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Facial Surface Anthropometric Features and Measurements With an Emphasis on Rhinoplasty (vol 42, pg 133, 2022)

AESTHETIC SURGERY JOURNAL 2022年第2期42卷 230-230页

作者： Celikoyar, M. Mazhar Perez, Michael F. Akbas, M. Ilhan Topsakal, Oguzhan Department of Otolaryngology Istanbul Florence Nightingale Hospital Istanbul Turkey Computer Science Department Florida Polytechnic University Lakeland FL USA Electrical Computer Software and Systems Engineering Department Embry-Riddle Aeronautical University Daytona Beach FL USA

Background Facial features and measurements are utilized to analyze patients’ faces for various reasons, including surgical planning, scientific communications, patient-surgeon communications, and post-surgery evaluations. Objectives There are numerous descriptions regarding these features and measurements scattered throughout the literature, and the authors did not encounter a current compilation of these parameters in the medical literature. Methods A narrative literature review of the published medical literature for facial measurements used for facial analysis in rhinoplasty was conducted through the electronic databases MEDLINE/PubMed and Google Scholar, along with a citation search. Results A total of 61 facial features were identified: 45 points (25 bilateral, 20 unilateral), 5 lines (3 bilateral, 2 unilateral), 8 planes, and 3 areas. A total of 122 measurements were identified: 48 distances (6 bilateral, 42 unilateral), 57 angles (13 bilateral, 44 unilateral), and 17 ratios. Supplemental figures were created to depict all features and measurements utilizing a frontal, lateral, or basal view of the face. Conclusions This paper provides the most comprehensive and current compilation of facial measurements to date. The authors believe this compilation will guide further developments (methodologies and software tools) for analyzing nasal structures and assessing the objective outcomes of facial surgeries, in particular rhinoplasty. Moreover, it will improve communication as a reference for facial measurements of facial surface anthropometry, in particular rhinoplasty.

关键词： anthropometry face rhinoplasty software surgical procedures operative nose facial features

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On the chronological understanding of the homogeneous dielectric barrier discharge

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High Voltage 2023年第6期8卷 1132-1150页

作者： Xinpei Lu Zhi Fang Dong Dai Tao Shao Feng Liu Cheng Zhang Dawei Liu Lanlan Nie Chunqi Jiang State Key Laboratory of Advanced Electromagnetic Engineering and Technology School of Electrical and Electronic EngineeringHuazhong University of Science and TechnologyWuhanChina College of Electrical Engineering and Control Science Nanjing Tech TechnologyNanjingChina School of Electric Power South China University of TechnologyGuangzhouChina Institute of Electrical Engineering Chinese Academy of SciencesBeijingChina Frank Reidy Research Center for Bioelectrics Old Dominion UniversityNorfolkVirginiaUSA Department of Electrical and Computer Engineering Old Dominion UniversityNorfolkVirginiaUSA

Dielectric barrier discharges(DBD)are widely utilised non‐equilibrium atmospheric pressure plasmas with a diverse range of applications,such as material processing,surface treatment,light sources,pollution control,and *** the course of several decades,extensive research has been dedicated to the generation of homogeneous DBD(H‐DBD),focussing on understanding the transition from H‐DBD to filamentary DBD and exploring strategies to create and sustain H‐*** paper first discusses the in-fluence of various parameters on DBD,including gas flow,dielectric material,surface conductivity,and mesh ***,a chronological literature review is presented,highlighting the development of H‐DBD and the associated understanding of its un-derlying *** encompasses the generation of H‐DBD in helium,nitrogen,and ***,the paper provides a brief overview of multiple‐current‐pulse(MCP)behaviours in H‐*** objective of this article is to provide a chronological un-derstanding of homogeneous dielectric barrier discharge(DBD).This understanding will aid in the design of new experiments aimed at better comprehending the mechanisms behind H‐DBD generation and ultimately assist in achieving large‐volume H‐DBD in an air environment.

