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In Bangladesh, there are only 0.2 million Internet users out of a population of 140 million. Because there is a lack of academic research on Internet usage, the prime objective of this study is to report the level of Internet use by university academics for their information and communication needs. The study also sought to find out whether differences exist among the various levels of academics in terms of their use of the Internet. Six categories of information and communication needs were identified and a survey conducted among the lecturers of Rajshahi University where the Internet was introduced in 2001. Findings showed that Internet use by academics is useful for some common needs and that the academic rank of users is an important factor in determining the priority of needs. It also showed that there are some barriers to adequate use of Internet resources. Suggestions are made for increased use of the Internet, to benefit the nation as a whole.

To evaluate the magnitude of public library uses and resulting values among the general people with associated socio‐economic‐cultural features of Bangladesh and thus to indicate strategies for better library impact in societal, cultural and economic development.

Primary data were collected from the users of four public libraries in the cities of Dhaka and Rajshahi considering rich library profiles and wide variety of users. Interviews were conducted based on a structured questionnaire by visiting the sample libraries that also result in studying the users and libraries closely.

Some factors like age, income, education, and gender are very important in using public library in relation to particular socio‐economic features of Bangladesh. Though the study reveals dissatisfaction in library resources, it shows a strong library impact on recreation and culture, self‐learning, social welfare, and on economic development of the country. The findings lead some recommendations for improved utilization of library.

The paper provides focus on studying the demographic variables of users to measure public library values and benefits in the areas of learning, recreation, culture, social welfare, and development.

Concerned authorities should come forward to minimize the funding and administrative barriers to make public library exclusively worthy to all with quality access.

Studying social factors are unavoidable to understand the magnitude of social inclusiveness of libraries and their strength of impact, and importantly, to ascertain the ways of comprehensive access to libraries by acquiring indication of realistic policy implementation from empirical evidence.

Development of an effective search system and interface largely depends on usability studies. The aim of this paper is to present the results of an empirical evaluation of a prototype web site search and browsing tool based on multidimensional taxonomies derived from the use of faceted classification.

A prototype Faceted Classification System (FCS), which classifies and organizes web documents under different facets (orthogonal sets of categories), was implemented on the domain of an academic institute. Facet are created from content oriented metadata, and then assembled into multiple taxonomies that describe alternative classifications of the web site content, such as by subject and location. The search and browsing interfaces use these taxonomies to enable users to access information in multiple ways. The paper compares the FCS interfaces to the existing single‐classification system to evaluate the usability of the facets in typical navigation and searching tasks.

The findings suggest that performance and usability are significantly better with the FCS in the areas of efficient access, search success, flexibility, understanding of content, relevant search result, and satisfaction. These results are especially promising since unfamiliarity often leads users to reject new search interfaces.

The results of the study in this paper can significantly contribute to interface research in the IR community, emphasizing the advantages of multidimensional taxonomies in online information collections.

The aim of this paper is to develop and implement a multidimensional classification system in the web that can provide an alternative but convenient structure for organising and finding information content.

A prototype system is developed following the views of Ranganathan's faceted classification, which is to provide multiple classifications of the web documents through content oriented metadata organised under different facets (orthogonal groups of categories).

Based on an architectural framework this study demonstrates a prototype faceted classification system (FCS) that is integrated into a general open‐source content management system and populated with a sample collection of institutional web pages/documents.

The study provides significant grounds for the IR community to improve interface structure for easy access, management, and retrieval of web information. In addition, the integration of content management tools with multidimensional taxonomies can be a new instance of a corporate web system for easy content creation, organisation, and navigation.

The purpose of this paper is to develop and implement a faceted classification structure to improve web information organization, access and navigability.

Some case studies of commercial web sites using faceted metadata were analyzed to develop the classification approach. The proposed framework adapts the facet analysis theory from Faceted Classification System (FCS) to use semantic web tools especially XML and RDF store, and ontology, and is designed to be integrated within a Content Management System (CMS). A detailed example of a faceted classification system for an academic information system is used to demonstrate the construction of an FCS from metadata.

Detailed examples show how classifying and organizing information in multidimensional hierarchies is more accessible than simple one‐dimensional taxonomic hierarchies.

A prototype, based on the proposed framework, is being developed using the web site of an academic institution as a case study.

