An optimized Identification System by using Shark Smell algorithm for Biometric Images Crossing

N. A. Majeed; K. Hameed; A. Abdulhadi

doi:https://doi.org/10.54216/JISIoT.100102

International Journal of Neutrosophic Science | 2023

Pre-separation Axioms in Neutrosophic Topological Spaces

In this article, we first establish a few relationships among neutrosophic interior, neutrosophic closure, neutrosophic pre-open sets, and neutrosophic pre-closed sets in single-valued neutrosophic topological spaces. Thereafter, we defined neutrosophic pre-  space, neutrosophic pre-  space, and neutrosophic pre-  space based on single-valued neutrosophic topological spaces and studied a few properties and relationships among them. We try to establish some relationships between existing neutrosophic separation axioms and newly defined neutrosophic pre-separation axioms. Finally, we study some hereditary properties of pre-separation axioms. Apart from these, we also explore some results implementing neutrosophic pre-open function, neutrosophic pre-continuous function, neutrosophic pre-irresolute function and neutrosophic pre -function based on our defined definitions.  

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Sudeep Dey mail -

Gautam Chandra Ray mail

link https://doi.org/10.54216/IJNS.220202

Volume & Issue

Vol. Volume 22 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

Bipolar Triangular Neutrosophic Chromatic Numbers with the Application of traffic light system

For addressing issues in several domains, such as theoretical computer science, engineering, physics, combinatorics, and the medical sciences, graph theory is a crucial component of mathematics. Graph coloring is one of the new settings that is emerging in a neutrosophic chromatic number environment. In addition to introducing the idea of bipolar triangular neutrosophic chromatic graphs (BTNCG), this work also examines and demonstrates the algebraic assumption. The proposed concept has been applied in a traffic signal system to discover a new lane to avoid traffic in peak hours.

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S. Sudha mail -

B. Shoba mail -

A. Rajkumar mail -

broumi said mail

link https://doi.org/10.54216/IJNS.220205

Volume & Issue

Vol. Volume 22 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

Neutrosophic Near Algebra Over Neutrosophic Field

This piece of paper aims to learn neutrosophic near algebra and neutrosophic sub near algebra. This paper is summarized with the suitable definitions and theorems of neutrosophic near algebra and neutrosophic sub near algebra. It has also been demonstrated that the direct product of neutrosophic near algebra is a neutrosophic near algebra and the intersection of neutrosophic sub near algebra is a neutrosophic near algebra on a neutrosophic field. It also examined the union of couple of neutrosophic near algebras is a neutrosophic near algebra.

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Bhurgula Harika mail -

K. Rajani mail -

P. Narasimha Swamy mail -

T. Nagaiah mail -

L. Bhaskar mail

link https://doi.org/10.54216/IJNS.220203

Volume & Issue

Vol. Volume 22 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

An Approach To Symbolic n-Plithogenic Square Real Matrices For 9≤ n ≤12

The concept of symbolic n-plithogenic algebraic matrices as symmetric structures with n+1 symmetric classical components with the special definition of the multiplication operation. This paper is dedicated to studying the properties of symbolic 10, and 9-plithogenic real square matrices and 11, 12-plithogenic real matrices from algebraic point of view, where algorithms for computing the eigenvalues and determinants will be proved. Also, the inverse of a symbolic n-plithogenic matrix for the special values n=10, n=9, n=11, and n=12 will be presented.

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Abuobida M. A. Alfahal mail -

Barbara Charchekhandra mail -

Raja Abdullah Abdulfatah mail -

Yaser Ahmad Alhasan mail -

Husain Alhayek mail

link https://doi.org/10.54216/IJNS.220204

Volume & Issue

Vol. Volume 22 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2023

Study on Student’s Performance using Single Valued Decagonal Neutrosophic Number in Decision Making Problem

This article presents a new single valued decagonal Neutrosophic number. The single valued decagonal Neutrosophic number is Deneutrosophicated with the help of bounded area method. The bounded area formula is derived. The single valued decagonal Neutrosophic number is used in the decision-making problem. The performance of students is analyzed using a ranking method. The attributes are taken from the problems related to students and teachers. The attributes are ranked through the single valued decagonal Neutrosophic number.