关键词： dielectric barrier pollution

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Robust Tweets Classification Using Arithmetic Optimization with Deep Learning for Sustainable Urban Living

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SN computer Science 2024年第5期5卷 549页

作者： Hamza, Manar Ahmed Hashim, Aisha Hassan Abdalla Motwakel, Abdelwahed Elhameed, Elmouez Samir Abd Osman, Mohammed Kumar, Arun Singla, Chinu Munjal, Muskaan Department of Electrical and Computer Engineering International Islamic University Malaysia Kuala Lumpur 53100 Malaysia Department of Computer and Self Development Preparatory Year Deanship Prince Sattam bin Abdulaziz University AlKharj Saudi Arabia Department of Management Information Systems College of Business Administration in Hawtat bani Tamim Prince Sattam bin Abdulaziz University AlKharj Saudi Arabia Department of Computer Science College of Post-Graduated Studies University of Science and Technology Omdurman Sudan Department of Information System Faculty of Computer Science and Information Technology Omdurman Islamic University Omdurman Sudan Department of Electronics and Communication Engineering New Horizon College of engineering Bengaluru India Computer Engineering Thapar Institute of Engineering and Technology Punjab Patiala India

Natural Language Processing (NLP) with Deep Learning (DL) for Tweets Classification includes use of advanced neural network designs to analyse and classify Twitter messages. DL techniques like recurrent neural network (RNN) or transformer-based frameworks like BERT are used to mechanically learn difficult linguistic patterns and contextual info from tweet data. These techniques able to capture subtleties of language with sarcasm, sentiment, and context-specific meanings and making them suitable for tasks like sentiment analysis or topic classification in realm of social media. Leveraging deep symbols learned from great amounts of textual data, these NLP techniques permit precise and nuanced classification of tweets, donating to enhanced information retrieval, sentiment tracking, and trend analysis in dynamic and fast-paced world of social media communication. In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. The goal of the AOADL-TC technique is to identify and discriminate different kinds of sentiments that exist in the tweet data. At the initial stage, the AOADL-TC model pre-processes tweet data to convert uniform data into a useful format. For sentiment detection, the AOADL-TC technique applies a parallel bidirectional gated recurrent unit (BiGRU) model. At last, tuning of parameters related to parallel BiGRU model performed by AOA. An wide set of tests carried out to illustrate better performance of AOADL-TC model. The experimental outcomes portrayed that AOADL-TC technique demonstrates the supremacy of the AOADL-TC technique in terms of different evaluation metrics. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Deep learning Machine learning Natural language processing Sentiment analysis Social media

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Robust Synergetic Observer based Fault-Tolerant Control for Electric Vehicle Applications 50

Robust Synergetic Observer based Fault-Tolerant Control for ...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Boumegouas, Mohammed Kabir Billa Kouzi, Katia Trabelsi, Mohamed Iqbal, Atif Birame, Mhamed Shadmand, Mohammad B. Laboratory of Semiconductors and Functional Materials Amar Telidji University of Laghouat Algeria Electronics and Communications Engineering Department Kuwait College of Science and Technology Kuwait Department of Electrical Engineering Qatar University Doha Qatar Department of Electrical & Computer Engineering University of Illinois ChicagoIL United States

ISBN: (纸本)9781665464543

Speed sensor faults are very common in electric vehicle (EV) applications, often disrupting system performance due to the reliance on speed sensor data by the electric drives. Consequently, fault-tolerant control approaches require robust observer structures capable of functioning effectively during faults, swiftly identifying and reconfiguring failures. Thus, this paper presents a novel fault-tolerant control design leveraging a synergetic observer (SO) to substitute the speed sensor in the event of fault. Comparative analysis with a super-twisting sliding mode observer (ST-SMO) highlights the proposed observer's superior performance in terms of tracking accuracy and ripple reduction. The presented simulation results demonstrate promising performance of the proposed observer for fault-tolerant control in EV applications. © 2024 IEEE.

关键词： Permanent magnets

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Distributed Consensus Multi-Agent System Control of AC Microgrid Under Various Communication Disturbances

Distributed Consensus Multi-Agent System Control of AC Micro...

