• Tuberculosis and Respiratory Diseases
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• v.49 no.1
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• pp.82-92
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• 2000

Background : In chronic airway disease, mucus secretion is increased, but extraction of mucin, which is the main component of mucus secretion, is a very complicated and limited in clinical use. Recently, monoclonal antibody for mucin was developed for possible clinical use. In this study, cellular analysis and quantification of respiratory mucin in sputum of patients with chronic airway diseases were performed. Method : Sputum was collected from patients with asthma(n=33), bronchiectasis(n=8) or chronic bronchitis (n=13) by spontaneous expectoration or by hypertonic saline induction. Collected sputums was treated by 0.1% dithiotreitol to dissociate the disulfide bond of the mucus and filtered through a nylon gauze. Total cell count, viability and differential count were measured. For detection of mucin, collected samples were treated with sodium dodecyl sulfate polyacrylamide gel electrophoresis and then with monoclonal antibody(HMO2), as the primary antibody, and PAS stain. The amount of mucin was measured with ELISA by HMO2. Correlation with clinical information, cellular analysis, and amount of measured mucin were analyzed. Results : Total cell counts of sputum were significantly increased in patients with bronchiectasis but viability remained the same. Eosinophils were significantly increased in patients with asthma, neutrophils in bronchiectasis chronic bronchitis, respectively (p<0.05). The results of Western blotting and PAS staining confirmed the presence of glycoproteins and matched? with mucin. The amounts of mucin measured by ELISA were not significantly different among the disease groups. Significant correlation was identified between the amount of mucin and viability(r=-0.482, p<0.05). Conclusion : Inflammatory cells in the sputum of those with chronic airway disease were different for each disease type. Measurement of mucin by ELISA via monoclonal antibodies may be a simple method for the evaluation of chronic airway disease.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.13 no.1
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• pp.36-43
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• 2010

Purpose: The aim of this study was to evaluate the clinical features and factors contributing to treatment outcome for chronic functional constipation in children. Methods: We analyzed the medical records of patients with constipation, who visited the inpatient or outpatient clinic of the Department of Pediatrics of Pusan National University Hospital, between January 1998 and December 2007. The clinical features, outcomes, and factors affecting the treatment response according to the main drug (lactulose vs. PEG 4000) were analyzed retrospectively. Results: Two hundred forty children (142 males and 98 females) were enrolled in this study. The mean age was 51.2${\pm}$37.9 months. The duration of symptoms was 32.6${\pm}$33.7 months. The accompanying symptoms were as follows: encopresis, 91 (30.4%); abdominal pain, 76 (31.6%); and blood-tinged stool, 37 (15.4%). The treatment response was achieved earlier in females (p<0.001), patients with accompanying symptoms (p<0.05), and patients treated with PEG 4000 (p=0.001). The duration of symptoms (p<0.05) and stool frequency before treatment (p<0.05) were related to a delayed treatment response. Relapse occurred in 7 children, all of whom were treated successfully later. Conclusion: Factors contributing to treatment response are female gender, accompanying symptoms, duration of symptoms, and stool frequency before treatment. PEG 4000 is superior to lactulose in response time and taken into consideration as a primary drug for the treatment of functional constipation of children. Early treatment and sufficient treatment time may also be important factors to achieve an early response and prevent relapse.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.99-120
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• 2010

Due to the wide spread of customers' frequent access of non face-to-face services, there have been many attempts to improve customer satisfaction using huge amounts of data accumulated throughnon face-to-face channels. Usually, a call center is regarded to be one of the most representative non-faced channels. Therefore, it is important that a call center has enough agents to offer high level customer satisfaction. However, managing too many agents would increase the operational costs of a call center by increasing labor costs. Therefore, predicting and calculating the appropriate size of human resources of a call center is one of the most critical success factors of call center management. For this reason, most call centers are currently establishing a department of WFM(Work Force Management) to estimate the appropriate number of agents and to direct much effort to predict the volume of inbound calls. In real world applications, inbound call prediction is usually performed based on the intuition and experience of a domain expert. In other words, a domain expert usually predicts the volume of calls by calculating the average call of some periods and adjusting the average according tohis/her subjective estimation. However, this kind of approach has radical limitations in that the result of prediction might be strongly affected by the expert's personal experience and competence. It is often the case that a domain expert may predict inbound calls quite differently from anotherif the two experts have mutually different opinions on selecting influential variables and priorities among the variables. Moreover, it is almost impossible to logically clarify the process of expert's subjective prediction. Currently, to overcome the limitations of subjective call prediction, most call centers are adopting a WFMS(Workforce Management System) package in which expert's best practices are systemized. With WFMS, a user can predict the volume of calls by calculating the average call of each day of the week, excluding some eventful days. However, WFMS costs too much capital during the early stage of system establishment. Moreover, it is hard to reflect new information ontothe system when some factors affecting the amount of calls have been changed. In this paper, we attempt to devise a new model for predicting inbound calls that is not only based on theoretical background but also easily applicable to real world applications. Our model was mainly developed by the interactive decision tree technique, one of the most popular techniques in data mining. Therefore, we expect that our model can predict inbound calls automatically based on historical data, and it can utilize expert's domain knowledge during the process of tree construction. To analyze the accuracy of our model, we performed intensive experiments on a real case of one of the largest car insurance companies in Korea. In the case study, the prediction accuracy of the devised two models and traditional WFMS are analyzed with respect to the various error rates allowable. The experiments reveal that our data mining-based two models outperform WFMS in terms of predicting the amount of accident calls and fault calls in most experimental situations examined.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.334-346
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• 2022

