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检索条件"任意字段=Conference on Advances in Optical Data Storage Technology"

共 5078 条记录，以下是61-70 订阅

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Emerging Technologies in Photovoltaic-Thermal (PVT) Systems: A Review of Cooling Strategies, Material advances, and Configurations

Emerging Technologies in Photovoltaic-Thermal (PVT) Systems:...

引用

Innovative Research in Applied Science, Engineering and technology (IRASET),conference on

作者： Ayoub Riad Houssam Amiry Abdelilah Sadik Said Yadir Fouad Belhora Abdelowahed Hajjaji Samira Touhtouh LabSIPE Laboratory ENSAJ Chouaib Doukkali University El Jadida Morocco MPEQ Laboratory ENSA Cadi Ayyad University Safi Morocco

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

The dual challenges of rising global energy demand and environmental degradation necessitate innovative approaches to harness renewable energy efficiently. This review investigates recent advancements in PVT systems, emphasizing thermal management, materials, and configurations. Results compiled from literature reveal that nanofluid-based systems enhance thermal conductivity and cooling performance compared to conventional fluids, while phase-change materials and dual-fluid configurations support temperature regulation and energy storage. Selective absorber coatings and bifacial PV modules contribute to improved optical-thermal efficiency and broader energy capture. Additionally, innovations like CPVT and BIPVT systems have enabled integration into industrial, residential, and off-grid contexts, with compact and scalable designs supporting modular deployment. Structured tables summarize performance trends across configurations, highlighting the effectiveness of radiative cooling, hybrid PCM integration, and advanced glazing in varying climates. Despite these advances, recurring challenges include material cost, performance degradation under harsh conditions, and integration into existing infrastructure. This review synthesizes current progress and highlights future research opportunities, providing a comprehensive understanding of the potential and limitations of PVT systems in addressing global energy sustainability goals.

关键词： Photovoltaic systems Phase change materials Technological innovation Reviews Cooling Market research Regulation Sustainable development Thermal stability Meteorology

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Research on optimization algorithm in grid engineering survey data acquisition and processing based on cloud computing 5

Research on optimization algorithm in grid engineering surve...

引用

5th International conference on Telecommunications, Optics, and Computer Science, TOCS 2024

作者： Zhang, Jiyong Sun, Xiaohu Huang, Bing Liu, Donghui Ren, Peixiang State Grid Economics and Technology Research Institute Co. Ltd. Beijing 102209 China

ISBN: (纸本)9781510691667

With the increasing scale of power grids and the growing demand for intelligence, efficient and accurate collection and processing of grid engineering survey data has become critical. This study aims to explore the optimization application of cloud computing technology in grid engineering data collection and processing. We design and implement an optimization algorithm based on cloud computing, which integrates several technologies such as distributed computing, big data storage and management, cluster monitoring and security management. Through comparative experiments, our algorithm significantly outperforms traditional methods in terms of data processing speed, achieving at least a four-fold improvement;in terms of data accuracy, the error rate is controlled at a lower level of 0.2%-0.3%. In addition, our method demonstrates good scalability and cost-effectiveness. This study not only provides an efficient data processing solution for power grid engineering, but also lays a solid foundation for the intelligent and digital transformation of future power grids. © 2025 SPIE.

关键词： cloud computing grid engineering optimization algorithm survey data

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Maize quality prediction method based on the PIC-former model

Maize quality prediction method based on the PIC-former mode...

