Arshad Ali
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View article: Effectiveness of WhatsApp-based health education in enhancing knowledge and attitudes towards diabetes and its complications among university students in Lahore, Pakistan: A quasiexperimental study
Effectiveness of WhatsApp-based health education in enhancing knowledge and attitudes towards diabetes and its complications among university students in Lahore, Pakistan: A quasiexperimental study Open
Background Pakistan faces a diabetes epidemic affecting 33 million adults, with limited health education among youth. Digital platforms offer potential for scalable health promotion. This study evaluated the effectiveness of WhatsApp-based…
View article: Implementasi Pengembangan Unit STB (Set-Top Box) Sebagai Sistem Home Server Dengan Menggunakan Firewall dan Docker
Implementasi Pengembangan Unit STB (Set-Top Box) Sebagai Sistem Home Server Dengan Menggunakan Firewall dan Docker Open
Latar Belakang: Transformasi teknologi mendorong pemanfaatan Set-Top Box (STB) HG680P Fiberhome dengan spesifikasi quad-core ARM Cortex-A53 1,51 GHz, RAM 2GB, storage 8GB sebagai infrastruktur server terintegrasi yang mendukung NAS, web se…
View article: Uncertainty-Aware Energy Consumption Forecasting Using LSTM Networks with Monte Carlo Dropout
Uncertainty-Aware Energy Consumption Forecasting Using LSTM Networks with Monte Carlo Dropout Open
View article: A Decision Framework for Intra Task Fixed Priority INTEL PXA270 Distributed Architecture for Soft RT- Applications Based on Deep Learning
A Decision Framework for Intra Task Fixed Priority INTEL PXA270 Distributed Architecture for Soft RT- Applications Based on Deep Learning Open
Distributed architectures with fixed-priority scheduling using Dynamic Power Management (DPM) for CPU optimization are one of the serious concerns in INTEL PXA270. Increasing the number of transistors and task mapping on chips causes great…
View article: Advancing wind energy potential estimation through multidistribution wind speed analysis in coastal Pakistan
Advancing wind energy potential estimation through multidistribution wind speed analysis in coastal Pakistan Open
Wind energy is becoming one of the most important elements toward the advancement of sustainable energy systems globally. The assessment of wind energy potential is critical to the optimization of resource application and improvement of te…
View article: Best Practices for Configuring and Optimizing Virtual Machines in Microsoft Azure
Best Practices for Configuring and Optimizing Virtual Machines in Microsoft Azure Open
As businesses increasingly migrate to cloud computing platforms, optimizing virtual machine (VM) configurations in Microsoft Azure has become essential for maximizing performance, cost-efficiency, and security. This paper explores best pra…
View article: Multiple brain cavernomas and pregnancy: Risk of seizures during obstetrical management
Multiple brain cavernomas and pregnancy: Risk of seizures during obstetrical management Open
Introduction: Cerebral cavernous malformations (CCMs) are linked to seizures and severe complications, including intracranial hemorrhage. Research on CCMs during pregnancy is limited, with only a few case series and observational studies a…
View article: Beyond Words: The Evolution of Large Language Models in Context-AwareLarge Language Models (LLMs) have revolutionized artificial intelligence by enabling sophisticated natural language understanding, generation, and reasoning. As these models evolve, context awareness has become a crucial factor in improving their adaptability, coherence, and decision-making capabilities. This paper explores the evolution of LLMs from rule-based systems to deep learning architectures, emphasizing advancements in contextual embeddings, multimodal learning, and real-time adaptation. We discuss the impact of reinforcement learning with human feedback (RLHF), memory-augmented models, and transformer-based architectures in enhancing contextual sensitivity. A (Preprint)
Beyond Words: The Evolution of Large Language Models in Context-AwareLarge Language Models (LLMs) have revolutionized artificial intelligence by enabling sophisticated natural language understanding, generation, and reasoning. As these models evolve, context awareness has become a crucial factor in improving their adaptability, coherence, and decision-making capabilities. This paper explores the evolution of LLMs from rule-based systems to deep learning architectures, emphasizing advancements in contextual embeddings, multimodal learning, and real-time adaptation. We discuss the impact of reinforcement learning with human feedback (RLHF), memory-augmented models, and transformer-based architectures in enhancing contextual sensitivity. A (Preprint) Open
