• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.86-94
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• 2003

Electronically available biological literature has been accumulated exponentially in the course of time. So, researches on automatically acquiring knowledge from these tremendous data by text mining technology become more and more prosperous. However, most of the previous researches are technology oriented and are not well focused in practical extraction target, hence result in low performance and inconvenience for the bio-researchers to actually use. In this paper, we propose a more biology oriented target domain specific text mining system, that is, POSTECH bio-text mining system (POSBIOTM), for signal transduction pathway extraction, especially for G protein-coupled receptor (GPCR) pathway. To reflect more domain knowledge, we specify the concrete target for pathway extraction and define the minimal pathway domain ontology. Under this conceptual model, POSBIOTM extracts interactions and entities of pathways from the full biological articles using a machine learning oriented extraction method and visualizes the pathways using JDesigner module provided in the system biology workbench (SBW) [14]

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.681-689
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• 2019

Web usage pattern discovery is an advanced means by using web log data, and it's also a specific application of data mining technology in Web log data mining. In education Data Mining (DM) is the application of Data Mining techniques to educational data (such as Web logs of University, e-learning, adaptive hypermedia and intelligent tutoring systems, etc.), and so, its objective is to analyze these types of data in order to resolve educational research issues. In this paper, the Web log data of a university are used as the research object of data mining. With using the database OLAP technology the Web log data are preprocessed into the data format that can be used for data mining, and the processing results are stored into the MSSQL. At the same time the basic data statistics and analysis are completed based on the processed Web log records. In addition, we introduced the Apriori Algorithm of Web usage pattern mining and its implementation process, developed the Apriori Algorithm program in Python development environment, then gave the performance of the Apriori Algorithm and realized the mining of Web user access pattern. The results have important theoretical significance for the application of the patterns in the development of teaching systems. The next research is to explore the improvement of the Apriori Algorithm in the distributed computing environment.

• Journal of Environmental Science International
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• v.12 no.2
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• pp.227-236
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• 2003

Electrokinetic remediation technique offers the opportunity to extract heavy metals from soils with high plasticity. The experiment demonstrated the applicability of electrokinetic remediation on metal-mining deposit and the decision of the enhancement method for four kinds of bench-scale studies. According to the sequential extraction of heavy metals in the "I" mining deposit, Pb and Cu were mostly associated with residual fraction and Zn and Cd were associated with water soluble and residual fraction. Therefore, removable fractions by electrokinetic technology was determined by the sum of the fraction of water soluble and exchangeable, which is Cu : 19.53%, Pb : 1.42%, Cd : 52.82%, Zn : 57.28%, respectively. When considering electrical potential, volume of effluent, soil pH, and eliminated rate of contaminant, results determined by sum of each weight were Citric aic+SDS (13) > 0.1N $HNO_3$ (10) > HAc (8) > DDW (4). Therefore, citric acid and SDS mixed solution was determined the best enhancing agent for the remediation of metal mining deposit.g deposit.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3230-3255
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• 2022

Causality mining in NLP is a significant area of interest, which benefits in many daily life applications, including decision making, business risk management, question answering, future event prediction, scenario generation, and information retrieval. Mining those causalities was a challenging and open problem for the prior non-statistical and statistical techniques using web sources that required hand-crafted linguistics patterns for feature engineering, which were subject to domain knowledge and required much human effort. Those studies overlooked implicit, ambiguous, and heterogeneous causality and focused on explicit causality mining. In contrast to statistical and non-statistical approaches, we present Bidirectional Encoder Representations from Transformers (BERT) integrated with Multi-level Feature Networks (MFN) for causality recognition, called BERT+MFN for causality recognition in noisy and informal web datasets without human-designed features. In our model, MFN consists of a three-column knowledge-oriented network (TC-KN), bi-LSTM, and Relation Network (RN) that mine causality information at the segment level. BERT captures semantic features at the word level. We perform experiments on Alternative Lexicalization (AltLexes) datasets. The experimental outcomes show that our model outperforms baseline causality and text mining techniques.

