• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.441-449
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• 2021

With advances in autonomous vehicles, there is a growing demand for more accurate position estimation. Especially, this is a case for a moving robot for the indoor operation which necessitates the higher accuracy in position estimation when the robot is required to execute the task at a predestined location. Thus, a method for improving the position estimation which is applicable to both the fixed and the moving object is proposed. The proposed method exploits the initial position estimation from Bluetooth beacon signals as observation signals. Then, it estimates the gravitational acceleration applied to each axis in an inertial frame coordinate through computing roll and pitch angles and combining them with magnetometer measurements to compute yaw angle. Finally, it refines the control inputs for an object with motion dynamics by computing acceleration on each axis, which is used for improving the performance of Kalman filter. The experimental assessment of the proposed algorithm shows that it improves the position estimation accuracy in comparison to a conventional Kalman filter in terms of average error distance at both the fixed and moving states.

• Journal of Animal Reproduction and Biotechnology
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• v.38 no.3
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• pp.151-157
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• 2023

Background: The potential impact of aqueous extracts from Psidium guajava leaves on the reproductive system of female rabbits was evaluated. Methods: Twenty-eight rabbits, aged five to six months were utilized. Rabbits were divided into four groups and were randomly assigned to receive one of the following oral doses of the guava leaf extracts: 0 (control group), 10, 20, or 30 mg/kg of body weight. After a treatment period of 30 days, blood was collected via jugular venipunture and the serum was extracted for the assessment of serum biochemical traits levels. The females were bred and monitored throughout their pregnancy to ascertain reproductive outcomes. Results: The results indicated that the guava leaf extract significantly increased the body weight of the rabbits during both pre- and post-pregnancy compared to the control group (p < 0.05). The litter size at three weeks post-birth, prolificity rate, FSH, LH, and protein levels were notably higher (p < 0.05) at a dose of 20 mg/kg of body weight. The viability rate three weeks post-birth increased with escalating extract doses, and the highest values were observed at doses of 20 and 30 mg/kg of body weight (p < 0.05). Conclusions: This study demonstrated that, the aqueous extract of guava leaves appears to stimulate the production of FSH, LH and enhance body weight, prolificity, and pregnancy outcomes in mammals. As such, it is suggested that a dose of 20 mg/kg body weight could be beneficial in improving the reproductive performance of female.

• Journal of Chest Surgery
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• v.57 no.2
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• pp.205-212
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• 2024

Background: Postoperative atrial fibrillation (A-fib) is a serious complication of cardiac surgery that is associated with increased mortality and morbidity. Traditional 24-hour Holter monitors have limitations, which have prompted the development of innovative wearable electrocardiogram (ECG) monitoring devices. This study assessed a patch-type wearable ECG device (MobiCARE-MC100) for monitoring A-fib in patients undergoing cardiac surgery and compared it with 24-hour Holter ECG monitoring. Methods: This was a single-center, prospective, investigator-initiated cohort study that included 39 patients who underwent cardiac surgery between July 2021 and June 2022. Patients underwent simultaneous monitoring with both conventional Holter and patchtype ECG devices for 24 hours. The Holter device was then removed, and patch-type monitoring continued for an additional 48 hours, to determine whether extended monitoring provided benefits in the detection of A-fib. Results: This 72-hour ECG monitoring study included 39 patients, with an average age of 62.2 years, comprising 29 men (74.4%) and 10 women (25.6%). In the initial 24 hours, both monitoring techniques identified the same number of paroxysmal A-fib in 7 out of 39 patients. After 24 hours of monitoring, during the additional 48-hour assessment using the patch-type ECG device, an increase in A-fib burden (9%→38%) was observed in 1 patient. Most patients reported no significant discomfort while using the MobiCARE device. Conclusion: In patients who underwent cardiac surgery, the mobiCARE device demonstrated diagnostic accuracy comparable to that of the conventional Holter monitoring system.

• Physical Therapy Korea
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• v.31 no.1
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• pp.40-47
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• 2024

Background: Single-leg squat (SLS)s are commonly used as assessment tool and closed kinetic exercises are useful for assessing performance of the lower extremities. Pronated feet are associated with foot pressure distribution (FPD) during daily activities. Objects: To compare the FPD during SLSs between groups with pronated and normal feet. Methods: This cross-sectional study included 30 participants (15 each in the pronated foot and control groups) are recruited in this study. The foot posture index was used to distinguish between the pronated foot and control groups. The Zebris FDM (Zebris Medical GmbH) stance analysis system was used to measure the FPD on the dominant side during a SLS, which was divided into three phases. A two-way mixed-model ANOVA was used to identify significant differences in FPD between and within the two groups. Results: In the hallux, the results of the two-way mixed-model ANOVAs revealed a significant difference between the group and across different phases (p < 0.05). The hallux, and central forefoot were significantly different between the group (p < 0.05). Moreover, significant differences across different phases were observed in the hallux, medial forefoot, central forefoot, lateral forefoot, and rearfoot (p < 0.05). The post hoc t-tests were conducted for the hallux and forefoot central regions. In participants with pronated foot, the mean pressure was significantly greater in hallux and significantly lower, in the central forefoot during the descent and holding phases. Conclusion: SLSs are widely used as screening tests and exercises. These findings suggest that individuals with pronated feet should be cautious to avoid excessive pressure on the hallux during the descent-to-hold phase of a SLS.

