• Steel and Composite Structures
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• v.11 no.3
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• pp.183-205
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• 2011

This paper presents the results of an investigation into the post-buckling behaviour and ultimate strength of imperfect corroded steel plates used in ship and other marine-related structures. A series of elastic-plastic large deflection finite element analyses is performed on randomly corroded steel plates. The effects of general corrosion on both sides of the plates are introduced into the finite element models using a random thickness surface model. The effects on plate compressive strength as a result of parametric variation of the corroded surface geometry are evaluated. A proposal on the effective thickness is concluded in order to estimate the ultimate strength and explore the post-buckling behaviour of randomly corroded steel plates under uniaxial compression.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.2
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• pp.148-154
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• 2016

In recent year, the interests of PQ is increase due to the increasing of non-linear load and distributed power sources in power system. For the parameters detection and feature extraction of PQ, and the PQ improvement method, continuous power signal monitering is needed. In this paper, the power signal compression and reconstruction method is suggested for power signal monitering. The power signal is compressed using DCT that has good compression performance, and the compressed signal is reconstructed through IDCT. And for the higher compression rate, DCT coefficients are arranged by magnitude in compression process, and in recouction process DCT coefficients are rearranged to original frequency position. The synthesized signal according to the IEC standard is used used in compression and reconstruction simulations. The performances of the proposed method are verified by comparing the error between synthesized signal and reconstructed signal.

• Journal of the Korean Geotechnical Society
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• v.19 no.6
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• pp.371-378
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• 2003

The compression index of clay distributed in the west and south coast of the Korean Peninsula had been studied. Compression index was obtained from the conventional consolidation test, and was conducted accordingly to obtain the field virgin compression curve by means of Schmertmann's graphical correction. To examine a correlation closely between physical properties of soils($e_o$, LL, w) and compression index(Cc), linen. and non-linear regression analysis were employed based on the data collected from tests. The conclusions are as follows. The compression index obtained by means of Schmereann's graphical correction is about 1.16 times for the value of original oedometer test curve for U/D samples. Non-liner regression curve was preferable to establish a correlation equation rather than linear regression curve. All derived equations so far achieved have been summarized and given. However, linear equation is better for practical use so that part by part simplified linear equations were also suggested alternatively together with their own non-linear regression curve.

• Journal of Industrial Technology
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• v.25 no.A
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• pp.57-65
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• 2005

In this paper, for the highly plastic marine soft clay distributed in west and southern coast of Korean peninsula of Kwangyang and Busan New Port areas, correlation between compression index and other indices representing geotechnical engineering properties such as liquid limit, void ratio and natural water content were analyzed. Appropriate empirical equations of being able to estimate the compressibility of clays in the specific areas were proposed and compared with other existing empirical ones. For analyses of the data and test results, data for marine clays were used from areas of the South Container Port of the Busan New Port, East Breakwater, Passenger Quay, Jungma Reclamation and Reclamation Containment in the 3rd stage in Kwangyang. In order to find the best regression model by using the commercially available software, MS EXCEL 2000, results obtained from the simple linear regression analysis, using the values of liquid limit, initial void ratio and natural water content as independent variables, were compared with the existing empirical equations. Multiple linear regression was also performed to find the best fit regression curves for compression index and other soil properties by combining those independent variables. On the other hands, another software of SPSS for non-linear regression was used to analyze the correlations between compression index and other soil properties.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.142-147
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• 2018

We present a practical design algorithm for quantizers at nodes in distributed systems in which each local measurement is quantized without communication between nodes and transmitted to a fusion node that conducts estimation of the parameter of interest. The benefits of vector quantization (VQ) motivate us to incorporate the VQ strategy into our design and we propose a low-complexity design technique that seeks to assign vector codewords into sets such that each codeword in the sets should be closest to its associated local codeword. In doing so, we introduce new distance metrics to measure the distance between vector codewords and local ones and construct the sets of vector codewords at each node to minimize the average distance, resulting in an efficient and independent encoding of the vector codewords. Through extensive experiments, we show that the proposed algorithm can maintain comparable performance with a substantially reduced design complexity.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.457-458
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• 2007

