• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.209-212
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• 2011

Triangulation is a typical method to locate or identify the location, which requires inherently at least three pre-recognized reference points. In some cases, owing to out of reachability to communication facility the target node can not reachable always to three base stations. This paper presents a predictive method, which can estimate the location of the moving target node in real time even though the target could not get in touch with all three base stations. The method is based on the PID-controlled Moving Objects Spatio-Temporal Model Algorithm. This can predict the moving direction of the moving target, and then combine with the past target position information to judge accurately the location.

• Fashion & Textile Research Journal
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• v.16 no.2
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• pp.266-274
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• 2014

Parametric bodies reproduce the actual shape of human body parts and should be convenient for general users to change size to judge the visual fit of clothes on-line. In this study, three parametric bodies(i.e. I, C, D ) were compared to verify the accuracy of the provided body dimensions and reproducibility to a target model. To compare reproducibility, the 20s female standard virtual model developed for an apparel industry by Korean agency for technology and standards is used. The investigation of existing parameters showed that the numbers and kinds of parameters provided by each program were different with some errors in notation; in addition, some of virtual body dimensions went beyond the maximum allowable error. The result of changing each parametric body to the 20s female standard body showed that D, C, I in order produced better reproducibility for body dimensions. There were different levels of protrusion and concavity in the virtual cross sections and virtual longitudinal sections despite the small differences in body dimensions and cross sectional areas; in addition, some parametric body was not bilateral symmetry. The results of this study can be used as basic information in the standardization of a virtual model used in a virtual garment program.

• Journal of Korean Society on Water Environment
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• v.24 no.1
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• pp.1-6
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• 2008

Biological and chemical sensors are the two most frequently used sensors to monitor the water resource. Chemical sensor is very accurate to pick up the types and to measure the concentration of the chemical substance. Drawback is that it works for just one type of chemical substance. Therefore a lot of expensive monitoring system needs to be installed to determine the safeness of the water, which costs too much expense. Biological sensor, on the contrary, can judge the degree of pollution of the water with just one monitoring system. However, it is not easy to figure out the type of contaminant with a biological sensor. In this study, an endeavor is made to identify the toxicant in the water using the shape of the chlorophyll fluorescence induction curve (FIC) from a biological monitoring system. Wem-tox values are calculated from the amount of flourescence of contaminated and reference water. Curve fitting is executed to find the representative curve of the raw data of Wem-tox values. Then the curves are digitalized at the same interval to train the neural network model. Taguchi method is used to optimize the neural network model parameters. The optimized model shows a good capacity to figure out the toxicant from FIC.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.99-106
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• 2013

Generally, software development schedule compression is decided within 75% of nominal schedule. However, there are some difficulties when we judge the possibility of development schedule compression because a nominal schedule has not been definitely. Therefore, this paper investigates various nominal schedule estimation models and decides the optimum range. Basing on the performance of ISBSG Release 8,614 projects are extracted from the actual 1,595 projects. We presented development effort estimation model from those data. Also, we derived the development schedule model from the development effort. When you apply the proposed model, you will be able to estimate development effort and schedule required for the development more actually.

• YAKHAK HOEJI
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• v.47 no.2
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• pp.110-119
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• 2003

The purpose of the present study was to kinetically investigate the carrier-mediated uptake in the hepatic transport of organic anions, and to simulate the ″in vivo counter-transport″ phenomena, using kinetic model which was developed in this study. The condition that the mobility of carrier-ligand complex is greater than that of free carrier is not essential for the occurrence of ″counter-transport″ phenomenon. To examine the inhibitory effects on the initial uptake of a ligand by the liver, it is necessary to judge whether the true counter-transport mechanism (trans-stimulation) is working or not. The initial plasma disappearance curves of a organic anion were then kinetically analyzed based on a flow model, in which the ligand is eliminated only from the peripheral compartment (liver compartment). Moreover, ″in vive counter-transport″ phenomena were simulated based on the perfusion model which incorporated the carrier-mediated transport and the saturable intracellular binding. The ″in vivo counter-transport″ phenomena in the hepatic transport of a organic anion were well demonstrated by incorporating the carrier-mediated process. However, the ″in vivo counter-transport″ phenomena may be also explained by the enhancement of back diffusion due to the displacement of intracellular binding. In conclusion, one should be more cautious in interpreting data obtained from so-called ″in vivo counter-transport″ experiments.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.138-151
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• 2022