There is a lack of knowledge and information on the understanding and application of the Process Safety Management (PSM) system, recognized as a major cause of industrial accidents in small-and medium-sized workplaces. Hence, it is necessary to prepare a protocol to secure the practical and continuous levels of implementation for PSM and eliminate human errors through tracking management. However, insufficient research has been conducted on this. Therefore, this study investigated and analyzed the various violations in the administrative measures, based on the regulations announced by the Ministry of Employment and Labor, in approximately 200 small-and medium-sized PSM workplaces with fewer than 300 employees across in korea. This study intended to contribute to the prevention of major industrial accidents by developing a facility maintenance web program that removed human errors in small-and medium-sized workplaces. The major results are summarized as follows. First, It accessed the web via a QR code on a smart device to check the equipment's specification search function, cause of failure, and photos for the convenience of accessing the program, which made it possible to make requests for the it inspection and maintenance in real time. Second, it linked the identification of the targets to be changed, risk assessment, worker training, and pre-operation inspection with the program, which allowed the administrator to track all the procedures from start to finish. Third, it made it possible to predict the life of the equipment and verify its reliability based on the data accumulated through the registration of the pictures for improvements, repairs, time required, cost, etc. after the work was completed. It is suggested that these research results will be helpful in the practical and systematic operation of small-and medium-sized PSM workplaces. In addition, it can be utilized in a useful manner for the development and dissemination of a facility maintenance web program when establishing future smart factories in small-and medium-sized PSM workplaces under the direction of the government.

• Economic and Environmental Geology
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• v.45 no.6
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• pp.643-659
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• 2012

The Chungju Fe-REE deposit is located in the Kyemyeongsan Formation of the Ogcheon Group. The Kyemyeongsan Formation includes meta-volcanic rocks and pegmatite hosted REE deposit which show different kind of REE-containing minerals. The meta-volcanic rocks hosted REE deposits' main REE minerals are allanite, zircon, apatite, and sphene, whereas the pegmatite hosted REE deposits is mainly composed of fergusonite, and karnasurtite, zircon, thorite. The meta-volcanic rock hosted major REE mineral is allanite as the form of aggregation and contains 23.89-29.19 wt% TREO (Total Rare Earth Oxide), 4.71-9.92 wt% $La_2O_3$, 11.30-14.33 wt% $Ce_2O_3$, 0.11-0.29 wt% $Y_2O_3$, 0.15-0.94 wt% $ThO_2$, as a formula of (Ca, Y, REE, Th)$_{2.095}$(Mg, Al, Ti, Mn, $Fe^{3+})_{2.770}(SiO_4)_{2.975}(OH)$. Accompanying REE in a coupled substitution for $Ca^{2+}$ (M1 site) and $Al^{3+}-Fe^{2+}$ (M2 site) leads to a large chemical variety. Due to the allanite's high contents of Fe, it belongs to Ferrialanite. The pegmatite hosted deposit's domi-nant REE mineral is fergusonite as prismatic or subhedral grains associated with zircon, fluorite and karnasurtite. Geochemical composition of the fergusonite($YNbO_4$) suggests substitution of Y-REE and Y-Th in A-site, and Nb-Ta-Ti in B-site, furthermore the proportion of $Y_2O_3$ and $Nb_2O_5$ is oddly 1:1.5 comparing to the ideal ratio 1:1 and Nb is higher than Y, also A-site Y actively substitutes with REE. Karnasurtite in pegmatite variously ranges 9.16-22.88 wt% $Ce_2O_3$, 2.15-9.16 wt% and $La_2O_3$, 0.44-10.8 wt% $ThO_2$, as a calculated formula (Y, REE, Th, K, Na, Ca)$_{1.478}(Ti, Nb)_{1.304}$(Mg, Al, Mn, $Fe^{3+})_{0.988}$(Si, P)$_{1.431}O_7(OH)_4{\cdot}3H_2O$. Firstly the 870-860 Ma is the initial age of the supercontinent Rhodinia dispersal and subsequent A-1 type volcanism, which contains Fe, REE, and HFS(High Field Strength elements; Nb, Zr, Y etc.) elements in Fe-rich meta-volcanic rocks dominant Kyemyeongsan Formation, might mineralized allanite. Another synthesis is that regional metamorphism at late Paleozoic 300-280 Ma(Cho et al., 2002) might cause allanite mineralization. Also pegmatite REE mineralization highly related to the granite intrusion over the Chungju area in Jurassic(190 Ma; Koh et al., 2012). Otherwise above all, A-1 type volcanism at the same time of the Kyemyeongsan Formation development, regional metamorphism and pegmatite, might have caused REE mineralization. Although REE ore bodies display a close spatial association, each ore bodies display temporal distinction, different mineral assemblage and environment of ore formation.

