• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.11
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• pp.3003-3013
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• 1995

The characteristics of the flow field in the tangentially fired furnace are presented. Experiments are conducted in the simplified cold type isothermal flow model. In the measurement of flow field, a hot wire anemometer is used. The hot wire was calibrated by lookup table method. The mean velocity field and turbulence characteristics are showed with changing the nozzle angle. In the center of the model, the low speed, unstable flow region is formed. The size and position of these regions are varied with changing the nozzle angle. It can be used as fundamental data in the design of the large furnace. From the experimental results, various turbulent characteristics of swirling flow field is obtained. And the entrainment mechanism of the jet flow field is described from the distribution of the skewness and the flatness. It can be used the raw data of approximate calculation and turbulent modelling.

• Korean journal of food and cookery science
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• v.10 no.1
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• pp.51-56
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• 1994

Conventional Doenjang, improved Doenjang prepared with Asp. oryzae were made to investigate the changes in the lipid content, and the carbonyl compounds during fermentation. Total lipid contents of conventional Doenjang increased slowly during fermentation, and that of the improved Doenjang increased at first, but showed sharp decrease at moment and then increased. Triglyceride contents of all samples decreased remarkedly during fermentation. Conversely, free acid contents increased. From the result of quantitative analysis of fatty acid by gas chromatography, saturated fatty acid ratio of total lipid in conventional Doenjang increased at early stages and then decreased, but unsaturated fatty acid ratio showed the reverse phenomenon. Saturated fatty acid in improved Doenjang increased during the fermentation but unsaturated fatty acid decreased by degrees. The concentration of total and monocarbonyl compounds in the fermented Doenjang were comparably higher than that found in raw Boenjang. Sensory evaluation revealed that off flavor had a negative effect on overall eating quality of Doenjang and total carbonyl content was related to the off flavor.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.1
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• pp.25-30
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• 2017

Currently, most of the grain sorter uses CCD optic camera to find defective products. The aim of this paper is to use the CCD camera, and aim for improving the sorting power of the grain separator by using NIR(Near Infrared Radiation) sensor based on moisture content measurement algorithm. We intend to develop a system to develop an NFC imaging system in real time by developing an NIR imaging system and developing the grain sorter system that is considered to be defective in real time by checking the internal moisture content of the raw material in the real time.

• Smart Structures and Systems
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• v.23 no.5
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• pp.507-520
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• 2019

In the structural health monitoring field, damage detection has been commonly carried out based on the structural model and the engineering features related to the model. However, the extracted features are often subjected to various errors, which makes the pattern recognition for damage detection still challenging. In this study, an automated damage identification method is presented for hanger cables in a tied-arch bridge using a convolutional neural network (CNN). Raw measurement data for Fourier amplitude spectra (FAS) of acceleration responses are used without a complex data pre-processing for modal identification. A CNN is a kind of deep neural network that typically consists of convolution, pooling, and fully-connected layers. A numerical simulation study was performed for multiple damage detection in the hangers using ambient wind vibration data on the bridge deck. The results show that the current CNN using FAS data performs better under various damage states than the CNN using time-history data and the traditional neural network using FAS. Robustness of the present CNN has been proven under various observational noise levels and wind speeds.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.257-268
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• 2022

When there is a missing value in the raw data, if ignore the missing values and proceed with the analysis, the accuracy decrease due to the decrease in the number of sample. The method of imputation and analyzing patterns and significant values can compensate for the problem of lower analysis quality and analysis accuracy as a result of bias rather than simply removing missing values. In this study, we proposed to study irregular data patterns and missing processing methods of data using machine learning techniques for the study of correction of missing values. we would like to propose a plan to replace the missing with data from a similar past point in time by finding the situation at the time when the missing data occurred. Unlike previous studies, data correction techniques present new algorithms using DNN and KNN-MLE techniques. As a result of the performance evaluation, the ANAE measurement value compared to the existing missing section correction algorithm confirmed a performance improvement of about 0.041 to 0.321.

• The Korean Journal of Food And Nutrition
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• v.35 no.4
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• pp.276-281
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• 2022

Antioxidant activities and α-glucosidase inhibitory activities of Taraxacum officinale solvent fractions were measured. Extraction yields (relative to raw material) of 50% ethanol, hexane, ethyl acetate, butanol, and water were found to be 10.29, 2.61, 5.54, 2.15, and 0.96%, respectively. Polyphenol and flavonoid contents were high in ethyl acetate extract of Taraxacum officinale at 56.88 mg gallic acid/g and 33.27 mg gallic acid/g, respectively. DPPH, hydroxyl radical scavenging activity, and SOD-like activity measurement (IC₅₀%) of Taraxacum officinale 50% ethanol extract, hexane, butanol, ethyl acetate, and water fractions were 22.64, 18.65, 10.29, 20.81, 20.46 mg/mL, 24.68, 10.69, respectively. It was found to be 9.66, 15.81, 13.77 mg/mL, 32.84, 17.09, 12.73, 33.63, and 33.91 mg/mL, and was high in the ethyl acetate layer. Results showed that α-glucosidase inhibitory activities of Taraxacum officinale solvent fraction were 25.75, 15.93, 35.87, 15.96, and 2.88% for 50% ethanol extract, hexane, butanol, ethyl acetate, and water fractions, respectively.

