• Bulletin of the Korean Mathematical Society
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• v.60 no.6
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• pp.1439-1451
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• 2023

This paper provides a constructive proof of the weak factorizations of the classical Hardy space H¹(ℝⁿ) in terms of multilinear fractional integral operator on the variable Lebesgue spaces, which the result is new even in the linear case. As a direct application, we obtain a new proof of the characterization of BMO(ℝⁿ) via the boundedness of commutators of the multilinear fractional integral operator on the variable Lebesgue spaces.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.5
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• pp.1-11
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• 2015

This paper is focused on how the trajectory of launch vehicle could be optimally estimated by the quadratic regression of trajectory data mining for the operation of telemetry ground system in NARO space center during real-time. To receive the telemetry data, the telemetry ground system has to track the space launch vehicle without tracking loss, and it is possible by the well-designed algorithm to estimate a flight position in real-time. For this reason, the quadratic regression model instead of interpolation was considered to estimate the exact position data of launch vehicle and the improvement of antenna performance. For analysis, the real trajectory data which had been logged during NARO 1st launch mission were used, the estimation result of launcher current position was analyzed by the mathematical modeling. In conclusion, the algorithm using quadratic regression based on trajectory data mining showed the better performance than previous interpolation algorithm to estimate the next flight position and the antenna driving performance.

• Journal of Computing Science and Engineering
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• v.1 no.2
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• pp.177-194
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• 2007

Index selection is one of the most important decisions to take in the physical design of relational data warehouses. Indices reduce significantly the cost of processing complex OLAP queries, but require storage cost and induce maintenance overhead. Two main types of indices are available: mono-attribute indices (e.g., B-tree, bitmap, hash, etc.) and multi-attribute indices (join indices, bitmap join indices). To optimize star join queries characterized by joins between a large fact table and multiple dimension tables and selections on dimension tables, bitmap join indices are well adapted. They require less storage cost due to their binary representation. However, selecting these indices is a difficult task due to the exponential number of candidate attributes to be indexed. Most of approaches for index selection follow two main steps: (1) pruning the search space (i.e., reducing the number of candidate attributes) and (2) selecting indices using the pruned search space. In this paper, we first propose a data mining driven approach to prune the search space of bitmap join index selection problem. As opposed to an existing our technique that only uses frequency of attributes in queries as a pruning metric, our technique uses not only frequencies, but also other parameters such as the size of dimension tables involved in the indexing process, size of each dimension tuple, and page size on disk. We then define a greedy algorithm to select bitmap join indices that minimize processing cost and verify storage constraint. Finally, in order to evaluate the efficiency of our approach, we compare it with some existing techniques.

• Computers and Concrete
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• v.31 no.3
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• pp.207-221
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• 2023

In this investigation, the interaction between opening space and neighboring joint has been examined by experimental test and Particle flow code in two dimension (PFC2D) simulation. Since, firs of all PFC was calibrated using Brazilian experimental test and uniaxial compression test. Secondly, diverse configurations of opening and neighboring joint were provided and tested by uniaxial test. 12 rectangular sample with dimension of 10 cm*10 cm was prepared from gypsum mixture. One quarter of tunnel and one and or two joint were drilled into the sample. Tunnel diameter was 5.5 cm. The angularities of joint in physical test were 0°, 45° and 90°. The angularities of joint in numerical simulation were 0°, 30°, 60°, -30°, -45°, -60° and its length were 2cm and 4cm. Loading rate was 0.016 m/s. Tensile strength of material was 4.5 MPa. Results shows that dominant type of crack which took place in the model was tensile cracks and or several shear bands develop within the model. The Final stress is minimum in the cases where oriented angle is negative. The failure stress decrease by decreasing the joint angle from 30° to 60°. In addition, the failure stress decrease by incrementing the joint angle from -30° to -60°. The failure stress was incremented by decreasing the number of notches. The failure stress was incremented by decreasing the joint length. The failure stress was incremented by decreasing the number of notches. Comparing experimental results and numerical one, showed that the failure stress is approximately identical in both conditions.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.164-173
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• 2005

Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. The decision tree approach is most useful in classification problems and to divide the search space into rectangular regions. Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud detection, data reduction and variable screening, category merging, etc. We analyze waste database united with local information using decision tree techniques for environmental information. We can use these decision tree outputs for environmental preservation and improvement.