This paper propose a method for representing distributed data of sensor networks. The proposed method is based on a general distributed regression framework that models sensor data by fitting a global function to each of the local measurements and explores the possible extensions of distribution regression by using complex signal representations. In order to reduce the amount of processed data and the required communication, the signal model has to be as compact as possible, with the ability to restore the arbitrary measurements. To achieve this requirement, data compression step is included, where the basis function set is changed to an overcomplete set. This have better advantages in case of nonstationary signal modeling than complete base representation.

• Journal of IKEEE
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• v.22 no.3
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• pp.558-564
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• 2018

In distributed estimation where each node can collect only partial information on the parameter of interest without communication between nodes and quantize it before transmission to a fusion node which conducts estimation of the parameter, we consider a novel quantization technique employed at local nodes. It should be noted that the performance can be greatly improved if each node can transmit its measurement to one designated node (namely, head node) which can quantize its estimate using the total rate available in the system. For this case, the best strategy at the head node would be simply to partition the parameter space using the generalized Lloyd algorithm, producing the global codewords, one of which is closest to the estimate is transmitted to a fusion node. In this paper, we propose an iterative design algorithm that seeks to efficiently assign the codewords into each of quantization partitions at nodes so as to achieve the performance close to that of the system with the head node. We show through extensive experiments that the proposed algorithm offers a performance improvement in rate-distortion perspective as compared with previous novel techniques.

• Smart Media Journal
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• v.8 no.4
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• pp.46-52
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• 2019

The size of data generated and collected at industrial sites or in public institutions is growing rapidly. The existing data processing server often handles the increasing data by increasing the performance by scaling up. However, in the big data era, when the speed of data generation is exploding, there is a limit to data processing with a conventional server. To overcome such limitations, a distributed cluster computing system has been introduced that distributes data in a scale-out manner. However, because distributed cluster computing systems distribute data, inefficient use of network bandwidth can degrade the performance of the cluster as a whole. In this paper, we propose a scheme that compresses data when transmitting data in a Hadoop cluster considering network bandwidth. The proposed scheme considers the network bandwidth and the characteristics of the compression algorithm and selects the optimal compression transmission scheme before transmission. Experimental results show that the proposed scheme reduces data transfer time and size.

• Journal of Acupuncture Research
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• v.26 no.1
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• pp.81-90
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• 2009

Objectives : This Study was to investigate the tendency of inpatient with Thoracolumbar Compression Fracture. Also we investigated effectiveness of Pharmacopuncture and Warming Acupuncture on Thoracolumbar Compression Fracture. Methods : We investigated 48 cases of patients with thoracolumbar compression fracture. We distributed inpatint with age, sex, number of injured vertebra, level of injured vertebra, admission duration, grade of clinical symptom, result of treatment and applied treatments. And we calculated statistically signification with this data. Results : 1. Female is prominent in distribution of sex, the average age bracket is 70's, and the largest group was accidental fall in the distribution of causes. 2. In regard to level of injury, T12 was found to be most prominent, followed in turn by L2, L1, T12. In regard to grade of clinical symptoms, Grade III was most Prominent, followed in turn by Grade IV, Grade II. In regard to grade of result of treatment, Good was most prominent. 3. There was not statistically significantly correlation about admission duration and result of treatment with number of injured vertebra, grade of clinical symptom, applied treatments. Conclusions : Most inpatients with thoracolumbar compression fracture was cured by oriental medicine treatment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1490-1501
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• 2016

In this paper, we propose an image-based indoor localization system using parallel distributed computing. In order to reduce computation time for indoor localization, an scale invariant feature transform (SIFT) algorithm is performed in parallel by using Apache Spark. Toward this goal, we propose a novel image processing interface of Apache Spark. The experimental results show that the speed of the proposed system is about 3.6 times better than that of the conventional system.