• 대한예방의학회:학술대회논문집
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• 1994.02b
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• pp.169-179
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• 1994

B-mode ultrasound is being used to assess carotid atherosclerosis in epidemiological studies and clinical trials. Recently the interpretation of measurements made from ultrasound images has been questioned. This study examines the anatomical correlates of B-mode ultrasound of carotid arteries in vitro and in situ in cadavers. Twenty-seven segments of human carotid artery were collected at autopsy. pressure perfusion fixed in buffered 2.5% gluteraldehyde and 4% paraformaldehyde and imaged using an ATL UM-8 (10 MHz single crystal mechanical probe). Each artery was then frozen, sectioned and stained with van Gieson or elastin van Gieson. The thickness of the intima. media and adventitia were measured 'to an accuracy of 0.01 mm from histological sections using a calibrated eye graticule on a light microscope. Shrinkage artifact induced by histological preparation was determined to be 7.8%. Digitised ultra sound images of the artery wall were analysed off-line. The distance from the leading edge of the first interface ($LE_{1}$) to the leading edge of the second interface ($LE_2$) was measured using a dedicated programme. $LE_{1}$-$LE_{2}$ measurements were correlated against histological measurements corrected for shrinkage. Mean values for the far wall were: ultra sound $LE_{1}$-$LE_{2}$ (0.97 mm, S.D. 0.26), total wall thickness (1.05 mm, S.D. 0.37), adventitia (0.35 mm, S.D. 0.16), media (0.61 mm, S.D. 0.18). intima (0.09 mm, S.D. 0.13). Ultrasound measurements corresponded best with total wall thickness, rather than elastin or the intima-media complex. Excision of part of the intima plus media or removal of the adventitia resulted in a corresponding decrease in the $LE_{1}$-$LE_{2}$ distance of the B-mode image. Furthermore. increased wall thickness due to intimal atherosclerotic thickening correlated well with $LE_{1}$-$LE_{2}$ distance of the B-mode images. B-mode images obtained from the carotid arteries in situ in four cadavers also corresponded best with total wall thickness measured from histological sections and not with the thickness of the intima plus media. In conclusion, the $LE_{1}$-$LE_{2}$ distance measured on B-mode images of the carotid artery best represents total wall thickness of intima plus media plus adventitia and not intima plus media alone.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.28 no.1
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• pp.41-50
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• 2023

Dissolved oxygen sensors have characteristics in which data drift occurs over time. Therefore, in-situ calibration of the dissolved oxygen sensor is essential to accurately measure the concentration of dissolved oxygen in seawater. In order to provide a method for in-situ calibration, appropriate number of samples for calibration, and laboratory calibration interval of the dissolved oxygen sensor, the dissolved oxygen sensor values were compared with the measured values by titration on a total of 133 samples from three different cruises in the Indian Ocean, Pacific Ocean, and East Sea over a period of about one year. As a result, it is preferable to calibrate the sensor value using the correlation of a straight line obtained by directly comparing the final concentration value given by the sensor and the measured value. For the accurate calibration, at least 30 samples must be used to enable in-situ calibration within an accuracy range of about 1%. In addition, it is recommended that a laboratory calibration should perform within 1 year for the membrane type dissolved oxygen sensor for CTD to achieve a performance of 70% or more.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.61-69
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• 2023

In recent years, due to heightened environmental awareness, Electric Power Steering (EPS) has been increasingly adopted as the steering control unit in manufactured vehicles. This has had numerous benefits, such as improved steering power, elimination of hydraulic hose leaks and reduced fuel consumption. However, for EPS systems to respond to actions, sensors must be employed; this means that the consistency of the sensor's linear variation is integral to the stability of the steering response. To ensure quality control, a reliable method for detecting defects and assessing linearity is required to assess the sensitivity of the EPS sensor to changes in the internal design characters. This paper proposes a data-driven defect and linearity assessment monitoring system, which can be used to analyze EPS component defects and linearity based on vehicle speed interval division. The approach is validated experimentally using data collected from an EPS test jig and is further enhanced by the inclusion of a Graphical User Interface (GUI). Based on the design, the developed system effectively performs defect detection with an accuracy of 0.99 percent and obtains a linearity assessment score at varying vehicle speeds.