• Tunnel and Underground Space
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• v.4 no.2
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• pp.170-185
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• 1994

Surface subsidence is one of the problems caused by mined out caverns. Depending on the geologic conditions and mining methods, subsidence can occur in various forms. This report describes the ground stability assessment for the mining induced subsidence area where unfilled caverns still exist abandoned. Geologic features which could affect the stability of the ground were investigated and all the possible geophysical methods were employed to obtain data that could explain the state of the ground in question. Basic rock tests were conducted from the drill cores and rock mass classification was performed by core logging and borehole camera investigation. Numerical analyses were carried out to predict the ground stability using data obtained by various investigations. The result could have been more reliable if in-situ stress were measure and reflected in the numerical analysis.

• Tunnel and Underground Space
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• v.32 no.1
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• pp.78-92
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• 2022

In this study, we proposed a diagnostics and assessment model for mining sites that can evaluate the smart mining technology level in a systematic and structured way. For this, the maturity of the smart mining was defined, and detailed assessment items of the diagnostics and assessment model for smart mining were derived by considering the smart factory diagnostics and assessment model (KS X 9001-3) used in the manufacturing industry. While maintaining the existing system, the existing 46 detailed assessment items were modified to be suitable for mining. As a result, a total of 29 detailed assessment items were derived in the areas of promotion strategy, process, information system and automation, and performance. Based on this, a questionnaire was designed to diagnose the level of smart mining technology, and assessment was performed by applying it to domestic iron mines. The level of smart mining technology in the study area was found to be level 2, and it could be inferred that it was about 40% lower than the average smart level of the general manufacturing industry. In addition, by using the developed model, it was possible to recognize the weak points of the mine at each stage of the introduction, operation, and advancement of smart mining, and to suggest investment and improvement directions.

• Journal of Korean Tunnelling and Underground Space Association
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• v.15 no.6
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• pp.613-623
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• 2013

As Limestone mines have been operated with various environmental, societal and managemental problems depending on their characteristics and developing methods, many great efforts have been applied to solve these problems. Installing the mining facilities underground is one of the successful efforts to keep the sustainable limestone mine development. This effort could reduce these problems. However, unfortunately it made an side effect of constructing a large underground space in mining site. Moreover, this space caused a necessity of various disaster managements for the safety of workers and facilities. This study introduces the priority list of a limestone mining process if there are disasters in underground mining site. This result is coming from the risk assessment and business impact analysis on survey data which were obtained from the miners of that particular limestone mine. According to the result, the highest risk is 'disregard of safety guidelines in crushing & classifier process'. The result also shows the highest priority business, above all things, is 'a pit linked work of in & out process'.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.51-58
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• 2016

The unprecedented power of cloud computing (CC) that enables free sharing of confidential data records for further analysis and mining has prompted various security threats. Thus, supreme cyberspace security and mitigation against adversaries attack during data mining became inevitable. So, privacy preserving data mining is emerged as a precise and efficient solution, where various algorithms are developed to anonymize the data to be mined. Despite the wide use of generalized K-anonymizing approach its protection and truthfulness potency remains limited to tiny output space with unacceptable utility loss. By combining L-diversity and (${\alpha}$,k)-anonymity, we proposed a hybrid K-anonymity data relocation algorithm to surmount such limitation. The data relocation being a tradeoff between trustfulness and utility acted as a control input parameter. The performance of each K-anonymity's iteration is measured for data relocation. Data rows are changed into small groups of indistinguishable tuples to create anonymizations of finer granularity with assured privacy standard. Experimental results demonstrated considerable utility enhancement for relatively small number of group relocations.

• Journal of Power Electronics
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• v.14 no.2
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• pp.315-323
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• 2014

An optimized space vector pulse width modulation (SVPWM) method with common mode voltage elimination and neutral point potential balancing is proposed for an open-end winding induction motor. The motor is fed from both of the ends with two neutral point clamped (NPC) three-level inverters. In order to eliminate the common mode voltage of the motor ends and balance the neutral point potential of the DC link, only zero common mode voltage vectors are used and a balancing control factor is gained from calculation in the strategy. In order to improve the harmonic characteristics of the output voltages and currents, the balancing control factor is regulated properly and the theoretical analysis is provided. Simulation and experimental results show that by adopting the proposed method, the common mode voltage can be completely eliminated, the neutral point potential can be accurately balanced and the harmonic performance for the output voltages and currents can be effectively improved.