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检索条件"任意字段=Conference on Real-Time Photonic Measurements, Data Management, and Processing"

共 171 条记录，以下是1-10 订阅

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XMeta-OS: A Conceptual Framework for Unified Resource management in Distributed Edge-Cloud Environments 3rd

XMeta-OS: A Conceptual Framework for Unified Resource Manag...

引用

3rd International conference on Advances in Computing Research, ACR 2025

作者： Zacharioudakis, Eleftherios Kakoulli, Elena Evripidou, Salomi Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos Pafos Cyprus National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus

ISBN: (纸本)9783031876462

This paper introduces XMeta-OS, a meta-operating system specially designed with Linux as its foundation to unify and optimize resource management for the distributed edge-cloud when dynamic use of GPU resources is possible. This approach offer a new GPU abstraction layer and dynamic edge-cloud allocation model that offer enhanced flexibility and resource utilization over existing systems like Kubernetes and OpenStack. By using likely sensitive data, the model applied cloud-pushed deployment model. XMeta-OS manages computer resources in real-time. Therefore, fulfilling high performance various needs. It allocates CPU and GPU in real-time to workloads requiring massive parallel processing, such as machine learning, scientific simulations, real-time data analytics, and transportation tasks. Fabrication in the laboratory of an edge-cloud environment can help to assess the scalability, fault tolerance and efficiency of the system. It showcases the overall architectural design of XMeta-OS. Changes to the kernel and security solutions for safe and effective distribution are suggested. This article presents the design of the XMeta-OS. The future of XMeta-OS entails usage and testing with which we see latency, energy, computation and other such measurements in labs. XMeta-OS is a solution to cost performance, emerging application, large-scale edge-cloud deployments, and distributed GPU-enabled infrastructures. Meta-Operating System in Edge-Cloud Continuum for dynamic resource management of GPU. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cluster computing

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real-time photonic measurements, data management, and processing IV

Real-Time Photonic Measurements, Data Management, and Proces...

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real-time photonic measurements, data management, and processing IV 2019

ISBN: (纸本)9781510631014

The proceedings contain 23 papers. The topics discussed include: multifunctional microwave signal generation and processing based on equivalent phase modulation;a triple-frequency microwave photonic link based on a polarizationmultiplexing dual-parallel mach-zehnder modulator;performance analysis of photonic RF self-interference cancellation for full-duplex communication;polarization characterization based on multidimensional Stokes vectors applied in aerosol identification;study on correlation matrix composed of multidimensional polarization index applied in aerosol recognition in the air;deep learning with synthetic photonic lattices for equalization in optical transmission systems;a comparison of image recognition algorithms for cell phenotyping in optofluidic time-stretch microscopy;and ultrafast time-encoded flow imaging for Giardia cysts and cryptosporidium oocysts detection.

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real-time photonic measurements, data management, and processing VI

Real-time Photonic Measurements, Data Management, and Proces...

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real-time photonic measurements, data management, and processing VI 2021

ISBN: (纸本)9781510646537

The proceedings contain 24 papers. The topics discussed include: LFM-Costas waveform generation based on a Fourier domain mode locking optoelectronic oscillator;ultra-narrow linewidth SOA fiber laser assisted by distributed self-injection feedbacks;all-fiber flat-top orbital angular momentum mode convertor realized by a SMF-based helical grating with phase modulation;low-speed photonic sampling for self-referenced frequency response characterization of high-speed photodetectors;a photonic-assisted transceiver for microwave doppler frequency shift measurement;simultaneous three-dimensional measurement of temperature and velocity fields in swirling combustion;and real-time construction and control on dynamic systems.

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real-time photonic measurements, data management, and processing V

Real-time Photonic Measurements, Data Management, and Proces...

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real-time photonic measurements, data management, and processing V 2020

ISBN: (纸本)9781510639256

The proceedings contain 15 papers. The topics discussed include: photonic microwave frequency measurement based on harmonic down-conversion by using a semiconductor optical amplifier;simultaneous distance and velocity measurement based on a bidirectional chirped fiber Bragg grating (CFBG);parity-time-symmetric system in photonic parameter space for hight quality signal generation;effect of bandwidth of direct detection receiver on multiparameter optical performance monitoring;a versatile single-photon spectrograph for the spectral measurement of the two-photon state;and simulation and analysis of single-mode beam splitter in lithium niobate thin film.

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real-time photonic measurements, data management, and processing VII

Real-time Photonic Measurements, Data Management, and Proces...

