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Accuracy enhancement during suspicious object detection using machine learning in IoT environment

AIP Conference Proceedings 2023年第1期2587卷

作者： Rituraj Jain Amit Kumar Kaushik Amogh Shukla Ranjeesh R. Chandran Sushma Jaiswal Ankur Gupta Dept. of Electrical and Computer Engineering Wollega University Nekemte Ethiopia Dept. of Electrical Engineering Vaish College of Engineering Rohtak Haryana India Vellore Institute of Technology Vellore Tamil Nadu India Dept. of Robotics and Automation AdiShankara Institute of Engineering & Technology Kalady Kerala India Dept. of Computer Science & Information Technology Guru GhasidasVishwavidyalaya Bilaspur Chhattisgarh India Dept. of Computer Science and Engineering Vaish College of Engineering Rohtak Haryana India

The term “Internet of Things” refers to gadgets that are primarily focused on communication and computing. IoT refers to the interconnection of physical things. Vehicles, structures, and electronics are examples of these things. It may also take into account the network that allows devices to communicate with one another. To collect the signal, researchers used an IoT model. On the other hand, prediction and detection were done using a trained neural network. Before performing a training operation, image processing allows for the capture and preparation of graphical information. On the basis of a trained neural network, the proposed work has an integrated IoT model to capture the signal (Fire, Humans, Vehicles, etc.) and forecast and detect it. This work enables prediction to be shown on a web page linked to a web interface. Previous studies have limitations in terms of time consumption and accuracy. It was discovered that a lot more work needed to be done on the performance and accuracy factors in order to make the IoT system more dependable. Furthermore, prior studies only provided restricted solutions. As a result, work that is capable of delivering excellent solutions is still required. By combining image processing and neural networks in an IoT system, the suggested study provides the optimum answer. The usage of neural networks has made the system smarter, while image processing has improved the system’s performance. The usage of IoT, on the other hand, has made the system scalable and adaptable. The neural network’s prediction and detection, with the help of image processing, may be shown on a distant site through a web interface. The suggested study is designed to offer a scalable, adaptable, and effective solution for detecting suspicious behaviours in organizations, such as the existence of a fire, an unauthentic vehicle or person, and so on. The suggested work is designed to make the most of limited resources while also performing operations more precisel

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Contrastive learning for context-aware neural machine translation using coreference information

arXiv

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arXiv 2021年

作者： Hwang, Yongkeun Yun, Hyungu Jung, Kyomin Dept. of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of Automation and Systems Research Institute Seoul National University Seoul Korea Republic of

Context-aware neural machine translation (NMT) incorporates contextual information of surrounding texts, that can improve the translation quality of document-level machine translation. Many existing works on context-aware NMT have focused on developing new model architectures for incorporating additional contexts and have shown some promising results. However, most existing works rely on cross-entropy loss, resulting in limited use of contextual information. In this paper, we propose CorefCL, a novel data augmentation and contrastive learning scheme based on coreference between the source and contextual sentences. By corrupting automatically detected coreference mentions in the contextual sentence, CorefCL can train the model to be sensitive to coreference inconsistency. We experimented with our method on common context-aware NMT models and two document-level translation tasks. In the experiments, our method consistently improved BLEU of compared models on English-German and English-Korean tasks. We also show that our method significantly improves coreference resolution in the English-German contrastive test suite. Copyright © 2021, The Authors. All rights reserved.

关键词： Neural machine translation

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Sneak attack against mobile robotic networks under formation control

arXiv

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arXiv 2021年

作者： Liy, Yushan Hey, Jianping Dingy, Xuda Caiz, Lin Guany, Xinping Dept. of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Dept. of Electrical and Computer Engineering University of Victoria VictoriaBC Canada

The security of mobile robotic networks (MRNs) has been an active research topic in recent years. This paper demonstrates that the observable interaction process of MRNs under formation control will present increasingly severe threats. Specifically, we find that an external attack robot, who has only partial observation over MRNs while not knowing the system dynamics or access, can learn the interaction rules from observations and utilize them to replace a target robot, destroying the cooperation performance of MRNs. We call this novel attack as sneak, which endows the attacker with the intelligence of learning knowledge and is hard to be tackled by traditional defense techniques. The key insight is to separately reveal the internal interaction structure within robots and the external interaction mechanism with the environment, from the coupled state evolution influenced by the model-unknown rules and unobservable part of the MRN. To address this issue, we first provide general interaction process modeling and prove the learnability of the interaction rules. Then, with the learned rules, we design an Evaluate-Cut-Restore (ECR) attack strategy considering the partial interaction structure and geometric pattern. We also establish the sufficient conditions for a successful sneak with maximum control impacts over the MRN. Extensive simulations illustrate the feasibility and effectiveness of the proposed attack. Copyright © 2021, The Authors. All rights reserved.

