How do NGOs Perform Strategic Entrepreneurial Activities to Achieve Competitive Advantage?

Master of Science in Business (Siviløkonom) - Nord universitet 202

ANTIOXIDANT, ANTIBACTERIAL AND CYTOTOXIC ACTIVITIES OF VARIOUS EXTRACTS OF THYSANOLAENA MAXIMA (ROXB) KUNTZE AVAILABLE IN CHITTAGONG HILL TRACTS OF BANGLADESH

Objective: To evaluate the presence of different phytoconstituents and investigate in vitro bioactivities of petroleum ether, chloroform and methanol extracts of Thysanolaena maxima available in Bangladesh.Methods: Phytochemical screening was conducted using the specific standard procedure. Antioxidant activity of the extracts was evaluated using DPPH radical scavenging assay and reducing power assay. Determination of total phenolic and flavonoid contents was also carried out. Antibacterial and cytotoxic activities were investigated using disc diffusion method and brine shrimp lethality bioassay, respectively.Results: The methanol extract showed highest DPPH radical scavenging activity as well as possessed highest phenolic content (IC50 value for DPPH is 36.94±0.62 μg/ml and total phenolic content is 74.39±2.87 in mg/g, GAE) compared to the petroleum ether and chloroform extracts. On the other hand, chloroform extract possessed maximum flavonoid content (81±7.542 in mg/g, QE) and highest reducing power compare to other extracts. All the extracts showed mild to moderate in vitro antibacterial activity with a zone of inhibition ranging from 7 mm to 16 mm. In brine shrimp lethality bioassay, the LC50 values for petroleum ether, chloroform and methanol extracts were found to be 579.05±78.08 μg/ml, 386.92±80.47 μg/ml and 494.29±104.82 μg/ml, respectively which revealed weak cytotoxic potentials of the extracts compared to the positive control.Conclusion: The results indicated that T. maxima could be a very potent source of natural radical scavenger. Isolation of active compounds from this plant responsible for producing such bioactivities is underway.Keywords: Thysanolaena maxima, DPPH, Total phenolic contents, Total flavonoid contents, Reducing power, Cytotoxicity, Antimicrobial activit

CLOUD COMPUTING TECHNOLOGY IN BANGLADESH: A FRAMEWORK OF SOCIAL &ECONOMIC DEVELOPMENT

Cloud computing is currently one the most hyped IT innovations that promises potential opportunities for business and social innovation as well as modernizing ICT. For developing countries like Bangladesh, this technology aims to provide the clients a cost effective and convenient means to manage the huge amount of IT resources and thus offer strong possibility of accelerating social and economic development, even in this time of limited resources. As the information technology industry goes through a major shift, founded on the Internet as a platform, new opportunities for Bangladesh are open to employ technology at a lower cost and with much greater ease and success than in the past. The Main purpose of our strategy is to help organizations of public and private sector in Bangladesh to adopt cloud computing technology opportunities and prevent its obstacles through our proposed framework. In this article, we tried to assess different aspects and strengths, weaknesses, opportunities and threats of these strategies for Bangladeshi organizations and enterprises. In addition some recommendations are provided for Bangladeshi organizations and enterprises to help them to adopt cloud computing technology

An Intelligent Computer-Aided Scheme for Classifying Multiple Skin Lesions

Skin diseases cases are increasing on a daily basis and are difficult to handle due to the global imbalance between skin disease patients and dermatologists. Skin diseases are among the top 5 leading cause of the worldwide disease burden. To reduce this burden, computer-aided diagnosis systems (CAD) are highly demanded. Single disease classification is the major shortcoming in the existing work. Due to the similar characteristics of skin diseases, classification of multiple skin lesions is very challenging. This research work is an extension of our existing work where a novel classification scheme is proposed for multi-class classification. The proposed classification framework can classify an input skin image into one of the six non-overlapping classes i.e., healthy, acne, eczema, psoriasis, benign and malignant melanoma. The proposed classification framework constitutes four steps, i.e., pre-processing, segmentation, feature extraction and classification. Different image processing and machine learning techniques are used to accomplish each step. 10-fold cross-validation is utilized, and experiments are performed on 1800 images. An accuracy of 94.74% was achieved using Quadratic Support Vector Machine. The proposed classification scheme can help patients in the early classification of skin lesions.</p

