• Safety and Health at Work
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• v.10 no.1
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• pp.67-74
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• 2019

Background: Few studies have examined the effects of a forward rotating shift pattern on police employee performance and well-being. This study sought to compare sleep duration, cognitive performance, and vigilance at the start and end of each shift within a three-shift, forward rotating shift pattern, common in United Kingdom police forces. Methods: Twenty-three police employee participants were recruited from North Yorkshire Police (mean age, 43 years). The participants were all working the same, 10-day, forward rotating shift pattern. No other exclusion criteria were stipulated. Sleep data were gathered using both actigraphy and self-reported methods; cognitive performance and vigilance were assessed using a customized test battery, comprising five tests: motor praxis task, visual object learning task, NBACK, digital symbol substitution task, and psychomotor vigilance test. Statistical comparisons were conducted, taking into account the shift type, shift number, and the start and end of each shift worked. Results: Sleep duration was found to be significantly reduced after night shifts. Results showed a significant main effect of shift type in the visual object learning task and NBACK task and also a significant main effect of start/end in the digital symbol substitution task, along with a number of significant interactions. Conclusion: The results of the tests indicated that learning and practice effects may have an effect on results of some of the tests. However, it is also possible that due to the fast rotating nature of the shift pattern, participants did not adjust to any particular shift; hence, their performance in the cognitive and vigilance tests did not suffer significantly as a result of this particular shift pattern.

• Journal of the Society of Disaster Information
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• v.17 no.3
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• pp.543-555
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• 2021

Purpose: The purpose of this study is to analyze the walking characteristics of jaywalking pedestrians, which account for a large proportion of deaths in pedestrian traffic accidents. Method: As for the analysis method, after collecting data of jaywalking pedestrians using imaging equipment, frequency analysis and statistical verification were performed on the jaywalking characteristics of elderly and non-elderly people. Result: It was found that there was a difference in the characteristics of jaywalking between the elderly and non-elders, but in the case of walking speed, insignificant results were derived. However, it was found that among the elderly, the group having difficulty walking in general had a lower walking speed than the group that did not. Conclusion: It is judged that one of the causes of jaywalking is the perception of illegal activities and insensitivity to the risk of accidents, not the age and walking ability. Therefore, in addition to safety education, it is judged that it is necessary to provide pedestrian safety information that requires the driver's attention in multiple jaywalking sections.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.191-197
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• 2021

Ensuring the economic security of agro-industrial complexes of Ukrainian regions has become a top-priority task of state regional policy, as their stable functioning is an essential element of economic security of the whole country. It is overcoming threats to the development of the agro-industrial complex that ensures its further effective functioning and has a significant impact on the economic security of our state. Methods: logical method; methods of system analysis; synthesis; economic and statistical method; method of expert assessment; SWOT analysis; economic and mathematical modelling and planning. Results. Characteristic features of economic security have been given. The essence and significance of the agro-industrial complex in improving the economic security of the state have been determined. It has been noted that in recent years, the agro-industrial complex, which acts as a driver of the domestic economy and has a direct impact on the development of the country, has been growing (in 2019 the cereal and legume harvest exceeded 75 million tons, 20,269 thousand tons of potatoes were dug, more than 15 million tons of sunflower, 9,688 thousand tons of vegetables and 2,119 thousand tons of fruits and berries were harvested, meat and egg production increased by 137.5 thousand tons (or 5.8%) and 545.5 million pieces (or 3.4%), respectively, the number of employed population in agriculture increased by 139.8 thousand people (or 4.9%), the labour productivity in crop production increased by UAH 294.4 thousand (or 44.6%), in livestock production - by UAH 311.3 thousand (or 61.8%)). Based on the system of production and economic indicators, the analysis of the state of the agro-industrial complex has been carried out. Taking into account the results of the obtained data and using SWOT-analysis, the major threats to the development of the agro-industrial complex have been identified. Ways of overcoming threats enhancing the economic security of Ukraine have been proposed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.3
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• pp.47-58
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• 2021

Recently, personal mobility (PM)-related complaints and PM accidents have increased as the number of users soars due to growth in the domestic PM market and the emergence of a number of electric scooter-sharing services. As a result, the need for PM education and practice spaces is emerging as a way to reduce accidents caused by poor PM manipulation and operation. In this study, we analyze the relevant conflict factors in order to come up with a systematic operation and activation plan for PM, and as an alternative, we review and propose how to operate a PM playground and test zone. It is expected that basic data collection and analysis of rudimentary driver behavior through PM playground operations will improve users' operational safety, and various conflicts of interest between users and non-users will be resolved by installing facilities to secure their safety.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.3
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• pp.59-73
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• 2021

There are many lives lost due traffic accidents, and which have not decreased despite advances in technology. In order to prevent traffic accidents, it is necessary to accurately forecast how they will change in the future. Until now, traffic accident-frequency forecasting has not been a major research field, but has been analyzed microscopically by traditional methods, mainly based on statistics over a previous period of time. Despite the recent introduction of AI to the traffic accident field, the focus is mainly on forecasting traffic flow. This study converts into time series data the records from 1,339,587 traffic accidents that occurred in Korea from 2014 to 2019, and uses the AI algorithm to forecast the frequency of traffic accidents based on driver's age and time of day. In addition, the forecast values and the actual values were compared and verified based on changes in the traffic environment due to COVID-19. In the future, these research results are expected to lead to improvements in policies that prevent traffic accidents.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.646-653
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• 2021

