• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.837-839
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• 2012

When the for occurred, the driver does not get the vision is has difficult on driving. In this case, the probability of occurrence of accidents are very high level. To reduce accidents, this system provide drivers with the safety of ensure to measures that a service inform current situation. in this paper, the crash occur in fog to prevent accident using vehicle safety system to give a alarm and control. The proposed system is installed on the outside of the vehicle, humidity, and ambient light sensors inside the car from the information collected by the system controller for the detection of fog conditions using video equipment and then finally the fog occurs if you do not get the driver's field of events is causing the system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.81-87
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• 2016

With the rapid growth of the up-to-date smartphone and wireless network technologies, huge and various types of smart applications using these technologies are actively developed recently. Especially, multiplex types of smart applications using smartphone are developed and diffused with the rapid development of the ubiquitous sensor network technology using various sensors and the mobile computing technology that enables us to get network services at any time in any places. In this paper, we design a smart application that can accurately diagnose and process the current state of the local environment, objects, and persons remotely based on the context information such as local ecology, circumstances, medical or healthcare records and realtime sound or motion pictures using up-to-date samrtphone technology on the USN based mobile computing environment.

• Journal of KIISE
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• v.43 no.5
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• pp.531-540
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• 2016

Development of various sensors attached to mobile and wearable devices has led to increasing recognition of current context-based service to the user. In this study, we proposed a probabilistic model for recognizing user's food intake context, which can occur in a great variety of contexts. The model uses low-level sensor data from mobile and wrist-wearable devices that can be widely available in daily life. To cope with innate complexity and fuzziness in high-level activities like food intake, a context model represents the relevant contexts systematically based on 4 components of activity theory and 5 W's, and tree-structured Bayesian network recognizes the probabilistic state. To verify the proposed method, we collected 383 minutes of data from 4 people in a week and found that the proposed method outperforms the conventional machine learning methods in accuracy (93.21%). Also, we conducted a scenario-based test and investigated the effect contribution of individual components for recognition.

• The Korean Journal of Physiology and Pharmacology
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• v.21 no.4
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• pp.415-421
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• 2017

We investigated the inhibitory effect of escitalopram, a selective serotonin reuptake inhibitor (SSRI), on voltage-dependent $K^+$ (Kv) channels in freshly separated from rabbit coronary arterial smooth muscle cells. The application of escitalopram rapidly inhibited vascular Kv channels. Kv currents were progressively inhibited by an increase in the concentrations of escitalopram, suggesting that escitalopram inhibited vascular Kv currents in a concentration-dependent manner. The $IC_{50}$ value and Hill coefficient for escitalopram-induced inhibition of Kv channels were $9.54{\pm}1.33{\mu}M$ and $0.75{\pm}0.10$, respectively. Addition of escitalopram did not alter the steady-state activation and inactivation curves, suggesting that the voltage sensors of the channels were not affected. Pretreatment with inhibitors of Kv1.5 and/or Kv2.1 did not affect the inhibitory action of escitalopram on vascular Kv channels. From these results, we concluded that escitalopram decreased the vascular Kv current in a concentration-dependent manner, independent of serotonin reuptake inhibition.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.3
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• pp.413-418
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• 2018

In this paper, we describe the development of a non-enzymatic glucose sensor based on copper nanocubes(Cu NCs) electroplated laser induced graphene(LIG) electrodes which can detect a certain range of glucose concentrations. $CO_2$ laser equipment was used to form LIG electrodes on the PI film. This fabrication method allows easy control of the LIG electrode size and shape. The Cu NCs were electrochemically deposited on the LIG electrodes to improve electron transfer rates and thus enhancing electrocatalytic reaction with glucose. The average sheet resistances before and after electroplating were $15.6{\Omega}/{\Box}$ and $19.6{\Omega}/{\Box}$, respectively, which confirmed that copper nanocubes were formed on the laser induced graphene electrodes. The prepared electrode was used to measure the current according to glucose concentration using an electrochemical method. The LIG electrodes with Cu NCs demonstrated a high degree of sensitivity ($1643.31{\mu}A/mM{\cdot}cm^2$), good stability with a linear response to glucose ranging from 0.05 mM to 1 mM concentration, and a limit of detection of 0.05 mM. In order to verify that these electrodes can be used as flexible devices, the electrodes were bent to $30^{\circ}$, $90^{\circ}$, and $180^{\circ}$ and cyclic voltammetry measurements were taken while the electrodes were bent. The measured data showed that the peak voltage was almost constant at 0.42 V and the signal was stable even in the flexed condition. Therefore, it is concluded that these electrodes can be used in flexible sensors for detecting glucose in the physiological sample like saliva, tear or sweat.

