Enhancing Urban Connectivity: Dynamic Implementation and Integration of Multi-IRS Systems in Smart Cities

Israa Ali; Alza A.; Alaa H; Sergey; Erina

doi:https://doi.org/10.54216/FPA.170209

International Journal of BIM and Engineering Science | 2024

Adapting Traditional Sustainable Architectural Elements in Modern Buildings Utilizing Modern BIM Technologies

This study aims to explore the role of traditional architectural elements in promoting sustainability and how to integrate them into modern buildings by utilizing modern technologies, especially Building Information Modeling (BIM), to restore heritage identity and apply green building standards to modern residential buildings. Despite the advancements in modern urban and architectural developments, sustainability is an ancient concept. Traditional architecture in our region has successfully balanced the use of natural resources with environmental preservation, thereby providing cultural and environmental identity to heritage buildings. In Aleppo, modern residential buildings suffer from a loss of this deep connection to the environment and authentic identity. This research employs BIM software to model and analyze the heritage house of Ajqabash, assessing its compliance with green building standards. The study highlights the role of modern BIM technologies in facilitating environmental analysis and emphasizes the importance of traditional elements, such as the iwan and the internal courtyard, in providing thermal comfort for residents. By studying and analyzing traditional architectural elements and using BIM techniques, the article demonstrates that the concept of sustainability is deeply rooted in our architectural heritage. The Revit program was utilized to model the Ajqabash house in its architectural and structural details, and an energy simulation plug-in was used to analyze the sun's impact on the house. The findings underscore the effectiveness of BIM in conducting environmental studies and in preserving heritage while promoting sustainability. The goal is to develop new design criteria that combine heritage architectural identity with global sustainability standards. This approach aims to contribute to building environmentally and economically sustainable architectural communities and providing innovative solutions to modern housing problems in Aleppo. Ultimately, the research seeks to honor our rich architectural heritage while addressing contemporary environmental challenges.

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Sima Bazerbashi mail -

Sakher Olabi mail -

Hala Aslan mail

link https://doi.org/10.54216/IJBES.090106

Volume & Issue

Vol. Volume 9 / Iss. Issue 1

Details open_in_new

Neutrosophic and Information Fusion | 2024

On the Numerical Solutions Based On Exponential Finite Difference Method for Kuramoto-Sivashinsky Equation and Numerical Stability Analysis

In this paper, we solve the Kuramoto-Sivashinsky Equation numerically by finite-difference methods, using two different schemes which are the Fully Implicit scheme and Exponential finite difference scheme, because of the existence of the fourth derivative in the equation we suggested a treatment for the numerical solution of the two previous scheme by parting the mesh grid into five regions, the first region represents the first boundary condition, the second at the grid point x1, while the third represents the grid points x2,x3,…xn-2, the fourth represents the grid point xn-1 and the fifth is the second boundary condition. We also, study the numerical stability by Fourier (Von-Neumann) method for the two scheme which used in the solution on all mesh points to ensure the stability of the point which had been treated in the suggested style, we using two interval with two initial condition and the numerical results obtained by using these schemes are compare with Exact Solution of Equation Excellent approximate is found between the Exact Solution and numerical Solutions of these methods.  

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Agnes Osagie mail

link https://doi.org/10.54216/NIF.040204

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

Details open_in_new

Neutrosophic and Information Fusion | 2024

On the Problem of Inverting Discrete Self-Regression Models to Continuous Models

In this paper, we discuss the problem of converting auto-regression models at a discrete time into auto-regression models at continuous time, based on the idea of converting auto-regression models from first to second order. We study the general formula of AR (p) and its ability to convert from discrete to continuous time. Also, we use our model to study some real-life problems as a direct application of our approach.

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Taher Ahmed Jubbori mail

link https://doi.org/10.54216/NIF.040205

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

Details open_in_new

Pure Mathematics for Theoretical Computer Science | 2024

Prediction of Tuberculosis in Iraq Using A ZIPR Model

In this article, the ZeroInflated Poisson Regression model (ZI-PRM) was used to predict the number of tuberculosis patients by estimating the model using the maximum likelihood method and compared with Poisson regression model (PRM). The results showed that the ZIPRM best represented TB data from PRM. The PRM showed that the importance of some variables, although they were not significant as a cause of the TB data. The ZIP model indicates that there will be more TB cases in 2027 than there were in 2023. These findings point to an improvement in the nation's health status.

