• Journal of the Korean Society for information Management
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• v.36 no.1
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• pp.191-213
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• 2019

The process of obtaining scientific knowledge is conducted through research. Researchers deal with the uncertainty of science and establish certainty of scientific knowledge. In other words, in order to obtain scientific knowledge, uncertainty is an essential step that must be performed. The existing studies were predominantly performed through a hedging study of linguistic approaches and constructed corpus with uncertainty word manually in computational linguistics. They have only been able to identify characteristics of uncertainty in a particular research field based on the simple frequency. Therefore, in this study, we examine pattern of scientific knowledge based on uncertainty word according to the passage of time in biomedical literature where biomedical claims in sentences play an important role. For this purpose, biomedical propositions are analyzed based on semantic predications provided by UMLS and DMR topic modeling which is useful method to identify patterns in disciplines is applied to understand the trend of entity based topic with uncertainty. As time goes by, the development of research has been confirmed that uncertainty in scientific knowledge is moving toward a decreasing pattern.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.2
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• pp.417-424
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• 2019

This paper presents the design of a JPEG-LS codec for lossless image compression from AR/VR device. The proposed JPEG-LS(: LosSless) codec is mainly composed of a context modeling block, a context update block, a pixel prediction block, a prediction error coding block, a data packetizer block, and a memory block. All operations are organized in a fully pipelined architecture for real time image processing and the LOCO-I compression algorithm using improved 2D approach to compliant with the SBT coding. Compared with a similar study in JPEG-LS, the Block-RAM size of proposed STB-FLC architecture is reduced to 1/3 compact and the parallel design of the predication block could improved the processing speed.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.4
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• pp.114-125
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• 1994

Fatigue behavior and life prediction method were presented for themal-mechanical and isothermal low cycle fatigue of 12 Cr forged steel used for high temperature applications. In-phase and out-of-phase thermal-mechanical fatigue test from 350 .deg. C to 600 .deg. C and isothermal low cycle fatigue test at 600 .deg. C, 475 .deg. C, 350 .deg. C were conducted using smooth cylindrical hollow specimen under strain-control with total strain ranges from 0.006 to 0.015. The phase difference between temperature and strain in thermal-mechanical fatigue resulted in significantly shorter fatigue life for out-of-phase than for in-phase. Thermal-mechanical fatigue life predication was made by partitioning the strain ranges of the hysteresis loops and the results of isothermal low cycle fatigue tests which were performed under the combination of slow and fast strain rates. Predicted fatigue lives for out-of-phase using the strain range partitioning method showed an excellent agreement with the actual out-of-phase thermal-mechanical fatigue lives within a factor of 1.5. Conventional strain range partitioning method exhibited a poor accuracy in the prediction of in-phase range partitioning method in a conservative way. By the way life prediction of thermal-mechanical fatigue by Taira's equivalent temperature method and spanning fartor method showed good agreement within out-of-phase thermal-mechanical fatigue.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.11 no.3
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• pp.1-15
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• 2016

This study has analyzed predication capabilities leveraging multi-variate model, logistic regression model, and artificial neural network model based on financial information of medium-small sized companies list in KOSDAQ. 83 delisted companies from 2009 to 2012 and 83 normal companies, i.e. 166 firms in total were sampled for the analysis. Modelling with training data was mobilized for 100 companies inlcuding 50 delisted ones and 50 normal ones at random out of the 166 companies. The rest of samples, 66 companies, were used to verify accuracies of the models. Each model was designed by carrying out T-test with 79 financial ratios for the last 5 years and identifying 9 significant variables. T-test has shown that financial profitability variables were major variables to predict a financial risk at an early stage, and financial stability variables and financial cashflow variables were identified as additional significant variables at a later stage of insolvency. When predication capabilities of the models were compared, for training data, a logistic regression model exhibited the highest accuracy while for test data, the artificial neural networks model provided the most accurate results. There are differences between the previous researches and this study as follows. Firstly, this study considered a time-series aspect in light of the fact that failure proceeds gradually. Secondly, while previous studies constructed a multivariate discriminant model ignoring normality, this study has reviewed the regularity of the independent variables, and performed comparisons with the other models. Policy implications of this study is that the reliability for the disclosure documents is important because the simptoms of firm's fail woule be shown on financial statements according to this paper. Therefore institutional arragements for restraing moral laxity from accounting firms or its workers should be strengthened.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.1
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• pp.77-85
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• 2000

