Application of Computer Vision and Mobile Systems in Education: A Systematic Review

The computer vision industry has experienced a significant surge in growth, resulting in numerous promising breakthroughs in computer intelligence. The present review paper outlines the advantages and potential future implications of utilizing this technology in education. A total of 84 research publications have been thoroughly scrutinized and analyzed. The study revealed that computer vision technology integrated with a mobile application is exceptionally useful in monitoring students’ perceptions and mitigating academic dishonesty. Additionally, it facilitates the digitization of handwritten scripts for plagiarism detection and automates attendance tracking to optimize valuable classroom time. Furthermore, several potential applications of computer vision technology for educational institutions have been proposed to enhance students’ learning processes in various faculties, such as engineering, medical science, and others. Moreover, the technology can also aid in creating a safer campus environment by automatically detecting abnormal activities such as ragging, bullying, and harassment

Academic Use of Smartphones in Secondary Level Education in Bangladesh: A Non-Parametric Approach

This study aims to examine the use of smartphones for educational purposes and the acceptance of online learning among secondary students. To investigate the academic utilization of smartphones among secondary students in Bangladesh, a sample of 384 students from different districts of Bangladesh were surveyed. The survey was conducted using a selfadministered, semi-tailored computerized questionnaire. The collected data was analyzed using IBM SPSS statistics 26 and the Mann-Whitney U test. The findings indicate that male students used smartphones for educational purposes with greater confidence and less difficulty than female students. On the other hand, students in 8th to 10th grade classrooms reported a greater willingness to use smartphones for academic purposes, with urban students being more enthusiastic than their rural peers. The study’s findings have implications for the government, policymakers, educators, and non-governmental organizations (NGOs). They highlight the importance of ensuring equal access to resources and tools that support academic success, as well as addressing the adverse effects of excessive smartphone usage. In addition, the government and NGOs should prioritize the elimination of inequities between rural and urban areas and provide subsidies to rural students

Ophthalmic Biomarker Detection Using Ensembled Vision Transformers -- Winning Solution to IEEE SPS VIP Cup 2023

This report outlines our approach in the IEEE SPS VIP Cup 2023: Ophthalmic Biomarker Detection competition. Our primary objective in this competition was to identify biomarkers from Optical Coherence Tomography (OCT) images obtained from a diverse range of patients. Using robust augmentations and 5-fold cross-validation, we trained two vision transformer-based models: MaxViT and EVA-02, and ensembled them at inference time. We find MaxViT's use of convolution layers followed by strided attention to be better suited for the detection of local features while EVA-02's use of normal attention mechanism and knowledge distillation is better for detecting global features. Ours was the best-performing solution in the competition, achieving a patient-wise F1 score of 0.814 in the first phase and 0.8527 in the second and final phase of VIP Cup 2023, scoring 3.8% higher than the next-best solution

Exploring barriers to accessing healthcare services for older indigenous people in the Chittagong Hill Tract, Bangladesh

We aim to investigate the obstacles faced by elderly indigenous individuals in the Chittagong Hill Tracts, Bangladesh when accessing healthcare services. A qualitative research approach was utilized, and data collection was carried out in three distinct regions of the aforementioned area. A total of 30 in-depth, semi-structured interviews and participant observations were conducted to achieve the research objectives. Thematic analysis utilizing both a deductive and inductive approach was employed to analyze the data. The Granheim method and Nvivo-12 software were utilized to process, analyze and code the data. The study's findings indicate that a lack of knowledge about healthcare needs, geographical barriers, poor financial conditions, higher cost of medical services, scarcity of hospitals nearby and communication barriers all contribute to inadequate access to healthcare services. By recognizing the factors that impede access to healthcare services in this region, this study offers valuable insight for policymakers and healthcare providers on how to enhance healthcare services for the indigenous population, especially the elderly. Furthermore, the government can adopt a more efficient approach to include these elderly individuals in various social safety net programs

Cellular and Transcriptional Adaptation of Bovine Granulosa Cells Under Ethanol-Induced Stress In Vitro

Aims Granulosa cells (GCs) are the major cellular component in a follicular microenvironment and play an indispensable role in ovarian function. This study was conducted to investigate the effects of ethanol exposure on the cellular and transcriptional changes of ovarian GCs

Social vulnerability, impacts and adaptations strategies in the face of natural hazards: insight from riverine islands of Bangladesh

