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Secrecy Capacity Optimization in RF/FSO Systems: Impact of.Mixed Rayleigh and Log-Normal Fading with Atmospheric Turbulence

Secrecy Capacity Optimization in RF/FSO Systems: Impact of M...

引用

2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India ABV Indian Institute of Information Technology and Management Data Science and Quantum Computing Gwalior India

ISBN: (纸本)9798350379525

This paper investigates the secrecy capacity optimization in RF/FSO systems with mixed Rayleigh and log-normal fading, while masking eavesdroppers channel state information () as well as suffering from atmospheric turbulence. We explore the impact of.several parameters including beamforming angles, modulation schemes and hybrid RF/FSO link configurations through a combination of.simulations as well as analytical models. Secrecy capacity is enhanced for an improved SNR and vice versa under higher turbulence conditions and cooler influents eavesdropped scenarios. Performance of.the hybrid RF/FSO systems dominates considerably over single-link solutions, especially at longer distances. All these mechanisms appreciably increase the secrecy capacity, while beamforming and advanced modulation techniques of.er most of.the improvement. The study also demonstrates the interdependencies of.system parameters, providing guidelines for designing secure communication systems under different environmental and operational conditions. © 2024 IEEE.

关键词： Beamforming

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Digital Image Encryption Based On Elliptic Curve Cryptography 4

Digital Image Encryption Based On Elliptic Curve Cryptograph...

引用

4th IEEE International Maghreb Meeting of.the Conference on sciences and Techniques of.Automatic Control and computer engineering, MI-STA 2024

作者： Hasan, Mahmoud H. S. Ahmed, Medht H. S. H. Alasmarya Islamic University College of Information Technology Dept. Computer Science Zliten Libya Higher Institute of Engineering Technology Dept. Communication Engineer Zliten Libya

ISBN: (纸本)9798350372632

information security is currently a major problem for data communication. Cryptography has emerged as a treatment and is essential to information security systems. Techniques for encryption can effectively prevent attacks on images. Elliptic curve cryptography (ECC) is an approach of.public-key encryption, depends on the algebraic grouping of.elliptic curves over finite fields. The present study introduces an intriguing elliptic curve cryptography-based image encryption approach and applied it to various images. The proposed technique was tested. We computed the number of.pixels change rate (NPCR), unified average changing intensity (UACI), and peak signal to noise ratio (PSNR) to assess the effectiveness of.the suggested technique. © 2024 IEEE.

关键词： Geometry

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Smart bracelet based on the Internet of.Things

Smart bracelet based on the Internet of Things

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Hu, ZhiJie Chang, Chih-Yung Shen, RuiBing Wu, Shih-Jung Hou, Di Xi'an Eurasia University School of Information Engineering Xi'an China Tamkang University Dept. of Computer Science and Information Engineering Taiwan Xi'an ShiYou University Dept. of Electronic Engineering China

ISBN: (纸本)9798350324174

With the development of.the economy and the improvement of.people's living standards, more and more people start to pay attention to health and exercise, and the smart bracelet is born. The designed smart bracelet in this paper can collect data such as heart rate, exercise, temperature, humidity, altitude, atmospheric pressure, and light intensity in the current environment. The collected data are processed by the STM32F103C8T6 controller. Then the processed data is displayed in the OLED display module. In addition, the corresponding data can be uploaded to the mobile phone for real-time display through the Bluetooth communication module. The test results show that the system is stable and reliable. © 2023 IEEE.

关键词： Bluetooth

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Constructing Disease Comorbidity Networks Using Statistical Methods from Electronic Health Records

Constructing Disease Comorbidity Networks Using Statistical ...

引用

2023 IEEE International Conference on Network, Multimedia and information Technology, NMITCON 2023

作者： Bramesh, S.M. Anil Kumar, K.M. P. E. S. College of Engineering Dept. of Information Science & Engineering Mandya India Jss Science and Technology University Dept. of Computer Science & Engineering Mysuru India

