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Journal of Neutrosophic and Fuzzy Systems | 2023

Approximate Solution of a Neutrosophic Nonlinear Van der Pol Oscillator Problem by Semi Analytical Method Using Thick Function

In this paper, an analytical method (Homotopy perturbation method HPM) is used for solving the initial value problem represented by a neutrosophic nonlinear Van der Pol oscillator equation (N-VDP) arising in applied dynamics using the thick function. We find the solutions of the (N-VDP) equation by HPM and then compare the numerical results with fourth order Runge-Kutta method (RK4). The results showed that the HPM lead to accurate and efficient results. Furthermore, these results of the HPM scheme and RK4 are implemented in Matlab.

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George A. Toma mail -
Fahed Farhood mail -
Taqi A. Alkhatib mail
link https://doi.org/10.54216/JNFS.060102

Volume & Issue

Vol. Volume 6 / Iss. Issue 1

Details open_in_new
Journal of Intelligent Systems and Internet of Things | 2020

A Machine Learning Approach for Energy-Efficient IoT Systems

  The energy challenge in IoT refers to the significant energy consumption of IoT devices, which can lead to sustainability issues, shorter battery life, and increased operating costs. IoT devices are known for their high energy consumption, and optimizing their energy usage can have a significant impact on sustainability and cost. Machine learning (ML) can learn from data and patterns to predict and control energy consumption in IoT systems, making them more energy efficient. The main contribution of this paper is the establishment of a novel deep learning framework for enhanced predictive modeling of energy consumption in IoT networks to help realize Energy-efficient IoT systems. our framework applies recurrent processing to capture long-term relations in the energy consumption of IoT appliances. Then, the self-attention mechanism is devised to help the model to focus on important predictive features.  Simulation experiments against the competing ML baselines demonstrate the predictive capability of our framework. 

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Mahmoud M. Ismail mail
link https://doi.org/10.54216/JISIoT.010105

Volume & Issue

Vol. Volume 1 / Iss. Issue 1

Details open_in_new
Journal of Intelligent Systems and Internet of Things | 2022

Federated Learning for Intelligent Resources Allocation in Internet of Things

By using federated learning (FL), multiple Internet-of-Things (IoT) devices can construct a shared learning model without sending raw data to a centralized server. While FL has come a long way, it still has a ways to go. Issues such as heterogeneous user equipment (UEs) and data that is not independently and uniformly distributed are still obstacles. Facilitating a numerous UEs to participate in the learning in each cycle poses a possible problem of the huge communication budget. A weighted adjoining factor is presented to the localized gradient descent, generalizing the present FedAvg to solve these concerns. At the start of each global round, the proposed FL method randomly selects a fraction of the UEs to perform stochastic gradient descent in parallel. Then, we utilize the suggested FL method in cellular IoT to reduce either total power usage or execution duration of FL, in which a straightforward but effective path-following method is constructed for its explanations. At last, obtained simulations on poorly balanced data are presented to show that the presented FL algorithm is superior to FedAvg in terms of performance with respect to fast convergence. Moreover, they show that the suggested algorithm needs significantly less time and energy to train than the FL algorithm does when users contribute heavily to the learning process. These findings provide strong support for the suggested FL algorithm as a potential paradigm change for training mobile IoT networks with limited bandwidth.

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Mahmoud Ismail mail -
Shereen Zaki mail
link https://doi.org/10.54216/JISIoT.070106

Volume & Issue

Vol. Volume 7 / Iss. Issue 1

Details open_in_new
International Journal of Neutrosophic Science | 2023

On the Split-Complex Neutrosophic Numbers and Their Algebraic Properties

The objective of this paper is to define for the first time the concept of split-complex numbers as a new generalization of classical split-complex numbers by using neutrosophic numbers. Also, we study the elementary properties of this new numerical class such as equations, conjugates, and vector spaces formed by it. On the other hand, some special AH-subspaces will be presented and handled with many corresponding examples.

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Abuobida M. A. Alfahal mail -
Yaser A. Alhasan mail -
Raja A. Abdulfatah mail -
Rozina Ali mail
link https://doi.org/10.54216/IJNS.200303

Volume & Issue

Vol. Volume 20 / Iss. Issue 3

Details open_in_new
International Journal of Neutrosophic Science | 2023

On the Solutions of Fermat's Diophantine Equation in 2-cyclic Refined Neutrosophic Ring of Integers

The Diophantine equation X^n+Y^n=Z^n is called the Fermat's Diophantine equation. Its solutions are called general Fermat's triples.The aim of this paper is to study the solutions of Fermat's Diophantine equation in the 2-cyclic refined neutrosophic ring of integers, where we determine all possible solutions of this Diophantine equation, as well as, the special case of Pythagoras triples.

groups
Abuobida M. A. Alfahal mail -
Yaser A. Alhasan mail -
Raja A. Abdulfatah mail -
Rozina Ali mail
link https://doi.org/10.54216/IJNS.200301

Volume & Issue

Vol. Volume 20 / Iss. Issue 3

Details open_in_new
Journal of Intelligent Systems and Internet of Things | 2021

Recurrent Model for Automatic Detection Cardiac Arrhythmia on the Internet of Healthcare Things

