• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.1-9
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• 2024

This study proposes a multi-scale template matching technique with image pyramids (TMI) to measure structural dynamic displacement using a vision sensor under atmospheric turbulence conditions and evaluates its displacement measurement performance. To evaluate displacement measurement performance according to distance, the three-story shear structure was designed, and an FHD camera was prepared to measure structural response. The initial measurement distance was set at 10m, and increased with an increment of 10m up to 40m. The atmospheric disturbance was generated using a heating plate under indoor illuminance condition, and the image was distorted by the optical turbulence. Through preliminary experiments, the feasibility of displacement measurement of the feature point-based displacement measurement method and the proposed method during atmospheric disturbances were compared and verified, and the verification results showed a low measurement error rate of the proposed method. As a result of evaluating displacement measurement performance in an atmospheric disturbance environment, there was no significant difference in displacement measurement performance for TMI using an artificial target depending on the presence or absence of atmospheric disturbance. However, when natural targets were used, RMSE increased significantly at shooting distances of 20 m or more, showing the operating limitations of the proposed technique. This indicates that the resolution of the natural target decreases as the shooting distance increases, and image distortion due to atmospheric disturbance causes errors in template image estimation, resulting in a high displacement measurement error.

• Journal of Biomedical Engineering Research
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• v.45 no.1
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• pp.10-19
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• 2024

The purpose of this study is to conduct a summative evaluation of the usability of a general-purpose ventilator to determine whether it can be used for its intended purpose in the intended environment by the intended user and to find possible errors in use. The importance of ventilators has increased due to the accelerated aging of the population and the impact of the pandemic. In addition, patients who require ventilators are often in critical condition, so even a small error in use can be fatal. Therefore, it is important to ensure that the ventilator has sufficient stability and can be used satisfactorily without inconvenience to the user. In this study, we conducted a usability test with 17 respiratory nurses with more than 3 years of experience using the ventilator. We analyzed the task success rate, satisfaction, and opinions of the intended users while going through a total of 17 scenarios. Satisfaction was captured through an ASQ questionnaire and subjective opinions were captured through a detailed opinion questionnaire. The results showed a high level of satisfaction with an average score of 6.3 for the use scenarios. Evaluators expressed satisfaction with the overall visibility and versatility of the features, but noted that improvements were needed for calibration tasks with low task success rates. As the calibration method is different from other equipment, it was suggested that specific explanations of the calibration method and the picture that appears when calibrating are needed, and that if relevant training is provided, the equipment can be used without problems. If the usability evaluation is not limited to securing efficiency and satisfaction from the intended users, but also continuously receives feedback from users to prepare for use in emergency environments such as pandemic situations, it will be very helpful to seize opportunities such as emergency authorization in future situations, and ultimately contribute to patient safety by reducing use errors.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.1-9
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• 2024

Bridges, which are construction structures, have increased from 584 to 38,405 since the 1970s. However, as the number of bridges increases, the number of bridges with a service life of more than 30 years increases to 21,737 (71%) by 2030, resulting in fatal accidents due to basic human resource maintenance of facilities. Accordingly, the importance of bridge safety inspection and maintenance measures is increasing, and the need for decision-making support for supervisors who manage multiple bridges is also required. Currently, the safety inspection and maintenance method of bridges is to write down damage, condition, location, and specifications on the exterior survey map by hand or to record them by taking pictures with a camera. However, errors in notation of damage or defects or mistakes by supervisors are possible, typos, etc. may reduce the reliability of the overall safety inspection and diagnosis. To improve this, this study visualizes damage data recorded in the BIM model in an AR environment and proposes a maintenance plan for bridges with a small number of people through maintenance decision-making support for supervisors.

• Smart Media Journal
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• v.13 no.3
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• pp.18-26
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• 2024

Road surface monitoring is essential for maintaining road environment safety through managing risk factors like rutting and crack detection. Using autonomous driving-based UGVs with high-performance 2D laser sensors enables more precise measurements. However, the increased energy consumption of these sensors is limited by constrained battery capacity. In this paper, we propose a fusion sensor system for efficient surface monitoring with UGVs. The proposed system combines color information from cameras and depth information from line laser sensors to accurately detect surface displacement. Furthermore, a dynamic sampling algorithm is applied to control the scanning frequency of line laser sensors based on the detection status of monitoring targets using camera sensors, reducing unnecessary energy consumption. A power consumption model of the fusion sensor system analyzes its energy efficiency considering various crack distributions and sensor characteristics in different mission environments. Performance analysis demonstrates that setting the power consumption of the line laser sensor to twice that of the saving state when in the active state increases power consumption efficiency by 13.3% compared to fixed sampling under the condition of λ=10, µ=10.