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S. Gomathy mail -

B. Shoba mail -

A. Rajkumar mail -

broumi said mail

link https://doi.org/10.54216/IJNS.220206

Volume & Issue

Vol. Volume 22 / Iss. Issue 2

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Journal of Artificial Intelligence and Metaheuristics | 2023

A Novel Long Short-Term Memory (LSTM) Deep Learning IoT Method for Lung Cancer Prediction and Detection

Lung cancer is the primary cause of cancer-related mortality in this generation, and it is expected to stay in foreseeable future. When the early indications of lung cancer are identified, a successful treatment can be initiated. A prototype environment friendly approach for treating lung cancer might be developed using the most recent developments in computational intelligence. Time and money will be saved since fewer resources will be wasted and manual tasks will take less effort to complete. An LSTM (Long Short-Term Memory)-based learning model was used to predict the lung cancer and improve the dataset procedure. With applications across medical image-based and textural data modalities, deep learning is one of the areas of medical imaging that is growing the fastest. Physicians may more easily and reliably identify and classify lung nodules with help of Deep Learning (DL)-based medical imaging technologies. This system covers the most recent advancements in deep learning-based imaging approaches for the early identification of lung cancer. The LSTM classifier sensitivity, specificity, and accuracy of our suggested system are best achieved by the Python software, with values of 80%, 85%, and 95%, respectively. Additionally, IoT (internet of things) to monitoring the lung cancer through cloud system through Adafruit Io. The lung cancer level is updating to NodeMCU controller.

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R. Ramani mail -

Padmaja Nimmagadda mail -

Shruti Bhargava choubey mail -

S. Rajasekar mail -

Omega John Unogwu mail -

Abdel-Hameed Al-Mistarehi mail -

Mostafa Abotaleb mail

link https://doi.org/10.54216/JAIM.050201

Volume & Issue

Vol. Volume 5 / Iss. Issue 2

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Journal of Artificial Intelligence and Metaheuristics | 2023

Deep Learning Algorithms for Smart Cars: A Survey

The rate of progress in autonomous car technology has increased exponentially over the past decade, mostly thanks to advancements in deep learning and artificial intelligence. This work aims to summarize recent progress made in the application of deep learning techniques to the problem of autonomous driving. First, we will go through the deep reinforcement learning paradigm and other AI-based solutions for autonomous driving, such as convolutional and recurrent neural networks. Algorithms for driving scene recognition, path planning, behavior arbitration, and motion control were developed with these techniques in mind. Both the End2End system, which immediately converts sensory input into steering commands, and the modular perception-planning-action pipeline, each module of which is built using deep learning techniques, are the focus of our studies. We also discuss the modern challenges of building AI systems for autonomous driving, such as making sure they are safe to use, finding good places to practice, and creating effective computing hardware. This survey's comparison sheds light on the pros and cons of AI and deep learning approaches to autonomous driving, which aids in making design decisions.

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Mostafa Abotaleb mail -

Ehsaneh khodadadi mail -

Nadjem Bailek mail

link https://doi.org/10.54216/JAIM.050202

Volume & Issue

Vol. Volume 5 / Iss. Issue 2

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Journal of Artificial Intelligence and Metaheuristics | 2023

