Article 1
A Text Feature-Based CNN Approach to Detect Fake News
Nazneen Akhter, Tasnim Binte Shiraj, Maliha Tabassum
With the spread of social media, rising digitalization, and sharing information without investigation have exploded towards the mass people. This exacerbated the long-standing issue of fake news, which has become substantially more relevant in recent years because of the harm it causes to society. Manual and Automated detection system has been introduced to tackle this problem. Deep learning techniques' most recent breakthroughs make them a potential tool for identifying fake news. In this study, we proposed a Convolutional Neural Network based learning model built in association with different test feature extraction methods to recognize false news. Experimental outcomes demonstrate that the proposed study was successful in achieving a training accuracy of 0.9879 and test accuracy of 0.9867, with a recall, and F-score of 0.98 each.
Article 2
Assessment of the Impact of Urbanization on Urban Park and Lake with Geospatial Techniques: A Case Study of Dhanmondi Lake, Dhaka, Bangladesh
Md Imran Hossian Rakib, Israt Jahan, Tahrima Jui Era
Urban parks are vital components of urban ecosystems, providing numerous benefits to both the environment and society. However, urban development has posed significant challenges to the sustainability and functionality of these green spaces. This research assesses the impacts of urban development activities on the Dhanmondi Lake and park area from 1990 to 2022, using Land Use Land Cover (LULC) and Normalized Difference Vegetation Index (NDVI) analyses. The study discovered that vegetation near the lakeside and park area has decreased by 15.74%, water bodies have decreased by 30.76%, and settlements have increased by 42.12%. From the NDVI, it was found that dense vegetation has decreased by 66.73% from 1990 to 2022. This work is significant as it highlights the critical need for sustainable urban planning to preserve urban green spaces. By investigating the spatial trends of urban development around the Dhanmondi Lake and park area, this research provides valuable insights into the potential consequences of such activities. Additionally, it proposes recommendations for future urban planning and park management strategies, including the implementation of green infrastructure, stricter zoning regulations, and community engagement programs to mitigate the adverse effects of urbanization on Dhanmondi Lake.
Article 3
IoT Ecosystem Readiness towards Smart Bangladesh
Md. Nasim Parvez, Kazi Abu Taher
Bangladesh has outlined the next steps to achieve the Smart Bangladesh Vision 2041 by riding on the strong connectivity foundation created by the telecommunication sector while achieving Digital Bangladesh Vision 2021. Making that vision a reality, this sector has propelled significant economic progress along with the connectivity indicators of the country. The next generation technologies are the key to achieving Smart Bangladesh goals. The Internet of Things (IoT) is one of the vital technologies that requires the right infrastructure and expedited adoption in the relevant areas. While the nation is aiming for Smart Citizen, Smart Government, Smart Society and Smart Economy; it is a prerequisite to have a thorough review of the connectivity infrastructure, the policies currently in place and the requirements for enabling a conducive environment for the adoption of IoT. There is a National Strategy on IoT formulated in March 2020 with defined objectives, goals, strategies and other frameworks touching IoT. However, there has been no assessment found on the progress of that strategy, existing frameworks, network connectivity and the other requirements for succeeding IoT in Bangladesh. Without a definitive plan and synchronized policy approach, it will not be possible to materialize IoT. The objective of this paper is to carry out a thorough assessment of the existing policies, frameworks, connectivity indicators, global connectivity comparison, recent changes to assess the gaps that should be addressed to ensure the full potential of IoT, Lastly, the probable actions are outlined as recommendations to facilitate the pathway for IoT in achieving Smart Bangladesh Vision 2041.
Article 4
Overview of the Emerging Biological Diseases (EBD): A Review of Bangladesh's Situation
Shamsunnahar Khanam, Md. Abu Rahath, Intehum Taufique Aurnab, Rashedul Islam Rasel, Rashedul Ismail Foysal, Md. Mostafizur Rahman
Since 1960, emerging infectious diseases have developed enormously due to excessive population growth, agricultural revolution, globalization, and increasing trade of animals. Consequently, the world community has already seen millions of people die losing many of their beloved ones. However, not many studies have been conducted on these issues, so it is difficult to identify what diseases may occur in future, including the reduction of the mortality rate due to these emerging biological diseases. The purpose of this systematic review study is to examine the factors responsible for increasing biological diseases, impacts of these diseases on public health, and the relation of these diseases with climate change and environmental phenomena and how their exacerbating effects are increasing the risk of disease transmission. This review also stresses the need for more research, particularly in developing countries that bear the brunt of these diseases but lack sufficient studies to address them. Finally, this review also lights up the existing scenario of Bangladesh regarding all these issues. The findings of this study can be able to raise public awareness and assist policymakers in making decisions on this crucial subject matter.
Article 5
Unleashing the Potential of Machine Learning Algorithms for Predicting Strokes
Elmeeh Hasan Shipra
Many different diseases now affect people due to the state of the environment and lifestyle choices made by humans. Such illnesses must be identified and predicted in advance if they areto reach their terminal phases. Cerebrovascular diseases like stroke are among the top reasons of mortality and these place a heavy financial burden on their victims. Health-related activity is a significant risk factor for stroke and it is receiving a lot of attention in terms of prevention. Numerous machine learning algorithms have been used to predict the occurance of stroke, including predictors such as lifestyle characteristics that allow for automated stroke diagnosis. In order to predict strokes, this study uses five supervised classifiers: K-Nearest Neighbour Algorithm, Decision Tree, Random Forest. Support Vector Machine, and Naïve Bayes. The aforementioned classifiers are trained on the dataset, which consists of 5110 items with 10 characteristics, and their performance is assessed using the confusion matrix. The dataset is pre-processed to make it acceptable for prediction. In the utilised dataset, the Random Forest algorithm performed better than all others in predicting strokes based on several physiological characteristics, with an accuracy of 95.85%. In contrast to an individual's medical history and level of physical activity, machine learning algorithms may be more useful for the clinical estimate of stroke.
Article 6
Reducing Food Waste: Bangladesh's Path to SDG 12.3 - A Policy and Practice Analysis
Marjia Jannatul Mukta, Sadia Sikder
Nowadays food loss and waste has become a major global challenge. This is especially true in Bangladesh, where recent data from the United Nations Environment Programme (UNEP) shows that over one crore tons of food are wasted annually. This persistent issue endangers the sustainability of the ecosystem in addition to sustaining cycles of poverty. In light of this, the international community's dedication to the Sustainable Development Goals (SDGs) denotes an attempt to solve environmental issues and poverty together. Bangladesh's agricultural sector and food loss/waste are closely related due to the country's agrarian background. According to the Food and Agriculture Organization (FAO), insufficient agricultural productivity accounts for thirty percent of worldwide food loss. SDG 12.3 is a cornerstone of this global endeavor, with the goal of halving food loss and waste by 2030. With a focus on the environmental effects of these issues and raising public awareness of the Food Losses and Wastes (FLW) SDGs, this study critically investigates the factors that lead to food loss and waste. This paper attempts a thorough policy analysis to identify the gaps that prevent Bangladesh from realizing SDG12.3. It then makes recommendations for closing these gaps and enabling the nation to achieve these targets by implementing practical policies and strategies that reduce food loss and waste.