关键词： Robotics

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An automated biometric identification system using CNN-based palm vein recognition

An automated biometric identification system using CNN-based...

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2020 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2020

作者： Jhong, Sin-Ye Tseng, Po-Yen Siriphockpirom, Natnuntnita Hsia, Chih-Hsien Huang, Ming-Shih Hua, Kai-Lung Chen, Yung-Yao National Cheng Kung University Dept. of Engineering Science Tainan Taiwan Grad. Inst. of Automation Technology National Taipei University of Technology Taipei Taiwan Dept. of Computer Science and Information Engineering National Ilan University Ilan Taiwan Open AI Fab Inc. Taipei Taiwan Dept. of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Dept. of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei Taiwan

ISBN: (纸本)9781728198231

Recently, automated biometric identification system (ABIS) has wide applications involving automatic identification and data capture (AIDC), which includes automatic security checking, verifying personal identity to prevent information disclosure or identity fraud, and so on. With the advancement of biotechnology, identification systems based on biometrics have emerged in the market. These systems require high accuracy and ease of use. Palm vein identification is a type of biometric that identifies palm vein features. Compared with other features, palm vein recognition provides accurate results and has received considerable attention. We developed a novel high-performance and noncontact palm vein recognition system by using high-performance adaptive background filtering to obtain palm vein images of the region of interest. We then used a modified convolutional neural network to determine the best recognition model through training and testing. Finally, the developed system was implemented on the low-level embedded Raspberry Pi platform with cloud computing technology. The results showed that the system can achieve an accuracy of 96.54%. © 2020 IEEE.

关键词： Biometrics

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Microwave Oscillator on Transistor Structures with Dielectric Resonators

Microwave Oscillator on Transistor Structures with Dielectri...

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2020 IEEE Ukrainian Microwave Week, UkrMW 2020

作者： Osadchuk, Iaroslav Osadchuk, Oleksandr Osadchuk, Vladimir Semenov, Andriy Semenova, Olena Koval, Kostyantyn Vinnytsia National Technical University Dept. of Radio-Frequency Engineering Vinnytsia Ukraine Vinnytsia National Technical University Dept. of Telecommunication Systems and Tv Broadcasting Vinnytsia Ukraine Vinnytsia National Technical University Faculty for Computer Systems and Automation Vinnytsia Ukraine

ISBN: (纸本)9781728173139

For the microwave oscillator with cylindrical dielectric resonator based on transistor structures two versions of electric circuit and construction were developed and researched. The oscillator operates according to compensation of active losses in a dielectric cylindrical resonator by the negative differential resistance of transistor structures. Experimental studies have shown that both versions of the microwave oscillator generate oscillations with the frequency of 10.25 GHz and amplitudes of 700..750 mV and 280..300 mV, respectively. The frequency and phase noise levels are -50 dB, -45 dB, and -39 dB when adjusted from the generation frequency to 120 kHz, 150 kHz, and 180 kHz, respectively. The long-term relative frequency instability is 2.2•10-6 1/°C. © 2020 IEEE.

关键词： Microwave oscillators

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ROBOSTEAMSEN Project - Training SEN Teachers to Use Robotics for Fostering STEAM and Develop Computational Thinking*

ROBOSTEAMSEN Project - Training SEN Teachers to Use Robotics...

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International Symposium on computers in Education (SIIE)

作者： Miguel Á. Conde Francisco J. Rodríguez-Sedano Francisco J. García-Peñalvo Jose Gonçalves Ilkka Jormanainen Andrea Anzanello Jonny Filipe Ribeiro Alves Raquel Fernández Hernáandez Alina- Andreia Ailincai Dept. of Mechanics Computer Science and Aerospace Engineering Universidad de Leon Leon Spain Dept. Electrical Systems and Automation Engineering Universidad de Leon Leon Spain Dpto. de Informatica y Autormatica - IUCE Universidad de Salamanca Salamanca Espana Research Centre in Digitalization and Intelligent Robotics (CeDRI) Instituto Politecnico de Braganca Braganca Portugal School of Computing University of Eastern Finland Joensuu Finland Dept of Project Management Pixel Florence Italy Colegio Internato Dos Carvalhos Carvalhos Portugal Colegio de Educacion Especial Ntra. Sra. del Sagrado Corazon de Leon Leon Spain EuroEd Primary School Lasi Romania

ISBN: (数字)9798350376616

ISBN: (纸本)9798350376623

Our contemporary society necessitates professionals equipped with 21st-century skills. Disciplines within Science, Technology, engineering, Arts, and Mathematics (known as STEAM) have been particularly effective in fostering these skills. However, when considering students with disabilities, especially those with intellectual or developmental disabilities (IDD), this assertion often falls short. In this context, the RoboSTEAMSEN project emerges as an initiative designed to enhance educational processes by providing teachers of IDD students with the necessary resources to promote STEAM engagement. The project proposes the use of active learning methodologies and robotics to achieve this goal. The primary objective of the project is realized through several strategies: understanding the needs of students with disabilities and adapting the use of robotics and active learning methodologies accordingly; training teachers in the use of these resources; and creating a platform to exchange experiences, resources, lessons learned, tools, case scenarios, etc., while reaching other potential stakeholders such as caregivers and policymakers. The main outcomes of the project are teacher training programs and the development of associated competencies, tools to identify and classify resources for the students, and technological platforms to ensure the sustain ability of the project once it concludes.

