• Geomechanics and Engineering
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• v.36 no.5
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• pp.489-509
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• 2024

Slope stability analysis and prediction are of critical importance to geotechnical engineers, given the severe consequences associated with slope failure. This research endeavors to forecast the factor of safety (FOS) for slopes through the implementation of six distinct ML techniques, including back propagation neural networks (BPNN), feed-forward neural networks (FFNN), Takagi-Sugeno fuzzy system (TSF), gene expression programming (GEP), and least-square support vector machine (Ls-SVM). 344 slope cases were analyzed, incorporating a variety of geometric and shear strength parameters measured through the PLAXIS software alongside several loss functions to assess the models' performance. The findings demonstrated that all models produced satisfactory results, with BPNN and GEP models proving to be the most precise, achieving an R² of 0.86 each and MAE and MAPE rates of 0.00012 and 0.00002 and 0.005 and 0.004, respectively. A Pearson correlation and residuals statistical analysis were carried out to examine the importance of each factor in the prediction, revealing that all considered geomechanical features are significantly relevant to slope stability. However, the parameters of friction angle and slope height were found to be the most and least significant, respectively. In addition, to aid in the FOS computation for engineering challenges, a graphical user interface (GUI) for the ML-based techniques was created.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.187-190
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• 2008

Owing to rapid advancements of the mobile computing technologies and the performance of mobile device recently, the data synchronization techniques between severs and mobile clients are getting more and more important. OMA also proposes and recommends standard synchronization methods to use SyncML. However, the feasible data in the method are limited to normal document data, scheduler data, etc. This paper a standard framework based on SyncML. We call it SCGFG. The SCGFG is able to synchronize not only the above data but also GIS data which is very useful in mobile applications. It applies GML, international GIS standard, to the synchronization. By means of using XML, it is also able to resolve the serious problem that is the increase of data volume occurred by SyncML and GML. efficiently. It is highly expected to be useful in the smart synchronization of GIS data among several servers and mobile clients.

• Journal of Periodontal and Implant Science
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• v.34 no.4
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• pp.759-769
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• 2004

Periodontal therapy has dealt primarily with attempts at arresting progression of disease, however, more recent techniques have focused on regenerating the periodontal ligament having the capacity to regenerate the periodontium. The effect of chitosan, a carbohydrate biopolymer extracted from chitin, on periodontal ligament regeneration is of particular interest. The purpose of this study was to evaluate the effect of chitosan on the expression of extracellular matrix proteins in primary rat calvarial cells in Vitro. In the control group, cells was cultured with BGjb media. In the experimental groups, cells were cultured with chitosan in concentration of 0.01, 0.1, 1.0 and 2.0 mg/ml. Then each group was characterized by examining alkaline phosphatase activity at 3 and 7 days, and the ability to produce mineralized nodules of rat calvarial cells at 14 and 21 days. Synthesis of type I collagen (COL-I), osteocalcin (OCN), bone sialoprotein (BSP) was evaluated by RT-PCR at 14 days. The results were as follows: 1. Alkaline phosphatase activity was significantly higher in the concentration of chitosan 0.01mg/ml, 0.1mg/ml and 1.0mg/ml compared to control (p<0.05). 2. The percentage of mineralized bone nodule was more in the concentration of chitosan 0.1mg/ml and 1.0mg/ml than the control. 3. At 14 day culture, the expression of OCN was increased by chitosan in concentration of 1.0 mg/ml and 2.0 mg/ml. These results suggested that chitosan in concentration of 0.1 and 1,0 mg/ml stimulate the extracellular matrix of primary rat calvarial cells and may facilitate the formation of bone.

• Korean Journal of Animal Reproduction
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• v.12 no.1
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• pp.24-30
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• 1988

These experiments were carried out to develop new techniques for In Vitro separatin of X-and Y-bearing spermatozoa. The bull semen was applied to the various Gel-Columns filled with swellen Sephadex G-50 Fine and then elutriated wtih Locke solution (elutriation rate; 1ml/3-4min., 1ml/1-2min.). Elutriated solution was fractionated into 1ml by automatic Fraction Collector and spermatozoa included in each fraction were subjected to the estimation of viability and recovery rate, and to B-body test. The results obtained in these experiments were summarized as follows: 1. When the column size and the elutriation rate were adjusted to 15$\times$1.6cm and 1ml/3-4min., respectively, the highest sperm concentration was obtained from the 8th to the 12th fraction. 2. As a trend, the viability of spermatozoa was improved by chromatography, and the degree of improvement ranged 5 to 10 percentage. 3. The average recovery rate of spermatozoa applied to column was 73.2 percentage and ranged 52.6 to 81.3 percentage. 4. The lowest rate of B-body bearing spermatozoa following chromatography was obtained when the column size and the elutriation rate were adjusted to 15$\times$0.8cm and 1ml/1-2min., respectively.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.17 no.4
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• pp.331-336
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• 1995

To use cultured mucosa as a graft of full thickness, our laboratory has been involved in the development of techniques to grow epidermis together with connective tissue. Human oral mucosa was obtained at dental surgery. Under sterile conditions the tissues were cut into explants of 0.1 $cm^2$ which were placed in the center of 24 well tissue culture dishes and incubated in a growth medium. The growth medium used for epithelial was MEM(Minimum Essential Medium) supplemented with 10% fetal calf serum, 0.5% dimethyl sulfoxide, glutamine (0.292 g/l), epidermal growth factor (40 ug/ml), cholera toxin (30 ng/ml), hydrocortisone (2 ug/ml), insulin (40 ug/ml) and transferin (5 ug/ml). The medium for stratification of epithelial cells was MEM supplemented with 10% fetal calf serum, 0.5% dimethyl sulfoxide and glutamine (0.292 g/l). The medium used for fibroblasts was MEM supplemented with 10% fetal calf serum. With the three types of media used alternatively, a mucosa composed of epidermis and connective tissue was obtained after 3 weeks of culture.

