DIP NANDI | American International University-Bangladesh (original) (raw)

Papers by DIP NANDI

Scientific reports, Feb 5, 2024

AIP Conference Proceedings, Dec 31, 2022

International Journal of Information Technology and Computer Science, Dec 7, 2023

International Journal of Information Engineering and Electronic Business, Dec 7, 2023

International Journal of Mathematical Sciences and Computing, Dec 7, 2023

Computers, Materials & Continua

2022 25th International Conference on Computer and Information Technology (ICCIT)

Proceedings of the 2nd International Conference on Computing Advancements

International Journal of Information Technology and Computer Science

Predicting crop yields is one of the more difficult tasks in the agriculture sector. A fascinatin... more Predicting crop yields is one of the more difficult tasks in the agriculture sector. A fascinating area of research to estimate agricultural productivity has emerged from recent advancements in information technology for agriculture. Crop yield prediction is a technique for estimating crop production based on a variety of factors, including weather conditions and parameters such as temperature, rainfall, fertilizer, and pesticide use. In the world of agriculture, Data mining techniques are extremely popular. In order to predict the crop production for the following year, data mining techniques are employed and evaluated in the agricultural sector. In this paper, we carried out the comparison between Naive Bayes, K-nearest neighbor, Decision Tree, Random Forest, and K-Means clustering algorithms to predict crop yield in order to determine which method is most effective at doing so. The results show which algorithm is better suitable for this particular purpose by comparing these data...

Diagnostics

Osteosarcoma is the most common type of bone cancer that tends to occur in teenagers and young ad... more Osteosarcoma is the most common type of bone cancer that tends to occur in teenagers and young adults. Due to crowded context, inter-class similarity, inter-class variation, and noise in H&E-stained (hematoxylin and eosin stain) histology tissue, pathologists frequently face difficulty in osteosarcoma tumor classification. In this paper, we introduced a hybrid framework for improving the efficiency of three types of osteosarcoma tumor (nontumor, necrosis, and viable tumor) classification by merging different types of CNN-based architectures with a multilayer perceptron (MLP) algorithm on the WSI (whole slide images) dataset. We performed various kinds of preprocessing on the WSI images. Then, five pre-trained CNN models were trained with multiple parameter settings to extract insightful features via transfer learning, where convolution combined with pooling was utilized as a feature extractor. For feature selection, a decision tree-based RFE was designed to recursively eliminate les...

International Journal of Modern Education and Computer Science

International Journal of Information Technology and Computer Science

Cardiovascular disease is the leading cause of death. In recent days, most people are living with... more Cardiovascular disease is the leading cause of death. In recent days, most people are living with cardiovascular disease because of their unhealthy lifestyle and the most alarming issue is the majority of them do not get any symptoms in the early stage. This is why this disease is becoming more deadly. However, medical science has a large amount of data regarding cardiovascular disease, so this data can be used to apply data mining techniques to predict cardiovascular disease at the early stage to reduce its deadly effect. Here, five data mining classification techniques, such as: Naïve Bayes, K-Nearest Neighbors, Support Vector Machine, Random Forest and Decision Tree were implemented in the WEKA tool to get the best accuracy rate and a dataset of 12 attributes with more than 300 instances was used to apply all the data mining techniques to get the best accuracy rate. After doing this research people who are at the early stage of cardiovascular disease or probably going to be a vic...

2023 3rd International Conference on Robotics, Electrical and Signal Processing Techniques (ICREST)

International Journal of Mathematical Sciences and Computing

COVID-19 hit the world unexpectedly, forcing humans to isolate themselves. It has placed the live... more COVID-19 hit the world unexpectedly, forcing humans to isolate themselves. It has placed the lives of people in jeopardy with its fury. The global pandemic had a detrimental effect on the worlds' education spheres. It has imposed a global lockdown, with a negative impact on the students' lives. Continuing regular classes on-campus was out of the question. At that moment, online learning came to us as a savior. The quality of online education was yet to be tested on a large scale compared to regular schooling. Educational data mining is a modern arena that holds promise for those who work in education. Data mining strategies are developed to uncover latent information and identify valuable trends that can increase students' performance and, in turn, contribute to the improvement of the educational system in the long run. This research mainly aims to identify a comparative analysis of the students' academic performance between online and on-campus environments and distinguish the significant characteristics that influence their academic endeavors. The impact of the factors on the students' performance is visualized with the help of the Decision Tree Classification Model. This paper will assist in giving a good overview that influences the distinguished factors on students' academic performance. Moreover, educators will also be benefited from this paper while making any important decision regarding the educational activity.

International Journal of Modern Education and Computer Science

International Journal of Information Engineering and Electronic Business

Proceedings of the 2nd International Conference on Computing Advancements

Journal of theoretical and applied information technology, 2018

Investigating the multi-core architecture is an essential issue to get superior in parallel reena... more Investigating the multi-core architecture is an essential issue to get superior in parallel reenactments. However, the simulation highlights must fit on parallel programming model to build the execution. The main goal of this research is to choose and evaluate parallelism using OpenMP over sequential program. For this purpose, there is a portrayal of two searching algorithms. The calculation is to discover the next edge of Prim's algorithm and single source shortest way of Dijkstra's algorithm. These two algorithm actualized in sequential formulation. Parallel searching algorithms are then implemented in view of multicore processor. The speed-up ratio and efficiency of parallel searching algorithms are tested and investigated in SGEMM GPU Kernel performance dataset with 241600 records and 18 attributes. Results show the dataset with different data sizes achieved super linear speed-up ratio and efficiency on OpenMP by running on 4 cores processor and reduction of the running ...

Advances in computer-mediated communication technologies have sparked and continue to facilitate ... more Advances in computer-mediated communication technologies have sparked and continue to facilitate the proliferation of online courses and degree programs in educational institutions. Fully online courses are becoming progressively more popular because of