• Journal of Advanced Marine Engineering and Technology
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• v.40 no.7
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• pp.629-634
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• 2016

This paper describes the implementation of a ZigBee sensor node that can be utilized as a multiband and machine to machine (M2M) communication gateway. The IEEE 802.15.4-2003 standard was used as the wireless network frequency band. Ember's Type EM357 SoC was used as the transmission and reception device to perform the communication function, and it was also used for both the main M2M gateway and the sensor node. For the implementation of the operating protocol, EmberZNet Stack 4.5.4 from the Ember Corporation was used. The measurement of the reception sensitivity in the receiving module and the actual output signal from the reference were obtained from the transmission of a packet, and the packet included the M2M gateway within the attached ZigBee sensor. The packet error rate was measured as 0% with a -98 dBm reception sensitivity at the ZigBee frequency. In addition, excellent current characteristics of the ZigBee modules were shown by the implementation of the low-power circuit.

• Journal of the Korea Society of Computer and Information
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• v.27 no.5
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• pp.1-9
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• 2022

Localization systems can be used with various circumstances like measuring population movement and rescue technology, even in security technology (like infiltration detection system). Vision sensors such as camera often used for localization is susceptible with light and temperature, and can cause invasion of privacy. In this paper, we used ultra-wideband radar technology (which is not limited by aforementioned problems) and machine learning techniques to measure the number and location of occupants in other indoor spaces behind the wall. We used four different algorithms and compared their results, including extremely randomized tree for four different situations; detect the number of occupants in a classroom, split the classroom into 28 locations and check the position of occupant, select one out of the 28 locations, divide it into 16 fine-grained locations, and check the position of occupant, and checking the positions of two occupants (existing in different locations). Overall, four algorithms showed good results and we verified that detecting the number and location of occupants are possible with high accuracy using machine learning. Also we have considered the possibility of service expansion using the oneM2M standard platform and expect to develop more service and products if this technology is used in various fields.

• Transactions of Materials Processing
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• v.32 no.2
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• pp.74-80
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• 2023

A deformation behavior of commercially pure titanium (CP-Ti) is highly dependent on material and processing parameters, such as deformation temperature, deformation direction, and strain rate. This study aims to predict the multivariable and nonlinear tensile behavior of CP-Ti using machine learning based on three algorithms: artificial neural network (ANN), light gradient boosting machine (LGBM), and long short-term memory (LSTM). The predictivity for tensile behaviors at the cryogenic temperature was lower than those in the room temperature due to the larger data scattering in the train dataset used in the machine learning. Although LGBM showed the lowest value of root mean squared error, it was not the best strategy owing to the overfitting and step-function morphology different from the actual data. LSTM performed the best as it effectively learned the continuous characteristics of a flow curve as well as it spent the reduced time for machine learning, even without sufficient database and hyperparameter tuning.

• Safety and Health at Work
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• v.6 no.4
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• pp.268-278
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• 2015

Background: This study aimed to assess the whole-body vibration (WBV) exposure among large blast hole drill machine operators with regard to the International Organization for Standardization (ISO) recommended threshold values and its association with machine- and rock-related factors and workers' individual characteristics. Methods: The study population included 28 drill machine operators who had worked in four opencast iron ore mines in eastern India. The study protocol comprised the following: measurements of WBV exposure [frequency weighted root mean square (RMS) acceleration ($m/s^2$)], machine-related data (manufacturer of machine, age of machine, seat height, thickness, and rest height) collected from mine management offices, measurements of rock hardness, uniaxial compressive strength and density, and workers' characteristics via face-to-face interviews. Results: More than 90% of the operators were exposed to a higher level WBV than the ISO upper limit and only 3.6% between the lower and upper limits, mainly in the vertical axis. Bivariate correlations revealed that potential predictors of total WBV exposure were: machine manufacturer (r = 0.453, p = 0.015), age of drill (r = 0.533, p = 0.003), and hardness of rock (r = 0.561, p = 0.002). The stepwise multiple regression model revealed that the potential predictors are age of operator (regression coefficient ${\beta}=-0.052$, standard error SE = 0.023), manufacturer (${\beta}=1.093$, SE = 0.227), rock hardness (${\beta}=0.045$, SE = 0.018), uniaxial compressive strength (${\beta}=0.027$, SE = 0.009), and density (${\beta}=-1.135$, SE = 0.235). Conclusion: Prevention should include using appropriate machines to handle rock hardness, rock uniaxial compressive strength and density, and seat improvement using ergonomic approaches such as including a suspension system.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.3
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• pp.42-47
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• 2003

In Part 2 of this paper, the dynamic cutting force model, thermal behavior model, and feed drive model used in the development of a virtual machine tool (VMT) are briefly described. Some results are presented to verify the proposed models. Experimental data agreed well with the predicted results fer each model. A comprehensive software environment to integrate the models into a VMT is also proposed.

