Reliable Data Communication Model for Fog Computing

Reem; Aditi

doi:https://doi.org/10.54216/IJWAC.020202

International Journal of Neutrosophic Science | 2022

Mapping on Interval Complex Neutrosophic Soft Sets

The neutrosophic idea is a fertile environment adaptable to different mathematical tools. This paper aims to introduce the mapping of complex interval neutrosophic soft sets (MI-CNSSs). Further, the images and inverse images of complex interval neutrosophic soft sets and their properties are explored. These will be supported by concrete examples, and this paper will present some theorems about complex interval neutrosophic soft images and inverse images.

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Faisal Al-Sharqi mail -

Abd Ghafur Ahmad mail -

Ashraf Al-Quran mail

link https://doi.org/10.54216/IJNS.190406

Volume & Issue

Vol. Volume 19 / Iss. Issue 4

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2022

Smart Learning in the Ecosystem: Examines Smart Learning Structural Design Features Considering IoT and IoB

The Internet of Things (IoT), IoT-Education, and smartness are emerging technology used in Industry 4.0 to enable smarter education systems that can be adapted to different learners. Using IoT as an acceptable and useable infrastructure is one of the leaders' innovative strategies. It is an intelligence enabler that will be integrated into many essential parts of the future world. This study looks at the key elements of smart learning structural design, such as IoT and IoB (internet of behavior), as well as the major issues that must be addressed when creating smart educational environments that allow for personalisation. To incorporate smart learning environments into the learning ecosystem and educational contexts, IoT, IoB, and cloud services for a smart education ecosystem must be used to orchestrate formal and informal learning. This study emphasizes smart learning paradigms and smart learning environments and the importance of involving future users in the design process to broaden understanding of the design and implementation of innovative systems for smart learning.

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Ossama H. Embarak mail -

Maryam J. Almesmari mail -

Fatima R. Aldarmaki mail

link https://doi.org/10.54216/JISIoT.070102

Volume & Issue

Vol. Volume 7 / Iss. Issue 1

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2020

An intelligent Multi-criteria Decision-making Model for Sustainable Higher Education Strategy Selection

This study provides a means for institutions and administrations to develop plans while taking into consideration the strategic linkages. Making strategic decisions on their programming may benefit institutions and governments when relevant material is examined and talks with higher education specialists are held (HE). To handle disagreement and different criteria, multi-criteria decision-making (MCDM) models are utilized. The most effective solution was evaluated using the new multi-criteria technique known as MABAC (Multi-Attributive Border Approximation area Comparison). Following the computation of the criterion weights, the MABAC is used to rank the options. The recommended approach may be used by institutions as well as central planners (usually the government) in higher education policy.

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N. Metawa mail -

Luka Bowanga mail

link https://doi.org/10.54216/JISIoT.010204

Volume & Issue

Vol. Volume 1 / Iss. Issue 2

Details open_in_new

International Journal of Wireless and Ad Hoc Communication | 2022

Quality of Service in Mobile Adhoc Networks with Non-Saturation Conditions

Numerous research has been conducted in order to investigate the performance of IEEE 802.11LEACH for a single-cell Wireless Local Area Network (WLAN) under saturation conditions. Saturation conditions are those in which it is anticipated that the queues of nodes will never be empty. To put it another way, there is always a packet waiting to be sent out from each and every node in the network. The term "infinite load" refers to the condition of saturation, which is a situation that may be regarded as having an endless load. Even though conducting an analysis under saturated conditions may provide some insight into how well the network operates in a high-pressure setting, this strategy does not appear to be practical because there is a possibility that the network will not always be at capacity. Even though conducting such an analysis under saturation circumstances may provide some insight into how well the network operates in a high-pressure setting, it is still not practical. When using CQSR, the source is aware of the correlation that exists between the many different paths that go to the destination. When it comes to the provision of quality service in an ad hoc network, having several pathways among a specific cause and an endpoint may be of assistance in the following scenarios. Having multiple pathways between a source and a destination may also be of assistance when it comes to the provision of quality service. It is feasible that a single channel will not be able to deliver adequate resources to meet the desired quality of service if the resources of mobile nodes are limited. This scenario might occur if mobile nodes are subject to resource limitations. The requirements of the application in terms of the quality of service might, however, be satisfied by the resources located along any one of the many possible paths that could exist between the specified pair of nodes. It seems likely that this will turn out to be the situation. The task force may be dispersed over a number of different routes if there are adequate resources available along each route. To put it another way, data packets are sent along each path that satisfies the criteria for acceptable quality-of-service levels. If you use many routes instead of just one, you may be able to obtain a throughput that is far higher than you would with a single route. In the previous proposed work, we did an analysis of IEEE 802.11 LEACH for an ad hoc network under saturation conditions. Saturation circumstances refer to scenarios in which it is believed that the queues of nodes are never empty. On the other hand, it is likely that the nodes that make up an ad hoc network will not always be totally filled.

