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A Colored Petri Net Tool for the Design of Robotic Palletizing Cells 9

A Colored Petri Net Tool for the Design of Robotic Palletizi...

引用

9th International Conference on Control, Decision and Information Technologies, CoDIT 2023

作者： Cavone, Graziana Stella, Silvia Scarabaggio, Paolo Carli, Raffaele Lisi, Stefano Garavelli, Achille Claudio Dotoli, Mariagrazia University Roma Tre Department of Civil Computer Science and Aeronautical Technologies Engineering Italy Polytechnic of Bari Department of Mechanics Mathematics and Management Italy Polytechnic of Bari Department of Electrical and Information Engineering Italy

ISBN: (纸本)9798350311402

Driven by the digital transformation required by Logistics 4.0, the use of automation in warehouses is constantly growing. In particular, robotic palletizers offer significant potential for optimizing warehouse operations, thanks to higher flexibility and throughput than traditional palletizing systems. Despite the availability of several solutions in the market, the optimal deployment of a robotic palletizer in warehouses is not straightforward: a design phase is needed to determine the most convenient configuration that ensures automatic palletizing is fully integrated into the warehouse processes. In this paper, we propose a simulation-based versatile tool for modeling and analysis purposes, aimed at supporting the design of a robotic palletizing cell in a bottom-up fashion. As a core methodology, we employ timed colored Petri nets, which allow - once the analysis on packing requirements and constraints is conducted - to rapidly model the system as a composition of basic subsystems, and implement alternative simulations to evaluate the corresponding performance and effectively benchmark the alternative configurations. The proposed approach is applied to a real case study, showing its effectiveness in identifying the solution that achieves a good compromise between the use of resources and the performance of warehouse operations. © 2023 IEEE.

关键词： Discrete event simulation

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Wireless DC-AC Inverter with Secondary Side SR Duty Cycle Modulation and Unfolding Stage

Wireless DC-AC Inverter with Secondary Side SR Duty Cycle Mo...

引用

2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Hsieh, Hsin-Che Gutierrez, Bryan Baek, Seunghoon Lai, Jih-Sheng Virginia Polytechnic Institute and State University The Bradley Department of Electrical and Computer Engineering BlacksburgVA United States Hanwha Qcells Santa ClaraCA United States

ISBN: (纸本)9798350376067

In a typical wireless power transfer (WPT) system, the high frequency current picked up by the receiving coil is rectified and filtered before delivering it to the load. If the load demands line-frequency ac instead of dc, an additional dc-ac inverter stage is usually required, increasing cost and complexity. Several primary side modulation schemes for WPT systems have been previously proposed to generate ac output without the additional dc-ac stage. However, modulating the WPT output from the primary side makes the system vulnerable to interference and communication delays if closed-loop output regulation is to be implemented. In this paper, a wireless dc-ac inverter based on secondary side modulation is proposed. By modulating the duty cycle of secondary side synchronous rectifier (SR) switch, the output of the WPT secondary side becomes a rectified sine wave that can be readily converted to ac by an unfolding stage. The proposed modulation scheme eliminates the communication requirements, allows primary side to switch at a constant frequency and duty cycle, and avoids the bulky LC filters required for conventional dc-ac inverters. The proposed wireless dc-ac inverter is verified with a 240-V/450-W GaN device based hardware prototype with grid-tie capability. © 2024 IEEE.

关键词： Inductive power transmission

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Performance Comparison of Double- and Single-Rotor Wound-Field Flux Switching Machines with Concentrated and Toroidal Windings

Performance Comparison of Double- and Single-Rotor Wound-Fie...

引用

2024 International Conference on electrical Machines, ICEM 2024

作者： Akuru, Udochukwu B. Wu, Zhongze Ullah, Wasiq Khan, Faisal Khan, Wasiullah Garner, Karen S. Tshwane University of Technology Dept. of Electrical Engineering Pretoria South Africa School of Electrical Engineering Southeast University Nanjing China Kabul Polytechnic University Kabul Afghanistan COMSATS University Islamabad Dept. of Electrical & Computer Eng'g Abbottabad Pakistan Stellenbosch University Dept. of Electrical & Electronic Eng'g Cape Town South Africa

ISBN: (纸本)9798350370607

Wound-field flux switching machines (WFFSMs) have gained attention lately due to their robust construction, brushless operation and high torque density performance comparable to permanent magnet machines. However, conventional WFFSMs suffer from issues such as increased copper losses, low fault tolerance and reduced efficiency. In this study, double-rotor (DR) and single-rotor (SR) configurations of the WFFSM, with concentrated field windings and toroidal armature windings, are presented and their electromagnetic performance evaluated using the finite element analysis (FEA) technique. The no-load characteristics such as airgap flux density, flux linkage, back-EMF and cogging torque, as well as on-load and overload performance, including electromagnetic torque, torque ripple, efficiency and power factor are performed. The results show that the DR machine exhibits higher torque density and efficiency compared to the SR machines. The findings of this study give an indication into the influence of rotor topology and winding configuration on the electromagnetic performance of WFFSMs for high torque density applications. © 2024 IEEE.

