• Journal of the Korean Society of Industry Convergence
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• v.23 no.4_2
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• pp.617-626
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• 2020

The drilling mud is essentially used in oil and gas development. There are several roles of using the drilling mud, such as cleaning the bottomhole, cooling and lubricating the drill bit and string, transporting the cuttings to the surface, keeping and adjusting the wellbore pressure, and preventing the collapse of the wellbore. The fragments from rocks and micro-sized bubbles generated by the high pressure are mixed in the drilling mud. The systems to separate those mixtures and to keep the uniformly maintained quality of drilling mud are required. In this study, the simulation is conducted to verify the performance of the mud tank's agitation capacity. The primary role of the mud tank is the mixing of mud at the surface with controlling the mud condition. The container type is chosen as a mud tank pursuing efficient transport and better management of equipment. The single- and two-phase simulations about the agitation in the mud tank are performed to analyze and identify the inner flow behavior. The convergence of results is obtained for the vertical- and axis-direction velocity vector fields based on the grid-dependency tests. The mixing time analysis depending on the multiphase flow conditions indicates that the utilization of a two-stepped impeller with a smaller size provides less time for mixing. This study's results are expected to be utilized as the preliminary data to develop the mixing and integrating equipment of the onshore drilling mud system.

• Journal of Biomedical Engineering Research
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• v.17 no.4
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• pp.449-458
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• 1996

Most of the conventional electrocardiowaphs foil to detect signals other than P-QRS-T due to the limited SNR and bandwidth. High-resolution electrocardiography(HRECG) provides better SNR and wider bandwidth for the detection of micro-potentials with higher frequency components such as vontricular late potentials(LP). We have developed a HRECG using uncorrected XYZ lead for the detection of LPs. The overall gain of the amplifier is 4000 and the bandwidth is 0.5-300Hz without using 60Hz notch filter. Three 16-bit A/D converters sample X, Y, and Z signals simultaneously with a sampling frequency of 2000Hz. Sampled data are transmitted to a PC via a DMA-controlled, optically-coupled serial communication channel. In order to further reduce the noise, we implemented a signal averaging algorithm that averaged many instances of aligned beats. The beat alignment was carried out through the use of a template matching technique that finds a location maximizing cross-correlation with a given beat tem- plate. Beat alignment error was reduced to $\pm$0.25ms. FIR high-pass filter with cut-off frequency of 40Hz was applied to remove the low frequency components of the averaged X, Y, and Z signals. QRS onset and end point were determined from the vector magnitude of the sigrlaIL and some parameters needed to detect the existence of LP were estimated. The entire system was designed for the easy application of the future research topics including the optimal lead system, filter design, new parameter extraction, etc. In the developed HRECG, without signal averaging, the noise level was less than 5$\mu$V$_rms RTI$. With signal averaging of at least 100 beats, the noise level was reduced to 0.5$\mu$V$_rms RTI$, which is low enough to detect LPs. The developed HRECG will provide a new advanced functionality to interpretive ECG analyzers.

• Journal of Korea Multimedia Society
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• v.5 no.1
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• pp.68-76
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• 2002

Multicast in mobile host has the problem of hast mobility, multicast decision, triangle routing, tunnel convergence, implosion of retransmission, and bandwidth waste. In particular, the bandwidth waste in radio is a definite factor that decreases transmission rate. To solve the problems, this paper proposes a new multicast transmission protocol called FIM(Forward Error Correction Integrated Multicast), which supports reliable packet recovery mechanism by integrating If Mobility Support for the host mobility, IGMP(Interned Group Management Protocol) for the group management, and DVMRP(Distance Vector Multicast Routing Protocol) for the multicast routing, and it also uses FEC and the local recovery method based on receiver. The performance measurement is performed by dividing the losses into the homogeneous independent loss, the heterogeneous independent loss, and the shared source link loss model.. The result shows that the performances improves in proportion to the size of local areal group when the size of transmission group exceeds designated size. This indicates FIM is effective in the environment where there are much of data and many receivers in the mobile host.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.726-735
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• 2013

This paper proposed face recognition methods about performance improvement of the face recognition using the properties of wavelet transform. Using discrete wavelet transform is Daubechies D4 filter that is similar to mother wavelet transform. For discrete wavelet transform method, In this case, by using LL subband only we can reduce processing time and amount of memory in recognition processing. To improve recognition ratio without further loss of 2 dimensional data changing, We applies 2D LDA. We perform SVM training algorithm to the feature vector obtained by 2D LDA. Experiment is performed using ORL database set and Yale database set by Matlab program. Test result shows that proposed method is superior to existence methods in recognition rate and performance time.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.2
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• pp.65-72
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• 2014

Change coupling is a measure to show how strongly change-related two entities are. When two source files have been frequently changed together, they are regarded as change-coupled files and they will probably be changed together in the near future. In the previous studies, the change coupling between two files is defined with the number of common changed time, that is, common commit time of the files. However, the frequency-based technique has limitations because of 'tangled changes', which frequently happens in the development environments with version control systems. The tangled change means that several code hunks have been changed at the same time, though they have no relation with each other. In this paper, the change types of the code hunks are also used to define change coupling, in addition to the common commit time of target files. First, the frequency vector based on change types are defined with the extracted change types, and then, the similarity of change patterns are calculated using the cosine similarity measure. We conducted experiments on open source project Eclipse JDT and CDT for case studies. The result shows that the applicability of the proposed method, compared to the previous studies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1129-1135
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• 2007

