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IEEE International Conference on robotics and Automation (ICRA)

作者： Rohan Chandra Xijun Wang Mridul Mahajan Rahul Kala Rishitha Palugulla Chandrababu Naidu Alok Jain Dinesh Manocha Department of Computer Science University of Maryland College Park USA Centre for Intelligent Robotics Indian Institute of Information Technology Allahabad India NavAjna Technologies Pvt. Ltd. Department of Electrical and Computer Engineering University of Maryland College Park USA

We present a new traffic dataset, Meteor, which captures traffic patterns and multi-agent driving behaviors in unstructured scenarios. Meteor consists of more than 1000 one-minute videos, over 2 million annotated frames with bounding boxes and GPS trajectories for 16 unique agent categories, and more than 13 million bounding boxes for traffic agents. Meteor is a dataset for rare and interesting, multi-agent driving behaviors that are grouped into traffic violations, atypical interactions, and diverse scenarios. Every video in Meteor is tagged using a diverse range of factors corresponding to weather, time of the day, road conditions, and traffic density. We use Meteor to benchmark perception methods for object detection and multi-agent behavior prediction. Our key finding is that state-of-the-art models for object detection and behavior prediction, which otherwise succeed on existing datasets such as Waymo, fail on the Meteor dataset. Meteor is a step towards developing more sophisticated perception models for dense, heterogeneous, and unstructured scenarios.

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Smart Fibers for Energy Transformation and Storing

Smart Fibers for Energy Transformation and Storing

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2023 Advances in Science and engineering Technology International Conferences, ASET 2023

作者： Al Jaghoub, Haya Rami Almallahi, Maryam Nooman Obaideen, Khaled Moustafa, Asmaa Al Nassan, Wafaa Ramadan, Omar H. Bonny, Talal University of Sharjah Industrial Engineering and Engineering Management Sharjah United Arab Emirates United Arab Emirates University Department of Mechanical and Aerospace Engineering Al Ain United Arab Emirates Rise University of Sharjah Sustainable Energy & Power Systems Research Centre Sharjah United Arab Emirates Ahram Canadian University Faculty of Engineering Giza Egypt University of Sharjah Department of Computer Engineering Sharjah United Arab Emirates University of Sharjah Department of Electrical and Electronic Engineering Sharjah United Arab Emirates

ISBN: (纸本)9781665454742

Fibers have been a crucial element in the development of textiles. This is attributed to the numerous advantages fibers provide, including the production of stronger and long-lasting cloths. Moreover, synthetic fibers are perceived as highly flexible and cost-effective materials. Due to the expansion in portable and wearable devices, the creation of intelligent and versatile fibers has been significantly boosted. Additionally, due to the intrinsic materials of fibers, such as semiconductors and electroactive materials, it is feasible to create fiber electronics. As a result, this paper focuses on fiber electronics and especially the sources of energy supply for these fibers. This paper initially starts to introduce the development of functional fibers in energy conversion and storage, with an emphasis on supercapacitors, solar cells, and nanogenerator batteries. Thereafter, the significance of fiber-shaped energy conversion and smart structural design for storage devices is examined. © 2023 IEEE.

关键词： Supercapacitor

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Unprecedented Smart Algorithm for Uninterrupted SDN Services During DDoS Attack

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computers, Materials & Continua 2022年第1期70卷 875-894页

作者： Muhammad Reazul Haque Saw Chin Tan Zulfadzli Yusoff Kashif Nisar Rizaludin Kaspin Iram Haider Sana Nisar J.P.C.Rodrigues Bhawani Shankar Chowdhry Muhammad AslamUqaili Satya Prasad Majumder Danda B.Rawat Richard Etengu Rajkumar Buyya Faculty of Computing&Informatics Multimedia UniversityPersiaranMultimediaCyberjaya63100SelangorMalaysia Faculty of Engineering Multimedia UniversityPersiaran MultimediaCyberjaya63100SelangorMalaysia Faculty of Computing and Informatics University Malaysia SabahJalan UMSKota Kinabalu Sabah88400Malaysia Telekom Malaysia Research&Development TM Innovation Centre63000CyberjayaSelangorMalaysia Federal University of Piauí(UFPI) TeresinaPIBrazil Instituto de Telecomunica珲es 6201-001Covilh?Portugal National Center of Robotics and Automation-Condition Monitoring Systems Lab MUETJamshoroPakistan Department of Electrical and Electronic Engineering BUETDhaka1205Bangladesh Department of Electrical Engineering and Computer Science Data Science and Cybersecurity CenterHoward UniversityWashingtonDCUSA Cloud Computing and Distributed Systems(CLOUDS)Laboratory School of Computing and Information SystemsThe University of MelbourneMelbourneVIC 3053Australia

