A5033739451- Blockchain Technology Applications and Security
- Gene expression and cancer classification
- Energy Load and Power Forecasting
- IoT and Edge/Fog Computing
- Machine Learning in Bioinformatics
- Retinal Imaging and Analysis
- Genetic Associations and Epidemiology
- Solar Radiation and Photovoltaics
- Human Mobility and Location-Based Analysis
- Traffic Prediction and Management Techniques
- COVID-19 diagnosis using AI
- Traditional Chinese Medicine Studies
- Physical Unclonable Functions (PUFs) and Hardware Security
- Transportation Planning and Optimization
- Electric Power System Optimization
- VLSI and Analog Circuit Testing
- Integrated Circuits and Semiconductor Failure Analysis
- Context-Aware Activity Recognition Systems
- Food Supply Chain Traceability
- Image and Video Quality Assessment
- Time Series Analysis and Forecasting
- Machine Fault Diagnosis Techniques
- Retinal and Macular Surgery
- Genetic and phenotypic traits in livestock
- Magnetic and transport properties of perovskites and related materials
University of Lahore
2023-2024
NED University of Engineering and Technology
2024
Guru Nanak Dev University
2023
Khalifa University of Science and Technology
2020-2023
Pakistan Institute of Engineering and Applied Sciences
2018-2021
Sangji University
2021
University of Engineering and Technology Taxila
2021
University of Engineering and Technology Lahore
2021
Lahore General Hospital
2020
Blockchain is a shared distributed ledger that promises tamper-proof secure transactions over the highly available and resilient network involving multiple participants. Directed Acyclic Graph (DAG) has revolutionized blockchain technology. Owing to its optimized validation mechanism, high scalability, efficient provenance, support for IoT multiparty involvement, DAG rapidly over-shadowing traditional architecture. In this paper, we present comparative analysis of most popular based...
Blockchain, smart contracts, and the Internet of Things (IoT) are essential technologies for business process re-engineering supply chains in era Industry 4.0. The agricultural food chain is one research areas where these disruptive can play a crucial role automating processes, providing real-time goods monitoring, securing transactions. With help blockchain, IoT, product's health environment be monitored throughout chain. In this study, we have critically examined relevance through various...
A smart contract is known to be useful for automating business processes triggered by specific events caused IoT sensors, data feeds, or other applications. blockchain-based management system an innovative technology that foreseen automate future business-to-business (B2B) processes. Blockchain well-known play a central role in process re-engineering optimizing workflow operations, especially multi-party arrangements. This paper presents multi-organizational which user can create, deploy,...
Problems with erroneous forecasts of electricity production from solar farms create serious operational, technological, and financial challenges to both Solar farm owners companies. Accurate prediction results are necessary for efficient spinning reserve planning as well regulating inertia power supply during contingency events. In this work, the impact several climatic conditions on generation in Amherst. Furthermore, three machine learning models using Lasso Regression, ridge ElasticNet...
Constructing the power curve of a generation facility integrated with complex and large-scale industrial processes is difficult task but can be accomplished using Industry 4.0 data analytics tools. This research attempts to construct data-driven generator installed at 660 MW plant by incorporating artificial intelligence (AI)-based modeling The produced from modeled an neural network (ANN)—a reliable analytical technique deep learning. Similarly, R2.ai application, which belongs automated...
The emergence of new technologies and the era IoT which will be based on compute-intensive applications. These applications increase traffic volume today’s network infrastructure impact more emerging Fifth Generation (5G) system. Research is going in many details, such as how to provide automation managing configuring data analysis tasks over cloud edges, achieve minimum latency bandwidth consumption with optimizing task allocation. major challenge for researchers push artificial...
Abstract Background Genotype–phenotype predictions are of great importance in genetics. These can help to find genetic mutations causing variations human beings. There many approaches for finding the association which be broadly categorized into two classes, statistical techniques, and machine learning. Statistical techniques good actual SNPs variation where Machine Learning we just want classify people different categories. In this article, examined Eye-color Type-2 diabetes phenotype. The...
