• Toxicological Research
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• v.34 no.2
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• pp.111-125
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• 2018

Solvents can be used in the manufacture of medicinal products provided their residual levels in the final product comply with the acceptable limits based on safety data. At worldwide level, these limits are set by the "Guideline Q3C (R6) on impurities: guideline for residual solvents" issued by the ICH. Diisopropyl ether (DIPE) is a widely used solvent but the possibility of using it in the pharmaceutical manufacture is uncertain because the ICH Q3C guideline includes it in the group of solvents for which "no adequate toxicological data on which to base a Permitted Daily Exposure (PDE) was found". We performed a risk assessment of DIPE based on available toxicological data, after carefully assessing their reliability using the Klimisch score approach. We found sufficiently reliable studies investigating subchronic, developmental, neurological toxicity and carcinogenicity in rats and genotoxicity in vitro. Recent studies also investigated a wide array of toxic effects of gasoline/DIPE mixtures as compared to gasoline alone, thus allowing identifying the effects of DIPE itself. These data allowed a comprehensive toxicological evaluation of DIPE. The main target organs of DIPE toxicity were liver and kidney. DIPE was not teratogen and had no genotoxic effects, either in vitro or in vivo. However, it appeared to increase the number of malignant tumors in rats. Therefore, DIPE could be considered as a non-genotoxic animal carcinogen and a PDE of 0.98 mg/day was calculated based on the lowest No Observed Effect Level (NOEL) value of $356mg/m^3$ (corresponding to 49 mg/kg/day) for maternal toxicity in developmental rat toxicity study. In a worst-case scenario, using an exceedingly high daily dose of 10 g/day, allowed DIPE concentration in pharmaceutical substances would be 98 ppm, which is in the range of concentration limits for ICH Q3C guideline class 2 solvents. This result might be considered for regulatory decisions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.15 no.26
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• pp.111-117
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• 1992

In the stock marketing. investor needs speedy and accurate decision making for the investment. A stock exchange index provides the important index of the early of 1993 in Korea using Fuzzy Delphi Method(F. D. M) which is widely used to a mid and long range forecasting in decision making problem. In the Fuzzy Delphi method, considerably qualified experts an first requested to give their opinion seperately and without intercommunication. The forecasting data of experts consist of Triangular Fuzzy Number (T.F.N) which represents the pessimistic, moderate, and optimistic forecast of a stock exchange index. A statistical analysis and dissemblance index are then made of these subject data. These new information are then transmitted to the experts once again, and the process of reestimation is continued until the process converges to a reasonable stable forecast of stock exchange index. The goal of this research is to forecast the stock exchange index using F.D.M. in which subjective data of experts are transformed into quasi -objective data index by some statistical analysis and fuzzy operations. (a) A long range forecasting problem must be considered as an uncertain but not random problem. The direct use of fuzzy numbers and fuzzy methods seems to be more compatible and well suited. (b) The experts use their individual competency and subjectivity and this is the very reason why we propose the use of fuzzy concepts. (c) If you ask an expert the following question: Consider the forecasting of the price index of stocks in the near future. This experts wi11 certainly be more comfortable giving an answer to this question using three types of values: the maximum value, the proper value, and the minimum value rather than an answer in terms of the probability.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.40 no.6
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• pp.367-373
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• 2007

We assessed the stock of the southern bluefin tuna (SBT, Thunnus maccoyii) by applying the MULTIFAN-CL model. The model is spatially disaggregated, with the population and fisheries stratified into a number of regions within the overall stock range. Catch, effort, length-frequency, and tagging data from 1965 to 2003 were stratified by three regions and four quarters (Jan-Mar, Apr-Jun, Jul-Sept and Oct-Dec). These data were used to estimate the instantaneous fishing mortality (F), biomass, spawning biomass, recruitment, and so on. The Commission for the Conservation of Southern Bluefin Tuna (CCSBT) used only Japanese data and did not consider migration for the SBT stock assessment. By contrast, we used Japanese, Australian, New Zealand, Taiwanese, and Korean data, and considered migration. As a result, the estimated annual average F of all age classes was 0.073/yr and the F of age class 6-10 was the highest. The results also showed that the biomass and recruitment of SBT had declined significantly after 1965. Compared with the CCSBT results, the estimated spawning biomass in this study was lower and more uncertain. However, we will conduct a sensitivity analysis to get more accurate biological parameters and results. In addition, we need to use the bootstrap resampling method to quantify the uncertainty.

