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SP-DSTS-MIMO Scheme-Aided H.266 for Reliable High Data Rate Mobile Video Communication

computers, Materials & Continua 2023年第1期74卷 995-1010页

作者： Khadem Ullah Nasru Minallah Durre Nayab Ishtiaque Ahmed Jaroslav Frnda Jan Nedoma Department of Computer Systems Engineering University of Engineering and Technology PeshawarPeshawar25000Pakistan National Centre in Big Data and Cloud Computing University of Engineering and Technology Peshawar(NCBC-UETP)Peshawar25000Pakistan Department of Quantitative Methods and Economic Informatics Faculty of Operation and Economics of Transport and CommunicationsUniversity of Zilina01026ZilinaSlovakia Department of Telecommunications Faculty of Electrical Engineering and Computer ScienceVSB-Technical University of OstravaOstrava-PorubaCzech Republic

With the ever growth of Internet users,video applications,and massive data traffic across the network,there is a higher need for reliable bandwidth-efficient multimedia *** Video Coding(VVC/H.266)is finalized in September 2020 providing significantly greater compression efficiency compared to Highest Efficient Video Coding(HEVC)while providing versatile effective use for Ultra-High Definition(HD)*** article analyzes the quality performance of convolutional codes,turbo codes and self-concatenated convolutional(SCC)codes based on performance metrics for reliable future video *** advent of turbo codes was a significant achievement ever in the era of wireless communication approaching nearly the Shannon *** codes are operated by the deployment of an interleaver between two Recursive Systematic Convolutional(RSC)encoders in a parallel *** RSC encoders may be operating on the same or different architectures and code *** proposed work utilizes the latest source compression standards H.266 and H.265 encoded standards and Sphere Packing modulation aided differential Space Time Spreading(SP-DSTS)for video transmission in order to provide bandwidth-efficient wireless video ***,simulation results show that turbo codes defeat convolutional codes with an averaged E_(b)/N_(0) gain of 1.5 dB while convolutional codes outperformcompared to SCC codes with an E_(b)/N_(0) gain of 3.5 dBatBit ErrorRate(BER)of 10−*** Peak Signal to Noise Ratio(PSNR)results of convolutional codes with the latest source coding standard of H.266 is plotted against convolutional codes with H.265 and it was concluded H.266 outperform with about 6 dB PSNR gain at E_(b)/N_(0) value of 4.5 dB.

关键词： H.265 RSC turbo codes SCC SP-DSTS BP-CNN BER PSNR

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Internet of Things (IoT) based Model for Water Management System

Internet of Things (IoT) based Model for Water Management Sy...

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2023 International Conference on Smart Computing and Application, ICSCA 2023

作者： Haque, Md. Alimul Ahmad, Sultan Eljialy, A.E.M. Uddin, Mohammed Yousuf Sonal, Deepa Veer Kunwar Singh University Department of Computer Science Ara India College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Department of Computer Science Alkharj11942 Saudi Arabia Department of Computer Science and Engineering Chandigarh University Gharuan Punjab Mohali140413 India College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Department of Information Systems Alkharj11942 Saudi Arabia Patna Women's College Patna University Department of Computer Science Patna India

ISBN: (纸本)9798350347050

A significant decline in water quality assurance in the supply system is a factor related to public health. Clean water demand has increased over the last decade, and supply in India is uncertain. Water pressure is now the world's most significant obstacle. Water management can then take place, and the most important factor is how the services available worldwide are handled. One of the main concerns around sustainable globalization is water contamination. The traditional water quality analysis methods need a lot of time and effort. The standard must be tracked in real-time to ensure the safe delivery of drinking water. This paper presents the design and implementation of an affordable framework for real-time water quality monitoring and filtering in IoT. The proposed model helps collect, distribute, and analyze the data on water quality in real time. This allows the framework to respond automatically to changes in system performance. Data and analysis have been given to support the experiment of the proposed model. The model also provides a consumer interface to demonstrate the performance indicators such as lower-top and acceptable levels with infographics and meters. © 2023 IEEE.