Human face detection technique plays an important role in computer vision area. It has lots of applications such as face recognition, video surveillance, human computer interface, face image database management, and querying image databases. In this paper, a fast face detection approach using Principal Component Analysis (PCA) and Support Vector Machines (SVM) is proposed based on the previous study on face detection technique. In the proposed detection system, firstly it filter the face potential area using statistical feature which is generated by analyzing the local histogram distribution the detection process is speeded up by eliminating most of the non-face area in this step. In the next step, PCA feature vectors are generated, and then detect whether there are faces present in the test image using SVM classifier. Finally, store the detection results and output the results on the test image. The test images in this paper are from CMU face database. The face and non-face samples are selected from the MIT data set. The experimental results indicate the proposed method has good performance for face detection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1682-1688
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• 2008

The Counterpropagation algorithm(CP) is a combination of Kohonen competition network as a hidden layer and the outstar structure of Grossberg as an output layer. CP has been used in many real applications for pattern matching, classification, data compression and statistical analysis since its learning speed is faster than other network models. However, due to the Kohonen layer's winner-takes-all strategy, it often causes instable learning and/or incorrect pattern classification when patterns are relatively diverse. Also, it is often criticized by the sensitivity of performance on the learning rate. In this paper, we propose an enhanced CP that has multiple Kohonen layers and dynamic controlling facility of learning rate using the frequency of winner neurons and the difference between input vector and the representative of winner neurons for stable learning and momentum learning for controlling weights of output links. A real world application experiment - pattern recognition from passport information - is designed for the performance evaluation of this enhanced CP and it shows that our proposed algorithm improves the conventional CP in learning and recognition performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.8
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• pp.1478-1485
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• 2007

In this paper, a meteorological system including a wind speed & direction module and the DSP(Digital Signal Processor) sensor interface circuit board are proposed. This DSP system accepts and process the informations from a wind speed & direction module, the atmospheric pressure sensor, the ambient air temperature sensor and transfers it to the PC monitoring system. Especially, a wind speed & direction module and a DSP hardware are directly designed and applied. A wind speed & direction module have a construction that it have four film type RID(Resistive Temperature Detectors) resistive sensor adhered around the circular metal body heated constantly by heating coil for obtaining vector informations about wind. By this structure, the module is enabled precise measurement having a robustness about vibration, humidity, corrosion. A sensor signal processing circuit is using TMS320F2812 TI(Texas Instrument) Corporation high speed DSP. An economical meteorological system could be constructed through the data from wind speed & direction module and by the fast processing of DSP interface circuit board.

• Experimental and Molecular Medicine
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• v.50 no.12
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• pp.8.1-8.12
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• 2018

FAM46B is a member of the family with sequence similarity 46. Little is known about the expression and functional role (s) of FAM46B in prostate cancer (PC). In this study, the expression of FAM46B expression in The Cancer Genome Atlas, GSE55945, and an independent hospital database was measured by bioinformatics and real-time PCR analysis. After PC cells were transfected with siRNA or a recombinant vector in the absence or presence of a ${\beta}$-catenin signaling inhibitor (XAV-939), the expression levels of FAM46B, C-myc, Cyclin D1, and ${\beta}$-catenin were measured by western blot and realtime PCR. Cell cycle progression and cell proliferation were measured by flow cytometry and the CCK-8 assay. The effects of FAM46B on tumor growth and protein expression in nude mice with PC tumor xenografts were also measured. Our results showed that FAM46B was downregulated but that ${\beta}$-catenin was upregulated in patients with PC. FAM46B silencing promoted cell proliferation and cell cycle progression in PC, which were abrogated by XAV-939. Moreover, FAM46B overexpression inhibited PC cell cycle progression and cell proliferation in vitro and tumor growth in vivo. FAM46B silencing promoted ${\beta}$-catenin protein expression through the inhibition of ${\beta}$-catenin ubiquitination. Our data clearly show that FAM46B inhibits cell proliferation and cell cycle progression in PC through ubiquitination of ${\beta}$-catenin.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.9
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• pp.373-378
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• 2019

Since many programming sources are open online, problems with reckless plagiarism and copyrights are occurring. Among them, source codes produced by repeated authors may have unique fingerprints due to their programming characteristics. This paper identifies each author by learning from a Google Code Jam program source using deep neural network. In this case, the original creator's source is to be vectored using a pre-processing instrument such as predictive-based vector or frequency-based approach, TF-IDF, etc. and to identify the original program source by learning by using a deep neural network. In addition a language-independent learning system was constructed using a pre-processing machine and compared with other existing learning methods. Among them, models using TF-IDF and in-depth neural networks were found to perform better than those using other pre-processing or other learning methods.