• Geomechanics and Engineering
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• v.32 no.1
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• pp.111-123
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• 2023

The slope of an open cut tunnel is located above the exit of the Leijia tunnel on the Changgan high-speed railway. During the excavation of the open cut tunnel foundation pit, the slope slipped twice, a large landslide of 92500 m³ formed. The landslide body and unstable slope body not only caused the foundation pit of the open cut tunnel to be buried and the anchor piles to be damaged but also directly threatened the operational safety of the later high-speed railway. Therefore, to study the stability change in the slope of the open cut tunnel under heavy rain and excavation conditions, a 3D numerical calculation model of the slope is carried out by Midas GTS software, the deformation mechanism is analyzed, anti-sliding measures are proposed, and the effectiveness of the anti-sliding measures is analyzed according to the field monitoring results. The results show that when rainfall occurs, rainwater collects in the open cut tunnel area, resulting in a transient saturation zone on the slope on the right side of the open cut tunnel, which reduces the shear strength of the slope soil; the excavation at the slope toe reduces the anti-sliding capacity of the slope toe. Under the combined action of excavation and rainfall, when the soil above the top of the anchor pile is excavated, two potential sliding surfaces are bounded by the top of the excavation area, and the shear outlet is located at the top of the anchor pile. After the excavation of the open cut tunnel, the potential sliding surface is mainly concentrated at the lower part of the downhill area, and the shear outlet moves down to the bottom of the open cut tunnel. Based on the deformation characteristics and the failure mechanism of the landslides, comprehensive control measures, including interim emergency mitigation measures and long-term mitigation measures, are proposed. The field monitoring results further verify the accuracy of the anti-sliding mechanism analysis and the effectiveness of anti-sliding measures.

• Smart Media Journal
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• v.11 no.11
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• pp.17-24
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• 2022

With the spread of smart speakers based on voice recognition technology and deep learning technology, not only non-disabled people, but also the blind or physically handicapped can easily control home appliances such as lights and TVs through voice by linking home network services. This has greatly improved the quality of life. However, in the case of speech-impaired people, it is impossible to use the useful services of the smart speaker because they have inaccurate pronunciation due to articulation or speech disorders. In this paper, we propose a personalized voice classification technique for the speech-impaired to use for some of the functions provided by the smart speaker. The goal of this paper is to increase the recognition rate and accuracy of sentences spoken by speech-impaired people even with a small amount of data and a short learning time so that the service provided by the smart speaker can be actually used. In this paper, data augmentation and one cycle learning rate optimization technique were applied while fine-tuning ResNet18 model. Through an experiment, after recording 10 times for each 30 smart speaker commands, and learning within 3 minutes, the speech classification recognition rate was about 95.2%.

• Applied Chemistry for Engineering
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• v.34 no.2
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• pp.137-143
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• 2023

In this study, natural surfactants were extracted from Medicago sativa L. The O/W emulsification processes with the extracted natural surfactants were optimized using central composite design model-response surface methodology (CCD-RSM) and a 95% confidence interval was used to confirm the reasonableness of the optimization. Herein, independent parameters were the ratio of saponins to total surfactant (P), amount of surfactant (W), and emulsification speed (R), whereas the reaction parameters were the emulsion stability index (ESI), mean droplet size (MDS), and viscosity (V). Using the multiple reaction, the optimal conditions for the ratio of saponins to total surfactant, amount of surfactant, and emulsification speed for O/W emulsification were 49.5%, 9.1 wt%, and 6559.5 rpm, respectively. Under these optimal conditions, the expected values of ESI, MDS, and V as the reaction parameters were 89.9%, 1058.4 nm, and 1522.5 cP, respectively. The values of ESI, MDS, and V from these expected values were 88.7%, 1026.4 nm, and 1486.5 cP, respectively, and the average experimental error for validating the accuracy was about 2.3 (± 0.4)%. Therefore, it was possible to design an optimization process for evaluating the O/W emulsion process with Medicago sativa L. using CCD-RSM.