关键词： pH sensors

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Algorithm-Driven Optimization of Cloud Computing Architectures for Superior Data Security and Efficiency 2

Algorithm-Driven Optimization of Cloud Computing Architectur...

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2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Pillai, N. Muthuvairavan Jesu Jayarin, P. David, D. Beulah Jeeva, K. Kumari, V Sheeja R.M.D Engineering College Department of Computer Science and Business Systems KavaraipettaiTamil Nadu Thiruvallur India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Information Technology Tamil NaduThandalam Chennai India Care College of Engineering Department of Computer Science and Engineering Tamil Nadu Trichy India Saveetha University Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Tamil NaduThandalam Chennai India

ISBN: (纸本)9798350384277

This paper examines how algorithm-driven optimization transforms cloud computing systems, focusing on data security and efficiency. Following a thorough cloud environment study, algorithms were picked and adapted to solve specific difficulties. After integration into the architecture, these algorithms were tested in a controlled simulation environment. CPU utilization rose from 70% to 90%, memory from 65% to 85%, storage from 60% to 80%, and network bandwidth from 75% to 95%. These improvements improve computational and storage efficiency. Intrusion detection became AI-based, and encryption increased from 128-bit to 256-bit. Data breaches dropped from 5 to 1 per year, while security standards compliance increased from partial to full. These improvements strengthened cloud security. The system became more responsive from 200 to 100 ms. Server load distribution evened out, peak load handling improved, and user experience rating rose from 3.5/5 to 4.5/5. These enhancements highlighted optimized load *** consumption dropped 30%, lowering operational costs. High cooling requirements became moderate due to energy-efficient infrastructure. Sustainability goals were met by reducing annual carbon footprint by 30%. © 2024 IEEE.

关键词： Cloud security

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Efficient UAV Routing Strategies for Wireless Sensor Network Data Retrieval

Efficient UAV Routing Strategies for Wireless Sensor Network...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Al-Sharhanee, Kareem Ali Malalah Najim, Ali Hamza Alheeti, Khattab M. Ali Satar, Nurhizam Safie Mohd Hashim, Aisha Hassan Abdallah Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq College of Engineering Techniques Department of Communication Technical Engineering Al-Farahidi University Baghdad10011 Iraq Department of Computer Technical Al-Diwaniyah Iraq College of Computer and Information Technology University of Anbar Computer Networking Systems Department Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

WSNs are applied in many disciplines where certain conditions require the ability to adapt to network sink mobility and changes in the dynamics of the area coverage. To meet these needs, it is necessary to develop integrated systems where the ''terrestrial' systems and the Unmanned Aerial Vehicles (UAVs)' collect data from sensors efficiently. Planning of UAV trajectories is another challenging issue if many WSN nodes are randomly deployed. This challenge has a big impact on the overall effectiveness of the system. This paper presents a novel approach for reducing the traveled distance of unscrewed aerial vehicles (UAVs) to improve the data collection efficiency in WSNs with poor node density. Yet the method that has been developed is aimed at increasing 'the efficiency and efficacy of data collection... with the assistance of Unmanned Aerial Vehicles (UAVs)' which means this work reveals practical application solutions. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Frequency Domain Auto-tuning of Structured LPV Controllers for High-Precision Motion Control 63

Frequency Domain Auto-tuning of Structured LPV Controllers f...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Broens, Yorick Butler, Hans Toth, Roland Asml Veldhoven Netherlands Eindhoven University of Technology Department of Electrical Engineering Eindhoven Netherlands Hunren Institute for Computer Science and Control Systems and Control Laboratory Hungary

