• Design & Manufacturing
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• v.14 no.3
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• pp.17-22
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• 2020

As devices such as smartphones, tablet PC, and wearable devices have been miniaturized, the connectors that go into the devices are also designed to be very small. The connector combines the plug and the receptacle to transfer electricity. As devices are miniaturized, the contact shape is formed by partially thinning the thickness of the raw material of the terminal in order to lower the coupling height of the plug and receptacle. The product used in this study is a receptacle terminal used for 0.4mm pitch board to board connector among fine pitch connectors. When the material thickness is reduced by forging the receptacle terminal, the width change of the pin is checked. To reduce the thickness of the material by forging, pre-notching is applied in the first step, forging in the second step, and notching in the third step. After forming the width dimension of the pin to 0.28 mm in the pre-notching process, in the forging process, the material thickness 0.08 mm and 0.02 mm (25%) were forged and the thickness was changed to 0.06 mm and the width change amount of the pin was measured. The facility produced 10,000 pieces at 400 SPM using a Yamada Dobby (MXM-40L) press, and thirty pins were measured and the average value was shown. After forging by using C5210-H (HP) and NKT322-EH, which are frequently used in connectors, analyze the amount of change in each material. The effect of punching oil on forging is investigated by appling FM-200M, which is highly viscous, and FL-212, fast drying oil. This study aims to minimize mold modification by predicting the amount of material change after forging.

• Biomolecules & Therapeutics
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• v.8 no.1
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• pp.63-72
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• 2000

We intended to show some basic requirements for spectrum analysis of electroencephalogram (EEG) by visualizing the differences of the results according to different values of some parameters for analysis. Spectrum analysis is the most popular technique applied for the quantitative analysis of the electroen- cephalographic signals. Each step from signal acquisition through spectrum analysis to presentation of parameters was examined with providing some different values of parameters. The steps are:(1) signal acquisition; (2) spectrum analysis; (3) parameter extractions; and (4) presentation of results. In the step of signal acquisition, filtering and amplification of signal should be considered and sampling rate for analog-to-digital conversion is two-time faster than highest frequency component of signal. For the spectrum analysis, the length of signal or epoch size transformed to a function on frequency domain by courier transform is important. Win dowing method applied for the pre-processing before the analysis should be considered for reducing leakage problem. In the step of parameter extraction, data reduction has to be considered so that statistical comparison can be used in appropriate number of parameters. Generally, the log of power of all bands is derived from the spectrum. For good visualization and quantitative evaluation of time course of the parameters are presented in chronospectrogram.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.23-30
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• 2013

In this paper, we propose pre-arrangement based task scheduling scheme to reduce MapReduce job processing time. If a task and data to be processed do not locate in same node, the data should be transmitted to node where the task is allocated on. In that case, a job processing time increases owing to data transmission time. To avoid that case, we schedule tasks into two steps. In the first step, tasks are sorted in the order of high data locality. In the second step, tasks are exchanged to improve their data localities based on a location information of data. In performance evaluation, we compare the proposed method based Hadoop with a default Hadoop on a small Hadoop cluster in term of the job processing time and the number of tasks sorted to node without data to be processed by them. The result shows that the proposed method lowers job processing time by around 18%. Also, we confirm that the number of tasks allocated to node without data to be processed by them decreases by around 25%.

• Journal of Microbiology and Biotechnology
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• v.9 no.2
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• pp.179-183
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• 1999

A recombinant form of hirudin, a potent thrombin-specific inhibitor derived from the bloodsucking leech, was expressed as a secretory product in Saccharomyces cerevisiae under the control of GALl0 promoter and the mating factor $\alpha$pre-pro leader sequence. In an attempt to produce recombinant hirudin (r-Hir) of therapeutic purity in large quantities, the fed-batch fermentation was carried out by using this recombinant yeast, and subsequently downstream processing was developed with the preparative-scale column chromatography systems. About 234 mg/l of biologically active r-Hir was produced as a secretory product by the fed-batch fermentation strategy developed for an efficient downstream processing. Using a two-step chromatography process (an anion exchange chromatography followed by the reverse phase HPLC), the r-Hir was purified to>98% with an overall recovery yield of 84%. According to the N-terminal amino acid sequencing, the purified r-Hir was found to have the predicted N-terminal amino acid sequence. The biological activity of the purified r-Hir to inhibit thrombin was also identical to that of the commercial hirudin.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.574-575
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• 2021

Re-manufacturing is the process of recovering the function and performance of the original product through a re-assembly process such as a new product assembly process after reprocessing by recovering used products or parts that are in the disposal stage at the end of their lifespan. One of the manufacturing methods. The remanufacturing industry is important not only in terms of environmental protection, but also in terms of economics. The success or failure of the industry as a whole depends on trust in products and price competitiveness. Image processing systems are used to reduce labor costs and improve product reliability in the product manufacturing process. In this study, foreign substances and defects that are difficult to identify with the human eye are detected by using the pre-processing step of determining whether to recycle the drum and image processing immediately before shipment after regenerating the drum to regenerate the waste drum.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.1
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• pp.35-41
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• 2006