Electrocardiogram Comparison as a Biometric Identifier: A Review

The electrocardiogram (ECG) is a type of biometric data that has recently attracted a lot of attention as a potentially useful biometric trait due to its high discriminatory power. However, precise and consistent biometric identification systems are challenging to deploy because to ECG signals' vulnerability to a wide range of sounds, including baseline wander, powerline interference, and high/low frequency noises. That's why ECG signal denoising is such an important aspect of the preprocessing phase for ECG-based biometric person identification: it removes noise from the raw ECG data. Biometric recognition using ECG signals is a difficult problem involving phases of preprocessing, feature extraction, feature selection, feature modification, and classification. Biometric system analysis also relies heavily on the use of appropriate success measures and a well-organized library of ECG signals. This is especially crucial when considering the fact that researchers rely significantly on freely accessible resources to gauge the efficacy of the algorithms they propose. In this study, we examine most of the approaches that have been taken toward ECG-based biometric verification of humans.

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Ammar Kadi mail -

Adel Oubelaid mail -

S. K. Towfek mail

link https://doi.org/10.54216/JAIM.050203

Volume & Issue

Vol. Volume 5 / Iss. Issue 2

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Journal of Intelligent Systems and Internet of Things | 2023

Catalyzing Future Education: Dynamic Learning and Remote Experiments through IoT-Integrated Learning Management Systems and Virtual Reality

As tools for developing, distributing, tracking, and managing a variety of training and educational materials online, Learning Management Systems (LMS) have become increasingly popular as tools for developing, distributing, tracking, and managing a variety of types of training and educational materials online. The evolution of Learning Management Systems (LMSs) has been dramatic since they were introduced in the 1990s. They have emerged as powerful applications for managing curricula, providing rich content courseware, assessing and evaluating student performance, and facilitating dynamic collaboration between educators and students. We can expect many changes in the structure, the functionalities, and the implementation of the learning management system in the near future as a result of a number of research fields exploring various technologies related to the learning management system. Our daily lives will be impacted by a wide variety of aspects as a result of the Internet of Things (IoT), as we move forward. There are several components to a learning management system that can be enhanced with the use of IoT capabilities that are discussed throughout this paper. In addition to its impact on many aspects of the learning management system, the Internet of Things will also bring to the learning management system a number of enhancements and changes that are expected to enhance the functionality of the system. An IoT-enhanced learning management system is one of the outcomes of a three-year research project that Arts, Science, and Technology University (AUL) is conducting as part of its Distance Learning program. It is intended to provide a brief overview of the project and the implementation plan for each component along with a description of the anticipated effects and the benefits that are anticipated to be derived from it. Locating objects in images and videos is one of the most fundamental and challenging tasks. Object classification, counting of objects, and object monitoring have received much attention in recent years. An in-depth literature review focusing on object detection is presented here.  

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Issa kamar mail -

Hadi Fares mail

link https://doi.org/10.54216/JISIoT.100101

Volume & Issue

Vol. Volume 10 / Iss. Issue 1

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Journal of Intelligent Systems and Internet of Things | 2023

An optimized Identification System by using Shark Smell algorithm for Biometric Images Crossing

The security and privacy fields and multimedia biometrics have been widely used today for personal authentication. Sclera and Palm-print of humans are one of the fastest, accurate, reliable, and secure biometric techniques for identification and verification based on unique features. The majority of the biometric systems are based on the global features, which may lead to weak performance in cases of poor-quality biometric images, therefore, swarm intelligence techniques are used to improve recognition accuracy, reliability, and quickness. In this paper, an enhancement shark smell optimization (ESSO) is proposed to build an efficient hybrid identification system depend on the sclera and palm-print images. The SIFT algorithm used to extract features from the biometric images. The optimal key-points from this feature are obtained using ESSO and chaotic map, and finally, generation digital signature using a 256-MD5 algorithm for each user. The Package of the NIST tests proves that the generated keys are random, unpredictable, uncorrelated, and robust against different kinds of attacks.  

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N. A. Majeed alhammadi mail -

K. Hameed Zaboon mail -

A. Abdulhadi Abdullah mail

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

Volume & Issue

Vol. Volume 10 / Iss. Issue 1

Details open_in_new