With the growing prevalence of the Internet of Health Things (IoHT), there is an increasing need for reliable and precise categorization of electrocardiogram (ECG) indications for the early detection of cardiovascular diseases. In this research, we propose a machine learning approach for ECG classification in IoHT applications. Our solution use wavelet transforms to clean the ECG records before passing them to the model. Then, a stack of long short-term memory (LSTM) cells is built to learn the temporal interrelations in the ECG signals and make accurate predictions. We assessed the performance of our model on a publicly available dataset of ECG signals, achieving an overall accuracy of 97.5%. The experimental findings demonstrate that our models can effectively classify ECG signals in IoHT applications, providing a valuable tool for the early discovery of vascular diseases. Furthermore, our model can be certainly incorporated into IoHT systems, providing a reliable and efficient solution for ECG classification.

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Waleed Abd Elkhalik mail
link https://doi.org/10.54216/JISIoT.020104

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new
Journal of Intelligent Systems and Internet of Things | 2022

Intelligent Learning System to Help People with Color Impairment Using Image Processing Algorithms

This study presents a novel framework to help people with color impairment in identifying colors. The proposed framework consists of three stages. These stages are electronically performing the Ishihara test, performing the color blindness type recognition test, and guiding the person to color by voice. The first stage, the person is subjected to an electronic color blindness test, by displaying different plates containing several points of different sizes and colors. The person is required to correctly identify the number or shape in the plate and at the end, the system determines the extent to which a person is color blind. The second stage is a color recognition test to determine the type of color blindness. If there is difficulty in determining red, this is called protanopia. But the difficulty in identifying the green color is called deuteranopia. While the inability to recognize the blue color is called tritanopia. And finally, the difficulty in identifying the colored style is called achromatopsia. The third stage is assistance phase and is divided into three subsectors are: smart educational system, identifying colors and extracting the content. The proposed system differs from other systems in that it is an integrated system. It includes identifying color blindness, determining its type, and finally aiding color blindness person. Also, it is the first system that deals with the rare type of color blindness called achromatopsia in addition to its other three types. The results obtained confirmed that the proposed system as well as the smart educational system are characterized by high accuracy and effectiveness.

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R.A.E. Ibrahim mail -
A. E. E. El Alfi mail -
A. AdbElbadie Abdallah mail
link https://doi.org/10.54216/JISIoT.070206

Volume & Issue

Vol. Volume 7 / Iss. Issue 2

Details open_in_new
Journal of Intelligent Systems and Internet of Things | 2022

Federated Knowledge Purification for Responsive Internet of Things

 The Internet of Things (IoT) has become a ubiquitous technology that enables the collection and analysis of large amounts of data. However, the limited resources of IoT devices pose challenges to enabling responsive decision-making. Many communications are required for network training, yet network updates can be very big if they include many parameters. Participants and the IoT ecosystem both bear the brunt of federated learning's high Latency due to the magnitude of its communications infrastructure requirements. In this paper, we propose a Federated Knowledge Purification (FKP) approach based on dynamic reciprocal knowledge purification and adaptive gradient compression, two strategies that allow for low-latency communication without sacrificing effectiveness, which enables responsive IoT devices with limited resources. The FKP approach leverages a collaborative learning approach to enable IoT devices to learn from each other's experiences while preserving the privacy of their data. A smaller model is trained on the aggregated knowledge of a larger model trained on a centralized server, and this smaller model can be deployed on IoT devices to enable responsive decision-making with limited computational resources. Experimental results demonstrate the effectiveness of the proposed approach in improving the performance of IoT devices while maintaining the privacy of their data. The proposed approach also outperforms existing federated learning methods in terms of communication efficiency and convergence speed.

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Things Irina V. Pustokhina mail -
Denis A. Pustokhin mail
link https://doi.org/10.54216/JISIoT.070207

Volume & Issue

Vol. Volume 7 / Iss. Issue 2

Details open_in_new
Prospects for Applied Mathematics and Data Analysis | 2023

Computerized Study and Analysis Electrical Power Systems Parameters

In this paper, a program for analyzing potential events and designing preventive measures to ensure safe operation of electrical power systems was developed, which was published in the Journal of Al-Baath University. The new visual software system performs all the functions of the previous program, in addition to a set of developed options, studies and comparisons. It also features a graphical method for entering electrical network data and conforms to software engineering standards, with an analytical study based on an approved methodology, the Unified Modeling Language (UML). The spiral software model was chosen during the research, which made it possible to obtain a reliable software product that is characterized by the highest possible standards. In this paper, the parameters of the electrical power system on a 6-busbar network were analyzed and studied, and the effect of changing the power factor on the possibility of finding the optimal solution, whether by changing generation or by changing generation and decreasing loads, was studied. The program's effectiveness, flexibility and accuracy of results have been proven.

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Ousama Asaad Bahbouh mail
link https://doi.org/10.54216/PAMDA.010205

Volume & Issue

Vol. Volume 1 / Iss. Issue 2

Details open_in_new