关键词： Permanent magnets

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Experimental Studies On Drivers Distractions: Investigating the Effects of Distractions on Driving Performance

Experimental Studies On Drivers Distractions: Investigating ...

引用

2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific, ITEC Asia-Pacific 2023

作者： Mynuddin, Mohammed Sadeeq, Lanre Gbenga Uddin Khan, Sultan Chowdhury, Zayed Uddin Islam, Foredul Hossain, Mohammad Iqbal Jahidul Islam, Md Ghose, Shantu North Carolina A & T State University Dept. of Electrical Engineering United States Georgia Southern University Dept. of Electrical Engineering United States Georgia Southern University Dept. of Computer Engineering United States Florida Polytechnic University Dept. of Computer Engineering United States Tuskegee University Dept. of Electrical Engineering United States

ISBN: (纸本)9798350314274

Driving hazards encompass a range of factors, such as poor road conditions, weather, and human behavior. They represent a significant threat to the safety of individuals on the road and are very likely one of the leading causes of traffic accidents. These hazards exist alongside well-known risk factors like driving under the influence of drugs, extreme fatigue, drowsiness, and excessive speeding. Impaired driving, which includes behaviors such as drunk or drugged driving, has persistently plagued American roads for many years. It poses an ongoing risk, not only to the impaired driver but also to other road users and the surrounding infrastructure. The primary objective of this paper is to investigate specific forms of distractions that drivers encounter. These distractions encompass activities such as texting or using a mobile device, eating, conversing with passengers, and paying attention to advertising signs along the roadside. The research aims to understand how each of these distractions affects a driver's ability to operate a vehicle safely. In essence, this chapter delves into the various ways in which these distractions can compromise a driver's attention and, consequently, impact road safety. © 2023 IEEE.

关键词： Hazards

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BOURNE: Bootstrapped Self-Supervised Learning Framework for Unified Graph Anomaly Detection 40

BOURNE: Bootstrapped Self-Supervised Learning Framework for ...

引用

40th IEEE International Conference on Data engineering, ICDE 2024

作者： Liu, Jie He, Mengting Shang, Xuequn Shi, Jieming Cui, Bin Yin, Hongzhi School of Computer Science Northwestern Polytechnical University Xi'an China The Hong Kong Polytechnic University Department of Computing Hong Kong Hong Kong School of Computer Science Peking University Beijing China School of Electrical Engineering & Computer Science The University of Queensland Brisbane Australia

ISBN: (纸本)9798350317152

Graph anomaly detection (GAD) has gained increasing attention in recent years due to its critical application in a wide range of domains, such as social networks, financial risk management, and traffic analysis. Existing GAD methods can be categorized into node and edge anomaly detection models based on the type of graph objects being detected. However, these methods typically treat node and edge anomalies as separate tasks, overlooking their associations and frequent co-occurrences in real-world graphs. As a result, they fail to leverage the complementary information provided by node and edge anomalies for mutual detection. Additionally, state-of-the-art GAD methods, such as CoLA and SL-GAD, heavily rely on negative pair sampling in contrastive learning, which incurs high computational costs, hindering their scalability to large graphs. To address these limitations, we propose a novel unified graph anomaly detection framework based on bootstrapped self-supervised learning (named BOURNE). We extract a subgraph (graph view) centered on each target node as node context and transform it into a dual hypergraph (hypergraph view) as edge context. These views are encoded using graph and hypergraph neural networks to capture the representations of nodes, edges, and their associated contexts. By swapping the context embeddings between nodes and edges and measuring the agreement in the embedding space, we enable the mutual detection of node and edge anomalies. Furthermore, BOURNE can eliminate the need for negative sampling, thereby enhancing its efficiency in handling large graphs. Extensive experiments conducted on six benchmark datasets demonstrate the superior effectiveness and efficiency of BOURNE in detecting both node and edge anomalies. © 2024 IEEE.

关键词： Anomaly detection

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Exploring the Importance of Security in Mobile Health (mHealth) Data Management 1

Exploring the Importance of Security in Mobile Health (mHeal...

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1st International Conference on Healthcare Innovations, Software and engineering Technologies, HISET 2024

作者： Kulkarni, Mukund Kashinath, Amruta Garagate Momin Irshad, Anjuman Sekhar, G Chandra Patil, P.B. Phatak, Pratiksha Institute of Management Kolhapur India Jaywant College of Engineering and Polytechnic Department of Computer Science Engineering Karad India Jaywant College of Management Karad India Institute of Aeronautical Engineering Department of Computer Science and Engineering Hyderabad India Krishna Vishwa Vidyapeeth Deemed to Be University Department of Anaesthesiology Karad India Jaywant College of Engineering and Polytechnic Department of Electrical Engineering Karad India

ISBN: (纸本)9798350360707

Clinical the healthcare and awareness towards it is now most prominent among the living beings in the world. The mobile health and healthcare are now increasing among the populations over the worlds. Thus, the focus of study is to know the importance of mobile healthcare and its data management, storage and security. The utilization of IoT gadgets and mHealth apps is only two examples of how digital medicine is becoming more and more common in daily medical practice. It has the ability to promote improved patient health outcomes, facilitate care coordination, and increase communication with lower costs. The security to healthcare helps to protect the health-related data from the hackers by providing high security to the devices and the applications. Thus, with time hacking will be getting more intense and will provide more damage so it is necessary to improve the security and data management through mHealth. © 2024 IEEE.