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2024 International conference on Computer Application and Information Security, ICCAIS 2024

作者： Zuo, Min Cui, Jingyi Zhang, Qingchuan Dong, Wei National Engineering Research Centre for Agri-Product Quality Traceability Beijing Technology and Business University Beijing 100048 China Beijing Wuzi University Beijing 101149 China Beijing Institute of Economic and Management Beijing 100102 China

ISBN: (纸本)9781510689312

Maize is one of the three major cereal crops in our country. During storage, maize quality can deteriorate. The speed of this deterioration is influenced by initial moisture content and storage conditions. It's essential to assess quality indicators during maize storage to determine the maize's state and better adjust storage strategies. This study considers time, initial moisture content, temperature, and humidity as independent variables, while multiple quality indicators of maize serve as dependent variables. We developed the PIC-former model based on the Transformer model to predict changes in maize quality. Additionally, the K-Means++ algorithm evaluates the quality during storage by comparing predicted values with actual values. We conducted experiments using maize storage data from Pinggu District in Beijing, and the results showed that the PIC-former model achieved the smallest prediction error. Therefore, this paper can provide technical support for maize storage and offer effective reference for warehouse personnel to adjust storage conditions. © The Authors.

关键词： deep learning Maize storage temporal prediction

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Landslide knowledge graph construction

Landslide knowledge graph construction

引用

2024 International conference on Computer Application and Information Security, ICCAIS 2024

作者： Hou, Yuhan Ye, Runqing Wu, Runze Huang, Jue Fu, Xiaolin Wuhan Center China Geological Survey (Geosciences Innovation Center of Central South China) Hubei Wuhan 430205 China Institute of Geological Survey China University of Geosciences Hubei Wuhan 430074 China Hubei Key Laboratory of Operation Safety of High Dam and Large Reservoir (China Three Gorges Corporation) Hubei Yichang 443133 China

ISBN: (纸本)9781510689312

In the contemporary era of big data, the field of landslide research has amassed a substantial volume of data. To effectively leverage this data, a bottom-up approach can be employed to construct a landslide knowledge graph, facilitating efficient retrieval and comprehensive analysis of landslide information. This paper proposes a framework for the construction of such a knowledge graph, aiming to integrate geological hazard data. The framework utilizes graph database technology for storage and enables visualization of the knowledge graph, enhancing its usability and interpretability. © The Authors.

关键词： Big data data integration knowledge graph landslide

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Fine-Grained Subjective Visual Quality Assessment for High-Fidelity Compressed Images

Fine-Grained Subjective Visual Quality Assessment for High-F...

引用

data Compression conference (DCC)

作者： Michela Testolina Mohsen Jenadeleh Shima Mohammadi Shaolin Su João Ascenso Touradj Ebrahimi Jon Sneyers Dietmar Saupe Multimedia Signal Processing Group EPFL Lausanne Switzerland Multimedia Signal Processing Group Universität Konstanz Konstanz Germany Instituto Superior Técnico Lisbon Portugal Media Technology Research Group Cloudinary Belgium

ISBN: (数字)9798331534714

ISBN: (纸本)9798331534721

advances in image compression, storage, and display technologies have made high-quality images and videos widely accessible. At this level of quality, distinguishing between compressed and original content becomes difficult, highlighting the need for assessment methodologies that are sensitive to even the smallest visual quality differences. Conventional subjective visual quality assessments often use absolute category rating scales, ranging from “excellent” to “bad”. While suitable for evaluating more pronounced distortions, these scales are inadequate for detecting subtle visual differences. The JPEG standardization project AIC is currently developing a subjective image quality assessment methodology for high-fidelity images. This paper presents the proposed assessment methods, a dataset of high-quality compressed images, and their corresponding crowdsourced visual quality ratings. It also outlines a data analysis approach that reconstructs quality scale values in just noticeable difference (JND) units. The assessment method uses boosting techniques on visual stimuli to help observers detect compression artifacts more clearly. This is followed by a rescaling process that adjusts the boosted quality values back to the original perceptual scale. This reconstruction yields a fine-grained, high-precision quality scale in JND units, providing more informative results for practical applications. The dataset and code to reproduce the results will be available at https://***/jpeg-aic/dataset-BTC-PTC-24.

关键词： Image quality Visualization Image coding Transform coding Standardization Observers Quality assessment Image storage Image reconstruction Videos

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Rapid Probe Microscope (RPM) technology advances High-Speed AFM Systems for Next-Generation Semiconductor Metrology

Rapid Probe Microscope (RPM) Technology Advances High-Speed ...

