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Space Charge Measurement by PEA Method on an Aeronautical Cable 3

Space Charge Measurement by PEA Method on an Aeronautical Ca...

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3rd IEEE international conference on Dielectrics (ICD)

作者： Benyoucef, Amin Berquez, Laurent Teyssedre, Gilbert Aubert, Eddy Univ Paul Sabatier Bat 3R3 Laplace 118 Route Narbonne F-31062 Toulouse France IRT St Exupery 3 Rue Tarfayan F-31405 Toulouse France Safran Elect & Power 1 Rue Louis Bleriot F-31700 Blagnac France

ISBN: (纸本)9781728189833

Technological evolutions in aircraft networks let us foresee an increase of the DC voltage up to several kilovolts while keeping minimal insulation thickness. This trend results in a strong increase of the electric field in the insulations and space charge can become an issue for the reliability of the systems. Indeed, space charge accumulation modifies the electric field distribution and may lead to a premature aging of the dielectric. Besides, the field distribution in complex structures such as multilayers cannot be anticipated under DC as easily as under AC because conductivity is more difficult to estimate and varies much more than permittivity. In this paper, we present the first results obtained on aeronautical cables. For this, it was necessary to develop a deconvolution strategy adapted to aeronautical cables to obtain electric field and charge density profiles in a part of the insulation thickness.

关键词： Electric space charge

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Face Anti-spoofing Based on Specular Feature Projections 3rd

Face Anti-spoofing Based on Specular Feature Projections

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3rd international conference on Computer Vision and Image Processing (CVIP)

作者： Katika, Balaji Rao Karthik, Kannan Indian Inst Technol Guwahati Dept Elect & Elect Engn Gauhati 781039 Assam India

ISBN: (纸本)9789813290884;9789813290877

The need for facial anti-spoofing has emerged to counter the usage of facial prosthetics and other forms of spoofing at unmanned surveillance stations. While some part of literature recognizes the difference in texture associated with a prosthetic in comparison with a genuine face, the solutions presented are largely prosthetic model specific and rely on two-sided calibration and training. In this paper, we focus on the specular component associated with genuine faces and claim that on account of the natural depth variation, its feature diversity is expected to be much larger as compared to prosthetics or even printed photo impersonations. In our work concerning one-sided calibration, we first characterize the specular feature space corresponding to genuine images and learn the projections of genuine and spoof data onto this basis. The trained SVM corresponding to genuine projections, 3D mask projections, and printed photo projections is then used as an anti-spoofing model for detecting impersonations.

关键词： Face Anti-spoofing Specular feature Eigenspace Printed photos 3D Mask Low-rank component Sparse component SVM classifier

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Processing RGB-D Data from a 3D Camera using Object Detection and Written Character Recognition in Convolutional Neural Networks for Virtual Finger Writing 2020

Processing RGB-D Data from a 3D Camera using Object Detectio...

引用

3rd international conference on Image and Graphics Processing (ICIGP)

作者： Del Rosario, Ezekiel G. Nadora, Carlo P. Trinidad, Renee Lou G. Samonte, Mary Jane C. Devaraj, Madhavi De Goma, Joel C. Mapua Univ Makati 1200 Philippines

ISBN: (纸本)9781450377201

This study presents an approach to Virtual Finger Writing by treating it as an object detection problem. A Convolutional Neural Network using the Tiny YOLOv3 Architecture was used in this study to enable real-time hand detection. A Kinect camera is used to capture the depth data within the bounding box of the hand region to detect the nearest point in that area which is assumed to be the writing finger. The goal of this study is to present an approach for real-time virtual finger-writing in uncontrolled environments as a possible input method for future hologram or virtual reality systems. After testing and validation of trained model, the study were able to achieve a vast improvement in speed and accuracy results with the application of modern object detection.

关键词： Virtual finger writing object detection convolutional neural networks hand detection human-computer interaction

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Proceeding - 2020 3rd international conference on Vocational Education and Electrical Engineering: Strengthening the framework of Society 5.0 through Innovations in Education, Electrical, Engineering and Informatics Engineering, ICVEE 2020

Proceeding - 2020 3rd International Conference on Vocational...

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3rd international conference on Vocational Education and Electrical Engineering, ICVEE 2020

ISBN: (纸本)9781728174341

The proceedings contain 71 papers. The topics discussed include: hydrothermal growth temperature dependence of nanostructured nickel oxide transparency;high availability in software-defined networking using cluster controller: a simulation approach;what’s in a caption?: leveraging caption pattern for predicting the popularity of social media posts;performance evaluation of ESP8266 for wireless nurse call system;the effect of participation in scientific research and conference on vocational teachers' competence;motion sensing for wireless body area networks based on android using Wi-Fi direct transmission;and deep learning implementation of facemask and physical distancing detection with alarm systems.

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An Improved Three-level DC-DC Boost Converter for Renewable energy systems.with High Gain

An Improved Three-level DC-DC Boost Converter for Renewable ...

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international conference on Energy, Power and Environment: Towards Sustainable Growth (ICEPE)

作者： S. Raghavendran K. Sateesh Kumar Abhilash. Tirupathi Chittibabu. B SRM Institute of Science and Technology Kattankulathur Chennai India Career Launcher Edu. Ltd Surampalem India IIITDM Kancheepuram India

ISBN: (纸本)9781665425360;9781665430869

High gain DC-DC converters are essential candidates for integrating the low voltage photovoltaic (PV) sources to the grid-tied distributed power generation systems. In this paper, a simple non-isolated high gain three-level boost (TLB) converter is developed by the addition of two power switches and two diodes to the standard TLB converter. The voltage boosting and balancing is achieved by regulating the phase shift between the main switches. Moreover, the proposed converter achieves high gain without using the high frequency transformer, coupled inductor, and switched capacitor networks. Also, it has larger degree of freedom for duty ratio without any core saturation of the inductor. Therefore, use of the proposed converter in grid-tied distributed power generation systems.enhances the reliability and efficiency of the overall system. PSIM 9.0 simulation toolbox is used to validate the performance of the proposed high gain converter.

