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Combining an online and traditional mode of learning is a significant challenge for third world countries. To face this challenge, educational institutions around the world adopted the strategies of blended learning (BL). This research aims to determine the factors affecting readiness to diffuse BL in Pakistani higher education institutions.

“Partial least squares structural equation modeling (PLS-SEM)” was used based on a suitable sample of 228 participants in Karachi, Pakistan.

The results reveal that resource support, management strategies (MSs) and technology infrastructure (TI) are positively and significantly associated with readiness to diffuse BL. However, institutional structure (IS) and ethical consideration (EC) have a positive but insignificant link with readiness to diffuse BL.

The research is reasonably required as research in the Karachi Pakistani context is scarce. Additionally, this study analyses the possibility of modern skills and techniques to diffuse BL in higher education in Pakistan.

As a strand in industrialization movement in architecture, engineering and construction (AEC) industry, prefabricated construction (PC) has gained widespread popularity due to high efficiency, energy saving, low environmental impacts, safety and other advantages of PC. Well-managed supply chain can further leverage the advantages of PC. However, there is a lack of more systematically overview of the prefabricated construction supply chain (PCSC). This paper aims to comb the current status and look into the future direction of PCSC by reviewing the existing research.

In total, 131 articles related to prefabricated construction supply chain management (PCSCM) from 2000 to 2022 have been collated to (1) conduct a bibliometric analysis by using VOSviewer, including the literature sources, keywords co-occurrence, co-authorships, authorship citation and country active in the field of PCSCM; (2) classify and summarize the status of research in PCSCM through qualitative discussion and (3) point out the future research directions.

In total, 131 articles are carried out for bibliometric analysis and in-depth qualitative discussion, the visualization maps and the main research themes in the field of PCSCM are obtained. The results show that supply chain intelligentization and informatization are hot topics. Finally, future research directions that should be paid attention to in the field of PCSCM are pointed out.

This study can help project managers understand the current status and problems of PCSC operations and provide a basis for future management decisions.

Compared with previous studies, this study adds the dimension of “article authorship” to the quantitative analysis and discusses the research themes in the field of PCSCM in a comprehensive manner. In addition, this paper deeply discusses the main research topics from both the specific contents and research methods adopted.

This paper presents a new surface reconstruction method based on complex form functions, genetic algorithms and neural networks. Surfaces can be reconstructed in an analytical representation format. This representation is optimal in the sense of least‐square fitting by predefined subsets of data points. The surface representations are achieved by evolution via repetitive application of crossover and mutation operations together with a back‐propagation algorithm until a termination condition is met. The expression is finally classified into specific combinations of basic functions. The proposed method can be used for CAD model reconstruction of 3D objects and free smooth shape modelling. We have implemented the system demonstration with Visual C++ and MatLab to enable real time surface visualisation in the process of design.

This research aims to develop an effective and efficient algorithm for solving the curve fitting problem arising in automated manufacturing systems.

This paper takes curve fitting as an optimization problem of a set of data points. Expressing the data as a function will be very effective to the data analysis and application. This paper will develop the stochastic optimization method to apply to curve fitting. The proposed method is a combination optimization method based on pattern search (PS) and simulated annealing algorithm (SA).

The proposed method is used to solve a nonlinear optimization problem and then to implement it to solve three circular arc‐fitting problems of curve fitting. Based on the analysis performed in the experimental study, the proposed algorithm has been found to be suitable for curve fitting.

Curve fitting is one of the basic form errors encountered in circular features. The proposed algorithm is tested and implemented by using nonlinear problem and circular data to determine the circular parameters.

The developed machine vision‐based approach can be an online tool for measurement of circular components in automated manufacturing systems.

The purpose of this paper is to design and fabricate a three-dimensional (3D) bionic airflow sensing array made of two multi-electrode piezoelectric metal-core fibers (MPMFs), inspired by the structure of a cricket’s highly sensitive airflow receptor (consisting of two cerci).

A metal core was positioned at the center of an MPMF and surrounded by a hollow piezoceramic cylinder. Four thin metal films were spray-coated symmetrically on the surface of the fiber that could be used as two pairs of sensor electrodes.

In 3D space, four output signals of the two MPMFs arrays can form three “8”-shaped spheres. Similarly, the sensing signals for the same airflow are located on a spherical surface.

Two MPMF arrays are sufficient to detect the speed and direction of airflow in all three dimensions.

The aim of this paper is to examine the underlying consumer behavior model of Facebook marketing for hotels, including the determinants, the process and the consequences of hotel Facebook marketing, as Facebook – the most popular social media platform – has become an important marketing tool for hotels.

The study proposed an integrated model consisting of antecedents and consequences of Facebook marketing based on both marketing and social psychology theories. A pseudo hotel Facebook page was created and an online survey was conducted to collect data. Structural equation modeling (SEM) was utilized to test the proposed model.

