Md. Atikur Rahman received his M.Sc. degree from Jahangirnagar University at Savar, Dhaka, Bangladesh in Computer Science & Engineering (CSE) in 2016. He received his B.Sc. degree in Computer Science & Engineering, from Gono University, Savar, Dhaka, Bangladesh in 2014. Since 2015, he is a faculty member having current Designation ”Lecturer” in the Department of Computer Science and Engineering of Gono University, Savar, Dhaka, Bangladesh. Currently his research focuses on Digital Image Processing, Data Mining and Big Data Analysis. Supervisors: Supervisor Address: Department of Computer Science & Engineering Gono Bishwabidyalay, Savar, Dhaka -1344, Bangladesh
International Journal of Computer Applications (0975 – 8887), 2019
The competitive nature of the contemporary business scenario
requires productivity‐ driven organi... more The competitive nature of the contemporary business scenario requires productivity‐ driven organizations to be aware of the efficiency level of their dealers. Most businesses need a strategy for sales and distribution of their products. The selling process comprises multiple business processes such as warranty and claim of a material produced from the manufacturer. This paper is useful for the sub-dealers to maintain sales and maintain account details. This is commonly known as ERP Software which mainly focuses on the dealers and sub-dealers of the small business sector has some extra features. Software functionality which is dealers basically needs to follow up with the customer after they purchase the product. This investigative study proposes an efficient framework for the sub-dealer management portal using oracle.
International Journal of Computer Applications (0975 – 8887), 2019
Lung cancer is characterized by uncontrolled cell growth in tissues of the lung. Recently, image ... more Lung cancer is characterized by uncontrolled cell growth in tissues of the lung. Recently, image processing techniques are widely used in several medical areas for image improvement in earlier detection and treatment stages, where the time factor is very important to discover the abnormality issues in target images, especially in various cancer tumors such as lung cancer, breast cancer, etc. This paper aims to develop an efficient lung nodule detection system by performing nodule segmentation through thresholding and morphological operations. Thresholding is one of the most powerful tools for image segmentation. The segmented image obtained from thresholding has the advantages of smaller storage space, fast processing speed and ease in manipulation, compared with the gray level image which usually contains 256 levels. Image Segmentation using the watershed transforms works well if we can identify or “mark” foreground objects and background locations, to find “catchment basins” and “watershed ridge lines” in an image by treating it as a surface where light pixels are high and dark pixels are low. Morphological operations apply a structuring element to an input image, creating an output image of the same size. By choosing the size and shape of the neighborhood, it can possible to construct a morphological operation that is sensitive to specific shapes in the input image. Morphological operation has been widely used to produce binary and grayscale images, with morphological techniques being applied to noise reduction, image enhancement, and feature detection. The proposed method has two stages: lung region segmentation through thresholding and then segmenting the lung nodules through thresholding and morphological operations.
This paper presents a Neural Network Ensemble (NNE) for Mango Leaf Diseases Recognition (MLDR). M... more This paper presents a Neural Network Ensemble (NNE) for Mango Leaf Diseases Recognition (MLDR). Mango trees are affected by various diseases and identifying disease is a complex task till now because those diseases are detected manually. This study intends to detect the symptoms of plant diseases easily with machine learning than a manual monitoring system. Here, Trained data are produced by classification technique collecting images of leaves that were various disease affected. A machine learning system is designed to identify the symptom of mangoes leaf diseases automatically uploading and matching new images of affected leaf with trained data.The proposed system could successfully detect and classify the examined disease with average accuracy of 80%. This proposed solution would clinch the Mango plants. The system will help to detect disease without the presence of agriculturist. It would also save time to identify disease with machine instead of traditional system, which helps to treat the affection of mango leaf disease properly, increase the production of mango and meet the demand of global market.
Day Long Seminar and AGM of Bangladesh Medical Physics Society (BMPS), 2017
Diabetes mellitus (DM) is a group of metabolic disorders that are
remained high blood sugar level... more Diabetes mellitus (DM) is a group of metabolic disorders that are remained high blood sugar levels during prolonged periods. It is occurred when human body is unable to produce or respond properly to insulin. In this work, we have collected a diabetes dataset, preprocessed and used conditional inference tree (C Tree) model to predict the severity of diabetes.
International Journal of Computer Applications (0975 – 8887), 2019
The competitive nature of the contemporary business scenario
requires productivity‐ driven organi... more The competitive nature of the contemporary business scenario requires productivity‐ driven organizations to be aware of the efficiency level of their dealers. Most businesses need a strategy for sales and distribution of their products. The selling process comprises multiple business processes such as warranty and claim of a material produced from the manufacturer. This paper is useful for the sub-dealers to maintain sales and maintain account details. This is commonly known as ERP Software which mainly focuses on the dealers and sub-dealers of the small business sector has some extra features. Software functionality which is dealers basically needs to follow up with the customer after they purchase the product. This investigative study proposes an efficient framework for the sub-dealer management portal using oracle.
