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NoSQL Cloud based Bigdata technologies for efficient performance evaluation in the modern era

NoSQL Cloud based Bigdata technologies for efficient perform...

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international conference on Computational Intelligence and communication networks (CICN)

作者： Sangeeta Gupta Kavita Agrawal CSE Department Chaitanya Bharathi Institute of Technology Hyderabad Telangana India

ISBN: (纸本)9781665487726

Modern society's most recent technology breakthroughs have given rise to innovations that, when handled effectively, can result in value-added outcomes or, when handled incorrectly, can cause disruptions. One such technology is the plethora of NoSQL cloud databases that have developed. there isn't a single store that combines all of these properties, despite the fact that these provide a wide range of features like consistency, availability, fault-tolerance, scalability, and security. this aspect gains wide support if integrated with various learning platforms to yield an added outcome. Regardless of the dataset, applying pre-processing techniques and identifying data splits is a necessary step to do in order to infer better outcomes. Towards this end, an efficient NoSQL cloud datstore based analysis is presented to showcase the significance of NoSQL over traditional relational databases to overcome bigdata analysis based difficulties. Based on the type of data to be examined and the evaluation of the results, an appropriate cloud datastore is chosen.

关键词： Performance evaluation Technological innovation Social networking (online) Scalability Loading Fault tolerant systems Memory

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2022 international conference on Microwave and Millimeter Wave Technology, ICMMT 2022 - Proceedings

2022 International Conference on Microwave and Millimeter Wa...

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14th international conference on Microwave and Millimeter Wave Technology, ICMMT 2022

ISBN: (纸本)9781665467520

the proceedings contain 722 papers. the topics discussed include: a cost-effective over-the-air test verification method for 5G active antennas;retro-directive microwave power beam steering with attitude and position errors of array modules;the adaptive wideband beamforming using convolutional neural network;simulation and research on vehicle-ground communication channel of Maglev train;deep learning approach for gesture recognition on millimeter-wave radar;design and implementation of mmWave phased-array radar for three-dimensional imaging;a series and parallel hybrid unequal power divider feeding network based on ridge gap waveguide;an adaptive maneuvering target tracking algorithm with unknown prior information in beamformer;a novel sonar image denoising algorithm based on block matching;a mode stirring-based automatic test system for indoor electromagnetic environment evaluation;wideband and low-RCS circularly polarized patch antenna based on polarization conversion metasurface using characteristic mode analysis;a method of generating orbital angular momentum based on curved meanderline;and a method of experimental measurement of the frequency stability in a magnetron.

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Image-based Road Pothole Detection using Deep Learning Model

Image-based Road Pothole Detection using Deep Learning Model

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international conference on Computational Intelligence and communication networks (CICN)

作者： Priyanka Gupta Manish Dixit Department of CSE MITS Gwalior India

ISBN: (纸本)9781665487726

Road pothole detection is essential to ensure any engineering structures' health. Manual pothole detection and classification is very human-intensive work. Several sensor-based techniques, laser imaging approaches, and image processing techniques have been deployed to less the intervention of humans in road inspections. Still, these approaches have some limitations, such as high cost, less accuracy, and risk during detection, as Machine learning-based approaches require manual feature extraction for the prediction. therefore, this proposed work aims to use deep learning modes for better pothole detection results. Several pothole datasets are available online, and deep learning-based methods require lots of data for the training; therefore, pothole images are collected from the different datasets and combined into one dataset to train the model. Augmentation is also applied to the dataset for better training, as augmentation provides images with different angles, and by fine-tuning the model consequently, records with about 98 % accuracy.

关键词： Deep learning Training Learning systems Roads Transfer learning Lasers Manuals

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A PSO Tuned CNN Approach for Accurate Fault Detection in PV Grid systems

A PSO Tuned CNN Approach for Accurate Fault Detection in PV ...

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international conference on communication systems and Network Technologies (CSNT)

作者： Naresh Kumar J. Raji S. Sridevi Md Mujahid Irfan R. Rajeshwari Abinaya Inbamani EES Uni. Poly. Faculty of Engineering and Technology Jamia Millia Islamia New Delhi India Department of Electrical and Electronics Engineering Bharath Institute of Higher Education and Research Chennai India Department of Electrical and Electronics Engineering Achariya College of Engineering Technology Puducherry India Department of Electrical and Electronics Engineering SR University Warangal Telangana India Department of Electrical and Electronics Engineering J.P. College of Engineering Ayikudi Tenkasi MM Research and Developments

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Photovoltaic (PV) systems are growing in popularity and are widely utilized in power systems to capture renewable energy. However, these systems remain susceptible to numerous defects caused by environmental variables, device lifespan, and failures in operation. the proposed system presents an effective methodology for fault diagnostics in PV-connected grid systems by combining Particle Swarm Optimization (PSO) with Convolutional Neural networks (CNN). the system utilizes data to monitor crucial factors like voltage, current, and other indicators of performance. this data is processed through acquisition and preprocessing stages, including normalization and structured transmission, to ensure effective analysis for further use in decision-making processes. the hybrid model employs PSO to optimize CNN hyperparameters, enhancing the network's ability to accurately detect and classify faults. In this work, Python software implemented to diagnose faults in PV systems, with the effectiveness of the proposed approach evaluated using a "Solar Panel Fault Detection Dataset". the results are evaluated to ensure accurate and making an accuracy of 93.36%, precision of 94%, recall of 95%, and an F1 score of 95% for maintaining the stability and efficiency of PV-connected grid systems.