TEAM-Atreides at SemEval-2022 Task 11: On leveraging data augmentation and ensemble to recognize complex Named Entities in Bangla

Many areas, such as the biological and healthcare domain, artistic works, and organization names, have nested, overlapping, discontinuous entity mentions that may even be syntactically or semantically ambiguous in practice. Traditional sequence tagging algorithms are unable to recognize these complex mentions because they may violate the assumptions upon which sequence tagging schemes are founded. In this paper, we describe our contribution to SemEval 2022 Task 11 on identifying such complex Named Entities. We have leveraged the ensemble of multiple ELECTRA-based models that were exclusively pretrained on the Bangla language with the performance of ELECTRA-based models pretrained on English to achieve competitive performance on the Track-11. Besides providing a system description, we will also present the outcomes of our experiments on architectural decisions, dataset augmentations, and post-competition findings.Comment: accepted in Proceedings of the 16th International Workshop on Semantic Evaluatio

Mobile-based Skin Lesions Classification Using Convolution Neural Network

This research work is aimed at investing skin lesions classification problem using Convolution Neural Network (CNN) using cloud-server architecture. Using the cloud services and CNN, a real-time mobile-enabled skin lesions classification expert system “i-Rash” is proposed and developed. i-Rash aimed at early diagnosis of acne, eczema and psoriasis at remote locations. The classification model used in the “i-Rash” is developed using the CNN model “SqueezeNet”. The transfer learning approach is used for training the classification model and model is trained and tested on 1856 images. The benefit of using SqueezeNet results in a limited size of the trained model i.e. only 3 MB. For classifying new image, cloud-based architecture is used, and the trained model is deployed on a server. A new image is classified in fractions of seconds with overall accuracy, sensitivity and specificity of 97.21%, 94.42% and 98.14% respectively. i-Rash can serve in initial classification of skin lesions, hence, can play a very important role early classification of skin lesions for people living in remote areas

Estimation of the Healthcare Waste Generation During COVID-19 Pandemic in Bangladesh

COVID-19 pandemic-borne wastes imposed a severe threat to human lives as well as the total environment. Improper handling of these wastes increases the possibility of future transmission. Therefore, immediate actions are required from both local and international authorities to mitigate the amount of waste generation and ensure proper disposal of these wastes, especially for low-income and developing countries where solid waste management is challenging. In this study, an attempt is made to estimate healthcare waste generated during the COVID-19 pandemic in Bangladesh. This study includes infected, ICU, deceased, isolated and quarantined patients as the primary sources of medical waste. Results showed that COVID-19 medical waste from these patients was 658.08 tons in March 2020 and increased to 16164.74 tons in April 2021. A top portion of these wastes was generated from infected and quarantined patients. Based on survey data, approximate daily usage of face masks and hand gloves is also determined. Probable waste generation from COVID-19 confirmatory tests and vaccination has been simulated. Finally, several guidelines are provided to ensure the country\u27s proper disposal and management of COVID-related wastes

Calorific Value Analysis of Azadirachta Excelsa and Endospermum Malaccense as Potential Solid Fuels Feedstock

