• Geomechanics and Engineering
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• 제23권6호
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• pp.503-512
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• 2020

Mining activities focus on the production of mineral resources for energy generation and raw material requirements worldwide and it is a known fact that shallow reserves become scarce. For this reason, exploration of new resources proceeds consistently to meet the increasing energy and raw material demand of industrial activities. Rock mechanics has a vital role in underground mining and surface mining. Devices and instruments used in laboratory testing to determine rock mechanics related parameters might have limited sensing capability of the failure behavior. However, methodologies such as, thermal cameras, digital speckle correlation method and acoustic emission might enable to investigate the initial crack formation in detail. Regarding this, in this study, thermographic analysis was performed to analyze the failure behaviors of different types of rock specimens during uniaxial compressive strength experiments. The energy dissipation profiles of different types of rocks were characterized by the temperature difference recorded with an infrared thermal camera during experiments. The temperature increase at the failure moment was detected as 4.45℃ and 9.58℃ for andesite and gneiss-schist specimens, respectively. Higher temperature increase was observed with respect to higher UCS value. Besides, a temperature decreases of about 0.5-0.6℃ was recorded during the experiments of the marble specimens. The temperature change on the specimen is related to release of radiation energy. As a result of the porosity tests, it was observed that increase in the porosity rate from 5.65% to 20.97% can be associated to higher radiation energy released, from 12.68 kJ to 297.18 kJ.

• Geomechanics and Engineering
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• 제37권6호
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• pp.555-563
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• 2024

The reasonable setting of coal pillar width plays a key role in guaranteeing the steadiness of surrounding rock of fully mechanized caving gateroad driving along the next goaf. Based on the engineering background of the Bayangaole mine, the discrete element method was used to simulate the fracture evolution of coal pillars with different pillar widths. The results show that the damage rate of the coal pillar increases with the decrease in the width of the coal pillar. Once the coal pillar width is smaller than 6 m, cracks run through the coal pillar, and the coal pillar is completely damaged. In the middle of the coal pillar, which has a width of 6 m and above, there is a relatively complete area with low damage. The results show that the pillar width of 6 m is the most appropriate. Field tests prove that the reserved width of a 6 m small coal pillar can effectively control the surrounding rock deformation, ensuring the overall steadiness of the gateroad in the thick coal seam. It is hoped that this study will offer some reference for the determination of the reasonable size of the coal pillar.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.143-146
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• 2005

Many data mining techniques have been proved useful in revealing important patterns from large data sets. Especially, data mining techniques play an important role in a customer data analysis in a financial industry and an electronic commerce. Also, there are many data mining related research papers in a semiconductor industry and an automotive industry. In addition, data mining techniques are applied to the bioinformatics area. To satisfy customers' various requirements, each industry should develop new processes with more accurate production criteria. Also, they spend more money to guarantee their products' quality. In this manner, we apply data mining techniques to the production-related data such as a test data, a field claim data, and POP (point of production) data in the automotive parts industry. Data collection and transformation techniques should be applied to enhance the analysis results. Also, we classify various types of manufacturing processes and proposed an analysis scheme according to the type of manufacturing process. As a result, we could find inter- or intra-process relationships and critical features to monitor the current status of the each process. Finally, it helps an industry to raise their profit and reduce their failure cost.

• 대한한의학원전학회지
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• 제31권4호
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• pp.27-46
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• 2018

Objectives : In this paper, we investigated the applicability of text mining to Korean Medical Classics and suggest that researchers of Medical Classics utilize this methodology. Methods : We applied text mining to the Huangdi's internal classic, a seminal text of Korean Medicine, and visualized networks which represent connectivity of terms and documents based on vector similarity. Then we compared this outcome to the prior knowledge generated through conventional qualitative analysis and examined whether our methodology could accurately reflect the keyword of documents, clusters of terms, and relationships between documents. Results : In the term network, we confirmed that Qi played a key role in the term network and that the theory development based on relativity between Yin and Yang was reflected. In the document network, Suwen and Lingshu are quite distinct from each other due to their differences in description form and topic. Also, Suwen showed high similarity between adjacent chapters. Conclusions : This study revealed that text mining method could yield a significant discovery which corresponds to prior knowledge about Huangdi's internal classic. Text mining can be used in a variety of research fields covering medical classics, literatures, and medical records. In addition, visualization tools can also be utilized for educational purposes.

• 스마트미디어저널
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• 제2권2호
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• pp.20-27
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• 2013

The concept of social media is top of the agenda for many business executives and decision makers, as well as consultants try to identify ways where companies can make profitable use of applications such as Netflix, Flixster. The social media is playing an increasingly important role as the information sources for customers making product choices etc. With the flourish of Web 2.0 technology, customer reviews are becoming more and more useful and important information resources for people to save their time and energy on purchasing products that they want. This paper proposes the Bayesian Probabilistic Classification algorithm to mine the social media review, and evaluates it by different splits and cross validation mechanism from the real data set. The explored study experimental results show the robustness and effectiveness of proposed approach for mining the social media review.

