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An Indoor Environment Sensing and Localization System via mmWave Phased Array

Journal of Communications and Information Networks 2022年第4期7卷 383-393页

作者： Yifei Sun Jie Li Tong Zhang Rui Wang Xiaohui Peng Xiao Han Haisheng Tan Department of Electronic and Electrical Engineering Southern University of Science and TechnologyShenzhen 518055China Department of Computer Science the University of Hong KongHong Kong 999077China Huawei Technologies Co. Ltd.Shenzhen 518129China LINKE Lab School of Computer Science and Technologythe University of Science and Technology of ChinaHefei 230026China

In this paper,an indoor layout sensing and localization system with testbed in the 60-GHz millimeter wave(mmWave)band,named mmReality,is *** mmReality system consists of one transmitter and one mobile receiver,both with a phased array and a single radio frequency(RF)*** reconstruct the room layout,the pilot signal is delivered from the transmitter to the receiver via different pairs of transmission and receiving beams,so that multipath signals in all directions can be *** spatial smoothing and the two-dimensional multiple signal classification(MUSIC)algorithm are applied to detect the angle-of-departures(AoDs)and angle-of-arrivals(AoAs)of propagation ***,the technique of multi-carrier ranging is adopted to measure the path ***,with the measurements of the receiver in different locations of the room,the receiver and virtual transmitters can be pinpointed to reconstruct the room *** show that the reconstructed room layout can be utilized to localize a mobile device via the AoA spectrum.

关键词： millimeter wave indoor sensing and localization MUSIC algorithm multi-input multi output(MIMO) room layout integrated sensing and communication(ISAC) environment sensing orthogonal frequency division multiplexing(OFDM)

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ENSEMBLE KNOWLEDGE DISTILLATION OF SELF-SUPERVISED SPEECH MODELS

arXiv

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arXiv 2023年

作者： Huang, Kuan-Po Feng, Tzu-Hsun Fu, Yu-Kuan Hsu, Tsu-Yuan Yen, Po-Chieh Tseng, Wei-Cheng Chang, Kai-Wei Lee, Hung-Yi College of Electrical Engineering and Computer Science National Taiwan University Taiwan ASUS Intelligent Cloud Services Singapore

Distilled self-supervised models have shown competitive performance and efficiency in recent years. However, there is a lack of experience in jointly distilling multiple self-supervised speech models. In our work, we performed Ensemble Knowledge Distillation (EKD) on various self-supervised speech models such as HuBERT, RobustHuBERT, and WavLM. We tried two different aggregation techniques, layerwise-average and layerwise-concatenation, to the representations of different teacher models and found that the former was more effective. On top of that, we proposed a multiple prediction head method for student models to predict different layer outputs of multiple teacher models simultaneously. The experimental results show that our method improves the performance of the distilled models on four downstream speech processing tasks, Phoneme Recognition, Speaker Identification, Emotion Recognition, and Automatic Speech Recognition in the hidden-set track of the SUPERB benchmark. © 2023, CC BY-NC-SA.

关键词： Distillation

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Delving into the Reversal Curse: How Far Can Large Language Models Generalize? 38

Delving into the Reversal Curse: How Far Can Large Language ...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Lin, Zhengkai Fu, Zhihang Liu, Kai Xie, Liang Lin, Binbin Wang, Wenxiao Cai, Deng Wu, Yue Ye, Jieping State Key Lab of CAD&CG Zhejiang University China Alibaba Cloud China College of Biomedical Engineering & Instrument Science Zhejiang University China College of Computer Science and Technology Zhejiang University of Technology China School of Software Technology Zhejiang University China Fullong Inc. China

While large language models (LLMs) showcase unprecedented capabilities, they also exhibit certain inherent limitations when facing seemingly trivial tasks. A prime example is the recently debated "reversal curse", which surfaces when models, having been trained on the fact "A is B", struggle to generalize this knowledge to infer that "B is A". In this paper, we examine the manifestation of the reversal curse across various tasks and delve into both the generalization abilities and the problem-solving mechanisms of LLMs. This investigation leads to a series of significant insights: (1) LLMs are able to generalize to "B is A" when both A and B are presented in the context as in the case of a multiple-choice question. (2) This generalization ability is highly correlated to the structure of the fact "A is B" in the training documents. For example, this generalization only applies to biographies structured in "[Name] is [Description]" but not to "[Description] is [Name]". (3) We propose and verify the hypothesis that LLMs possess an inherent bias in fact recalling during knowledge application, which explains and underscores the importance of the document structure to successful learning. (4) The negative impact of this bias on the downstream performance of LLMs can hardly be mitigated through training alone. These findings offer a novel perspective on interpreting LLMs' generalization through their intrinsic mechanisms and provide insights for developing more effective learning methods. © 2024 Neural information processing systems foundation. All rights reserved.

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Parasitic Parameters Effect on the Operation of High Frequency Electric Drive System

Parasitic Parameters Effect on the Operation of High Frequen...