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real-time photonic measurements, data management, and processing VII 2023

ISBN: (纸本)9781510667938

The proceedings contain 12 papers. The topics discussed include: polarization dynamics of ultra-narrow modes generated in random fiber lasers;advancing phase recovery in time-stretch computational cell imaging;a novel Rayleigh lidar signal denoising algorithm for far-field noise suppression and high-accuracy retrieval;research on lightweight synchronization recognition algorithms for multiple acoustic sources in a photoacoustic sensor system based on Sagnac interference;a study on the improvement of sensitivity consistency in Sagnac photoacoustic sensing system;practical issues in repetition-rate control of optical pulse trains and frequency combs by talbot self-imaging;research on electrode-free rf receiver front-end based on lithium niobate photonic chip;and hybrid-integrated optoelectronic oscillator with wideband tunability and low phase noise.

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Auto Text Correction Using NLP Techniques

Auto Text Correction Using NLP Techniques

引用

Mobile Computing and Sustainable Informatics (ICMCSI), International conference on

作者： Nalla Srivarsha Gummadi Nithin Shanmugasundaram Hariharan Bibhuti Bhusan Dash Subrata Chowdhury Sudhansu Shekhar Patra Department of Artificial Intelligence and Data Science Vardhaman College of Engineering Hyderabad India School of Computer Applications Kalinga Institute of Industrial Technology (KIIT) Deemed to be University Bhubaneswar India Dept. of Computer Science and Engineering Sreenivasa Institute of Technology and Management Studies(A) Chittoor Andhra Pradesh India

ISBN: (数字)9798331522667

ISBN: (纸本)9798331522674

Auto text correction is a fundamental tool in modern Natural Language processing (NLP) that upgrades user involvement by decreasing typographical and linguistic errors in composed content. This extends leverages progressed NLP procedures to create a strong and proficient auto-correction framework that precisely predicts and corrects content input errors in real-time. The framework utilizes a combination of deep learning models, such as sequence-to-sequence models and transformers, in conjunction with conventional strategies like n-grams and edit distance algorithms. By analyzing the context and structure of input sentences, the model is able to offer relevant rectifications, making it versatile to different dialects and user composing styles. Moreover, we investigate diverse assessment measurements and compare different calculations to optimize the precision and productivity of the correction system. The arrangement has potential applications in word processors, mobile keyboards, and other content input platforms where high accuracy and low latency are crucial.

关键词： Productivity Program processors Keyboards Linguistics Transformers Prediction algorithms Natural language processing real-time systems Low latency communication Mobile computing

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Innovative, Semi-Permanent Sensors in the Era of Industry 4.0: Technological Solutions for Efficient Monitoring and Automation

Innovative, Semi-Permanent Sensors in the Era of Industry 4....

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International Russian Smart Industry conference (SmartIndustryCon)

作者： Ilya Kovalev Elena Korshunova Arsen Tagaev Department of Computer Control Systems MSUT “STANKIN” Moscow Russia Department of Economics and Enterprise Management MSUT “STANKIN” Moscow Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

In the era of Industry 4.0, manufacturing and research environments demand increasingly sophisticated monitoring and diagnostic systems. Alongside traditional stationary and portable sensors, semi-permanent (hybrid) sensors have emerged to offer a balanced solution that leverages the high accuracy of fixed installations and the mobility of handheld devices. These hybrid sensors integrate seamlessly with wireless communication protocols, such as Bluetooth Low Energy (BLE) and Wi-Fi etc, providing sufficient data throughput for moderate to high-frequency measurements (e.g., vibration analysis). Their adaptability allows rapid relocation, on-the-fly updates, and real-time data processing, reducing downtime and enhancing responsiveness in dynamic production workflows. Furthermore, the hybrid approach facilitates advanced analytics—such as machine learning algorithms and augmented reality (AR) overlays—without relying solely on dedicated, permanent instrumentation. Semi-permanent sensors address various operational challenges, including cost-effective deployment, compatibility with legacy systems, and centralized data management within ERP platforms. They are thus particularly beneficial for organizations aiming to accelerate digital transformation initiatives, improve predictive maintenance strategies, and minimize equipment failure risks. Although extremely harsh or specialized environments may still favor fully stationary or highly portable options, semi-permanent sensors strike an optimal balance of flexibility and reliability. As a result, they represent an effective foundation for modern condition-monitoring frameworks in Industry 4.0.

关键词： Wireless communication Vibrations Accuracy Production Vibration measurement Sensors Fourth Industrial Revolution Monitoring Intelligent sensors Wireless fidelity

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An Advanced Cognitive Approach for Personalized Drug Formulation in Type 2 Diabetes Using Deep Neural Networks and Feature-based Fusion

An Advanced Cognitive Approach for Personalized Drug Formula...