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Afraa A. Hamada mail

link https://doi.org/10.54216/PMTCS.040202

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

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Fusion: Practice and Applications | 2025

A Novel Behavioral Monitoring based Trust Model for enhancing Edge Security using Adaptive Neuro-fuzzy Inference System

The Internet of Things (IoT) is in a recent state of instability due to the flooding of virtual data. It is believed that IoT and cloud computing have met their maximum thresholds and loading them with data after this point will only deteriorate their performance. Hence, edge computing has been introduced to mitigate the processing burden of IoT. To meet the security demands of edge computing, we intend to combine the method of blockchain along with edge computing for a better solution. Accordingly, this paper proposes the introduction of a novel blockchain model that is based on artificial neural networks and trust estimation called the behavioral monitoring trust estimation model. Performance metrics such as accuracy, precision, recall, and F-measure are calculated under normal conditions and under the injection of attacks like false data injection, booting attack, and node capturing. The proposed behavioral monitoring trust classification model is compared with existing classifiers like Naive Bayes, K-nearest neighbor, Auto Encoder, Random Forest, and Support Vector Machine, and is found to have improved performance. Additional evaluation parameters like execution time, encryption time, storage cost, computational overhead, energy efficiency, and packet drop possibility are also calculated for the proposed model and compared with existing blockchain techniques of Bitcoin, Ethereum, Hyperledger, Direct and indirect trust model, and mutual trust chain based blockchain model. The proposed model achieved an accuracy of 95%, a precision score of 90%, a recall score of 94%, and an F-measure of 94% indicating superior performance.

groups

D. Jayakumar mail -

K. Santhosh Kumar mail

link https://doi.org/10.54216/FPA.170204

Volume & Issue

Vol. Volume 17 / Iss. Issue 2

Details open_in_new

Fusion: Practice and Applications | 2025

Enhancing Cloud Computing Efficiency with Crocodile Optimization Algorithm: A Novel Approach to Distributed Workload and VM Management

Cloud computing has introduced itself as a mighty mechanism for delivering customers through the service model with on-demand, scalable, and instant access to computer resources. It will conduct effective load balancing and resource management, high importance so that the cloud system works with optimized performance and resource utilization. This gives a new strategy in load balancing and virtual machine (VM) control in cloud computing applied in the field using the Crocodile Optimization Algorithm (COA) for better performance. Inspired by crocodile hunting behaviors, the COA-based strategy is adopted to balance loads and manage VMs. This approach seeks to balance the number of the workload given to VMs with respect to the processing power of VMs and also the distribution of workload. It best uses resources in such a way that tasks are dynamically distributed to VMs in such a way that response time is at its minimum, and thus overall efficiency is enhanced in cloud computing. On the other hand, COA-based load balancing incorporates VM management techniques like migration and scaling to be adjustable in relation to the changing conditions of the workload. This allows dynamically adjusting the allocation of resources with respect to current demands, in such a way that assures optimal utilization of computational resources with high performance. The proposed approach was evaluated using simulations through CloudSim, one of the most adopted tools for simulating cloud computing. The COA effectively works are divided between the VM, which in turn will lead to better response time for the user request and improve cloud resource utilization. That is to mean, subsequent research would be some type of unique attempt in the area of load balancing and VM management in cloud computing, based on the Crocodile Optimization Algorithm. This approach improves efficient cloud computing through the balancing of load distribution, maximization of resource utilization, and lowering of response time.

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Ibrahim A. Ibrahim mail -

Warshine Barry mail -

Narek Badjajian mail

link https://doi.org/10.54216/FPA.170205

Volume & Issue

Vol. Volume 17 / Iss. Issue 2

Details open_in_new

Fusion: Practice and Applications | 2025

Securing Drug Traceability: Block chain-Enhanced Privacy Protection and Anti-Counterfeit Measures in Pharmaceutical Supply Chains

The pharmaceutical industry encounters numerous challenges in the management of medications and ensuring their authenticity, as well as safeguarding sensitive information within the supply chain. Maintaining the integrity of drug manufacturing processes, transaction records, and patient data from unauthorized access or tampering is crucial. Any breach in security could undermine trust throughout the entire supply chain.  To mitigate these concerns, a multi-layered approach is employed. Initially, data encryption using QR codes with Attribute-Based Encryption provides a foundation for securing information. This is followed by an innovative strategy that combines Red Panda Optimization (RPO) Algorithm and Group Teaching Optimization algorithms (GTOA) to optimize encryption key selection. Finally, Multi-Party Computation (MPC) protocols along with Shamir's Secret Sharing enhances overall security measures. These procedures ensure that only authorized individuals have access to critical information essential for identifying counterfeit products and maintain confidentiality through Secure MPC verification without compromising sensitive details.

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Abdulrahman Mohammed Alshehri mail -

Thamer Alhussain mail

link https://doi.org/10.54216/FPA.170206

Volume & Issue

Vol. Volume 17 / Iss. Issue 2

Details open_in_new

Fusion: Practice and Applications | 2025

Machine Learning and Deep Learning Approaches for Detecting DDoS Attacks in Cloud Environments

Distributed Denial of Service (DDoS) attacks pose a significant threat to cloud computing environments, necessitating advanced detection methods. This review examines the application of Machine Learning (ML) and Deep Learning (DL) techniques for DDoS detection in cloud settings, focusing on research from 2019 to 2024. It evaluates the effectiveness of various ML and DL approaches, including traditional algorithms, ensemble methods, and advanced neural network architectures, while critically analyzing commonly used datasets for their relevance and limitations in cloud-specific scenarios. Despite improvements in detection accuracy and efficiency, challenges such as outdated datasets, scalability issues, and the need for real-time adaptive learning persist. Future research should focus on developing cloud-specific datasets, advanced feature engineering, explainable AI, and cross-layer detection approaches, with potential exploration of emerging technologies like quantum machine learning.

