• Journal of the Korean neurological association
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• v.35 no.1
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• pp.8-15
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• 2017

Near-infrared spectroscopy (NIRS), a noninvasive optical method, utilizes the characteristic absorption spectra of hemoglobin in the near-infrared range to provide information on cerebral hemodynamic changes in various clinical situations. NIRS monitoring have been used mainly to detect reduced perfusion of the brain during orthostatic stress for three common forms of orthostatic intolerance (OI); orthostatic hypotension, neurally mediated syncope, and postural orthostatic tachycardia syndrome. Autonomic function testing is an important diagnostic test to assess their autonomic nervous systems for patients with symptom of OI. However, these techniques cannot measure dynamic changes in cerebral blood flow. There are many experimentations about study of NIRS to reveal the pathophysiology of patients with OI. Research using NIRS in other neurologic diseases (stroke, epilepsy and migraine) are ongoing. NIRS have been experimentally used in all stages of stroke and may complement the established diagnostic and monitoring tools. NIRS also provide pathophysiological approach during rehabilitation and secondary prevention of stroke. The hemodynamic response to seizure has long been a topic for discussion in association with the neuronal damage resulting from convulsion. One critical issue when unpredictable events are to be detected is how continuous NIRS data are analyzed. Besides, NIRS studies targeting pathophysiological aspects of migraine may contribute to a deeper understanding of mechanisms relating to aura of migraine. NIRS monitoring may play an important role to trend regional hemodynamic distribution of flow in real time and also highlights the pathophysiology and management of not only patients with OI symptoms but also those with various neurologic diseases.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.34-39
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• 2018

Along with the development of ICT technology, wearable devices of various sizes and shapes have been developed. In addition, performance and specifications are rebuilt with IOT fusion products so that they can connect with the current smartphone. This is one of the general-purpose technologies of the 4th industrial revolution, which is spot-lighted with technology that changes the quality and environment of our lives. Along with this, as new technology products combining health care technology increases, various functions are provided to users who need it. Wearable technology is ongoing trend of technology development. It also sells products developed as products in the form of smart watches. At present, various related products are made in various ways, and it is recommended to use the Arduino processor in accordance with the application. In this study, we developed wearable physical activity monitoring system using open source hardware based TinyDuino. TinyDuino is an ultra-compact Arduino compatible board made on the basis of Atmega process Board, and it can be programmed in open source integrated development environment(named Sketch). The physical activity monitoring system of the welfare body can be said to be a great advantage, as a smart u-Healthcare system that can perform daily health management.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.173-177
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• 2009

With the advent of light-weight daily physiological signal monitoring sensors, intelligent inference and analysis method for physiological signal monitoring application, commercialized products and services are released. However, practical constraints still remain for daily physiological signal monitoring. Most devices provide rough health check function and analyze with randomly sampled measurements. In this work, we propose the probabilistic modeling of physiological signal analysis. This model represent the relationship between previous user measurement (history), other group`s type, model and current observation. From the experiment, we found that the personalized analysis with long term regular data shows reliable result and reduces the analyzing errors. In addition, participants agree that the personalized analysis shows reliable and adaptive information than other standard analysis method.

• Composites Research
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• v.28 no.3
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• pp.75-80
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• 2015

Poly(vinylidene fluoride-trifluoroethylene; P(VDF-TrFE)) is one of the most promising electroactive polymers with numerous application potentials in many fields of industry. Because of its good electro-mechanical properties P(VDF-TrFE) has been used for a number of sensors and actuators and also can be used for monitoring composite structure behaviors as a sensor. Three different ways (Electrical poling, annealing-cooling, and pressing) to enhance ${\beta}$-phase of P(VDF-TrFE) film were carried out. A microscopic analysis was conducted using X-ray diffraction to investigate the effect of such treatments on piezoelectric properties of P(VDF-TrFE) film. From the results, poling, annealing-cooling, and pressing were all effective to enhance ${\beta}$ crystallinity of P(VDF-TrFE) film and the maximum increase rate was 62.80% from 45.29% of the control group.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.12
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• pp.1238-1244
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• 2009

This work proposes a GUI-type on-line diagnostic program using SIMULINK and Fuzzy-Neuro algorithms for a helicopter turboshaft engine. During development of the diagnostic program, a look-up table type base performance module for reducing computer calculating time and a signal generation module for simulating real time performance data are used. This program is composed of the on-line condition monitoring program to monitor on-line measuring performance condition, the fuzzy inference system to isolate the faults from measuring data and the neural network to quantify the isolated faults. The reliability and capability of the proposed on-line diagnostic program were confirmed through application to the helicopter engine health monitoring.

