• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.141-148
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• 2022

The development of the education system and the labor market today requires new conditions for unification and functioning, the introduction of an innovative culture in the field of Education. The construction of modern management of innovative development of a higher education institution requires consideration of the existing theoretical, methodological and practical planes on which its formation is based. The purpose of the article is to substantiate the modern paradigm of organizing the mechanism of managing the innovative development of higher education institutions. Innovation in education is represented not only by the final product of applying novelty in educational and managerial processes in order to qualitatively improve the subject and objects of management and obtain economic, social, scientific, technical, environmental and other effects, but also by the procedure for their constant updating. The classification of innovations in education is presented. Despite the positive developments in the development of Education, numerous problems remain in this area, which is discussed in the article. The concept of innovative development of higher education institutions is described, which defines the prerequisites, goals, principles, tasks and mechanisms of university development for a long-term period and should be based on the following principles: scientific, flexible, efficient and comprehensive. The role of the motivational component of the mechanism of innovative development of higher education institutions is clarified, which allows at the strategic level to create an innovative culture and motivation of innovative activity of each individual, to make a choice of rational directions for solving problems, at the tactical level - to form motives for innovative activity in the most effective directions, at the operational level - to monitor the formation of a system of motives and incentives, to adjust the directions of motivation. The necessity of the functional component of the mechanism, which consists in determining a set of steps and management decisions aimed at achieving certain goals of innovative development of higher education institutions, is proved. The monitoring component of the mechanism is aimed at developing a special system for collecting, processing, storing and distributing information about the stages of development of higher education institutions, prediction based on the objective data on the dynamics and main trends of its development, and elaboration of recommendations.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.40 no.6
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• pp.716-722
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• 1995

Near Infrared Reflectance Spectroscopy (NIRS) has been used as a tool for the rapid, accurate and nondestructive assay of small grain and forage quality analysis. The objective of this study was to establish the rapid, easy and accurate analysis method for major components of covered barley using NIRS system. NIRS used in this study was filter type instrument, Neotec 102. To obtain a useful calibration equation, standard regression between the data was analyzed by chemical analysis and by NIRS method. Standard errors of prediction (SEP) and simple correlations for unknown samples were calculated using obtained equation. SEPs for starch, $\beta$-glucan, protein and ash contents were 2.75%, 0.64%, 0.26% and 0.19%, respectively. The simple correlations for starch, $\beta$-glucan, protein and ash contents were 0.932, 0.588, 0.984 and 0.867, respectively. It was concluded that the NIRS method would be applicabl for the rapid determination of starch, protein and ash contents in barley grains.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.159-165
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• 2023

While the frequency of seismic occurrence has been increasing recently, the domestic seismic response system is weak, the objective of this research is to compare and analyze the seismic vulnerability of buildings using statistical analysis and machine learning techniques. As the result of using statistical technique, the prediction accuracy of the developed model through the optimal scaling method showed about 87%. As the result of using machine learning technique, because the accuracy of Random Forest method is 94% in case of Train Set, 76.7% in case of Test Set, which is the highest accuracy among the 4 analyzed methods, Random Forest method was finally chosen. Therefore, Random Forest method was derived as the final machine learning technique. Accordingly, the statistical analysis technique showed higher accuracy of about 87%, whereas the machine learning technique showed the accuracy of about 76.7%. As the final result, among the 22,296 analyzed building data, the seismic vulnerabilities of 1,627(0.1%) buildings are expected as more dangerous when the statistical analysis technique is used, 10,146(49%) buildings showed the same rate, and the remaining 10,523(50%) buildings are expected as more dangerous when the machine learning technique is used. As the comparison of the results of using advanced machine learning techniques in addition to the existing statistical analysis techniques, in spatial analysis decisions, it is hoped that this research results help to prepare more reliable seismic countermeasures.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.27-40
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• 2023

With the increase in the spread of smart devices and the impact of COVID-19, the consumption of media contents through smart devices has significantly increased. Along with this trend, the amount of media contents viewed through OTT platforms is increasing, that makes contents recommendations on these platforms more important. Previous contents-based recommendation researches have mostly utilized metadata that describes the characteristics of the contents, with a shortage of researches that utilize the contents' own descriptive metadata. In this paper, various text data including titles and synopses that describe the contents were used to recommend similar contents. KLUE-RoBERTa-large, a Korean language model with excellent performance, was used to train the model on the text data. A dataset of over 20,000 contents metadata including titles, synopses, composite genres, directors, actors, and hash tags information was used as training data. To enter the various text features into the language model, the features were concatenated using special tokens that indicate each feature. The test set was designed to promote the relative and objective nature of the model's similarity classification ability by using the three contents comparison method and applying multiple inspections to label the test set. Genres classification and hash tag classification prediction tasks were used to fine-tune the embeddings for the contents meta text data. As a result, the hash tag classification model showed an accuracy of over 90% based on the similarity test set, which was more than 9% better than the baseline language model. Through hash tag classification training, it was found that the language model's ability to classify similar contents was improved, which demonstrated the value of using a language model for the contents-based filtering.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.89-103
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• 2023

