Intelligent Video Moving Target Detection Based on Multi-Attribute Single Value Medium Neutrosophic Method

Gopal; Manju; Amena

doi:https://doi.org/10.54216/JISIoT.050105

Journal of Sustainable Development and Green Technology | 2023

Contribution Title Analysis and evolution of mortality and morbity: a review of articles published during 2016–2021

Morbidity and mortality are two frequent epidemiological monitoring measures. These parameters indicate how a health issue develops and how severe it becomes. They're important for learning about illness risk factors and comparing health events and populations. From 2016 to 2021, 241 bibliographic records were extracted from the Scopus database and evaluated through author, journal, country, and keyword analyses. The United States, United Kingdom, Australia, France, and Canada made the most substantial contributions to the domain. Moreover, the findings revealed that during the study period, the publication of papers relating to mortality and morbity increased, and the United States produced the largest proportion of publications and authors (22 percent of total). The researchers are interested in strongly highly loaded citation. This work also examines the most used input keywords. Accordingly, the major findings of this study will be useful for politicians, researchers, and institutions to determine future research directions and identify potential consultants to assist formulating their mortality and morbity control policies and future mortality reduction objectives

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Khakimova Feruza Ikramjon Kizi mail -

Allayarov Piratdin mail

link https://doi.org/10.54216/JSDGT.010202

Volume & Issue

Vol. Volume 1 / Iss. Issue 2

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Galoitica: Journal of Mathematical Structures and Applications | 2023

On Some Properties of Fuzzy Spectrums of Implicative BCI Algebras

An implicative BCI algebra is a non empty set X with a special element O and a binary operation * with many clear conditions.In this work, we study the topological space  and present some properties especially the compactness and connection. Also, we prove that it is a Hausdorff space and regular.

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Abd Alrida Basheer mail

link https://doi.org/10.54216/GJMSA.030203

Volume & Issue

Vol. Volume 3 / Iss. Issue 2

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Galoitica: Journal of Mathematical Structures and Applications | 2023

Improving Karmarker Algorithm to Obtain Optimal Solution

In this research, the Karmarker's method of linear programming was improved using the eigenvector of the starting point with all iterations.Where the improvement showed that Karmarker's method can be reduced in a theoretical way by direct method without iterations and access to the optimal solution. The procedure was also Comparison of the two methods and the results of the proposed method were faster and better to reach.

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Ahmad Khaldi mail

link https://doi.org/10.54216/GJMSA.030204

Volume & Issue

Vol. Volume 3 / Iss. Issue 2

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Journal of Intelligent Systems and Internet of Things | 2023

Intelligent Edge Computing for IoT: Enhancing Security and Privacy

Edge computing is a distributed computing paradigm that involves processing data at or near the edge of the internet of things (IoT) network, instead of centralized server. This makes the cyber-attacks increasingly sophisticated, and traditional security measures become no longer sufficient to protect against them. Concurrently, privacy concerns arise when sensitive data is involved in Edge computing applications containing confidential information. In this paper, we propose a privacy-preserved federated learning (FL) approach for cyber-attack detection in edge based IoT ecosystem. A novel lightweight convolutional Transformer network (LCT) network is designed to precisely identify cyber-attacks though learning attack patterns from IoT traffics in local edge devices, where model is personalized though fine-tuning. The privacy of model and data is preserved in our system via incorporating differential privacy and secure aggregation during the cooperative training process on edge devices. We evaluate our proposed approach on a real-world dataset of network traffic (NSL-KDD) containing various types of attacks, and the experimental results show that our personalized FL approach outperforms traditional FL in terms of detection accuracy. We also show that our approach is effective in handling non-stationary data and adapting to changes in the network environment.