关键词： Photovoltaic systems Low voltage Renewable energy sources Switched capacitor networks Transformer cores distributed power generation High-frequency transformers

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3rd international conference on Advanced Science and Engineering, ICOASE 2020

3rd International Conference on Advanced Science and Enginee...

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3rd international conference on Advanced Science and Engineering, ICOASE 2020

ISBN: (纸本)9781665415798

The proceedings contain 38 papers. The topics discussed include: video delivery based on random linear network coding;SAARSNet: a deep neural network for COVID-19 cases diagnosis;a fusion scheme of texture features for COVID-19 detection of CT scan images;glove word embedding and DBSCAN algorithms for semantic document clustering;COVID-19 diagnosis systems.based on deep convolutional neural networks techniques: a review;trust evaluation model based on statistical tests in social network;distributed denial of service attack mitigation using high availability proxy and network load balancing;voltage build-up behavior of self-excited induction generator under different loading conditions;enhance the performance of independent component analysis for text classification by using particle swarm optimization;and clustering documents based on semantic similarity using HAC and K-mean algorithms.

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CPD 2020: The 3rd international Workshop on Combining Physical and Data-Driven Knowledge in Ubiquitous computing 20

CPD 2020: The 3rd International Workshop on Combining Physic...

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ACM international Joint conference on Pervasive and Ubiquitous computing (UbiComp) / ACM international Symposium on Wearable Computers (ISWC)

作者： Chen, Xinlei Pan, Shijia Amini, M. Hadi Carnegie Mellon Univ Pittsburgh PA 15213 USA Univ Calif Merced Merced CA USA Florida Int Univ Miami FL 33199 USA

ISBN: (纸本)9781450380768

In the real-world ubiquitous computing systems. it is difficult to require a significant amount of data to obtain accurate information through pure data-driven methods. The performance of data-driven methods relies on the quantity and 'quality' of data. They perform well when a sufficient amount of data is available, which is regarded as ideal conditions. However, in real-world systems. collecting data can be costly or impossible due to practical limitations. On the other hand, it is promising to utilize physical knowledge to alleviate these issues of data limitation. The physical knowledge includes domain knowledge from experts, heuristics from experiences, analytic models of the physical phenomena and etc. The goal of the workshop is to explore the intersection between (and the combination of) data and physical knowledge. The workshop aims to bring together domain experts that explore the physical understanding of the data, practitioners that develop systems.and the researchers in traditional data-driven domains. The workshop welcomes papers, which focuses on addressing these issues in different applications/domains as well as algorithmic and systematic approaches to applying physical knowledge. Therefore, we further seek to develop a community that systematically analyzes the data quality regarding inference and evaluates the improvements from physical knowledge. Preliminary and on-going work is welcomed.

关键词： ubiquitous computing data-driven physical knowledge cyber-physical system

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3rd international conference on Machine Learning for Cyber Security, ML4CS 2020

3rd International Conference on Machine Learning for Cyber S...

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3rd international conference on Machine Learning for Cyber Security, ML4CS 2020

ISBN: (纸本)9783030624590

The proceedings contain 158 papers. The special focus in this conference is on Machine Learning for Cyber Security. The topics include: Classification of Malware Variant Based on Ensemble Learning;Detection of Malicious Domains in APT via Mining Massive DNS Logs;Spatio-Temporal Graph Convolutional Networks for DDoS Attack Detecting;cerebral Microbleeds Detection Based on 3D Convolutional Neural Network;Liver Tumor Segmentation of CT Image by Using Deep Fully Convolutional Network;Machine Learning Based SDN-enabled distributed Denial-of-Services Attacks Detection and Mitigation System for Internet of Things;A New Lightweight CRNN Model for Keyword Spotting with Edge computing Devices;machine Learning Agricultural Application Based on the Secure Edge computing Platform;qoS Investigation for Power Network with distributed Control Services;AndrOpGAN: An Opcode GAN for Android Malware Obfuscations;fog Server Placement for Multimodality Data Fusion in Neuroimaging;event-Triggered Control for distributed Optimal in Multi-agent systems.with External Disturbance;Towards Privacy-Preserving Aggregated Prediction from SPDZ;a Secure Neural Network Prediction Model with Multiple Data Providers;GAN-Based Image Privacy Preservation: Balancing Privacy and Utility;A Novel Color Image Encryption Scheme Based on Controlled Alternate Quantum Walks and DNA Sequence Operations;cloud-Assisted Privacy Protection for Data Retrieval Against Keyword Guessing Attacks;deep Learning Algorithms Design and Implementation Based on Differential Privacy;building Undetectable Covert Channels Over Mobile Networks with Machine Learning;an Improved Privacy-Preserving Stochastic Gradient Descent Algorithm;an Anomalous Traffic Detection Approach for the Private Network Based on Self-learning Model;recommender systems.with Condensed Local Differential Privacy;exploiting Bluetooth to Enquire Close Contacts Without Privacy Leakage.

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3rd international conference on Machine Learning for Cyber Security, ML4CS 2020

3rd International Conference on Machine Learning for Cyber S...

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3rd international conference on Machine Learning for Cyber Security, ML4CS 2020

ISBN: (纸本)9783030624620

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3rd international conference on Machine Learning for Cyber Security, ML4CS 2020

3rd International Conference on Machine Learning for Cyber S...

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3rd international conference on Machine Learning for Cyber Security, ML4CS 2020

ISBN: (纸本)9783030622220

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