• Korean Journal of Poultry Science
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• v.51 no.2
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• pp.73-82
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• 2024

The gut microbiome of broilers is a critical factor in overall health and productivity. However, high summer temperatures and high stocking density (conventional farm condition) may cause stress to broilers, resulting in an imbalance in the gut microbiome. This study was conducted to compare the gut microbiome of broilers between spring and summer in welfare (Bosung, Jeollanam-do, South Korea) and conventional farms (Jangsu, Jeollabuk-do, South Korea). A total of 31 broilers were assigned to the following groups: conventional farm in spring (n = 8); conventional farm in summer (n = 8); welfare farm in spring (n = 7); welfare farm in summer (n = 8). Cecal digesta were collected from eight broilers from each farm, and microbiome analysis was performed using 16S rRNA gene sequencing. Beta diversity analysis indicated clear differences in cecal microbiome composition between spring and summerin both welfare and conventional farm. At the phylum level, analysis of conventional farm revealed a higher proportion of Bacteroidetes in spring than in summer. At the genus level, broilers exhibited a higher abundance of Bacteroides and Alistipesin spring compared to summer. In contrast, the difference in microbial flora composition observed in welfare farm was relatively small compared to conventional farm. In conclusion, the results of this study suggest that heat stress can negatively affect the caecum microbiome of broilers. However, improvements in the housing environment can mitigate the effects of heat stress.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.2
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• pp.113-128
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• 2024

Items of road tunnel PISD (Precise Inspection for Safety and Diagnosis) were reviewed and analyzed using newly enhanced MMS (Mobile Mapping System) technology. Possible items with MMS can be visual inspection, survey and non-destructive test, structural analysis, and maintenance plan. The resolution of 3D point cloud decreased when the vehicle speed of MMS is too fast while the calibration error increased when it is too slow. The speed measurement of 50 km/h is determined to be effective in this study. Although image resolution by MMS has a limit to evaluating the width of crack with high precision, it can be used as data to identify the status of facilities in the tunnel and determine whether they meet disaster prevention management code of tunnel. 3D point cloud with MMS can be applicable for matching of cross-section and also possible for the variation of longitudinal survey, which can intuitively check vehicle clearance throughout the road tunnel. Compared with the measurement of current PISD, number of test and location of survey is randomly sampled, the continuous measurement with MMS for environment condition can be effective and meaningful for precise estimation in various analysis.

• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.3940-3955
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• 2023

A new method of numerical simulating prediction and decontamination effect evaluation for abrasive jet decontamination to radioactively contaminated metal is proposed. Based on the Computational Fluid Dynamics and Discrete Element Model (CFD-DEM) coupled simulation model, the motion patterns and distribution of abrasives can be predicted, and the decontamination effect can be evaluated by image processing and recognition technology. The impact of three key parameters (impact distance, inlet pressure, abrasive mass flow rate) on the decontamination effect is revealed. Moreover, here are experiments of reliability verification to decontamination effect and numerical simulation methods that has been conducted. The results show that: ⁶⁰Co and other homogeneous solid solution radioactive pollutants can be removed by abrasive jet, and the average removal rate of Co exceeds 80%. It is reliable for the proposed numerical simulation and evaluation method because of the well goodness of fit between predicted value and actual values: The predicted values and actual values of the abrasive distribution diameter are Ф57 and Ф55; the total coverage rate is 26.42% and 23.50%; the average impact velocity is 81.73 m/s and 78.00 m/s. Further analysis shows that the impact distance has a significant impact on the distribution of abrasive particles on the target surface, the coverage rate of the core area increases at first, and then decreases with the increase of the impact distance of the nozzle, which reach a maximum of 14.44% at 300 mm. It is recommended to set the impact distance around 300 mm, because at this time the core area coverage of the abrasive is the largest and the impact velocity is stable at the highest speed of 81.94 m/s. The impact of the nozzle inlet pressure on the decontamination effect mainly affects the impact kinetic energy of the abrasive and has little impact on the distribution. The greater the inlet pressure, the greater the impact kinetic energy, and the stronger the decontamination ability of the abrasive. But in return, the energy consumption is higher, too. For the decontamination of radioactively contaminated metals, it is recommended to set the inlet pressure of the nozzle at around 0.6 MPa. Because most of the Co elements can be removed under this pressure. Increasing the mass and flow of abrasives appropriately can enhance the decontamination effectiveness. The total mass of abrasives per unit decontamination area is suggested to be 50 g because the core area coverage rate of the abrasive is relatively large under this condition; and the nozzle wear extent is acceptable.

