• Journal of Aquaculture
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• v.12 no.3
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• pp.247-254
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• 1999

Changes of oxygen consumption of Nile tilapia in relation to different body sizes(average body weight 4 g, 40 g, 120 g and 400 g) and water temperatures ($20^{\circ}C$, $25^{\circ}C$ and $30^{\circ}C$) were investigated by a continuous oxygen monitoring system. Mean oxygen consumption of 4 g, 40 g, 120 g and 400 g Nile tilapia at $20^{\circ}C$ were 318.8, 214.9, 84.1 and 69.4 mg $O_2$/kg fish/hr and that at $25^{\circ}C$ were 435.2, 345.9, 151.5 and 115.9 mg $O_2$/kg fish/hr, and that at $30^{\circ}C$ were 611.1, 538.4, 320.8, and 236.0 mg $O_2$/kg fish/hr, respectively. Oxygen consumption per unit body weight tended to decrease exponentially at all temperatures (P<0.05) as body weigth of the fish increased. Oxygen consumption of this fish at $25^{\circ}C$ was $1.61\pm0.18$ times higher than that at $20^{\circ}C$ and oxygen consumption at $30^{\circ}C$ was $1.53\pm0.27$ times higher than that at $25^{\circ}C$. Oxygen consumption per unit body weight linearly increased with the water temperature increased. Also, oxygen consumption of this fish during day time was higher than that during night time at 12L:12D day light condition. The differences between maximum and minimum daily oxygen consumption of this fish increased with the water temperature increased.

• IEMEK Journal of Embedded Systems and Applications
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• v.10 no.4
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• pp.213-219
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• 2015

Real-time energy monitoring systems is a demand-response system which is reported to be effective in saving energy up to 12%. Real-time energy monitoring system is commonly composed of smart-plugs which sense how much electrical power is consumed and IHD(In-Home Display device) which displays power consumption patterns. Even though the monitoring system is effective, users should themselves match which smart plus is connected to which appliance. In order to make the matching work to be automatic, the monitoring system need to have appliance identification algorithm, and some works have made under the name of NILM(Non-Intrusive Load Monitoring). This paper proposed an algorithm which utilizes multiple classifiers to improve accuracy of appliance identification. The algorithm proposes to understand each classifiers performance, that is, when a classifier make a result how much the result is reliable, and utilize it in choosing the final result among result candidates from many classifiers. By using the proposed algorithm this paper make 4.5% of improved accuracy with respect to using single best classifier, and 2.9% of improved accuracy with respect to other method using multiple classifiers, so called CDM(Commitee Decision Mechanism) method.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.5
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• pp.480-485
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• 2013

Enhancing energy efficiency of machine tools causes substantial impacts on the manufacturing industries, to cope with the competitive introduction of the total energy management strategies. Real-time energy monitoring is essential to identify energy consumption patterns of the machine tools and correlate them with the energy management strategy. Integrated analysis of machine tool's operation status and the corresponding energy usage is most important to accurately evaluate the energy efficiency under the various machining process environments. This paper proposes a system architecture to realize the online energy monitoring system and the embedded energy monitoring approach interconnected with the CNC kernel. The shop-floor operation management system is presented to integrate the proposed online energy monitoring approach.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.5
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• pp.702-712
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• 2016

A wrist watch type wearable cardiovascular monitoring device is proposed for continuous and convenient monitoring of the patient's cardiovascular system. For comprehensive monitoring of the patient's cardiovascular system, the concurrent electrocardiogram (ECG) and arterial pulse wave (APW) sensor front-end are fabricated in $0.18{\mu}m$ CMOS technology. The ECG sensor frontend achieves 84.6-dB CMRR and $2.3-{\mu}Vrms$-input referred noise with $30-{\mu}W$ power consumption. The APW sensor front-end achieves $3.2-V/{\Omega}$ sensitivity with accurate bio-impedance measurement lesser than 1% error, consuming only $984-{\mu}W$. The ECG and APW sensor front-end is combined with power management unit, micro controller unit (MCU), display and Bluetooth transceiver so that concurrently measured ECG and APW can be transmitted into smartphone, showing patient's cardiovascular state in real time. In order to verify operation of the cardiovascular monitoring system, cardiovascular indicator is extracted from the healthy volunteer. As a result, 5.74 m/second-pulse wave velocity (PWV), 79.1 beats/minute-heart rate (HR) and positive slope of b-d peak-accelerated arterial pulse wave (AAPW) are achieved, showing the volunteer's healthy cardiovascular state.

