A5001956353- Blind Source Separation Techniques
- Sparse and Compressive Sensing Techniques
- Face and Expression Recognition
- Network Security and Intrusion Detection
- EEG and Brain-Computer Interfaces
- Medical Image Segmentation Techniques
- Brain Tumor Detection and Classification
- Data Mining Algorithms and Applications
- Medical Imaging and Analysis
- Acute Myeloid Leukemia Research
- Antiplatelet Therapy and Cardiovascular Diseases
- Information Systems and Technology Applications
- Big Data and Business Intelligence
- Image and Signal Denoising Methods
- Image Retrieval and Classification Techniques
- Drug-Induced Adverse Reactions
- Photoacoustic and Ultrasonic Imaging
- Advanced Neural Network Applications
- Platelet Disorders and Treatments
- Advanced Image Processing Techniques
- Image Processing Techniques and Applications
- Statistical Methods and Inference
- Advanced Clustering Algorithms Research
- Big Data Technologies and Applications
- Advanced Computational Techniques and Applications
SUNY Upstate Medical University
2024
Narsee Monjee Institute of Management Studies
2024
Upstate University Hospital
2024
Community Hospital
2024
Jamia Hamdard
2023
Indian Institute of Technology Delhi
2018-2020
GD Goenka University
2020
Guru Nanak Dev University
2016-2018
Institute of Information Science
2016
Cancer cohorts are now known to be associated with increased rates of clonal hematopoiesis (CH). We sort characterize the hematopoietic compartment patients melanoma and non-small cell lung cancer (NSCLC) given our recent population level analysis reporting evolving secondary leukemias. The advent immune checkpoint blockade (ICB) has dramatically changed understanding biology altered standards care for patients. However, impact ICB on myeloid expansion remains determined. studied if exposure...
Due to the nonsparse representation, use of compressed sensing (CS) for physiological signals, such as a multichannel electroencephalogram (EEG), has been challenge. We present generalized Bayesian CS framework that is capable handling representations arise in spatiotemporal setting. The proposed model utilizes standard linear Gaussian observation associated with hierarchical modeling data using matrix-variate scale mixture (GSM). It deploys various random and deterministic parameters...
Introduction: Brain tumors are fatal diseases that spread worldwide and affect all types of age groups. Due to its direct impact on the central nervous system, if tumor cells prevail at certain locations in brain, overall functionality body is disturbed chances a person approaching death high. Tumors can be cancerous or non-cancerous but many cases, complete recovery less as result rate has increased over world despite recent advancements technology, equipment awareness. So main concern...
Categorical data needs special treatment before it can be clustered using popular methods of pattern analysis. Or separate to deal with categorical have devised. All such use some kind similarity metric judge how similar two objects are. There are several measures and switching between them requires much effort. This paper presents a Generalized Similarity Metric (GSM) which inculcates five into single parameterized formulation. Its implementation in famous ROCK algorithm is also presented...
During last few years cloud computing has been emerging from the promising business idea to one fastest growing part of IT industry.It is an internet based technology and most exciting today's world because its scalability, flexibility reduced cost.Cloud vendors provide services users on as needed basis Paas through Iaas, SaaS.Data stored remotely user's location.Therefore security privacy are major issues which hampers growth companies have lots data includes audio, videos, text digital...
Summary Detecting anomalies is crucial for maintaining security in Wireless Sensor Networks (WSNs), as they are susceptible to various attacks that compromise nodes and yield inaccurate outcomes. Conventional attack detection approaches face challenges like high false positives, vulnerability complex attacks, limited adaptability changing due predefined patterns. Additionally, the computational strain on resource‐constrained hampers network efficiency, demanding innovative resilient...
The paper explores the dynamic intersection of financial markets and advanced data analytics. In a world where evolve swiftly, informed decision-making is imperative for investors, traders, analysts. addresses this need by developing machine learning model employing random forest classifier to forecast direction S&P 500 index. It unfolds through systematic process, commencing with retrieval from Yahoo Finance, preprocessing ensure quality, attribute selection, training. We rigorously...
Brain tumors are fatal diseases that spread worldwide and affect all types of age groups. Due to its direct impact on Central Nervous System if tumor cells prevail at certain locations in the brain, overall functionality body is disturbed chances a person approaching death accelerate. Tumors can be cancerous or non-cancerous but many cases, complete recovery less as result rate has increased over world despite recent advancements technology, equipment awareness. So main concern detect brain...
Presented strategies for obtaining face identification in the existence of blur are maintain convolution model and can't handle non-uniform blurring things that regularly occur from tilt rotary motion hand-held cameras.This paper, include a trend to propose method recognition within occurrence space-varying comprise arbitrarily-shaped kernels.We have tendency blurred as rounded arrangement geometrically remodel instance targeted gallery face, show set all images obtained by non-uniformly...
This paper addresses the problem of Bayesian Block Sparse Modeling when coefficients within blocks are correlated. In contrast to current hierarchical methods which do not exploit correlation structure blocks, we propose a three level estimation framework. It employs heavy-tailed priors for block sparse modeling and variational inference estimation. also describes relationship between proposed framework some existing Learning (SBL) show that these SBL can be viewed as its special cases....
Compressed Sensing (CS) has emerged as an alternate method to acquire high dimensional signals effectively by exploiting the sparsity assumption. However, owing non-sparse and non-stationary nature, it is extremely difficult process Electroencephalograph (EEG) using CS paradigm. The success of Bayesian algorithms in recovering triggered research based models for neurophysiological signal processing. In this paper, we address problem Temporal Modeling EEG Signals Block Sparse Variational...
Classification of Iris flower dataset is the best known problem to be found in pattern recognition literature. It contains four attributes flowers belonging three different species. The objective design a model which can differentiate species based on fl
Bayesian Sparse Signal Recovery (SSR) for Multiple Measurement Vectors, when elements of each row solution matrix are correlated, is addressed in the paper. We propose a standard linear Gaussian observation model and three-level hierarchical estimation framework, based on Scale Mixture (GSM) with some random deterministic parameters, to unknown matrix. This induces heavy-tailed marginal distribution over which encompasses several choices distributions viz. Laplace distribution, Student's t...
We use network security in many infrastructure technologies modern life. It is used to safeguard our daily life sensitive data and ensure the uninterrupted flow of information has become paramount there are tools techniques that contribute security. Firewalls a fundamental aspect They act as barrier bеtwееn trusted internal untrusted external networks, such internet. responsible for monitoring, filtering, controlling incoming outgoing traffic enforce policies prevent unauthorized access or...