• Trans-
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• v.14
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• pp.65-92
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• 2023

The knowledge of the narrative agent not only constitutes the content and meaning of the narrative itself, but is also closely related to the emotional response of the recipient. Also, the disparity of knowledge between narrative agents is an important factor in making a narrative richer and more interesting. But It tends to be treated as a sub-topic of narration theory or genre/style studies rather than an independent subject of narrative studies or criticism. In this paper, I propose a model that can systematically and quantitatively analyze the knowledge of narrative agents. The proposed model consists of the knowledge structure that represents a narrative, the knowledge state that expresses the knowledge of narrative agent as a degree of belief, and the knowledge flow that means changes in the knowledge state according to the development of events. In addition, the formal notation of the knowledge structure and a probabilistic inference model that could obtain the state of knowledge were proposed, and the knowledge structure and knowledge flow were analyzed by applying the model to the actual narrative. It is expected that the proposed model will be of practical help in the creation and evaluation of narratives.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.273-283
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• 2021

The aim of this paper is to review the current knowledge management (KM) practices and their importance in the public sector of Saudi Arabia. Using the term "knowledge management in public sector", a search for available works was done in Google Scholar. In the first stage, the search for literature published under anytime choice was done in the first 10 pages of the search engine. Then another nine pages of Goggle Scholar were searched for more recent works published setting the time as 2014 to 2018. The search yielded 37 usable works for this review. The results of this literature search and review indicated that out of the 37 works reviewed, only three works were related to Saudi Arabia. Number of papers on factors of KM were maximum, many of them giving diagrammatic presentation of their results. KM modelling itself is not easy as only very few papers on KM modelling were available. Problems of too much reliance on qualitative data and hypotheses not matching with the literature backgrounds for them were also found. Considering the works related to KM, the number of papers in various categories may indicate the dimensions of KM to be considered when KM is implemented or evaluated in any public sector of any country. This applies to Saudi Arabian public sector organizations also. There is a fertile ground of research waiting to be investigated by researchers in Saudi Arabia.

• The Plant Pathology Journal
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• v.33 no.6
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• pp.529-542
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• 2017

Control of plant diseases is largely dependent on use of agrochemicals. However, there are widening gaps between our knowledge on plant diseases gained from genetic/mechanistic studies and rapid translation of the knowledge into target-oriented development of effective agrochemicals. Here we propose that the time is ripe for computer-aided drug discovery/design (CADD) in molecular plant pathology. CADD has played a pivotal role in development of medically important molecules over the last three decades. Now, explosive increase in information on genome sequences and three dimensional structures of biological molecules, in combination with advances in computational and informational technologies, opens up exciting possibilities for application of CADD in discovery and development of agrochemicals. In this review, we outline two categories of the drug discovery strategies: structure- and ligand-based CADD, and relevant computational approaches that are being employed in modern drug discovery. In order to help readers to dive into CADD, we explain concepts of homology modelling, molecular docking, virtual screening, and de novo ligand design in structure-based CADD, and pharmacophore modelling, ligand-based virtual screening, quantitative structure activity relationship modelling and de novo ligand design for ligand-based CADD. We also provide the important resources available to carry out CADD. Finally, we present a case study showing how CADD approach can be implemented in reality for identification of potent chemical compounds against the important plant pathogens, Pseudomonas syringae and Colletotrichum gloeosporioides.

• Nuclear Engineering and Technology
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• v.42 no.2
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• pp.145-150
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• 2010

The paper is describing work being developed in the frame of a 5-year IAEA Coordinated Research Programme (CRP) started in late 2005. Participants gained knowledge of modelling methodologies and experience in the development and use of rather sophisticated simulation tools in support of site characterization and performance assessment calculations. These goals were achieved by a coordinated effort, in which the advantages and limitations of numerical models are examined and demonstrated through a comparative analysis of simplified, illustrative test cases. This knowledge and experience should help them address these issues in their own country's nuclear waste program. Coordination efforts during the first three years of the project aimed at enabling this transfer of expertise and maximizing the learning experience of the participants as a group. This was accomplished by identifying common interests of the participants (i.e., Process Modelling and Total System Performance Assessment methodology), and by defining complementary tasks that are solved by the members. Synthesis of all available results by comparative assessments is planned in the coming months. The project will be completed end of 2010. This paper is summarizing activities up to November 2009.

