• Journal of IKEEE
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• v.26 no.3
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• pp.510-514
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• 2022

In this paper, we propose the development of high-sensitivity low-end radiation measuring sensor module. The proposed measurement sensor module is a scintillator + photomultiplier(SiPM) sensor optimization structure design, amplification and filter and control circuit design for sensor driver, control circuit design including short-distance communication, sensor mechanism design and manufacturing, and GUI development applied to prototypes consists of, etc. The scintillator + photomultiplier(SiPM) sensor optimization structure design is designed by checking the characteristics of the scintillator and the photomultiplier (SiPM) for the sensor structure design. Amplification, filter and control circuit design for sensor driver is designed to process fine scintillation signal generated by radiation with a scintillator using SiPM. Control circuit design including short-distance communication is designed to enable data transmission through MCU design to support short-range wireless communication function and wired communication support. The sensor mechanism design and manufacture is designed so that the glare generated by wrapping a reflective paper (mirroring) on the outside of the plastic scintillator is reflected to increase the efficiency in order to transmit the fine scintillation signal generated from the plastic scintillator to the photomultiplier(SiPM). The GUI development applied to the prototype expresses the date and time at the top according to each screen and allows the measurement unit and time, seconds, alarm level, communication status, battery capacity, etc. to be expressed. In order to evaluate the performance of the proposed system, the results of experiments conducted by an authorized testing institute showed that the radiation dose measurement range was 30 𝜇Sv/h ~ 10 mSv/h, so the results are the same as the highest level among products sold commercially at domestic and foreign. In addition, it was confirmed that the measurement uncertainty of ±7.4% was measured, and normal operation was performed under the international standard ±15%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.149-155
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• 2023

Photovoltaic power generation is the most familiar power generation facility among new and renewable energies, and its supply began to expand about 10 years ago, and at this point, interest in solutions and technologies for system maintenance management is increasing. In particular, it is necessary to take measures to maximize the overall efficiency of the solar power generation system, whether or not there is an abnormality in the solar power generation system, and when to replace parts. The PV inverter, one element of the photovoltaic power generation system, is a power conversion system that relies on power switching devices, and DC-Link capacitors are used according to the configuration of DC/DC converters and DC-AC inverters. These DC capacitors also affect system safety (Safety) through renewable energy facilities due to the decrease in power generation of PV inverters, power loss, and increase in harmonics (THD, total distortion of AC output current) due to aging and deterioration due to long-term use. factors can be analyzed. Therefore, in this paper, the PV inverter operating characteristics according to the DC capacitor capacity state currently operating in the photovoltaic power generation system were considered, and research contents were proposed to secure the safety and reliability of renewable energy facilities.

• Journal of IKEEE
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• v.27 no.3
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• pp.345-349
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• 2023

In this paper, we propose a study on the development of deep learning structure for defective pixel detection of next-generation smart LED display board using imaging device. In this research, a technique utilizing imaging devices and deep learning is introduced to automatically detect defects in outdoor LED billboards. Through this approach, the effective management of LED billboards and the resolution of various errors and issues are aimed. The research process consists of three stages. Firstly, the planarized image data of the billboard is processed through calibration to completely remove the background and undergo necessary preprocessing to generate a training dataset. Secondly, the generated dataset is employed to train an object recognition network. This network is composed of a Backbone and a Head. The Backbone employs CSP-Darknet to extract feature maps, while the Head utilizes extracted feature maps as the basis for object detection. Throughout this process, the network is adjusted to align the Confidence score and Intersection over Union (IoU) error, sustaining continuous learning. In the third stage, the created model is employed to automatically detect defective pixels on actual outdoor LED billboards. The proposed method, applied in this paper, yielded results from accredited measurement experiments that achieved 100% detection of defective pixels on real LED billboards. This confirms the improved efficiency in managing and maintaining LED billboards. Such research findings are anticipated to bring about a revolutionary advancement in the management of LED billboards.

• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.258-264
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• 2023

The greenhouse gas (GHG) emission assessment of kenaf pellet, produced from locally generated kenaf residues in South Korea, has been studied based on the EU RED-II methodology for calculating GHG impact of biomass fuels. Based on the production pathway of kenaf residue pellet and emission coefficients from EU JRC report, the life cycle GHG emission of kenaf residue pellet is assessed as 3.0 gCO₂eq/MJ_pellet and the life cycle GHG emission of electricity generated from kenaf residue pellet is assessed as 11.9 gCO₂eq/MJ when electrical efficiency of final conversion is 25%. The potential GHG emission reduction of electricity produced from kenaf pellet is 90.3% compared to the domestic electricity emission factor 42.8 kgCO₂eq/MWh. Also, the electricity produced from kenaf pellet can reduce at least 59.6% of GHG emission compared to the electricity produced from imported wood pellets.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.5-24
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• 2022

As a new academic publication model is attempted to improve the transparency, efficiency, and speed of scientific knowledge production and distribution, the open peer review platform for verification and openness of peer review history is also activated. Publons is a global platform for tracking, validating, disclosing, and recognizing the peer-reviewed histories of more than 3 million researchers worldwide. This study analyzed the review activities of 579 researchers from domestic universities who are actively reviewing international journals through Publons. As a result of the analysis, first, researchers from domestic universities who actively review international academic journals were found to be in the fields of medicine and electrical and electronics, and in most fields, assistant professors or higher with high WOS indexed research papers are participating. Second, there was a long-tail phenomenon in which a small number of reviewers with extremely high number of review papers existed in all academic fields, and there was no significant difference in the number of review papers and review report length depending on the nationality, academic status, and age of the reviewers. Lastly, although there was a weak correlation between the amount of papers reviewed by reviewers and the number of published papers, it was found that researchers with an extremely large number of reviews do not necessarily produce as many research papers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6B
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• pp.661-667
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• 2006

In this study, an experiment of sewage sludge dewatering is carried by using electrokinetic method, and the electrokinetic dewatering efficiency of digested sludge is analyzed. Digested sludge without coagulants is selected and gravitational and pressing dewatering methods are applied in combination with electro-osmotic and electro-osmotic pulse technology. After the test of digested sludge, dewatering test of thickened sludge is carried to evaluate the electrokinetic dewatering feasibility of thickened sludge. Under the condition of constantly applied voltage, however, electrical resistance increases with decreasing of water content so that dewatering rate decreases with time. To reduce such a hindrance caused by constantly applied voltage, electro-osmotic pulse technology which is considered to reduce the difference of water content with height, is applied. For the application of electro-osmotic pulse, the dewatered flow rate and the dewatered volume became more increasing from the middle of the dewatering process than that of continuous voltage. Through the test of thickened sludge, electro-osmotic dewatering combined with gravitational and expression also showed high dewatering rate, which proved the possibility of using electrokinetic dewatering.

• Smart Media Journal
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• v.12 no.10
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• pp.63-70
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• 2023

Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.

• Journal of IKEEE
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• v.27 no.4
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• pp.486-493
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• 2023

In this paper, we propose an automatic hand gesture area extraction and recognition technique using FMCW radar-based point cloud and LSTM. The proposed technique has the following originality compared to existing methods. First, unlike methods that use 2D images as input vectors such as existing range-dopplers, point cloud input vectors in the form of time series are intuitive input data that can recognize movement over time that occurs in front of the radar in the form of a coordinate system. Second, because the size of the input vector is small, the deep learning model used for recognition can also be designed lightly. The implementation process of the proposed technique is as follows. Using the distance, speed, and angle information measured by the FMCW radar, a point cloud containing x, y, z coordinate format and Doppler velocity information is utilized. For the gesture area, the hand gesture area is automatically extracted by identifying the start and end points of the gesture using the Doppler point obtained through speed information. The point cloud in the form of a time series corresponding to the viewpoint of the extracted gesture area is ultimately used for learning and recognition of the LSTM deep learning model used in this paper. To evaluate the objective reliability of the proposed technique, an experiment calculating MAE with other deep learning models and an experiment calculating recognition rate with existing techniques were performed and compared. As a result of the experiment, the MAE value of the time series point cloud input vector + LSTM deep learning model was calculated to be 0.262 and the recognition rate was 97.5%. The lower the MAE and the higher the recognition rate, the better the results, proving the efficiency of the technique proposed in this paper.