Thermal conversion of woody biomass to fuel has been intensified in recent decades due to the depletion of fossil fuels, greenhouse effect and high energy demand worldwide. Screening the potential feedstock is being considered as one of the alternatives to identifying the most suitable biomass resources prior to being converted into renewable energy in the form of solid fuels, such as charcoal and briquettes. Generally, high calorific value (CV) indicates high potential of feedstock for briquettes, torrefied wood and coal generation. In this study, CV was characterized using a bomb calorimeter that was based on 3 different ranges of moisture content (MC) that are ? 25%, 20%?25% and ? 20% for two tropical tree species, namely Azadirachta excelsa (Sentang) and Endospermum malaccense (Sesenduk), respectively. This standard method for the characterization process was considered to determine the CV. Average CV for both samples ranged between 16?17 MJ/kg. The highest CV was 17.3490 MJ/kg and 17.1273 MJ/kg for Sesenduk and Sentang, respectively and calorific values were obtained at MC less than 20%. The experimental study demonstrated that the decreasing value of MC has increased the CV because of the high value of oxygen-to-carbon (O/C) ratio in the wood; additionally, the energy density of the wood sample was also improved when CV increased. Both of these species were proved to contain the potential of being feedstock as wood fuel resources, since they carry standard CVs, obtain fast growth with suitable conditions in Malaysia and are grown at very low cost of production for plantations, fertilizer, pesticides, labor, transportation and handling

Current Scenario of Solar Energy Applications in Bangladesh: Techno-Economic Perspective, Policy Implementation, and Possibility of the Integration of Artificial Intelligence

Bangladesh is blessed with abundant solar resources. Solar power is considered the most desirable energy source to mitigate the high energy demand of this densely populated country. Although various articles deal with solar energy applications in Bangladesh, no detailed review can be found in the literature. Therefore, in this study, we report on the current scenario of renewable energy in Bangladesh and the most significant potential of solar energy’s contribution among multiple renewable energy resources in mitigating energy demand. One main objective of this analysis was to outline the overall view of solar energy applications in Bangladesh to date, as well as the ongoing development of such projects. The technical and theoretical solar energy potential and the technologies available to harvest solar energy were also investigated. A detailed techno-economic design of solar power applications for the garment industry was also simulated to determine the potential of solar energy for this specific scenario. Additionally, renewable energy policies applied in Bangladesh to date are discussed comprehensively, with an emphasis on various ongoing projects undertaken by the government. Moreover, we elaborate global insight into solar power applications and compare Bangladesh’s current solar power scenario with that of other regions worldwide. Furthermore, the potential of artificial intelligence to accelerate solar energy enhancement is delineated comprehensively. Therefore, in this study, we determined the national scenarios of solar power implementation in Bangladesh and projected the most promising approaches for large-scale solar energy applications using artificial intelligence approaches

Out-of-pocket expenditure for seeking health care for sick children younger than 5 years of age in Bangladesh: findings from cross-sectional surveys, 2009 and 2012

Background: Bangladesh has committed to universal health coverage, and options to decrease household out-of-pocket expenditure (OPE) are being explored. Understanding the determinants of OPE is an essential step. This study aimed to estimate and identify determinants of OPE in seeking health care for sick under-five children. Methods: Cross-sectional data was collected by structured questionnaire in 2009 (n = 7362) and 2012 (n = 6896) from mothers of the under-five children. OPE included consultation fees and costs of medicine, diagnostic tests, hospital admission, transport, accommodation, and food. Expenditure is expressed in US dollars and adjusted for inflation. Linear regression was used for ascertaining the determinants of OPE. Results: Between 2009 and 2012, the median OPE for seeking care for a sick under-five child increased by ~ 50%, from USD 0.82 (interquartile range 0.39\u20131.49) to USD 1.22 (0.63\u20132.36) per child/visit. Increases were observed in every component OPE measured, except for consultation fees which decreased by 12%. Medicine contributed the major portion of overall OPE. Higher overall OPE for care seeking was associated with a priority illness (20% increase), care from trained providers (90% public/~ 2-fold private), residing in hilly/wet lands areas (20%) , and for mothers with a secondary education (19%). Conclusion: OPE is a major barrier to quality health care services and access to appropriate medicine is increasing in rural Bangladesh. To support the goal of universal health care coverage, geographic imbalances as well as expanded health financing options need to be explored