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7th Edition Global Conference on Wireless and Optical Technologies, GCWOT 2024

作者： Noor, Shaheena Saleem, Muhammad Imran Ismat, Najma Siddiqui, Aneeta Minhas, Humera Noor Inam, Hamza Sir Syed University of Engineering & Technology Department of Computer Engineering Karachi Pakistan Ssuet Department of Software Engineering Karachi Pakistan Ssuet Department of Computer Engg. Karachi Pakistan Eyeo Quality Filtering Engineering Department Cologne Germany Avioinics Engineering Pakistan Air Force Islamabad Pakistan

ISBN: (纸本)9798331534271

MobileNetV2 represents a significant advancement in the design of efficient neural networks for mobile and embedded applications. Its innovative use of inverted residuals, linear bottlenecks, and depthwise separable convolutions makes it an ideal choice for developers seeking to deploy powerful AI models on resource-constrained devices. This paper presents an efficient algorithm leveraging the MobileNetV2 architecture for the classification of eye diseases, specifically targeting Normal, Cataract, Glaucoma, and Retina Disease categories. The proposed model is designed to perform with high accuracy on resource-constrained devices, making it suitable for mobile and embedded applications in telemedicine and ophthalmology. Extensive testing on a comprehensive dataset has demonstrated the model's effectiveness, achieving precision and accuracy of 96.15% and 97.39%, respectively. This research addresses the growing need for accessible and reliable diagnostic tools in eye care, particularly in remote and underserved regions. © 2024 IEEE.

关键词： Ophthalmology

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Estimation of Chromatic Dispersion by means of Innovative Rectification Element 6

Estimation of Chromatic Dispersion by means of Innovative Re...

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6th Global Conference on Wireless and Optical Technologies, GCWOT 2023

作者： Abbasi, Madiha Rafique, Ayesha Akram, Noreen Akram, Ambreen Sir Syed University of Engineering and Technology Telecommunication Engineering Department Karachi Pakistan Bahria University Computer Science Department Karachi Pakistan

ISBN: (纸本)9798350333718

An optical signal becomes progressively more distorted as it travels a long-haul fiber transmission system. This distortion is the consequence of interamodal dispersion in single mode fibers. These distortion effects can be elucidated by inspecting the behavior of the group velocities of the guided *** this Research, the vital factors of optical fiber transmission system like Chromatic dispersion (CD) and Mode-Field-Diameter (MFD) has been estimated competitively and precisely. A modern formulation has been created with the concern of group refractive-index of optical fiber within the backscattered control of Optical-Time-Domain-Reflectometer OTDR that results to a more improved measurement. © 2023 IEEE.

关键词： Single mode fibers

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Review on Three-Factor Authorization based on different IoT Devices 6

Review on Three-Factor Authorization based on different IoT ...

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6th Global Conference on Wireless and Optical Technologies, GCWOT 2023

作者： Mairaj, Maryam Khan, M. Sadiq Ali Agha, Dur-E-Shawar Qazi, Farheen Sir Syed University of Engineering and Technology Department of Computer Engineering Karachi Pakistan University of Karachi Department of Computer Science Karachi Pakistan

ISBN: (纸本)9798350333718

Some of the most fundamental aspects of cybersecurity include authentication, confidentiality, integrity, and security. In this review paper, we provide a review of different existing Internet of things (IoT) devices like smart home devices, smart buildings, smart factories, etc. based on three factors of authentication. The solution of IoT applications anticipated by wireless networks to legitimate clients and users. For making secure IoT solutions for users, numerous mechanisms and protocols and cryptographic techniques have been studied which are proposed by some researchers. Things need a proper authentication system. Different research papers are reviewed that are based on Physically Secure lightweight protocol, multi-Gateway secure IoT Environments protocol, Tele biometric objects (TAO) with biometric sensors and telecommunication networks, and Multi-Factor Authentication that prevent for the users to avoid threats and man-in-The-middle attacks, etc. The paper concludes with some services that can benefit from security techniques anticipated from future technology. © 2023 IEEE.

关键词： Authentication

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A Comparative Study of the Performance of Real time databases and Big data Analytics Frameworks 7

A Comparative Study of the Performance of Real time database...

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7th International Multi-Topic ICT Conference: IMTIC 2023

作者： Mustafa, syed Muhammd Nabeel Farooq, Muhammad Umer Zehra, syeda Sundus Noronha, Jospeh Peter Terenece Ned University of Engineering and Technology Dept. of Computer Science & I.T Karachi Pakistan Sir Syed University of Engineering and Technology Dept. of Software Engineering Karachi Pakistan

ISBN: (纸本)9798350338461

The amelioration of information technology and the infiltration of it almost all the sectors of world have resulted in massive efflux of data. The rampant increase in the generation of data has introduced to a new term called, Big data. Big data is letting industry set the pace of future research and development. The need rose to further refine the data and get most out of it. Scientists and researchers performed analytic on the Big data to analyze it for patterns and behaviors hidden inside the data. Big data analytics aid in understanding the data through various tools, algorithms and frameworks. It allows stakeholders to make business plans and strategies according to the revelations from data. There are various tools and technologies available to perform analytics on the data. The most popular among scientists and researchers are real-time database and Big data analytics frameworks. In the paper, we evaluate the performance of the tools and technologies of Big data analytics. Mongodb and Firebase are real-time databases implemented in this study and Impala and Hive are the BDA frameworks. The parameter to perform the comparison is the query execution time. It is found out that Impala and Hive gave lesser execution time than Mongodb and Firebase. The query execution time of Impala on 50 mb dataset and 100 mb dataset was recorded to be 4 ms and 14 ms respectively. Hence, Big data Analytics Frameworks are better performing analytics tools for Big data Analytics. © 2023 IEEE.