关键词： Renewable energy sources Accuracy Fault detection Voltage Power system stability Stability analysis Software Convolutional neural networks Particle swarm optimization Python

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Secret Key Rate of Quantum Key Distribution Assuming Worst-Case Attacks

Secret Key Rate of Quantum Key Distribution Assuming Worst-C...

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international ITG conference on Source and Channel Coding (SCC)

作者： Amelie Sophia Ettinger Marcel Kokorsch Guido Dietl University of Würzburg Professorship of Satellite Communication and Radar Systems Würzburg Germany

ISBN: (数字)9798331522896

ISBN: (纸本)9798331522902

Quantum Key Distribution (QKD) represents a revolutionary approach in the field of cryptography, offering the potential for unconditional security by leveraging the principles of quantum mechanics. this paper addresses the crucial issue of calculating secure key rates in entanglement based QKD systems. We present a method of key rate calculations that is independent of an eavesdropper's quantum system, relying solely on the quantum states shared between two communicating parties under the assumption of a worst-case attack. We undertake a comparison of asymptotic key rates with those observed in the finite regime, in which only a limited number of quantum states are exchanged. Furthermore, we investigate the influence of entanglement distillation on the achievable key rates. By identifying the numerically optimal number of entanglement distillation iterations based on the initial fidelity and the number of exchanged quantum states, we demonstrate how to achieve a balance between the quantity and quality of entangled states, thereby maximizing the secure key rate. Our results show that there is a unique optimum within a defined search range. Moreover, we determine the minimum number of exchanged quantum states necessary to attain a positive key rate and to obtain a desired number of secure key bits, which are both contingent upon the quality of the communication channel. It is anticipated that the insights gained from this work will prove instrumental in the development of optimal routing strategies in quantum communication networks.

关键词： Measurement Quantum system Limiting Quantum entanglement Instruments Quantum state Routing Encoding Quantum key distribution Quantum communication

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Shared Cross-Prediction Neural Network for Efficient Key Generation in IoT networks

Shared Cross-Prediction Neural Network for Efficient Key Gen...

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international ITG conference on Source and Channel Coding (SCC)

作者： Anas Alashqar Ehsan Olyaei Torshizi Raed Mesleh Werner Henkel School of Computer Science and Engineering Constructor University Bremen Germany School of Electrical Engineering and information technology German Jordanian University Amman Jordan

ISBN: (数字)9798331522896

ISBN: (纸本)9798331522902

Physical layer secret key generation (PSKG) lever-ages the reciprocal properties of wireless channels to establish cryptographic keys between legitimate users. However, in time-division duplex (TDD) systems, this reciprocity can be compromised by hardware imperfections and channel noise, complicating the key generation process. To address these challenges, we propose a shared cross-prediction neural network (SCP-NN) model that operates in an unsupervised manner, eliminating the need for perfect channel state information (CSI). Specifically, the proposed SCP-NN model employs a cross-prediction strategy that minimizes the difference between the predicted channels of legitimate users, ensuring that the outputs converge toward each other. Furthermore, we present a comprehensive PSKG procedure that leverages the SCP-NN architecture to extract key information from the phase characteristics of the channel frequency responses. Experimental results demonstrate that the proposed SCP-NN significantly reduces the key disagreement ratio (KDR), providing a robust and effective solution for secure key generation in dynamic IoT environments.

关键词： Wireless communication Deep learning Neural networks Noise Predictive models Physical layer Hardware Encoding Data mining Cryptography

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Smart systems of open science in teachers' education 14

Smart systems of open science in teachers' education

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14th international conference on Mathematics, Science and Technology Education, ICon-MaSTEd 2022

作者： Marienko, M.V. Nosenko, Yu H Shyshkina, M.P. Institute For Digitalisation Of Education Of The Naes Of Ukraine 9 M. Berlynskoho Str. Kyiv04060 Ukraine

the project announced by the authors is focused on the smart systems of open science, the issues of elaboration of methodological, methodic, and organizational support for the use of these emerging ICT in teaching and research, increasing the level of ICT competence of educators, including teachers. Given the significant pedagogical potential and novelty of existing approaches to the use of smart learning systems meaning first of all the cloud-based adaptive open science systems, their design and use in educational institutions, these issues still need theoretical and experimental research, refinement of approaches, models, methods and techniques, possible ways of implementation. In the process of studying leading experience, the following advantages of using the cloud-based services for teachers' training were identified: resource savings, access mobility, elasticity, and others. the cloud-based methodological system for educational personnel training at different levels was proposed and considered: for the training of students for the Master level for educational sciences;for the in-service teachers' training. the methods and tools of smart systems design and implementation were considered and evaluated. the recommendations and suggestions for the advisable ways for smart systems of open science introduction into the learning process were provided. © Published under licence by IOP Publishing Ltd.