Machines are built to give accessibility, precision, cost-effectiveness, and adaptability characteristics. This work will facilitate the recognition of hand gestures based on supervised learning. Signal processing-based techniques such as pre-processing (normalization) segmentation (empirical mode decomposition) employed. The Cubic-Support Vector Machine classifier is trained four different EMG (Electromyography) named wrist flexion, extension, resting hand, clenched fist. Spectral domain...
For some understudied populations, genotype data is minimal for genotype-phenotype prediction. However, we can use the of other large populations to learn about disease-causing SNPs and that knowledge prediction small populations. This manuscript illustrated transfer learning applicable prediction.Using HAPGEN2 PhenotypeSimulator, generated eight phenotypes 500 cases/500 controls (CEU, population) 100 cases/100 (YRI, populations). We considered 5 (4 phenotypes) 10 different risk each...
This article proposes and documents a machine-learning framework tutorial for classifying images using mobile phones. Compared to computers, the performance of deep learning model degrades when deployed on phone requires systematic approach find that performs optimally both computers By following proposed pipeline, which consists various computational tools, simple procedural recipes, technical considerations, one can bring power medical image classification devices, potentially unlocking...
Travel Time Prediction (TTP) has become an essential service that people use in daily commutes. With the precise TTP, individuals, logistic companies, and transport authorities can better manage their activities operations. This paper presents a novel Hybridized Deep Feature Space (HDFS) based TTP ensemble model (HDFS-TTP) for accurate travel time prediction. In first step, extensive endogenous exogenous data sources are augmented with traffic obtained using sensors. Next, we used Principal...
Wind energy is one of the renewable sources like solar energy, and accurate wind power prediction can help countries deploy farms at particular locations yielding more electricity. For any problem, determining optimal time step (lookback) information primary importance, using from previous timesteps improve scores. This article uses simulated annealing to find an for prediction. Finding timestep computationally expensive may require brute-forcing evaluate deep learning model each time. The...
With the advent of Big Data technology and Internet Things, Intelligent Transportation Systems (ITS) have become inevitable for future transportation networks. Travel time prediction (TTP) is an essential part ITS plays a pivotal role in congestion avoidance route planning. The novel data sources such as smartphones in-vehicle navigation applications allow traffic conditions smart cities to be analyzed forecast more reliably than ever. Such massive amount geospatial provides rich source...
Abstract Background : Genotype-Phenotype predictions are of great importance in genetics. These can help to find genetic mutations causing variations human beings. There many approaches for finding the association which be broadly categorized into two classes, statistical techniques, and machine learning. Statistical techniques good actual SNPs variation where Machine Learning we just want classify people different categories. In this article, examined Eye-color Type-2 diabetes phenotype....
Abstract BackgroundWe compared the procedure to calculate polygenic risk scores and machine learning for simulated data, devised a way compare results with PRS, highlighted required files formats PRS calculation model training. For calculation, we used three tools: Plink, PRSice, Lassosum, algorithm, artificial neural networks. ResultsBased on our survey, cannot say is better or because it depends phenotype under consideration. The average classification AUC of Machine was 0.27, 0.3, 0.35,...
An amendment to this paper has been published and can be accessed via the original article.
Edge-Fog Computing is closely related to IoT, 5G, and the blockchain, various new technologies which are being actively studied in fields of smart city, machine vision, Industries. Specifically, rapid growth dissemination high-performance sensing with ability acquire high-level information, emphasis on need importance further development platforms like, edge-fog computing for processing real-time response IoT based applications. In this paper, we introduce work-in-progress an intelligent...
Blockchain as a decentralized distributed ledger is revolutionizing the world with secure design data storage mechanism. In case of Bitcoin, mining involves process packing transactions in block by calculating random number termed nonce. The nonce calculation done special nodes called miners, and all miners follow Proof Work (PoW) mechanism to perform task. transaction verification time PoW-based blockchain systems, i.e., much slower than other digital systems such PayPal. It needs be...