• Polymer(Korea)
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• 제29권5호
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• pp.440-444
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• 2005

An increase in the surface area of drugs by reducing particle sizes from microns to nanometers has been known as an efficient method to improve the bioavailability of water-insoluble drugs. To prevent drug nanoparticles from aggregation during the processes of drug formulation, a limited number of pharmaceutical inactive ingredients such as hydroxypropyl cellulose has been employed as stabilizers or dispersants. In this study, copolymers of hydrophilic and hydrophobic amino acids were synthesized by the ring opening polymerization of their N-carboxyanhydride monomers and evaluated as novel candidates to stabilize the nanoparticles of a water insoluble drug, naproxen. Naproxen nanoparticles stabilized by synthesized amino acid copolymers were successfully prepared in the size of $200\~500nm$ in 60 min by a wet comminution process. Particle size analysis showed that the effective stabilization performance of copolymers required the hydrophobic moiety content to be higher than $10 mol\%$. However, the molecular weight and morphology of copolymers was not the critical parameters in determining the particle size reduction. Their particle size was found to be stable up to 14 days without significant aggregation.

• Journal of the Korean Society for Nondestructive Testing
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• 제36권1호
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• pp.35-44
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• 2016

Seed viability is one of the most important parameters that is directly related with seed germination performance and seedling emergence. In this study, a hyperspectral imaging (HSI) system having a range of 1000-2500 nm was used to classify viable watermelon seeds from nonviable seeds. In order to obtain nonviable watermelon seeds, a total of 96 seeds were artificially aged by immersing the seeds in hot water ($25^{\circ}C$) for 15 days. Further, hyperspectral images for 192 seeds (96 normal and 96 aged) were acquired using the developed HSI system. A germination test was performed for all the 192 seeds in order to confirm their viability. Spectral data from the hyperspectral images of the seeds were extracted by selecting pixels from the region of interest. Each seed spectrum was averaged and preprocessed to develop a classification model of partial least square discriminant analysis (PLS-DA). The developed PLS-DA model showed a classification accuracy of 94.7% for the calibration set, and 84.2% for the validation set. The results demonstrate that the proposed technique can classify viable and nonviable watermelon seeds with a reasonable accuracy, and can be further converted into an online sorting system for rapid and nondestructive classification of watermelon seeds with regard to viability.

• Journal of the Korean Society for Nondestructive Testing
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• 제36권3호
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• pp.195-201
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• 2016

Eddy current testing (ECT) is commonly applied for the inspection of automated production lines of metallic products, because it has a high inspection speed and a reasonable price. When ECT is applied for the inspection of a metallic object having an uneven target surface, such as the spline gear of a spline shaft, it is difficult to distinguish between the original signal obtained from the sensor and the signal generated by a defect because of the relatively large surface signals having similar frequency distributions. To facilitate the detection of defect signals from the spline gear, implementation of high-order filters is essential, so that the fault signals can be distinguished from the surrounding noise signals, and simultaneously, the pass-band of the filter can be adjusted according to the status of each production line and the object to be inspected. We will examine the infinite impulse filters (IIR filters) available for implementing an advanced filter for ECT, and attempt to detect the flaw signals through optimization of system design parameters for detecting the signals at the system level.

• Journal of the Korean Society for Nondestructive Testing
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• 제34권2호
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• pp.148-154
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• 2014

Photoelasticity is a useful technique for obtaining the differences and directions of principal stresses in a model. In conventional photoelasticity, the photoelastic parameters are measured manually point by point. Identifying and measuring photoelastic data is time-consuming and requires skill. The fringe phase shifting method was recently developed and has been found to be convenient for measuring and analyzing fringe data in photo-mechanics. This paper presents an experimental study on the stress distribution along a horizontal line that passes the central point of a rhombus plate made of Photoflex (i.e., type of urethane rubber). The isoclinic fringe and/or principal stress direction is constant on this horizontal line, so a four-bucket phase shifting method can be applied. The method requires four photoelastic fringes that are obtained from a circular polariscope by rotating the analyzer at $0^{\circ}C$, $45^{\circ}C$, $90^{\circ}C$ and $135^{\circ}C$. Experimental measurements using the method were quantitatively compared with the results from FEM analysis; the results from the two methods showed comparable agreement.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제15권5호
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• pp.3336-3344
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• 2014

The purpose of this study is small scale coagulation module is developed and demonstrated through a lab-scale test. Recent as a sewage treatment rate increases, have heightened the interest in the necessity on the nonpoint source and developing a small processing unit has been increased. Coagulation sedimentation module in this study is additional growth of floc through swirling in the outside zone, reduction of microstructure floc number and the internal settling zone through vertical/level flow complex sedimentation method after the coagulation process precipitation method as an effective high separation efficiency can be divided was also assessed. Coagulation sedimentation module can increase the load factor was 4.4 times compared to conventional clarifier base on the same volume and surface area through vertical/level flow. In this study, this process was selected formation and maintenance of swirling and uniform flow distribution in the internal settling zone as an important design factor, to derive its FLUENT was used to characteristics of the flow model. Through the simulation of swirling, influent velocity, dimensions of external basin, hopper depth of bottom cone was determined and through analysis of velocity distribution, flow distribution detailed specifications are derived like as diameter and number of effluent hole. Lab-scale($120{\ell}/hr$) test results, influent of 300~800 NTU to less than 10 NTU without polymer feeding was able to operate in the 20minutes retention time(surface loading rate $37.3m^3/m^2$-day), and through analysis FLUENT the possibility of using design parameters were derived.