To investigate the practical assessing method of pork quality, 302 carcasses were selected randomly to represent commercial conditions and were probed at 24 hr postmortem (PM) by Danish Meat Quality Marbling (MQM), Hennessy Grading Probe (HGP), Sensoptic Resistance Probe (SRP) and NWK pH-K21 meter (NpH). Also, filter paper wetness (FPW), lightness (L*), ultimate pH (pHu), subjective color (SC), firmness/wetness (SF) and marbling scores (SM) were recorded. Each carcass was categorized as either PSE (pale, soft and exudative), RSE (Reddish-pink, soft and exudative), RFN (reddish-pink, firm and non-exudative) or DFD (dark, firm and dry). When discriminant analysis was used to sort carcasses into four quality groups the highest proportion of correct classes was 65% by HGP, 60% by MQM, 52% by NpH and 32% by SRP. When independent variables were combined to sort carcasses into groups the success was only 67%. When RSE and RFN groups were merged so that there were only three groups (PSE, RSE+RFN, DFD) differentiating by color MQM was able to sort the same set of data into the new set of three groups with 80% accuracy. The proportions of correct classifications for HGP, NpH and SRP were 75%, 61% and 35% respectively. There was a decline in predication accuracy when only two groups, exudative (PSE and RES) and non exudative (RFN and DFD) were sorted. However, when two groups designated PSE and non-PSE (RSE, RFN and DFD) were sorted then the proportion of correct classification by MQM, HGP, SRP and NpH were 87%, 81%, 71% and 66% respectively. Combinations of variables only increased the prediction accuracy by 1 or 2% over prediction by MQM alone. When the data was sorted into three marbling groups based on SM this was not well predicted by any of the probe measurements. The best prediction accuracy was 72% by a combination of MQM and NpH.

• Journal of the Korea Concrete Institute
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• v.15 no.1
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• pp.87-94
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• 2003

Construction plan and strength control have limitations in construction production field because it is difficult to predict the form removal strength and development of specified concrete strength. However, we can have reasonable construction plan and strength control if prediction of concrete strength is available. In this study, firstly, the newly proposed strength prediction model with maturity method was compared with the logistic model to test the adaptability. Secondly, the determination of time of form removal was verified through the new strength prediction model. As the results, it is found that investigation of the activation energy that are used to calculate equivalent age is necessary, and new strength prediction model was proved to be more accurate in the strength prediction than logistic model in the early age. Moreover, the use of new model was more reasonable because it has low SSE and high decisive factor. If we adopt new strength prediction model at construction field, we can expect the reduced period of work through the reduced time of form removal.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.5
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• pp.1460-1466
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• 2008

The purpose of this study is to verify how the accounting information of a bankrupt firm which is defined as a dishonor, an impaired total capital, a poor financial performance of a business, a rejection of auditor's opinion and an incongruity of auditor's opinion differs from that of a healthy firm on the basis of the index of financial affairs if the accounting information released by KOSDAQ is valuable. The sampling firms consists of 45 KOSDAQ firms that went bankrupt from 2000 to 2007 and 45 healthy firms which are selected in accordance with the sizes of assets. It has also selected the 30 sampling firms for the confirmation of the model in the same way. According to the result of the in-depth analysis, the variables related to security among the 17 indexes of financial affairs that have been used in this study for 5 years show a noticeable difference between a bankrupt firm and a healthy one. The accuracy of failed firms using this model for confirmation demonstrates 76.7% in 5 years before the bankruptcy, 76.7% in 4 years before that, 65.0% in 3 years before it, 76.7% in 2 years, 88.3% in 1 year. This data shows that the process from a healthy firm to a bankrupt one has progressed gradually and confirms the value of the index of financial affairs, exhibiting the accuracy with 83.8% of a presuming sample and 76.7% of a confirming sample for 5 years.