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IEEE Industry Applications Society Annual Meeting (IAS)

作者： Ibtissam Kharchouf Mahmoud S. Abdelrahman Hossam M. Hussein S M Sajjad Hossain Rafin Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami USA

ISBN: (数字)9798350372717

ISBN: (纸本)9798350372724

The resilience of AC microgrids (MGs) in the face of communication disturbances, including variable delays, packet loss, packet corruption (noise), and limited bandwidth, is studied. A Controller Hardware-in-the-Loop (CHIL) platform is used to investigate the ramifications of these disturbances comprehensively. The MG cyber-physical system (CPS) integrates a real-time islanded AC microgrid deployed on RT-LAB, distributed secondary consensus controllers on single-board computers, and a real communication network infrastructure. Through meticulous analysis and experimentation, this research highlights the vulnerabilities of AC MGs to communication disturbances and their detrimental effects on the system resiliency, stability, and efficiency. The experiments emphasize the need for designing robust and adaptive control strategies that can effectively mitigate the effects of communication disruptions and enhance the overall reliability and performance of AC microgrid systems.

关键词： Noise Packet loss Microgrids Bandwidth Cyber-physical systems Stability analysis Real-time systems Delays Resilience Multi-agent systems

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A High-Frequency Transformer Design with Leakage Integration for Auxiliary Power Supply in Railway Application 11

A High-Frequency Transformer Design with Leakage Integration...

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11th International Conference on Power Electronics - ECCE Asia, ICPE 2023-ECCE Asia

作者： Li, Zheqing Jin, Feng Zhao, Chunyang Hsieh, Eric Li, Qiang Virginia Polytechnic and State University Center for Power Electronic Systems Bradley Department of Electrical and Computer Engineering BlacksburgVA24061 United States

ISBN: (纸本)9788957083505

DC-DC converters are a critical component for the auxiliary power supplies in railway applications to regulate wide range input voltage. With the power consumption increasing, the momentum toward high-power high-density continues unbated. The key to shrink the converter size is high-frequency operation. The bottleneck is the magnetic component, especially for the high-power converters. With wide-band gap (WBG) devices, frequency can be hundreds of kilohertz level, which can reduce the transformer volume significantly. By adopting the shorting control for gain boost, only a small resonant inductance is required to handle the wide input voltage. The low inductance provides the opportunity to integrate the resonant inductor into the transformer to further reduce the size of magnetic components. In this paper, a novel transformer is proposed with the integration of additional leakage inductor for resonance with evenly distributed core loss, and no sacrifice the winding loss and. A 30-kW 100-kHz prototype with 2.4 kW/L power density is built to verify the feasibility of the proposed transformer, whose peak efficiency reaches 99.2%. © 2023 The Korean Institute of Power Electronics.

关键词： Energy gap

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EMS-Based HESS Using an Adaptive Filter Approach with SoC Balancing for DCMG

EMS-Based HESS Using an Adaptive Filter Approach with SoC Ba...

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IEEE Industry Applications Society Annual Meeting (IAS)

作者： Hossam M. Hussein Mahmoud S. Abdelrahman Ibtissam Kharchouf S M Sajjad Hossain Rafin Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami USA

ISBN: (数字)9798350372717

ISBN: (纸本)9798350372724

Globally, microgrid-based renewable energy systems are increasingly adopted as part of the transition to sustainable energy sources. However, their intermittent nature and low inertia necessitate energy storage systems to maintain system stability. A highly effective solution involves employing hybrid energy storage systems combining batteries and supercapacitors. This combination leverages the unique characteristics of each component, particularly their energy and power densities, to effectively mitigate fluctuations in the DC-bus voltage under varying power conditions. To address these challenges, this paper proposes a novel energy management system-based hybrid energy storage system and a modified filter-based control technique to enhance the stability of islanded DC microgrids. Further, balance the state of charge of each storage device without breaching the stability state of the system. The effectiveness of the proposed system was validated through various study cases conducted in the MATLAB/SIMULINK environment. Additionally, this paper explores the topology of hybrid battery/supercapacitor systems, the dynamics of pulsed power loads, and the capability of the energy management system (EMS) to manage available resources across different operating modes to minimize their impact on DC-bus voltage stability.