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Lobna Osman mail -

Olutosin Taiwo mail -

Ahmed Elashry mail -

Absalom E. Ezugwu mail

link https://doi.org/10.54216/JISIoT.080105

Volume & Issue

Vol. Volume 8 / Iss. Issue 1

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Neutrosophic and Information Fusion | 2023

Neutrosophic MCDM Methodology to Select Best Industrial Arc Welding Robot

Industrial robots have made it possible for industrial companies to make goods of a good quality at lower costs. As a result, industrial robots are an integral component of sophisticated manufacturing systems. Industrial robots may be programmed to do a wide variety of tasks, including welding, painting, construction, and debugging. All of the elements are completed with an exceptional level of endurance, swiftness, and accuracy. The efficiency of industrial robots is governed by a number of different factors, some of which are in direct opposition to one another; for a strong choice approach, all of these criteria must be examined concurrently. For the purpose of selecting an industrial robot for the arc soldering process, a straightforward multi-criteria decision-making (MCDM) approach that is VIKOR method will be described in this research. The VIKOR method used to rank the robots. The results of the VIKOR methodology are provided here in the form of a priority of rating. The findings demonstrated that the MCDM strategies are highly helpful when selecting robots to utilize.

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Mahmoud Ismail mail -

Shereen Zaki mail

link https://doi.org/10.54216/NIF.010101

Volume & Issue

Vol. Volume 1 / Iss. Issue 1

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Neutrosophic and Information Fusion | 2023

Ranking Renewable Energy Alternatives by using Triangular Neutrosophic Sets Integrated with MCDM

In this age of ecological sustainability, energy planning has grown more complicated as a result of the inclusion of numerous standards, including technological, political, financial, and environmental considerations. As a result, this places significant limitations on the ability of policymakers to independently and covertly optimize energy sources, which is particularly problematic for rural populations. In contrast, the constraints imposed by the topography of the land on renewable energy (REEN) systems, which are for the most part dispersed across the natural environment, make energy planning more difficult. In these kinds of situations, decision analysis plays a crucial part in the process of creating these kinds of systems by taking into account a wide range of requirements and goals, even at fragmented levels of digitization. Many criterion decision making, often known as MCDM, is a subfield of operational research that focuses on finding optimum outcomes in complicated situations that include various measures, competing goals, and multiple criteria. Because it enables decision-makers to make choices while simultaneously taking into account all of the standards and goals, this tool is gaining traction in the area of energy planning, which is one of the reasons why it is becoming more famous. In this paper, the TOPSIS MCDM methodology is integrated with the triangular neutrosophic sets to rank and select best source of REEN in Egypt. The neutrosophic sets used due to incomplete and uncertainty in this ranking.

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Ahmed M. Ali mail

link https://doi.org/10.54216/NIF.010102

Volume & Issue

Vol. Volume 1 / Iss. Issue 1

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Neutrosophic and Information Fusion | 2023

Sustainable Supplier Selection using Neutrosophic Sets and MCDM Framework

Because of stricter rules from the government and growing awareness among the general public, sustainable supply chain management (SSCM) performs a significant role in the management of firm manufacturing operations. Companies that want to promote sustainable supply chain management (SSCM) must first choose the most suitable sustainable supplier, which is a MCDM dilemma, as highlighted in a number of research studies. In addition, because of their limited expertise, those who make decisions have a propensity to convey their opinions via the use of language phrases. The purpose of this work is to report on a unique MCDM model for the choice of sustainable suppliers. This approach integrates the MCDM MABAC method inside an uncertain language situation. With the assistance of uncertain linguistic sets, the neutrosophic sets used to overcome these uncertainty. When it comes to generating the ranking of possible suppliers, the MABAC is dependable and easy to understand. In conclusion, an iron maker is used as an example to illustrate the practicability and efficacy of the suggested strategy for the selection of sustainable suppliers.

