• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.189-193
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• 2013

Many epidemiological studies in Asian populations have investigated associations between the Arg399Gln gene polymorphism of X-ray repair cross complementing gene 1 (XRCC1) and risk of cervical carcinoma, but no conclusions have been available because of controversial results. Therefore a meta-analysis was conducted for clarification. Relevant studies were identified by searching the Pubmed, Embase, the Web of Science, Cochrane Collaboration's database, Chinese National Knowledge Infrastructure (CNKI), Wanfang database and China Biological Medicinse (CBM) until September, 2012. A total of eight studies were included in the present meta-analysis, which described 1,759 cervical carcinoma cases and 2,497 controls. Odds ratios (ORs) and corresponding 95% confidence intervals (95%CIs) as effect size were calculated by fixed-effect or random-effect models. The overall results indicated that the XRCC1-399G/A polymorphism was marginally associated with cervical carcinoma in Asians: OR (95%CI): 1.16 (1.07, 1.26) in the G/A vs G/G inheritance model, 1.24 (0.87, 1.76)in A/A vs G/G inheritance model, 1.13 (1.01, 1.27) in the dominant inheritance model and 1.18 (0.94, 1.47) in the recessive inheritance model. Subgroup analyses on sample size showed no significant correlation in the small-sample size group but the large-sample size group was consistent with the outcomes of overall meta-analysis. In the subgroup analysis by regions, we only found significant association under the G/A vs G/G inheritance model in the Chinese population. For the non-Chinese populations, no correlation was detected in any genetic inheritance model. In the Asian populations, XRCC1-399G/A gene polymorphism was implied to be associated with cervical carcinoma.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.278-284
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• 2016

Software reliability in the software development process is an important issue. In infinite failure NHPP software reliability models, the fault occurrence rates may have constant, monotonic increasing or monotonic decreasing pattern. In this paper, infinite failures NHPP models that the situation was reflected for the fault occurs in the repair time, were presented about comparing property. Commonly, the software model of the infinite failures using the linear hazard rate distribution software reliability based on intercept parameter was used in business economics and actuarial modeling, was presented for comparison problem. The result is that a relatively large intercept parameter was appeared effectively form. The parameters estimation using maximum likelihood estimation was conducted and model selection was performed using the mean square error and the coefficient of determination. The linear hazard rate distribution model is also efficient in terms of reliability because it (the coefficient of determination is 90% or more) in the field of the conventional model can be used as an alternative model could be confirmed. From this paper, the software developers have to consider intercept parameter of life distribution by prior knowledge of the software to identify failure modes which can be able to help.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.11
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• pp.481-492
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• 2023

This study explores how to build a Korean dataset to extract information from text using generative large language models. In modern society, mixed information circulates rapidly, and effectively categorizing and extracting it is crucial to the decision-making process. However, there is still a lack of Korean datasets for training. To overcome this, this study attempts to extract information using text-based zero-shot learning using a generative large language model to build a purposeful Korean dataset. In this study, the language model is instructed to output the desired result through prompt engineering in the form of "system"-"instruction"-"source input"-"output format", and the dataset is built by utilizing the in-context learning characteristics of the language model through input sentences. We validate our approach by comparing the generated dataset with the existing benchmark dataset, and achieve 25.47% higher performance compared to the KLUE-RoBERTa-large model for the relation information extraction task. The results of this study are expected to contribute to AI research by showing the feasibility of extracting knowledge elements from Korean text. Furthermore, this methodology can be utilized for various fields and purposes, and has potential for building various Korean datasets.

