Student support : bridging the gap between students and the university

Bangladesh introduced open and distance learning as a means of providing education for people in isolated and remote locations through the establishment of the Bangladesh Open University (BOU). The broad aim of the BOU is to provide flexible and needs-based education to those unable or not wishing to enter conventional educational institutions. The BOU is presently the only university in Bangladesh to provide mass education and also to provide continuing education and professional and technical education to support the existing educational system. The BOU has a mission that encompasses secondary and higher levels of education. BOU operates its programs through a centralised academic and administrative staff, and regional and local offices throughout Bangladesh that organise local tutorials and distribute information and materials. BOU has adult students in all parts of the country, and most of the students live in rural areas. They need support that is appropriate to their local circumstances. Using an interpretive approach, this research examines the support needs of students studying for the Secondary School Certificate and the Bachelor of Education, assesses the effectiveness of current support services and explores alternatives to the current system. The underlying assumption is that support needs to be appropriate to the country’s culture and circumstances, and useful and feasible from the perspectives of students, staff, administrators and senior university officials. To investigate the appropriate support for distance education students, this research was conducted in four sample regions. Two were selected from areas of sparse population where the terrain makes transport difficult and two from areas that are more densely populated and where transport is easier. A questionnaire survey and focus groups were conducted with students, focus groups with local staff and interviews with Regional Directors within the four sample regions. Interviews were also undertaken with central University senior staff to get their perspectives on current and future policies for student support

Sustainability adoption through buyer supplier relationship across supply chain: A literature review and conceptual framework

AbstractThe sustainability of an entire supply chain and the final product is affected by the sustainability performance of each partner in the chain. The buyer-supplier relationship plays an important role in improving sustainability of the supply chain. This paper aims to provide a systematic review of existing literature on the adoption of sustainability practices through supply relationships. To this end, a structured literature review has been carried out that analyzes published research, evaluates contributions, and summarizes the results. The authors selected only those papers that discussed sustainability practices adoption and relationship management in the supply chain. An in-depth analysis of the supply chain and its processes reveals that a buyer-supplier relationship should be determined on the basis of the capability and capacity of the partner (supplier). In cases where the supplier firm lacks capability or capacity, the focal firm may decide to help or extend support. The buyer-supplier relationship starts with selecting suppliers based on their sustainability standards. In order to give a better understanding of the mechanisms active, and processes involved in the development of a sustainable supply chain, the authors offer a conceptual model. The study also identifies indicators, enablers and barriers to a sustainable supply chain

An empirical study on the interrelationship between trade openness and carbon emission in Bangladesh

Volume 3, Issue 2, July 201

NeuDetect: A neural network data mining system for wireless network intrusion detection

This thesis proposes an Intrusion Detection System, NeuDetect, which applies Neural Network technique to wireless network packets captured through hardware sensors for purposes of real time detection of anomalous packets. To address the problem of high false alarm rate confronted by the current wireless intrusion detection systems, this thesis presents a method of applying the artificial neural networks technique to the wireless network intrusion detection system. The proposed system solution approach is to find normal and anomalous patterns on preprocessed wireless packet records by comparing them with training data using Back-propagation algorithm. An anomaly score is assigned to each packet by calculating the difference between the output error and threshold. If the anomaly score is positive then the wireless packet is flagged as anomalous and is negative then the packet is flagged as normal. If the anomaly score is zero or close to zero it will be flagged as an unknown attack and will be sent back to training process for re-evaluation

Application of Transformations for Orthogonality

In the statistical analysis of multivariate data, principal component analysis is widely used to form orthogonal variables. Realizing the difficulties of interpreting the principal components, Garthwaite et al. (2012) proposed two transformations, each of which yield surrogates of the original variables. Recently, Garthwaite and Koch (2016) proposed a transformation that also produces orthogonal components and can be used to partition the contribution of individual variables to a quadratic form. The aim of this thesis is to discover and explore applications of these transformations. We consider bootstrap methods for forming interval estimates of the contribution of individual variables to a Mahalanobis distance and their percentages. New bootstrap methods are proposed and compared with the percentile, bias-corrected percentile, non-studentized pivotal, and studentized pivotal methods via a large simulation study. The new methods enable use of a broader range of pivotal quantities than with standard pivotal methods, including vector pivotal quantities. Both equal-tailed intervals and shortest intervals are constructed; the latter are particularly attractive when (as here) squared quantities are of interest. Using a transformation to orthogonality, new measures are constructed for evaluating the contribution of individual variables to a regression sum of squares. The transformation yields an orthogonal approximation of the columns of the predictor scores matrix. The new measures are compared with three previously proposed measures through examples, and the properties of the measures are examined. We consider one new procedure and two older procedures for identifying collinear sets. The new procedure is based on transformations that partition variance inflation factors into contributions from individual variables, and they provide detailed information about the collinear sets. The procedures are compared using three examples from published studies that addressed issues of multicollinearity