Enhances the FCS research with a notion of integrating ontology driven faceted classification structures by XML/RDF language and content management tools. A dynamic approach to organizing and searching web information provides users with multiple ways of accessing information based on their knowledge and information needs.

There is a strong prerequisite for organizations to analyze customer review behavior to evaluate the competitive business environment. The purpose of this study is to analyze and predict customer reviews of halal restaurants using machine learning (ML) approaches.

The authors collected customer review data from the Yelp website. The authors filtered the reviews of only halal restaurants from the original data set. Following cleaning, the filtered review texts were classified as positive, neutral or negative sentiments, and those sentiments were scored using the AFINN and VADER sentiment algorithms. Also, the current study applies four machine learning methods to classify each review toward halal restaurants into its sentiment class.

The experiment showed that most of the customer reviews toward halal restaurants were positive. The authors also discovered that all of the methods (decision tree, linear support vector machine, logistic regression and random forest classifier) can correctly classify the review text into sentiment class, but logistic regression outperforms the others in terms of accuracy.

The results facilitate halal restaurateurs in identifying customer review behavior.

Sentiment and emotions, according to appraisal theory, form the basis for all interactions, facilitating cognitive functions and supporting prospective customers in making sense of experiences. Emotion theory also describes human affective states that determine motives and actions. The study looks at how potential customers might react to a halal restaurant’s consensus on social media based on reviewers’ opinions of halal restaurants because emotions can be conveyed through reviews.

This study applies machine learning approaches to analyze and predict customer sentiment based on the review texts toward halal restaurants.

This paper aims to accentuate the behavior of second-grade hybrid Al₂O₃–Cu nanofluid flow and its thermal characteristics driven by a stretching/shrinking Riga plate.

The second-grade fluid is considered with the combination of Cu and Al₂O₃ nanoparticles. Three base fluids namely water, ethylene glycol (EG) and methanol with different Prandtl number are also examined. The formulation of the mathematical model of second-grade hybrid nanofluid complies with the boundary layer approximations. The complexity of the governing model is reduced into a simpler differential equations using the similarity transformation. The bvp4c solver is fully used to solve the reduced equations. The observation of multiple solutions is conducted for the assisting (stretching) and opposing (shrinking) cases.

The impact of suction parameter, second-grade parameter, electromagnetohydrodynamics (EMHD) parameter, velocity ratio parameter and the volumetric concentration of the alumina and copper nanoparticles are numerically analyzed on the velocity and temperature profiles, skin friction coefficient and local Nusselt number (thermal rate) of the second-grade Al₂O₃–Cu/water. The solution is unique when (static and stretching cases) while dual for a specific range of negative in the presence of suction effect. Based on the appearance of the first solution in all cases of, it is physically showed that the first solution is stable. Further examination reveals that the EMHD and suction parameters are the contributing factors for the thermal enhancement of this non-Newtonian working fluid. Meanwhile, the viscosity of the non-Newtonian fluid also plays a significant role in the fluid motion and heat transfer rate based on the finding that the EG base fluid produces the maximum heat transfer rate but the lowest critical value and skin friction coefficient.

The results are novel and contribute to the discovery of the hybrid nanoparticles’ performance in the non-Newtonian second-grade fluid. Besides, this study is beneficial to the researchers in this field and general audience from industries regarding the factors, which contributing to the thermal enhancement of the working fluid.

This paper aims to investigate the effects of economic growth, population density and international trade on energy consumption and environmental quality in India.

Taking annual data of 1971-2011, autoregressive distributed lag bounds testing technique is applied to explore the long run link between the series. The Granger causality test is used to determine the direction of causality between the variables.

The obtained results confirm the cointegration of variables, and economic growth and population density are found to have significant positive effects on energy consumption in both the short and long runs. CO₂ emissions are also positively and significantly affected by population density and energy consumption, and negatively affected by economic growth.

The paper is original and valuable in the sense that it has considered two relevant additional explanatory variables, namely, population density and trade openness, which got little attention in the past. This research is an improvement over the previous studies because it has looked at the separate effects of explanatory variables on energy consumption, in addition to the effects on carbon emissions. Therefore, the findings of this research are more reliable because this adopted methodology is better and extensive, and the authors have properly addressed the issue of omitted variable bias.