• The Korean Journal of Pain
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• v.36 no.1
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• pp.113-127
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• 2023

Background: Resting-state functional connectivity (rs-FC) may aid in understanding the link between painmodulating brain regions and the descending pain modulatory system (DPMS) in fibromyalgia (FM). This study investigated whether the differences in rs-FC of the primary somatosensory cortex in responders and non-responders to the conditioned pain modulation test (CPM-test) are related to pain, sleep quality, central sensitization, and the impact of FM on quality of life. Methods: This cross-sectional study included 33 females with FM. rs-FC was assessed by functional magnetic resonance imaging. Change in the numerical pain scale during the CPM-test assessed the DPMS function. Subjects were classified either as non-responders (i.e., DPMS dysfunction, n = 13) or responders (n = 20) to CPM-test. A generalized linear model (GLM) and a receiver operating characteristic (ROC) curve analysis were performed to check the accuracy of the rs-FC to differentiate each group. Results: Non-responders showed a decreased rs-FC between the left somatosensory cortex (S1) and the periaqueductal gray (PAG) (P < 0.001). The GLM analysis revealed that the S1-PAG rs-FC in the left-brain hemisphere was positively correlated with a central sensitization symptom and negatively correlated with sleep quality and pain scores. ROC curve analysis showed that left S1-PAG rs-FC offers a sensitivity and specificity of 85% or higher (area under the curve, 0.78, 95% confidence interval, 0.63-0.94) to discriminate who does/does not respond to the CPM-test. Conclusions: These results support using the rs-FC patterns in the left S1-PAG as a marker for predicting CPM-test response, which may aid in treatment individualization in FM patients.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.112-119
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• 2023

Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.

• Korean Chemical Engineering Research
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• v.61 no.1
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• pp.26-31
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• 2023

For durability improvement of polymer electrolyte membrane fuel cell (PEMFC) polymer membrane, accelerated durability evaluation methods that can evaluate durability in a short time have been researched and developed. However, the lifespan of fuel cells for large commercial vehicles such as trucks and buses is more than three times that of passenger cars, and the chemical accelerated stress test (AST) time is also longer, reaching 1,500 hours or more. Therefore, in this study, as a method to evaluate the chemical durability of a membrane within a short time, it was examined whether the durability could be predicted by the pristine membrane characteristics. Hydrogen crossover current density (HCCD) and short resistance (SR) were estimated as initial characteristics, and AST time was predicted through the Fenton experiment, which was possible as an out-of-cell experiment for 3 hours. As the HCCD and fluoride ion emission concentration increased, the AST time tended to be linearly shortened, but there was a deviation (R² ≒0.65). When the SR decreased, the AST time showed a linear increase, and the accuracy was high (R² =0.93), so the AST time could be predicted with the initial SR of the membrane.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.1
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• pp.9-18
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• 2023

Predicting the compressive strength of high-performance concrete (HPC) is challenging because of the use of additional cementitious materials; thus, the development of improved predictive models is essential. The purpose of this study was to develop an HPC compressive-strength prediction model using an ensemble machine-learning method of combined bagging and stacking techniques. The result is a new ensemble technique that integrates the existing ensemble methods of bagging and stacking to solve the problems of a single machine-learning model and improve the prediction performance of the model. The nonlinear regression, support vector machine, artificial neural network, and Gaussian process regression approaches were used as single machine-learning methods and bagging and stacking techniques as ensemble machine-learning methods. As a result, the model of the proposed method showed improved accuracy results compared with single machine-learning models, an individual bagging technique model, and a stacking technique model. This was confirmed through a comparison of four representative performance indicators, verifying the effectiveness of the method.