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检索条件"任意字段=3rd International Conference on Signal and Data Processing, ICSDP 2023"

共 2953 条记录，以下是401-410 订阅

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Development of an optical particle counter for high particle number concentration 3

Development of an optical particle counter for high particle...

引用

3rd international conference on Optics and Image processing, ICOIP 2023

作者： Zhou, Quan Chen, Liang Chang, Liuyong Zhang, Chenglin Li, Guangze Li, Yuanhao School of Optics and Electronic Technology China Jiliang University Hangzhou311100 China Hangzhou Innovation Institute Yuhang Beihang University Hangzhou311100 China School of Mechanical and Electrical Engineering China Jiliang University Hangzhou311100 China

ISBN: (纸本)9781510667426

The upper limit of the particle concentration that current optical particle counters (OPC) can detect is generally lower than 100 P/cm3, while the particle concentration in industry gas is usually on the order of 104 P/cm3. In the present study, the reasons that the current OPC is limited for high particle concentration were analyzed, and a new high-concentration optical particle counter was developed. The reasons for the low detection limit of the current OPC are as follows: (1) the thickness of the laser is on the order of millimeters;(2) the current signal processing method by detecting the rising edge is sensitive to coverage loss. Based on this, the thickness of the sheet laser was reduced by optimizing the beam shaping components, and the coverage loss of traditional signal processing methods was overcome by counting the pulse peaks. After developing the new OPC, it was used to detect particles with different concentration, and the detecting results were compared with the counting results of a commercial condensation particle counter. The comparison results showed that the developed OPC can accurately detect the particles with the concentration lower than 12000 P/cm3 © 2023 SPIE. All rights reserved.

关键词： signal processing

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Embedded System of signal processing on FPGA: Implementation OpenMP Architecture 2nd

Embedded System of Signal Processing on FPGA: Implementation...

引用

3rd international conference on Digital Technologies and Applications

作者： Hadji, Mhamed Elhanaoui, Abdelkader Skouri, Rachid Agounad, Said Fac Sci & Technol REPTI Lab BP 509 Boutalamine Errachida Morocco Moulay Ismail Univ Meknes Meknes Morocco Moulay Ismail Univ Meknes High Sch Technol Km 5Rd AgourayN6 Meknes 50040 Morocco Ibn Zohr Univ Fac Sci Lab Metrol & Traitement Informat Agadir 80000 Morocco

ISBN: (纸本)9783031298561;9783031298578

The purpose of this paper is to study the phenomenon of acoustic scattering by using a new method. The signal processing (FFT iFFT BESSEL functions) is widely applied to obtain information with high precision accuracy. signal processing has a wider implementation in general-purpose processors Our interest was focused on the use of FPGAs (Field-Programmable Gate Arrays) in order to minimize the computational complexity in single processor architecture then be accelerated on FPGA and meet real time and energy efficiency ***-purpose processors are not efficient for signal processing. We implemented the acoustic backscattered signal processing model on the DE1SOC FPGA and compared it to Odroid xu4. By comparison, the computing latency of Odroid xu4 and FPGA are 60 s, and 20 s respectively. The detailed SoC FPGA-based system has shown that acoustic spectra are performed at up to 3 times faster than the Odroid xu4 implementation. FPGA-based system of processing algorithms is realized with an absolute error about 10(-2). This study underlines the increasing importance of embedded systems in underwater acoustics, especially in non-destructive testing. It is possible to obtain information related to the detection and characterization of submerged cells. So we have achieved good experimental results in real time and energy efficiency.

关键词： DE1 FPGA acoustic scattering Form function signal processing Non-destructive testing

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Reversible data Hiding for Interpolated Images using CNN based Nearest Neighbour Interpolation 3

Reversible Data Hiding for Interpolated Images using CNN bas...

引用

3rd international conference on Secure Cyber Computing and Communications, ICSCCC 2023

作者： Kumar, Praveen Ravi, Prateek Kumar, Rajeev Delhi Technological University Department of Computer Engineering Delhi India

ISBN: (纸本)9798350300710

Interpolation based reversible data hiding (rdH) has gained plenty of research interest because to its ability to increase large amount of secret information in an image. However, one of the issues is that it involves approximating pixel values, which can result in a loss of image detail or in other words deteriorated image quality. To resolve this issue, this paper defines an innovative rdH method for interpolated images using convolution neural network based nearest neighbor interpolation (CNN-NNI). The CNN-NNI generates high-resolution image that closely matches the original image by processing through a series of convolutional layers. On the other hand, the strategy for embedding data involves using both interpolated pixels as well as reference pixels for data insertion in each block. Experimental findings indicate that the suggested approach beats recently developed and comparable techniques not only on final visual quality yet also at the maximum embedding ability i.e., higher than 1.75 bpp including an average PSNR value higher than 30 dB. © 2023 IEEE.