• Communications for Statistical Applications and Methods
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• v.8 no.2
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• pp.531-541
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• 2001

In this study, we compare the capabilities of the data mining tools of the most updated version objectively and provide the useful information in which enterprises and universities chose them. In particular, we compare the SAS/Enterprise Miner 3.0, SPSS/Clementine 5.2 and IBM/Intelligent Miner 6.1 which are well known and easily gotten.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.1085-1089
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• 2015

Text-mining technique in the past had difficulty in realizing the analysis algorithm due to text complexity and degree of freedom that variables in the text have. Although the algorithm demanded lots of effort to get meaningful result, mechanical text analysis took more time than human text analysis. However, along with the development of hardware and analysis algorithm, big data technology has appeared. Thanks to big data technology, all the previously mentioned problems have been solved while analysis through text-mining is recognized to be valuable as well. However, applying text-mining to Korean text is still at the initial stage due to the linguistic domain characteristics that the Korean language has. If not only the data searching but also the analysis through text-mining is possible, saving the cost of human and material resources required for text analysis will lead efficient resource utilization in numerous public work fields. Thus, in this paper, we compare and evaluate the public document classification by handwork to public document classification where word frequency(TF-IDF) in a text-mining-based text and Cosine similarity between each document have been utilized in big data environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2986-2999
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• 2019

The uncertainties of the uncertain graph make the traditional definition and algorithms on mining dense graph for certain graph not applicable. The subgraph obtained by maximizing expected density from an uncertain graph always has many low edge-probability data, which makes it low reliable and low expected edge density. Based on the concept of ${\beta}$-subgraph, to overcome the low reliability of the densest subgraph, the concept of optimal ${\beta}$-subgraph is proposed. An efficient greedy algorithm is also developed to find the optimal ${\beta}$-subgraph. Simulation experiments of multiple sets of datasets show that the average edge-possibility of optimal ${\beta}$-subgraph is improved by nearly 40%, and the expected edge density reaches 0.9 on average. The parameter ${\beta}$ is scalable and applicable to multiple scenarios.

• Geomechanics and Engineering
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• v.17 no.2
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• pp.157-164
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• 2019

The effect of electrochemical modification of the physical and mechanical properties of sandstone from Paleozoic coal measure strata was investigated by means of liquid nitrogen physical adsorption, X-ray diffraction and uniaxial compressive strength (UCS) tests using purified water, 1 mol/L NaCl, 1 mol/L $CaCl_2$ and 1 mol/L $AlCl_3$ aqueous solution as electrolytes. Electrochemical corrosion of electrodes and wire leads occurred mainly in the anodic zone. After electrochemical modification, pore morphology showed little change in distribution, decrease in total pore specific surface area and volume, and increased average pore diameter. The total pore specific surface area in the anodic zone was greater than in the cathodic zone, but total pore volume was less. Mineralogical composition was unchanged by the modification. Changes in UCS were caused by a number of factors, including corrosion, weakening by aqueous solutions, and electrochemical cementation, and electrochemical cementation stronger than corrosion and weakening by aqueous solutions.

• Geomechanics and Engineering
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• v.29 no.6
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• pp.697-706
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• 2022

In order to explore the stable anchoring conditions of coal side under the mining disturbance of soft section coal pillar in Wangcun Coal Mine of Chenghe Mining Area, the distribution model of the anchoring support pressure at the coal pillar side was established, using the strain-softening characteristics of the coal to study the distribution law of anchoring coal side support pressure. The analytical solution for the reinforcement anchorage stress in the coal pillar side was derived with the inelastic state mechanical model. The results show that the deformation angle of the roadway side and roof increases with the roof subsidence due to the mining influence at the adjacent working face, the plastic deformation zone extends to the depth of the coal side, and the increase of anchorage stress can effectively control the roof subsidence and further deterioration of plastic zone. The roadway height and the peak support pressure have a certain influence on the anchorage stress, the required anchorage stress of the coal side rises with the roadway height and the peak support pressure. The required anchorage stress of the coal pillar side decreases as the cohesion between the coal seam and the roof and floor and the anchor length increases. Then, applied the research result to Wangcun coal mine in Chenghe mining area, the design of anchor cable reinforcement support was proposed for the section of coal pillars side that has been anchored and deformed, which achieved great results and effectively controlled the convergence and deformation of the side, providing a safety guarantee for the roadway excavation and mining.

• Steel and Composite Structures
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• v.51 no.2
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• pp.117-126
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• 2024

There are many challenges in the construction of large-section tunnels, such as extremely soft rock and fractured zones. In order to solve these problems, the confined concrete support technology is proposed to control the surrounding rocks. The large-scale laboratory test is carried out to clarify mechanical behaviours of the combined confined concrete and traditional I-steel arches. The test results show that the bearing capacity of combined confined concrete arch is 3217.5 kN, which is 3.12 times that of the combined I-steel arch. The optimum design method is proposed to select reasonable design parameters for confined concrete arch. The parametric finite element (FE) analysis is carried out to study the effect of the design factors via optimum design method. The steel pipe wall thickness and the longitudinal connection ring spacing have a significant effect on the bearing capacity of the combined confined concrete arch. Based on the above research, the confined concrete support technology is applied on site. The field monitoring results shows that the arch has an excellent control effect on the surrounding rock deformation. The results of this research provide a reference for the support design of surrounding rocks in large-section tunnels.