引用

IEEE/SEMI conference and Workshop on Advanced Semiconductor Manufacturing

作者： Lei Feng Vishal Panchal Richard Thorogate James Robinson Andrew Humphris Infintesima Ltd Abingdon U.K

ISBN: (数字)9798331531850

ISBN: (纸本)9798331531867

High-speed AFM systems for in-line semiconductor process control have recently been commercialised, and this emerging technology is now being integrated into advanced device manufacturing. This paper explores the applications and opportunities of these systems in supporting next-generation metrology and process control, focusing on measurement, data analysis, and achievable throughput under production conditions. Performance data from the Metron3D system is provided, highlighting its use in next-generation lithography and advanced packaging case *** the advent of High Numerical Aperture Extreme Ultraviolet (HNA-EUV) lithography, the reduction in lithographic depth of focus necessitates near-perfect planarization across varying lateral scales. For lithographic process optimisation, accumulating evidence demonstrates that 3D Atomic Force Microscopy (AFM) metrology provides critical data for the fine-tuning of these processes, offering localised 3D insights that are unattainable with current electron beam (e-beam) and optical metrology methods. The Rapid Probe Microscope (RPM), an advanced hybrid optical AFM incorporated into the Metron3D system is evaluated. The RPM’s sensitivity to lithographic process parameters is demonstrated through 3D characterisation of contact hole geometries at feature sizes smaller than current technology nodes, achieving critical dimensions (CD) down to 12 nm, aligning with the stringent requirements of HNA-EUV *** advancing demands of next-generation packaging technologies impose equally rigorous performance standards on Chemical Mechanical Planarisation (CMP) processes. For advanced packaging, particularly in hybrid bonding processes, A robust methodology for measuring copper pad heights on semiconductor wafers is presented, at a scanning speed of 7.1 mm/s, with exceptional repeatability of 20 pm, whilst achieving throughput rates exceeding 60 wafers per hour (WPH) under standard sampling conditions for in – line use.

关键词： Semiconductor device measurement Three-dimensional displays Production Metrology Packaging Semiconductor device manufacture Throughput Probes Next generation networking Standards

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Machine and Deep Learning Classifications for IoT-Enabled Healthcare Devices

Machine and Deep Learning Classifications for IoT-Enabled He...

引用

Pervasive Computational Technologies (ICPCT), International conference on

作者： Lalit Kumar Tyagi Anish Gupta Vibhash Singh Sisodia Department of Computer Science & Engineering Chandigarh Engineering College Chandigarh Group of Colleges Mohali India Sri Bhawani Niketan Institute of Technology and Management Jaipur India

ISBN: (数字)9798331508685

ISBN: (纸本)9798331519476

The Internet of Things (IoT) is transforming academic research and will impact various industries, including healthcare. IoT has transformed healthcare from blast-shaped outdated centralized methods to decentralized smart devices. This led to tailored health systems. Recent advances in wearables, sensor networks, and computing cloud have made large-scale health care IoT usage easier. Despite its serious limitations, IoT can change medicine. Maintenance of various appliances, pricing increases, and the need for greater storage space all issues. IoT is a diverse and durable technology, thus this study will analyze its health sector use. How machine learning and deep learning interact is being studied. The Internet of Things (IoT) health system architecture is also covered in this article, along with its benefits and use cases. This helps highlight IoHT difficulties and encourages academics to create innovative solutions. This paper examines the current work of numerous researchers in machine learning and deep learning, which are heavily linked with IoT-based healthcare approaches.

关键词： Deep learning Ethics Accuracy data security Medical services Transforms Internet of Things Predictive analytics Wearable devices Biomedical imaging

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Learning Structured Compressed Sensing with Automatic Resource Allocation

Learning Structured Compressed Sensing with Automatic Resour...

