• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.6
• /
• pp.1037-1044
• /
• 2020

Since radar wind profiler (RWP) provides wind field data with high time and space resolution in all weather conditions, their verification of the accuracy and quality is essential. The simultaneous wind measurement from rawinsonde is commonly used to evaluate wind vectors from RWP. In this study, the simulation algorithm which produces the spectrum and raw time series (I/Q) data from the average values of moments is presented as a step-by-step verification method for the signal processing algorithm. The possibility of the simulation algorithm was also confirmed through comparison with the raw data of LAP-3000. The Doppler power spectrum was generated by assuming the density function of the skew-normal distribution and by using the moment values as the parameter. The simulated spectrum was generated through random numbers. In addition, the coherent averaged I/Q data was generated by random phase and inverse discrete Fourier transform, and raw I/Q data was generated through the Dirichlet distribution.

• The Korean Journal of Applied Statistics
• /
• v.35 no.5
• /
• pp.667-684
• /
• 2022

Gene expression data present the level of mRNA abundance of each gene, and analyses of gene expressions have provided key ideas for understanding the mechanism of diseases and developing new drugs and therapies. Nowadays high-throughput technologies such as DNA microarray and RNA-sequencing enabled the simultaneous measurement of thousands of gene expressions, giving rise to a characteristic of gene expression data known as high dimensionality. Due to the high-dimensionality, learning models to analyze gene expression data are prone to overfitting problems, and to solve this issue, dimension reduction or feature selection techniques are commonly used as a preprocessing step. In particular, we can remove irrelevant and redundant genes and identify important genes using gene selection methods in the preprocessing step. Various gene selection methods have been developed in the context of machine learning so far. In this paper, we intensively review recent works on gene selection methods using machine learning approaches. In addition, the underlying difficulties with current gene selection methods as well as future research directions are discussed.

• Journal of Electrochemical Science and Technology
• /
• v.12 no.2
• /
• pp.173-187
• /
• 2021

In the present research, a simple electrochemical sensor based on a carbon paste electrode (CPE) modified with ZnO-Zn₂SnO₄-SnO₂ and graphene (ZnO-Zn₂SnO₄-SnO₂/Gr/CPE) was developed for the direct, simultaneous and individual electrochemical measurement of Acetaminophen (AC), Caffeine (Caf) and Ascorbic acid (AA). The synthesized nano-materials were investigated using scanning electron microscopy, X-ray Diffraction, Fourier-transform infrared spectroscopy, and electrochemical impedance spectroscopy techniques. Cyclic voltammetry and differential pulse voltammetry were applied for electrochemical investigation ZnO-Zn₂SnO₄-SnO₂/Gr/CPE, and the impact of scan rate and the concentration of H⁺ on the electrode's responses were investigated. The voltammograms showed a linear relationship between the response of the electrode for individual oxidation of AA, AC and, Caf in the range of 0.021-120, 0.018-85.3, and 0.02-97.51 μM with the detection limit of 8.94, 6.66 and 7.09 nM (S/N = 3), respectively. Also, the amperometric technique was applied for the measuring of the target molecules in the range of 0.013-16, 0.008-12 and, 0.01-14 μM for AA, AC and, Caf with the detection limit of 6.28, 3.64 and 3.85 nM, respectively. Besides, the ZnO-Zn₂SnO₄-SnO₂/Gr/CPE shows an excellent selectivity, stability, repeatability, and reproducibility for the determination of AA, AC and, Caf. Finally, the proposed sensor was successfully used to show the amount of AA, AC and, Caf in urine, blood serum samples with recoveries ranging between 95.8% and 104.06%.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.12
• /
• pp.1935-1941
• /
• 2021