• 대한산업공학회지
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• 제42권5호
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• pp.327-336
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• 2016

Prediction of customer failure rates plays an important role for establishing appropriate management policies and improving the profitability for industries. For these reasons, many LCD (Liquid crystal display) manufacturing industries have attempted to construct prediction models for customer failure rates. However, most traditional models are based on the parametric approaches requiring the assumption that the data follow a certain probability distribution. To address the limitation posed by the distributional assumption underpinning traditional models, we propose using parameter-free data mining models for predicting customer failure rates. In addition, we use various information associated with product attributes and field return for more comprehensive analysis. The effectiveness and applicability of the proposed method were demonstrated with a real dataset from one of the leading LCD companies in South Korea.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.3-5
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• 2006

Recent advances in the internet infrastructure have resulted in a large number of huge Web sites and portals worldwide. These Web sites are being visited by various types of users in many different ways. Among all the web page access sequences from different users, some of them occur so frequently that may need an attention from those who are interested. We call them frequent access patterns and access sequences that can be frequent the candidate patterns. Since these candidate patterns play an important role in the incremental Web mining, it is important to efficiently generate, add, delete, and search for them. This thesis presents a novel tree structure that can efficiently store the candidate patterns and a related set of algorithms for generating the tree structure adding new patterns, deleting unnecessary patterns, and searching for the needed ones. The proposed tree structure has a kind of the 3 dimensional link structure and its nodes are layered.

• Computers and Concrete
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• 제22권2호
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• pp.239-248
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• 2018

TBM penetration rate is a function of intact rock properties, rock mass conditions and TBM operational parameters. Machine rate of penetrationcan be predicted by knowledge of the ground conditions and its effects on machine performance. The variation of TBM operational parameters such as penetration rate and thrust plays an important role in its performance. This study presents the results of the analysis on the TBM penetration rates in schistose rock types present along the alignment of Golab tunnel based on the analysis of a TBM performance database established for every stroke through different schistose rock types. The results of the analysis are compared to the results of some empirical and theoretical predictive models such as NTH and QTBM. Additional analysis was performed to find the optimum thrust and revolution per minute values for different schistose rock types.

• 인터넷정보학회논문지
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• 제17권6호
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• pp.53-59
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• 2016

최근 무선 센서 네트워크, 사물 인터넷, 소셜 네트워크 서비스와 같은 다양한 응용 분야에서 대용량 스트림 데이터가 실시간으로 생성되고 있으며, 효율적인 기법을 통해 처리 및 분석하여 유용한 정보를 찾아내고, 이를 의사 결정을 위해 사용할 수 있도록 하는 것은 중요한 이슈 중에 하나이다. 스트림 데이터는 끊임없이 빠른 속도로 생성되므로 최소한의 접근을 통해 처리해야 하며, 신속한 저전력 처리를 필요로 하는 자원이 제한된 환경에서 분석될 수 있도록 적합한 기법이 요구된다. 이러한 문제를 해결하기 위해, 슬라이딩 윈도우 개념이 제안되어 연구되고 있다. 한편, 대용량 데이터로부터 의미 있는 정보를 찾아내기 위한 데이터 마이닝 기법 중에 하나인 패턴 마이닝은 중요 정보를 패턴 형태로 추출한다. 전통적인 빈발 패턴 마이닝은 이진 데이터베이스를 대상으로 하고 모든 아이템을 동일한 중요도로 고려함으로써 데이터 마이닝 분야에서 중요한 역할을 수행해 왔지만, 실제 데이터 특성을 반영하지 못하는 단점을 지닌다. 하이 유틸리티 패턴 마이닝은 비 이진 데이터베이스로부터 상대적인 아이템 중요도를 반영하여 더욱 의미 있는 정보를 찾아내기 위해 제안되었다. 정적 데이터를 대상으로 하는 하이 유틸리티 패턴 마이닝 기법은 그러나 스트림 데이터 처리에 적합하지 못하다. 제한된 환경에서 스트림 데이터의 특성을 반영하고 효율적으로 처리하여 중요한 정보를 찾아내기 위해 슬라이딩 윈도우 기반의 접근법이 제안되었다. 본 논문은 슬라이딩 윈도우 기반 하이 유틸리티 패턴 마이닝 기법들의 성능을 평가하고 분석하여 해당 기법들의 특성 및 발전 방향을 고찰한다.

• 한국통신학회논문지
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• 제39B권6호
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• pp.370-378
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• 2014

잘 알려진 바와 같이 데이터마이닝 (Data Mining)은 대용량의 데이터를 분석하여 필요한 정보를 추출하는데 있어서 매우 중요한 역할을 수행한다. 그중에서 집합에 포함된 원소들의 빈도수 (Frequency)를 알아내는 것은 데이터마이닝에서 기본적으로 지원되어야 하는 필수기능이다. 동시에 사용자가 소유한 다중집합 (혹은 집합) 자체의 공개를 원하지 않는 경우에 대비하여 다중집합의 원소는 공개하지 않고 빈도수만 계산하는 방법이 필요하다. 본 논문에서는 암호학적 도구를 기반으로 사용하여 이러한 조건을 만족하는 기법을 개발하고, 이것의 안전성을 엄밀하게 증명한다. 본 논문에서 제안된 기법은 기존 기법들과 달리 첫째, 시스템 가정이 일반적이고 둘째, 통신/연산 복잡도가 효율적이고 마지막으로 엄밀한 안전성 증명을 제시한다.