International Journal of Computer Applications (0975 – 8887), 2019
Lung cancer is characterized by uncontrolled cell growth in tissues of the lung. Recently, image ... more Lung cancer is characterized by uncontrolled cell growth in tissues of the lung. Recently, image processing techniques are widely used in several medical areas for image improvement in earlier detection and treatment stages, where the time factor is very important to discover the abnormality issues in target images, especially in various cancer tumors such as lung cancer, breast cancer, etc. This paper aims to develop an efficient lung nodule detection system by performing nodule segmentation through thresholding and morphological operations. Thresholding is one of the most powerful tools for image segmentation. The segmented image obtained from thresholding has the advantages of smaller storage space, fast processing speed and ease in manipulation, compared with the gray level image which usually contains 256 levels. Image Segmentation using the watershed transforms works well if we can identify or “mark” foreground objects and background locations, to find “catchment basins” and “watershed ridge lines” in an image by treating it as a surface where light pixels are high and dark pixels are low. Morphological operations apply a structuring element to an input image, creating an output image of the same size. By choosing the size and shape of the neighborhood, it can possible to construct a morphological operation that is sensitive to specific shapes in the input image. Morphological operation has been widely used to produce binary and grayscale images, with morphological techniques being applied to noise reduction, image enhancement, and feature detection. The proposed method has two stages: lung region segmentation through thresholding and then segmenting the lung nodules through thresholding and morphological operations.
This paper presents a Neural Network Ensemble (NNE) for Mango Leaf Diseases Recognition (MLDR). M... more This paper presents a Neural Network Ensemble (NNE) for Mango Leaf Diseases Recognition (MLDR). Mango trees are affected by various diseases and identifying disease is a complex task till now because those diseases are detected manually. This study intends to detect the symptoms of plant diseases easily with machine learning than a manual monitoring system. Here, Trained data are produced by classification technique collecting images of leaves that were various disease affected. A machine learning system is designed to identify the symptom of mangoes leaf diseases automatically uploading and matching new images of affected leaf with trained data.The proposed system could successfully detect and classify the examined disease with average accuracy of 80%. This proposed solution would clinch the Mango plants. The system will help to detect disease without the presence of agriculturist. It would also save time to identify disease with machine instead of traditional system, which helps to treat the affection of mango leaf disease properly, increase the production of mango and meet the demand of global market.
Day Long Seminar and AGM of Bangladesh Medical Physics Society (BMPS), 2017
Diabetes mellitus (DM) is a group of metabolic disorders that are
remained high blood sugar level... more Diabetes mellitus (DM) is a group of metabolic disorders that are remained high blood sugar levels during prolonged periods. It is occurred when human body is unable to produce or respond properly to insulin. In this work, we have collected a diabetes dataset, preprocessed and used conditional inference tree (C Tree) model to predict the severity of diabetes.
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requires productivity‐ driven organizations to be aware of the
efficiency level of their dealers. Most businesses need a
strategy for sales and distribution of their products. The
selling process comprises multiple business processes such as
warranty and claim of a material produced from the
manufacturer. This paper is useful for the sub-dealers to
maintain sales and maintain account details. This is
commonly known as ERP Software which mainly focuses on
the dealers and sub-dealers of the small business sector has
some extra features. Software functionality which is dealers
basically needs to follow up with the customer after they
purchase the product. This investigative study proposes an
efficient framework for the sub-dealer management portal
using oracle.
remained high blood sugar levels during prolonged periods. It is
occurred when human body is unable to produce or respond properly
to insulin. In this work, we have collected a diabetes dataset,
preprocessed and used conditional inference tree (C Tree) model to
predict the severity of diabetes.
requires productivity‐ driven organizations to be aware of the
efficiency level of their dealers. Most businesses need a
strategy for sales and distribution of their products. The
selling process comprises multiple business processes such as
warranty and claim of a material produced from the
manufacturer. This paper is useful for the sub-dealers to
maintain sales and maintain account details. This is
commonly known as ERP Software which mainly focuses on
the dealers and sub-dealers of the small business sector has
some extra features. Software functionality which is dealers
basically needs to follow up with the customer after they
purchase the product. This investigative study proposes an
efficient framework for the sub-dealer management portal
using oracle.
remained high blood sugar levels during prolonged periods. It is
occurred when human body is unable to produce or respond properly
to insulin. In this work, we have collected a diabetes dataset,
preprocessed and used conditional inference tree (C Tree) model to
predict the severity of diabetes.