The SEM results indicated the proposed model to be a good fit with the data and all the hypotheses were supported except one. The findings suggested that compliance, internalization and identification are all determinants of the customer’s attitude toward a hotel Facebook page, while hotel booking intentions and intention of spreading word-of-mouth on Facebook are two consequences of hotel Facebook marketing.

The study used a pseudo hotel Facebook page and messages created solely for the purpose of the study, and so the survey participants might not be hotel guests or hotel Facebook fans. Future research using real hotel brands, “live” hotel Facebook pages and actual hotel guests or hotel Facebook fans to collect data may provide stronger support for the integrated model proposed in the study.

The attitude toward a hotel Facebook site is influenced by the site’s congruency with the customer’s value system and personal identity with other users rather than external rewards. Hotel booking intentions and spreading word-of-mouth are two significant consequences of hotel Facebook marketing. Hotels should aim to create an interactive site for users and establish communities with a clear identity so that users can easily relate their own self-identity with other group members and maintain satisfying relationships with them.

This is a preliminary and exploratory study of the fundamental marketing mechanism of hotel Facebook marketing. The proposed model reveals not only the antecedents but also the consequences of hotel Facebook marketing. The study and the proposed model may be used as a starting point for further hospitality Facebook marketing research.

In the community of visual tracking or object tracking, discriminatively learned correlation filter (DCF) has gained more importance. When it comes to speed, DCF gives the best performance. The main objective of this study is to anticipate the object visually. For tracking the object visually, the authors proposed a new model based on the convolutional regression technique. Features like HOG & Harris are used for the process of feature extraction. The proposed method will give the best results when compared to other existing methods.

This paper introduces the concept and research status of tracks; later the authors focus on the representative applications of deep learning in visual tracking.

Better tracking algorithms are not mentioned in the existing method.

Visual tracking is the ability to control eye movements using the oculomotor system (vision and eye muscles working together). Visual tracking plays an important role when it comes to identifying an object and matching it with the database images. In visual tracking, deep learning has achieved great success.

The authors implement the multiple tracking methods, for better tracking purpose.

The main theme of this paper is to review the state-of-the-art tracking methods depending on deep learning. First, we introduce the visual tracking that is carried out manually, and secondly, we studied different existing methods of visual tracking based on deep learning. For every paper, we explained the analysis and drawbacks of that tracking method. This paper introduces the concept and research status of tracks, later we focus on the representative applications of deep learning in visual tracking.

The purpose of this study is to provide a progress review of published Internet marketing research within the top eight hospitality and tourism journals and to provide suggestions on future research directions.

The study collected 331 Internet marketing-related articles published in the top eight hospitality and tourism journals during the period of 1996-2013. Using content analysis, the study analyzed and discussed research topics, research methods and industry sectors of selected articles. The study period was broken into three sub-periods and used correspondence analysis (CA) to examine the significant changes of topical areas over time. A follow-up CA was conducted to compare the topical and methodological preferences of the selected eight journals.

In all, 5-category and 27-subcategory classifications of research topics were identified in the study. The two-dimensional perceptual map indicates that Internet marketing research in the hospitality and tourism fields experienced introduction, growth and maturity stages. The research focus changed from business perspective to customer perspective and then to both business and customer perspectives. The eight top hospitality and tourism journals were grouped into four journal sets that share similar article characteristics and preferences.

Due to the sample size, the classifications and trends generated in this study may not be generalized to all Internet marketing research in hospitality and tourism disciplines. The process of identifying topic and method categories might be biased, especially in identifying new topics. Future research may apply CA method in literature review studies on other research topics.

The study analyzed published research in Internet marketing in the hospitality and tourism fields and provided topical and methodological recommendations to academia for future research. This study may also give hospitality managers new insights into Internet marketing applications in the industry.

This study is one of the few attempts to provide a comprehensive review of Internet marketing research in the hospitality and tourism fields. This study uses CA in literature review study, opening up a new way to easily analyze and visually display the literature trends. This study also creatively compared the publication preferences among eight top-tier hospitality and tourism journals using correspondence analysis.

This paper examines the effect of intellectual capital (IC) and market capitalization (MC) on corporate investment decisions (ID) through the mediating and moderating effects of knowledge/information sharing (KS) and the Covid-19 pandemic.

With the use of SPSS 26 and SmartPLS version 3.0, the partial least square structural equation modelling (PLS-SEM) technique is employed with 1,036 observations to examine the effects.

Our findings show that IC and social interactions (SI) have a positive effect on KS. KS affects positively both MC and ID. KS has the mediating and moderating effects while the Covid-19 has the moderating impact on ID.

This research suggests that company leaders should understand the important role of IC and MC in enhancing ID through KS. They should pay attention to MC to enhance their investment and SI among employees, partners, consumers and authorities should be encouraged.

This research contributes to the existing literature by employing the perceptual scale to examine the effect of IC and MC, the mediating and moderating effects of KS, and analyze the moderating role of the Covid-19 on ID. It also expands the current models by including the Covid-19 and MC to clarify the ID determinants. New measurements of MC and the Covid-19 constructed are also another contribution.