The purpose of this study is to diagnose problems in the regulation and management of Restricted Development Zone and to prepare a construction plan to convert it to a data-based monitoring system. Unlike other land-use zones, the Restricted Development Zone is a exceptional zone that prohibits all development activities other than the minimum maintenance and must be strictly controlled and managed by the local government. However, the current Restricted Development Zone management is distributed according to the conditions of each local government, and it is not possible to monitor changes in the entire Restricted Development Zone as shown in the survey results. In particular, in this study, by introducing an AI-based monitoring system, MOLIT sends the results of detecting changes across the country at regular time points(monthly and quarterly) to the local governments based on the same regulation standards, and the local governments can be trusted while inputting the regulation results into the system. To propose this methodology, first, a survey and interview were conducted with local government officials and experts. Second, we analyzed cases in which AI analysis was applied to local governments and proposed a plan to improve the efficiency of regulation work according to the introduction of the monitoring system. Third, a plan was prepared to establish a monitoring system based on the advancement of the management information system. This monitoring system can be expanded and applied to land that needs periodic regulation and management in the future, and this study tried to propose a methodology and policy for this.
Objective: The aim of this study was to investigate the effect Tiger-step walking on the movement of the lower extremities during walking. Method: Twenty healthy male adults who had no experience of musculoskeletal injuries on lower extremities in the last six months (age: 26.85 ± 3.28 yrs, height: 174.6 ± 3.72 cm, weight: 73.65 ± 7.48 kg) participated in this study. In this study, 7-segments whole-body model (pelvis, both side of thigh, shank and foot) was used and 29 reflective markers and cluster were attached to the body to identify the segments during the gait. A 3-dimensional motion analysis with 8 infrared cameras and 7 channeled EMG was performed to find the effect of tigerstep on uphill walking. To verify the tigerstep effect, a one-way ANOVA with a repeated measure was used and the statistical significance level was set at α=.05. Results: Firstly, Both Tiger-steps showed a significant increase in stance time and stride length compared with normal walking (p<.05), while both Tiger-steps shown significantly reduced cadence compared to normal walking (p<.05). Secondly, both Tiger-steps revealed significantly increased in hip and ankle joint range of motion compared with normal walking at all planes (p<.05). On the other hand, both Tiger-steps showed significantly increased knee joint range of motion compared with normal walking at the frontal and transverse planes (p<.05). Lastly, Gluteus maximus, biceps femoris, medial gastrocnemius, tibialis anterior of both tiger-step revealed significantly increased muscle activation compared with normal walking in gait cycle and stance phase (p<.05). On the other hand, in swing phase, the muscle activity of the vastus medialis, biceps femoris, tibialis anterior of both tiger-step significantly increased compared with those of normal walking (p <.05). Conclusion: As a result of this study, Tiger step revealed increased in 3d range of motion of lower extremity joints as well as the muscle activities associated with range of motion. These findings were evaluated as an increase in stride length, which is essential for efficient walking. Therefore, the finding of this study prove the effectiveness of the tiger step when walking uphill, and it is thought that it will help develop a more efficient tiger step in the future, which has not been scientifically proven.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.40
no.3
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pp.169-175
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2022
Korea's construction industry has a shortage and aging of construction manpower, low productivity compared to other industries, and a high rate of industrial accidents. The Ministry of Land, Infrastructure and Transport is preparing for the 4th industrial revolution and is expanding investment in construction automation and innovative growth engines to improve productivity in the construction industry. In order for new technologies to be utilized in the road construction field, the accuracy of the technologies and the applicability of each type of work must be evaluated. In this study, the accuracy of the mobile mapping system was tried to verify based on the relevant work regulations, and to suggest the applicability of the mobile mapping system to high-speed driving tracks through data acquisition and analysis on road construction sites. The accuracy of the equipment used in the study was verified in accordance with the relevant work regulations, and the possibility of applying the mobile mapping system used for the study to road construction surveying was presented with a maximum error of less than 10cm in the horizontal and vertical directions. In addition, the possibility of utilizing the road construction survey using the mobile mapping system was presented through comparison with the existing method for data acquisition time for construction surveying, production of construction status survey results, and calculation of heatmap and earthworks. In the future, the use of construction status surveying of the mobile mapping system will greatly improve the efficiency of construction work.
