• Journal of Climate Change Research
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• v.6 no.4
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• pp.331-344
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• 2015

A long-term gridded historical data at 3 km spatial resolution has been generated for practical regional applications such as hydrologic modelling. However, overly high or low values have been found at some grid points where complex topography or sparse observational network exist. In this study, the Inverse Distance Weighting (IDW) method was applied to properly smooth the overly predicted values of Improved GIS-based Regression Model (IGISRM), called the IDW-IGISRM grid data, at the same resolution for daily precipitation, maximum temperature and minimum temperature from 2001 to 2010 over South Korea. We tested various effective distances in the IDW method to detect an optimal distance that provides the highest performance. IDW-IGISRM was compared with IGISRM to evaluate the effectiveness of IDW-IGISRM with regard to spatial patterns, and quantitative performance metrics over 243 AWS observational points and four selected stations showing the largest biases. Regarding the spatial pattern, IDW-IGISRM reduced irrational overly predicted values, i. e. producing smoother spatial maps that IGISRM for all variables. In addition, all quantitative performance metrics were improved by IDW-IGISRM; correlation coefficient (CC), Index Of Agreement (IOA) increase up to 11.2% and 2.0%, respectively. Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were also reduced up to 5.4% and 15.2% respectively. At the selected four stations, this study demonstrated that the improvement was more considerable. These results indicate that IDW-IGISRM can improve the predictive performance of IGISRM, consequently providing more reliable high-resolution gridded data for assessment, adaptation, and vulnerability studies of climate change impacts.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.1
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• pp.1-12
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• 2021

The present study proposes the modified-stoichiometric model for describing hydration of sodium silicate-based alkaliactivated slag(AAS), and compares the results with the thermodynamic modelling-based calculations. The proposed model is based on Chen and Brouwers(2007a) model with updated database as reported in recent studies. In addition, the calculated results for AAS are compared to those for hydrated portland cement. The maximum difference between the proposed model and the thermodynamic calculation for AAS was at most 20%, and the effects of water-to-binder ratio and activator dosages were identically described by both approaches. In particular, the amount of non-evaporable water was within 10% difference, and was in excellent agreement with the experimental results. Nevertheless, notable deviation was observed for the chemical shrinkage, which is largely dependent on the volume of hydrates and pores.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.390-399
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• 2022

Cyber security and resilience are phrases that describe safeguards of ICTs (information and communication technologies) from cyber-attacks or mitigations of cyber event impacts. The sole purpose of Risk models are detections, analyses, and handling by considering all relevant perceptions of risks. The current research effort has resulted in the development of a new paradigm for safeguarding services offered online which can be utilized by both service providers and users. customers. However, rather of relying on detailed studies, this approach emphasizes task selection and execution that leads to successful risk treatment outcomes. Modelling intelligent CSGs (Cyber Security Games) using MLTs (machine learning techniques) was the focus of this research. By limiting mission risk, CSGs maximize ability of systems to operate unhindered in cyber environments. The suggested framework's main components are the Threat and Risk models. These models are tailored to meet the special characteristics of online services as well as the cyberspace environment. A risk management procedure is included in the framework. Risk scores are computed by combining probabilities of successful attacks with findings of impact models that predict cyber catastrophe consequences. To assess successful attacks, models emulating defense against threats can be used in topologies. CSGs consider widespread interconnectivity of cyber systems which forces defending all multi-step attack paths. In contrast, attackers just need one of the paths to succeed. CSGs are game-theoretic methods for identifying defense measures and reducing risks for systems and probe for maximum cyber risks using game formulations (MiniMax). To detect the impacts, the attacker player creates an attack tree for each state of the game using a modified Extreme Gradient Boosting Decision Tree (that sees numerous compromises ahead). Based on the findings, the proposed model has a high level of security for the web sources used in the experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3313-3332
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• 2022

This study is an investigation into the factors affecting patient dissatisfaction among Saudi hospitals. The selected factors considered for analysis are security of information sharing, operational practices, disruptive technologies, and the ease of use of EHR patient information management systems. From the literature review section, it was clear that hardly any other studies have embraced these concepts in one as was intended by this study. The theories that the study heavily draws from are the service dominant logic and the feature integration theory. The study surveyed 350 respondents from three large major hospitals in three different metropolitan cities in the Kingdom of Saudi Arabia. This sample came from members of the three hospitals that were willing to participate in the study. The number 350 represents those that successfully completed the online questionnaire or the limited physical questionnaires in time. The study employed the structural equation modelling technique to analyze the associations. Findings suggested that security of information sharing had a significant direct effect on patient satisfaction. Operational practice positively mediated the effect of security of information sharing on patient dissatisfaction. However, ease of use failed to significant impact this association. The study concluded that to improve patient satisfaction, Saudi hospitals must work on their systems to reinforce them against the active threats on the privacy of patients' data by leveraging disruptive technology. They should also improve their operational practices by embracing quality management techniques relevant to the healthcare sector.