In order to develop an algorithm using deep learning, which has been recently applied to various fields, it is necessary to have rich, high-quality learning data. In this paper, we propose an acquisition system for biological signals that simultaneously collects bio-signal data such as optical videos, thermal videos, and voices, which are mainly used in developing deep learning algorithms and useful in derivation of information, and transmit them to the server. To increase the portability of the collector, it was made based on Raspberry Pi, and the collected data is transmitted to the server through the wireless Internet. To enable simultaneous data collection from multiple collectors, an ID for login was assigned to each subject, and this was reflected in the database to facilitate data management. By presenting an example of biological data collection for fatigue measurement, we prove the application of the proposed acquisition system.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2004.03a
• /
• pp.802-806
• /
• 2004

For the protection of the local air quality and the global atmosphere, the emissions of trace species including nitric oxides (NO and NO$_2$) from gas turbines are regulated by local governments and by the International Civil Aviation Organization. In-situ measurements of such species are needed not only for the development of advanced low-emission combustion concepts but also for providing emissions data required for the sound assessment of the effects of the emissions on environment. We have been developing a laser absorption system that has a capability of simultaneous determination of NO and NO$_2$concentrations in the exhaust jets from aero gas turbines. A diode laser operating near 1.8 micrometer is used for the detection of NO while a separated visible tunable diode laser operating near 676 nanometers is used for NO$_2$. The sensitivities at elevated temperature conditions were determined for simulated gas mixtures heated up to 500K in a heated cell of a straight 0.5 m optical path. Sensitivity limits estimated as were 30 ppmv-m and 3.7 ppmv-m for NO and NO$_2$, respectively, at a typical exhaust gas temperature of 800K. Experiments using the simulated exhaust flows have proven that $CO_2$ and $H_2O$ vapor - both major combustion products - do not show any interference in the NO or NO$_2$ measurements. The measurement system has been applied to the NO/NO$_2$ measurements in NO and NO$_2$ doped real combustion gas jets issuing from a rectangular nozzle having 0.4 m optical path. The lower detection limits of the system were considerably decreased by using a multipass optical cell. A pair of off-axis parabola mirrors successfully suppressed the beam steering in the combustion gas jets by centralizing the fluctuating beam in sensor area of the detectors.

• Mass Spectrometry Letters
• /
• v.14 no.3
• /
• pp.91-103
• /
• 2023

As one of the most common mood disorders, numerous studies have shown depression is the main risk factor for non-suicidal self-harm. The pathogenesis of depression is complex, and a comprehensive and rapid measurement of monoamine neurotransmitters and their metabolites will be very helpful in understanding the pathogenesis of depression. Therefore, a rapid and sensitive underivatized liquid chromatography-tandem mass spectrometry method was developed and validated for the simultaneous monitoring of the levels of ten neurotransmitters and their metabolites in rat serum and limbic system and successfully applied to quantify the changes of neurotransmitter levels in chronic unpredictable mild stress-induced rats. The analytes studied were mainly involved in tyrosine metabolism, tryptophan metabolism, and glutamate cycling pathways, which are important in the pathogenesis of depression. It had been verified the method was sensitive and effective, with satisfactory linearity, and met the requirements of biological sample determination. Levels of neurotransmitters in rat serum, hippocampus, amygdala, prefrontal cortex, striatum, and hypothalamus were determined via the method. The results showed serotonin, dopamine, norepinephrine, and their metabolites were decreased, glutamine was increased, and glutamate was disturbed in chronic unpredictable mild stress-induced depression rats. This method provides a new approach to studying the pathogenesis of depression and other neurological disorders.

