The Importance of Patents in the Development of Industrial Production in the Region

Khabibullo Abdullaev

doi:https://doi.org/10.54216/JSDGT.040208

International Journal of Neutrosophic Science | 2024

Foundations of neutrosophic convex structures

In this paper an idea of neutrosophic convex structures (briefly, NC-structures) is given and some of their properties are explored. Also, NC-sets, neutrosophic concave sets and neutrosophic convex hull are defined and their properties are investigated. Moreover, the notions of NC-derived operator and NC-base are studied and their relationship to NC-structures are established.

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Jos´e Sanabria mail -

Ennis Rosas mail -

Elvis Aponte mail

link https://doi.org/10.54216/IJNS.240214

Volume & Issue

Vol. Volume 24 / Iss. Issue 2

Details open_in_new

International Journal of Neutrosophic Science | 2024

Abelian subgroups based on neutrosophic sets

The notion of a neutrosophic Abelian subgroup of a group is introduced. The characterizations of a neutrosophic Abelian subgroup are investigated. We show that the homomorphic preimage of a neutrosophic Abelian subgroup of a group is a neutrosophic Abelian subgroup, and the onto homomorphic image of a neutrosophic Abelian subgroup of a group is a neutrosophic Abelian subgroup.

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Aiyared Iampan mail -

C. Sivakumar mail -

P. Maragatha Meenakshi mail -

N. Rajesh mail

link https://doi.org/10.54216/IJNS.240215

Volume & Issue

Vol. Volume 24 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2024

Evaluating the Potential of Mesh Networks in Enhancing Rural Connectivity based on Internet of Thing

Rural communities struggle to connect to the internet, a phenomenon known as the "digital divide." Mesh networks, with improved access in rural regions, might help to tackle this problem. From a social, economic, and scientific standpoint, this study investigated whether mesh networks may improve rural connectivity. This project developed and implemented methodologies to assess community participation, cost, and network coverage. Five well-known methods were pitted against these ones. Locals are working on a mesh node placement project in a rural location with diverse topography. In terms of network coverage, the Network Coverage Assessment revealed that the proposed approach frequently outperformed the most recent approaches. Finding the ideal locations for mesh nodes helped to tackle challenges in rural regions. After putting the strategy into effect, the Cost-Effectiveness Analysis revealed a positive ROI. Many alternative options seemed unprofitable. On the Community Engagement Index, the recommended method performed better than others. Participating in network activities with individuals from the local community helps to foster ownership and shared accountability.

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Neelima Gurrapu mail -

Akhil Nair R. mail -

C. Laxmikanth Reddy mail -

V. V. J. Rama Krishnaiah mail -

S. Shiek Aalam mail -

Kancharla Suresh mail

link https://doi.org/10.54216/JISIoT.120213

Volume & Issue

Vol. Volume 12 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2024

Investigating the Impact of Compressed Sensing Techniques and IoT in Medical Imaging

 This research paper examines compressed sensing's impact on medical imaging. Math and signal processing inspired compressed sensing. Future picture-capturing will be radically different. The paper focuses on adaptive random sampling (ARS), iterative shrinkage-thresholding algorithms (ISTA), and temporal compressed sensing (TCS). These approaches were rigorously tested using MRIs, X-rays, and dynamic imaging patterns. Low scan times, picture quality, and dynamic imaging were the main test criteria. The technologies considerably reduced scan time, demonstrating their potential to speed up imaging procedures. The reconstructed photos had higher SNRs and SSIs than those obtained using normal techniques, indicating greater accuracy. The TCS algorithm's dynamic imaging skills, especially evident in heart and musculoskeletal imaging, eliminated motion defects while exhibiting real-time physiological changes. The study was expanded to incorporate customized treatment, and the recommended procedures have proven amazing adaptability to each patient's demands. This adaptability fits current medical treatments, making unique imaging technologies viable.

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Suresh Kumar Mandala1 mail -

Shahnaz K. V. mail -

Chopparapu Gowthami mail -

S. Shiek Aalam mail -

B. Laxmi Kantha mail -

K. Chandran mail

link https://doi.org/10.54216/JISIoT.120214

Volume & Issue

Vol. Volume 12 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2024

Strategizing IoT Network Layer Security Through Advanced Intrusion Detection Systems and AI-Driven Threat Analysis

This research introduces an algorithmic framework for enhancing the security of Internet of Things (IoT) networks. The Enhanced Anomaly Detection (EAD) algorithm initiates the process by detecting anomalies in real-time IoT data, serving as the foundational layer. The Behavior Analysis for Profiling (BAP) algorithm builds upon EAD, adding behavior analysis for profiling and adaptive identification of abnormal behavior. Signature-Based Detection (SBD) involves pre-identified attack signatures, which supports detection of known attacks and provides proactive defense measures against documented threats. The MLID, or the Machine Learning-Based Intrusion Detection, algorithm uses trained machine learning models in order to detect anomalies and the adaptability to changing security risks. The Real-Time Threat Intelligence Integration (RTI) algorithm integrates updated threat intelligence feeds, which improves the framework's responsiveness to emerging threats. The visual representations illustrate once again the idea of the new framework being very accurate at intergration, applicability, and overal security effectiveness. The research makes a standard solution which proves to be a smart and responsive way guarding the IoT networks reducing and even fighting known and potential threats in a real-time mode.