ISBN: (纸本)9798350316339

Motion systems are a vital part of many industrial processes. However, meeting the increasingly stringent demands of these systems, especially concerning precision and throughput, requires novel control design methods that can go beyond the capabilities of traditional solutions. Traditional control methods often struggle with the complexity and position-dependent effects inherent in modern motion systems, leading to compromises in performance and a laborious task of controller design. This paper addresses these challenges by introducing a novel structured feedback control auto-tuning approach for multiple-input multiple-output (MIMO) motion systems. By leveraging frequency response function (FRF) estimates and the linear-parameter-varying (LPV) control framework, the proposed approach automates the controller design, while providing local stability and performance guarantees. Key innovations include norm-based magnitude optimization of the sensitivity functions, an automated stability check through a novel extended factorized Nyquist criterion, a modular structured MIMO LPV controller parameterization, and a controller discretization approach which preserves the continuous-time (CT) controller parameterization. The proposed approach is validated through experiments using a state-of-the-art moving-magnet planar actuator prototype. © 2024 IEEE.

关键词： Continuous time systems

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The SWH-Analytics Framework 2

The SWH-Analytics Framework

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2nd Italian Conference on Big Data and Data science, ITADATA 2023

作者： Antelmi, Alessia Torquati, Massimo Gregori, Daniele Polzella, Francesco Spinatelli, Gianmarco Aldinucci, Marco Computer Science Department University of Torino Italy Computer Science Department University of Pisa Italy HPC-KTT national lab CINI Italy E4 Computer Engineering SpA Italy Zerodivision systems Srl Italy

The Software Heritage (SWH) dataset serves as a vast repository for open-source code, with the ambitious goal of preserving all publicly available open-source projects. Despite being designed to effectively archive project files, its size of nearly 1 petabyte presents challenges in efficiently supporting Big Data MapReduce or AI systems. To address this disparity and enable seamless custom analytics on the SWH dataset, we present the SWH-Analytics (SWHA) architecture. This development environment quickly and transparently runs custom analytic applications on open-source software data preserved over time by SWH. © 2023 Copyright for this paper by its authors.

关键词： Open source software

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Using IoT to Smart Security Door System with Face Tracking Camera

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Intelligent Information Management 2024年第4期16卷 157-175页

作者： Amer Nizar AbuAli College of Computer Science and Engineering Information Systems Department Taibah University Medina KSA

Security is a serious concern, whether it may be the security of assets, data and human life. Providing humans with security and safety for their belongings and items is an important need. A smart lock door project/ with different types of methods for entry, like fingerprint and authentication PIN code is suggested with an unnoticeable face tracking camera capturing a photo in case of error data entry. It is to be controlled via the user’s smartphone using Blynk with the implementation of IoT. This technology is made with two microcontrollers. ESP32 is used to control the solenoid lock, fingerprint sensor and keypad. ESP32-CAM is used to capture a photo and send it to the owner’s smartphone to be viewed on Telegram application. Many conclusions are extracted from system results, as well as suggested ideas for future work.

关键词： Security Block Diagram Microcontroller Bluetooth Dual Mode

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Retinal Image Analysis for Early Deduction of Diabetic Retinopathy 9

Retinal Image Analysis for Early Deduction of Diabetic Retin...

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9th International Conference on Advanced Computing and Communication systems, ICACCS 2023

作者： Chinnasamy, A. Selvakumari, P. SRMIST School of Computing Department of Data Science and Business Systems Chennai India Anna University Chennai Institute of Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350397376

The prevalence of DR is steadily rising, which necessitates the automatic disease severity extraction and classification. About 2% of those with this illness are entirely blind because of the diabetic mellitus problem and 10% get vision impairment after 15 years of diabetes as a result of the DR complication. It is also a significant contributor to blindness in both middle aged and older age groups. The patient may develop to severe stages of irreversible blindness if the condition is not detected early. The growing number of diabetic patients face a major issue due to a lack of ophthalmologists. It is suggested that an automated DR screening system be created to aid the ophthalmologist in making decisions. One of the primary symptoms of the DR is hard exudates. The detection of hard exudates is crucial for screening purposes and aids in disease monitoring and diagnosis. Thus, utilising Lloyd's clustering technique, this work offered a unique techniques to segment the exudates and irregularities in DR were found. © 2023 IEEE.