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International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Han Wang Eduardo Pérez Iris A. M. Huijben Hans van Gorp Ruud Van Sloun Florian Römer Applied AI Signal Processing and Data Analysis Fraunhofer Institute for Nondestructive Testing IZFP Germany Electronic Measurements and Signal Processing Ilmenau University of Technology Germany Department of Electrical Engineering Eindhoven University of Technology The Netherlands

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Multidimensional data acquisition often requires extensive time and poses significant challenges for hardware and software regarding data storage and processing. Rather than designing a single compression matrix as in conventional compressed sensing, structured compressed sensing yields dimension-specific compression matrices, reducing the number of optimizable parameters. Recent advances in machine learning (ML) have enabled task-based supervised learning of subsampling matrices, albeit at the expense of complex downstream models. Additionally, the sampling resource allocation across dimensions is often determined in advance through heuristics. To address these challenges, we introduce Structured COmpressed Sensing with Automatic Resource Allocation (SCOSARA) with an information theory-based unsupervised learning strategy. SCOSARA adaptively distributes samples across sampling dimensions while maximizing Fisher information content. Using ultrasound localization as a case study, we compare SCOSARA to state-of-the-art ML-based and greedy search algorithms. Simulation results demonstrate that SCOSARA can produce high-quality subsampling matrices that achieve lower Cramér Rao Bound values than the baselines. In addition, SCOSARA outperforms other ML-based algorithms in terms of the number of trainable parameters, computational complexity, and memory requirements while automatically choosing the number of samples per axis.

关键词： Location awareness Ultrasonic imaging Supervised learning Signal processing algorithms Software Resource management Sparse matrices Speech processing Compressed sensing Unsupervised learning

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36.6 A 112Gb/s 0.61pJ/b PAM-4 Linear TIA Supporting Extended PD-TIA Reach in 28nm CMOS

36.6 A 112Gb/s 0.61pJ/b PAM-4 Linear TIA Supporting Extended...

引用

IEEE International conference on Solid-State Circuits (ISSCC)

作者： Yangyi Zhang Zhenyu Yao Wentao Zhou Xiongshi Luo Zhenghao Li Dongshen Zhan Quan Pan Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798331541019

ISBN: (纸本)9798331541026

The growing demand for cloud storage and artificial intelligence applications pushes optical communications to higher data rates and lower cost. Co-packaging the PD, BiCMOS TIA, and CMOS switch ASIC on the same substrate can effectively improve signal integrity and reduce power consumption, improving integration density and reducing the cost [1]–[2]. Integrating the TIA into the switch ASIC in CMOS can further reduce the total component counts, achieving lower cost and power consumption [3], as shown in Fig. 36.6.1 (top left). A reasonable distance from the PD to TIA+ASIC is needed to circumvent the constraints of the ASIC thermal expansion, the optical coupling flexibility, the mechanical stability, and field replacement caused by short PD-TIA reach, as shown in the table of Fig. 36.6.1 (middle left). A PD-TIA reach of 0.2inch is confirmed to be adequate through industry trial and error. However, extending PO- TIA reach leads to increased signal reflection, induces in-band amplitude un-flatness, and deteriorates bandwidth. Previous works [3]–[4] have sought to address these issues by scaling the characteristic impedance of the interconnect lines and introducing damping resistors. However, these approaches only support a maximum PD-TIA reach of 0.03inch [4]. This paper presents a 4×112Gb/s PAM-4 TIA with active-input-termination TIA (AIT-TIA) and signal-interpolation-based single-ended-to-differential convertor (S2D), supporting a 0.2inch PD-TIA reach with a 0.61 pJ/b power efficiency.

关键词： Resistors Thermal expansion Costs Power demand optical switches Solid state circuits Thermal stability Substrates Signal integrity Switching circuits

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advances In optical data storage technology: 8-10 November 2004, Beijing, China (Proceedings of S P I E)

Advances In Optical Data Storage Technology: 8-10 November 2...

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2005年

作者： Duanyi Xu Kees A Schouhamer Immink Keiji Shono

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