• Coupled systems mechanics
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• v.11 no.1
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• pp.79-91
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• 2022

Models for water treatment processes include simulation, i.e., modelling of water quality, flow hydraulics, process controls and design. Water treatment processes are inherently dynamic because of the large variations in the influent water flow rate, concentration and composition. Moreover, these variations are to a large extent not possible to control. Mathematical models and computer simulations are essential to describe, predict and control the complicated interactions of the water treatment processes. An accurate description of such systems can therefore result in highly complex models, which may not be very useful from a practical, operational point of view. The main objective is to combine knowledge of the process dynamics with mathematical methods for processes estimation and identification. Good modelling practice is way to obtain this objective and to improve water treatment processes(its understanding, design, control and performance- efficiency). By synthesize of existing knowledge and experience on good modelling practices and principles the aim is to help address the critical strategic gaps and weaknessesin water treatment models application.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.714-718
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• 2005

Knowledge management (KM) continues to receive mounting interest within the construction industry due to its potential to offer solutions for organisations seeking competitive advantage. This paper presents a KM input-process-output conceptual model comprising unique and well-defined theoretical constructs representing KM practices and their internal and external determinants in the context of construction. The paper also presents the underlying principles used in operationally defining each construct using extant KM literature, and offers a number of testable hypotheses that capture the inter-relationships between the identified constructs.

• Computers and Concrete
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• v.25 no.4
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• pp.369-382
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• 2020

This paper presents a discussion of the Finite Element Analysis (FEA) when applied for the analysis of concrete elements reinforced with glass fibre reinforced polymer (GFRP) bars. The purpose of such nonlinear FEA model development is to create a tool that can be used for numerical parametric studies which can be used to extend the existing (and limited) experiment database. The presented research focuses on the numerical analyses of concrete beams reinforced with GFRP longitudinal and shear reinforcements. FEA of concrete members reinforced with linear elastic brittle reinforcements (like GFRP) presents unique challenges when compared to the analysis of members reinforced with plastic (steel) reinforcements, which are discussed in the paper. Specifically, the behaviour and failure of GFRP reinforced members are strongly influenced by the compressive response of concrete and thus modelling of concrete behaviour is essential for proper analysis. FEA was performed using the commercial software ABAQUS. A damaged-plasticity model was utilized to simulate the concrete behaviour. The influence of tension, compression, dilatancy, mesh, and reinforcement modelling was studied to replicate experimental test data of beams previously tested at the University of Waterloo, Canada. Recommendations for the finite element modelling of beams reinforced with GFRP longitudinal and shear reinforcements are offered. The knowledge gained from this research allows for the development of a rational methodology for modelling GFRP reinforced concrete beams, which subsequently can be used for extensive parametric studies and the formation of informed recommendations to design standards.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.367-375
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• 2021

This study aimed to identify the knowledge structure of researches on 'untact' and derived implications for directions for the studies using text mining. The study included network analysis and topic modelling of keywords and abstracts from 171 thesis published until October 2020. Centrality analysis showed that 'untact' studies had been focused on service, usage, consumption, technology and online. From the topic modelling, 6 topics such as 'COVID-19 and socio-technological change', 'needs and utilization of education contents', 'technology and service for user convenience', 'product marketing and sales', 'service design of the company', 'influence factors of usage and consumption' were extracted. Keywords that connect each topic were technology, service, usage, consumption, needs and factor. Exploratory analysis of 'untact' researches using text mining provides useful results for development of 'untact' studies.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.295-300
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• 1998

Recently graphical modelling is being studied as a useful process analysis tool for exploratory causal analysis. Graphical modelling is a presentation method that uses graphs to describe statistical models of the structures of multivariate data. This paper describes an application of this graphical modeling with two cases from the automotive parts industry. One case is the unbalance problem of the pulley, an automotive generator part. There is multivariate data of the product from each of the processes which are connected in the series. By means of exploratory causal analysis between the variables using graphical modeling, the key processes which causes the variation of the final characteristics and their mechanism of the causal relationship have become clear. Another case is, also, the unbalanced problem of automotive starter parts which consists of many parts and is manufactured by complex machinery and assembling process. By means of the similar technique, the key processes are obtained easily and the results are reasonable from technical knowledge.

• Journal of Korean Institute of Industrial Engineers
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• v.10 no.1
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• pp.17-25
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• 1984

The use of Box-Jenkins technique is still very limited due to the high level of knowledge required in comprehending the technique and the cumbersome iterative procedure which requires a large amount of cost and time. This paper proposes a method of automating the univariate Box-Jekins modelling to overcome the limitations of subjective identification in iterative procedure by using Variate Difference method, D-statistic and Pattern Recognition algorithm combined with Akaike's Information Criterion. The results of the application to real data show that the average performance of automatic modelling procedure is better or not worse, at least, than those of the existing models which have been manually set up and reported in the literature.