• Journal of Ocean Engineering and Technology
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• v.37 no.1
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• pp.38-48
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• 2023

To maintain the existing systems of ships and introduce autonomous operation technology, it is necessary to improve situational awareness through the sensor fusion of the automatic identification system (AIS) and automatic radar plotting aid (ARPA), which are installed sensors. This study proposes an algorithm for determining whether AIS and ARPA signals are sent to the same ship in real time. To minimize the number of errors caused by the time series and abnormal phenomena of heterogeneous signals, a tracking method based on the combination of the unscented Kalman filter and probabilistic data association filter is performed on ARPA radar signals, and a position prediction method is applied to AIS signals. Especially, the proposed algorithm determines whether the signal is for the same vessel by comparing motion-related components among data of heterogeneous signals to which the corresponding method is applied. Finally, a measurement test is conducted on a training ship. In this process, the proposed algorithm is validated using the AIS and ARPA signal data received by the voyage data recorder for the same ship. In addition, the proposed algorithm is verified by comparing the test results with those obtained from raw data. Therefore, it is recommended to use a sensor fusion algorithm that considers the characteristics of sensors to improve the situational awareness accuracy of existing ship systems.

• Journal of the Korean Society of Safety
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• v.38 no.5
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• pp.43-50
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• 2023

With the advent of industrialization, consumers and end-users demand more reliable products. Meeting these demands requires a comprehensive approach, involving tasks such as market information collection, planning, reliable raw material procurement, accurate reliability design, and prediction, including various reliability tests. Moreover, this encompasses aspects like reliability management during manufacturing, operational maintenance, and systematic failure information collection, interpretation, and feedback. Improving product reliability requires prioritizing it from the initial development stage. Failure mode and effect analysis (FMEA) is a widely used method to increase product reliability. In this study, we reanalyzed using the FMEA method and proposed an improved method. Domestic railways lack an accurate measurement method or system for maintenance, so maintenance decisions rely on the opinions of experienced personnel, based on their experience with past faults. However, the current selection method is flawed as it relies on human experience and memory capacity, which are limited and ineffective. Therefore, in this study, we further specify qualitative contents to systematically accumulate failure modes based on the Failure Modes Table and create a standardized form based on the Master FMEA form to newly systematize it.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.69-80
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• 2024

Currently rebar spacing inspection is carried out by human inspectors who heavily rely on their individual experience, lacking a guarantee of objectivity and accuracy in the inspection process. In addition, if incorrectly placed rebars are identified, the inspector need to correct them. Recently, laser scanning and AR technologies have been widely used because of their merits of measurement accuracy and visualization. This study proposes a technology for rebar spacing inspection and fixing by combining laser scanning and AR technology. First, scan data acquisition of rebar layers is performed and the raw scan data is processed. Second, AR-based visualization and fixing are performed by comparing the design model with the model generated from the scan data. To verify the developed technique, performance comparison test is conducted by comparing with existing drawing-based method in terms of inspection time, error detection rate, cognitive load, and situational awareness ability. It is found from the result of the experiment that the AR-based rebar inspection and fixing technology is faster than the drawing-based method, but there was no significant difference between the two groups in error identification rate, cognitive load, and situational awareness ability. Based on the experimental results, the proposed AR-based rebar spacing inspection and fixing technology is expected to be highly useful throughout the construction industry.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.212-220
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• 2024

When a typhoon or natural disaster occurs, a significant number of orchard fruits fall. This has a great impact on the income of farmers. In this paper, we introduce an AI-based method to enhance low-quality raw images. Specifically, we focus on apple images, which are being used as AI training data. In this paper, we utilize both a basic program and an artificial intelligence model to conduct a general image process that determines the number of apples in an apple tree image. Our objective is to evaluate high and low performance based on the close proximity of the result to the actual number. The artificial intelligence models utilized in this study include the Convolutional Neural Network (CNN), VGG16, and RandomForest models, as well as a model utilizing traditional image processing techniques. The study found that 49 red apple fruits out of a total of 87 were identified in the apple tree image, resulting in a 62% hit rate after the general image process. The VGG16 model identified 61, corresponding to 88%, while the RandomForest model identified 32, corresponding to 83%. The CNN model identified 54, resulting in a 95% confirmation rate. Therefore, we aim to select an artificial intelligence model with outstanding performance and use a real-time object separation method employing artificial function and image processing techniques to identify orchard fruits. This application can notably enhance the income and convenience of orchard farmers.