• Journal of Ecology and Environment
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• v.48 no.2
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• pp.173-181
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• 2024

Background: Pollination is an ecosystem service of utmost importance for agriculture. In this context, the study aimed to evaluate the pollination service of naturally occurring bees and after densification with colonies of stingless bees (Nannotrigona testceicornis and Tetragonisca angustula) in commercial strawberry plantation. The study was carried out in the four seasons of the year and under two experimental conditions: natural pollination (NP) and pollination under bee densification. The supply of flowers and bee density were estimated. For bee densification, four boxes of colonies of Iraí bees and four of Jataí bees were placed near the strawberry plantation. Five treatments were established for each condition, considering NP and pollination with bee densification on different days from flower anthesis, ranging from the 1st to the 5th day. Fruits were harvested, quantified, and submitted to evaluations to determine biometry, degree of deformity, and percentage of fertilized achenes. Results: There was a higher density in summer compared to other seasons in both conditions evaluated. The weight was greater (20.19 g) when fruits were pollinated on the first day after floral anthesis under pollination conditions with bee densification. It was observed that free pollination provided fruits with greater a greater of deformation of flowers on the fourth and fifth day after anthesis. However, when bee density became higher, the greatest degree of deformity was observed only in fifth-day fruits. The densification with stingless bees provided a 50% increase in the number of bees present on strawberry plants in summer and also a 15% increase in fruit weight and the occurrence of a lower degree of fruit deformity. Conclusions: Density with stingless bees provided a 50% increase in the number of bees present on strawberry plant in the summer, with an improvement in fruit quality and aggregate commercial value, providing a 15% increase in fruit weight and a lower degree of deformity under the conditions of densification of Iraí (N. testceicornis) and Jataí (T. angustula) bees. Under the evaluated conditions, the introduction of stingless bee boxes in the summer is recommended.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.135-140
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• 2024

It is said that PV power generation systems have a long lifespan compared to other renewable energy sources and require little maintenance. However, there are cases where the performance expected during initial design is not achieved due to shading, temperature rise, mismatch, contamination/deterioration of PV modules, failure of inverter, leakage current, and arc generation. Therefore, in order to solve the problems of these systems, the power generation amount and operation status are investigated qualitatively, or the performance is comparatively analyzed based on the performance ratio (PR), which is the performance index of the solar power generation system. However, because it includes large losses, it is difficult to accurately determine whether there are any abnormalities such as performance degradation, failure, or defects in the PV power generation system using only the performance coefficient. In this paper, we studied a status diagnosis algorithm for shading, inverter failure, leakage, and arcing of PV modules to optimize the power generation of PV power generation systems according to changes in the surrounding environment. In addition, using the studied algorithm, we examined the results of an empirical test on condition diagnosis for each area and the resulting optimized operation of power generation.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.1-11
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• 2024

Bridges crack and become damaged due to age and external factors such as earthquakes, lack of maintenance, and weather conditions. With the number of aging bridge on the rise, lack of maintenance can lead to a decrease in safety, resulting in structural defects and collapse. To prevent these problems and reduce maintenance costs, a system that can monitor the condition of bridge and respond quickly is needed. To this end, existing research has proposed artificial intelligence model that use sensor data to identify the location and extent of cracks. However, existing research does not use data from actual bridge to determine the performance of the model, but rather creates the shape of the bridge through simulation to acquire data and use it for training, which does not reflect the actual bridge environment. In this paper, we propose a bridge safety determination edge AI model that detects bridge abnormalities based on artificial intelligence by utilizing acceleration data from bridge occurring in the field. To this end, we newly defined filtering rules for extracting valid data from acceleration data and constructed a model to apply them. We also evaluated the performance of the proposed bridge safety determination edge AI model based on data collected in the field. The results showed that the F1-Score was up to 0.9565, confirming that it is possible to determine safety using data from real bridge, and that rules that generate similar data patterns to real impact data perform better.