The Neutrosophic Hyperbolic Functions

Yaser A.; Iqbal A.; Eman A.; Suliman

doi:https://doi.org/10.54216/IJNS.200304

Neutrosophic and Information Fusion | 2023

Neutrosophic Sets and Metaheuristic Optimization: A Survey

Smarandache presents neutrosophic sets and provides a domain area that is made up of three separate subsets to reflect the various kinds of uncertainty. Neutrosophic sets are defined as the sets where every other element of the universe possesses a degree of truthiness, indeterminacy, and falsity, which range from 0 to 1, and where these degrees are subsets of the neutrosophic sets that are independent of each other. Neutrosophic sets are also known as neutrosophical subsets. In the neutrosophic sets, impreciseness is represented as truth and falsity functions, but the indeterminacy function represents degrees of belongingness and non-belongingness and differentiates between absoluteness and relativeness. Neutrosophic sets can deal with the unpredictability of the system and cut down on the paralysis brought on by conflicting information thanks to this notation. As a result, one might argue that this capacity is the single most significant benefit offered by neutrosophic sets in comparison to the many other forms of fuzzy extensions. By making use of these three functions, neutrosophic sets are able to create a domain area. This area makes it possible for various kinds of mathematical operations to be carried out separately despite the presence of uncertainty. Due to the fact that the behavior of these methodologies is inspired by Nature and its capacity for adapting to issues, in addition to the potential for combining more than one method to reach the best alternatives, metaheuristic algorithms are employed to initiate the finest or the best possible alternatives to a lot of optimization techniques. This is possible because metaheuristic algorithms have the ability to adapt to problems. The fact that numerous academics have utilized these techniques with neutrosophic science to offer several systems in recent years was the impetus for writing this overview study in the first place, which was based on the above rationale.

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Ahmed Abdelhafeez mail -

Ahmed E Fakhry mail -

Nariman A. Khalil mail

link https://doi.org/10.54216/NIF.010105

Volume & Issue

Vol. Volume 1 / Iss. Issue 1

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2023

Forecasting COVID-19 Infection Using Encoder-Decoder LSTM and Attention LSTM Algorithms

The COVID-19 epidemic has in fact placed the whole community in a dire predicament that has led to numerous tragedies, including an economic downturn, political unrest, and job losses. Forecasting and identifying COVID-19 infection cases is crucial for the government at all levels because the pandemic grows exponentially and results in fatalities. Hence, by giving information about the spread of the epidemic, the government can move quickly at multiple levels to establish new policies and modalities in order to minimize the trajectory of the COVID-19 pandemic's effects on both public health and the economic sectors. Forecasting models for COVID-19 infection cases in the Ural region in Russia were developed using two deep Long Short-Term Memory (LSTM) learning-based approaches namely Encoder–Decoder LSTM and Attention LSTM algorithms. The models were evaluated based on five standard performance evaluation metrics which include Mean Square Error (MSE), Mean Absolute Error (MAE), Root MSE (RMSE), Relative RMSE (RRMSE), and coefficient of determination (R2). However, the Encoder–Decoder LSTM deep learning-based forecasting model achieved the best performance results (MSE=32794.09, MAE=168.56, RMSE=181.09, RRMSE=13.46, and R2=0.87) compared to the model developed with Attention LSTM models.

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Khder Alakkari mail -

Alhumaima Ali Subhi mail -

Hussein Alkattan mail -

Ammar Kadi mail -

Artem Malinin mail -

Irina Potoroko mail -

Mostafa Abotaleb mail -

El-Sayed M El-kenawy mail

link https://doi.org/10.54216/JISIoT.080202

Volume & Issue

Vol. Volume 8 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2023

Smart Security Area (SSA) for Radar system technology

Our ability to align with the trend of innovations in science and technology will not only emancipate ignorance but also unfold our ability to evaluate, understand and predict possibilities in our society, environment, and the world at large. Radar system technology gives us the privilege to achieve the above-mentioned fact. The word Radar is an acronym for Radio Detection and Ranging. It is a mean of getting information about a distant target, by sending electromagnetic waves to them and analyzing the echoes from the target to generate relevant reports about the target. In this paper, we will focus on some metrics and the effect of changes in them on the performance of the radar system using the MATLAB Radar Designer.

