Papers by SHAKAWAT HOSSAIN 1712581630
The emergence of the internet of things spread across several sectors and the agricultural indust... more The emergence of the internet of things spread across several sectors and the agricultural industry is not left out. The application of smart agriculture using IoT will improve productivity among stakeholders in the sector. It gives automation, control, and monitoring in agro-industry which leads to food sufficiency. This project was designed to address food sufficiency through smart agriculture using IoT. A methodic literature assessment (MLA) was adopted for this research where some research questions that we believe if addressed properly will increase food sufficiency were asked and answer with from literature. This project address the IoT sensor or devices and their application to achieve robust farming.
Utilizing IoT associations has been trending recently. They have been used in numerous fields of ... more Utilizing IoT associations has been trending recently. They have been used in numerous fields of life, comprising protected and subtle segments like the healthcare and military. Images that are used across IoT platforms infringe copyright strategies and rescind the authenticity of the images taken with hard work by a human. Thus, the objective of this study is to provide IoT association of images (pictures/photos) to pages across content management websites with unique watermarks to account for Royalty to the person/association owning the camera. This model indulges in emerging and registering a distinctive number that exclusively ties up the human and the camera which is getting used in such a way that the photo taken by the person will leave a unique identifier or mark which will make the image copyrighted and uploads to cloud for direct usage on any pages in IoT so that direct revenue of the copyrighted photograph goes to the person who clicked the photo. Our results presented th...
Shakawat Hossain , 2022
In certain real-world data sets, class imbalance occurs when one class (the minority class) has a... more In certain real-world data sets, class imbalance occurs when one class (the minority class) has a limited number of data points and the other (the dominant class) has a large number of data points. It is notably difficult to develop an effective model using current machine learning algorithms without considering data prepossessing to balance the imbalanced data sets. Random under sampling have been used in numerous studies to ensure that the different classes contain the same number of data points. In this project, we are working with under sampling strategies in which a clustering technique is used during the data prepossessing step. We use under sampling techniques with normalization in this project. We work with a imbalanced data set which is composed of a majority class and a minority class. The majority and minority classes contain data points, respectively. First we divide this imbalanced data set into training and testing sets based on the k-fold cross validation method. After normalize data we divide it into a majority class subset and a minority class subset. The clustering-based under sampling method is employed to reduce the number of data samples in the majority class. The reduced majority class subset is then combined with the minority class subset, resulting in a balanced training set. Then we again Normalize the Data. Finally, the classifier is trained and tested by the balanced training and testing sets, respectively.
Shakawat Hossain , 2021
In certain real-world data sets, class imbalance occurs when one class (the minority class) has a... more In certain real-world data sets, class imbalance occurs when one class (the minority class) has a limited number of data points and the other (the dominant class) has a large number of data points. It is notably difficult to develop an effective model using current machine learning algorithms without considering data prepossessing to balance the imbalanced data sets. Random under sampling have been used in numerous studies to ensure that the different classes contain the same number of data points. In this project, we are working with under sampling strategies in which a clustering technique is used during the data prepossessing step. We use under sampling techniques with normalization in this project. We work with a imbalanced data set which is composed of a majority class and a minority class. The majority and minority classes contain data points, respectively. First we divide this imbalanced data set into training and testing sets based on the k-fold cross validation method. After normalize data we divide it into a majority class subset and a minority class subset. The clustering-based under sampling method is employed to reduce the number of data samples in the majority class. The reduced majority class subset is then combined with the minority class subset, resulting in a balanced training set. Then we again Normalize the Data. Finally, the classifier is trained and tested by the balanced training and testing sets, respectively.
Conference Presentations by SHAKAWAT HOSSAIN 1712581630
THE GROWING RISK OF COX'S BAZAR, 2022
As per as we have seen the graph of climate change to grow, we try to figure out the sources, fac... more As per as we have seen the graph of climate change to grow, we try to figure out the sources, factors and impacts. Unfortunately, for an uncertain interruption like Corona Virus Pandemics, it goes under carpet. Though a Paris Agreement is occurred amongst all the government directives to decrease the vulnerabilities into 2 degree centigrade, it's totally dormant now. Despite this, many scientists get link between corona and rising Zoonoses. More threatening news is climate change is going to be increment and perpetual. Hence, global concern is needed at any cost. Undoubtedly, temperature in high, the change in wind pattern, precipitation and worsen weather condition will be costing enormously the life. Not only it brings ecological imbalance but also It destroys necessary species so far. In this way, climate change leads socioeconomic problem and political instability. According to it, we human beings are only responsible in tis increment and for producing greenhouse gas at the higher rate. Recently the conference held in Madrid goes in vein to give the measurement to all the countries.
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Papers by SHAKAWAT HOSSAIN 1712581630
Conference Presentations by SHAKAWAT HOSSAIN 1712581630