• Journal of the Korean Society of Tobacco Science
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• v.22 no.1
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• pp.91-98
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• 2000

This study was carried out to evaluate the uncertainty in the analysis of menthol content from the mentholated cigarette. Menthol in the sample cigarette was extracted with methanol containing an anethole as an internal standard, and then analyzed by gas chromatography. As the sources of uncertainty associated with the analysis of menthol, were the following points tested, such as the weighing of sample, the preparation of extracting solution, the pipetting of extracting solution into the sample, the preparation of standard solution, the precision of GC injections for standard & sample solution, the GC response factor of standard solution, the reproducibility of menthol analysis, and the determination of water content in tobacco, etc. For calculating the uncertainties, type A of uncertainty was evaluated by the statistical analysis of a series of observation, and type B by the information based on supplier's catalogue and/or certificated of calibration. Sources of uncertainty were subsequently included and mathematically combined with the uncertainty arising from the assessment of accuracy to provide the overall uncertainty. It was shown that the main source of uncertainty came from the errors in the reproducibility of menthol and water determination, the purity of menthol reference material in the preparation of standard solution, and the precision of GC injections for sample solution. The errors in sample weighing and volume measurement contributed relatively little to the overall uncertainty. The expanded uncertainty in the mentholated cigarettes, Korean and American brand, at 0.95 level of statistical confidence was $\pm$0.06 and $\pm$0.07 mg/g for a menthol content of 1.89 and 2.32 mg/g, respectively.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.212-222
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• 2021

Multiple waves of COVID-19 highlighted one crucial aspect of this pandemic worldwide that factors affecting the spread of COVID-19 infection are evolving based on various regional and local practices and events. The introduction of vaccines since early 2021 is expected to significantly control and reduce the cases. However, virus mutations and its new variant has challenged these expectations. Several countries, which contained the COVID-19 pandemic successfully in the first wave, failed to repeat the same in the second and third waves. This work focuses on COVID-19 pandemic control and management in Saudi Arabia. This work aims to predict new cases using deep learning using various important factors. The proposed method is called Deep Learning and Dynamic Weighing-based (DLDW) COVID-19 cases prediction method. Special consideration has been given to the evolving factors that are responsible for recent surges in the pandemic. For this purpose, two weights are assigned to data instance which are based on feature importance and dynamic weight-based time. Older data is given fewer weights and vice-versa. Feature selection identifies the factors affecting the rate of new cases evolved over the period. The DLDW method produced 80.39% prediction accuracy, 6.54%, 9.15%, and 7.19% higher than the three other classifiers, Deep learning (DL), Random Forest (RF), and Gradient Boosting Machine (GBM). Further in Saudi Arabia, our study implicitly concluded that lockdowns, vaccination, and self-aware restricted mobility of residents are effective tools in controlling and managing the COVID-19 pandemic.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1976_1977
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• 2009

The number and percentage of people in need of a wheelchair are increasing every year, both manual and power wheelchair users express an interest in monitoring their weight. However, frequent measurements are not possible when relying on hospital scales and models designed for home use are expensive. So the goals of this study became to create a product that's relatively inexpensive, portable, and precise, which means varying little between measurements. Secondary goals were ease of use, compatibility with different kinds of wheelchairs, and accuracy, which means achieving proximity to an actual value and isn't as important when trying to monitor increases or decreases in weight.

• Journal of Industrial Technology
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• v.15
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• pp.83-91
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• 1995

This paper presents the design of a smart A/D conversion interface used for measuring the load of a truck. Since the load-cell sensor to be used is very sensitive for weight variation, the interface board must have the low-drift and the A/D conversion for accuracy. A new integrator and comparator has been developed to reduce the offset voltage and the drift current of operational amplifiers and has been adapted into the interface board. Also, a software algorithm has been developed to obtain the stable and accrurate A/D conversion. This software includes a RS-485 communication program to control the interface, which gives a capability of backing-up the calibration data and transferring control data. The test and evaluation of the designed interface has been shown as having the better performance compared to the other types of existing weighing systems and sensor instruments.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.437-437
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• 2000

It is more difficult to accurately weigh vehicles in motion than to weigh standing vehicles. The difficulties in weighing vehicles result from sensor Limitations as well as dynamic effects induced by vehicle/pavement interactions, This paper presents a method for improving the accuracy of measured axle load information using the so-called adaptive footprint tire model. The total vehicle weight as well as individual axle weight information are obtained experimentally using two piezoelectric sensors. Results are obtained for a light car, mid-site passenger car, and 2 dump trucks with known weight experimental results show that the proposed method using the tire model is accurate.

