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MohamedElhosemy; MohamedElhoseny

Journal of Intelligent Systems and Internet of Things | 2019

Intelligent Differential Evolution based Feature Selection with Deep Neural Network for Intrusion Detection in Wireless Sensor Networks

Wireless sensor network (WSN) is mainly utilized for data gathering and surveillance applications. As WSN is majorly deployed in harsh and hostile environments, security remains a critical issue which needs to be resolved. An intrusion detection system (IDS) is one of the proficient ways used to determine the presence of abnormal behaviors (i.e. intrusions) in the network. Earlier studies have focused on the design of machine learning (ML) and deep learning (ML) models to design IDS. With this motivation, this paper presents an intelligent differential evolution based feature selection with deep neural network (IDEFS-DNN) for intrusion detection in WSN. The proposed IDEFS-DNN model aims to select optimum set of features and classify the intrusions in the network. In addition, the IDEFS-DNN technique involves the design of IDEFS technique to choose a subset of optimum features. Moreover, the chosen features are fed into the DNN technique for classification purposes. The usage of IDEFS technique helps to reduce the complexity and increase the classifier outcome. In order to portray the improved performance of the IDEFS-DNN technique, wide ranging experiments take place on benchmark datasets and the results are inspected under varying aspects. The simulation results ensured the enhanced intrusion detection performance of the IDEFS-DNN technique over the other IDS models.

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Ibrahim M. EL-Hasnony mail

link https://doi.org/10.54216/JISIoT.000204

Volume & Issue

Vol. Volume 0 / Iss. Issue 2

Details open_in_new

Journal of Cybersecurity and Information Management | 2019

Dragonfly Algorithm with Gated Recurrent Unit for Cybersecurity in Social Networking

The advancements of information technologies and wireless networks have created open online communication channels. Inappropriately, trolls have abused the technologies to impose cyberattacks and threats. Automated cybersecurity solutions are essential to avoid the threats and security issues in social media. This paper presents an efficient dragonfly algorithm (DFA) with gated recurrent unit (GRU) for cybersecurity in social networking. The proposed DFA-GRU model aims to determine the social networking data into neural statements or insult (cyberbullying) statements. Besides, the DFA-GRU model primarily undergoes preprocessing to get rid of unwanted data and TF-IDF vectorizer is used. In addition, the GRU model is employed for the classification process in which the hyperparameters are optimally adjusted by the use of DFA, and thereby the overall classification results get improved. The performance validation of the DFA-GRU model is carried out using benchmark dataset and the results are examined under varying aspects. The experimental outcome highlighted the enhanced performance of the DFA-GRU model interms of distinct measures.

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Yutao Han mail -

Ibrahim M. EL-Hasnony mail -

Wenbo Cai mail

link https://doi.org/10.54216/JCIM.000107

Volume & Issue

Vol. Volume 0 / Iss. Issue 2

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Journal of Intelligent Systems and Internet of Things | 2025

A Hybrid Heuristic AI Technique for Enhancing Intrusion Detection Systems in IoT Environments

In the evolving landscape of the Internet of Things (IoT), effective intrusion detection is paramount for maintaining security and data integrity. This study introduces a hybrid heuristic technique utilizing artificial intelligence for enhancing intrusion detection systems (IDS) in IoT environments. By integrating various machine learning models, the research focuses on training, tuning, and validating a sequential neural network to predict intrusion occurrences based on extensive data analysis. The methodology involves modelling, which starts with training machine learning algorithms to predict labels from features, tuning the models to meet organizational requirements, and validating them using holdout data. Key machine learning techniques explored include logistic regression, k-nearest neighbors (KNN), naive Bayes, support vector machines (SVM), decision trees, random forests, and neural networks. Each technique's applicability to classification tasks, particularly binary and multivariate scenarios, is discussed in the context of enhancing IDS capabilities. A sequential neural network model, comprising multiple dense and dropout layers, was developed and trained with 148,033 parameters to achieve high accuracy and robustness. The architecture's effectiveness in learning intricate patterns associated with malicious activities while avoiding overfitting is emphasized. The study demonstrates the model's proficiency in binary classification tasks, which is critical for distinguishing between normal and anomalous behaviors in IoT systems. The results indicate that the neural network, optimized using the hybrid heuristic approach, shows a significant reduction in validation loss and a steady improvement in accuracy over multiple epochs. Despite initial overfitting signs, the model maintains high performance on unseen data, underscoring the importance of ongoing model assessment and tuning.