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Muhammad Asif Khan mail -

Mohd Faizal Ab Razak mail -

Zafril Rizal Bin M Azmi mail -

Ahmad Firdaus mail -

Abdul Hafeez Nuhu mail -

Syed Shuja Hussain mail

link https://doi.org/10.54216/FPA.170207

Volume & Issue

Vol. Volume 17 / Iss. Issue 2

Details open_in_new

Fusion: Practice and Applications | 2025

Optimization of Federated Learning Communication Costs through the Implementation of Cheetah Optimization Algorithm

Recently, Federated Learning (FL) has promptly gained aggregate interest owing to its emphasis on the data privacy of the user. As a privacy-preserving distributed learning algorithm, FL enables multiple parties to construct machine learning (ML) algorithms without exposing sensitive information. The distributed computation of FL may lead to drawn-out learning and constrained communication processes, which necessitate client-server communication cost optimization. The two hyperparameters that have a considerable effect on the FL performance are the number of local training passes and the ratio of chosen clients. Owing to training preference across different applications, it is challenging for the FL practitioner to manually choose these hyperparameters. Even though FL has resolved the problem of collaboration without compromising privacy, it has a transmission overhead because of repetitive model updating during training. Various researchers have introduced transmission-effective FL techniques for addressing these issues, but sufficient solutions are still lacking in cases where parties are in charge of data features. Therefore, this study develops an Optimization of Federated Learning Communication Costs through the Implementation of the Cheetah Optimization Algorithm (OFLCC-COA) technique. The OFLCC-COA technique is mainly applied for effectually optimizing the communication process in the FL to minimize the data transmission cost with the guarantee of enhanced model accuracy. The OFLCC-COA technique enhances the robust performance in unsteady network environment via the transmission of score values instead of large weights. Besides, the OFLCC-COA technique improves the communication efficiency of the network by transforming the form of data that clients send to servers. The performance analysis of the OFLCC-COA model occurs utilizing different performance measures. The simulation outcomes indicated that the OFLCC-COA model obtains superior performances over other methods in terms of distinct metrics

groups

Khalid Alleihaibi mail

link https://doi.org/10.54216/FPA.170208

Volume & Issue

Vol. Volume 17 / Iss. Issue 2

Details open_in_new

Fusion: Practice and Applications | 2025

Enhancing Urban Connectivity: Dynamic Implementation and Integration of Multi-IRS Systems in Smart Cities

This is in preparation to stand out in urban connectivity to be used faster for Multi-Intelligent Reflecting Surfaces (Multi-IRS) in the latest thirst response. It will determine in advance the application of IRS technology for electromagnetic wave control, so that it is fine-tuned at full power to boost signal transmission and coverage across the urban areas in high-density population. It outlines flexible strategies on how to integrate the Multi-IRS system with both past and urban future establishments in a view of making connected connectivity. In reality, multi-IRS integrated with foundational smart city technologies such as IoT, 5G networks, AI, and others are nothing but a leap toward accomplishing unparalleled data flow and connectivity, both very essential for the modern urban ecosystem. Detailed case studies have demonstrated how multi-IRS systems can enable the breaking of traditional barriers in connectivity: more essentially, it can offer higher bandwidth, lower latency, and increased communication effectiveness. This development marks one of the serious steps under the concept of smart cities, where the data will be spreading and flowing without barriers between the multifarious urban systems and services. Lastly, the paper concludes with a future-looking view of urban connectivity underscored through continuous innovation and research of multi-IRS applications within the smart city landscape. The study points out the fact that dynamic IRS implementation creates an indispensable role in the pathway for upcoming development in smart city connectivity solutions, thus making a case for sustained collaborative efforts in research, policy formulating, and technological innovation for realizing the full potential of IRS technology in taming the connectivity challenges of contemporary urban settings. Performance comparison between a sequential beam search and a proposed model across varying Rician Factors, showing the proposed model's superior channel gain progression from -57 dB at 5 dB to -48 dB at 30 dB, outperforming the sequential method in environments with strong direct signals.

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Israa Ali Al-Neami mail -

Alza A. Mahmod mail -

Alaa H Ahmed mail -

Sergey Drominko mail -

Erina Kovachiskaya mail

link https://doi.org/10.54216/FPA.170209

Volume & Issue

Vol. Volume 17 / Iss. Issue 2

Details open_in_new