• Journal of KIISE
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• v.44 no.11
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• pp.1149-1155
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• 2017

Recently, with the development of communication technology, it has become possible to collect various sensor data that indicate the environmental stimuli within a space. In this paper, we propose a group emotion prediction system using a modular Bayesian network that was designed considering the psychological impact of environmental stimuli. A Bayesian network can compensate for the uncertain and incomplete characteristics of the sensor data by the probabilistic consideration of the evidence for reasoning. Also, modularizing the Bayesian network has enabled flexible response and efficient reasoning of environmental stimulus fluctuations within the space. To verify the performance of the system, we predict public emotion based on the brightness, volume, temperature, humidity, color temperature, sound, smell, and group emotion data collected in a kindergarten. Experimental results show that the accuracy of the proposed method is 85% greater than that of other classification methods. Using quantitative and qualitative analyses, we explore the possibilities and limitations of probabilistic methodology for predicting group emotion.

• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.117-127
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• 2009

This study analyzed the uncertainty of the forecasted link traffic flow, and estimated of the interval link flow using Korea Transport Data Base (KTDB) to consider those risks into the feasibility study. In the paper, the uncertainty was analyzed according to the stochastic variation of the KTDB origin-destination traffic. It was found that the uncertainty of the entire network traffic forecasts was 15.4% in average,. when the stochastic variation of the KTDB was considered. The results showed that the more congested the roads were, the bigger the uncertainty of forecasted link traffic flow were found. In particular, we estimated the variance of the forecasted traffic flow, and suggested interval estimates of the forecasted traffic flow instead of point estimates which were presented in the common feasibility studies. These results are expected to contribute the quantitative evaluation of uncertain road investment projects and to provide valuable information to the decision makers for the transport investment.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.211-221
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• 2006

Manufacturing Execution System(MES) immediately enables users to share the information of systems industrywide, efficiently manages synthetic information with data collection through treating the data in a fast way, and helps their decision-making. MES for real-time information processing requires certain conditions such as data modeling of RFID, which has recently attracted attentions, and monitoring of each product unit from manufacture to sales. However, in the middle of processing the unit with a RFID tag, transponders(readers) can't often read the tag due to reader's malfunctions, intentional damages, loss and the circumstantial effects; for that reason, users are unable to confirm the location of the product unit. In this case, users cannot avoid tracing the path of units with uncertain clues. In this paper we suggest that the unique MES based on RFID and Bayesian Network can immediately track the product unit, and show how to evaluate it.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.6
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• pp.1167-1174
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• 2009

In the monitoring of a patient in a sickroom, not only the physiologic and environmental data of the patient, which is automatically measured, but also the clinical data(clinical chart)of the patient, which is drew up by a doctor or nurse, are recognized as important data. However, since in the current environment of a sickroom, clinical data is collected being divided from the data that is automatically measured, the two data are used without an effective integration. This is because the integration of the two data is difficult due to their different collection times, which leads the reconstruction of clinical data to be remarkably uncertain. In order to solve these problems, a method to synchronize the continuous environmental data of a sickroom and clinical data is appearing as an important measure. In addition, the increase of use of small machines and the development of solutions based on wireless communications provide a communication platform to the developers of health care. Thus, this paper realizes a remote system for taking care of patients based on a web that uses mobile phones. That is, clinical data made by a nurse or doctor and the environmental data of a sick room comes to be collected by a collection module through a wireless sensor network. An observer can see clinical data and the environmental data of a sickroom through his/her mobile phone, integrating and storing his/her data into the database. Families of a patient can see clinical data made by hospital and the environment of the sick room of the patent through their computers or mobile phones outside the hospital. Through the system,hospital can provide better medical services to patients and their families.

