• Journal of Computing Science and Engineering
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• 제5권2호
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• pp.111-120
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• 2011

Data mining algorithms should exploit new hardware technologies to accelerate computations. Such goal is difficult to achieve in database management system (DBMS) due to its complex internal subsystems and because data mining numeric computations of large data sets are difficult to optimize. This paper explores taking advantage of existing multithreaded capabilities of multicore CPUs as well as caching in RAM memory to efficiently compute summaries of a large data set, a fundamental data mining problem. We introduce parallel algorithms working on multiple threads, which overcome the row aggregation processing bottleneck of accessing secondary storage, while maintaining linear time complexity with respect to data set size. Our proposal is based on a combination of table scans and parallel multithreaded processing among multiple cores in the CPU. We introduce several database-style and hardware-level optimizations: caching row blocks of the input table, managing available RAM memory, interleaving I/O and CPU processing, as well as tuning the number of working threads. We experimentally benchmark our algorithms with large data sets on a DBMS running on a computer with a multicore CPU. We show that our algorithms outperform existing DBMS mechanisms in computing aggregations of multidimensional data summaries, especially as dimensionality grows. Furthermore, we show that local memory allocation (RAM block size) does not have a significant impact when the thread management algorithm distributes the workload among a fixed number of threads. Our proposal is unique in the sense that we do not modify or require access to the DBMS source code, but instead, we extend the DBMS with analytic functionality by developing User-Defined Functions.

• The Journal of Engineering Geology
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• 제31권1호
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• pp.31-42
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• 2021

Database of Cut-slope management system (CSMS) has been constructed based on investigations of all slopes on the roads of the whole country. The investigation data is documented by human, so it is inevitable to avoid human-error such as missing-data and incorrect entering data into computer. The goal of this paper is constructing a prediction model based on several machine-learning algorithms to solve those imperfection problems of the CSMS data. First of all, the character-type data in CSMS data must be transformed to numeric data. After then, two algorithms, i.g., multinomial logistic regression and deep-neural-network (DNN), are performed, and those prediction models from two algorithms are compared. Finally, it is identified that the accuracy of DNN-model is better than logistic model, and the DNN-model will be utilized to improve data-quality.

• Journal of the Korean Data and Information Science Society
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• 제25권5호
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• pp.1039-1055
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• 2014

The distribution of a test statistic under a null hypothesis depends on the unknown distribution of the data and thus is unknown as well. Conditional tests replace the unknown null distribution by the conditional null distribution, that is, the distribution of the test statistic given the observed data. This approach is known as permutation tests and was developed by Fisher (Fisher, 1935). Theoretical framework for permutation tests was given by Strasser and Weber(1999). The coin package developed by Hothon et al. (2006, 2008) implements a unified approach for conditional inference via the generic independence test. Because convenient functions for the most prominent problems are available, users will not have to use the extremely flexible procedure. In this article we briefly review the underlying theory from Strasser and Weber (1999) and explain how to transform the data to perform the generic function independence test. Finally it was illustrated with a few real data sets.

• The Journal of the Korea Contents Association
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• 제17권4호
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• pp.541-549
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• 2017

This research investigates the quantitative screening methods for the Grant Funding system and seeks for the efficient evaluation of a number of proposals. We search foreign cases of Grand Funding, but we found no appropriate model for using in Korea. Thus, we had to develope our own model for better screening. First, we analyse the existing evaluation system and find some problems and challenges. Second, we suggest a quantitative screening system for Grant Funding with a numeric model, and operates a tedious simulation by using the previous data and our suggested model. Third, we test the suggested model and find the optimal model by using simulation method The number of data analysed for simulation is larger than 200 thousands. Last, we suggest some brief policy implications based on the results in the paper.

• Journal of the Korean Institute of Intelligent Systems
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• 제14권5호
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• pp.660-665
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• 2004

In this study, a new architecture and comprehensive design methodology of genetically optimized Multi-layer Fuzzy Neural Networks (gMFNN) are introduced and a series of numeric experiments are carried out. The gMFNN architecture results from a synergistic usage of the hybrid system generated by combining Fuzzy Neural Networks (FNN) with Polynomial Neural Networks (PNN). FNN contributes to the formation of the premise part of the overall network structure of the gMFNN. The consequence part of the gMFNN is designed using PNN. The optimization of the FNN is realized with the aid of a standard back-propagation learning algorithm and genetic optimization. The development of the PNN dwells on the extended Group Method of Data Handling (GMDH) method and Genetic Algorithms (GAs). To evaluate the performance of the gMFNN, the models are experimented with the use of a numerical example.