Although reachers have studied for a long time, they don't make criteria for anesthesia depth. anesthetists can't make a prediction about patient's reaction. Therefor, patients have potential risk such as poisonous side effect late-awake, early-awake and strain reaction. EEG are received from twenty-five patients who agreed to investigate themselves during operation with Enflurane-anesthesis in progress of anesthesia. EEG are divided pre-anesthesia, before incision of skin, operation 1, operation 2, awaking, post-anesthesia by anesthesia progress step. EEG is applied pre-processing, base line correct, linear detrend to get more reliable data. EEG data are handled by electronic processing and the EEG data are calculated by bicoherence. During pre-anesthesia and post anesthesia, appearance rate of bicoherence value is observed strong appearance rate in high frequency range($15\~30Hz$). During the anesthesia of patient, a strong appearance rate is revealed the low frequency area(0~10Hz). After bicoherence is calculated by percentage of a appearance rate, that is, Bicpara$\#$1, Bicpara$\#$2, Bicpara$\#$3 and Bicpara$\#$4 parameter are extracted. In result of bicoherence analysis, Bicpara$\#$2 and Bicpara#4 are considered that the best parameter showed progress of anesthesia effectively. And each separated bicoherence are calculated by average bicoherence's numerical value, divide by 2 area, appear by each BicHz$\#$1, BicHz$\#$2, and observed BicHz$\#$1/BicHz$\#$2's change. In result of bicoherence analysis, BicHz$\#$1, BicHz$\#$2 and BicHz$\#$1/BicHz$\#$2 are considered that the best parameter showed progress of anesthesia effectively. In conclusion, I confirmed the anesthesia progress phase, concluded to usefulness of parameter on bispectrum and bicoherence analysis and evaluated the depth of anesthesia. In the future, it is going to use for doctor's diagnosis and apply to protect an medical accident owing to anesthesia.

• Spatial Information Research
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• v.19 no.5
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• pp.1-11
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• 2011

This study mainly focused on the method of accurately extracting damage information in the im agery change detection process using the constructed high resolution aerial im agery. Bongwha-gun in Gyungsangbuk-do which had been severely damaged from a localized torrential downpour at the end of July, 2008 was selected as study area. This study utilized aerial im agery having photographing scale of 30cm gray image of pre-disaster and 40cm color image of post-disaster. In order to correct errors from the differences of the image resolution of pre-/post-disaster and time series, the prelim inary phase of image processing techniques such as normalizing, contrast enhancement and equalizing were applied to reduce errors. The extent of the damage was calculated using one to one comparison of the intensity of each pixel of pre-/post-disaster im aged. In this step, threshold values which facilitate to extract the extent that damage investigator wants were applied by setting difference values of the intensity of pixel of pre-/post-disaster. The accuracy of optimal image processing and the result of threshold values were verified using the error matrix. The results of the study enabled the early exaction of the extents of the damages using the aerial imagery with identical characteristics. It was also possible to apply to various damage items for imagery change detection in case of utilizing multi-band im agery. Furthermore, more quantitative estimation of the dam ages would be possible with the use of numerous GIS layers such as land cover and cadastral maps.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.2
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• pp.81-86
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• 2014

In this paper, we present an effective sound classification system for recognizing the real-time context of a smartphone user. Our system avoids unnecessary consumption of limited computational resource by filtering both silence and white noise out of input sound data in the pre-processing step. It also improves the classification performance on low energy-level sounds by amplifying them as pre-processing. Moreover, for efficient learning and application of HMM classification models, our system executes the dimension reduction and discretization on the feature vectors through k-means clustering. We collected a large amount of 8 different type sound data from daily life in a university research building and then conducted experiments using them. Through these experiments, our system showed high classification performance.

• Journal of Information Processing Systems
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• v.10 no.3
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• pp.395-411
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• 2014

Temporal medical data is often collected during patient treatments that require personal analysis. Each observation recorded in the temporal medical data is associated with measurements and time treatments. A major problem in the analysis of temporal medical data are the missing values that are caused, for example, by patients dropping out of a study before completion. Therefore, the imputation of missing data is an important step during pre-processing and can provide useful information before the data is mined. For each patient and each variable, this imputation replaces the missing data with a value drawn from an estimated distribution of that variable. In this paper, we propose a new method, called Newton's finite divided difference polynomial interpolation with condition order degree, for dealing with missing values in temporal medical data related to obesity. We compared the new imputation method with three existing subspace estimation techniques, including the k-nearest neighbor, local least squares, and natural cubic spline approaches. The performance of each approach was then evaluated by using the normalized root mean square error and the statistically significant test results. The experimental results have demonstrated that the proposed method provides the best fit with the smallest error and is more accurate than the other methods.

• Journal of Sensor Science and Technology
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• v.30 no.6
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• pp.429-435
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• 2021

In this study, the creation of emotional dialogue was investigated within the process of developing a robot's natural language understanding and emotional dialogue processing. Unlike an English-based dataset, which is the mainstay of natural language processing, the Korean-based dataset has several shortcomings. Therefore, in a situation where the Korean language base is insufficient, the Korean dataset should be dealt with in detail, and in particular, the unique characteristics of the language should be considered. Hence, the first step is to base this study on a specific Korean dataset consisting of conversations on emotional topics. Subsequently, a model was built that learns to extract the continuous dialogue features from a pre-trained language model to generate sentences while maintaining the context of the dialogue. To validate the model, a chatbot system was implemented and meaningful results were obtained by collecting the external subjects and conducting experiments. As a result, the proposed model was influenced by the dataset in which the conversation topic was consultation, to facilitate free and emotional communication with users as if they were consulting with a chatbot. The results were analyzed to identify and explain the advantages and disadvantages of the current model. Finally, as a necessary element to reach the aforementioned ultimate research goal, a discussion is presented on the areas for future studies.