• Spatial Information Research
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• v.22 no.3
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• pp.79-87
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• 2014

In order to foster rapid disaster response and public life protection, National Emergency Management Agency has been trying to spread 'Emergency Rescue Standard System' on a national scale since 2006. The agency has also intensified management of firefighter's safety on disaster site by implementing danger predication training, specialized training and education and safety procedure check as a part of safety management officer duties. Nevertheless, there are limitations for effective fire fighting steps, such as damage spreading and life damage due to unawareness of illegal converted structure, structure transformation by high temperature and nearby hazardous material storage as well as extemporary situation handling endangered firefighter's life. In order to eliminate these limitations there is a need for an effort and technology application to minimize human errors such as inaccurate situational awareness, wrong decision built on experience and judgment of field commander and firefighters. The purpose of this study is to propose a new disaster response model which is applied with geospatial information. we executed spatial contextual awareness map analysis using fire-fighting vulnerable zone model to propose the new disaster response model and also examined a case study for Dalseo-gu in Daegu Metropolitan City. Finally, we also suggested operational concept of new proposed model on a national scale.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.545-550
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• 2019

The frequency of natural disasters and the scale of damage are increasing due to the abnormal weather phenomenon occurring all over the world. As a result, as the hydrological aspect of the urban watershed changes, the increase in impervious area leads to serious domestic flood damage due to increased rainfall. In order to minimize the damage of life and property, domestic flooding prediction system is needed. In this study, we developed a flood nomogram capable of predicting flooding only by rainfall intensity and duration. This study suggests a method to set the internal water immersion alarm criterion by analyzing the characteristics of the flooding damage in the flooded area in the metropolitan area where flooding is highly possible and the risk of flooding is high. In addition, based on the manhole and the pipe, the water level was set as follows under the four conditions. 1) When manhole overflows, 2) when manhole is full, 3) when 70% of the pipe is reached, and 4) when 60% of the pipe is reached. Therefore, it can be used as a criterion and a predictive measure to cope with the pre-preparation before the flooding starts, through the rainfall that causes the flooding and the flooding damage.

• Animal Bioscience
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• v.35 no.11
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• pp.1760-1770
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• 2022

Objective: It is crucial to accurately determine the net energy (NE) values of feed ingredients because the NE system is expected to be applied to the formulation of broilers feed. The NE values of 5 wheat and 5 wheat brans were determined in 12-to 14-day old Arbor Acres (AA) broilers with substitution method and indirect calorimetry method. Methods: A total of 12 diets, including 2 reference diets (REF) and 10 test diets (5 wheat diets and 5 wheat bran diets) containing 30% of test ingredients, were randomly fed to 864 male AA birds with 6 replicates of 12 birds per treatment. These birds were used to determine metabolizable energy (ME) (8 birds per replicate) in the chicken house and NE (4 birds per replicate) in the chamber respectively at the same time. After a 4-d dietary and environment adaptation period, growth performance, energy values, energy balance and energy utilization were measured during the following 3 d. Multiple linear regression analyses were further performed to generate prediction equations for NE values based on the chemical components and ME values. The NE prediction equation were also validated on another wheat diet and another wheat bran diet with high correlation (r = 0.98, r = 0.75). Results: The NE values of 5 wheat and 5 wheat bran samples are 9.34, 10.02, 10.27, 11.33, and 10.49 MJ/kg, and 5.37, 5.17, 4.87, 5.06, and 4.88 MJ/kg DM, respectively. The equation with the best fit were NE = 1.968AME-0.411×ADF-14.227 (for wheat) and NE = -0.382×CF-0.362×CP-0.244×ADF+20.870 (for wheat bran). Conclusion: The mean NE values of wheat and wheat bran are 10.29 and 5.07 MJ/kg DM in AA broilers. The NE values of ingredients could be predicted by their chemical composition and energy value with good fitness.