关键词： Big data

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Predicting Lung Cancer Risk Using Artificial Intelligence 2

Predicting Lung Cancer Risk Using Artificial Intelligence

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2nd International Conference on Computing and Data Analytics, ICCDA 2024

作者： Shah, syed Mehr Ali Jamil, Danish Khan, Muhammad Numan Ali Al-Jarwani, Fatma Mahfoodh Mohammed College of Computing & Information Sciences University of Technology and Applied Sciences Musandam Oman University of Santiago de Compostela Spain Sir Syed University of Engineering & Technology Department of Software Engineering India College of Computing & Information Sciences University of Technology and Applied Sciences shinas Oman

ISBN: (纸本)9798331542573

This research proposes a method to accurately forecast the risk of lung cancer in its initial stages by the combination of medical diagnosis and artificial intelligence. Two distinct models are employed: a symptoms-based model utilizing linear regression, and VGG19, a component of CNNs is employed for the analysis of chest x-ray images. The objective of this dual-model approach is to improve comprehensiveness and precision in the early prediction of lung cancer risk. The JSRT and Chest Xray-14 datasets were utilized to train and validate the convolutional neural network (CNN). The Regression model was trained using the Survey Lung cancer Dataset. This initiative prioritizes user-friendliness, interpretability, and ethical considerations of healthcare AI. Initial positive results show that this combined approach has a lot of potential for early detection © 2024 IEEE.

关键词： Lung cancer

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Smart Water Level Monitoring System Using Internet of Things (IoT) 6

Smart Water Level Monitoring System Using Internet of Things...

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6th Global Conference on Wireless and Optical Technologies, GCWOT 2023

作者： Parveen, Safina Nabeel Mustafa, syed Muhammad Soomro, Sanober Bano, Shama Sir Syed University of Engineering and Technology Department of Computer Engineering Karachi Pakistan NED University of Engineering and Technology Department of Computer Science & I.T Karachi Pakistan

ISBN: (纸本)9798350333718

Water shortage is the major issue in the modern world. Conservation is urgently needed as a result of the population's growing need for water on a minute-by-minute basis. Every aspect of life has been automated thanks to information and technology. Automation is now simpler because to the expansion of the Internet of Things (IoT). It has applications in the monitoring and management of equipment. IoT has given humans the ability to remotely operate a variety of instruments. We provide a model to manage and monitor the water flow in order to conserve water using the wonders of IoT. The proposed methodology uses water tanks with ultrasonic sensors to measure the liquid level and contrast it with the depth of the container. The storage system's water level is detected by the system. In this case, sensors are installed in the tank at various levels. A microcontroller is attached to the sensors. The sensors gauge the water level and transmit that information to the microprocessor, which updates the mobile application and LCD with the tank condition. Using an ultrasonic sensor, the user can manually override the mobile application's operation of the pump. This technology will give users a mobile application and buzzer to let them know how their tanks are doing, making it simple for them to operate. The system can be enhanced to ensure that dams operate effectively. © 2023 IEEE.

关键词： Internet of things

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Enhancing Smart Mobility Through Machine Learning and Neural Networks 7

Enhancing Smart Mobility Through Machine Learning and Neural...

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7th Edition Global Conference on Wireless and Optical Technologies, GCWOT 2024

作者： Nadeem, Muhammad Haider, Waleej Ahmed, Haris Khan, Sallar Sir Syed University of Engineering & Technology Department of Computer Science & Information Technology Karachi Pakistan School of Informatics & Cybersecurity Technological University Dublin Dublin Ireland

ISBN: (纸本)9798331534271

This study investigates the prediction of taxi trip durations in New York City using machine learning (ML) models and neural networks (NN). Three models Linear Regression, Random Forest Regressor, and a Neural Network were developed and evaluated on a dataset containing various trip details. The analysis highlighted the importance of geographic and temporal features in predicting trip durations. The Neural Network model outperformed others, achieving a mean squared error (MSE) of 12,577,211 and a root mean squared error (RMSE) of 3,546, significantly better than the comparative models. These results underscore its capacity to capture complex urban mobility patterns effectively. The superior performance of the Neural Network supports its potential to optimize traffic flow and reduce congestion in dense urban environments, offering substantial improvements to urban transportation systems. © 2024 IEEE.

关键词： Neural network models

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Lightweight security Mechanism for IoT Applications using Substitution-Box 4

Lightweight security Mechanism for IoT Applications using Su...