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Shimaa A. Hussein mail -

Eslam Hesham mail

link https://doi.org/10.54216/JISIoT.080203

Volume & Issue

Vol. Volume 8 / Iss. Issue 2

Details open_in_new

Galoitica: Journal of Mathematical Structures and Applications | 2023

Approximate Solution of Boundary Value Problem for Heat Equation after Represented by Volterra Integral Equation of the First Kind

In this work, we study the regularization method for solving the Boundary Value Problem (BVP) for heat equation. The discretization method applied with two variables on Volterra integral equation in order to covert the problem into a linear operator equation after applied the separation of variables method to solve the partial differential equation. The regularization way used to obtain the estimate solution by using the Lavrentiev regularization method.

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H.K. Al-Mahdawi mail -

Mostafa Abotaleb mail -

Hussein Alkattan mail -

El-Sayed M El-kenawy mail

link https://doi.org/10.54216/GJMSA.030205

Volume & Issue

Vol. Volume 3 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2023

Smart Sensor Networks for Industrial IoT Applications

Smart Sensor Networks (SSNs) are an indispensable part of the Industrial Internet of Things (IIoT), which seeks to improve efficiency, productivity, and safety in different industrial applications. SSNs consist of a large number of sensors, regularly deployed in a wireless ad-hoc network, which communicates with each other and with other devices, such as gateways and servers. Nevertheless, the building of SSNs in IIoT environments encounters many challenges, such as trust management, data reliability, privacy, and security. These challenges necessitate proposing novel solutions and protocols, to provide a reliable, secure, and efficient SSN. To this end, this study presents a novel DL system that can effectively discriminate between normal traffics and malicious traffic in SSNs. A convolutional feature extractor is developed to learn important discriminative features necessary for the early detection of security threats in SSNs. Then, an improved LSTM (ILSTM) is presented to model the temporal dynamics of the SSNs flows, which helps model long interdependency between traffic samples. A focal loss function is applied to deal with the imbalance between class samples. Experimental analysis is performed on an open-source SSN security dataset, named WSN-DS, the findings demonstrated the competitive advantages of our system over the prevailing solutions.

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Nihal N. Mostafa mail -

Esmeralda Kazia mail

link https://doi.org/10.54216/JISIoT.080204

Volume & Issue

Vol. Volume 8 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2023

AI-Driven Smart Homes: Challenges and Opportunities

As AI-based smart homes become increasingly popular, there is a need to better understand the benefits and challenges of this emerging technology. A survey on AI-based smart homes can provide valuable insights into user needs, adoption rates, user satisfaction, barriers to adoption, and opportunities for innovation. This research overviews the cutting-edge literature on smart home development with an emphasis on the utilization of artificial intelligence (AI) approaches in this application area. We begin with a review of AI technologies and the smart home necessities needed to implement AI. Then, we introduce several applications of AI for smart homes and describe the most popular approaches already present in literary works. The open Issues (e.g., security and privacy, data collection and sharing, data analytics, and latency) meeting the development of smart homes are also discussed in this work. Finally, the paper suggests some directions for future study that could be fruitful.

groups

Waleed Abd Elkhalik mail

link https://doi.org/10.54216/JISIoT.080205

Volume & Issue

Vol. Volume 8 / Iss. Issue 2

Details open_in_new

International Journal of BIM and Engineering Science | 2023

Proposing a Framework for Introducing the Concept of Engineering Digitization to Develop Curricula: Case Study - Tishreen University, Faculty of Civil Engineering