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Intelligent Control, Computing and Communications (IC3), International conference on

作者： Brijendra Pratap Singh Jagendra Singh Madhuri Suryavanshi Jailani S A. beer A. Amer Rakesh Kumar School of Computer Science Engineering & Technology Bennett University Greater Noida India Pimpri Chinchwad College of Engineering Pune India R&D Formulation Dev. Alpha Pharma KAEC Rabigh Saudi Arabia Sadat academy for management and Sciences Alexandria Egypt Department of Computer Science and I.T. Magadh University Bodh Gaya India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

Personalized medicine is an innovative approach toward achieving improved therapeutic outcomes, notably in chronic diseases like Type 2 Diabetes (T2D), where individualised drug formulations represent the crux of treatment. Conventional methods of drug prescription tend to focus on generic approaches without considering the specific genetic, physiological, and lifestyle characteristics of individuals. This research fills this gap by developing an advanced deep learning-based method for personalised drug formulation in T2D. It integrates diverse patient data, including demographics, medical history, clinical measurements, genomic information, pharmacokinetic information, real-time monitoring data, and responses to previous treatments. For optimal drug formulation, it makes use of a combination of deep learning models, such as Recurrent Neural Network (RNN) for time-series prediction, Convolutional Neural Network (CNN) for genomic analysis, GAN for producing synthetic data, and auto-encoder for feature extraction. The dataset consists of 2700 patient records collected over one year, wherein the pre-processing phase includes handling missing values, normalising continuous variables, and encoding categorical features. Trained models were assessed based on precision, recall, F1-score, and AUC ROC levels; the best performance came from the RNN model with a maximum accuracy of 97.35%. CNN, GAN, and Autoencoder also obtained similar competitive results. However, the RNN-based model received the highest score in recommending the appropriate drugs. The application of this research can contribute to the broader discipline of precision medicine.

关键词： Drugs Recurrent neural networks Accuracy Autoencoders Genomics Generative adversarial networks real-time systems Diabetes Convolutional neural networks Bioinformatics

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An Advanced Cognitive Approach for Personalized Drug Formulation in Type 2 Diabetes Using Deep Neural Networks and Feature-based Fusion

An Advanced Cognitive Approach for Personalized Drug Formula...

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2025 International conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Singh, Brijendra Pratap Singh, Jagendra Suryavanshi, Madhuri Jailani, S. Amer, A. Beer A. Kumar, Rakesh School of Computer Science Engineering & Technology Bennett University Greater Noida India Pimpri Chinchwad College of Engineering Pune India Alpha Pharma Kaec R&d Formulation Dev. Rabigh Saudi Arabia Sadat academy for management and Sciences Canob street Alexandria Egypt Magadh University Department of Computer Science and I.T. Bodh Gaya India

ISBN: (纸本)9798331527495

Personalized medicine is an innovative approach toward achieving improved therapeutic outcomes, notably in chronic diseases like Type 2 Diabetes (T2D), where individualised drug formulations represent the crux of treatment. Conventional methods of drug prescription tend to focus on generic approaches without considering the specific genetic, physiological, and lifestyle characteristics of individuals. This research fills this gap by developing an advanced deep learning-based method for personalised drug formulation in T2D. It integrates diverse patient data, including demographics, medical history, clinical measurements, genomic information, pharmacokinetic information, real-time monitoring data, and responses to previous treatments. For optimal drug formulation, it makes use of a combination of deep learning models, such as Recurrent Neural Network (RNN) for time-series prediction, Convolutional Neural Network (CNN) for genomic analysis, GAN for producing synthetic data, and auto-encoder for feature extraction. The dataset consists of 2700 patient records collected over one year, wherein the pre-processing phase includes handling missing values, normalising continuous variables, and encoding categorical features. Trained models were assessed based on precision, recall, F1-score, and AUC ROC levels;the best performance came from the RNN model with a maximum accuracy of 97.35%. CNN, GAN, and Autoencoder also obtained similar competitive results. However, the RNN-based model received the highest score in recommending the appropriate drugs. The application of this research can contribute to the broader discipline of precision medicine. © 2025 IEEE.

关键词： Theranostics

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Reconfigurable photonic integrated computing chip based on quadrilateral MZI topology network 6

Reconfigurable photonic integrated computing chip based on q...

引用

conference on real-time photonic measurements, data management, and processing VI

作者： Yao, Yuhan Zhao, Yuhe Dong, Jianji Huazhong Univ Sci & Technol Wuhan Natl Lab Optoelect Wuhan 430074 Peoples R China

ISBN: (数字)9781510646544

ISBN: (纸本)9781510646544;9781510646537

photonic integrated circuits (PICs) play an important role in transporting and processing analog information. Reconfigurable optical computing chip can meet the needs of implementing miniaturized and multi-functional signal processors which has become a research hotspot in recent years. Here, we designed and fabricated a reconfigurable photonic integrated computing chiyp based on a quadrilateral MZI topology network. Several analog signal processing functions including temporal differentiation, integration and Hilbert transformation are experimental demonstrated with a processing bandwidth of 40 GHz. By reconfiguring optical path and changing the spectral ratio of the MZI structure in the network, the functions can be switched and the operation order can be tuned. The quadrilateral network is universal and can be extended to a larger network structure in the future.

关键词： Silicon photonics reconfigurable photonic circuits photonic analog signal processing

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