• Korean Journal of Construction Engineering and Management
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• v.11 no.4
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• pp.22-31
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• 2010

Because the estimated cost at early stage has great influence on decisions of project owner, the importance of early cost estimation is increasing. However, it depends on experience and knowledge of the estimator mainly due to shortage of information. Those tendency developed into case-based reasoning(CBR) method which solves new problems by adapting previous solution to similar past problems. The performance of CBR model is affected by attribute weight, so that its accurate determination is necessary. Previous research utilizes mathematical method or subjective judgement of estimator. In order to improve the problem of previous research, this suggests CBR schematic cost estimation method using genetic algorithm to determine attribute weight. The cost model employs nearest neighbor retrieval for selecting past case. And it estimates the cost of new cases based on cost information of extracted cases. As the result of validation for 17 testing cases, 3.57% of error rate is calculated. This rate is superior to accuracy rate proposed by AACE and the method to determine attribute weight using multiple regression analysis and feature counting. The CBR cost estimation method improve the accuracy by introducing genetic algorithm for attribute weight. Moreover, this makes user understand the problem-solving process easier than other artificial intelligence method, and find solution within short time through case retrieval algorithm.

• Korean Journal of Comparative Education
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• v.24 no.5
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• pp.53-70
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• 2014

This study was performed in order to suggest the future model of Asian universities that could be used in the planning of the global competitive strategy. Futurologists forecasted the future of higher education using Harman Fan Scenario as like this. First, most current universities will be 'the satellite university' until 2015. Second, they also will replace 'the bookless university' until 2020. Third, they will be 'no calendar university' until 2025. And then they may be 'all have access university' until 2030. After 2030, futurologists prospected that almost universities based on off-line campus will be disappeared into the history. The analysis method of Harman fan scenario and applied scenarios were also used to "A study on the future scenario of Korean university". The predictive model and the alternative models were explored in a view point of students, enterprise, and government. Individuality with educational excellence are standardized for learner, profit and effectiveness are applied for enterpriser, and equality with welfare are adapted for national leader. Asian universities need to focus on bringing up the practical ability based on conscious and emotional education instead of knowledge based on memory. Also they need to enforce the specialized education that can create new jobs through convergence of interdisciplinary. Especially, Asian nations need to explore, to find the strengthen area of their universities compared with USA. And these area should be specialized. The convergency strategy between oriental medicine and informatics is a meaningful sample. Based on this point, a predicted with 3 alternative scenarios in a view point of equality were suggested for the future of Asian universities.

• Journal of Korean Elementary Science Education
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• v.40 no.2
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• pp.127-144
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• 2021

The purpose of this research was to conduct grounded-theory-based explorations on the types of motivation that make pre-service elementary school teachers learn science and on their type-based science-learning processes. One hundred thirty-two pre-service elementary school teachers' motivation types were analyzed, and amongst them, 12 were selected as the subjects to observe their science-learning processes to which grounded theory applied. As a result of analyzing their science-learning motivation types, it was found that the majority belonged to the type "accurators", followed in descending order by the types "directors", "explorers", and "coordinators". Coding various phenomena that appeared in their science-learning processes made it possible to derive 30 categories from them according to the grounded-theory paradigm model elements. Based on such categories derived, analysis could be made on their science-learning process flows by motivation types, according to the grounded-theory paradigm model. For example, the "accurators" were attending science lectures or reading science books to learn science knowledge and how to teach it, from a sense of obligation they took for granted as elementary school teachers. Although their experiences of science-learning processes could not be from pure intentions, due to the teacher certification examination, curriculum, or other environmental factors, they were found to have new perspectives on science with their individual efforts and participations.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.9
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• pp.3973-3980
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• 2014

