0.04) and cumulative dose of cisplatin (P =0.005) were the significant risk factors in predicting hearing loss in children treated with cisplatin. In all the patients who had hearing loss, there was neither improvement nor aggravation during the follow-up (3-8 months). Conclusion : The cumulative dose of cisplatin (>$500mg/m^2$) and younger age at treatment (<12 years) were 2 most important risk factors for ototoxicity in patients treated with cisplatin. Serial audiometric evaluations are needed in the patients with risk factors during and after cisplatin treatment.

• The Journal of the Acoustical Society of Korea
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• v.35 no.4
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• pp.261-271
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• 2016

In the prediction of response of a pile in soil, numerical approaches such as a finite element method are generally applied due to complicate nonlinear behaviors of soils. However, the numerical methods based on the finite elements require heavy efforts in pile and soil modelling and also take long computing time. So their usage is limited especially in the early design stage in which principal dimensions and properties are not specified and tend to vary. On the contrary, theoretical approaches adopting linear approximations for soils are relatively simple and easy to model and take short computing time. Therefore, if they are validated to be reliable, they would be applicable in predicting responses of a pile in soil, particularly in early design stage. In case of wind turbines regarded in this study, it is required to assess their natural frequencies in early stages, and in this simulation the supporting pile inserted in soil could be replaced with a simplified elastic boundary condition at the bottom end of the wind turbine tower. To do this, analysis for a pile in soil is performed in this study to extract the spring constants at the top end of the pile. The pile in soil can be modelled as a beam on elastic spring by assuming that the soils deform within an elastic range. In this study, it is attempted to predict pile deformations and influence factors for lateral loads by means of the beam-on-spring model. As two example supporting structures for wind turbines, mono pile and suction pile models with different diameters are examined by evaluating their influence factors and validated by comparing them with those reported in literature. In addition, the deflection profiles along the depth and spring constants at the top end of the piles are compared to assess their supporting features.

• Journal of Navigation and Port Research
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• v.26 no.1
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• pp.106-111
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• 2002

The estimation of pile bearing capacity is important since the design details are determined from the result. There are numerous ways of determining the pile design load, but only few of them are chosen in the actual design. According to the recent investigation in Korea, the formulas proposed by Meyerhof based on the SPT N values are most frequently chosen in the design stage. In the study, various static and dynamic formulas have been used in predicting the allowable bearing capacity of a pile. Further, the reliability of these formulas has been verified by comparing the perdicted values with the static and dynamic load test measurements. Also, in most cases, these methods of pile bearing capacity determination do not take the time effect consideration, the actual allowable load as determined from pile load test indicates severe deviation from the design value. The principle results of this study are summarized as follows : As a result of estimate the reliability in criterion of the Davisson method, t was showed that Terzaghi & Peck >Chin>Meyerhof > Modified Meyerhof method was the most reliable method for the prediction of bearing capacity. Comparisons of the various pile-driving formulas showed that Modified Engineering News was the most reliable method. However, a significant error happened between dynamic bearing capacity equation was judged that uncertainty of hammer efficiency, characteristics of variable, time effect etc... was not considered. As a result of considering time effect increased skin friction capacity higher than end bearing capacity. It was found out that it would be possible to increase the skin friction capacity 1.99 times higher than a driving. As a result of considering 7 day's time effect, it was obtained that Engineering news, Modified Engineering News, Hiley, Danish, Gates, CAPWAP(CAse Pile Wave Analysis Program) analysis for relation, repectively, $Q_{u(Restrike)} / Q_{u(EOID)} = 0.98t_{0.1}$ , $0.98t_{0.1}$, $1.17t_{0.1}$, $0.88t_{0.1}$, $0.89t_{0.1}$, $0.97t_{0.1}$.