• Journal of Korean Society for Quality Management
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• v.27 no.2
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• pp.201-217
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• 1999

Industrial Measuring Instrument is a general name of equipments or tools for measuring and weighing. Inaccurate measuring instruments produce inferior goods in spite of excellent experts, good materials and wonderful equipments. Three characteristics are important for measuring instruments: choosing the proper instruments for measuring, using them properly and managing them to keep accuracy and precision. The purpose of this thesis is to develope the management standard for effective control of measuring instruments by analysing the problems and the management conditions of 100 PPM certified companies out of the domestic small and medium manufacturing industry, which steadily carry out quality control.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.821-825
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• 2008

A fuzzy control algorithm is used to weigh alloy metal into electric arc furnace and implemented by using ladder program for programmable logic controller, where weight error and its derivative are used for input variables and vibration amplitude of alloy bin is used for output variable. Proposed fuzzy control algorithm is applied to the plant and results in higher measuring accuracy as well as faster measuring term than conventional on-off control system.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.11 no.1
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• pp.114-122
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• 1997

This paper describes the design and development of a smart digital load cell used forweighing installations. Sice the load cell sensor to be used is very sensitive for weight cariation, the load cell must have the temperature stability, low-drift and the high-resolution of the A/D conversion for accuracy. A new analog circuit which is controlled by one chip micro-processer has been developed to reduce the offset voltage and the drift characteristics of operational amplifiers, and has been adapted into the digital load cell. Also, a software algorithm has been developed to obtain the stable and accurate A/D conversion. This software includes a RS-485 communication program to control the digital load cell, which gives a capability of backing-up the calibration data and transferring control data. The simulation and evaluation of the designed digital load cell has been shown as having the good performance. which will give useful application to the weighing installations as a remote weighing sensor.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.20 no.1
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• pp.1-6
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• 2024

Crud is a corrosion deposit that forms in equipments and piping of nuclear reactor's primary systems. When crud circulates through the reactor's primary system coolant and adheres to the surface of the nuclear fuel cladding tube, it can lead to the Axial Offset Anomaly (AOA) phenomenon. This occurrence is known to potentially reduce the output of a nuclear power plant or to necessitate an early shutdown. Consequently, worldwide nuclear power plants have employed ultrasonic cleaning methods since 2000 to mitigate crud deposition, ensuring stable operation and economic efficiency. This paper details the system configuration of ultrasonic nuclear fuel cleaning equipment, outlining the function of each component. The objective is to contribute to the local domestic production of ultrasonic nuclear fuel cleaning equipment. Additionally, the paper introduces a method for accurately measuring the weight of removed crud, a crucial factor in assessing cleaning effectiveness and providing input data for the BOA code used in core safety evaluations. Accurate measurement of highly radioactive filters containing crud is essential, and weighing them underwater is a common practice. However, the buoyancy effect during underwater weighing may lead to an overestimation of the collected crud's weight. To address this issue, the paper proposes a formula correcting for buoyancy errors, enhancing measurement accuracy. This improved weight measurement method, accounting for buoyancy effects in water, is expected to facilitate the quantitative assessment of filter weights generated during chemical decontamination and system operations in nuclear power plants.

• Korean Journal of Agricultural Science
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• v.51 no.1
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• pp.63-77
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• 2024

Yield monitoring systems have become integral to precision agriculture, providing insights into the spatial variability of crop yield and playing an important role in modern harvesting technology. This paper aims to review current research trends in yield monitoring systems, specifically designed for non-grain crops, including cabbages, radishes, potatoes, and tomatoes. A systematic literature survey was conducted to evaluate the performance of various monitoring methods for non-grain crop yields. This study also assesses both mass- and volume-based yield monitoring systems to provide precise evaluations of agricultural productivity. Integrating load cell technology enables precise mass flow rate measurements and cumulative weighing, offering an accurate representation of crop yields, and the incorporation of image-based analysis enhances the overall system accuracy by facilitating volumetric flow rate calculations and refined volume estimations. Mass flow methods, including weighing, force impact, and radiometric approaches, have demonstrated impressive results, with some measurement error levels below 5%. Volume flow methods, including paddle wheel and optical methodologies, yielded error levels below 3%. Signal processing and correction measures also play a crucial role in achieving accurate yield estimations. Moreover, the selection of sensing approach, sensor layout, and mounting significantly influence the performance of monitoring systems for specific crops.