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2024 International Conference on electrical Machines, ICEM 2024

作者： Abdo, Fawzy A. Tawfiq, Kotb B. Sergeant, Peter Systems and Metal Engineering Ghent University Department of Electromechanical Ghent9000 Belgium Flanders Make@UGent Core Lab MIRO Leuven3001 Belgium Menoufia University Department of Electrical Engineering Menoufia32511 Egypt Khalifa University Department of Electrical Engineering and Computer Science Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350370607

The rapid switching of semiconductor power modules in electric drive systems generates high frequency (HF) common mode voltage at the motor terminals which causes bearing failure and winding degradation. Therefore, accurate characterization of the inverter and motor parameters - including parasitic effects - is vitally important to understand the high frequency performance as well as to model and mitigate the switching oscillations of the electric drive system. In this paper, the high frequency operation of the inverter in the electric drive system, as well as the direct effect of the parasitic components on the complete system are thoroughly investigated. Moreover, a detailed extraction process of the high frequency parasitic parameters is introduced. An equivalent circuit model of the complete drive system based on the impedance characteristics is introduced. Additionally, a HF model of a 750W three-phase induction motor is developed with parameter values determined from measurements on this motor. © 2024 IEEE.

关键词： Terminals (electric)

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Guest Editorial: Ubiquitous Intelligence for Internet of Vehicles

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IEEE Internet of Things Magazine 2023年第3期6卷 52-54页

作者： Peng, Haixia Cheng, Nan Ye, Qiang Fang, He Yan, Shen Choo, Kim-Kwang Raymond Duong, Trung Q. California State University Long Beach Department of Computer Engineering and Computer Science Long BeachCA United States School of Telecommunications Engineering Xidian University State Key Lab. of ISN Shaanxi China Memorial University of Newfoundland Department of Computer Science NL Canada Soochow University China Intelligent Automotive Solution BU Huawei Technologies Co. Ltd Policy Standard & Patent Dept. China The University of Texas at San Antonio Cloud Technology Endowed United States Royal Academy of Engineering Queen's University Belfast United Kingdom

As one of the prominent networking paradigms in the realm of the Internet of Things (IoT), the Internet of Vehicles (IoV) facilitates seamless information dissemination and task processing among vehicles equipped with onboard sensing, communication, computing, and storage capabilities. With the advancements in artificial intelligence (AI) techniques, there is a vision to achieve pervasive intelligence within the IoV ecosystem. Various network entities, including connected vehicles, wireless base stations, edge/cloud servers, and aerial/space-assisted devices (such as drones and satellites), are expected to interact efficiently to perceive, reason, and make intelligent decisions based on contextual awareness. These advancements aim to enhance networking and computing effectiveness. The realization of an intelligent, safe, and ubiquitous IoV heavily relies on highly responsive task computing, adaptive networking, and efficient resource control to meet the increasingly diverse requirements of vehicular applications.

关键词： Special issues and sections Internet of Vehicles Intelligent systems Ubiquitous computing

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Improving DeepFake Video Detection Performance with a Noval Deep Learning Approach 3

Improving DeepFake Video Detection Performance with a Noval ...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： Fouda, Mona A. El-Shafai, Walid El-Rabaie, El-Sayed M. Menoufia University Faculty of Electronic Engineering Department of Electronics and Electrical Communications Engineering Menouf32952 Egypt Prince Sultan University Security Engineering Lab Computer Science Department Riyadh11586 Saudi Arabia

ISBN: (纸本)9798350323511

With the rise in both the quantity and sophistication of deepfake videos, the need for robust detection systems to identify potentially misleading content on social media and the internet has become paramount. However, current automated face forgery detection systems still face limitations, often demonstrating bias towards the training dataset. This research paper addresses this issue by proposing a novel approach for detecting deepfake media. We introduce a custom Visual Geometry Group (VGG16) deepfake detection method that leverages convolutional neural network architectures. To evaluate the effectiveness of our approach, we utilize the deepfake detection challenge (DFDC) dataset on Kaggle to build network models and compare the performance of our custom VGG16 method against the standard VGG16. Additionally, we investigate the impact of data augmentation techniques on the performance of Convolutional Neural Network (CNN)-based deepfake detectors, examining their effect on both VGG16 and our custom VGG16 approach using the DFDC dataset. Our results demonstrate a high level of accuracy, with precision, recall, and f1-score values of 0.983, 0.975, and 0.979, respectively, and an overall accuracy of 0.986 for deepfake detection. This study presents a promising approach to enhance the accuracy of deepfake video detection, representing a crucial step towards mitigating the potential negative impacts of deepfake technology. © 2023 IEEE.

