Zobrazeno 1 - 10
of 9 126
pro vyhledávání: '"A/Rahman, Mohammad"'
A Novel Ensemble-Based Deep Learning Model with Explainable AI for Accurate Kidney Disease Diagnosis
Autor:
Arifuzzaman, Md., Ahmed, Iftekhar, Chowdhury, Md. Jalal Uddin, Sakib, Shadman, Rahman, Mohammad Shoaib, Hossain, Md. Ebrahim, Absar, Shakib
Chronic Kidney Disease (CKD) represents a significant global health challenge, characterized by the progressive decline in renal function, leading to the accumulation of waste products and disruptions in fluid balance within the body. Given its perva
Externí odkaz:
http://arxiv.org/abs/2412.09472
Deep learning (DL) techniques have achieved significant success in various software engineering tasks (e.g., code completion by Copilot). However, DL systems are prone to bugs from many sources, including training data. Existing literature suggests t
Externí odkaz:
http://arxiv.org/abs/2411.12137
Autor:
Sykot, Arman, Rahman, Mohammad Hasibur, Anannya, Rifat Tasnim, Upoma, Khan Shariya Hasan, Mahdy, M. R. C.
This paper presents a novel hybrid Quantum Key Distribution ,QKD, protocol that combines entanglement based and non entanglement based approaches to optimize security and the number of generated keys. We introduce a dynamic system that integrates a t
Externí odkaz:
http://arxiv.org/abs/2411.06586
Autor:
Haque, Nur Imtiazul, Mali, Prabin, Haider, Mohammad Zakaria, Rahman, Mohammad Ashiqur, Paudyal, Sumit
Incorporating advanced information and communication technologies into smart grids (SGs) offers substantial operational benefits while increasing vulnerability to cyber threats like false data injection (FDI) attacks. Current SG attack analysis tools
Externí odkaz:
http://arxiv.org/abs/2411.04731
Autor:
Asif, Muneeba, Kazmi, Mohammad Kumail, Rahman, Mohammad Ashiqur, Hasan, Syed Rafay, Homsi, Soamar
As edge computing and the Internet of Things (IoT) expand, horizontal collaboration (HC) emerges as a distributed data processing solution for resource-constrained devices. In particular, a convolutional neural network (CNN) model can be deployed on
Externí odkaz:
http://arxiv.org/abs/2409.17279
This article develops multiple novel climate risk measures (or variables) based on the television news coverage by Bloomberg, CNBC, and Fox Business, and examines how they affect the systematic and idiosyncratic risks of clean energy firms in the Uni
Externí odkaz:
http://arxiv.org/abs/2409.08701
Autor:
Cai, Hongyi, Rahman, Mohammad Mahdinur, Akhtar, Mohammad Shahid, Li, Jie, Wu, Jingyu, Fang, Zhili
Image Transformers show a magnificent success in Image Restoration tasks. Nevertheless, most of transformer-based models are strictly bounded by exorbitant memory occupancy. Our goal is to reduce the memory consumption of Swin Transformer and at the
Externí odkaz:
http://arxiv.org/abs/2409.06206
Simulation modelling systems are routinely used to test or understand real-world scenarios in a controlled setting. They have found numerous applications in scientific research, engineering, and industrial operations. Due to their complex nature, the
Externí odkaz:
http://arxiv.org/abs/2409.03957
Seismocardiogram (SCG) signals can play a crucial role in remote cardiac monitoring, capturing important events such as aortic valve opening (AO) and mitral valve closure (MC). However, existing SCG methods for detecting AO and MC typically rely on e
Externí odkaz:
http://arxiv.org/abs/2408.09513
Seismocardiography (SCG) has gained significant attention due to its potential applications in monitoring cardiac health and diagnosing cardiovascular conditions. Conventional SCG methods rely on accelerometers attached to the chest, which can be unc
Externí odkaz:
http://arxiv.org/abs/2408.09512