关键词： Electronic health record

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End-to-end Nanophotonic Inverse Design for Computational Imaging

End-to-end Nanophotonic Inverse Design for Computational Ima...

引用

2023 International Applied Computational Electromagnetics Society Symposium, ACES-Monterey 2023

作者： Lin, Zin Virginia Polytechnic Institute and State University Electrical Engineering Arlington Research Cente Bradley Department of Electrical and Computer Engineering 900 N Glebe Road ArlingtonVA22203 United States

We introduce end-to-end inverse design in which a nanophotonics frontend is optimized in conjunction with a computational-imaging backend to minimize reconstruction errors. We present several nanophotonics designs for... 详细信息

ISBN: (纸本)9781733509633

关键词： Nanophotonics

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PrivShape: Extracting Shapes in Time Series under User-Level Local Differential Privacy 40

PrivShape: Extracting Shapes in Time Series under User-Level...

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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Mao, Yulian Ye, Qingqing Hu, Haibo Wang, Qi Huang, Kai Southern University of Science and Technology Department of Computer Science and Engineering China The Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Hong Kong Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology China School of Computer Science and Engineering Macau University of Science and Technology China

ISBN: (纸本)9798350317152

Time series have numerous applications in finance, healthcare, IoT, and smart city. In many of these applications, time series typically contain personal data, so privacy infringement may occur if they are released directly to the public. Recently, local differential privacy (LDP) has emerged as the state-of-the-art approach to protecting data privacy. However, existing works on LDP-based collections cannot preserve the shape of time series. A recent work, PatternLDP, attempts to address this problem, but it can only protect a finite group of elements in a time series due to ?-event level privacy guarantee. In this paper, we propose PrivShape, a trie-based mechanism under user-level LDP to protect all elements. PrivShape first transforms a time series to reduce its length, and then adopts trie-expansion and two-level refinement to improve utility. By extensive experiments on real-world datasets, we demonstrate that PrivShape outperforms PatternLDP when adapted for offline use, and can effectively extract frequent shapes. © 2024 IEEE.

关键词： Time series

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A Comprehensive Analysis of Fetal Electrocardiogram Signals

A Comprehensive Analysis of Fetal Electrocardiogram Signals

引用

IEEE Middle East and North Africa Communications Conference (MENACOMM)

作者： Brandon Camacho Muhammad Sana Ullah Electrical and Computer Engineering Department Florida Polytechnic University Lakeland USA

ISBN: (数字)9798331519957

ISBN: (纸本)9798331519964

This paper reviews different feature extraction and analysis methods for FECG signals. The FECG signals are very critical in monitoring the health of the fetuses; hence, most of the time, they are masked by maternal ECG and noise and introducing significant challenges during the analysis of the same signal. In this paper, several feature-extraction techniques are reviewed and compared. Techniques included, but were not limited to, time-domain, frequency-domain, and time-frequency domain methods such as PCA and ICA. We also review some newer approaches for machine learning, including deep learning methods that could be applied further to enhance the performance of signal separation and classification performance. Then, each method is tested on synthetic and realworld datasets, emphasizing computational efficiency and clinical applicability. By elaborating on the strengths and weaknesses of each approach, this paper summarize the results that give insight into optimum strategies to improve FECG signal processing for better diagnosis regarding fetal health.

关键词： Time-frequency analysis Technological innovation Source separation Reviews Noise Feature extraction Computational efficiency Time-domain analysis Monitoring Principal component analysis

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Analysis of Noise Cancellation Techniques for Enhancing the ECG Signals

Analysis of Noise Cancellation Techniques for Enhancing the ...

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IEEE Southeastcon

作者： Hasnain Ahamad Ziad Muhammad Sana Ullah Electrical and Computer Engineering Florida Polytechnic University Lakeland Florida USA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

Electrocardiogram (ECG) signals are fundamental physiological indicators used extensively in clinical settings. However, their utility can be compromised by various sources of noise and interference. This article presents simplified signal processing techniques aimed at enhancing ECG signals by removing noise effectively. The proposed methods include adaptive sequential filtering, high-pass filtering for baseline wander removal and band-stop filtering for powerline interference mitigation. Through simulations and analysis, our results demonstrate the efficacy of these techniques in significantly improving the quality of ECG signals by attenuating noise while preserving essential signal features.

关键词： Analytical models Adaptation models Filtering Prevention and mitigation Interference Electrocardiography Noise cancellation Physiology Notch filters

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