关键词： Renewable energy sources Uncertainty Adaptive filters Microgrids Stability analysis Topology State of charge Energy management systems MATLAB Voltage control

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Strategies for Optimizing Energy Efficiency in Residential Buildings: An Integrated Framework Approach 3

Strategies for Optimizing Energy Efficiency in Residential B...

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3rd International Conference on Energy Transition in the Mediterranean Area, SyNERGY MED 2024

作者： Kourougianni, Fanourios Olympios, Andreas V. Arsalis, Alexandros Georghiou, George E. University of Cyprus PV Technology Laboratory Department of Electrical and Computer Engineering Nicosia Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus

ISBN: (纸本)9798350375923

Sustainable design and nearly zero-energy buildings (NZEBs) are essential for managing energy consumption and reducing carbon emissions in the building sector while maintaining occupant comfort. This study focuses on developing an advanced modeling framework for optimizing energy efficiency in residential buildings, integrating computational design, building performance simulation, and multi-objective optimization (MOO). Applied to a typical archetype in Cyprus, the framework evaluates diverse energy-efficient strategies, including innovative measures such as thermochromic glazing, natural ventilation, automated dimming of artificial lighting, and rule-based control electrochromic glazing systems, among other conventional energy efficiency measures (EEMs). MOO considers energy needs and investment costs. Results demonstrate significant energy savings potential, with optimal combinations of EEMs achieving a 77% reduction in cooling demand and 73% in heating demand compared to the baseline. This tool proves valuable for decision-making in both new construction and retrofitting, identifying cost-effective pathways towards NZEBs. © 2024 IEEE.

关键词： Green buildings

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A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 812-833页

作者： Xinlei Yi Shengjun Zhang Tao Yang Tianyou Chai Karl Henrik Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technologyand also affiliated with the Digital FuturesStockholm 10044Sweden Department of Electrical Engineering University of North TexasDentonTX 76203 USA IEEE State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China

The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is *** problem is an important component of many machine learning techniques with data parallelism,such as deep learning and federated *** propose a distributed primal-dual stochastic gradient descent(SGD)algorithm,suitable for arbitrarily connected communication networks and any smooth(possibly nonconvex)cost *** show that the proposed algorithm achieves the linear speedup convergence rate O(1/(√nT))for general nonconvex cost functions and the linear speedup convergence rate O(1/(nT)) when the global cost function satisfies the Polyak-Lojasiewicz(P-L)condition,where T is the total number of *** also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global *** demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms.

关键词： Distributed nonconvex optimization linear speedup Polyak-Lojasiewicz(P-L)condition primal-dual algorithm stochastic gradient descent

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Federated Learning Incorporating Non-Orthogonal Transmission and Unstructured Model Pruning

Federated Learning Incorporating Non-Orthogonal Transmission...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Gao, Siyu Zhao, Ming Zhou, Shengli University of Science and Technology of China Cas Key Laboratory of Wireless-Optical Communications Hefei China University of Connecticut Department of Electrical and Computer Engineering Storrs United States

ISBN: (纸本)9798350351255

In federated learning (FL), the servers are generally seen as omnipotent to distribute the full models to all clients. This is not the case in wireless systems. The broadcast of models inevitably excludes some users with poor channel gain but valuable computation power and diverse local data. In this paper, taking the various computation and communication capabilities of users into account, we propose a federated learning scheme incorporating unstructured model pruning and non-orthogonal transmission. The pruning process divides the model into the core and the extended parts, with the ratio adaptive to the users' achievable working rates. With non-orthogonal transmission, the strong users get both parts of the model while the weak get only the core part. Simulation results show that the proposed scheme involves more users than traditional wireless FL and improves the accuracy of tasks within the given communication rounds. © 2024 IEEE.

关键词： Federated learning

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