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Abduallah Gamal mail -

Nehal Nabil Mostafa mail

link https://doi.org/10.54216/NIF.010103

Volume & Issue

Vol. Volume 1 / Iss. Issue 1

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Neutrosophic and Information Fusion | 2023

An Interval Valued Neutrosophic Sets Integrated with the AHP MCDM Methodology to Assess the Station of 5G Network

In latest days, 5G technology has undergone fast development and has since found widespread use in a variety of industries including medicine, travel, agriculture, and others. The 5G network's fundamental equipment, known as 5G ground stations, are responsible for achieving wireless signal transfer among wired communications systems and wireless endpoints. Additionally, 5G stations give communication range. Nevertheless, as the size of 5G ground stations continues to progressively develop, difficulties such as inadequate coverage area and subpar user experiences commonly arise. As a result, it is essential to conduct an all-encompassing performance evaluation of 5G ground stations in order to better understand the challenges that now exist in the development of ground stations. To begin, the components of the performance assessment index system, which include operating efficiency, economic condition, ecological effects, and social pressure, are assembled from their respective vantage points. In the next step, a unique hybrid multi-criteria decision-making (MCDM) approach that is built on the AHP methodology is used. In conclusion, ten 5G base stations are selected as samples for further investigation. The AHP is integrated with the Interval Valued Neutrosophic Sets (IVNSs). The IVNSs used to overcome incomplete and vague information.  The AHP method used to compute the weights of criteria.

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Ahmed Sleem mail -

Ibrahim Elhenawy mail

link https://doi.org/10.54216/NIF.010104

Volume & Issue

Vol. Volume 1 / Iss. Issue 1

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Journal of Intelligent Systems and Internet of Things | 2023

Intelligent Traffic Management using IoT and Machine Learning

The continuous improvements in the Internet of Things (IoTs) and machine learning (ML) make them the key enabling technologies for intelligent traffic management (ITM).The ability to accurately predict network traffic has been demonstrated as crucial for effective network management and strategic planning. Proactive management of future congestion incidents requires access to reliable long-term forecasting models. Conventional prediction methods often fail to completely capture the spatiotemporal features of the traffic flows because of the complexity of the interdependence between the flows. To this end, we proposed to improve the management of traffic with a novel framework for the predictive modeling of traffic flows. The proposed formwork introduces an improved graph network to capture the positional information in traffic follows. It is also capable of precisely capturing temporal dynamics using an improved bidirectional learning module. An attention mechanism is presented to capture the interactions among spatial and temporal patterns to further empower the predictive power of the model. Proof-of-concept experimentations are conducted on the PeMSD7 dataset, and the results (MAE: 0.197, MSE: 0.13, RMSE: 0.36, ) demonstrate the efficiency of our model over the state-of-the-art.

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Reem Atassi mail -

Aditi Sharma mail

link https://doi.org/10.54216/JISIoT.080201

Volume & Issue

Vol. Volume 8 / Iss. Issue 2

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Journal of Intelligent Systems and Internet of Things | 2021

Intelligent Video Moving Target Detection Based on Multi-Attribute Single Value Medium Neutrosophic Method

Competition in social sports has many benefits for athlete training due to this competition gives researchers a chance to making and developing new methods and ways that support them. The competition in sport growth rapidly these days. During the last several years, there has been a significant increase in the volume of traffic using multimedia. In addition, some of the most recent paradigm shifts suggested, such as IoT, bring about the introduction of new kinds of traffic and applications. Software-defined networks, often known as SDNs, are beneficial to network management since they enhance its capabilities. When used with SDN, artificial intelligence (AI) has the potential to solve network issues using categorization and estimate strategies. So, in this paper discuss and develop a new method for sports video moving target detection. This method is based on multi-criteria decision making (MCDM) because targeting detection has many criteria and sub-criteria. This paper collected five main criteria and twenty sub-criteria impacts in target detection of sports video. We use the Analytical hierarchy Process (AHP) to determine the importance of these criteria and their weights. These criteria were evaluated under a neutrosophic environment. An application is provided to measure the outcome of the proposed method.

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Gopal Chaudhary mail -

Manju Khari mail -

Amena Mahmoud mail

link https://doi.org/10.54216/JISIoT.050105

Volume & Issue

Vol. Volume 5 / Iss. Issue 1

Details open_in_new