With the advent of cryptocurrencies such as Bitcoin in 2009, the paradigm of money, a means of payment, has been changing significantly. And it has a great impact on our daily lives. Thus central banks have attempted various analyzes on the issuance and impact of digital currencies including electronic payments but a study on which issuance method is suitable is insufficient. In this study, the issuance of digital currency was analyzed compared to the electronic payments which are currently used. As a result, the account-based model did not show any significant differences from the current RTGS(real-time gross settlement systems) and retail payment systems. But the token-based model is expected that it can improve the efficiency of finance and induce technological innovation in the financial field. However, it was analyzed that this model would weaken the intermediary function of financial institutions such as loans due to the characteristics of digital signature technology. In addition, in order to protect consumers against security attacks such as hacking and phishing of CBDCs, legal and institutional supports similar to the current electronic payment method are required, and continuous technology development efforts are also required for the CBDC issuance model to maintain convenience and anonymity equivalent to cash.
The tropospheric ozone is a pollutant that causes a great deal of damage to humans and ecosystems worldwide. In the event that ozone moves downwind from its source, a localized problem becomes a regional and global problem. To enhance ozone monitoring efficiency, geostationary satellites with continuous diurnal observations have been developed. The objective of this study is to derive the Tropospheric Ozone Movement Vector (TOMV) by employing continuous observations of tropospheric ozone from geostationary satellites for the first time in the world. In the absence of Geostationary Environmental Monitoring Satellite (GEMS) tropospheric ozone observation data, the GEOS-Chem model calculated values were used as synthetic data. Comparing TOMV with GEOS-Chem, the TOMV algorithm overestimated wind speed, but it correctly calculated wind direction represented by pollution movement. The ozone influx can also be calculated using the calculated ozone movement speed and direction multiplied by the observed ozone concentration. As an alternative to a backward trajectory method, this approach will provide better forecasting and analysis by monitoring tropospheric ozone inflow characteristics on a continuous basis. However, if the boundary of the ozone distribution is unclear, motion detection may not be accurate. In spite of this, the TOMV method may prove useful for monitoring and forecasting pollution based on geostationary environmental satellites in the future.
Although CSV means pursuing social and economic values at the same time, research on consumer benefits recognized by consumers, the subject of economic value, is insufficient. The purpose of this study is to investigate the effect of CSV activities of financial companies on purchase intention through consumer benefits and psychological distance for consumers. 265 copies of survey data were collected, and the research hypothesis was verified using SPSS 25.0 and Smart PLS 3.0. As a result of the analysis, first, fairness and authenticity had a positive (+) effect on both social and personal benefits. Second, it was found that the social and personal benefits subjectively perceived by consumers had a positive (+) effect on both purchase intention. Third, it was found that the social benefits perceived by consumers through CSV activities of financial companies had a positive (+) effect on purchase intention through psychological distance, but the mediating effect of personal benefits was not significant. Based on these research results, practical proposals were made to increase the efficiency of CSV activities by grasping the effect of consumers and purchase intentions on CSV activities of financial companies, and conclusions, implications, and future research directions were presented.