How do the poor cope with shocks in Bangladesh ? evidence from survey data

This paper uses household survey data collected in September-October 2009 on a nationally representative sample of 2,000 households in Bangladesh to examine the nature of shocks experienced by households over the preceding 12 months and the type of coping mechanisms that were adopted. The analysis finds that more than half the sample claimed to have faced a shock -- economic, health, climatic, or asset related -- over the previous year. Surprisingly, the non-poor face a larger share of these shocks compared with the poor. A closer look at this result shows that the non-poor report a significantly larger share of"asset-related"shocks, which is consistent with the fact that the poor have fewer assets to lose. Health-related shocks dominate and households appear to have coped with these shocks through savings and loans, help from friends, and depletion of assets. The results show that households, when faced with covariate shocks due to climatic reasons, are less able to cope. As would be expected, the poor are less able to cope with shocks compared with the non-poor; the poor are more likely to use coping mechanisms that could have negative welfare implications in the longer term, including the depletion of assets, reduction of essential consumption, and use of high-interest loans. Econometric analysis suggests that geographical location, socio-economic status, and access to microfinance all affect the ability to cope with shocks. Policy implications include the importance of developing safety nets that take into account the vulnerability to climate-related shocks and further developing the links between micro-finance and safety net programs.Access to Finance,Safety Nets and Transfers,Rural Poverty Reduction,Small Area Estimation Poverty Mapping,Housing&Human Habitats

Performance of arsenic and iron removal plants in Bangladesh

Arsenic in groundwater above 0.05 mg/L was found in 61 out of the total of 64 districts, and 433 out of the total of the 496 thanas in Bangladesh. But this dimension of the arsenic occurrence problem in groundwater in Bangladesh is yet to be fully identified. Water in around 65% areas of Bangladesh contain iron in excess of 2 mg/L, and arsenic has been found to co-exist with iron in many situations. Thus arsenic can be removed by both co-precipitation and adsorption onto the precipitated Fe(OH)3 in iron removal plants. This study evaluates the performance of 60 arsenic and iron removal plants (AIRPs) presently operating in different geo-hydrological conditions of Bangladesh

LVLane: Deep Learning for Lane Detection and Classification in Challenging Conditions

Lane detection plays a pivotal role in the field of autonomous vehicles and advanced driving assistant systems (ADAS). Over the years, numerous algorithms have emerged, spanning from rudimentary image processing techniques to sophisticated deep neural networks. The performance of deep learning-based models is highly dependent on the quality of their training data. Consequently, these models often experience a decline in performance when confronted with challenging scenarios such as extreme lighting conditions, partially visible lane markings, and sparse lane markings like Botts' dots. To address this, we present an end-to-end lane detection and classification system based on deep learning methodologies. In our study, we introduce a unique dataset meticulously curated to encompass scenarios that pose significant challenges for state-of-the-art (SOTA) models. Through fine-tuning selected models, we aim to achieve enhanced localization accuracy. Moreover, we propose a CNN-based classification branch, seamlessly integrated with the detector, facilitating the identification of distinct lane types. This architecture enables informed lane-changing decisions and empowers more resilient ADAS capabilities. We also investigate the effect of using mixed precision training and testing on different models and batch sizes. Experimental evaluations conducted on the widely-used TuSimple dataset, Caltech lane dataset, and our LVLane dataset demonstrate the effectiveness of our model in accurately detecting and classifying lanes amidst challenging scenarios. Our method achieves state-of-the-art classification results on the TuSimple dataset. The code of the work will be published upon the acceptance of the paper.Comment: 8 page

Causing Security Threat to Host State by Refugees: Context of Rohingya Refugees in Bangladesh

Bangladesh has been the host state of a large number of Rohingya refugees since August 2017 Rohingya An ethnic minority group of Rakhine state Myanmar have been fleeing to Bangladesh after the Myanmar army started an ethnic cleansing on that area in august 2017 Since then Bangladesh has been hosting around 1 1 million Rohingya refugees till now In the first three months of the crisis the majority arrived During the first half of 2018 an estimated 12 000 people entered Bangladesh Women and children are the vast majority in Bangladesh and more than 40 percent are under 12 years of age UNHCR 2020 As per the latest update of UNHCR 860 243 Rohingya refugees are living in 187 534 households inside the camps UNHCR 2020 After three years of this influx Bangladesh is bearing the burden of Rohingya refugees and repatriation from Bangladesh is a far cry from reality As Mallick 2020 explain that due to China and India s rising economic and strategic interests in repatriating the Rohingya refugees to the Rakhine State Myanmar foreign and regional organizations were unable to take any visible action Organizations such as the United Nations OIC ASEAN and other regional bodies have struggled to put pressure on Myanmar to take back Bangladeshi Rohingya refugee