BACKGROUND Large Language Models (LLMs) have transformed artificial intelligence (AI) by enabling machines to understand, generate, and interact with human language in increasingly sophisticated ways. From early rule-based systems and sta…
View article: Unveiling the Future: A Comprehensive Review of Machine Learning, Deep Learning, Multi-model Models and Explainable AI in Robotics
Unveiling the Future: A Comprehensive Review of Machine Learning, Deep Learning, Multi-model Models and Explainable AI in Robotics Open
The rapid advancements in artificial intelligence (AI) have significantly transformed the fields of machine learning, deep learning, and robotics. This comprehensive review aims to provide an in-depth survey of the current state of AI mode…
View article: Case of severe thrombocytopenia with recurrent extensive deep vein thrombosis due to antiphospholipid syndrome, management challenge
Case of severe thrombocytopenia with recurrent extensive deep vein thrombosis due to antiphospholipid syndrome, management challenge Open
Key Clinical Message Severe thrombocytopenia in secondary antiphospholipid syndrome (APS) presents a significant management challenge. This case highlights the complexity of managing APS‐related thrombocytopenia, requiring a nuanced approa…
View article: Catalytic exploration metallic and nonmetallic nano-catalysts, properties, role in photoelectrochemistry for sustainable applications
Catalytic exploration metallic and nonmetallic nano-catalysts, properties, role in photoelectrochemistry for sustainable applications Open
This article provides an overview of the photoelectrochemistry of nano-catalysts, their advantages, mechanisms, and the interactions between nanostructures and reactivity. The applications of nanomaterials in various processes, such as dye…
View article: A novel energy pattern factor-based optimized approach for assessing Weibull parameters for wind power applications
A novel energy pattern factor-based optimized approach for assessing Weibull parameters for wind power applications Open
View article: Newspaper Article Element Detection Using Multimodal Transformers for Longer Texts
Newspaper Article Element Detection Using Multimodal Transformers for Longer Texts Open
View article: Enhancing Anomaly Detection in Attributed Networks Using Proximity Preservation and Advanced Embedding Techniques
Enhancing Anomaly Detection in Attributed Networks Using Proximity Preservation and Advanced Embedding Techniques Open
The increasing relevance of anomaly detection in attributed networks is gaining traction in fields such as cybersecurity, finance, and healthcare. However, large-scale attributed networks often exhibit noisy and inconsistent node propertie…
View article: Malignant Hypertension Complicated by Posterior Reversible Encephalopathy Syndrome (PRES)
Malignant Hypertension Complicated by Posterior Reversible Encephalopathy Syndrome (PRES) Open
Clinical signs and symptoms of posterior reversible encephalopathy syndrome (PRES) include headache, altered mental state, vision loss, and seizures. Neuroradiological results exhibiting white matter abnormalities, primarily in the parieto…
View article: An Optimal Approach for Assessing Weibull Parameters and Wind Power Potential for Six Coastal Cities in Pakistan
An Optimal Approach for Assessing Weibull Parameters and Wind Power Potential for Six Coastal Cities in Pakistan Open
Assessing and effectively optimizing wind power potential for a wind site demands accurate calculation of Weibull parameters. In this research, we have ameliorated the performance of the recently-introduced novel energy pattern factor meth…
View article: A Quantum Encryption Algorithm based on the Rail Fence Mechanism to Provide Data Integrity
A Quantum Encryption Algorithm based on the Rail Fence Mechanism to Provide Data Integrity Open
The rapid development of quantum computer technology poses an increasing threat to conventional encryption algorithms, and accordingly, more advanced security practices need to be developed. The current paper presents an innovative quantum…
View article: Abstract 374: Predictors of early intracerebral hemorrhage in patients with cerebral sinus venous thrombosis: Systematic review and meta‐analysis
Abstract 374: Predictors of early intracerebral hemorrhage in patients with cerebral sinus venous thrombosis: Systematic review and meta‐analysis Open
Objectives Patients with cerebral venous thrombosis (CVT) may present with early intracerebral hemorrhage (EICH). The objective of this study was to identify predictors for EICH in CVT patients via a systematic review and meta‐analysis of …