ISBN: (纸本)9798350300826

Disease comorbidity is a prevalent and significant concern in modern medical practice. Patients in such circumstances will need specialized medical interventions. This study proposes a network-based computation model to extract the disease comorbidity patterns by utilizing the electronic health records of.a 'Diabetes 130-US hospitals for years 1999-2008' dataset. The estimate of.disease-disease relationships using statistical methods is a crucial step in this paradigm. A Disease Comorbidity Network (DCN) was constructed based on these relationships. This model can then be used to extract the corresponding illness comorbidity patterns for various races and genders, using the endocrine disease (diabetes) as an example to determine the associations between various diseases and their comorbidities. The outcomes of.this research demonstrated that the strength of.some interesting and or clinically relevant disease associations (Example: musculoskeletal disorder and endocrine disorder, nervous disorder and endocrine disorder) is stronger in male patients than in female patients. Also, observed that the endocrine-specific comorbidity patterns will vary based on the race and gender of.a patient. Finally, extracted comorbidities patterns are validated with medical literature as well as with the state of.art method. Notably, this study exploits the network-level relationships between diseases, which will improve our perception about disease associations at the level of.the patient population. © 2023 IEEE.

关键词： Statistical methods

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Deep Learning for Channel Prediction in Non-Stationary Wireless Fading Environments

Deep Learning for Channel Prediction in Non-Stationary Wirel...

引用

2024 IEEE International Conference on Intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Electronics and Communication Engineering Dehradun India Data Science and Quantum Computing ABV Indian Institute of Information Technology and Management Gwalior India

ISBN: (纸本)9798350379525

In non-stationary wireless fading channels deep learning models are effective in predicting channel states as indicated by this study. This work compared the LSTM and GRU models with autoregressive methods or Kalman filter, implying that deep learning is indeed able to capture temporal dependence between variables and was likely more adapted than linear method when dealing with many changes in dynamics. From the perspective of.pre-processing data, keys like attention mechanism and transfer learning were decisive elements in helping them to improve prediction scores and make models more robust. These results showed that these enhanced procedures allow the models to generalise over a wide range of.non-stationary situations, generating consistent performance in various diverse environments. This study indicates the promise of.deep learning for enhancing wireless network operation, which could lead to greater self-awareness and utilization features in emerging future-generation wireless systems. © 2024 IEEE.

关键词： Prediction models

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Improving Liver Disease Diagnosis Through Generative Adversarial Network Driven Synthetic Tabular Data

Improving Liver Disease Diagnosis Through Generative Adversa...

引用

2024 IEEE Silchar Subsection Annual Conference, SILCON 2024

作者： Mahendran, S. Venkatasekhar, D. Shanmugasundaram, G. Annamalai University Department of Information Technology Chidambaram India Chennai Institute of Technology Dept. of Computer Science & Engineering Chennai India

ISBN: (数字)9798331540821

ISBN: (纸本)9798331540821

Liver ailments pose a significant worldwide health concern, with their extensive effects and severe repercussions highlighting the pressing necessity for precise diagnosis. Diagnosing hepatic disorders is frequently intricate and expensive. This work presents a Generative Adversarial Network (GAN) based methodology for producing synthetic tabular data to enhance early prediction of.liver ailments, employing a dataset of.Indian liver patients. The contribution of.the work is the introduction of.innovative architecture that integrates Stacked Ensemble Model with advanced preprocessing techniques and the use of.Generative Adversarial Networks for data augmentation not extensively explored in current data-driven machine learning approaches for liver ailments prediction. The Stacked Ensemble Model has two tiers: the base-level and the meta-level. The base-level learning component trains various base learners, including Gradient Boosting, Ride classifier, Multi-layer Perceptron, and LightGBM on the input dataset. A strong prediction model is then constructed by combining and feeding the outputs of.these several classifiers into a Random Forest classifier, which is the meta-learner. The results show that the model performs much better when synthetic data generated by GANs is included, obtaining an overall accuracy of.95%. This approach aims to greatly improve the prediction of.liver ailments, hence enabling quick intervention and more effective treatment. © 2024 IEEE.

关键词： Generative adversarial networks

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Poster: Towards Edge-Intelligent Wearable for early Drowning Detection 16

Poster: Towards Edge-Intelligent Wearable for early Drowning...

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16th International Conference on Underwater Networks and Systems, WUWNet 2022

作者： Kabir, Maliha Mummadi, Teja Sree Sundaravadivel, Prabha Dept. Of. Electrical Engineering The University of Texas at Tyler TylerTX United States Dept. Of. Computer Science The University of Texas at Tyler TylerTX United States

ISBN: (纸本)9781450399524

This research aims to develop a wearable monitoring system that can help in monitoring respiratory distress. Drowning-related accidents are 3rd leading cause of.unintentional death. Among the victims most of.them are children and world statistics state that there are 4000 fatalities per day in children due to drowning. In this research project, we propose a wearable system that can help in monitoring the heart rate, oxygen level, and body temperature variability, along with the accelerometer. Our proposed framework is designed as an anklet that can help detect drowning incidents early. © 2022 Owner/Author.

