Simulator for Scheduling Real-Time Systems with Reduced Power Consumption DOI Open Access

Hakeem Al-Fareed,

Omar Alghamdi,

Abdulaziz Alshuraya

et al.

Mathematical Modelling and Engineering Problems, Journal Year: 2022, Volume and Issue: 9(5), P. 1225 - 1232

Published: Dec. 13, 2022

Optimum resources utilization in computing devices especially power is among the prime areas of research from very beginning computer systems. However, its importance current era has been significantly increased due to diverse nature and their real time applications. On other hand, paradigm shifting towards sustainable that are green/environment friendly (low emission) produce relatively low energy/power. Real systems (RTS) power-hungry constrained nature. So, there room investigate scheduling algorithms (schedulers) with minimum (low) consumption. hand simulators software mimic environment for various parameter testing without actual implementation could be costly as well complex build beginning. In this study, we intended develop a simulator Real-Time Systems Reduced Power Consumptions (RPC). That potentially an where can tested over different case studies examine performance pertaining RPC RTS.

Language: Английский

The Synergy of Artificial Intelligence and Cybersecurity DOI
Atif Ali, Shahzad Ahmed, Muhammad Hussain

et al.

Published: Feb. 26, 2024

As the menace of cyber threats intensifies, artificial intelligence emerges as a crucial tool for enhancing cybersecurity. This article delves into advantages and drawbacks AI in The findings highlight positive outcomes preventing gathering information about attacks using AI. In summary, advancing is imperative to address attacks' escalating volume intricacy, recognizing that cybercriminals also leverage their malicious activities.

Language: Английский

Citations

1
Blockchain Empowered Interoperable Framework for Smart Healthcare DOI Creative Commons
Atta Rahman,

Mohammed Almomen,

Abdullah Albahrani

et al.

Mathematical Modelling and Engineering Problems, Journal Year: 2024, Volume and Issue: 11(5), P. 1330 - 1340

Published: May 30, 2024

In the past, healthcare industry used paper-based systems to manage and store medical records.However, these are vulnerable data breaches, loss, errors.To overcome issues, a research study has been conducted create safe efficient Electronic Data Interchange (EDI) system for using blockchain technology.The utilized various tools methods including Python as programming language implement environment, pyQT5 library graphical user interface (GUI), MySQL database management repository Health Records (EHR) with DBeaver, cross-platform tool management.The work involves development of blockchain-based smart contract storage, exchange, retrieval EHR.Additionally, application based on is created provide users friendly GUI.The proposed provides secure platform storing managing EHR well enabling EDI among stakeholders like practices, doctors, labs, pharmacies.Furthermore, scalable user-friendly, includes features patient visits, history, appointment scheduling.Blockchain technology ensures integrity, EDI, confidentiality, while user-friendly enhances experience compared existing standards health level 7 (HL7).

Language: Английский

Citations

1
Network Intrusion Detection Empowered with Federated Machine Learning DOI Creative Commons
Muhammad Umar Nasir, Shahid Mehmood, Muhammad Adnan Khan

et al.

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: Sept. 19, 2023

Abstract Security and privacy are greatly enhanced by intrusion detection systems. Now, Machine Learning (ML) Deep (DL) with Intrusion Detection Systems (IDS) have seen great success due to their high levels of classification accuracy. Nevertheless, because data must be stored communicated a centralized server in these methods, the confidentiality features system may threatened. This article proposes blockchain-based Federated (FL) approach that maintains training inferring models locally. improves diversity as trained on from different sources. We employed Scaled Conjugate Gradient Algorithm, Bayesian Regularization Levenberg-Marquardt Algorithm for our model. The weights were then applied federated learning To maintain security aggregation model, blockchain technology is used store exchange models. ran extensive testing Network Laboratory-Knowledge Discovery Databases (NSL-KDD) set evaluate efficacy proposed approach. According simulation results, FL model achieved higher accuracy level than traditional non-FL method. Classification was 98.93% 97.35% testing.

Language: Английский

Citations

3
Enhancing Multi-User Detection in Multicarrier 5G and Beyond: A Space-Time Spreading Approach with Parallel Interference Cancellation DOI Open Access
Sumayh S. Aljameel, Atta Rahman

Mathematical Modelling and Engineering Problems, Journal Year: 2023, Volume and Issue: 10(4), P. 1207 - 1215

Published: Aug. 30, 2023

This study explores a composite space-time and frequency-domain spreading strategy, designed to augment the capacity of multicarrier 5G systems operating over frequencyselective Rayleigh fading channels.The focus is directed towards comprehensive analysis Bit Error Rate (BER) performance proposed system, with adjustments made various parametric values.In tandem, receiver optimization techniques are meticulously studied, their outcomes positioned against existing literature.Within this context, Parallel Interference Canceller (PIC) emerges as viable alternative De-correlating Detector (DD), shift primarily driven by latter's heightened complexity noise amplification.Additionally, demonstrates acquisition larger number users exclusively employing transmission diversity, thereby eliminating need for receiving diversity additional code sets.This approach incrementally augments hardware at both ends link, minor trade-off benefits garnered.The efficacy scheme substantiated through MATLAB simulations, indicating promising avenue improving systems.The findings pave way significant advancements in development efficient robust communication era beyond.

Language: Английский

Citations

2
Enhancing Healthcare Data Security in IoT Environments Using Blockchain and DCGRU with Twofish Encryption DOI Creative Commons
D. R. Kumar Raja, B. N. Jagadesh, J. Kumar

et al.