In the design and planning of next-generation Internet of Things(IoT),telecommunication,and satellite communication systems,controller placement is crucial in software-defined networking(SDN).The programmability of the SDN controller is sophisticated for the centralized control system of the entire ***,it creates a significant loophole for the manifestation of a distributed denial of service(DDoS)attack ***,recently a Distributed Reflected Denial of Service(DRDoS)attack,an unusual DDoS attack,has been ***,minimal deliberation has given to this forthcoming single point of SDN infrastructure failure ***,recently the high frequencies of DDoS attacks have increased *** this paper,a smart algorithm for planning SDN smart backup controllers under DDoS attack scenarios has *** proposed smart algorithm can recommend single or multiple smart backup controllers in the event of DDoS *** obtained simulated results demonstrate that the validation of the proposed algorithm and the performance analysis achieved 99.99%accuracy in placing the smart backup controller under DDoS attacks within 0.125 to 46508.7 s in SDN.

关键词： SDN smart algorithm RTZLK-DAASCP DDoS attack DRDoS

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QoS Improvement using Federated Learning-based Position Prediction for mobile IoT

QoS Improvement using Federated Learning-based Position Pred...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Saniya Zafar Mohammed S. Alshehri Syed Aziz Shah Jawad Ahmad Adnan Zafar Aizaz Ahmad Khattak Department of Electrical Engineering Institute of Space Technology Islamabad Pakistan Department of Computer Science College of Computer Science and Information Systems Najran University KSA Research Centre for Intelligent Healthcare Coventry University UK Cybersecurity Center Prince Mohammad Bin Fahd University Alkhobar Saudi Arabia School of Computing Engineering and the Built Environment Edinburgh Napier University UK

ISBN: (数字)9798350373011

ISBN: (纸本)9798350373028

The rapid advancement in mobile broadband technology has evolved wireless infrastructure influencing internet-of-things (IoTs). This evolution has made mobile IoTs (mIoTs) as centre of attention due to its potential of providing seamless connectivity to enable intelligent transportation systems with huge data demands of vehicular users. To address the ever-escalating data demands of vehicular mobile users, vehicular edge computing (VEC) and moving small cells (mSCs) play a pivotal role. mSCs together with VEC are capable to provide improved service quality for mIoTs. However, incorporating the mSCs in vehicles for mIoTs presents challenges while assigning the resources in mIoT-mSC network. This is due to the existence of time varying interference among mSCs. This work explores the distributed resource assignment mechanism for RSU assisted mIoT-mSC network formed in vehicular environment. In the proposed work, location prediction of city buses deployed with mSCs is done using federated learning (FL) which is subsequently utilized for efficient assignment of resources in mIoT-mSC network. Numerical results are provided to validate the proposed resource assignment mechanism.

关键词： Wireless communication Urban areas Interference Quality of service Predictive models Prediction algorithms Probabilistic logic Internet of Things Long short term memory Edge computing

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Introduction of hydrogen technologies to mitigate the impact of thermal consumption in a university campus

Introduction of hydrogen technologies to mitigate the impact...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Jorge Bracho Chrysanthos Charalambous Venizelos Efthimiou Dimitrios Lagos Tomasz Samotyjak Magnus Askeland George E. Georghiou Department of Electrical and Computer Engineering PV Technology Laboratory University of Cyprus Nicosia Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus Energy Systems Analytics Group Catalonia Institute for Energy Research (IREC) Barcelona Spain Instytut Energetyki Gdansk Poland Energy Systems SINTEF Energy Research Trondheim Norway

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

It is imperative for energy systems to reduce their environmental footprint in a cost-efficient manner, for which renwable energy sources (RES) and complementary technologies become desirable options to achieve said task. This is particularly the case for systems with different energy sources, as they’d be able to either address one specific type of energy demand and/or allow for the coupling of different energy carriers that would allow for technologies that normally don’t interact to start complementing each other. Therefore, this paper proposes various scenarios for the UCY campus in which hydrogen technologies would allow for the electrification of thermal demand while harnessing the surplus production coming from a solar park, which is modelled through the Integrate optimization tool and validated through DidSILENT PowerFactory. The results showcased a rise of up to 58% in self-sufficiency while the annual energy costs and CO2 emissions were reduced by 45% and 48% respectively.