• Journal of the Ergonomics Society of Korea
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• v.31 no.1
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• pp.49-61
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• 2012

Objective: The aim of this study is to offer a holism based Service Experience Analysis System(HSEAS) for service design. Background: Customer experience has been focused in a lot of service area. But it is difficult to understand the customer's needs and their experiences because it's so complex and uncertain. Thus it needs holistic approach that means it's difficult to explain general character merely through the understanding of small parts that composes an object and it must be analyzed within the overall context. Method: Accordingly, the thesis paper proposes the Service Experience Analysis System that satisfies the four following needs. (1) Need of solid Experience Framework in which the special quality of the service experience is considered, (2) need of support for the semantic cohesion between different kinds of data, (3) need of support for the management and search of vast data, and (4) need of building the knowledge base system for collaborative research. Results: HSEAS combines the short information in the customers' words and behaviors or situations and circumstances and provides a place of analysis where the context of the general experience can be read and allows concrete understanding of the actual state and factor of the problem as a Combined Data Analysis Tool. Conclusion: HSEAS becomes the center of information management, analysis and connection and it provides a free collaboration place where physical condition has no relations to as a knowledge base system based on network. Application: It is expected that length and width will be added to the analysis and assistance for effectively accumulating information will be provided in the area of diverse service.

• Journal of Forest and Environmental Science
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• v.28 no.3
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• pp.158-169
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• 2012

Sabah has experienced a rapid decline in the extent of forest cover. The precise impact of habitat loss on the conservation status of the plants of Sabah is uncertain. In this study we use the niche modelling algorithm MAXENT to construct preliminary, revised and final ecological niche models for Dipterocarpus lamellatus and Dipterocarpus ochraceus and combined these models with data on current land-use to derive conservation assessments for each species. Preliminary models were based on herbarium data alone. Ground surveys were conducted to evaluate the performance of these preliminary models, and a revised niche model was generated from the combined herbarium and ground survey data. The final model was obtained by constraining the predictions of the revised models by filters. The range overlap between the preliminary and revised models was 0.47 for D. lamellatus and 0.39 for D. ochraceus, suggesting poor agreement between them. There was substantial variation in estimates of habitat loss for D. ochraceus, among the preliminary, revised and constrained models, and this has the potential to lead to incorrect threat assessments. From these estimates of habitat loss, the historic distribution and estimates of population size we determine that both species should be classified as Critically Endangered under IUCN Red List guidelines. Our results suggest that ground-truthing of ecological niche models is essential, especially if the models are being used for conservation decision making.

• Safety and Health at Work
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• v.7 no.4
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• pp.307-316
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• 2016

Background: Resilience engineering (RE) is a new paradigm that can control incidents and reduce their consequences. Integrated RE includes four new factors-self-organization, teamwork, redundancy, and fault-tolerance-in addition to conventional RE factors. This study aimed to evaluate the impacts of these four factors on RE and determine the most efficient factor in an uncertain environment. Methods: The required data were collected through a questionnaire in a petrochemical plant in June 2013. The questionnaire was completed by 115 respondents including 37 managers and 78 operators. Fuzzy data envelopment analysis was used in different ${\alpha}$-cuts in order to calculate the impact of each factor. Analysis of variance was employed to compare the efficiency score means of the four abovementioned factors. Results: The results showed that as ${\alpha}$ approached 0 and the system became fuzzier (${\alpha}=0.3$ and ${\alpha}=0.1$), teamwork played a significant role and had the highest impact on the resilient system. In contrast, as ${\alpha}$ approached 1 and the fuzzy system went toward a certain mode (${\alpha}=0.9$ and ${\alpha}=1$), redundancy had a vital role in the selected resilient system. Therefore, redundancy and teamwork were the most efficient factors. Conclusion: The approach developed in this study could be used for identifying the most important factors in such environments. The results of this study may help managers to have better understanding of weak and strong points in such industries.