The selection of a suitable gridding method for the interpolation of input dataset has always been a big challenge. In this study, a dimensionality reduction-based analysis is proposed, in order to find, a suitable interpolator for the mapping of solar irradiation. For this purpose, sunshine duration data for the period of 3 years obtained from 50 meteorological stations was used to predict solar radiations based on Angstrom-Prescott model. Different gridding methods including; Inverse distance to a power, Kriging, Local polynomial, Moving average, Minimum curvature, Modified Shepard’s method, Nearest neighbor, Polynomial regression and Radial basis function were used to interpolate monthly mean daily global solar irradiation. Results show that an average estimated global horizontal solar irradiation (GHI) across the Pakistan range between 4.50-6.00 kWh/m2/day. Using SPSS software package (version 23), a dimensionality reduction-based technique i.e. principal component analysis (PCA) was employed to choose a suitable interpolator for the mapping of solar irradiation in Pakistan. Based on the results of PCA, Kriging was considered as the most suitable interpolation method among all interpolators used in this analysis. To validate the results of PCA, interpolated GHI maps were compared with the solar atlas developed by the World Bank’s Energy Sector Management Assistance Program (ESMAP). The estimated value of performance indicators showed that the Kriging had comparatively lowest value of mean absolute error (MAE) and root mean square error (RMSE). The outcomes of this study will be useful in the analysis and planning of solar energy development at the local and regional level.

Ontologies remain the focal asset for the effective functioning of semantic search approaches, as they’re able to describe concepts based on a uniform and common vocabulary providing a machine-readable and shareable format. Nowadays, the challenge concerning ontologies exceeds their conception and creation, as a multitude of ontologies are proposed in various domain of applications. Thus, the effective challenge consists of evaluating those ontologies in order to choose the fitting and suitable one. In this paper, we present a new approach to select the convenient ontologies from a set of candidate ontologies by ranking them according to predefined criteria. Our approach takes into account not only the taxonomic structure but also the semantic aspect of the ontology. In addition, we insist on both semantic relations and specific concepts, which must be favored since they reflect the semantic richness of the ontology. By comparing it with a concept-based one, our method shows encouraging results regarding the final selection of ontologies for each document to annotate; when comparing both of methods, the sorting order becomes more accurate and precise since the concept centrality and the type of relations linking it to the other concepts are the main factors that made the difference.

This paper investigated multi-objective seismic damage assessment procedure. Primarily, it estimates damage Index (DI) of RC framed residential buildings under the seismic ground motions, considering the code provisions (IS-1893-2016) in seismic zone-V in India. Three dimensional DI has been estimated for a four storey building by Park-Ang (1985) method. With increasing storey number, calculation of Park-Ang DI becomes tedious and more time consuming procedure; therefore this method is not suitable for large scale damage investigation. To avoid the complexity, a simplified method has been proposed to estimate global damage index (GDI) easily for buildings. In this study, it is important to observe the position of local damage concentration along the height of the building and their percentage contribution to the global DI (GDI). In this study, it is also observed that ground floor is experiencing maximum damage and 4th floor is experiencing least damage in a four storey building. To describe the worst damage scenario most vulnerable storey DI could be considered as global DI rather than whole structure’s global DI and found a good agreement between highest local DI and GDI through the present study. Based on this study, it has been observed that 0.893 times ground storey DI (i.e. local DI) estimates similar GDI for a four storey building; instead of considering all members’ individual DI finally that reduces the computational time. Most influential response parameters are directly contributing the global damage of the structure known as engineering demand parameters (EDPs) and estimated/identified through sensitivity analysis and presented in the form of correlation matrix. A relationship (both individual and combined) between DI and EDPs has been proposed to estimate the GDI of the structure easily with less effort.

The article proves the inaccuracy of the Riemann theorem on the in applicability of the commutative law to conditionally convergent series. The existing misconception is not harmless. After all, the imaginary in applicability of the commutation law to such series draws far-reaching consequences, namely the inadmissibility of the summation and subtraction of such series, their multiplication or division. All these operations are performed with absolutely convergent series, allowing you to solve problems of numerical analysis, but the consequences of the Riemann theorem (erroneous) deprive the mathematics of the basic tools of numerical analysis in operations with conditionally convergent series.

Internet banking is one of the new services in Iranian banking system. The purpose of this study is to measure internet service quality and to find out the determinants that mainly affect the customer satisfaction and commitment of internet banking amongst genders and different age group. Also, we investigate difference internet service quality between banks with different ownership. In Iran, there is 5 kind of banks and it is very important to investigate the quality of Internet banking in all of them. For this purpose, we used a statistical method, Factor Analysis method, and OLS regression, with SPSS 22. A sample of 40 Internet banking customers was used to gather data, which was further utilized to find out how major determinants affect the customer service quality perception of Internet banking. The research found that 1. Cronbach\'s Alpha for a total of question is 0.95, which shows the questionnaire is reliable; 2.Privatized banks are more qualified than others, 3. The statistical test result (KMO =0.504, Bartlett\'s Test of Sphericity 566.301, Significance 0.000) indicate that the factor analysis method is appropriate, 4. The 21 items are reduced to five factors with eigenvalues greater than 1.0, which are retained for subsequent analysis,5. Given high coefficients of determination in two models (0.607 and 0.574), the scale of Internet-based service quality proved reliable in predicting customer satisfaction and commitment to using Internet banking.

The paper presents an original method of identifying suitable Augmented Reality (AR)-based learning systems including learning content (i.e. learning objects) and activities necessary for particular user/learner. AR is often used in environmental education to enhance students’ motivation by visualizing learning content and activities. The method is aimed to personalise learning by applying Felder-Silverman learning styles model and intelligent technologies and thus to ensure that suitable AR-based learning systems should be selected for particular users to improve their learning motivation, quality and efficiency. The method of identifying students preferring to actively use AR-based learning systems is based on identification of probabilistic suitability indexes to choose the most suitable AR-based learning systems for particular students and acquire these products in the market. Literature review on AR application in education, presented in the paper, has revealed that the possibilities of AR application in education bring many advantages to students of all ages. The research is multidisciplinary, including education, computer science, engineering, operational research and psychology areas. Application of the personalisation method presented here may be extended beyond the education area and used in e.g. e-commerce to apply AR for particular customers’ needs.

This study was aimed at analyzing and assesing the financial and non-financial performance of captured fishery industries in Bengkulu province by comparing among various fishing gears. This research based on a survey from 60, 76, 10, and 12 fishermen of fishing fleets with Gillnet, handline, floating bagan, and purse seine fishing gears respectively. Two financial indicators were used to measure, i.e., profitability measured by Net Profit Margin, and business efficiency indicated by Revenue Cost Ratio and Benefit-Cost ratio. The non-financial indicator used in this research include productivity of fishing crew measured in the basis of per trip, per day and per day per vessel size. One Way ANOVA and t-test for independent samples are used for different test analysis Research found that economically every fishing gear is efficient. Overall, purse seine fishing gear was the most efficient and profitable fishing gear. This research also found that in term of non-financial performance, the fishing crew of purse seine per trip was the highest productivity but the lowest when fishing day and vessel size under consideration. However, when using productivity per day per GT and per Crew, purse seine is the lowest