关键词： Mean square error

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Robust Tweets Classification Using Arithmetic Optimization with Deep Learning for Sustainable Urban Living

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SN computer science 2024年第5期5卷 1-11页

作者： Hamza, Manar Ahmed Hashim, Aisha Hassan Abdalla Motwakel, Abdelwahed Elhameed, Elmouez Samir Abd Osman, Mohammed Kumar, Arun Singla, Chinu Munjal, Muskaan Department of Electrical and Computer Engineering International Islamic University Malaysia Kuala Lumpur 53100 Malaysia Department of Computer and Self Development Preparatory Year Deanship Prince Sattam bin Abdulaziz University AlKharj Saudi Arabia Department of Management Information Systems College of Business Administration in Hawtat bani Tamim Prince Sattam bin Abdulaziz University AlKharj Saudi Arabia Department of Computer Science College of Post-Graduated Studies University of Science and Technology Omdurman Sudan Department of Information System Faculty of Computer Science and Information Technology Omdurman Islamic University Omdurman Sudan Department of Electronics and Communication Engineering New Horizon College of engineering Bengaluru India Computer Engineering Thapar Institute of Engineering and Technology Punjab Patiala India

Natural Language Processing (NLP) with Deep Learning (DL) for Tweets Classification includes use of advanced neural network designs to analyse and classify Twitter messages. DL techniques like recurrent neural network (RNN) or transformer-based frameworks like BERT are used to mechanically learn difficult linguistic patterns and contextual info from tweet data. These techniques able to capture subtleties of language with sarcasm, sentiment, and context-specific meanings and making them suitable for tasks like sentiment analysis or topic classification in realm of social media. Leveraging deep symbols learned from great amounts of textual data, these NLP techniques permit precise and nuanced classification of tweets, donating to enhanced information retrieval, sentiment tracking, and trend analysis in dynamic and fast-paced world of social media communication. In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. The goal of the AOADL-TC technique is to identify and discriminate different kinds of sentiments that exist in the tweet data. At the initial stage, the AOADL-TC model pre-processes tweet data to convert uniform data into a useful format. For sentiment detection, the AOADL-TC technique applies a parallel bidirectional gated recurrent unit (BiGRU) model. At last, tuning of parameters related to parallel BiGRU model performed by AOA. An wide set of tests carried out to illustrate better performance of AOADL-TC model. The experimental outcomes portrayed that AOADL-TC technique demonstrates the supremacy of the AOADL-TC technique in terms of different evaluation metrics. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep learning Machine learning Natural language processing Sentiment analysis Social media

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Rosacea Classification Using Deep Stacking Multi-Layer Model (DSMLM) 2

Rosacea Classification Using Deep Stacking Multi-Layer Model...

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2nd International Conference on Emerging Trends in Information Technology and engineering, ic-ETITE 2024

作者： Antony Sophia, N. Saravanan, T.R. Vigneshwari, M. Deepika, N. Uma, K. Madhavan, P. Srm Institute of Science & Technology Department of Computational Intelligence Chennai Kattankulathur India Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering College Department of Information Technology Chennai India Sri Venkateswara College of Engineering Department of Computer Science and Engineering Chennai India School of Computer Science Engineering and Information Systems Vellore Institute of Technology Vellore Katpadi632014 India

ISBN: (纸本)9798350328202

Rosacea, a widespread and complex skin disorder affecting most of the world population, is divided into various subtypes with unique clinical features the complexity of these subtypes makes accurate classification difficult. A unique technique called the Deep Stacking Multi-Layer Model (DSMLM) has been proposed as a solution for this complex classification. To extract microelements from clinical images and patient history data, DSMLM uses a multilayered neural network architecture. Using the stacking ensemble strategy to combine predictions from different base models makes it possible to improve the classification performance. The effectiveness of the DSMLM is evaluated using a large dataset of different rose cases, and it shows remarkable accuracy in distinguishing between different rose subtypes © 2024 IEEE.

关键词： Large datasets

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