关键词： Interpolation

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Human Evaluation Reproduction Report for data-to-text Generation with Macro Planning 3

Human Evaluation Reproduction Report for Data-to-text Genera...

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3rd Workshop on Human Evaluation of NLP Systems, HumEval 2023

作者： Arvan, Mohammad Parde, Natalie University of Illinois Chicago United States

ISBN: (纸本)9789544520885

This paper presents a partial reproduction study of data-to-text Generation with Macro Planning by Puduppully and Lapata (2021). This work was conducted as part of the ReproHum project, a multi-lab effort to reproduce the results of NLP papers incorporating human evaluations. We follow the same instructions provided by the authors and the ReproHum team to the best of our abilities. We collect preference ratings for the following evaluation criteria in order: conciseness, coherence, and grammaticality. Our results are highly correlated with the original experiment. Nonetheless, the presented results may be insufficient to conclude that the system proposed and developed by the original paper is superior compared to other systems. We suspect that combining our results with the three other reproductions of this paper through the ReproHum project will paint a clearer picture. Overall, we hope that our work is a step towards a more transparent and reproducible research landscape. © HumEval 2023 - Proceedings of the 3rd Workshop on Human Evaluation of NLP Systems, associated with the 14th international conference on Recent Advances in Natural Language processing 2023, RANLP 2023.

关键词： Natural language processing systems

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Research And Analysis of Blockchain System Based on Computer Big data Model 3

Research And Analysis of Blockchain System Based on Computer...

引用

3rd international conference on Digital signal and Computer Communications, DSCC 2023

作者： Di, Fuhao Economics School Ocean University of China Qingdao China

ISBN: (数字)9781510666566

ISBN: (纸本)9781510666559

In the cloud-side aggregated computing scenario, the base stations, routers and gateways deployed by edge servers are publicly accessible infrastructures, whose security is not guaranteed, and users' private data are vulnerable to huge threats, requiring means to safeguard user privacy. In an edge cloud, a large number of services will be deployed due to the need to support numerous edge-end devices, and selecting the optimal service combination solution from the large number of services is an imminent task. The existing cloud service providers can hardly take the responsibility of protecting users' privacy, and none of the users will actually own their data, so a data access control scheme needs to be designed to protect users' data from illegal access and tampering. © 2023 SPIE.

关键词： Big data

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DravidianLangTech 2023 - 3rd Workshop on Speech and Language Technologies for Dravidian Languages, associated with 14th international conference on Recent Advances in Natural Language processing, RANLP 2023 - Proceedings

DravidianLangTech 2023 - 3rd Workshop on Speech and Language...

引用

3rd Workshop on Speech and Language Technologies for Dravidian Languages, DravidianLangTech 2023

ISBN: (纸本)9789544520854

The proceedings contain 45 papers. The topics discussed include: on the errors in code-mixed Tamil-English offensive span identification;hate and offensive keyword extraction from CodeMix Malayalam social media text using contextual embedding;acoustic analysis of the fifth liquid in Malayalam;improving reinforcement learning agent training using text based guidance: a study using commands in Dravidian languages;social media data analysis for Malayalam YouTube comments: sentiment analysis and emotion detection using ML and DL models;findings of the second shared task on offensive span identification from code-mixed Tamil-English comments;overview of the shared task on fake news detection from social media text;findings of the shared task on sentiment analysis in Tamil and Tulu code-mixed text;and findings of the shared task on multimodal abusive language detection and sentiment analysis in Tamil and Malayalam.

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Research on College Student Employment Market Information Mining Based on Grey Theory 3

Research on College Student Employment Market Information Mi...

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3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Wang, Yue Computer Engineering and Science Academy Anhui University of Science & Technology Huainan China

ISBN: (纸本)9798350317022

This paper employs an integrated approach of data mining and grey theory to comprehensively analyze college student employment market dynamics from 2019 to 2023. Establishing an employment information data model and a grey relational model, the study introduces algorithms for processing certification, awards, and employment indices. A customized annual employment index algorithm, utilizing clustering strategies, is designed for college student employment attributes. Utilizing the grey relational model for binary and continuous attributes, the research identifies key factors significantly correlated with college student employment outcomes, including academic performance, certification qualifications, awards, gender, ethnicity, and language proficiency. The findings underscore the pivotal influence of academic achievements and certifications on employment prospects, further unveiling the nuanced impact of demographic factors. These results not only provide valuable insights for job seekers and recruiters but also contribute to a deeper understanding of the dynamic college student employment landscape, facilitating more informed decision-making strategies. © 2023 IEEE.

