• The Journal of the Korean dental association
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• v.52 no.8
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• pp.472-477
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• 2014

The new paradigm of dentistry require the detection of caries in their earlier stages. To achieve this, a high technology detection device and systematic and organized caries management system are needed. Caries management by risk assessment (CAMBRA) model is representative caries management system that satisfied new paradigm. Dental caries prevention and treatment according to CAMBRA model is patient-centered, risk-based, evidence-based practice. Therefore, individual caries management such as CAMBRA should be performed through accurate assessment of caries disease indicators and comprehensive assessment of caries risk factors and protective factors. Based on the CAMBRA better effectiveness of comprehensive dental caries management including non-surgical treatment will be accomplished.

• Bulletin of the Korean Chemical Society
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• v.19 no.5
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• pp.524-526
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• 1998

A sensitive and specific method is described for the determination of midazolam in human plasma. The drug was extracted from 1 mL of carbonate buffered plasma (pH 9.6) with 8 mL of diethyl ether. Famprofazone was used as internal standard. The organic phase was evaporated to dryness. The residue was dissolved in methanol for the direct analysis by gas chromatograph-nitrogen phosphorus detector system. In the concentration range of 1-5000 ng/mL, the calibration curve was linear. The coefficients of variation from the precision test were <6% at the range of the concentration of 0.10-2.00 μg/mL and the detection limit for midazolam in 1 mL of plasma was o.5 ng. This assay is more sensitive, selective, simple and rapid than earlier methods. Plasma midazolam concentrations were determined by this method after administration of midazolam.

• Journal of Multimedia Information System
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• v.9 no.2
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• pp.161-170
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• 2022

Under General anesthesia with isoflurane, we insert a chicken's esophageal catheter into the near the left atrium. 1MHz radio wave was added to electrocardiogram electrodes of the esophagus, and the change of impedance (phase) was obtained by amplitude synchronous detection technique. At the same time, a thin tube is surgically inserted into the axillary artery to continuously measure blood pressure. The correlation between impedance (phase) and blood pressure was obtained. Both showed a very high correlation (R²=0.9665). It was also observed the waveform flowing from the left atrium into the left ventricle. When an individual infected with the avian influenza virus develops, the cytokine storms lead to hypotension earlier than the test for antigen-antibody reaction. In order to detect this, in the future, this impedance technique will be useful for screening individuals infected with avian influenza virus by measuring the blood pressure of chickens in cages in a non-contact manner using microwaves.

• Journal of Broadcast Engineering
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• v.20 no.6
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• pp.871-879
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• 2015

With the increase of mass contents data, a method of a scene change detection is required for analysis, indexing and editing. Although many researchers are studying a variety of scene change detection method, it is too difficult to accurately detect various movements of the cameras and scene changes. Also, earlier scene change detection methods take too much time to apply to UHD video contents. That is because the UHD video contents with 4K (3820x2160) resolution or higher have greater amount of data. Therefore a method for detecting a scene change by using the next-generation codec, HEVC, is required. In this paper, we propose four scene change detection methods using the coding additional information of HEVC, and a new pixel-based scene change detection system. Furthermore, through the experimental results, we check the possibility of detecting the scene changes of UHD videos encoded in HEVC format.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.1
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• pp.1-10
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• 2008

In this paper, we designed a facial feature(eyes, a moult and a nose) detection hardware based on the ICT transform which was developed for face detection earlier. Our design used a pipeline architecture for high throughput and it also tried to reduce memory size and memory access rate. The algerian and its hardware implementation were tested on the BioID database, which is a worldwide face detection test bed, and its facial feature detection rate was 100% both in software and hardware, assuming the face boundary was correctly detected. After synthesizing the hardware on Dongbu $0.18{\mu}m$ CMOS library, its die size was $376,821{\mu}m^2$ with the maximum operating clock 78MHz.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.192-197
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• 2020

Multivariate processes, such as large scale power plants or chemical processes are operated in very hazardous environment, which can lead to significant human and material losses if a fault occurs. On-line monitoring technology, therefore, is essential to detect system faults. In this paper, the ICA-based fault detection method is conducted using three different multivariate process data. Fault detection procedure based on ICA is divided into off-line and on-line processes. The off-line process determines a threshold for fault detection by using the obtained dataset when the system is normal. And the on-line process computes statistics of query vectors measured in real-time. The fault is detected by comparing computed statistics and previously defined threshold. For comparison, the PCA-based fault detection method is also implemented in this paper. Experimental results show that the ICA-based fault detection method detects the system faults earlier and better than the PCA-based method.