The use of 3-dimensional (3D) printing is becoming more common, and its use is increasing in the orthopedic surgery. Currently, there are four major methods of using 3D printing technology in orthopedic surgery. First, surgical planning simulation using 3D printing model; second, patient-specific surgical instruments; third, production of customized prosthesis using 3D printing technique; fourth, patient-specific prosthesis produced by 3D printing. The areas of orthopedic surgery where 3D printing technology can be used are shoulder joint, spine, hip and pelvis, knee joints, ankle joint, and tumors. Since the diseases and characteristics handled by each area are different, the method of using 3D printing technology is also slightly different in each area. However, using 3D printing technology in all areas can increase the efficiency of surgery, shorten the surgery time, and reduce radiation exposure intraoperatively. 3D printing technology can be of great help in treating patients with particularly complex and difficult orthopedic diseases or fractures. Therefore, the orthopedic surgeon should make the most of the benefits of the 3D printing technology so that patient can be treated effectively.
Journal of Korean Tunnelling and Underground Space Association
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v.24
no.1
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pp.57-78
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2022
The disc cutter and cutterbit, which are the most important factors to increase the excavation efficiency of TBM, are key factors in the design and construction of the cutter head. The arrangement, spacing, number, size, and material of disc cutters suitable for the ground conditions determine the success or failure of TBM construction. The disc cutter, which is a representative consumable part in TBM construction, can cause enormous disruption to the construction cost as well as the construction cost unless accurate prediction of wear and replacement cycle is accompanied. Therefore, in this study, the method of calculating the replacement cycle of the disc cutter calculated at the time of design for the slurry shield TBM field, and the depth of wear and replacement location of the disc cutter that occurred during actual construction were compared by analyzing the field data. For a quantitative comparison, weathered soil/weathered rock, soft rock, and hard rock were classified according to the ground in the section showing constant excavation data, and the trajectory of circle was different depending on the location of the disc cutter, so it was compared and analyzed.
Background: No studies have reported on the effects of loess beddings on insomnia patients. Purpose: It studied the change in quality of life and quality of sleep after having 15 insomnia subjects use the bedding that emits far-infrared rays. Methods: After using loess bedding for the test group and general yellow bedding for the control group, the study was conducted in the form of a questionnaire on the WHO quality of life of the subjects. Results: In the overall quality of life evaluation, the pre-and post-changes significantly improved in the test group. Using loess bedding was greatly enhanced the physical change, the actual sleep time, and the quality of sleep of the test group. The period of sleep was significantly longer post-treating, and the habitual sleep efficiency was considerably higher, and sleep disturbance was significantly lower than before in the test group. Sleep drug use and daytime dysfunction after treating in the test group significantly improved the sleep effect. Changes in the Sociality Scale, Environmental Change Scale, and Quality of Life Scale significantly improved in the test group. The quality of life for 14 items in the test group was significantly correlated. Daytime drowsiness, depression, and anxiety scale changes were significantly improved in the test group. According to the predictive survey, the subjects felt warmth in their body and comfort in mind during and after using loess bedding and evaluated that sleep quality was good. Conclusions: The overall quality of life in the test group increased using loess bedding.
Remotely sensed data have been used in various fields, such as disasters, agriculture, urban planning, and the military. Recently, the demand for the multitemporal dataset with the high-spatial-resolution has increased. This manuscript proposed an automatic image matching algorithm using a deep learning technique to utilize a multitemporal remotely sensed dataset. The proposed deep learning model was based on High Resolution Net (HRNet), widely used in image segmentation. In this manuscript, denseblock was added to calculate the correlation map between images effectively and to increase learning efficiency. The training of the proposed model was performed using the multitemporal orthophotos of the National Geographic Information Institute (NGII). In order to evaluate the performance of image matching using a deep learning model, a comparative evaluation was performed. As a result of the experiment, the average horizontal error of the proposed algorithm based on 80% of the image matching rate was 3 pixels. At the same time, that of the Zero Normalized Cross-Correlation (ZNCC) was 25 pixels. In particular, it was confirmed that the proposed method is effective even in mountainous and farmland areas where the image changes according to vegetation growth. Therefore, it is expected that the proposed deep learning algorithm can perform relative image registration and image matching of a multitemporal remote sensed dataset.
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