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Harith Yas mail -

Manal M. Nasir mail

link https://doi.org/10.54216/IJWAC.050205

Volume & Issue

Vol. Volume 5 / Iss. Issue 2

Details open_in_new

Journal of Artificial Intelligence and Metaheuristics | 2022

Arrhythmia Modern Classification Techniques: A Review

Artificial intelligence methods are utilized in biological signal processing to locate and extract interesting data. The examination of ECG signal characteristics is crucial for the diagnosis of cardiac disease. This heart condition, known as arrhythmia, is quite prevalent. To put it simply, an irregular heartbeat is known as cardiac arrhythmia. It manifests itself when the heart beats abnormally (too slowly, too quickly, or erratically) for no apparent reason. Specifically, the ECG features of the PR, QRS, T, PQ, QT, RR, and cardiac frequency and rhythm are analyzed to diagnose cardiac arrhythmias. The performance of several arrhythmia classification and detection models is analyzed in this work through extensive simulations, emphasizing the most recent developments in this field. Ultimately, the research provides new perspectives on arrhythmia classification methods to address the shortcomings of the current approaches.

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Mohamed Saber mail -

Mostafa Abotaleb mail

link https://doi.org/10.54216/JAIM.010205

Volume & Issue

Vol. Volume 1 / Iss. Issue 2

Details open_in_new

Journal of Artificial Intelligence and Metaheuristics | 2022

Evaluating the Effect of Optimized Voting Using Hybrid Particle Swarm and Grey Wolf Algorithm on the Classification of the Zoo Dataset

When there are numerous possible solutions for a given class in a given problem, majority voting or plurality voting is typically employed. One common technique for improving classification accuracy is bagging, which involves training many classifiers on slightly different datasets and then voting on the combined results. In this research, we examine how alternative voting procedures affect the efficiency of two distinct classification algorithms applied to datasets of varying complexity. Despite the increased computing cost associated with determining preference order, the results show that the single transferable vote can be a suitable alternative to plurality voting.

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Doaa S. Khafaga mail -

Hussein Alkattan mail -

Alhumaima A. Subhi mail

link https://doi.org/10.54216/JAIM.020101

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2022

Intelligent Wheat Types Classification Model Using New Voting Classifier

When assessing the quality of the grain supply chain's quality, it is essential to identify and authenticate wheat types, as this is where the process begins with the examination of seeds. Manual inspection by eye is used for both grain identification and confirmation. High-speed, low-effort options became available thanks to automatic classification methods based on machine learning and computer vision. To this day, classifying at the varietal level is still challenging. Classification of wheat seeds was performed using machine learning techniques in this work. Wheat area, wheat perimeter, compactness, kernel length, kernel width, asymmetry coefficient, and kernel groove length are the 7 physical parameters used to categorize the seeds. The dataset includes 210 separate instances of wheat kernels, and was compiled from the UCI library. The 70 components of the dataset were selected randomly and included wheat kernels from three different varieties: Kama, Rosa, and Canadian. In the first stage, we use single machine learning models for classification, including multilayer neural networks, decision trees, and support vector machines. Each algorithm's output is measured against that of the machine learning ensemble method, which is optimized using the whale optimization and stochastic fractal search algorithms. In the end, the findings show that the proposed optimized ensemble is achieving promising results when compared to single machine learning models.

