A5008322023- Gene expression and cancer classification
- AI in cancer detection
- Distributed and Parallel Computing Systems
- Distributed systems and fault tolerance
- Complex Network Analysis Techniques
- Neural Networks and Reservoir Computing
- COVID-19 epidemiological studies
- Vaccine Coverage and Hesitancy
- Data Mining Algorithms and Applications
- Caching and Content Delivery
- Ultrasound in Clinical Applications
- Peer-to-Peer Network Technologies
- Infrared Thermography in Medicine
- Flood Risk Assessment and Management
- COVID-19 Pandemic Impacts
- Coastal and Marine Dynamics
- Wind Energy Research and Development
- Lung Cancer Diagnosis and Treatment
- Brain Tumor Detection and Classification
- Hydrological Forecasting Using AI
- Radiomics and Machine Learning in Medical Imaging
- Multi-Agent Systems and Negotiation
- Digital Radiography and Breast Imaging
- Ocean Waves and Remote Sensing
- Mobile Agent-Based Network Management
Persian Gulf University
2011-2024
Islamic Azad University, Bushehr Branch
2010
Islamic Azad University, Tehran
2009
Nowadays, breast cancer is one of the leading causes women’s death in world. If detected at initial stages, it can ensure long-term survival. Numerous methods have been proposed for early prediction such cancer. However, efforts are still ongoing, given importance problem. Artificial Neural Networks (ANN) a prevalent machine learning algorithm, which very popular and classification problems. In this paper, an Intelligent Ensemble Classification method based on Multi-Layer Perceptron neural...
Replicating of objects at multi nodes has been considered a promising technique for decreasing access cost and network traffic large distributed systems like Data Grids. In this paper we propose Optimal Placement Replicas (OPR) algorithm with the objective minimizing total replication including communication storage cost, given that maximum k replicas are allowed in tree data grid n height h. OPR time complexity O(nhk), which is lowest compared other algorithms same function past literature....
Several non-supervised machine learning methods have been used in the analysis of gene expression data obtained from microarray experiments. Recently, biclustering, a approach that performs simultaneous clustering on row and column dimensions matrix, has shown to be remarkably effective variety applications. The discovery biclusters, which denote groups items show coherent values across subset all transactions set, is an important type performed real-valued sets various domains, such as...
Research activities in mobile computing environments have been focused, recent years. To deal with the dynamic nature of environments, middleware has cited as an appropriate approach for development applications. Several models proposed so far. We a new model middleware, based on tuple-spaces. Clustering technique is applied to tuple-spaces, order increase performance, when large number tuples are involved. The developed, and implemented coordination service environments. Tuple-space few...
Abstract Background The first confirmed cases of COVID-19 in Iran were reported on February 19, 2020. This study aimed to analyze the epidemic curves and investigate correlation between parameters furthermore impact control measures spread during 365 days epidemic. Methods We used data from 20, 2020, 18, 2021, number by Iranian governments. Pearson coefficient was applied different parameters. daily deaths per new averaged calculate death rate same method positive tests. Furthermore, we...
Pneumothorax is a life-threatening and urgent chest disease than can be detected using Chest X-Ray (CXR) image. CXR images are low resolution diagnosis of pneumothorax based on them error prone. Deep learning-based computer aided systems improve performance pneumothorax. Convolutional Neural Networks (CNNs) default networks in deep medical image process. However, CNNs fail to capture long range features. On the other side, Transformer proposed exploit feature, but they cannot local In this...