关键词： Renewable energy sources Energy consumption Costs Hydrogen Fuel cells Production Optimization Carbon emissions Investment Resistance heating

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Real-time Efficacy of Features Extraction using Machine Learning and Deep Learning for Frontal Alpha Asymmetry. 5

Real-time Efficacy of Features Extraction using Machine Lear...

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5th IEEE International Symposium in robotics and Manufacturing Automation, ROMA 2022

作者： Hafeez, Yasir Ali, Syed Saad Azhar Amin, Hafeez Ullah Naqvi, Syed Faraz Adil, Syed Hasan Boon, Tang Tong University of Nottingham Malaysia School of Computer Science Faculty of Science and Engineering Semenyih43500 Malaysia Universiti Teknologi Petronas Centre for Intelligent Signal and Imaging Research Electrical and Electronics Engineering Department Perak Seri Iskandar32610 Malaysia University of Nottingham Malaysia Faculty of Science and Engineering School of Computer Science Semenyih43500 Malaysia Iqra University Software Engineering Department Karachi Pakistan

ISBN: (数字)9781665459327

ISBN: (纸本)9781665459327

The frontal alpha asymmetry represents as the neuromarker for stress. Stress is the psycho-physiological state of brain in response to some event or a demand. The continuous monitoring of mental stress is necessary to avoid chronic health issues. The real-time monitoring of frontal alpha asymmetry is necessary in daily life and to help in the therapy for example neurofeedback. In this paper, different approaches of machine learning and deep learning were adopted to extract the frontal alpha asymmetry features. The results analysis was based on the efficacy and the comparison of techniques for feature extraction has also been presented. © 2022 IEEE.

关键词： Feature extraction

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Towards a Theoretical Framework of Autonomous systems Underpinned by Intelligence and systems Sciences

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IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 52-63页

作者： Yingxu Wang Ming Hou Konstantinos NPlataniotis Sam Kwong Henry Leung Edward Tunstel Imre JRudas Ljiljana Trajkovic International Institute of Cognitive Informatics and Cognitive Computing Department of Electrical and Computer EngineeringSchulich School of Engineering and Hotchkiss Brain InstituteUniversity of CalgaryCalgary T2N 1N4Canada Toronto Research Centre Defence Research&Development CanadaToronto M3K 2C9Canada Department of Electrical&Computer Engineering University of TorontoToronto M5S3G4Canada Department of Computer Science City University of Hong KongHong KongChina Department of Electrical and Computer Engineering Schulich School of EngineeringUniversity of CalgaryCalgary T2N 1N4Canada Autonomous&Intelligent Systems Department United Technologies Research CenterCT 06108 USA University Research&Innovation Center(EKIK) Óbuda UniversityBudapest H-1034Hungary School of Engineering Science Simon Fraser UniversityBurnaby V5A 1S6Canada

Autonomous systems are an emerging AI technology functioning without human intervention underpinned by the latest advances in intelligence,cognition,computer,and systems *** paper explores the intelligent and mathematical foundations of autonomous *** focuses on structural and behavioral properties that constitute the intelligent power of autonomous *** explains how system intelligence aggregates from reflexive,imperative,adaptive intelligence to autonomous and cognitive intelligence.A hierarchical intelligence model(HIM)is introduced to elaborate the evolution of human and system intelligence as an inductive *** properties of system autonomy are formally analyzed towards a wide range of applications in computational intelligence and systems *** paradigms of autonomous systems including brain-inspired systems,cognitive robots,and autonomous knowledge learning systems are *** in autonomous systems will pave a way towards highly intelligent machines for augmenting human capabilities.

关键词： Autonomous systems(AS) cognitive systems computational intelligence engineering paradigms intelligence science intelligent mathematics

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Modelling the Dependence of Chlorophyll Leaf-Clip Measures on Vegetation Indices Derived from Multispectral UAS Images in Vineyards Parcels

Modelling the Dependence of Chlorophyll Leaf-Clip Measures o...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Gil Gonçalves Umberto Andriolo Lúcio Paiva Cristiano Premebida António Ferraz Department of Mathematics University of Coimbra Coimbra Portugal Department of Electrical and Computer Engineering INESC Coimbra Coimbra Portugal Research Centre for Natural Resources Environment and Society Polytechnic Institute of Coimbra Coimbra Agrarian Technical School Coimbra Portugal Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal NASA Jet Propulsion Laboratory Pasadena United States