关键词： College Student Employment data mining Employment information Grey theory Relational degree

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Study on Wind Resource Assessment Based on Refined Wind Measurement data 3

Study on Wind Resource Assessment Based on Refined Wind Meas...

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3rd international conference on New Energy and Power Engineering, ICNEPE 2023

作者： Li, Deyuan Energy Development Co. Ltd. Chifeng New Energy Division Chaganhada Wind Farm Inner Mongolia Autonomous Region China

ISBN: (纸本)9798350393224

The data measured by millimeter wave radar in wind measurement has the advantages of high accuracy rate and low data loss rate, and the processing of the measured data is more accurate and reliable in the use of wind resource detection unit calibration, error revision of yaw pitch system, field station adaptability evaluation, and unit power generation capacity assessment. The wind data measured by a wind farm in Guizhou using millimeter wave radar at 10min intervals and based on a variety of different horizontal heights (10-200m) are used as a benchmark for wind resource assessment of wind power plants. This paper adopts correlation analysis to process the data and uses Weibull two-parameter distribution to theoretically study the wind frequency distribution law to calculate the annual effective wind power density in the region. The results of this study can accurately assess the wind resources. The results of this study can also avoid the loss of power generation caused by inaccurate data measurement in the process of fine evaluation of wind farm capacity and improve the reliability of wind farm site selection. © 2023 IEEE.

关键词： correlation analysis millimeter wave radar Weibull parameters wind power plants wind resource assessment

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Secure Image Communication: Integrating Diffie-Hellman Key Exchange for Enhanced Confidentiality 3

Secure Image Communication: Integrating Diffie-Hellman Key E...

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3rd international conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Shifani Francis, M. Dhalia Sweetlin, J. Sandhiya, M. Madras Institute of Technology Department of Information Technology Chennai India

ISBN: (纸本)9798350372120

The safety of data or images is a critical step in the vast field of Internet of Things (IoT) network communication. Image encryption is a well-known technique for protecting the information contained in images in order to maintain their confidentiality, authenticity, and integrity. The goal of the secure communication system described in the work proposed is to make image data exchange easier while preserving confidentiality and integrity. To create a secret key that is shared between communicating parties over an unsecure channel, the system uses the Diffie-Hellman key exchange mechanism. Sensitive image information connected to the sent photos is encrypted and decrypted using this shared key. In order to prevent eavesdropping and unauthorized access, the Diffie-Hellman key exchange algorithm makes it possible to securely generate a shared key without the need for direct key transmission. Encrypted image data guarantees that the sensitive information contained in the images can only be accessed and decoded by the designated recipient, who has the necessary decryption key. Through the integration of image data encryption techniques with the Diffie-Hellman key exchange's strength, the proposed system aims to offer a dependable and secure means of transferring images while protecting the privacy and confidentiality of related sensitive data. This system's efficiency stems from its capacity to securely exchange images over possibly unreliable channels while preserving the data's integrity and confidentiality. This system's efficiency extends beyond secure image exchange, finding potential applications in signal and image processing and enhancing its versatility for broader usage over possibly unreliable channels while preserving data integrity and confidentiality. © 2024 IEEE.

关键词： Electronic data interchange

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Efficient Hardware and Software Co-design for EEG signal Classification based on Extreme Learning Machine 3

Efficient Hardware and Software Co-design for EEG Signal Cla...

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3rd international conference on Electrical, Computer and Communication Engineering, ECCE 2023

作者： Lyu, Songyang Chowdhury, Mehdi Hasan Cheung, Ray C.C. City University of Hong Kong Department of Electrical Engineering Hong Kong Chittagong University of Engineering and Technology Department of Eee Chittagong Bangladesh

ISBN: (纸本)9798350345360

ElectroEncephaloGram (EEG) is associated with multiple functions, including communications with neurons, organic monitoring, and interactions with external stimuli. By decoding EEG signals, certain human activities such as sleeping, brain diseases, motor imagery, movement of limbs, and others can be observed and controlled through the brain-computer interface (BCI). Therefore, it is vital to efficiently process EEG signals with a robust and accurate system to build BCI systems with powerful applications. However, as a weak biosignal, EEG demands a fast-reaction system signal processing with high accuracy and sensitivity. In this work, a hardware/software co-design network based on Extreme Learning Machine (ELM) is introduced for the classification of certain actions, motor imagery of the human brain. This system is based on an optimized Hierarchical Extreme Learning Machine (H-ELM) on the software layer. The proposed method has advantages over previous designs with an accuracy of 90.3%. It also improves the training speed by around 25X compared to conventional methods. The software model is also translated into efficient FPGA hardware design to maintain high computation efficiency and reduce power consumption for biomedical applications. © 2023 IEEE.

关键词： Electroencephalography

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