• Steel and Composite Structures
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• v.44 no.1
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• pp.33-47
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• 2022

This paper presents a finite element model for predicting the monotonic behaviour of bolted endplate joints connecting steel-concrete composite walls and steel beams. The demountable Hollo-bolts are utilised to facilitate the quick installation and dismantling for replacement and reuse. In the developed model, material and geometric nonlinearities were included. The accuracy of the developed model was assessed by comparing the numerical results with previous experimental tests on hollow/composite column-to-steel beam joints that incorporated endplates and Hollo-bolts. In particular, the Hollo-bolts were modelled with the expanded sleeves involved, and different material properties of the Hollo-bolt shank and sleeves were considered based on the information provided by the manufacture. The developed models, therefore, can be applied in the present study to simulate the wall-to-beam joints with similar structural components and characteristics. Based on the validated model, the authors herein compared the behaviour of wall-to-beam joints of two commonly utilised composite walling systems (Case 1: flat steel plates with headed studs; Case 2: lipped channel section with partition plates). Considering the ease of manufacturing, onsite erection and the pertinent costs, composite walling system with flat steel plates and conventional headed studs (Case 1) was the focus of present study. Specifically, additional headed studs were pre-welded inside the front wall plates to enhance the joint performance. On this basis, a series of parametric studies were conducted to assess the influences of five design parameters on the behaviour of bolted endplate wall-to-beam joints. The initial stiffness, plastic moment capacity, as well as the rotational capacity of the composite wall-to-beam joints based on the numerical analysis were further compared with the current design provision.

• Steel and Composite Structures
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• v.46 no.4
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• pp.451-469
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• 2023

The use of precast hollow-core slabs (PCHCS) in civil construction has been increasing due to the speed of execution and reduction in the weight of flooring systems. However, in the literature there are no studies that present a finite element model (FEM) to predict the load-slip relationship behavior of pushout tests, considering headed stud shear connector and PCHCS placed at the upper flange of the downstand steel profile. Thus, the present paper aims to develop a FEM, which is based on tests to fill this gap. For this task, geometrical non-linear analyses are carried out in the ABAQUS software. The FEM is calibrated by sensitivity analyses, considering different types of analysis, the friction coefficient at the steel-concrete interface, as well as the constitutive model of the headed stud shear connector. Subsequently, a parametric study is performed to assess the influence of the number of connector lines, type of filling and height of the PCHCS. The results are compared with analytical models that predict the headed stud resistance. In total, 158 finite element models are processed. It was concluded that the dynamic implicit analysis (quasi-static) showed better convergence of the equilibrium trajectory when compared to the static analysis, such as arc-length method. The friction coefficient value of 0.5 was indicated to predict the load-slip relationship behavior of all models investigated. The headed stud shear connector rupture was verified for the constitutive model capable of representing the fracture in the stress-strain relationship. Regarding the number of connector lines, there was an average increase of 108% in the resistance of the structure for models with two lines of connectors compared to the use of only one. The type of filling of the hollow core slab that presented the best results was the partial filling. Finally, the greater the height of the PCHCS, the greater the resistance of the headed stud.

• International Journal of Computer Science & Network Security
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• v.23 no.3
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• pp.67-80
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• 2023

Rice is an important food crop for most of the population in Nowadays, psychologists consider social media an important tool to examine mental disorders. Among these disorders, depression is one of the most common yet least cured disease Since abundant of writers having extensive followers express their feelings on social media and depression is significantly increasing, thus, exploring the literary text shared on social media may provide multidimensional features of depressive behaviors: (1) Background: Several studies observed that depressive data contains certain language styles and self-expressing pronouns, but current study provides the evidence that posts appearing with self-expressing pronouns and depressive language styles contain high emotional temperatures. Therefore, the main objective of this study is to examine the literary cyber writers' posts for discovering the symptomatic signs of depression. For this purpose, our research emphases on extracting the data from writers' public social media pages, blogs, and communities; (3) Results: To examine the emotional temperatures and sentences usage between depressive and not depressive groups, we employed the SentiStrength algorithm as a psycholinguistic method, TF-IDF and N-Gram for ranked phrases extraction, and Latent Dirichlet Allocation for topic modelling of the extracted phrases. The results unearth the strong connection between depression and negative emotional temperatures in writer's posts. Moreover, we used Naïve Bayes, Support Vector Machines, Random Forest, and Decision Tree algorithms to validate the classification of depressive and not depressive in terms of sentences, phrases and topics. The results reveal that comparing with others, Support Vectors Machines algorithm validates the classification while attaining highest 79% f-score; (4) Conclusions: Experimental results show that the proposed system outperformed for detection of depression trends in literary cyber writers using sentiment analysis.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.1-13
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• 2023