• Smart Structures and Systems
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• v.6 no.8
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• pp.939-951
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• 2010

A low-cost wireless sensor network (WSN) solution with highly expandable super and simple nodes was developed. The super node was designed as a sensing unit as well as a receiving terminal with low energy consumption. The simple node was designed to serve as a cheaper alternative for large-scale deployment. A 12-bit ADC inputs and DAC outputs were reserved for sensor boards to ease the sensing integration. Vibration and thermal field tests of the Chi-Lu Bridge were conducted to evaluate the WSN's performance. Integral acceleration, temperature and tilt sensing modules were constructed to simplify the task of long-term environmental monitoring on this bridge, while a star topology was used to avoid collisions and reduce power consumption. We showed that, given sufficient power and additional power amplifier, the WSN can successfully be active for more than 7 days and satisfy the half bridge 120-meter transmission requirement. The time and frequency responses of cables shocked by external force and temperature variations around cables in one day were recorded and analyzed. Finally, guidelines on power characterization of the WSN platform and selection of acceleration sensors for structural health monitoring applications were given.

• Biomedical Science Letters
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• v.30 no.1
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• pp.24-31
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• 2024

Mercury is a chemical pollutant widely present in the environment. Humans are generally exposed to mercury in the form of organic Hg (methylmercury) through the consumption of seafood. Koreans enjoy eating fish therefore blood mercury concentration is usually higher than in developed countries. By investigating blood mercury concentration according to the frequency of seafood consumption and sociodemographic factors, we aimed to identify recent trends in blood mercury concentration in Korean adults. This study was conducted using KoNEHS cycle 4 (2018~2020) from the National Institute Environmental Research Survey. The geometric mean concentration of blood mercury of the subjects was 2.959 (±1.018) ㎍/L, which was significantly higher in men than in women. It was observed that as the frequency of fish and shellfish consumption increased, the blood mercury concentration increased. In adjusted logistic regression, fish consumption was associated with 36.7% increased risk of blood mercury levels [Odds ratio, 1.367; 95% confidence interval (CI), 1.246~1.500], and shellfish consumption was associated with 26.5% increased risk of blood mercury levels [Odds ratio, 1.265; 95% confidence interval (CI), 1.134~1.410]. Blood mercury concentration was also found to increase as the socioeconomic level increased. In conclusion, the geometric mean concentration of blood mercury was increased compared to the one in the 3rd KoNEHS (2015~2017) and seafood consumption and socioeconomic level were still significantly associated with increasing blood mercury concentration in Korea. Therefore, it is necessary to encourage healthy seafood consumption habits and conduct continuous monitoring considering various factors to reduce blood mercury levels.

• International Journal of Advanced Culture Technology
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• v.2 no.2
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• pp.11-14
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• 2014

In the smart grid, it will be possible to communicate with the consumers for the purposes of monitoring and controlling their power consumption without disturbing their business or comfort. This will bring easier administration capabilities for the utilities. On the other hand, consumers will require more advanced home automation tools which can be implemented by using advanced sensor technologies. For instance, consumers may need to adapt their consumption according to the dynamically varying electricity prices which necessitates home automation tools. This paper tries to combine neural network and nonlinear autoregressive with exogenous variable (NARX) class for next week electric load forecasting. The suitability of the proposed approach is illustrated through an application to electric load consumption data. The suggested system provides a useful and suitable tool especially for the load forecasting.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.441-443
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• 2002

This paper presents a window-based load management system (LMS) package developed as a decision-making tool in the competitive electricity market. The presented LMS package can help the users to monitor system load patterns, analyze their past energy consumption and schedule the future energy consumption. The LMS package can also provide the effective information on real-time energy/cost monitoring, consumed energy/cost analysis, demand schedule and cost-savings. The developed LMS package can be used to establish the optimal demand schedule and consumption strategy.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.2
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• pp.50-54
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• 2009

In this paper, we address a novel system-level power management technique which is specifically targeted for an ARM 11 MPCore system. Our proposed solution is a DPM technique which includes process monitoring, real time power analysis, and policy application to reduce the power consumption while meeting the performance requirement. One of the main contributions of this paper is that we systematically infer QoS requirements of processes without getting any additional information from the application. When multiple processes are running under various user level policies, priorities of the policy application are determined in such a way that the overall system performance is maintained while power consumption is effectively managed. Experimental results show that our DPM technique is very effective in reducing power consumption without violating system's QoS requirements.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.5
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• pp.3323-3329
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• 2013

Background: The Global Adult Tobacco Survey (GATS) was carried out for systematically monitoring tobacco use and for tracking key tobacco control indicators. Materials and Methods: A total of 70,802 households, including 42,647 in rural areas and 28,155 in urban areas, were covered with a three stage sampling design. Data were collected on sociodemographic characteristics, knowledge, attitude and practices of tobacco consumption.Results: GATS-India highlighted that total tobacco use among its residents is overall 34.6%, varying for males (47.9%) and females (20.7%). The rural areas of the country exhibit comparatively higher prevalence rates (38.4%) in comparison to urban areas (25.3%). Overall, Khaini, a smokeless tobacco product (12.0%), is the most popular form of tobacco use among males and females, followed by bidi smoking (9.0%). Conclusion: Results of GATS data can be used as baseline for evaluation of new tobacco control approaches in India integrating culturally acceptable and cost effective measures.