关键词： Accidents

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Literature Review on Packet Sniffing: Essential for Cybersecurity & Network Security 5

Literature Review on Packet Sniffing: Essential for Cybersec...

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5th International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2024

作者： Shaw, Ranju Parveen, Suraiya Jamia Hamdard University Dept. of Computer Science Engineering with Specialization in Cyber Forensic Information Security Delhi India Faculty at Jamia Hamdard University Sest Department of Computer Science Engineering Delhi India

ISBN: (纸本)9798350385649

In the realm of.cybersecurity and network security, the significance of.monitoring and analyzing network traffic cannot be overstated Network packet sniffing, a technique employed to capture and inspect data packets traversing a network, has emerged as an imperative tool for understanding network behavior, identifying vulnerabilities, and enhancing overall security. This study analyzes packet sniffing by exploring its role in modern cybersecurity practices. By analyzing packet sniffing mechanisms, including its methodologies and potential applications, this res earch sheds light on its effectiveness as a proactive security solution. Furthermore, the study examines the ethical considerations surrounding packet sniffing, addressing concerns related to user privacy and data protection. It also investigates the legal aspects that govern the use of.packet sniffing techniques, ensuring compliance with regulations while maximizing its benefits. Through case studies and real-world examples, this research illustrates how packet sniffing can be leveraged to detect network anomalies, thwart malicious activities, and fortify network infrastructures. By presenting a comprehensive overview of.packet sniffing's capabilities and limitations, this study equips cybersecurity practitioners with the knowledge needed to make informed decisions about its integration into their defensive strategies. © 2024 IEEE.

关键词： Cybersecurity

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Secure and Efficient Face Recognition via Supervised Federated Learning 2

Secure and Efficient Face Recognition via Supervised Federat...

引用

2nd International Conference on Artificial Intelligence, Blockchain, and Internet of.Things, AIBThings 2024

作者： Solomon, Enoch Woubie, Abraham Emiru, Eyael Solomon Abdelzaher, Ahmed F Virginia State University Department of Computer Science RichmondVA United States Silo Ai Helsinki Finland University of Trento Dept. of Information Engineering and Computer Science Italy

ISBN: (纸本)9798331529529

Facial recognition systems frequently rely on training with large image dataset acquired from several sources on a single device. These databases of.en store sensitive data, leading to significant privacy concerns. To mitigate this, we propose employing federated learning for supervised face recognition. Federated learning enables model training while maintaining privacy by leveraging decentralized edge devices. In our method, each edge device trains a model individually, which is subsequently sent to a secure aggregator. We use GAN to introduce different data without sending actual data. The aggregator combines various models into a global one, which is subsequently disseminated to the edge devices. Experiments with CelebA datasets show that federated learning effectively protects privacy while maintaining performance levels. © 2024 IEEE.

关键词： Federated learning

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Efficient Fund Tracking system using Blockchain and GraphDB 7

Efficient Fund Tracking system using Blockchain and GraphDB

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7th International Conference on Image information Processing, ICIIP 2023

作者： Kaushal, Arpit Nadda, Shiveen Modi, Praveen Jaypee University of Information Technology Dept. of Computer Science And Engineering And Information Technology H.P Solan India

ISBN: (纸本)9798350371406

Powerful Asset Tracking System is a cutting edge arrangement that utilizes the force of.blockchain innovation and Graph Database to give a vigorous and secure resource following stage. Conventional asset global positioning frameworks frequently face difficulties connected with straightforwardness, security and effectiveness. Notwithstanding, this framework conquers these limits by exploiting the blockchain and its decentralized and permanent nature, as well as the adaptability and versatility of.diagram information bases. By incorporating blockchain innovation, the framework guarantees a straightforward and unapproved recording of.asset exchanges. Every exchange is safely put away in blocks that structure a chain of.information that can't be changed or erased. This increases responsiveness and disposes of.the requirement for middle man, decreasing expenses and handling time. © 2023 IEEE.

关键词： Blockchain

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