关键词： Personnel training

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Security and Privacy Issues of Satellite communication in the Avlatlon Domain 14

Security and Privacy Issues of Satellite Communication in th...

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14th international conference on Cyber Conflict, CyCon 2022

作者： Baselt, Georg Strohmeier, Martin Pavur, James Lenders, Vincent Martinovic, Ivan ETH Zurich Department of Computer Science Zurich Switzerland Cyber-Defence Campus armasuisse Science + Technology Thun Switzerland University of Oxford Department of Computer Science Oxford United Kingdom

ISBN: (纸本)9789916978900

Modern aviation systems increasingly use satellite channels for data communication. However, many SATCOM providers do not offer encryption below the application layer by default, making their services vulnerable to eavesdroppers and creating security concerns. this research analyses such vulnerabilities specifically with regard to the aviation domain. We show that even low-resourced attackers can exploit this lack of security. We capture a broad range of SATCOM transmissions in the Ku-Band frequencies using a TV Tuner Card and widely available low-budget equipment for under 400 US dollars. Over 370 GB of aviation-related satellite-downstream data from high-throughput satellites were analysed from a measurement site in Central Europe. the results of this campaign reveal both security and privacy concerns across the whole spectrum of the industry. We identify unencrypted SATCOM usage comprising usage from in-flight entertainment systems to leaked private encrypted keys. Furthermore, we identified 328 specific aircraft broadcasting their live operations, including three government aircraft that actively blocked any information on their flights from air-traffic tracking sites. this work concludes with recommendations for both satellite service providers and aviation stakeholders on how these issues could be solved by using encryption at different network layers. © 2022 NATO CCDCOE.

关键词： Satellites

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Improved Dynamic Collision Recovery in Wireless Ad-Hoc networks: System and RTL Modeling

Improved Dynamic Collision Recovery in Wireless Ad-Hoc Netwo...

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international conference on Computing and Networking Technology (ICCNT)

作者： Hussam Murad Fatma Newagy M. Watheq El-Kharashi Computer and Systems Eng. Dept. Ain Shams University Cairo Egypt Electronics and Communication Eng. Dept. Ain Shams University Cairo Egypt

Wireless ad-hoc networks are local area networks that are built without a centralized administration point. they are widely utilised in many applications, particularly those involving the Internet of things (IoT), such as environmental monitoring, smart homes, smart agriculture, and many other IoT applications. However, when the network's size grows, network throughput rapidly declines, mainly because of more collisions. According to the IEEE 802.11 standard, the carrier sense multiple access with collision avoidance protocol is the basic medium access control technique used by the 802.11 standard, also known as the distributed coordination function. It uses the Binary Exponential Backoff (BEB) algorithm for collision avoidance. Avoiding collisions will optimize the network with regard to throughput. this paper proposes an improved dynamic backoff algorithm called Dynamic Enhanced Collision Resolution Algorithm (D-ECRA), which improves the recently introduced Enhanced Collision Resolution Algorithm (ECRA) by replacing the contention window exponential increment with a less aggressive and dynamic contention window increment based on the network’s size. the Register Transfer Level (RTL) design of D-ECRA is proposed using Verilog HDL. Results demonstrate that D-ECRA surpasses BEB and ECRA with regard to throughput with a maximum improvement percentage of 4% and 1.2% respectively. Also, results showed that D-ECRA performed better than ECRA with regard to delay with a maximum improvement percentage of 43%. this thesis shows the assessment process for D-ECRA including simulation parameters and test scenarios for both system and RTL modelling.

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Quantum Image Classification on NISQ Devices

Quantum Image Classification on NISQ Devices

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international conference on Computational Intelligence and communication networks (CICN)

作者： Shuroog Al-Ogbi Abdulrahman Ashour Muhamad Felemban Computer Engineering Department KFUPM Dhahran Saudi Arabia Mechanical Engineering Department KFUPM Dhahran Saudi Arabia Computer Engineering Department Center for Intelligent Secure Systems KFUPM Dhahran Saudi Arabia

ISBN: (纸本)9781665487726

Quantum computing is an emerging computing field that is expected to make a huge impact on several scopes of science and technology. In this paper, we investigate the role of quantum computing in image classification, as an important branch of machine learning with widely used applications in healthcare, military, and IR4.0. In particular, we systemically compare the performance of two well-known classical image classification systems, i.e., Support Vector Machine (SVM) and Convolutions Neural Network (CNN), with equivalent quantum image classification algorithms, i.e., Quantum Support Vector Machine (Q-SVM) and Quantum Convolutional Neural Network (Q-CNN). Both quantum and classical algorithms are implemented on available Noisy-Intermediate Scale Quantum (NISQ) devices using MNIST dataset. Performance of models were compared regarding accuracy and training time. the results show that classical algorithms outperform the quantum algorithms for the given tasks. However, we observe that large-scale fault-tolerant quantum computing can effectively perform image classification tasks in the future.

关键词： Support vector machines Performance evaluation Quantum algorithm Machine learning algorithms Fault tolerant systems Machine learning Classification algorithms

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