• Journal of radiological science and technology
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• v.31 no.1
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• pp.17-23
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• 2008

Purpose : Because there is a difference depending on the environment as for an inspection equipment the important part of bone density scan and the precision/accuracy of a tester, the management of quality must be made systematically. The equipment failure caused by overload effect due to the aged equipment and the increase of a patient was made frequently. Thus, the replacement of equipment and additional purchases of new bonedensity equipment caused a compatibility problem in tracking patients. This study wants to know whether the clinical changes of patient's bonedensity can be accurately and precisely reflected when used it compatiblly like the existing equipment after equipment replacement and expansion. Materials and methods : Two equipments of GE Lunar Prodigy Advance(P1 and P2) and the Phantom HOLOGIC Spine Road(HSP) were used to measure equipment precision. Each device scans 20 times so that precision data was acquired from the phantom(Group 1). The precision of a tester was measured by shooting twice the same patient, every 15 members from each of the target equipment in 120 women(average age 48.78, 20-60 years old)(Group 2). In addition, the measurement of the precision of a tester and the cross-calibration data were made by scanning 20 times in each of the equipment using HSP, based on the data obtained from the management of quality using phantom(ASP) every morning (Group 3). The same patient was shot only once in one equipment alternately to make the measurement of the precision of a tester and the cross-calibration data in 120 women(average age 48.78, 20-60 years old)(Group 4). Results : It is steady equipment according to daily Q.C Data with $0.996\;g/cm^2$, change value(%CV) 0.08. The mean${\pm}$SD and a %CV price are ALP in Group 1(P1 : $1.064{\pm}0.002\;g/cm^2$, $%CV=0.190\;g/cm^2$, P2 : $1.061{\pm}0.003\;g/cm^2$, %CV=0.192). The mean${\pm}$SD and a %CV price are P1 : $1.187{\pm}0.002\;g/cm^2$, $%CV=0.164\;g/cm^2$, P2 : $1.198{\pm}0.002\;g/cm^2$, %CV=0.163 in Group 2. The average error${\pm}$2SD and %CV are P1 - (spine: $0.001{\pm}0.03\;g/cm^2$, %CV=0.94, Femur: $0.001{\pm}0.019\;g/cm^2$, %CV=0.96), P2 - (spine: $0.002{\pm}0.018\;g/cm^2$, %CV=0.55, Femur: $0.001{\pm}0.013\;g/cm^2$, %CV=0.48) in Group 3. The average error${\pm}2SD$, %CV, and r value was spine : $0.006{\pm}0.024\;g/cm^2$, %CV=0.86, r=0.995, Femur: $0{\pm}0.014\;g/cm^2$, %CV=0.54, r=0.998 in Group 4. Conclusion: Both LUNAR ASP CV% and HOLOGIC Spine Phantom are included in the normal range of error of ${\pm}2%$ defined in ISCD. BMD measurement keeps a relatively constant value, so showing excellent repeatability. The Phantom has homogeneous characteristics, but it has limitations to reflect the clinical part including variations in patient's body weight or body fat. As a result, it is believed that quality control using Phantom will be useful to check mis-calibration of the equipment used. A value measured a patient two times with one equipment, and that of double-crossed two equipment are all included within 2SD Value in the Bland - Altman Graph compared results of Group 3 with Group 4. The r value of 0.99 or higher in Linear regression analysis(Regression Analysis) indicated high precision and correlation. Therefore, it revealed that two compatible equipment did not affect in tracking the patients. Regular testing equipment and capabilities of a tester, then appropriate calibration will have to be achieved in order to calculate confidential BMD.