• Geomechanics and Engineering
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• v.37 no.4
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• pp.307-321
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• 2024

This paper delves into the critical assessment of predicting sidewall displacement in underground caverns through the application of nine distinct machine learning techniques. The accurate prediction of sidewall displacement is essential for ensuring the structural safety and stability of underground caverns, which are prone to various geological challenges. The dataset utilized in this study comprises a total of 310 data points, each containing 13 relevant parameters extracted from 10 underground cavern projects located in Iran and other regions. To facilitate a comprehensive evaluation, the dataset is evenly divided into training and testing subset. The study employs a diverse array of machine learning models, including recurrent neural network, back-propagation neural network, K-nearest neighbors, normalized and ordinary radial basis function, support vector machine, weight estimation, feed-forward stepwise regression, and fuzzy inference system. These models are leveraged to develop predictive models that can accurately forecast sidewall displacement in underground caverns. The training phase involves utilizing 80% of the dataset (248 data points) to train the models, while the remaining 20% (62 data points) are used for testing and validation purposes. The findings of the study highlight the back-propagation neural network (BPNN) model as the most effective in providing accurate predictions. The BPNN model demonstrates a remarkably high correlation coefficient (R2 = 0.99) and a low error rate (RMSE = 4.27E-05), indicating its superior performance in predicting sidewall displacement in underground caverns. This research contributes valuable insights into the application of machine learning techniques for enhancing the safety and stability of underground structures.

• Journal of the Earthquake Engineering Society of Korea
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• v.28 no.4
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• pp.183-191
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• 2024

Accurate seismic vulnerability assessment requires high quality and large amounts of ground motion data. Ground motion data generated from time series contains not only the seismic waves but also the background noise. Therefore, it is crucial to determine the high-pass cut-off frequency to reduce the background noise. Traditional methods for determining the high-pass filter frequency are based on human inspection, such as comparing the noise and the signal Fourier Amplitude Spectrum (FAS), f² trend line fitting, and inspection of the displacement curve after filtering. However, these methods are subject to human error and unsuitable for automating the process. This study used a deep learning approach to determine the high-pass filter frequency. We used the Mel-spectrogram for feature extraction and mixup technique to overcome the lack of data. We selected convolutional neural network (CNN) models such as ResNet, DenseNet, and EfficientNet for transfer learning. Additionally, we chose ViT and DeiT for transformer-based models. The results showed that ResNet had the highest performance with R² (the coefficient of determination) at 0.977 and the lowest mean absolute error (MAE) and RMSE (root mean square error) at 0.006 and 0.074, respectively. When applied to a seismic event and compared to the traditional methods, the determination of the high-pass filter frequency through the deep learning method showed a difference of 0.1 Hz, which demonstrates that it can be used as a replacement for traditional methods. We anticipate that this study will pave the way for automating ground motion processing, which could be applied to the system to handle large amounts of data efficiently.

• Journal of the Korean earth science society
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• v.43 no.6
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• pp.691-711
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• 2022

The state-of-the-art Earth system model as a virtual Earth is required for studies of current and future climate change or climate crises. This complex numerical model can account for almost all human activities and natural phenomena affecting the atmosphere of Earth. The Unified Model (UM) from the United Kingdom Meteorological Office (UK Met Office) is among the best Earth system models as a scientific tool for studying the atmosphere. However, owing to the expansive numerical integration cost and substantial output size required to maintain the UM, individual research groups have had to rely only on supercomputers. The limitations of computer resources, especially the computer environment being blocked from outside network connections, reduce the efficiency and effectiveness of conducting research using the model, as well as improving the component codes. Therefore, this study has presented detailed guidance for installing a new version of the UM on high-performance parallel computers (Linux clusters) owned by individual researchers, which would help researchers to easily work with the UM. The numerical integration performance of the UM on Linux clusters was also evaluated for two different model resolutions, namely N96L85 (1.875° ×1.25° with 85 vertical levels up to 85 km) and N48L70 (3.75° ×2.5° with 70 vertical levels up to 80 km). The one-month integration times using 256 cores for the AMIP and CMIP simulations of N96L85 resolution were 169 and 205 min, respectively. The one-month integration time for an N48L70 AMIP run using 252 cores was 33 min. Simulated results on 2-m surface temperature and precipitation intensity were compared with ERA5 re-analysis data. The spatial distributions of the simulated results were qualitatively compared to those of ERA5 in terms of spatial distribution, despite the quantitative differences caused by different resolutions and atmosphere-ocean coupling. In conclusion, this study has confirmed that UM can be successfully installed and used in high-performance Linux clusters.