• Journal of the Korea Institute of Building Construction
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• v.24 no.2
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• pp.203-213
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• 2024

This study delves into the mechanical properties of fiber-reinforced cement composites(FRCC) concerning the dispersion method of multi-walled carbon nanotubes(MWCNTs). MWCNTs find utility in industrial applications, particularly in magnetic sensing and crack detection, owing to their diverse properties including heat resistance and chemical stability. However, current research endeavors are increasingly directed towards leveraging the electrical properties of MWCNTs for self-sensing and smart sensor development. Notably, achieving uniform dispersion of MWCNTs poses a challenge due to variations in researchers' skills and equipment, with excessive dispersion potentially leading to deterioration in mechanical performance. To address these challenges, this study employs ultrasonic dispersion for a defined duration along with PCE surfactant, known for its efficacy in dispersion. Test specimens of FRCC are prepared and subjected to strength, drawing, and direct tensile tests to evaluate their mechanical properties. Additionally, the influence of MWCNT dispersion efficiency on the enhancement of FRCC mechanical performance is scrutinized across different dispersion methods.

• Journal of Animal Science and Technology
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• v.45 no.4
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• pp.543-550
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• 2003

Two experiments were conducted to determine the effects of deletion of vitamin and trace mineral premixes on growth, feed efficiency, backfat thickness, hemoglobin content, muscle vitamin E content, and fecal, serum and muscle trace mineral contents in finishing pigs raised under two different housing conditions. In Exp. 1, three pens (or experimental units) of five pigs each (average weight $\pm$ s.e., 70 $\pm$ 0.5 kg) were assigned to a control diet (with vitamin and trace mineral premixes) or diets with 50 or 100% of the premixes deleted. Pigs were fed to market weight under sub-optimal housing conditions with sawdust-covered concrete floor and no electrical ventilation. In Exp. 2, three pens of four pigs each (average weight $\pm$ s.e., 56 $\pm$ 1.1 kg) were assigned to a control (with vitamin and trace mineral premixes), Diet-P (100% of the premixes deleted) or Diet-P+E (Diet-P plus 100 mg $\alpha$-tocopherol acetate/kg diet fed for the last 2 wk before slaughter). Pigs were fed to market weight under optimal housing conditions with 70%-slatted concrete floor, electrical ventilation and temperature control. No significant differences were found in average daily gain (ADG), average daily feed intake (ADFI), and gain/feed among treatments in both experiments, but in Exp. 2 done with younger pigs, ADG and ADFI tended to be higher in the control group than in pigs fed diet without premixes. Hemoglobin content, hematocrit and red blood cell count were not influenced by the deletion of premixes. Backfat thickness was not different among treatments. Fecal Mn (twofold) and Zn (threefold) contents were higher in the control than in pigs fed diets without the premixes. Serum trace mineral contents were not influenced by diets. $\alpha$-Tocopherol content in gluteus maxima was decreased (P< 0.01) by deleting the dietary premixes, but increased to the level higher than the control by adding 100 mg $\alpha$-tocopheryl acetate/kg diet fed for the last 2 wk before slaughter. Results indicate that: 1) supplementary vitamins and trace minerals may not be necessary for optimum growth in finishing pigs, and 2) deletion of the dietary premixes reduces muscle vitamin E content, but the reduced content can be reversed by adding $\alpha$- tocopherol to diets fed for the last 2 wk before slaughter. The deletion may help to alleviate the environmental load of certain minerals from manure.