• YAKHAK HOEJI
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• v.33 no.5
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• pp.312-318
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• 1989

Microcapsule of Propranolol HCl with Cellulose Acetate Phthalate (CAP) by coacervation-phase separation method was studied. Encapsulation was carried out in the CAP-liquid paraffin-acetone ethanol solvent system. The optimum weight ratio for microencapsulation in the CAP-liquid paraffin-solvent system was 1.32:89.18:9.50 or 1.65:89.42:8.93. The wall thickness of microcapsules increased according to increasing of CAP concentration, but dissolution rate decreased. The dissolution of propranolol-HCl in simulated gastric and intestinal fluid test solution was completed within 3 min., but T50% of propranolol HCl from 10.0% CAP-microcapsules were 390 min. and 210 min. respectively. The released amount from 12.5% CAP-microcapsules was 41.8% within 720 min. in simulatd gastric fluid test solution and T50% of those in simulated intestinal fluid test solution was 250 min.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.305-318
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• 2022

Abusive behaviors have become a common issue in many online social media platforms. Profanity is common form of abusive behavior in online. Social media platforms operate the filtering system using popular profanity words lists, but this method has drawbacks that it can be bypassed using an altered form and it can detect normal sentences as profanity. Especially in Korean language, the syllable is composed of graphemes and words are composed of multiple syllables, it can be decomposed into graphemes without impairing the transmission of meaning, and the form of a profane word can be seen as a different meaning in a sentence. This work focuses on the problem of filtering system mis-detecting normal phrases with profane phrases. For that, we proposed the deep learning-based framework including grapheme and syllable separation-based word embedding and appropriate CNN structure. The proposed model was evaluated on the chatting contents from the one of the famous online games in South Korea and generated 90.4% accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.2211-2217
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• 2009

In this paper, we propose the speech enhancement algorithm using an one-microphone in a reverberant room environments. Spectral subtraction is the effective method which can reduce the reverberation element and the noise in a spectrum domain. Spectral subtraction needs correct separation of voice section and silent section therefore to improve the performance, voice activity detection(VAD) based on entropy has been applied to the proposed method. We test a performance of the proposed method by comparing with conventional method which used VAD based on energy detection. Reverberation reduction ratio with variable of SNR and a reverberation time is used as a test index. From the simulation result, proposed method shows performance better than conventional method.

• Bulletin of the Korean Chemical Society
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• v.33 no.10
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• pp.3298-3302
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• 2012

Although offline enrichment of phosphorylated peptides is widely used, enrichment for phosphopeptides using $TiO_2$ is often performed manually, which is labor-intensive and can lead to irreproducible results. To address the problems associated with offline enrichment and to improve the effectiveness of phosphopeptide detection, we developed an automated online enrichment system for phosphopeptide analysis. A standard protein mixture comprising BSA, fetuin, crystalline, ${\alpha}$-casein and ${\beta}$-casein, and ovalbumin was assessed using our new system. Our multidimensional system has four main parts: a sample pump, a 20-mm $TiO_2$-based column, a weak anion-exchange, and a strong cation-exchange (2:1 WAX:SCX) separation column with LC/MS. Phosphorylated peptides were successfully detected using the $TiO_2$-based online system with little interference from nonphosphorylated peptides. Our results confirmed that our online enrichment system is a simple and efficient method for detecting phosphorylated peptides.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.4
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• pp.102-110
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• 2009

In this paper, we propose an object detection method for real-time in infrared (IR) images and PowerPC (PPC) and H/W design based on field programmable gate array (FPGA). An open H/W architecture has the advantages, such as easy transplantation of HW and S/W, support of compatibility and scalability for specification of current and previous versions, common module design using standardized design, and convenience of management and maintenance. Proposed background modeling for an open H/W architecture design decreases size of search area to construct a sparse block template of search area in IR images. We also apply to compensate for motion compensation when image moves in previous and current frames of IR sensor. Separation method of background and objects apply to adaptive values through time analysis of pixel intensity. Method of clutter reduction to appear near separated objects applies to median filter. Methods of background modeling, object detection, median filter, labeling, merge in the design embedded system execute in PFC processor. Based on experimental results, proposed method showed real-time object detection through global motion compensation and background modeling in the proposed embedded system.