• Korean Journal of Cognitive Science
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• v.28 no.1
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• pp.1-26
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• 2017

This study investigated the cortical generators of P300 in college students with schizotypal traits by using an auditory oddball paradigm, event-related potentials (ERPs) and standardized low resolution brain electromagnetic tomography (sLORETA) model. We also investigated the relationship between the current density of P300 and the clinical symptoms of schizophrenia. Based on the scores of Schizotypal Personality Questionnaire(SPQ), schizotypal trait (n=37) and control (n=42) groups were selected. For the measurement of P300, an auditory oddball paradigm, in which frequent standard tones (1000Hz) and rare target tones (1500Hz) were presented randomly, was used. Participants were required to count the number of the target tones during the task and report this at the end of the experiment. The two groups did not differ significantly in the accuracy of the oddball task. The schizotypal trait group showed significantly smaller P300 amplitudes than control group. In terms of source localization, both groups showed the P300 current density over bilateral frontal, parietal, temporal and occipital lobes. However, the schizotypal trait group showed significantly reduced activations in the left superior temporal gyrus and the right middle temporal gyrus, but increased activations in both left inferior frontal gyrus and right superior frontal gyrus compared to the control group. Furthermore, a negative correlation between the current density of the right superior frontal gyrus and SPQ disorganization score was found in the schizotypal trait group. These findings indicate that the individuals with schizotypal traits have dysfunctions of frontal and temporal areas, which are known to be the source of P300, as observed in patients with schizophrenia. In addition, the present results indicate that the disorganization score, rather than total score, of the SPQ is useful in predicting the risk of future schizophrenia.

• Clinical and Experimental Pediatrics
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• v.46 no.10
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• pp.977-982
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• 2003

Purpose : This study aimed to examine the excretion of various urinary proteins in children with a history of urinary tract infection(UTI), with or without vesicoureteral reflux(VUR) or reflux nephropathy, and to identify means of predicting the severity of VUR or the presence of reflux nephropathy as indicated by these markers, and to know how these markers are changed after resolution of VUR. Methods : We studied 30 children with previous UTI, without VUR and renal scarring(group I), 12 children with VUR, without evidence of renal scarring(group II), and 34 children with VUR and renal scarring(group III). 24-hour or 12-hour urine ${\beta}_2$ microglobulin(${\beta}_2$ MG), microalbumin and N-acetyl-${\beta}$-D-glucosaminidase(NAG) were measured in each child. Urinary protein excretions were analyzed according to the degree of VUR(mild VUR : a grade reflux I-III, severe VUR : a grade reflux IV-V). Cases of bilateral VUR were graded by the higher grade of reflux detected. A total of 46 children with primary VUR were followed. Among these patients, VUR was completely resolved in 16 children. Voiding cystourethrography(VCUG) and DMSA scan were performed every year. Values for urinary markers were estimated every year. Results : 24 or 12 hour urine microalbumin and NAG excretions were significantly increased in group III compared to group I(microalbumin : $27.7{\pm}26.0mg/gCr$ vs $15.0{\pm}10.7mg/gCr$, P<0.05, NAG : $15.2{\pm}18.7U/gCr$ vs $3.4{\pm}2.2U/gCr$, P<0.05). Urinary ${\beta}_2$ MG excretions were not significantly different between groups. Urinary NAG excretions were elevated in the group of children with severe VUR compared to mild VUR($26.8{\pm}27.1U/gCr$ vs $7.6{\pm}3.8U/gCr$, P<0.05). After resolution of VUR, urinary microalbumin and NAG excretions were decreased(P<0.05). Conclusion : Urinary microalbumin and NAG may be useful clinical indicators to predict the presence of reflux nephropathy and the resolution of VUR. Especially, urinary NAG excretions may be used as a possible method to predict the severity of VUR.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.5
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• pp.492-501
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• 2007

Coastal disasters have become one of the most important issues in every coastal country. In Korea, coastal disasters such as storm surge, sea level rise and extreme weather have placed many coastal regions in danger of being exposed or damaged during subsequent storms and gradual shoreline retreat. A storm surge is an onshore gush of water associated with a tow pressure weather system, typically in typhoon season. However, it is very difficult to predict storm surge height and inundation due to the irregularity of the course and intensity of a typhoon. To provide a new scheme of typhoon damage prediction model, the scenario which changes the central pressure, the maximum wind radius, the track and the proceeding speed by corresponding previous typhoon database, was composed. The virtual typhoon scenario database was constructed with individual scenario simulation and evaluation, in which it extracted the result from the scenario database of information of the hereafter typhoon and information due to climate change. This virtual typhoon scenario database will apply damage prediction information about a typhoon. This study performed construction and analysis of the simulation system with the storm surge/coastal inundation model at Masan coastal areas, and applied method for predicting using the scenario of the storm surge.