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Abdelaziz A. Abdelhamid mail -

El-Sayed M. El-Kenawy mail -

Abdelhameed Ibrahim mail -

Marwa M. Eid mail

link https://doi.org/10.54216/JISIoT.070103

Volume & Issue

Vol. Volume 7 / Iss. Issue 1

Details open_in_new

Journal of Cybersecurity and Information Management | 2022

Detection and Classification of Malware Using Guided Whale Optimization Algorithm for Voting Ensemble

Malware is software that is designed to cause damage to computer systems. Locating malicious software is a crucial task in the cybersecurity industry. Malware authors and security experts are locked in a never-ending conflict. In order to combat modern malware, which often exhibits polymorphic behavior and a wide range of characteristics, novel countermeasures have had to be created. Here, we present a hybrid learning approach to malware detection and classification. In this scenario, we have merged the machine learning techniques of Random Forest and K-Nearest Neighbor Classifier to develop a hybrid learning model. We used current malware and an updated dataset of 10,000 examples of malicious and benign files, with 78 feature values and 6 different malware classes to deal with. We compared the model's results with those of current approaches after training it for both binary and multi-class classification. The suggested methodology may be utilized to create an anti-malware application that is capable of detecting malware on newly collected data.

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Marwa M. Eid mail -

M. I. Fath Allah mail

link https://doi.org/10.54216/JCIM.100102

Volume & Issue

Vol. Volume 10 / Iss. Issue 1

Details open_in_new

International Journal of Wireless and Ad Hoc Communication | 2021

Blockchain Communication Platform Selection in IoT Healthcare Industry using MARCOS

The Internet of Things (IoT) healthcare industry is under tremendous pressure to simplify its secure data communication processes. Patients are beginning to consider healthcare services, such as those relating to wellness promotion, illness prevention, diagnosis, care, and recovery, as ongoing cycles. With the prevalence of chronic illnesses on the rise and public perceptions of healthcare shifting, many people increasingly see modern health services as ongoing commitments. Using data provided through the most cutting-edge technology, efficient healthcare systems should reliably provide all their patients with access to the high-quality, comprehensive medical treatment they can afford. So, this study presents a neutrosophic multicriteria decision-making (MCDM) model to optimize the selection of blockchain communication platforms in IoT healthcare applications. To identify the best blockchain platform for use in healthcare, the Measurement of Alternatives and Ranking according to the Compromise Solution (MARCOS) technique was created. The proposed model improves the efficiency, accuracy, and reliability for better Blockchain secure communication in the IoT healthcare industry.  

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Mahmoud Zaher mail -

Nashaat EL-Khameesy ElGhitany mail

link https://doi.org/10.54216/IJWAC.020104

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

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International Journal of Wireless and Ad Hoc Communication | 2021

Reliable Data Communication Model for Fog Computing

To maintain data privacy and control who has access to what in the cloud, attribute-based encryption might be utilized. Attribute security is violated when apparent qualities are introduced to the encrypted message to assist people to identify necessary details in vast systems. To offer an effective attribute-based access control with an authorized search strategy, this research expands the anonymous key-policy attribute-based encryption (AKP-ABE) to provide fine-grained data retrieval while safeguarding attribute privacy (EACAS). In EACAS, data users may generate the trapdoor using the secret key supplied by data owners and conduct searches based on access restrictions to get the relevant data. Cryptographic protocols and trapdoor generation use a synthetic property devoid of syntactic significance to provide an attribute-based search on the exported encoded information in the fog. Data owners may implement granular access control on their outsourced data by establishing the search criteria that will be used by data consumers to locate relevant content based on protected attributes. We show that compared to the state-of-the-art methods, EACAS requires less time and space to process and store data. 

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Reem Atassi mail -

Aditi Sharma mail

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

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

Details open_in_new