• Journal of environmental and Sanitary engineering
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• v.24 no.2
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• pp.17-30
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• 2009

In Iksan city, there have been a lot of complaints caused by offensive odor from residents living near the public environmental infrastructures and the Iksan industrial complex. To solve these problems, it is important to know the present condition of odor pollution level in these areas, the emission characteristics of malodorous gases in temporal and spatial variations in addition to meteorological components, and the facilities of major sources emitting malodorous compounds. The objectives of this study is to make the odor monitoring network for 20 people who lived and worked in areas where the environmental infrastructures and the Iksan industrial complex are located and their neighboring areas for six months from June 1st to October 31st in 2008 in Iksan and to monitor the temporal and regional frequency and characteristics of odor intensity using direct olfactory methods. As a result of odor monitoring, the highest frequency of sensed odor per month and 20 people for six months was found to be 107 in July, followed by 84 in September, 80 in August, 54 in June, 38 in October, respectively. Odor intensity trend showed a regional trend in the decreasing order of Dongsan-dong, Busong-dong, and Palbong-dong. Odor was widely perceived from night through next morning and considered as the sense of excreta, chemicals, sewage, compost, waste, etc. When high odor intensity was sensed, there were constant meteorological characteristics: relative humidity was 80~90%, wind speed was less than 0.5~1 m/sec, and main wind directions were from the east, the southeast, and the south.

• Smart Structures and Systems
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• v.6 no.3
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• pp.197-209
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• 2010

The structural state of a bridge is currently examined by visual inspection or by wired sensor techniques, which are relatively expensive, vulnerable to inclement conditions, and time consuming to undertake. In contrast, wireless sensor networks are easy to deploy and flexible in application so that the network can adjust to the individual structure. Different sensing techniques have been used with such networks, but the acoustic emission technique has rarely been utilized. With the use of acoustic emission (AE) techniques it is possible to detect internal structural damage, from cracks propagating during the routine use of a structure, e.g. breakage of prestressing wires. To date, AE data analysis techniques are not appropriate for the requirements of a wireless network due to the very exact time synchronization needed between multiple sensors, and power consumption issues. To unleash the power of the acoustic emission technique on large, extended structures, recording and local analysis techniques need better algorithms to handle and reduce the immense amount of data generated. Preliminary results from utilizing a new concept called Acoustic Emission Array Processing to locally reduce data to information are presented. Results show that the azimuthal location of a seismic source can be successfully identified, using an array of six to eight poor-quality AE sensors arranged in a circular array approximately 200 mm in diameter. AE beamforming only requires very fine time synchronization of the sensors within a single array, relative timing between sensors of $1{\mu}s$ can easily be performed by a single Mote servicing the array. The method concentrates the essence of six to eight extended waveforms into a single value to be sent through the wireless network, resulting in power savings by avoiding extended radio transmission.

• Korean Journal of Environmental Agriculture
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• v.42 no.3
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• pp.193-202
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• 2023

Residue monitoring of propiconazole (PCZ) in cabbage, shallot, and spinach was conducted under multi-trial greenhouse conditions. This study aimed to understand the fate of the applied fungicide in these vegetables. Furthermore, the associated health risk of PCZ in leafy vegetables was assessed through dietary risk assessment. Commercially available PCZ (22% suspension concentrate) was administered thrice according to the OECD fungicide application interval guideline. The plant samples were extracted using a slightly modified QuEChERS technique and analyzed using gas chromatography-tandem mass spectrometry. The average PCZ recovery was between 84.5% and 117.6%, with a <5% coefficient of variance. The dissipation of PCZ residue in cabbage, shallot, and spinach after 14 days was 96%, 90%, and 99%, respectively, with half-lives of <5 days. Meanwhile, dietary risk assessments of PCZ residues in the studied vegetables using the risk quotient (RQ) were significant < 100 (RQ < 100). Thus, the population groups considered in this study were not at substantial risk from consuming leafy vegetables sprayed with PCZ following critical, good agricultural practices.

• Biomedical Science Letters
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• v.28 no.4
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• pp.334-339
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• 2022

African swine fever virus (ASFV) is a highly contagious and lethal pathogen that poses a threat to the global pork industry. The World Organization for Animal Health (WOAH) has placed strict surveillance measures for ASFV. The possibility of long-term survival of ASFV in raw meat or undercooked pork has been reported. Accordingly, the problem of secondary infection in food waste from households or waste disposal facilities has emerged, raising the need for ASFV monitoring of food waste. However, most of the previously reported ASFV gene detection methods are focused on clinical monitoring of pigs. There are very few cases in which their application in waste has been verified. Since ASFV diagnosis requires rapid monitoring and immediate action, loop-mediated isothermal amplification (LAMP) may be suitable, but this requires conformity assessment for LAMP to be used as a diagnostic technique. In this study, six LAMP methods were evaluated, and two methods (kit and manual) were recommended for use in diagnosing ASFV in food waste.

• Smart Structures and Systems
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• v.6 no.2
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• pp.115-133
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• 2010

A modal filter is a tool used to extract the modal coordinates of each individual mode from a system's output. This is achieved by mapping the response vector from the physical space to the modal space. It decomposes the system's responses into modal coordinates, and thus, on the output of the filter, the frequency response with only one peak corresponding to the natural frequency to which the filter was tuned can be obtained. As was shown in the paper (Deraemecker and Preumont 2006), structural modification (e.g. a drop in stiffness or mass due to damage) causes the appearance of spurious peaks on the output of the modal filter. A modal filter is, therefore, a great indicator of damage detection, with such advantages as low computational effort due to data reduction, ease of automation and lack of sensitivity to environmental changes. This paper presents the application of modal filters for the detection of stiffness changes. Two experiments were conducted: the first one using the simulation data obtained from the numerical 7DOF model, and the second one on the experimental data from a laboratory stand in 4 states of damage.