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Student attritions in tertiary educational institutes may play a significant role to achieve core values leading towards strategic mission and financial well-being. Analysis of data generated from student interaction with learning management systems (LMSs) in blended learning (BL) environments may assist with the identification of students at risk of failing, but to what extent this may be possible is unknown. However, existing studies are limited to address the issues at a significant scale.

This study develops a new approach harnessing applications of machine learning (ML) models on a dataset, that is publicly available, relevant to student attrition to identify potential students at risk. The dataset consists of the data generated by the interaction of students with LMS for their BL environment.

Identifying students at risk through an innovative approach will promote timely intervention in the learning process, such as for improving student academic progress. To evaluate the performance of the proposed approach, the accuracy is compared with other representational ML methods.

The best ML algorithm random forest with 85% is selected to support educators in implementing various pedagogical practices to improve students’ learning.

L. Gǎvruţa (2012) introduced a special kind of frames, named K-frames, where K is an operator, in Hilbert spaces, which is significant in frame theory and has many applications. In this paper, first of all, we have introduced the notion of approximative K-atomic decomposition in Banach spaces. We gave two characterizations regarding the existence of approximative K-atomic decompositions in Banach spaces. Also some results on the existence of approximative K-atomic decompositions are obtained. We discuss several methods to construct approximative K-atomic decomposition for Banach Spaces. Further, approximative _d-frame and approximative _d-Bessel sequence are introduced and studied. Two necessary conditions are given under which an approximative _d-Bessel sequence and approximative _d-frame give rise to a bounded operator with respect to which there is an approximative K-atomic decomposition. Example and counter example are provided to support our concept. Finally, a possible application is given.

Twitter is the most widely used platform with an open network; hence, tourists often resort to Twitter to share their travel experiences, satisfaction/dissatisfaction and other opinions. This study is divided into two sections, first to provide a framework for understanding public sentiments through Twitter for tourism insights, second to provide real-time insights of three Indian heritage sites i.e., the Taj Mahal, Red Fort and Golden Temple by extracting 5,000 tweets each (n = 15,000) using Twitter API. Results are interpreted using NRC emotion lexicon and data visualisation using R.

This study attempts to understand the public sentiment on three globally acclaimed Indian heritage sites, i.e. the Taj Mahal, Red Fort and Golden temple using a step-by-step approach, hence proposing a framework using Twitter analytics. Extensive use of various packages of R programming from the libraries has been done for various purposes such as extraction, processing and analysing the data from Twitter. A total of 15,000 tweets from January 2015 to January 2021 were collected of the three sites using different key words. An exploratory design and data visualisation technique has been used to interpret results.

After data processing, 12,409 sentiments are extracted. Amongst the three tourists' spots, the greatest number of positive sentiments is for the Taj Mahal and Golden temple with approximately 25% each. While the most negative sentiment can be seen for the Red Fort (17%). Amongst the positive emotions, the maximum joy sentiment (12%) can be seen in the Golden Temple and trust (21%) in the Red Fort. In terms of negative emotions, fear (13%) can be seen in the Red fort. Overall, India's heritage sites have a positive sentiment (20%), which surpasses the negative sentiment (13%). And can be said that the overall polarity is towards positive.

This study provides a framework on how to use Twitter for tourism insights through text mining public sentiments and provides real- time insights from famous Indian heritage sites.

This study was designed to specifically explore confirmation and perceived usefulness associated with mobile food ordering apps (MFOAs) in consideration of their impacts upon attitudes, satisfaction and intention to continuously use.

The research utilized the convenience sampling to gather data from 250 respondents having prior experience with MFOAs during COVID-19 pandemic period in Bangladesh. The Structural Equation Modeling technique was applied to analyze the data using SmartPLS 3 software.

This study's results showed that customers' perceived confirmation and usefulness were significant in determining their dinning attitudes. Besides, customers' dining attitudes were positively related to e-satisfaction. Finally, the customers’ continuance intention to use MFOAs was significantly influenced by their e-satisfaction.

Restaurants managers should focus on online sales through MFOAs during the pandemic period since social distancing is a key strategy to manage COVID-19. Customers should be assured that the safety measures are undertaken while delivering the food.

This study incorporated the expectation-confirmation theory and technology acceptance model and tested it in the context of MFOAs.

This paper attempts to evaluate the impact of intellectual capital on bank performance in Bangladesh.

The authors analyze an unbalanced longitudinal data of 32 banks, which cover 318 observations of bank-year from 2010 to 2019. The study employs a dynamic panel model with the two-step system generalized methods of moments (SGMM).

The results show that bank performance is significantly positively affected by the intellectual capital (IC) in Bangladesh. In addition, the findings show that capital employed efficiency (CEE) is an essential determinant of bank performance rather than structural capital efficiency (SCE) and human capital efficiency (HCE) for the Bangladeshi banking sector.