• Proceedings of the KIEE Conference
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.240-242
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• 2005

It is well known that the PD (Partial Discharge) signals are generated if insulators have some defects such as voids in electrical facility and various PD detection methods are developed for preventing electrical troubles. So, an interest for the PD signals is higher and higher according to the high concern for the defects detection method of the aging electrical facility. When the equipment to detect PD signals installed at site and it works, a lot of noises flow in the equipment from surrounding situation and it will be mixed with original PD waveform. So we can not get the desired PD waveform. Therefore, there are many trial to reject or suppress the noise from the PD signals from long times ago. The greater of them used the hardware such as bridge circuits and frequency filters to suppress the noise. This paper proposed a novel noise rejection method in acquired data from PD detection equipment. The noise has the irregular phase and higher signal level than real PD, and noise decision is performed after inspection of pulse distribution in ${\Phi}$-q-n graph of acquired data from PD detection equipments. By experimental results on high voltage electric equipments, it is shown that proposed method has good performance. It is expected that this noise rejection technology is useful in numeric calculation and trend management of PD level.

• Journal of Environmental Science International
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• 제21권4호
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• pp.471-478
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• 2012

In this study, the flow characteristic analysis at the curved-channel of the actual channel section is compared and reviewed using the 2D RMA-2 model and the 3D FLOW-3D model. the curve section with curve rate 1.044 in the research section is analyzed applying the frequency of he project flood of 100 years. According to the result, the issue for the application of the FLOW-3D Model's three-dimensional numeric analysis result to the actual river is found to be reviewed with caution. Also, application of the 3D model to the wide basin's flood characteristic is determined to be somewhat risky. But, the applicability to the hydraulic property analysis of a partial channel section and the impact analysis and forecast of hydraulic structure is presumed to be high. In addition, if the parameters to reflect the vegetation of basin and the actual channel, more accurate topological measurement data and the topological data with high closeness to the current status are provided, the result with higher reliability is considered to be drawn.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.199-202
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• 2001

An elevator system, which is essential equipment for vertical movement of an object, as a property of building, has been driven by various expenditures and purposes. Since developing electrical control technology, control system are highly developed. The elevator system has expanded widely, but a data accuracy acquisition technique and safety predict technique for securing system safety is still at a basic level. So, objective verification for elevator confidence condition requires an absolute accuracy measurement technique. Therefore, this study is executed in order to acquire a method of depending on sense of a manager with simple numeric measurement data, and to construct a logical, analytical foresight system for more efficient elevator management system. As an artificial intelligence for diagnosis, the fuzzy inference algorithm is used for foreseeing the system in this thesis, because the fuzzy algorithm is the most useful method for resolving subjective ideas and a vague judgment of humans. The fuzzy inference algorithm is developed for each sensor signal(i.e. vibration, velocity, current).

• Journal of Korea Society of Digital Industry and Information Management
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• 제11권1호
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• pp.19-25
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• 2015

In this time, as an industrial society developed to a welfare society, more and more people want their quality of lives upgraded and specially customized service by mass production/mass consumption. And it leads to an increase of requiring service. There're active developments and studies on various IT equipment as the requirement made IT devices used in service. In this paper, we try to design and realize radio paging DID by using smart device to be used as a receiver of a radio pager which is broadly used at face to face service. Firstly, we used MCU to design and implement Wireless Calling Gateway which change radio calling signal of ISM band to smart device. A receiver of wireless caller used original receiver module. Also it used bluetooth module to communicate with smart device. It was possible to have satisfactory communication since radio paging signal converter and smart device were linked in 3M. Secondly, to indicate various paging information delivered from a radio pager, we realized DID application program by using Smart PAD. As a result, we could indicate various information compared to an original receiver which only could indicate letters or numeric data. Secondly, we implemented the DID app for wireless calls that can display a variety of information sent from a wireless pager. Was implemented using the Smart Pad. As a result, it is shown that can display a variety of information than the existing receiver.

• Child Health Nursing Research
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• 제11권4호
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• pp.427-435
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• 2005

Purpose: The purpose of this study was to identify the effects of hand acupuncture therapy on headaches in children. Method: A quasi experimental pre-test and post (1,2,3)-test design was used. Data were collected from March 2 to April 16 2001. Forty children were assigned to an experimental (20) or control group (20). The experimental group received Hand-Acupuncture therapy on the meridian point; A30, A31, A32, A33, E8, I2, M2, M3, M5, B25, B26, B27 for each 3 minutes, while the control group rested on a bed. Data were analyzed using the SAS program with $x^2$-test, t-test, repeated measured ANOVA, and ANCOVA. Result: In the experimental group, descriptive headache intensity (f=64.33, p=0.00), numeric headache intensity (F=74.69, 122.50, 7.52. p=0.00), and medication requirements ($x^2$=19.00, p=0.00) were significantly lower than those of the control group. Conclusion: These findings indicate that hand acupuncture therapy is effective for reduction of headaches. Therefore, hand acupuncture therapy can be considered an independent nursing intervention for reducing headaches in children.