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Deepak Dasaratha Rao mail -

Akhilesh A. Waoo mail -

Murlidhar Prasad Singh mail -

Piyush Kumar Pareek mail -

Shoaib Kamal mail -

Shraddha V. Pandit mail

link https://doi.org/10.54216/JISIoT.120215

Volume & Issue

Vol. Volume 12 / Iss. Issue 2

Details open_in_new

International Journal of Neutrosophic Science | 2024

Arithmetic Operations on Generalized Pentagonal Fuzzy Numbers

Fuzzy concepts have been widely used to treat imprecision in many fields of natural and social sciences. In most of the natural science fields such as applied mathematics, physics, chemistry, and engineering, triangular and trapezoidal fuzzy numbers are commonly used and arithmetic operations on those numbers are studied in detail. On the other hand, in engineering and social science fields such as sociology and psychology, while treating the uncertainties, these numbers are not applicable and fuzzy numbers with more parameters and clear definitions of their arithmetic operations are needed. In order to fill this gap in the literature, in this study we propose the generalized pentagonal fuzzy numbers, and we define fuzzy arithmetic operations based on both extension and the function principle.

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Aslı Guldurdek mail -

G. Yazgı Tutuncu mail

link https://doi.org/10.54216/IJNS.240216

Volume & Issue

Vol. Volume 24 / Iss. Issue 2

Details open_in_new

Fusion: Practice and Applications | 2024

Integrating Improved Mobile Net and Homomorphic Encryption in Hybrid IoT Security Frameworks for Enhanced Resilience Against Advanced Persistent Threats

IoT devices have transformed smart cities and healthcare. The expanding usage of IoT devices creates major security threats, leaving critical systems vulnerable to sophisticated and persistent assaults. Our hybrid IoT security approach employs homomorphic encryption and improved MobileNet to protect data and simplify feature extraction. Our extensive testing and assessment prove that the proposed structure makes IoT settings more resistant to sophisticated persistent attacks. We discovered superior methodologies for F1 score, accuracy, precision, and memory performance measurement. To ensure data privacy and security during analysis and transmission, homomorphic encryption is incorporated. Our ablation research lays out each framework component's contributions. To increase system speed, it emphasizes safe data processing, real-time analytical optimization, lightweight feature extraction, and privacy-preserving computing. The scalability study indicates that the framework can scale with IoT installations while maintaining peak performance and resource efficiency. Finally, the hybrid IoT security architecture improves IoT security. It provides a full and effective security solution for IoT infrastructure. Lawmakers, business experts, and students in the sector may learn from this research regarding genuine IoT security systems.

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Abhishek Kumar mail -

Samta Jain Goyal mail -

Sumit Kumar mail -

Hitesh Kumar Sharma mail

link https://doi.org/10.54216/FPA.160107

Volume & Issue

Vol. Volume 16 / Iss. Issue 1

Details open_in_new

Fusion: Practice and Applications | 2024

Optimizing Message Response Time in IoT Security Using DenseNet and Fusion Techniques for Enhanced Real-Time Threat Detection

As IoT devices increase, accuracy and data security become increasingly crucial. This research recommends a powerful threat detection system that accelerates message responses to improve IoT security. The recommended strategy finds dangers in using many data sources. Our deep learning system is DenseNet. It groups photographs nicely. We show how the approach works using real-world experiments. It has few false positives and negatives and is effective at recognizing items. Through ablation research, we examine how design and component selections impact technique performance. This clarifies the method's fundamentals. The research reveals that feature selection, fusion, and DenseNet design improve the technique. We discuss the need for fine-tuning hyperparameters to improve approaches and monitor more individuals. The strategy makes IoT communities safer and more robust by laying the groundwork for threat detection and response. This approach solves message transmission delay concerns, making the IoT safer. These discoveries may benefit hacking specialists. They improve and speed up IoT security. 

groups

Hitesh Kumar Sharma mail -

Samta Jain Goyal mail -

Sumit Kumar mail -

Abhishek Kumar mail

link https://doi.org/10.54216/FPA.160108

Volume & Issue

Vol. Volume 16 / Iss. Issue 1

Details open_in_new

Fusion: Practice and Applications | 2024

Facial Recognition for Criminal Identification using Convolutional Neural Network

The process of identifying and recognising the criminal is the time consuming and difficult task. There are several ways to identify culprits at the crime site, including fingerprinting, DNA matching, and eyewitness testimony. The criminal face identification system will be built on a existing criminal database. The method for identifying a human face using features extrapolated from an image is presented in this study. The technique for identifying a human face using characteristics extrapolated from a picture is presented in this research. It is quite difficult to develop a computer model for recognizing the human face since it is a complicated multidimensional visual representation. The video captured by the camera will be translated into frames as part of the suggested process. To increase detection accuracy, this suggested a Binary Gradient Alignment (BGA) algorithm a description texture classification technique. When a facial feature is detected in an image frame, it undergoes pre-processing to eliminate unnecessary data and reduce unwanted distortions. The real- time processed image is compared to the trained images that have previously been saved in the database. The technology will send an automatic email notice to the police officials if the surveillance camera detects a criminal.

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V. Sathya Preiya mail -

R. Vijay mail -

A. Hemlathadhevi mail -

C. Bharathi Sri mail

link https://doi.org/10.54216/FPA.160109

Volume & Issue

Vol. Volume 16 / Iss. Issue 1

Details open_in_new

Journal of Sustainable Development and Green Technology | 2024

The Importance of Patents in the Development of Industrial Production in the Region

In this article, patents play an important role in the development of industrial production in the region. As legal documents protecting intellectual property, patents serve as a catalyst for innovation, investment, and economic growth. By analyzing historical and contemporary examples, this study discusses how patents stimulate research and development, encourage technological progress, and increase competitiveness in regional industries. In addition, the article examines the effect of patents on the volume of production of industrial products per capita. By examining the relationship between patents and industrial production, this study highlights the importance of robust patent systems in shaping the trajectory of regional economic development.

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Khabibullo Abdullaev mail

link https://doi.org/10.54216/JSDGT.040208

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

Details open_in_new