• Geomechanics and Engineering
• /
• v.36 no.3
• /
• pp.217-229
• /
• 2024

Determining lateral earth pressure coefficient (EPC) K is a classic problem in geotechnical engineering. It is a key parameter for estimating the stresses in backfilled openings. For backfilled openings with rigid and immobile walls, some suggested using the Jaky's at-rest earth pressure coefficient K₀ while other suggested taking the Rankine's active earth pressure coefficient K_a. A single value was proposed for the entire backfilled opening. To better understand the distributions of stresses and K in a backfilled opening, a series of laboratory tests have been conducted. The horizontal and vertical normal stresses at the center and near the wall of the opening were measured. The values of K at the center and near the wall were then calculated with the measured horizontal and vertical normal stresses. The results show that the values of K are close to K_a at the center and close to K₀ near the wall. Furthermore, the experimental results show that the horizontal stress is almost the same at the center and near the wall, indicating a uniform distribution from the center to the wall. It can be estimated by analytical solutions using either K_a or K₀. The vertical stress is higher near the center than near the wall. Its analytical estimation can only be done by using K_a at the center and K₀ near the wall. Finally, the test results were used to calibrate a numerical model of FLAC2D, which was then used to analyze the influence of column size on the stresses and K in the backfilled opening.

• Advances in materials Research
• /
• v.13 no.3
• /
• pp.233-241
• /
• 2024

Quantitative analysis of the Zingiber Officinale sample using subcritical water extraction (SWE) was developed employing High-Performance Liquid Chromatography (HPLC) to bolster the advancement of this innovative green extraction process. This research focuses on three principal ginger bioactive compounds: 6-gingerol, 6-shagoal, and 10-gingerol. Various stages were undertaken to establish the quantitative analysis method, encompassing the optimisation of HPLC operating conditions and the formulation of standard calibration curves, yielding individual compound equations. A robust correlation within the calibration curve was achieved, exhibiting an r² value of 0.9814 and an RSD of 5.00%. A simultaneous, swift, and dependable method was established with an injection time of 20 minutes and an 8-minute delay between injections, in contrast to the previous HPLC analysis requiring a 45-minute injection time for detecting and quantifying all components. Notably, no post-treatment was applied after the SWE process. This advancement allows for potential future online measurement of Zingiber Officinale bioactive compounds extracted using subcritical water extraction through this technology.

• Physical Therapy Rehabilitation Science
• /
• v.13 no.2
• /
• pp.179-186
• /
• 2024

Objective: This study aims to assess the reliability and validity of the new hand-held spirometer as a potential substitute for traditional pulmonary function testing (PFT) devices. Design: Cross-sectional study. Methods: In this study, thirty healthy adults underwent spirometry using both the new hand-held spirometer and the MIR spirometer, which is a standard PFT device. Parameters including peak expiratory flow (PEF), forced expiratory volume in one second (FEV₁), and forced vital capacity (FVC) were measured and analyzed for validity and reliability. Inter-rater reliability and validity were evaluated through 95% limits of agreement (LOA) and intraclass correlation coefficients (ICC). Statistical analyses, including the Bland-Altman plots and the ICC, were utilized to assess agreement between the two devices. Results: The new hand-held spirometer exhibited a good agreement with intra-class coefficient (ICC [2,1]) ranging 0.762 to 0.956 and 95% LOA of -1.94 to 1.80 when compared with MIR. The test-retest reliability of the hand-held spirometer analyzed using - ICC [2,1] demonstrated a good level of consistency (ICC [2,1] =0.849-0.934). Conclusions: In conclusion, the study aimed to assess the potential of the new hand-held spirometer as a viable alternative to traditional PFT devices, with a specific focus on its reliability and validity in spirometric measurements. The new hand-held spirometer exhibited good test-retest reliability across all measured variables, suggesting its potential as a valid and reliable tool for simultaneous PFT measurements.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.17 no.4
• /
• pp.245-254
• /
• 2024

Recently, virtual reality (VR) has been actively used in various fields such as education, healthcare, entertainment, and training by providing immersive experiences. To operate multiple VR content programs without assistants and improve training efficiency, remote control of VR content programs within HMDs is necessary. In this paper, we develop management app for remotely controlling and monitoring multiple HMDs. First, we develop a function for HMD devices to connect to the management app. Second, we develop a function for simultaneously controlling HMD devices. Finally, we develop a function for monitoring HMD devices. In order to verify the developed functions, we measured the simultaneous control time and monitoring time. The measurement results showed that control took an average of 0.15 seconds and monitoring took an average of 0.81 seconds.