关键词： Convolutional neural networks

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Heterogeneous GNN-RL-Based Task Offloading for UAV-Aided Smart Agriculture

IEEE Networking Letters

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IEEE Networking Letters 2023年第4期5卷 213-217页

作者： Pamuklu, Turgay Syed, Aisha Kennedy, W. Sean Erol-Kantarci, Melike University of Ottawa School of Electrical Engineering and Computer Science OttawaK1N 6N5 Canada Nokia Bell Labs AI Research Lab Murray HillNJ07974 United States

Having unmanned aerial vehicles (UAVs) with edge computing capability hover over smart farmlands supports Internet of Things (IoT) devices with low processing capacity and power to accomplish their deadline-sensitive tasks efficiently and economically. In this letter, we propose a graph neural network-based reinforcement learning solution to optimize the task offloading from these IoT devices to the UAVs. We conduct evaluations to show that our approach reduces task deadline violations while also increasing the mission time of the UAVs by optimizing their battery usage. Moreover, the proposed solution has increased robustness to network topology changes and is able to adapt to extreme cases, such as the failure of a UAV. © 2019 IEEE.

关键词： Reinforcement learning

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Design and Development of Novel Routing Protocols for Ubiquitous Network 7

Design and Development of Novel Routing Protocols for Ubiqui...

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7th IEEE International conference for Convergence in Technology, I2CT 2022

作者： Chavan, Chandrashekhar Pomu Talabattula, Srinivas Pes University Department of Computer Science and Engineering Bangalore India Electrical Communication Engineering Indian Institute of Science Applied Photonics Lab Bangalore India

ISBN: (纸本)9781665421683

In this paper, we designed and developed ECA (Event Condition Action) scheme based novel Improved AODV Position and Speed Aware Routing (ECA-IAODV-PSAR) and Improved AODV Edge Connectivity (ECA-IAODV-EC) routing protocols. In specific, these two routing protocols use the speed and position information of the node received from the Global Positioning System (GPS) to deal with routing control packet overhead during inflated mobility. The primary routing protocol ECA-IAODV-PSAR is an alteration of the PSAR routing protocol. The ECA-IAODV-PSAR protocol set limits flooding of the route query packet to the tiny zone of the ubiquitous network to select the optimal route towards the ultimate destination. The results produced in the simulation demonstrate the feasibility of the scheme proposed. © 2022 IEEE.

关键词： Routing protocols

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Acute lymphoblastic leukemia Classification Based on Convolutional Neural Network 6

Acute lymphoblastic leukemia Classification Based on Convolu...

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6th International Conference on Artificial Intelligence and Big Data, ICAIBD 2023

作者： Fan, Qile Qu, Boan Teng, Jingjing Hui, Anqi Toe, Teoh Teik Nanjing University of Post and Telecommunications School of Communication and Information Engineering Nanjing China Beijing University of Chemical Technology School of Electrical and Mechanical Engineering Beijing China Suzhou University of Science and Technology Electrical Engineering and the Automatization Specialty Suzhou China Xidian University of Computer Science and Technology Computer Science AndTechnology Xi'an China Nanyang Technological University NTU Business AI Lab Singapore

ISBN: (纸本)9781665491259

Acute lymphoblastic leukemia (ALL) is a type of blood cancer that affects white blood cells, primarily affecting children. Early diagnosis is crucial for successful treatment and recovery. In recent years, convolutional neural networks (CNNs) have been increasingly used in medical image analysis, including the detection and classification of ALL from medical images. In this paper, we propose a model called QCResNet for the classification of ALL from peripheral blood smear images. Our proposed model achieved a high accuracy of 98.9% on a dataset of 15,135 images, outperforming several state-of-the-art methods. Our results demonstrate the potential of QCResNet for accurate and rapid effective diagnosis of acute lymphocytes. © 2023 IEEE.

关键词： Convolutional neural networks

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Using Self-Sovereign-Identity principles to prove your worth in Decentralized Autonomous Organizations 9

Using Self-Sovereign-Identity principles to prove your worth...

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9th Workshop on Software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2022

作者： Keršič, Vid Vrečko, Andraž Vidovič, Urban Domajnko, Martin Turkanović, Muhamed Faculty of Electrical Engineering and Computer Science University of Maribor Institute of Informatics Blockchain Lab:UM Maribor Slovenia

Decentralized autonomous organizations (DAO) have many use cases and are becoming increasingly more popular in recent years. The paper analyses the disadvantages and problems of current DAOs (i.e., the Plutocracy problem) and presents a solution, in which the existing implementations of DAO are combined with the Self-Sovereign Identity (SSI) ecosystem to solve those issues. The solution is presented in the form of an extension to the crypto wallet MetaMask, using Snaps, which enables DAO users to create SSI-based identifiers (DID) and manage verifiable credentials (VC), which are later on used as a voting ticket in a DAO. We validate the solution by presenting the prototype of the SSI Snap and demonstrating its usage on the Snapshot decentralized voting system. © 2022 Copyright for this paper by its authors.

关键词： DAO decentralized decentralized autonomous organization MetaMask proof of concept self-sovereign identity Snaps SSI Veramo verifiable credential

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