• Journal of Korean Home Economics Education Association
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• v.19 no.4
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• pp.91-117
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• 2007

This study was to compare the contents and practical problems addressed, the process of teaching-learning method, and evaluation method of Korean Home Economics curriculum and of the Oregon and Ohio's Practical Problem Focused Family & Consumer Sciences Curricula. The results are as follows. First, contents of Korean curriculum are organized by major sub-concepts of Home Economics academic discipline whereas curricular of both Oregon and Ohio states are organized by practical problems. Oregon uses the practical problems which integrate multi-subjects and Ohio uses ones which are good for the contents of the module by integrating concerns or interests which are lower or detailed level (related interests). Since it differentiates interest and module and used them based on the basic concept of Family and Consumer Science, Ohio's approach could be easier for Korean teachers and students to adopt. Second, the teaching-learning process in Korean home economics classroom is mostly teacher-centered which hinders students to develop higher order thinking skills. It is recommended to use student-centered learning activities. State of Oregon and Ohio's teaching-learning process brings up the ability of problem-solving by letting students clearly analyze practical problems proposed, solve problems by themselves through group discussions and various activities, and apply what they learn to other problems. Third, Korean evaluation system is heavily rely on summative evaluation such as written tests. It is highly recommended to facilitate various performance assessment tools. Since state of Oregon and Ohio both use practical problems, they evaluate students mainly based on their activity rather than written tests. The tools for evaluation include project documents, reports of learning activity, self-evaluation, evaluation of discussion activity, peer evaluation in a group for each students for their performance, assessment about module, and written tests as well.

• Journal of Wetlands Research
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• v.20 no.4
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• pp.424-431
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• 2018

Stormwater runoff containing considerable amounts of pollutants such as particulates, organics, nutrients, and heavy metals contaminate natural bodies of water. At present, best management practices (BMP) intended to reduce the volume and treat pollutants from stormwater runoff were devised to serve as cost-effective measures of stormwater management. However, improper design and lack of proper maintenance can lead to degradation of the facility, making it unable to perform its intended function. This study evaluated an infiltration trench (IT) that went through a series of maintenance operations. 41 monitored rainfall events from 2009 to 2016 were used to evaluate the pollutant removal capabilities of the IT. Assessment of the water quality and hydrological data revealed that the inflow volume was the most relative factor affecting the unit pollutant loads (UPL) entering the facility. Seasonal variations also affected the pollutant removal capabilities of the IT. During the summer season, the increased rainfall depths and runoff volumes diminished the pollutant removal efficiency (RE) of the facility due to increased volumes that washed off larger pollutant loads and caused the IT to overflow. Moreover, the system also exhibited reduced pollutant RE for the winter season due to frozen media layers and chemical-related mechanisms impacted by the low winter temperature. Maintenance operations also posed considerable effects of the performance of the IT. During the first two years of operation, the IT exhibited a decrease in pollutant RE due to aging and lack of proper maintenance. However, some events also showed reduced pollutant RE succeeding the maintenance as a result of disturbed sediments that were not removed from the geotextile. Ultimately, the presented effects of maintenance operations in relation to the pollutant RE of the system may lead to the optimization of maintenance schedules and procedures for BMP of same structure.

• Korean Journal of Comparative Education
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• v.27 no.4
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• pp.187-209
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• 2017

The purpose of this study was to highlight the necessity of a conceptual reestablishment of world university evaluations. The hitherto most well-known and validated world university evaluation systems such as Times Higher Education (THE), Quacquarelli Symonds (QS) or Academic Ranking of World Universities (ARWU) primarily assess big universities with quantitative evaluation indicators and performance results in the rankings. Those Systems have instigated a kind of elitism in higher education and neglect numerous small or local institutions of higher education, instead of providing stakeholders with comprehensive information about the real possibilities of tertiary education so that they can choose an institution that is individually tailored to their needs. Also, the management boards of universities and policymakers in higher education have partly been manipulated by and partly taken advantage of the elitist ranking systems with an economic emphasis, as indicated by research-centered evaluations and industry-university cooperation. To supplement such educational defects and to redress the lack of world university evaluation systems, a new system called 'U-Multirank' has been implemented with the financial support of the European Commission since 2012. U-Multirank was designed and is enforced by an international team of project experts led by CHE(Centre for Higher Education/Germany), CHEPS(Center for Higher Education Policy Studies/Netherlands) and CWTS(Centre for Science and Technology Studies at Leiden University/Netherlands). The significant features of U-Multirank, compared with e.g., THE and ARWU, are its qualitative, multidimensional, user-oriented and individualized assessment methods. Above all, its website and its assessment results, based on a mobile operating system and designed simply for international users, present a self-organized and evolutionary model of world university evaluation systems in the digital and global era. To estimate the universal validity of the redefinition of the world university evaluation system using U-Multirank, an epistemological approach will be used that relies on Edgar Morin's Complexity Theory and Karl Popper's Philosophy of Science.