Abstract Background Bangladesh is one of the countries at risk of natural disasters due to climate change. In particular, inhabitants of its riverine islands (char) confront ongoing climatic events that heighten their vulnerability. This study aims to assess social vulnerability, impacts, and adaptation strategies to climate change in the riverine island areas of Bangladesh. Methods A mixed-method approach incorporating qualitative and quantitative procedures was used on data collected from 180 households of riverine islands in Gaibandha, Bangladesh. The social vulnerability of riverine island communities was assessed based on their adaptation capacity, sensitivity, and exposure to climatic stressors. Results The findings show that char dwellers' vulnerability, impacts, and adaptation capability to climate change vary significantly depending on their proximity to the mainland. Social vulnerability factors such as geographical location, fragile and low-grade housing conditions, illiteracy and displacement, climate-sensitive occupation and low-income level, and so on caused to the in-height vulnerability level of these particular areas. This study also displays that climate change and its associated hazards cause severe life and livelihood concerns for almost all households. In this case, the riverine dwellers employed several adaptation strategies to enhance their way of life to the disaster brought on changing climate. However, low education facilities, deficiency of useful information on climate change, poor infrastructure, and shortage of money are still the supreme hindrance to the sustainability of adaptation. Conclusion The findings underscore the importance of evaluating the susceptibility of local areas to climate change and emphasize the need for tailored local initiatives and policies to reduce vulnerability and enhance adaptability in communities residing in char households

Understanding the Food Insecurity and Coping Strategies of Indigenous Households during COVID-19 Crisis in Chittagong Hill Tracts, Bangladesh: A Qualitative Study

This study examined the food insecurity and coping mechanisms among the indigenous Bangladeshi population of the Chittagong Hill Tracts (CHT) region to extract empirical evidence on the ongoing discussion on the COVID-19 pandemic-exacerbated food-insecurity situation. The study adopted a qualitative approach by interviewing 60 indigenous households. Data were collected in two phases between 15 June 2020, and 30 July 2021 in Bangladesh’s Chittagong Hill Tracts (CHT) region. Thematic data analyses were performed using the Granheim approach and NVivo-12 software. The authors used Huston’s social–ecological theory to explain the indigenous coping mechanisms. The research evidence revealed that most households experienced challenges over daily foods, manifesting in the decreasing consumption of them, the increased price of food items, a food crisis due to an income shock, malnutrition, the shifting to unhealthy food consumption, starvation and hunger, and food insufficiency, thereby leading to mental stress. This study further revealed that the indigenous population took crucial coping strategies to survive the pandemic. In response to COVID-19, they took loans and borrowed foods, reduced expenses, changed their food habits, avoided nutritional foods, relied on vegetables, sold domestic animals and properties, collected forest and hill foods, and depended on governmental and societal relief. This study also provides the in-depth policy actions for the urgent intervention of government, stakeholders, policymakers, NGOs, and development practitioners to take necessary initiatives to enhance the quality of life of the people that were affected by the post-pandemic recovery period

Estimation of drought trends and comparison between SPI and SPEI with prediction using machine learning models in Rangpur, Bangladesh

ABSTRACTThis study investigates drought trends, SPI-SPEI comparisons, and predictions in Rangpur, Bangladesh, from 1979 to 2020. We employed Modified Mann-Kendall for trend analysis, SPI and SPEI for drought assessment, and Pearson Correlation Coefficient and Simple Linear Regression for evaluating SPI and SPEI relationships. Additionally, we utilized ANN, SVM, and RF for prediction. The study revealed notable negative trends in seasonal and annual drought, with the highest z statistics observed for SPI 06 (-2.75), SPI 09 (-4.50), SPI 12 (5.60), SPI 24 (-8.40), SPEI 06 (-5.13), SPEI 09 (-6.82), SPEI 12 (-8.04), and SPEI 24 (-11.20). Strong correlations were identified across all SPI and SPEI indices, with coefficients peaking at 97%, 98%, 98%, and 97% for 06, 09, 12, and 24-month periods, respectively. The comparative assessment favored SPEI over SPI, highlighting its superiority and accuracy. The ANN prediction model showed significant results for short-term and seasonal drought forecasts, projecting SPEI 03 and SPEI 06 increases of 0.02 and 0.24, respectively. However, long-term drought estimation exhibited insignificant performance across all predictive models. This emphasizes the need for developing essential predictive tools for future drought variability