• Polymer(Korea)
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• 제38권2호
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• pp.193-198
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• 2014

Lens and DVD require high quality of optical property. Conventional injection molded products contain high residual stress and this invokes birefringence since high cavity pressure and high temperature variation are involved in a molding process. Thus these products are often molded by injection compression molding in order to minimize the residual stress through reducing cavity pressure and uniform cavity pressure. In this study, molding parameters affecting molding quality such as property uniformity in injection compression molding were investigated through experiment. Molding quality deviations among the cavities in multi-cavity mold were also studied. Transparent resins, PC and PS were used in this study. Compression gap, compression speed, compression force, and compression delay time for processing variables in injection compression molding were applied in experiment. Compression force, compression delay time, and compression gap significantly affected the optical property of product. The degree of influence of process variable on the product quality was different in different resins. This implies that the optimal operational conditions in injection compression molding existed for each resin according to flow property.

• Korean Journal of Remote Sensing
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• 제15권2호
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• pp.147-158
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• 1999

Remote sensing technique has offered better understanding of our environment for the decades by providing useful level of information on the landcover. In many applications using the remotely sensed data, digital image processing methodology has been usefully employed to characterize the features in the data and develop the models. Random field models, especially Markov Random Field (MRF) models exploiting spatial relationships, are successfully utilized in many problems such as texture modeling, region labeling and so on. Usually, remotely sensed imagery are very large in nature and the data increase greatly in the problem requiring temporal data over time period. The time required to process increasing larger images is not linear. In this study, the methodology to reduce the computational cost is investigated in the utilization of the Markov Random Field. For this, multiresolution framework is explored which provides convenient and efficient structures for the transition between the local and global features. The computational requirements for parameter estimation of the MRF model also become excessive as image size increases. A Bayesian approach is investigated as an alternative estimation method to reduce the computational burden in estimation of the parameters of large images.

• Korean Journal of Remote Sensing
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• 제14권3호
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• pp.250-261
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• 1998

The purpose of this paper is to extract fast DEM (Digital Elevation Model) using satellite images. DEM extraction consists of three parts. First part is the modeling of satellite position and attitude, second part is the matching of two images to find corresponding points of them and third part is to calculate the elevation of each point by using the results of the first and second part. The position and attitude modeling of satellite is processed by using GCPs. A area based matching method is used to find corresponding points between the stereo satellite images. The elevation of each point is calculated using the exterior orientation parameters obtained from modeling and conjugate points from matching. In the DEM generation system, matching procedure holds most of a processing time, therefore to reduce the time for matching, a new fast matching algorithm using gradient correlation and fast similarity measure calculation method is proposed. In this paper, the SPOT satellite images, level 1A 6000$\times$6000 panchromatic images are used to extract DEM. The experiment result shows the possibility of fast DEM extraction with the satellite images.

• Journal of Life Science
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• 제31권4호
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• pp.410-417
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• 2021

Next-generation sequencing (NGS) is a high-throughput technique for sequencing large numbers of DNA fragments that are prepared from a genome. This sequencing technique has been used to elucidate whole genome sequences of living organisms and to analyze complementary DNA (cDNA) or chromatin immunoprecipitated DNA (ChIPed DNA) at the genome level. After NGS, the use of proper tools is important for processing and analyzing data with reasonable parameters. However, handling large-scale sequencing data and programing for data analysis can be difficult. The Galaxy platform, a public web service system, provides many different tools for NGS data analysis, and it allows researchers to analyze their data on a web browser with no deep knowledge about bioinformatics and/or programing. In this study, we explain the procedure for preparing chromatin immunoprecipitation-sequencing (ChIP-seq) libraries and steps for analyzing ChIP-seq data using the Galaxy platform. The data analysis steps include the NGS data upload to Galaxy, quality check of the NGS data, premapping processes, read mapping, the post-mapping process, peak-calling and visualization by window view, heatmaps, average profile, and correlation analysis. Analysis of our histone H3K4me1 ChIP-seq data in K562 cells shows that it correlates with public data. Thus, NGS data analysis using the Galaxy platform can provide an easy approach to bioinformatics.

• KIPS Transactions on Computer and Communication Systems
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• 제10권7호
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• pp.191-198
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• 2021

Since the size of training dataset become large and the model is getting deeper to achieve high accuracy in deep learning, the deep neural network training requires a lot of computation and it takes too much time with a single node. Therefore, distributed deep learning is proposed to reduce the training time by distributing computation across multiple nodes. In this study, we propose hybrid allreduce strategy that considers the characteristics of each layer and communication and computational overlapping technique for synchronization of distributed deep learning. Since the convolution layer has fewer parameters than the fully-connected layer as well as it is located at the upper, only short overlapping time is allowed. Thus, butterfly allreduce is used to synchronize the convolution layer. On the other hand, fully-connecter layer is synchronized using ring all-reduce. The empirical experiment results on PyTorch with our proposed scheme shows that the proposed method reduced the training time by up to 33% compared to the baseline PyTorch.