Information Dynamics and Applications, Journal Year: 2023, Volume and Issue: 2(4), P. 173 - 185

Published: Dec. 1, 2023

In the rapidly evolving landscape of digital healthcare, integration cloud computing, Internet Things (IoT), and advanced computational methodologies such as machine learning artificial intelligence (AI) has significantly enhanced early disease detection, accessibility, diagnostic scope. However, this progression concurrently elevated concerns regarding safeguarding sensitive patient data. Addressing challenge, a novel secure healthcare system employing blockchain-based IoT framework, augmented by deep biomimetic algorithms, is presented. The initial phase encompasses blockchain-facilitated mechanism for data storage, authentication users, prognostication health status. Subsequently, modified Jellyfish Search Optimization (JSO) algorithm employed optimal feature selection from datasets. A unique status prediction model introduced, leveraging Deep Convolutional Gated Recurrent Unit (DCGRU) approach. This ingeniously combines Neural Network (CNN) (GRU) processes, where GRU network extracts pivotal directional characteristics, CNN architecture discerns complex interrelationships within Security management fortified through implementation twofish encryption algorithm. efficacy proposed rigorously evaluated using standard medical datasets, including Diabetes EEG Eyestate, diverse performance metrics. Experimental results demonstrate model's superiority over existing best practices, achieving notable accuracy 0.884. Furthermore, comparative analyses with Advanced Encryption Standard (AES) Elliptic Curve Cryptography (ECC) models reveal metrics, processing time throughput 40 45.42, respectively.

Language: Английский

Citations

2
Early Detection of Diabetic Retinopathy Utilizing Advanced Fuzzy Logic Techniques DOI Creative Commons

Mohammed Imran Basheer Ahmed

Mathematical Modelling and Engineering Problems, Journal Year: 2023, Volume and Issue: 10(6), P. 2086 - 2094

Published: Dec. 21, 2023

The escalating prevalence of diabetes globally, exacerbated by lifestyle changes postpandemic-including increased screen time, sedentary behavior, and remote workhas consequently driven a surge in associated complications, notably, Diabetic Retinopathy (DR).This ocular complication presents pressing concern due to its potential precipitate irreversible vision loss.Consequently, the necessity for timely accurate DR detection is paramount, especially circumstances where conventional diagnostic approaches are either challenging or financially prohibitive.Capitalizing on prowess fuzzy logic managing uncertainties, this study introduces an innovative application Extended Fuzzy Logic early-stage DR.Rather than focusing solely overt symptoms, approach discerns subtle similarities retinal irregularities between diabetic patients non-diabetic individuals.To quantify these similarities, 'f-validity' value was computed based risk factors which were subsequently transformed into membership function values.The aggregation values facilitated Ordered Weighted Averaging (OWA) operator.The experimental outcomes align satisfactorily with expert anticipations, boasting accuracy 90%, precision 92.2%, sensitivity 75%.These results, when juxtaposed against contemporary studies field, underscore promise scheme advancing early diagnostics DR.The thus proposes solution that leverages power address burgeoning challenge DR.

Language: Английский

Citations

2
Nanoparticle analysis based on optical ion beam in nuclear imaging by deep learning architectures DOI

M. Manjula,

Navneet Kumar,

Vipul Vekariya

et al.

Optical and Quantum Electronics, Journal Year: 2023, Volume and Issue: 55(10)

Published: July 23, 2023

Language: Английский

Citations

1
Fetal Health Prediction Using Bio-Signal Cardiotocography Empowered with Blockchain Technology and Federated Machine Learning DOI Creative Commons
Sang-Woong Lee, Muhammad Umar Nasir, Tariq Shahzad

et al.

Research Square (Research Square), Journal Year: 2023, Volume and Issue: unknown

Published: Aug. 3, 2023

Abstract Cardiotocography measures the fetal heart rate in fetus during pregnancy to ensure physical health because cardiotocography gives data about and uterine shrinkages which is very beneficial detect whether normal or suspect pathologic. Various infer wrongly give wrong predictions of human error. The traditional way reading time taken belongs numerous errors as well. Fetal condition important measure at stages proper medications fetuses for their well-being. In current period Machine learning (ML) a well-known classification strategy used biomedical field on various issues ML fast appropriate results are better than results. This research article Federated machine (FML) techniques classify fetal. proposed model detection bio-signal uses FML train test data. So, achieves 99.06% 0.94% prediction accuracy misprediction respectively K-nearest neighbor (KNN) achieved 82.93% 17.07% respectively. by comparing both models outperformed KNN technique achieve best most

Language: Английский

Citations

1
ML-Based Prediction of Ideal Discipline for UG Students: A Sustainable Educational Perspective DOI
Mohammad Aftab Alam Khan,

Mohammad Aljebali,

Mustafa Youldash

et al.

Technical and vocational education and training, Journal Year: 2024, Volume and Issue: unknown, P. 283 - 293

Published: Jan. 1, 2024

Language: Английский

Citations

0
Experimental Evaluation in Identification of Kidney Cancer using Modified Learning Scheme DOI

S.R. Niranjana,

Anita Titus,

S Venkat

et al.

2022 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI), Journal Year: 2024, Volume and Issue: unknown, P. 1 - 6

Published: May 9, 2024

Language: Английский

Citations

0