Multispectral images and leaf-clip measurements were used for evaluating the Chlorophyll (Chl) content on grapevine leaves through the use of vegetation indices. The multispectral leaf images were taken by a sensor onboard an UAS, which was placed over a table at a height of 70 cm. Images were radiometrically and geometrically processed to obtain accurate coregistered five band image stacks. Using a Kmeans segmentation, each leaf imaged in a multispectral image was automatically detected and the mean leaf reflectance values were used to compute three vegetation indices: NDVI, NDRE, and GLI. When compared to leaf-clip measurements, the results indicated that the NDRE index was the best predictor of Chl leaf content (R2=0.81). The obtained NDRE regression model can be used in UAS-based multispectral orthomosaics to generate canopy Chl maps at vine-row scale, which can assist vine growers in monitoring the spatial and temporal variability of grapevine vigor.

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Cooperative RIS and STAR-RIS assisted mMIMO Communication: Analysis and Optimization

arXiv

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arXiv 2023年

作者： Papazafeiropoulos, Anastasios Elbir, Ahmet M. Kourtessis, Pandelis Krikidis, Ioannis Chatzinotas, Symeon The Communications and Intelligent Systems Research Group University of Hertfordshire HatfieldAL10 9AB United Kingdom Interdisciplinary Centre for Security Reliability Luxembourg The University of Luxembourg Luxembourg The IRIDA Research Centre for Communication Technologies Department of Electrical and Computer Engineering University of Cyprus Cyprus

Reconfigurable intelligent surface (RIS) has emerged as a cost-effective and promising solution to extend the wireless signal coverage and improve the performance via passive signal reflection. Different from existing works which do not account for the cooperation between RISs or do not provide full space coverage, we propose the marriage of cooperative double-RIS with simultaneously transmitting and reflecting RIS (STAR-RIS) technologies denoted as RIS/STAR-RIS under correlated Rayleigh fading conditions to assist the communication in a massive multiple-input multiple-output (mMIMO) setup. The proposed architecture is superior since it enjoys the benefits of the individual designs. We introduce a channel estimation approach of the cascaded channels with reduced overhead. Also, we obtain the deterministic equivalent (DE) of the downlink achievable sum spectral efficiency (SE) in closed form based on large-scale statistics. Notably, relied on statistical channel state information (CSI), we optimise both surfaces by means of the projected gradient ascent method (PGAM), and obtain the gradients in closed form. The proposed optimization achieves to maximise the sum SE of such a complex system, and has low complexity and low overhead since it can be performed at every several coherence intervals. Numerical results show the benefit of the proposed architecture and verify the analytical framework. In particular, we show that the RIS/STAR-RIS architecture outperforms the conventional double-RIS or its single-RIS counterparts. © 2023, CC BY.

关键词： Spectrum efficiency

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A Multi-stage Precision Landing Method for Autonomous eVTOL Based on Multi-marker Joint Localization

A Multi-stage Precision Landing Method for Autonomous eVTOL ...

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IEEE International Conference on robotics and Biomimetics

作者： Senwei Xiang Minxiang Ye Shiqiang Zhu Jason Gu Anhuan Xie Zehua Men Zhejiang Lab Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Hangzhou China Department of Electrical and Computer Engineering Dalhousie University Halifax NS Canada

ISBN: (纸本)9781665481106

Electric vertical takeoff and landing aircraft (eVTOL) has drawn more and more attention from home and abroad in recent years. It is believed autonomous eVTOL will create a new era of Urban Air Mobility (UAM) and Advanced Air Mobility (AAM). To autonomous eVTOL, precision landing is an extremely critical operation for it directly affects flight safety. In this paper, we analyze the special issues an eVTOL will encounter when it lands in the UAM applications. A multi-stage precision landing method based on multi-marker joint localization is proposed accordingly. Our method contains three key elements: a compatible vertiport with multiple visual markers; an accurate, fast detection and localization algorithm for the vertiport and a multi-stage landing strategy. We implement our method on an eVTOL prototype named ZJ-Copter developed by Zhejiang Lab. A series of real-world experiments have been conducted to validate the effectiveness and accuracy of the proposed method. Experiment results show that our method works well in real-world scenarios for autonomous eVTOL without GPS signal during landing process. The positioning accuracy is less than 0.1m (altitude $< \mathbf{10}\mathbf{m}$ ), while the landing accuracy is less than 0.5m.

关键词： Location awareness Visualization Robot kinematics Helicopters Prototypes Feature extraction Safety

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