Prostate adenocarcinoma is one of the leading causes of cancer related mortality in men but still limited knowledge is available about its associated functional SNPs including rs1042522 (Pro72Arg). The present study was undertaken to explore the association of this SNP with susceptibility to prostate adenocarcinoma along with its structural and functional impacts in the Pakistani population in a case-control study. Three-dimensional structure of human TP53 with Pro72Arg polymorphism was predicted through homology modeling, refined and validated for detailed structure-based assessment. We also carried out a HuGE review of the previous available data for this polymorphism. Different genetic models were used to evaluate the genotypes association with the increased risk of PCa (Allelic contrast: OR=0.0.34, 95%CI 0.24-0.50, p=0.000; GG vs CC: OR=0.17, 95%CI 0.08-0.38, p=0.000; Homozygous: OR=0.08, 95%CI 0.04-0.15, p=0.000; GC vs CC: OR=2.14, 95%CI 1.01-4.51, p=0.046; Recessive model: OR=0.10, 95%CI 0.05-0.18, p=0.000; Log Additive: OR=3.54, 95%CI 2.13-5.89, p=0.000) except the Dominant model (OR=0.77, 95%CI 0.39-1.52, p=0.46). Structure and functional analysis revealed that the SNP in the proline rich domain is responsible for interaction with HRMT1L2 and WWOX. In conclusion, it was observed that the Arg coding G allele is highly associated with increased risk of prostate adenocarcinoma in the Pakistani population (p=0.000).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.483-503
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• 2014

In this paper, human action recognition using pyramid histograms of oriented gradients and collaborative multi-task learning is proposed. First, we accumulate global activities and construct motion history image (MHI) for both RGB and depth channels respectively to encode the dynamics of one action in different modalities, and then different action descriptors are extracted from depth and RGB MHI to represent global textual and structural characteristics of these actions. Specially, average value in hierarchical block, GIST and pyramid histograms of oriented gradients descriptors are employed to represent human motion. To demonstrate the superiority of the proposed method, we evaluate them by KNN, SVM with linear and RBF kernels, SRC and CRC models on DHA dataset, the well-known dataset for human action recognition. Large scale experimental results show our descriptors are robust, stable and efficient, and outperform the state-of-the-art methods. In addition, we investigate the performance of our descriptors further by combining these descriptors on DHA dataset, and observe that the performances of combined descriptors are much better than just using only sole descriptor. With multimodal features, we also propose a collaborative multi-task learning method for model learning and inference based on transfer learning theory. The main contributions lie in four aspects: 1) the proposed encoding the scheme can filter the stationary part of human body and reduce noise interference; 2) different kind of features and models are assessed, and the neighbor gradients information and pyramid layers are very helpful for representing these actions; 3) The proposed model can fuse the features from different modalities regardless of the sensor types, the ranges of the value, and the dimensions of different features; 4) The latent common knowledge among different modalities can be discovered by transfer learning to boost the performance.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.55-62
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• 2005

In this paper, a CAB/CAE integrated optimal design system is developed, in which design and analysis process is automated using CAD/CAE softwares, for a complicated model for which parametric modeling provided by CAD software is not possible. CAD modeling process is automated by using UG/OPEN API function and UG/Knowledge Fusion provided by Unigraphics. The generated model is transferred to the analysis code ANSYS in parasolid format. Visual DOC software is used for optimization. The system is developed for PLS(Plasma Lighting System), which is a next generation illumination system that is used to illuminate stadium or outdoor advertizing panel. The PLS system consists of more then 20 components, which requires a lot of human efforts in modeling and analysis. The analysis for PLS includes static load, wind load and impact load analysis. As a result of analysis, it is found that the most critical component is a tilt assembly, which links lower & upper body assembly. For more reliable analysis, experiment is conducted using MTS and compared with the Finite element analysis result. The objective in the optimization is to minimize the material volume under allowable stresses. The design variables are three parameters in the tilt assembly that are chosen to be the most sensitive in stress values of twelve parameters. Gradient based method and RSM(Response Surface Method) are used for the algorithm and the results are compared. As a result of optimization, the maximum stress is reduced by 57%.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.2
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• pp.168-174
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• 2008

Diagnosis on setteability based on human operator's experimental knowledge, which could be established by long term operation, is a limit factor to construction of automation control system in wastewater treatment plant. On-line SVI(Sludge Volume Index) analyzer was developed which can measure SV30 automatically by image capture and image analysis method. In this paper, information got by settling process was studied using On-line SVI analyzer for better operation & management of WWTPs. First, SV30 detection algorithm was developed using image capture and image analysis for settling test and it showed that automatic detection is feasible even if deflocculation and bulking was occurred. Second, turbidity assessment model was developed using image analysis.