The emergence of Building Information Modeling (BIM) technology has made a major development in the fields of engineering and construction and has provided a means for documentation and design management throughout the building's life cycle. Despite this, the construction sector suffers from a clear shortage of specialists equipped with work skills, and therefore there is a gap and lack of skills. In order to meet the future needs for the skills of using (BIM) technology in the labor market, it was necessary to take serious steps to introduce BIM in education programs in Syrian universities to prepare future specialists, so this study aimed to identify the current reality of teaching Building Information Modeling (BIM) and to identify obstacles and challenges that prevent the application of (BIM) and propose a framework for introducing the concept of engineering digitization to develop curricula at Tishreen University, Faculty of Civil Engineering. The study used the descriptive survey method, and to collect data, two questionnaires were developed, which were applied to a sample of (32) faculty members from all disciplines of the Faculty of Civil Engineering. The study also used the statistical package for social sciences (SPSS) program to analyze the results of the questionnaire. The study showed a positive awareness of the culture of building information modeling among the various disciplines of civil engineering, despite the presence of many challenges and obstacles facing the implementation of BIM, and the study provided a general framework for the integration of building information modeling (BIM) technology with curricula The most important recommendations indicate the need to enhance awareness of the BIM culture and its applications by offering specialized training courses for academics in the use of modern technological tools based on BIM as an effective educational tool that can be integrated into the teaching curricula.

groups

Fotoun Ahmaad Dalloul mail -

Lama Adel Saoud mail

link https://doi.org/10.54216/IJBES.060103

Volume & Issue

Vol. Volume 6 / Iss. Issue 1

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2023

Survey of Artificial Intelligence of Things for Smart Buildings: A closer outlook

Artificial Intelligence of Things (AIoT) is a term used to describe the integration of Artificial Intelligence (AI) and Internet of Things (IoT) technologies. AIoT combines the capabilities of AI algorithms with the data generated by IoT devices to enable real-time decision-making and automation of various processes. Smart buildings refers to a type of building that utilizes advanced technologies to improve its efficiency, performance, and functionality of indoor tasks in a way that provide a safe and comfortable environment for occupants. This paper provides an overview of the research literature on AIoT technologies that is contribute to the development of smart buildings and their functionality. We discuss the benefits of AIoT empowered smart buildings, which include reduced energy consumption and costs, improved occupant comfort and productivity, and increased safety and security. we also discusses the challenges associated with the deployment of AIoT in smart buildings, including data privacy and security concerns, interoperability issues, and the need for specialized expertise. Further,  we discuss the promising areas of future research that pave the way for further research on AIoT empowered smart buildings. We concludes our work with a discussion of the potential for AIoT empowered smart buildings to contribute to the sustainability of cities and improve the quality of life for their occupants.

groups

Ahmed Sleem mail -

Ibrahim Elhenawy mail

link https://doi.org/10.54216/JISIoT.080206

Volume & Issue

Vol. Volume 8 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2023

Securing Wireless Sensor Networks Against DoS attacks in Industrial 4.0

Wireless Sensor Networks (WSNs) play a vital role in Industrial 4.0 by facilitating significant data collection for monitoring and control purposes. However, their distributed and resource-constrained nature makes WSNs vulnerable to Denial-of-Service (DoS) attacks, which can impede their normal operation and jeopardize their functionality. To address this issue, we propose a new machine learning (ML) approach that enhances the security of WSNs against DoS attacks in Industrial 4.0. Our approach incorporates a spatial learning unit, which captures the positional information in WSN traffic flows, and a temporal learning unit which captures time interdependency features within periods of traffic flows. To evaluate the proposed approach, we tested it on a publicly available dataset. The results demonstrate that it achieves a high detection rate while maintaining a low false alarm rate. Moreover, our Intrusion Detection System (IDS) exhibits good scalability and robustness against various DoS attacks. Our approach provides a reliable and effective solution to secure WSNs in Industrial 4.0 against DoS attacks and can be further developed and tested in various real-world scenarios.

groups

Ossama H. Embarak mail -

Raed Abu Zitar mail

link https://doi.org/10.54216/JISIoT.080106

Volume & Issue

Vol. Volume 8 / Iss. Issue 1

Details open_in_new

International Journal of Neutrosophic Science | 2023