• Journal of Sensor Science and Technology
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• v.26 no.1
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• pp.15-23
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• 2017

In this study, bioelectrical impedance analysis, which has been used to assess an alteration in intracellular fluid (ICF) of the body, was applied to detect intravenous infiltration. The experimental results are described as follows. Firstly, when infiltration occurred, the resistance gradually decreased with time and frequency i.e., the resistance decreased with increasing time, proportional to the amount of infiltrated intravenous (IV) solution. At each frequency, the resistance gradually decreased with time, indicating the IV solution (also blood) accumulated in the extracellular fluid (ECF) (including interstitial fluid). Secondly, the resistance ratio started to increase at infiltration, showing the highest value after 1.4 min of infiltration, and gradually decreased thereafter. Thirdly, the impedance ($Z_C$) of cell membrane decreased significantly (especially at 50 kHz) during infiltration and gradually decreased thereafter. Fourthly, Cole-Cole plot indicated that the positions of (R, $X_C$) shifted toward left owing to infiltration, reflecting the IV solution accumulated in the ECF. The resistance ($R_0$) at zero frequency decreased continuously over time, indicating that it is a vital impedance parameter capable of detecting early infiltration during IV infusion. Finally, the mechanism of the current flowing through the ECF, cell membrane, and ICF in the subcutaneous tissues was analyzed as a function of time before and after infiltration, using an equivalent circuit model of the human cell. In conclusion, it was confirmed that the infiltration could be detected early using these impedance parameters during the infusion of IV solution.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.5
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• pp.384-390
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• 2016

It is important to have a pipeline leak-detection system that determines the presence of a leak and quickly identifies its location. Current leak detection methods use a acoustic emission sensors, microphone arrays, and camera images. Recently, many researchers have been focusing on using cameras for detecting leaks. The advantage of this method is that it can survey a wide area and monitor a pipeline over a long distance. However, conventional methods using camera monitoring are unable to target an exact leak location. In this paper, we propose a method of detecting leak locations using leak-detection results combined with multi-frame analysis. The proposed method is verified by experiment.

• Safety and Health at Work
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• v.7 no.4
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• pp.347-353
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• 2016

Background: This study aimed to investigate the relation between key strike forces and musculoskeletal symptoms (MSS). Moreover, this study presents a key strike force measurement method to be used in a workplace setting. The correlation between key strike force characteristics and MSS was previously studied, but the measurement methods used either a single-key switch or force platforms applied under the keyboard. Most of the studies were conducted in a laboratory setting. The uniqueness of measurement methods in the current study is their ability to measure forces applied to a specific key in a workplace setting and to provide more information about specific key strike forces during typing. Methods: Twenty-four healthy computer workers were recruited for the study. The demographic questionnaire, and self-reported questionnaires for psychosocial status (General Nordic Questionnaire for Psychological and Social Factors at Work) and for detecting MSS were filled up, which later helped in dividing the participants into two groups (12 participants with pain and 12 without pain). Participants typed a predetermined text that utilized the instrumented keys multiple times. The dynamic forces applied to the keys were recorded and collected, using four thin and flexible force sensors attached to the preselected keys according to their location. Results: The results demonstrated that participants with high levels of MSS, specifically in the back and neck, in the last year exerted significantly higher key strike forces than those with lower levels of symptoms (p < 0.005). Conclusion: The key strike force exerted while typing on a keyboard may be a risk factor for MSS, and should therefore be considered in ergonomic evaluations and interventional programs.

• Journal of Sensor Science and Technology
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• v.23 no.6
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• pp.368-376
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• 2014

In order to measure the segmental impedance of the body, a bioelectrical impedance measurement system (BIMS) using multi-frequency applying method and two-electrode method was implemented in this study. The BIMS was composed of constant current source, automatic gain control, and multi-frequency generation units. Three experiments were performed using the BIMS and a commercial impedance analyzer (CIA). First, in order to evaluate the performance of the BIMS, four RC circuits connected with a resistor and capacitor in serial and/or parallel were composed. Bioelectrical impedance (BI) was measured by applying multi-frequencies -5, 10, 50, 100, 150, 200, 300, 400, and 500 KHz - to each circuit. BI values measured by the BIMS were in good agreement with those obtained by the CIA for four RC circuits. Second, after measuring BI at each frequency by applying multi-frequency to the left and right forearm and the popliteal region of the body, BI values measured by the BIMS were compared to those acquired by the CIA. Third, when the distance between electrodes was changed to 1, 3, 5, 7, 9, 11, 13, and 15 cm, BI by the BIMS was also compared to BI from the CIA. In addition, BI of extracellular fluid (ECF) was measured at each frequency ranging from 10 to 500 KHz. BI of intracellular fluid (ICF) was calculated by subtracting BI of ECF measured at 500 kHZ from BI measured at seven frequencies ranging from 50 to 500 KHz. BI of ICF and ECF decreased as the frequency increased. BI of ICF sharply decreased at frequencies above 300 KHz.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.1
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• pp.57-62
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• 2017

The purpose of this study is to develop a method for diagnosing the degree of gradual degradation of a reciprocating pump caused by continuous use as a water supply pump in a nuclear power plant. Normally, the progress of such degradation is too slow to be noticed. Hence, it is difficult to determine the degree of degradation using the existing diagnostic methods. In this paper, we propose a new method by which the normal state and the degraded state of the pump can be differentiated, so that the degree of degradation can be identified. First, an emulator was developed using FPGA by providing the parameters of the pump under normal state, so that the emulator generates the information of the pump in the healthy state. Then, by comparing this information with the parameters received from various output sensors of the emulator during the current state, it is possible to identify and measure the degree of gradual degradation. This paper presents some of the results obtained during the development process, and results that show how the emulator operates, by comparing the data collected from an actual pump.