• Journal of Korean Neurosurgical Society
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• v.56 no.6
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• pp.455-462
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• 2014

Objective : To propose a new measure for effective monitoring of intraoperative somatosensory evoked potentials (SEP) and to validate the feasibility of this measure for evoked potentials (EP) and single trials with a retrospective data analysis study. Methods : The proposed new measure (hereafter, a slope-measure) was defined as the relative slope of the amplitude and latency at each EP peak compared to the baseline value, which is sensitive to the change in the amplitude and latency simultaneously. We used the slope-measure for EP and single trials and compared the significant change detection time with that of the conventional peak-to-peak method. When applied to single trials, each single trial signal was processed with optimal filters before using the slope-measure. In this retrospective data analysis, 7 patients who underwent cerebral aneurysm clipping surgery for unruptured aneurysm middle cerebral artery (MCA) bifurcation were included. Results : We found that this simple slope-measure has a detection time that is as early or earlier than that of the conventional method; furthermore, using the slope-measure in optimally filtered single trials provides warning signs earlier than that of the conventional method during MCA clipping surgery. Conclusion : Our results have confirmed the feasibility of the slope-measure for intraoperative SEP monitoring. This is a novel study that provides a useful measure for either EP or single trials in intraoperative SEP monitoring.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.783-793
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• 2019

Purpose: The purpose of this study is to apply the machine and deep learning methodology on error terms which are continuously auto-generated on the sensors with specific time period and prove the improvement effects of power generator prediction diagnosis system by comparing detection ability. Methods: The SVM(Support Vector Machine) and MLP(Multi Layer Perception) learning procedures were applied for predicting the target values and sequentially producing the error terms for confirming the detection improvement effects of suggested application. For checking the effectiveness of suggested procedures, several detection methodologies such as Cusum and EWMA were used for the comparison. Results: The statistical analysis result shows that without noticing the sequential trivial changes on current diagnosis system, suggested approach based on the error term diagnosis is sensing the changes in the very early stages. Conclusion: Using pattern of error terms as a diagnosis tool for the safety control process with SVM and MLP learning procedure, unusual symptoms could be detected earlier than current prediction system. By combining the suggested error term management methodology with current process seems to be meaningful for sustainable safety condition by early detecting the symptoms.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.2
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• pp.125-133
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• 2009

RDF is widely used as the ontology language for representing metadata on the semantic web. Since ontology models the real-world, ontology changes overtime. Thus, it is very important to detect and analyze changes in knowledge base system. Earlier studies on detecting changes between RDF models focused on the structural differences. Some techniques which reduce the size of the delta by considering the RDFS entailment rules have been introduced. However, inferencing with RDF models increases data size and upload time. In this paper, we propose a new change detection using RDF reasoning that only computes a small part of the implied triples using backward chaining strategy. We show that our approach efficiently detects changes through experiments with real-life RDF datasets.

• Journal of Communications and Networks
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• v.8 no.1
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• pp.93-105
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• 2006

The domination of the Internet by TCP-based services has spawned many efforts to provide high network utilization with low loss and delay in a simple and scalable manner. Active queue management (AQM) algorithms attempt to achieve these goals by regulating queues at bottleneck links to provide useful feedback to TCP sources. While many AQM algorithms have been proposed, most suffer from instability, require careful configuration of nonintuitive control parameters, or are not practical because of slow response to dynamic traffic changes. In this paper, we propose a new AQM algorithm, hybrid random early detection (HRED), that combines the more effective elements of recent algorithms with a random early detection (RED) core. HRED maps instantaneous queue length to a drop probability, automatically adjusting the slope and intercept of the mapping function to account for changes in traffic load and to keep queue length within the desired operating range. We demonstrate that straightforward selection of HRED parameters results in stable operation under steady load and rapid adaptation to changes in load. Simulation and implementation tests confirm this stability, and indicate that overall performances of HRED are substantially better than those of earlier AQM algorithms. Finally, HRED control parameters provide several intuitive approaches to trading between required memory, queue stability, and response time.