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Yousra Abdul Alsahib S. Aldeen mail -

Fadhel K. Jabor mail -

Ghufran A. Omran mail -

Mohammed Hamid Kassem mail -

Raghad Hamid Kassem mail -

Ali Naseer Abood mail

link https://doi.org/10.54216/JISIoT.140101

Volume & Issue

Vol. Volume 14 / Iss. Issue 1

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2025

Digital Automatic of Clothing Design Cad Based on Intelligent Sensing Technology

Clothing design plays an important role in personal image expression and social and cultural transmission. The traditional fashion design method has many problems, such as low efficiency and large design error, and it is difficult to bring users better wearing experience. In order to meet different users’ Design needs, reduce design errors, and improve users’ satisfaction with design results, this paper combined with intelligent sensing technology, conducted in-depth research on digital automation analysis of clothing design CAD (Computer Aided Design). Aiming at the clothing design process, this paper first constructed a brand-new clothing design CAD system, using the depth transducer to solve the 3D information of the relevant feature points, and realized the accurate acquisition of the human body feature size information. Through the registration of adjacent frame point data, the 3D human body modeling was carried out. Then, according to the user’s physical characteristics and related information collected by the sensor, the paper compared the user’s characteristic information to filter out the user’s preferences, and used the recommendation algorithm to calculate the corresponding parameters to realize the intelligent choice of clothing styles. Finally, through the measurement of each index by the sensor, the size adjustment of the garment and the specific design of the garment were realized. In order to verify the effect of clothing design CAD system based on intelligent sensing technology, this paper conducted system tests. The results showed that in terms of clothing comfort, clothing quality and clothing functionality, the number of users satisfied and very satisfied reached 50.4%, 47.9% and 51.3%, respectively. From the overall survey results, the system has a high degree of user satisfaction. The research conclusion of this paper shows that the digital automatic analysis of clothing design CAD based on intelligent sensing technology can effectively meet the needs of users, improve their wearing experience, and promote the intelligent development of clothing design.

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Hai Liu mail -

Lei Hu mail

link https://doi.org/10.54216/JISIoT.140102

Volume & Issue

Vol. Volume 14 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2021

Air Quality Index Analysis Using Single-Valued Neutrosophic Plithogenic Graph for Multi-Decision Process

Recently, Plithogenic set and its graphical structure visualization is stuide for dealing with multi-attribute data set. In this pocess a problem arises while characterization of uncertainty in tue, false and uncertain regions, independently. One of the suitable examples is Air Quality Index and its impact on human health contains multi-valued attributes. In this case the conflict may arise among two experts about acceptation, rejection and uncertain impact of AQI for human health. To resolve this issue a single-valued neutrosophic Plithogenic set and its graphical strcutue visualization is discussed in this paper with an illustrative example.

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Prem Kumar Singh mail

link https://doi.org/10.54216/IJNS.160103

Volume & Issue

Vol. Volume 16 / Iss. Issue 1

Details open_in_new

International Journal of BIM and Engineering Science | 2019

Practical Approach for Paving the Way to Motivate BIM Non-users to Adopt BIM

Typically, the Architecture, Engineering, and Construction (AEC) industry is considered one of the most effective contributor to the national developments worldwide. However, the AEC industry is facing myriad challenges due to the pressing calls for creativity and innovative solutions. Several issues are confronted such as failure to meet client satisfaction, delays in delivering projects on time, cost overruns, low quality, conflicts among parties, safety issues, increasing requests for change orders, tremendous increases in materials waste and project complexity. Building Information Modeling (BIM) is rapidly growing worldwide as a viable tool for improving the efficiency of the AEC industry to solve its salient issues. However, BIM is seldom adopted on the government level, especially in the developing countries. This study aims to explore the stakeholders’ perceptions on the benefits of BIM and the barriers that hindered its adoption. Furthermore, practical solutions to motivate BIM non-users to adopt BIM are proposed. A questionnaire was sent to BIM users and non-users in the Kingdom of Saudi Arabia (KSA) as a case study. The key findings that deterred the implementation of BIM were personal correlated issues such as resistance to change and lack of appropriate awareness of BIM. This study convinces the industry players concerning BIM benefits and reveals the barriers and their potential solutions to encourage them to reap the benefits from BIM adoption.