This work is unique as no one has explored the impact of intellectual capital on Bangladesh's bank performance. The findings suggest that business owners, managers and policymakers who want to improve the efficiency of their organizations should spend continuously on IC and expand their investment into CEE, which includes both financial and physical resources, in order to obtain better bank performance.

The purpose of this study is to investigate the impact of Islamic microfinance services (IMFS) on women’s empowerment in rural Bangladesh.

The study is based on a multi-stage sampling technique. The primary data are collected through a face-to-face survey of 389 women respondents who have received IMFS from the Islami Bank Bangladesh Limited. Cronbach’s alpha test is conducted to test the reliability and internal consistency of collected data. Paired-sample tests, logit regression and proportion hypothesis tests are conducted to measure the impact of IMFS on women’s empowerment. Descriptive and inferential statistics are used to interpret the data.

The study reveals that IMFS have led to structural transformation in the occupation dynamics of the respondents’ families from agriculture to retail businesses. IMFS have had a significant positive impact on household income, savings and expenditure; have improved standard of living and human capital formation; and have enhanced all three dimensions of empowerment, namely, economic empowerment (ECEM), socio-cultural empowerment (SCEM) and familial empowerment (FLEM). Of them, ECEM and SCEM have positively contributed toward overall women’s empowerment, while FLEM has a negative but insignificant impact on overall empowerment. The respondents’ perception also supports the finding that IMFS have benefited rural women and empowered them.

The study is based on primary data. It leads to an inquiry as to whether women are dominant in familial affairs. If so, it may reduce the state of happiness and overall women’s empowerment. There is a clear gap in the existing literature about this inquiry.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

Women’s empowerment remains a key development challenge in Kenya. The purpose of this study is to attempt to understand the status of women’s empowerment and the key contributors to their disempowerment in Kenya’s aquaculture sector.

A cross-sectional survey was conducted on 534 male and female fish farmers from 300 households drawn from six counties in Kenya (Kakamega, Kisumu, Kisii, Kiambu, Meru and Nyeri). The Abbreviated Women’s Empowerment in Agriculture Index (A-WEAI) was adapted to Abbreviated Women’s Empowerment in Fisheries and Aquaculture Index (A-WEFI) to suit the aquaculture and fisheries sub-sector. The adapted A-WEFI was then used to estimate and the status of women’s and men’s using five domains of empowerment (5DE) and a gender parity index (GPI). Data were analysed using descriptive statistics, Cramer’s V and sensitivity analysis as test statistics.

About 86% of the men and 80% of the women were classified as empowered. The mean score of the 5DE was 0.93 and 0.95 for women and men, respectively. In addition, 82% of the households achieved gender parity, suggesting that for such households, empowerment of men was no greater than that of women. Overall, the results suggest no major differences between the empowerment of women and men. Findings suggest areas of improvement in empowerment: when observed separately, women report lack of agency in production, resource, time-use and allocation and leadership.

This paper adapts the A-WEAI to the fisheries and aquaculture context, in bid to bridge the gap in standard women’s empowerment measurement methods in this area. Also, there are limited empirical studies on the multifaceted empowerment of women in aquaculture in Kenya. The findings are meant to serve as a point of reference for policymakers, as they develop gender-responsive intervention programmes, and in implementing gender mainstreaming in Kenya.

The COVID-19 has brought with it valuable opportunities for the retail sector. Notably, online channels have assumed a key role for businesses that can rely less on physical channels due to the pandemic's restrictions. Within this context, the study aims to identify the main antecedents leading to the formation of the male and female customers' continuance intention of using online food delivery services (OFDS) in the restaurant industry.

A web-based self-completion survey and a subsequent structural equation modelling have been employed on a sample of 360 participants.

Findings reveal that perceived healthiness, quarantine procedures, perceived hygiene, perceived ease of app use and attitude significantly influence continuance intention. Moreover, the moderator analysis corroborates that male consumers' continuance intention is mainly influenced by perceived healthiness, quarantine procedures and perceived hygiene. Conversely, female customers' continuance intention is predicated on perceived healthiness and attitude.

Although the adoption of a sample of young customers (18–29 years) guarantees good research internal validity, findings are not generalizable.

The study provides valuable contributions for restaurants related to the (1) creation/management of their own OFDS platforms; (2) selection of the right third-party platforms.

The paper is one of the first studies examining the predictors impacting on customers' OFDS continuance intention in the COVID-19 context by also focusing on gender differences.

The purpose of this study is to explore the perceptions of teachers’ and undergraduate students concerning the provision of written corrective feedback (WCF) in Saudi EFL writing classrooms in the form of a case study.

The sample consisted of three teachers and five students, whose views on WCF were recorded via individual semi-structured interviews to gather qualitative data.

The results revealed some divergent viewpoints between students and teachers and among peers in both groups.

By offering the best WCF practice and considering students' interests, this research is important for improving the pedagogical approaches used by EFL instructors for teaching writing to university learners. It will, therefore, have more of an impact on EFL writing instruction.