关键词： Training computers Ecosystems Collaboration Fasteners People with disabilities Mathematics

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A Paper Recommendation System Based on User Interest and Citations 1

A Paper Recommendation System Based on User Interest and Cit...

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1st International Informatics and Software engineering Conference, IISEC 2019

作者： Bulut, Betul Kaya, Buket Kaya, Mehmet Firat University Dept. of Computer Engineering Elaziǧ Turkey Firat University Dept. of Electronics and Automation Elaziǧ Turkey

ISBN: (纸本)9781728139920

It is difficult for researchers to access useful scientific articles from an excessive number of articles. This difficulty has led to article recommendation systems. Many studies have been conducted on the article recommendation. Article recommendation studies in the literature generally do not take into account the interest of users. The innovation of this study is to propose research articles by using bibliography and creating a user profile. The proposed approach aims to personalize scientific recommendations based on article-bibliographic relationships and user profile. In our study, candidate recommendation articles were clustered by K-Means clustering method according to their bibliographies. In our study, K-NN algorithm is used to determine which cluster is closer to the user's profile. Once the cluster to which the user belongs is determined, other articles in the cluster are recommended to the user. Experimental results show that the method is successful. © 2019 IEEE.

关键词： Bibliographies

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Live Demo: E2P–Events to Polarization Reconstruction from PDAVIS Events

Live Demo: E2P–Events to Polarization Reconstruction from P...

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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Tobi Delbruck Zuowen Wang Haiyang Mei Germain Haessig Damien Joubert Justin Haque Yingkai Chen Moritz B. Milde Viktor Gruev Sensors Group Institute of Neuroinformatics Univ. of Zurich and ETH Zurich Switzerland AIT Austrian Institute of Technology Center for Vision Automation & Control High-Performance Vision Systems Vienna Austria Intl. Centre for Neuromorphic Systems The MARCS Institute Western Sydney University Sydney Australia Dept. of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana IL USA

This demonstration shows live operation of of PDAVIS polarization event camera reconstruction by the E2P DNN reported in the main CVPR conference paper Deep Polarization Reconstruction with PDAVIS Events (paper 9149 [...

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Point-of-Interest Recommendation in Location-Based Social Networks 1

Point-of-Interest Recommendation in Location-Based Social Ne...

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1st International Informatics and Software engineering Conference, IISEC 2019

作者： Cakmak, Elifgul Kaya, Buket Kaya, Mehmet Firat University Dept. of Computer Engineering Elaziǧ Turkey Firat University Dept. of Electronics and Automation Elaziǧ Turkey

ISBN: (纸本)9781728139920

This article investigates the problem of proposing new locations to users who have previously been informed about location-based social networks. In the study, user profiles (past location information), the popularity of the place and the time of preference of the place were obtained. Using this information, a different place is offered to the users. However, when users have a different location (a different city or country), it is provided to recommend one of the point of interests designated by categories according to the pre-made check-in details. Social media has been a component of daily life of users. Applications such as Foursquare/Swarm constitute the data source of the communication that geographically contains location data. This study analyzes the personal behaviors of the users using social networks for the spaces and reveals the characteristics of the spaces and people by past notification activities through the applications made in the past. The experiments on real foursquare data showed the usability of the proposed method and achieved results with high accuracy. © 2019 IEEE.

关键词： Location

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A novel DMP formulation for global and frame independent spatial scaling in the task space

A novel DMP formulation for global and frame independent spa...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Leonidas Koutras Zoe Doulgeri Automation & Robotics Lab Dept. of Electrical & Computer Engineering Aristotle University of Thessaloniki Greece

ISBN: (数字)9781728160757

ISBN: (纸本)9781728160764

In this work we study the DMP spatial scaling in the Cartesian space. The DMP framework is claimed to have the ability to generalize learnt trajectories to new initial and goal positions, maintaining the desired kinematic pattern. However we show that the existing formulations present problems in trajectory spatial scaling when used in the Cartesian space for a wide variety of tasks and examine their cause. We then propose a novel formulation alleviating these problems. Trajectory generalization analysis, is performed by deriving the trajectory tracking dynamics. The proposed formulation is compared with the existing ones through simulations and experiments on a KUKA LWR 4+ robot.

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