• Journal of Mechanical Science and Technology
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• v.20 no.1
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• pp.51-58
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• 2006

To compensate for the motion errors in hydrostatic tables, a method to actively control the clearance of a bearing corresponding to the amount of error using actively controlled capillaries is introduced in this paper. The design method for an actively controlled capillary that considers the output rate of a piezo actuator and the amount of error that must be corrected is described. The basic characteristics of such a system were tested, such as the maximum controllable range of the error, micro-step response, and available dynamic bandwidth when the capillary was installed in a hydrostatic table. The tests demonstrated that the maximum controllable range was $2.4\;{\mu}m$, the resolution was 27 nm, and the frequency bandwidth was 5.5 Hz. Simultaneous compensation of the linear and angular motion errors using two actively controlled capillaries was also performed for a hydrostatic table driven by a ballscrew and a DC servomotor. An iterative compensation method was applied to improve the compensation characteristics. Experimental results showed that the linear and angular motion errors were improved to $0.12{\mu}m$ and 0.20 arcsec, which were about $1/15^{th}$ and $1/6^{th}$ of the initial motion errors, respectively. These results confirmed that the proposed compensation method improves the motion accuracy of hydrostatic tables very effectively.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.5-10
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• 2022

Ground Subsidence has been continuously occurring in densely populated downtown. The main cause of ground subsidence is the damaged underground facility like sewer. Currently, ground subsidence is being dealt with by discovering cavities in ground using GPR. However, this consumes large amount of manpower and cost, so it is necessary to predict hazardous area for efficient operation of GPR. In this study, ◯◯city is divided into 500 m×500 m grids. Then, data set was constructed using the characteristics of the underground facility and ground subsidence in grids. Data set used to machine learning model for ground subsidence risk grade prediction. The purposed model would be used to present a ground subsidence risk map of target area.

• Korean Journal of Food Science and Technology
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• v.46 no.6
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• pp.723-728
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• 2014

The physicochemical characteristics of coffees extracted using 7 different extraction methods were investigated. The pH values of coffees extracted via different extraction methods ranged from 5.26 to 5.54, and coffee extracted by Ibrik had the highest pH among all samples. The soluble solid content and titratable acidity of coffee extracted using an Espresso machine were significantly higher than those obtained using other extraction methods. Furthermore, the total phenol and caffeine contents of coffee extracted using an Espresso machine were 6.46 and 2.65 mg/mL, respectively. In regard to color, the $L^*$, $a^*$ and $b^*$ values of coffee extracted via different extraction methods were in the ranges of 0.81-38.94, 4.49-37.75, and 0.71-66.42, respectively. In regard to the phenolic compounds, the chlorogenic acid, caffeic acid and ferulic acid contents of coffee extracted using an Espresso machine were higher than those obtained by other extraction methods at 0.15 mg/mL, $0.075{\mu}g/{\mu}L$, and $0.019{\mu}g/{\mu}L$, respectively.

• Journal of Animal Environmental Science
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• v.15 no.2
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• pp.99-106
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• 2009

We conducted a comparison experiment of our wide-area spraying high speed fan with a fan which was developed by Japan MARUYAMA Inc. have been much recognized for it's history and skills in a field of spraying machine. In result, MARUYAMA Inc. fan sprayed up to 120 m and, on the other hand, wide-area spraying high speed fan of our own making was able to spray up to more than 160 m. Wide-area spraying machine have been supplied to domestic demands by importing from Japan, but it is determined to be possible that home products will occupy market for it's ability, price and A/S environment in future. The main research results are below. Some plastic cups which are in the open market are used for our experiment. After distributing 90 cups in a range of 10m vertically with localizing 5 cups horizontally and 18 cups vertically, spraying machine was moved and finally we make distribution charts by estimating the sprayed amounts on each cup. Vertical distance was set up to 5m and we calculated average values by using sprayed amount and data of 4 observers. In result our fan showed much sprayed amounts than MARUYAMA Inc. all over the field except situations of vehicle departing and stopping.

• Journal of Broadcast Engineering
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• v.21 no.3
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• pp.298-306
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• 2016

With the advent of Internet of Things (IoT) technology that allows the communications between things and devices over the Internet, a lot of researches on the IoT services, such as smart home or healthcare, have been progressed. In the existing machine-to-machine (M2M) communications, however, since the underlying link-layer technologies, such as Bluetooth or ZigBee, do not use the Internet Protocol (IP) communication, those technologies are not suitable to provide the IoT services. Accordingly, this paper discusses how to provide the Internet services in the M2M communication, and propose an implementation of the Constrained Application Protocol (CoAP) over 6LoWPAN for providing IoT services in the BLE networks. Based on the implementation, we compared the performance between HTTP and CoAP for IoT communications. From the experimental results, we can see that the CoAP protocol gives better performance than the HTTP protocol with two times higher throughput, 21% faster transmission time, and 22% smaller amount of generated packets.