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4th IEEE International Conference on Artificial Intelligence in Cybersecurity, ICAIC 2025

作者： Hanif, Fozia Shams, Rehan Waheed, Urooj University of Karachi Department of Mathematics Karachi Pakistan Sir Syed University of Engineering and Technology Karachi Department of Telecommunication Pakistan DHA Suffa University Karachi Department of Computer Science Pakistan

ISBN: (纸本)9798331518882

In recent times the use of small computing devices for gathering information from the real world is increasing day by day. The devices like wireless sensors, RIFD tags, embedded devices and IoT devices are required to transmit huge amounts of confidential data for monitoring and controlling. IoT applications have now become an important factor across various industries. That is why the security of IoT device is always been an important issue, because they transmit private and sensitive data. For handling the security issue cryptography is one the way for handling the security issues of IoT devices but sometimes cryptographic algorithms are cracked and as well as very costly. Lightweight cryptography requires less memory and less computational cost. Substitution box is a very useful concept in generating the lightweight cryptographic algorithm that provide robust security in the process of encryption. This study produces lightweight cryptographic encryption and decryption algorithm with the help of substitution boxes. The provided scheme not only provides the encryption procedure but also generating a flexible key structure which enhances the security for IoT devices where lightweight image encryption is crucial. The provided technique will be beneficial for those places where confidential public data has to be secured. The aim of this paper is to recommend effective original and straightforward techniques of encryption and decryption by using the substitution box. Experimental results show the efficiency of the suggested technique in terms of execution time and throughput. © 2025 IEEE.

关键词： Encryption algorithms

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Recursive Neural Network Based Degradation Trend Estimation for Efficient Maintenance of Aerial Bundled Cables 6

Recursive Neural Network Based Degradation Trend Estimation ...

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6th Global Conference on Wireless and Optical Technologies, GCWOT 2023

作者： Talha, syed Muhammad Umar Ali, syed Muhammad Ahmed, syed Sheraz Ali, Asif Mairaj, Tariq Sir Syed University of Engineering & Technology Department of Telecommunication Engineering Karachi Pakistan National University of Sciences and Technology Pakistan Navy Engineering College Department of Electrical Engineering IslamabadH-12 Pakistan

ISBN: (纸本)9798350333718

Aerial Bundle Cables (ABCs) have been used for overhead power distribution in many parts of the world. ABCs are of great interest to metropolitan areas with electrical pilferage problems, as their inherent insulation offers better protection. One such instance is M/s KE deploying ABCs in the coastal city of Karachi. The ABCs experienced rapid degradation due to the moist, humid, and harsh environment of Karachi. However, the degradation is not visually observable due to insulation, and in turn, compromises early detection. Non-Destructive Testing (NDT) techniques offer a solution for condition monitoring of the ABCs for degradation detection. A historical database of appropriate NDT and environmental data enables degradation trend prediction. This research work reports a degradation trend prediction scheme for ABCs using Recursive Neural Network (RNN) based Artificial Intelligence (AI) model. The reported work uses custom-Acquired real NDT data of in-service ABCs. Promising results show the efficacy of the AI-based prediction scheme. © 2023 IEEE.

关键词： Condition monitoring

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COVID-19 Classification from X-Ray Images:An Approach to Implement Federated Learning on Decentralized Dataset

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Computers, Materials & Continua 2023年第5期75卷 3883-3901页

作者： Ali Akbar Siddique S.M.Umar Talha M.Aamir Abeer D.Algarni Naglaa F.Soliman Walid El-Shafai Department of Telecommunication Engineering Sir Syed University of Engineering&TechnologyKarachi75300Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

The COVID-19 pandemic has devastated our daily lives,leaving horrific repercussions in its *** to its rapid spread,it was quite difficult for medical personnel to diagnose it in such a big *** who test positive for Covid-19 are diagnosed via a nasal PCR *** comparison,polymerase chain reaction(PCR)findings take a few hours to a few *** PCR test is expensive,although the government may bear expenses in certain ***,subsets of the population resist invasive testing like ***,chest X-rays or Computerized Vomography(CT)scans are preferred in most cases,and more importantly,they are non-invasive,inexpensive,and provide a faster response *** advances in Artificial Intelligence(AI),in combination with state-of-the-art methods,have allowed for the diagnosis of COVID-19 using chest *** article proposes a method for classifying COVID-19 as positive or negative on a decentralized dataset that is based on the Federated learning *** order to build a progressive global COVID-19 classification model,two edge devices are employed to train the model on their respective localized dataset,and a 3-layered custom Convolutional Neural Network(CNN)model is used in the process of training the model,which can be deployed from the *** two edge devices then communicate their learned parameter and weight to the server,where it aggregates and updates the *** proposed model is trained using an image dataset that can be found on *** are more than 13,000 X-ray images in Kaggle Database collection,from that collection 9000 images of Normal and COVID-19 positive images are *** edge node possesses a different number of images;edge node 1 has 3200 images,while edge node 2 has *** is no association between the datasets of the various nodes that are included in the *** doing it in this manner,each of the nodes will have access to a separate image collection that has no correl

关键词： Artificial intelligence deep learning federated learning COVID-19 decentralized image dataset

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