Obstructive sleep apnea (OSA) is one of the most prevalent sleep disorders that can lead to serious consequences, including hypertension and/or cardiovascular diseases, if not treated promptly. Continuous positive airway pressure (CPAP) is widely recognized as the most effective treatment for OSA, which needs the proper titration of airway pressure to achieve the most effective treatment results. However, the process of CPAP titration can be time-consuming and cumbersome. There is a growing importance in predicting personalized CPAP pressure before CPAP treatment. The primary objective of this study was to optimize the CPAP titration process for obstructive sleep apnea patients through EEG feature engineering with machine learning techniques. We aimed to identify and utilize the most critical EEG features to forecast key OSA predictive indicators, ultimately facilitating more precise and personalized CPAP treatment strategies. Here, we analyzed 126 OSA patients' PSG datasets before and after the CPAP treatment. We extracted 29 EEG features to predict the features that have high importance on the OSA prediction index which are AHI and SpO2 by applying the Shapley Additive exPlanation (SHAP) method. Through extracted EEG features, we confirmed the six EEG features that had high importance in predicting AHI and SpO2 using XGBoost, Support Vector Machine regression, and Random Forest Regression. By utilizing the predictive capabilities of EEG-derived features for AHI and SpO2, we can better understand and evaluate the condition of patients undergoing CPAP treatment. The ability to predict these key indicators accurately provides more immediate insight into the patient's sleep quality and potential disturbances. This not only ensures the efficiency of the diagnostic process but also provides more tailored and effective treatment approach. Consequently, the integration of EEG analysis into the sleep study protocol has the potential to revolutionize sleep diagnostics, offering a time-saving, and ultimately more effective evaluation for patients with sleep-related disorders.

• Journal of Korean Neurosurgical Society
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• v.66 no.1
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• pp.44-52
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• 2023

Objective : This study aimed to investigate the efficacy of transverse process (TP) hook system at the upper instrumented vertebra (UIV) for preventing screw pullout in adult spinal deformity surgery using the pedicle Hounsfield unit (HU) stratification based on K-means clustering. Methods : We retrospectively reviewed 74 patients who underwent deformity correction surgery between 2011 and 2020 and were followed up for >12 months. Pre- and post-operative data were used to determine the incidence of screw pullout, UIV TP hook implementation, vertebral body HU, pedicle HU, and patient outcomes. Data was then statistically analyzed for assessment of efficacy and risk prediction using stratified HU at UIV level alongside the effect of the TP hook system. Results : The screw pullout rate was 36.4% (27/74). Perioperative radiographic parameters were not significantly different between the pullout and non-pullout groups. The vertebral body HU and pedicle HU were significantly lower in the pullout group. K-means clustering stratified the vertebral body HU ≥205.3, <137.2, and pedicle HU ≥243.43, <156.03. The pullout rate significantly decreases in patients receiving the hook system when the pedicle HU was from ≥156.03 to < 243.43 (p<0.05), but the difference was not statistically significant in the vertebra HU stratified groups and when pedicle HU was ≥243.43 or <156.03. The postoperative clinical outcomes improved significantly with the implementation of the hook system. Conclusion : The UIV hook provides better clinical outcomes and can be considered a preventative strategy for screw-pullout in the certain pedicle HU range.

• The korean journal of orthodontics
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• v.52 no.2
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• pp.150-160
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• 2022

Objective: To provide reliable prediction models based on dentoskeletal and soft tissue variables for customizing maxillary incisor positions and to optimize digitalized orthodontic treatment planning. Methods: This study included 244 Chinese women (age, 18-40 years old) with esthetic profiles after orthodontic treatment with fixed appliances (133 in group I: 1° ≤ The angle between the nasion [N]-A point [A] plane and the N-B point [B] plane [ANB] ≤ 4°; 111 in group II: 4° < ANB ≤ 7°). Dental, skeletal, and soft tissue measurements were performed on lateral cephalograms of the participants. Correlation and multiple linear regression analyses were used to determine the influence of dentoskeletal and soft tissue variables on maxillary incisor position. Results: The ideal anteroposterior position of the maxillary incisor varied between sagittal skeletal patterns. The position of the maxillary incisor correlated with the sagittal discrepancy between the maxilla and the mandible (ANB), protrusion of the midface, nasal tip projection, development of the chin, and inclination of both the maxillary and mandibular incisors. Distance from the maxillary central incisor to nasion-pogonion plane predicted using multiple linear regression analysis was accurate and could be a practical measurement in orthodontic treatment planning. Conclusions: Instead of using an average value or norm, orthodontists should customize a patient's ideal maxillary incisor position using dentoskeletal and soft tissue evaluations.