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Ashraf Elhendawi mail -

Hany Omar mail -

Emad Elbeltagi mail -

Andrew Smith mail

link https://doi.org/10.54216/IJBES.020201

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

Details open_in_new

International Journal of BIM and Engineering Science | 2019

A Comparative Review of Building Information Modeling Frameworks

The building sector influences the Gross Domestic Product (GDP) of many countries. There is a vast amount of waste generated in the building process, with many projects suffering from delivery delays, running over budget, and resulting in buildings of minimal quality. Building Information Modeling (BIM) has shown great potential towards solving these problems. BIM sets frameworks for Architects, Engineers, and Contractors (AEC), enhancing management of the building process. This paper analyzes select framework methods, tools, and processes, identifying key guidelines required to create a BIM framework customized to local requirements; this will have a positive effect on the construction industry by lowering the cost of buildings and improving the communication among parties, and leading to the development of frameworks based on local indicators. A comprehensive literature review was conducted to determine components and factors from structure frameworks with the main findings then classified and categorized into the following sectors -- government support, maturity level measurement, standards, protocol, database, and education plan. This permits the development of a comparison highlighting the frameworks’ differences and summing up possible strategies for BIM implementation on several bases, such as region differentiation and the local industries’ Political, Economic, Socio-Cultural, Technological (PEST) aspects, allowing for greater understanding of BIM implementation on various scales. The selection of the BIM frameworks was dependent on specific criteria with a minimum score of 4 out of 5 required to merit inclusion. Three strategies for the creation of a BIM framework were discovered and were seen to vary across regions. The discovery of these strategies lays the groundwork for future research into the development of these frameworks to determine the potential advantages and downsides of each.

groups

Abdulaziz Banawi mail -

Obaid Aljobaly mail -

Cyril Ahiable mail

link https://doi.org/10.54216/IJBES.020202

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

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International Journal of BIM and Engineering Science | 2020

Influence of Partnering Agreements Associated with BIM Adoption on Stakeholder’s Behaviour in Construction Mega-Projects

Construction mega-projects are typically associated with cost overruns and time delays due to conflicts of interest between diverse stakeholders. This research investigates the influence of the partnering approach and the adoption of Design and Build (D-B) contractual agreement on the behaviour of stakeholders on mega-projects. Through a case study, the significant factors that influence stakeholder management are appraised, such as cooperation, developing trust, and a dearth of communication. The research concluded that mutual trust, transparency, leadership, the well-defined scope of work, a clear definition of responsibilities, collaboration, and training are the main success factors of partnering projects. The research also emphasised that Building Information Modelling (BIM) plays a vital role to secure the mentioned key successful factors for partnering. Furthermore, BIM facilitates achieving project objectives with the adoption of D-B contracts. This research contributes to the developing body of knowledge addressing the application of partnering in construction. The outcomes of this research will be beneficial for clients, contractors, project managers, and contract managers when taking into account future execution plans for D-B projects. Forthcoming studies can develop a framework to combine various stakeholders to obtain optimum satisfaction.

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Martin Evans mail -

Peter Farrell mail -

Emad Elbeltagi mail -

Ayman Mashali mail -

Ashraf Elhendawi mail

link https://doi.org/10.54216/IJBES.030101

Volume & Issue

Vol. Volume 3 / Iss. issue 1

Details open_in_new

International Journal of BIM and Engineering Science | 2020

Analysis of Barriers and Drivers for BIM Adoption

Research on 'digitalization and collaboration' in the construction industry has been gaining momentum in the recent academic engagements. Despite its existence in many industries (i.e. financial services, retailing, publishing and travelling) for over ten years, it is yet to catch up by the construction market; this is due to several challenges whose existence are more dynamic and contextual than generic to various countries. The problems are defined in many studies across borders, but their impacts varied with countries. This case is equally the same to drivers toward the adoption of BIM. This study analyses barriers and drivers to BIM adoption in the Nigerian construction industry from adopters and non-adopters perspectives as to allow an informed decision in developing a strategy for macro BIM adoption. Primary data fetched from professional stakeholders through an online questionnaire survey were analysed using SPSS software and Microsoft Excel. This investigation reveals the most significant barriers against BIM adoption as Lack of expertise, Lack of standardization and protocols to mention but a few. And, most influential drivers from both adopters and non-adopters as Availability of trained professionals to handle the tools, Proof of cost savings by its adoption, BIM Software affordability, and awareness of the technology among the industry stakeholders. The adopters and non-adopters groups have nearly equal Percentage Disagreement (PD) and Percentage Agreement (PA) for both the barriers and drivers to BIM adoption. Thus, this suggests that the adopters are still at the early stage of BIM adoption, so have nearly the same perceptions with the non-adopters. The study recommends proper consideration of the established barriers and drivers while developing any strategy for effective BIM adoption. Further face-to-face (interview) study is necessary to explore more and in-depth challenges to adoption of BIM in the industry; and as the industry is getting more aware of the BIM, periodic evaluation of the critical barriers and drivers is vital.

groups

Mansur Hamma-adama mail -

Tahar Kouider mail -

Huda Salman mail

link https://doi.org/10.54216/IJBES.030102

Volume & Issue

Vol. Volume 3 / Iss. issue 1

Details open_in_new

Journal of Neutrosophic and Fuzzy Systems |