• Journal of Aerospace System Engineering
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• v.15 no.5
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• pp.81-88
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• 2021

In general, a non-explosive nylon wire cutting-based holding and release mechanism has been used to store and deploy deployable solar panels of CubeSat. However, with this method, accessing the solar panel's access port for charging the cube satellite's battery and electrical inspection and testing of the PCB and payloads while the solar panel is in storage is difficult. Additionally, the mechanism must have a reliable release function in an in-orbit environment, and reusability for stow and deploy of the solar panel, which is a hassle for the operator and difficult to maintain a consistent nylon wire fastening process. In this study, we proposed a pin-puller-based solar panel holding and release mechanism that can easily deploy a solar panel without cutting nylon wires by separating constraining pins. The proposed mechanism's release function and performance were verified through a solar panel deployment test and a maximum separation load measurement test. Through this, we also verified the design feasibility and effectiveness of the pin-puller-based separation device.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.183-194
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• 2021

In this study, the conversion factor for 2020 is estimated based on an outpatient and inpatient conversion factor separation model developed from SGR and AR by using actual medical expense data. In addition, a policy plan is proposed to calculate the values of single and multiple conversion factors for each type of medical expense, and to effectively use the conversion factor separation model as one of the means to establish a medical delivery system. The major results are as follows. First, at r=0.1, the rate of adjustment in the hospital single conversion index in 2020 was 2.0%, and the outpatient and hospitalization conversion rates for hospitals were 2.2% and 2.3%, respectively. In addition, a combination of outpatient and inpatient conversion factors can be used for the adjustment. Second, as a measure to establish a medical delivery system, instead of adjusting the addition rate, a method of interlocking the addition rate and the conversion factor is proposed. Third, it is necessary to develop a model that enables target management of volumes, in addition to the outpatient conversion factor, the inpatient conversion factor, and the adjustment coefficient.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.838-842
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• 2007

A brain-computer interface(BCI) system is a communication channel which transforms a subject's thought process into command signals to control various devices. These systems use electroencephalographic signals or the neuronal activity of many single neurons. The presented study deals with an efficient analysis method of neuronal signals from a BCI System using an independent component analysis(ICA) algorithm. The BCI system was implemented to generate event signals coding movement information of the subject. To apply the ICA algorithm, we obtained the perievent histograms of neuronal signals recorded from prefrontal cortex(PFC) region during target-to-goal(TG) task trials in the BCI system. The neuronal signals were then smoothed over 5ms intervals by low-pass filtering. The matrix of smoothed signals was then rearranged such that each signal was represented as a column and each bin as a row. Each column was also normalized to have a unit variance. As a result, we verified that different patterns of the neuronal signals are dependent on the target position and predefined event signals.

• Membrane Journal
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• v.16 no.3
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• pp.167-181
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• 2006

Continuous Electrodeionization (CEDI) is a hybrid separation process of electrodialysis and ion exchange to produce high purity water under electric field. CEDI system is generally explained with two regimes, ionic removal and electroregeneration. The performance optimization and modification of stack configuration is required for the effective utilization and various applications of a CEDI system. Understanding on various system characterization method and ion transport equation is thus necessary to utilize the CEDI system more effectively. This article provides a general review of continuous electrodeionization, including the basic principles and current stage of technologies of a CEDI system.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.3
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• pp.259-266
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• 2013

An automated cell tracking system is used to automatically analyze and track the changes in cell behavior in time-lapse cell images acquired using a microscope with a cell culture. Clustering is the partial overlapping of neighboring cells in the process of cell change. Separating clusters into individual cells is very important for cell tracking. In this study, we proposed an algorithm for separating clusters by using ellipse fitting based on a direct least square method. We extracted the contours of clusters, divided them into line segments, and then produced their fitted ellipses using a direct least square method for each line segment. All of the fitted ellipses could be used to separate their corresponding clusters. In experiments, our algorithm separated clusters with average precisions of 91% for two overlapping cells, 84% for three overlapping cells, and about 73% for four overlapping cells.