Cladding ballooning and rupture are the important phenomena at the early stage of a severe accident. Most severe accident analysis codes determine the cladding rupture based on simple parameter models. In this paper, a FRTMB module was developed using the thermal-mechanical model to analyze the fuel mechanical behavior. The purpose is to judge the cladding rupture with the severe accident analysis code. The FRTMB module was integrated into the self-developed severe accident analysis code ISAA to simulate the PHEBUS FPT3 experiment. The predicted rupture time and temperature of the cladding were basically consistent with the measured values, which verified the correctness and effectiveness of the FRTMB module. The results showed that the rising of gas pressure in the fuel rod and high temperature led to cladding ballooning. Consequently, the cladding hoop strain exceeded the strain limit, and the cladding burst. The developed FRTMB module can be applied not only to rod-type fuel, but also to plate-type fuel and other types of reactor fuel rods. Moreover, the FRTMB module can improve the channel blockage model of ISAA code and make contributions to analyzing the effect of clad ballooning on transient and subsequent parts of core degradation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2927-2941
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• 2022

The primary task of machine fault diagnosis is to judge whether the current state is normal or damaged, so it is a typical binary classification problem with mutual exclusion. Mutually exclusive events and out-of-domain detection have one thing in common: there are two types of data and no intersection. We proposed a fusion model method to improve the accuracy of machine fault diagnosis, which is based on the mutual exclusivity of events and the commonality of out-of-distribution detection, and finally generalized to all binary classification problems. It is reported that the performance of a convolutional neural network (CNN) will decrease as the recognition type increases, so the variational auto-encoder (VAE) is used as the primary model. Two VAE models are used to train the machine's normal and fault sound data. Two reconstruction probabilities will be obtained during the test. The smaller value is transformed into a correction value of another value according to the mutually exclusive characteristics. Finally, the classification result is obtained according to the fusion algorithm. Filtering normal data features from fault data features is proposed, which shields the interference and makes the fault features more prominent. We confirm that good performance improvements have been achieved in the machine fault detection data set, and the results are better than most mainstream models.

• The Journal of Bigdata
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• v.6 no.1
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• pp.51-62
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• 2021

In the field of medical artificial intelligence, there have been a lot of researches on disease prediction and classification algorithms that can help doctors judge, but relatively less interested in artificial intelligence that can help medical consumers acquire and judge information. The fact that more than 150,000 questions have been asked about which hospital to go over the past year in NAVER portal will be a testament to the need to provide medical information suitable for medical consumers. Therefore, in this study, we wanted to establish a classification model that classifies 8 medical subjects for symptom text directly described by patients which was collected from NAVER portal to help consumers choose appropriate medical subjects for their symptoms. In order to ensure the validity of the data involving patients' subject matter, we conducted similarity measurements between objective symptom text (typical symptoms by medical subjects organized by the Seoul Emergency Medical Information Center) and subjective symptoms (NAVER data). Similarity measurements demonstrated that if the two texts were symptoms of the same medical subject, they had relatively higher similarity than symptomatic texts from different medical subjects. Following the above procedure, the classification model was constructed using a ridge regression model for subjective symptom text that obtained validity, resulting in an accuracy of 0.73.

• Journal of Korean Society of Forest Science
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• v.98 no.3
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• pp.351-356
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• 2009

This study purposed to judge potential possibility of building highly precise empirical model using environmental variables. Environmental variables such as altitude, mean annual rainfall, mean annual temperature and organic matter ratio of soil were added to height and diameter model for Chamaecyparis obtusa, and examined accuracy and residuals of prediction model. Improvement in precision was found for the Gompertz polymorphic height model by including mean temperature and altitude as independent variables, while the Gompertz diameter model with annual rainfall and altitude was showed improvement of precision and accuracy. Comparing the improvement of precision between the model before adding environmental variables and the model after adding them, an improvement or some ratio was obtained though it is not obvious. Therefore, there is enough proof that adding environmental variables, which can be easily acquired relatively when considering the difficulties of measurement and budget, into the model as independent variables would improve the accuracy and precision of growth models.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.24 no.2
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• pp.208-218
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• 2014

Objectives: The major objective of this study was to develop and validate a tier 1 exposure model utilizing worker exposure monitoring data and characteristics of worker activities routinely performed at construction sites, in order to estimate worker exposures without sampling. Methods: The Registration, Evaluation, Authorization and Restriction of Chemicals(REACH) system of the European Union(EU) allows the usage of exposure models for anticipating chemical exposure of manufacturing workers and consumers. Several exposure models have been developed such as Advanced REACH Tools(ART). The ART model is based on structured subjective assessment model. Using the same framework, a tier 1 exposure model has been developed. Worker activities at construction sites have been analyzed and modifying factors have been assigned for each activity. Korean Occupational Safety and Health Agency(KOSHA) accrued work exposure monitoring data for the last 10 years, which were retrieved and converted into exposure scores. A separate set of sampling data were collected to validate the developed exposure model. These algorithm have been realized on Excel spreadsheet for convenience and easy access. Results: The correlation coefficient of the developed model between exposure scores and monitoring data was 0.36, which is smaller than those of EU models(0.6~0.7). One of the main reasons explaining the discrepancy is poor description on worker activities in KOSHA database. Conclusions: The developed tier 1 exposure model can help industrial hygienists judge whether or not air sampling is required or not.