• Animal Bioscience
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• v.35 no.10
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• pp.1545-1555
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• 2022

Objective: Our study aimed to investigate the effects of a 2% increase in dietary total digestible nutrients (TDN) value during the growing (7 to 12 mo of age) and fattening (13 to 30 mo of age) period of Hanwoo steers. Methods: Two hundred and twenty Hanwoo steers were assigned to one of two treatments: i) a control group (basal TDN, BTDN, n = 111 steers, growing = 70.5%, early fattening = 71.0%, late fattening = 74.0%) or high TDN (HTDN, n = 109 steers, growing = 72.6%, early = 73.1%, late = 76.2%). Growth performance, carcass traits, blood parameters, and gene expression of longissimus dorsi (LD) (7, 18, and 30 mo) were quantified. Results: Steers on the BTDN diets had increased (p≤0.02) DMI throughout the feeding trial compared to HTDN, but gain did not differ appreciably. A greater proportion of cattle in HTDN received Korean quality grade 1 (82%) or greater compared to BTDN (77%), while HTDN had a greater yield grade (29%) than BTDN (20%). Redness (a^*) of LD muscle was improved (p = 0.021) in steers fed HTDN. Feeding the HTDN diet did not alter blood parameters. Steers fed HTDN diet increased (p = 0.015) the proportion of stearic acid and tended to alter linoleic acid. Overall, saturated, unsaturated, monounsaturated, and polyunsaturated fatty acids of LD muscle were not impacted by the HTDN treatment. A treatment by age interaction was noted for mRNA expression of myosin heavy chain (MHC) IIA, IIX, and stearoyl CoA desaturase (SCD) (p≤0.026). No treatment effect was detected on gene expression from LD muscle biopsies at 7, 18, and 30 mo of age; however, an age effect was detected for all variables measured (p≤0.001). Conclusion: Our results indicated that feeding HTDN diet could improve overall quality grade while minimum effects were noted in gene expression, blood parameters, and growing performance. Cattle performance prediction in the feedlot is a critical decision-making tool for optimal planning of cattle fattening and these data provide both benchmark physiological parameters and growth performance measures for Hanwoo cattle feeding enterprises.

• Animal Bioscience
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• v.35 no.10
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• pp.1512-1523
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• 2022

Objective: The growth of pigs involves multiple regulatory mechanisms, and modern molecular breeding techniques can be used to understand the skeletal muscle growth and development to promote the selection process of pigs. This study aims to explore candidate lncRNAs and mRNAs related to skeletal muscle growth and development among Duroc pigs with different average daily gain (ADG). Methods: A total of 8 pigs were selected and divided into two groups: H group (high-ADG) and L group (low-ADG). And followed by whole transcriptome sequencing to identify differentially expressed (DE) lncRNAs and mRNAs. Results: In RNA-seq, 703 DE mRNAs (263 up-regulated and 440 down-regulated) and 74 DE lncRNAs (45 up-regulated and 29 down-regulated) were identified. In addition, 1,418 Transcription factors (TFs) were found. Compared with mRNAs, lncRNAs had fewer exons, shorter transcript length and open reading frame length. DE mRNAs and DE lncRNAs can form 417 lncRNA-mRNA pairs (antisense, cis and trans). DE mRNAs and target genes of lncRNAs were enriched in cellular processes, biological regulation, and regulation of biological processes. In addition, quantitative trait locus (QTL) analysis was used to detect the functions of DE mRNAs and lncRNAs, the most of DE mRNAs and target genes of lncRNAs were enriched in QTLs related to growth traits and skeletal muscle development. In single-nucleotide polymorphism/insertion-deletion (SNP/INDEL) analysis, 1,081,182 SNP and 131,721 INDEL were found, and transition was more than transversion. Over 60% of percentage were skipped exon events among alternative splicing events. Conclusion: The results showed that different ADG among Duroc pigs with the same diet maybe due to the DE mRNAs and DE lncRNAs related to skeletal muscle growth and development.

• 한국노년학
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• v.29 no.1
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• pp.243-258
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• 2009

Background: Falls are among the most common and serious health problems of older people. The psychological symptoms of falling have received relatively little attention compared to physical problems. Objective: The purpose of this study is to test a model to explain the factors that influence fear of falling among older adults living in a continuing care retirement community (CCRC) in Baltimore city, United States. Methods: A secondary analysis was conducted using data obtained from a Health Promotion Survey done on 149 older adults living in a CCRC. Data was originally obtained during face to face interviews with each participant. Descriptive statistics and bivariate correlations were used to describe the sample and evaluate simple correlations. A path analysis was done using the AMOS 4.0 statistical program. Results: Of the 49 hypothesized paths, 13 were statistically significant, and the model accounted for 22% of the variance in fear of falling among the elderly. There was support for the fit of the model to the data with a nonsignificant chi square at 0.478 (df=2, p=0.79), and the ratio of chi-square to degrees of freedom was 0.24, a CFI of 0.99 and RMSEA of 0.00. In particular, gender, a history of falling, and exercise were significant predictors of fear of falling. Conclusions/Implications: As anticipated, exercise is an important factor to prevent fear of falling. As a modifiable variable, self-efficacy and outcome expectation indirectly influence fear of falling through exercise.