The medical bed developed in this study consists of N keys and each is driven vertically by an actuator. Since M sensors are mounted on each keyboard to measure body pressure, the resolution of the body pressure map is determined by the MN. A sensor controller is mounted on each keyboard, and the body pressure values measured from M sensors are transmitted to the main controller through a serial communication network such as CAN (Car Area Network). Each keyboard is equipped with a servo driver that drives a motor, and it is connected to the main controller via CAN to control the height of the keyboard according to the displacement value indicated by the main controller. In addition, the maximum body pressure value and body pressure ratio applied to each part of the keyboard are calculated and used as the basic data for controlling bed comfort by artificial intelligence. As a result, the proposed system can be a foundation that can be used for the control of body comfort and pressure sore prevention by artificial intelligence to be developed in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.849-856
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• 2020

Recently, as the number of high-height vehicles such as double-decker buses has increased, collision accidents have occurred in bridges and tunnels due to the deviation from the designated routes and driver's carelessness. In the case of the existing front collision warning system, it is limited to vehicles and pedestrians, so it is difficult to use it as a pass height warning system for the high height vehicles. In this paper, we propose a system that generates a warning by determining the correlation and time series characteristics of data for each segment using multiple lidar sensors and then determining the possibility of collision in the upper part of the vehicle. Also, the proposed system confirmed the proper operation through a real-time driving test and a system performance evaluation by the Korea Automobile Testing & Research Institute.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.464-470
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• 2021

Automobiles have been used as simple means of transportation, but recently, as automobiles are rapidly becoming intelligent and smart, and automobile preferences are increasing, research on IT technology convergence is underway, requiring basic high-performance functions such as driver's convenience and safety. As a result, autonomous driving and semi-autonomous vehicles are developed, and these technologies sometimes deviate from lanes due to environmental problems, situations that cannot be judged by autonomous vehicles, and lane detectors may not recognize lanes. In order to improve the performance of lane departure from the lane detection system of autonomous vehicles, which is such a problem, this paper uses fast recognition, which is a characteristic of YOLO(You only look once), and is affected by the surrounding environment using CSI-Camera. We propose a lane detection system that recognizes the situation and collects driving data to extract the region of interest.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.2
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• pp.137-145
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• 2022

Objectives: This study aimed to identify PM₁₀ mass concentration levels and conduct peak identification during five tasks in agricultural works. Methods: We investigated five agricultural tasks in 12 farms, which were harvesting, plowing, sowing, planting, and decapitation. All samples were measured by using the portable aerosol spectrometer(PAS 1.108) and the aerosol monitor(SidePak AM520). The collected data were compared with the national PM₁₀ concentrations. They were calculated to descriptive statistics, independent t-test, or ANOVA, and the peak identification on time series graph. Results: The ten investigated farms showed no significant difference with the national PM₁₀ concentrations, but the two greenhouses(AM, 143.31, 85.16 ㎍/m³) showed significant difference(p<0.05). As a result of the peak identification, the harvesting tasks showed repeated peak occurrence with the background concentration level of about 50 ㎍/m³. For plowing and sowing tasks, the peak occurred intermittently when the working was conducted near the sampling sites. Among the five tasks, the arithmetic mean of the harvesting task was 138.84±294.71 ㎍/m³, which was significantly higher than the other tasks(p<0.05). In addition, the case of using a tractor was higher than the case of not using the tractor(p<0.05), and the driver's seat showed the highest concentration(AM, 95.81 ㎍/m³). Conclusions: Works in greenhouses might have exposure to PM₁₀, while outdoor works is similar to general atmospheric PM₁₀ concentration levels. However, there is a possibility of intermittent exposure to high concentrations of PM₁₀ depending on the characteristics of agricultural tasks.

• Journal of Veterinary Science
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• v.21 no.2
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• pp.25.1-25.16
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• 2020

Porcine epidemic diarrhea virus (PEDV) emerged into Canada in January 2014, primarily affecting sow herds. Subsequent epidemiological analyses suggested contaminated feed was the most likely transmission pathway. The primary objective of this study was to describe general biosecurity and management practices implemented in PEDV-positive sow herds and matched control herds at the time the virus emerged. The secondary objective was to determine if any of these general biosecurity and farm management practices were important in explaining PEDV infection status from January 22, 2014 to March 1, 2014. A case herd was defined as a swine herd with clinical signs and a positive test result for PEDV. A questionnaire was used to a gather 30-day history of herd management practices, animal movements on/off site, feed management practices, semen deliveries and biosecurity practices for case (n = 8) and control (n = 12) herds, primarily located in Ontario. Data was analyzed using descriptive statistics and random forests (RFs). Case herds were larger in size than control herds. Case herds had more animal movements and non-staff movements onto the site. Also, case herds had higher quantities of pigs delivered, feed deliveries and semen deliveries on-site. The biosecurity practices of case herds were considered more rigorous based on herd management, feed deliveries, transportation and truck driver practices than control herds. The RF model found that the most important variables for predicting herd status were related to herd size and feed management variables. Nonetheless, predictive accuracy of the final RF model was 72%.