View article: A Proactive Approach to Fault Tolerance Using Predictive Machine Learning Models in Distributed Systems
A Proactive Approach to Fault Tolerance Using Predictive Machine Learning Models in Distributed Systems Open
In the era of cloud computing and large-scale distributed systems, ensuring uninterrupted service and operational reliability is crucial. Conventional fault tolerance techniques usually take a reactive approach, addressing problems only af…
View article: A Machine Learning Approach to Reduce Latency in Edge Computing for IoT Devices
A Machine Learning Approach to Reduce Latency in Edge Computing for IoT Devices Open
Nowadays, high latency in Edge Computing (EC) for Internet of Things (IoT) devices due to network congestion and online traffic reduces the acquired precision, performance, and processing power of the network. Data overload in IoT signific…
View article: An Efficient Optimization System for Early Breast Cancer Diagnosis based on Internet of Medical Things and Deep Learning
An Efficient Optimization System for Early Breast Cancer Diagnosis based on Internet of Medical Things and Deep Learning Open
Improving patient outcomes and treatment efficacy requires effective early detection of breast cancer. Recently, medical diagnostics has been transformed by merging the Internet of Things (IoT) technology with AI and ML methods. Better and…
View article: An Enhanced Lung Cancer Identification and Classification Based on Advanced Deep Learning and Convolutional Neural Network
An Enhanced Lung Cancer Identification and Classification Based on Advanced Deep Learning and Convolutional Neural Network Open
In this research, a fast, accurate, and stable system of lung cancer detection based on novel deep learning techniques is proposed. Lung cancer continues to be one of the most monumental global health concerns, which is why there is an urg…
View article: Abattoir Effluents’ Impacts on the Badri Nullah Stream’s Water Quality
Abattoir Effluents’ Impacts on the Badri Nullah Stream’s Water Quality Open
This investigation focuses on the Badri Nullah stream's water quality in the Swabi region. The study was conducted concerning effluents released from a nearby Abattoir (slaughterhouse). A total of five samples were taken, two were upstream…
View article: Smart Logistics for Sustainable Supply Chain: A Bibliometric Analysis
Smart Logistics for Sustainable Supply Chain: A Bibliometric Analysis Open
This study undertakes a bibliometric analysis of 143 documents on smart logistics research from 1998 to 2023.Quantitative techniques encompassing publication trend analysis, keyword co-occurrence, conceptual structure mapping, and bibliogr…
View article: Evaluation of Material Models Used in Multi-Material Topology Optimization
Evaluation of Material Models Used in Multi-Material Topology Optimization Open
View article: Planning of Radial Distribution System with Distributed Generation-A Review
Planning of Radial Distribution System with Distributed Generation-A Review Open
View article: Building a Cloud-IDS by Hybrid Bio-Inspired Feature Selection Algorithms Along With Random Forest Model
Building a Cloud-IDS by Hybrid Bio-Inspired Feature Selection Algorithms Along With Random Forest Model Open
The adoption of cloud computing has become increasingly widespread across various domains. However, the inherent security vulnerabilities of cloud computing pose significant risks to its overall safety. Consequently, intrusion detection sy…
View article: Improvement of Translation Accuracy for the Word Sense Disambiguation System using Novel Classifier Approach
Improvement of Translation Accuracy for the Word Sense Disambiguation System using Novel Classifier Approach Open
Machine Translation (MT) is a crucial application of Natural language Processing (NLP). This MT technique automatic and based on computers. One of the most modern techniques adopted in MT is Machine Learning (ML). Over the past few years, …
View article: The Impact of Climatic Parameters on the Streamflows & Future Sustainable Hydro-Energy Generation Predicting Streamflows for the 21st Century Under Climate Change Scenarios
The Impact of Climatic Parameters on the Streamflows & Future Sustainable Hydro-Energy Generation Predicting Streamflows for the 21st Century Under Climate Change Scenarios Open
View article: Naïve Bayes Approach for Word Sense Disambiguation System With a Focus on Parts-of-Speech Ambiguity Resolution
Naïve Bayes Approach for Word Sense Disambiguation System With a Focus on Parts-of-Speech Ambiguity Resolution Open
Natural languages are written and spoken languages, and NLP (Natural Language Processing) is the ability of a computer program to recognize both written and spoken languages. Word Sense Disambiguation (WSD) is identified as a challenging a…