YouTube has become a popular platform for vlogs. Among various forms of vlogs, office worker vlogs, in which a person engaged in a specific job shows his/her work environment and daily routine, are gaining popularity. Thus, focusing on office worker vlogs, the present research investigates the effects of office worker vlogs' characteristics (i.e., vlog content characteristics, vlogger characteristics) on the YouTube viewers' educational value of the vlog and their job engagement. Specifically, this research examines whether(1) vlog content characteristics (i.e., usefulness, accessibility, and vividness) and (2) vlogger characteristics (i.e., job similarity, credibility, and expertise) influence the YouTube viewers' educational value of the vlog. Moreover, this research examines how the YouTube viewers' educational value of the vlog affects their job engagement. With a sample of YouTube viewers of office worker vlogs (N = 215), structural equation modelling was implemented to investigate the relationships in the proposed model. The results indicate that (1) perceived usefulness of the office worker vlog is positively associated with the educational value of the vlog; (2) perceived accessibility of the office worker vlog is positively associated with the educational value of the vlog, albeit marginally significant; (3) perceived vividness of the office worker vlog is positively associated with the educational value of the vlog; (4) perceived job similarity to the office worker vlogger is positively associated with the educational value of the vlog; (5) perceived credibility of the office worker vlogger is positively associated with the educational value of the vlog; (6) perceived expertise of the office worker vlogger is positively associated with the educational value of the vlog; and (7) the educational value of the office worker vlog is positively associated with the YouTube viewers' job engagement. The findings provide important implications for the production and use of office worker vlog contents.

• Journal of the Korean Geotechnical Society
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• v.25 no.10
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• pp.41-53
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• 2009

In order to analyze the influence of particle shape on evolution of particle crushing and characteristic of shear behavior of granular soil, direct shear test was simulated by using DEM (Discrete Element Method). Six particle shapes were generated by clump and cluster model built in PFC (Particle Flow Code). The results of direct shear test for six particle shapes were compared and analyzed with those for circular particle shape. The results of numerical tests showed a good agreement with those of experimental tests, thus the appropriateness of numerical modelling set in this study was proved. As for particle shape, more angular and rougher particle induced larger internal friction angle and more particle crushing than relatively round and smooth particle. When particles were crushed, crushing was concentrated on the shear band adjacent to the shear plane. Finally, it can be concluded that the numerical models suggested in this study can be used extensively for other studies concerning the shear behavior of granular soil including soil crushing.

• Journal of Korean Neurosurgical Society
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• v.66 no.4
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• pp.382-392
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• 2023

Objective : The use of indocyanine green videoangiography (ICG-VA) to assess blood flow in the brain during cerebrovascular surgery has been increasing. Clinical studies on ICG-VA have predominantly focused on qualitative analysis. However, quantitative analysis numerical modelling for time profiling enables a more accurate evaluation of blood flow kinetics. In this study, we established a multiple exponential modified Gaussian (multi-EMG) model for quantitative ICG-VA to understand accurately the status of cerebral hemodynamics. Methods : We obtained clinical data of cerebral blood flow acquired the quantitative analysis ICG-VA during cerebrovascular surgery. Varied asymmetric peak functions were compared to find the most matching function form with clinical data by using a nonlinear regression algorithm. To verify the result of the nonlinear regression, the mode function was applied to various types of data. Results : The proposed multi-EMG model is well fitted to the clinical data. Because the primary parameters-growth and decay rates, and peak center and heights-of the model are characteristics of model function, they provide accurate reference values for assessing cerebral hemodynamics in various conditions. In addition, the primary parameters can be estimated on the curves with partially missed data. The accuracy of the model estimation was verified by a repeated curve fitting method using manipulation of missing data. Conclusion : The multi-EMG model can possibly serve as a universal model for cerebral hemodynamics in a comparison with other asymmetric peak functions. According to the results, the model can be helpful for clinical research assessment of cerebrovascular hemodynamics in a clinical setting.