• Proceedings of the Microbiological Society of Korea Conference
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• 2000.10a
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• pp.119-127
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• 2000

The development and performance of a competitive indirect immunoassay for the quantitative measurement of polychlorinated biphenyl compounds in insulating oils is presented. Reagent preparation and the assay characterisation, optimisation and validation steps are described. The dynamic range of the assay for Aroclors 1254 and 1260 in methanol was $50-800 {\mu}g\;ml^{-1}$ with $50\%$ signal inhibition values of 217 and $ 212 {\mu}g\;ml^{-1}$ respectively. Impending legislation in the UK is likely to decree that oils containing $ >50 {\mu}g\;ml^{-1}$ PCB be considered contaminated. Assay sensitivity increased with the degree of PCB chlorination. The assay of structurally related compounds of environmental concern yielded cross-reactivity values of under $0.6\%$. The immunoassay proved reliable for the analysis of transformer oils containing $>70{\mu}g\;ml^{-1}$ PCB, but over-estimated PCB levels in oils containing $<20{\mu}g\;ml^{-1}$ of the analyte with the oils requiring pre-treatment using either solid-phase extraction techniques or washing with KOH-ethanol/sulphuric acid to remove matrix interferents. The analytical performance of the assay was compared against a commercially available semi-quantitative immunoassay kit for PCBs in soil and water.

• Journal of Microbiology and Biotechnology
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• v.1 no.3
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• pp.157-162
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• 1991

Conditions for glutathione production in E. coli cells which possess pGH501 (2 gshI+gshII) were studied. In terms of ATP supply for the glutathione synthesis, two different systems have been constructed and compared. When the acetate kinase reaction of E. coli was used for ATP generation, 20 mM of L-cysteine was completely converted to glutathione by toluene-treated E. coli cells (100 mg/ml) harboring pGH501 within 2 h at $37^{\circ}C$. However, considering the economical aspects, the glycolytic pathway of yeast was chosen as a better system for ATP generation. The optimal concentrations of reactants for glutathione production were determined to be as follows; 80 mM L-glutamate, 20 mM L-cysteine, 20 mM glycine, 20 mM $MgCl_2$, 50 mM potassium phosphate buffer (pH 7.5), 400 mM glucose, polyoxyethylene stearylamine ($5\;\mul/ml$), toluene-treated E. coli HB101/pGH501 (100 mg/ml), and dried yeast cells (400 mg/ml). The conversion ratio of L-cysteine to glutathione was 80% (about 5 mg/ml) under optimal condition within 6 h at $37^{\circ}C$.

• Computers and Concrete
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• v.32 no.3
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• pp.233-246
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• 2023

Accurate prediction of concrete compressive strength can minimize the need for extensive, time-consuming, and costly mixture optimization testing and analysis. This study attempts to enhance the prediction accuracy of compressive strength using stacking ensemble machine learning (ML) with feature engineering techniques. Seven alternative ML models of increasing complexity were implemented and compared, including linear regression, SVM, decision tree, multiple layer perceptron, random forest, Xgboost and Adaboost. To further improve the prediction accuracy, a ML pipeline was proposed in which the feature engineering technique was implemented, and a two-layer stacked model was developed. The k-fold cross-validation approach was employed to optimize model parameters and train the stacked model. The stacked model showed superior performance in predicting concrete compressive strength with a correlation of determination (R²) of 0.985. Feature (i.e., variable) importance was determined to demonstrate how useful the synthetic features are in prediction and provide better interpretability of the data and the model. The methodology in this study promotes a more thorough assessment of alternative ML algorithms and rather than focusing on any single ML model type for concrete compressive strength prediction.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.209-214
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• 2024

This is an extended research paper focusing on the applications of Machine Learing and Artificial Intelligence in virtual learning environment. The world is moving at a fast pace having the application of Machine Learning (ML) and Artificial Intelligence (AI) in all the major disciplines and the educational sector is also not untouched by its impact especially in an online learning environment. This paper attempts to elaborate on the benefits of ML and AI in E-Learning (EL) in general and explain how King Khalid University (KKU) EL Deanship is making the best of ML and AI in its practices. Also, researchers have focused on the future of ML and AI in any academic program. This research is descriptive in nature; results are based on qualitative analysis done through tools and techniques of EL applied in KKU as an example but the same modus operandi can be implemented by any institution in its EL platform. KKU is using Learning Management Services (LMS) for providing online learning practices and Blackboard (BB) for sharing online learning resources, therefore these tools are considered by the researchers for explaining the results of ML and AI.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.479-486
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• 2024

This study reviews the recently conducted case studies to explore the innovative integration of Artificial Intelligence (AI) and Machine Learning (ML) in the domain of building facility management and predictive maintenance. It systematically examines recent developments and applications of advanced computational methods, emphasizing their role in enhancing asset management accuracy, energy efficiency, and occupant comfort. The study investigates the implementation of various AI and ML techniques, such as regression methods, Artificial Neural Networks (ANNs), and deep learning models, demonstrating their utility in asset management. It also discusses the synergistic use of ML with domain-specific technologies such as Geographic Building Information Modeling (BIM), Information Systems (GIS), and Digital Twin (DT) technologies. Through a critical analysis of current trends and methodologies, the paper highlights the importance of algorithm selection based on data attributes and operational challenges in deploying sophisticated AI models. The findings underscore the transformative potential of AI and ML in facility management, offering insights into future research directions and the development of more effective, data-driven management strategies.