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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Kevin Braathen de Carvalho Iure Rosa L. de Oliveira Alexandre S. Brandão Department of Electrical Engineering Graduate Program in Computer Science Nucleus of Specialization in Robotics Universidade Federal de Viçosa Viçosa MG Brazil Department of Electrical Engineering Federal University of Viçosa Viçosa MG Brazil

Unmanned Aerial Vehicles (UAVs) are widely used in various applications, from inspection and surveillance to transportation and delivery. Navigating UAVs in complex 3D environments is a challenging task that requires robust and efficient decision-making algorithms. This paper presents a novel approach to UAV navigation in 3D environments using a Curriculum-based Deep Reinforcement Learning (DRL) approach. The proposed method utilizes a deep neural network to model the UAV’s decision-making process and to learn a mapping from the state space to the action space. The learning process is guided by a reinforcement signal that reflects the performance of the UAV in terms of reaching its target while avoiding obstacles and with energy efficiency. Simulation results show that the proposed method has a positive trade off when compared to the baseline algorithm. The proposed method was able to perform well in environments with a state space size of 22 millions, allowing the usage in big environments or in maps with high resolution. The results demonstrate the potential of DRL for enabling UAVs to operate effectively in complex environments.

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A weighted multivariate fuzzy time series method for multiple output high-dimensional time series forecasting in IoT applications

A weighted multivariate fuzzy time series method for multipl...

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2024 IEEE Latin American Conference on Computational Intelligence, LA-CCI 2024

作者： Bitencourt, Hugo Vinicius De Oliveira Lucas, Patricia Orang, Omid Silva, Petronio Guimaraes, Frederico Gadelha Universidade Federal de Minas Gerais Graduate Program in Electrical Engineering Belo Horizonte31270-901 Brazil Instituto Federal Do Norte de Minas Gerais Salinas Brazil Universidade Federal de Minas Gerais Department of Computer Science Belo Horizonte31270-901 Brazil Instituto Federal Do Norte de Minas Gerais Januária Brazil

ISBN: (纸本)9798350374575

In Internet of Things (IoT) applications, data flows are continuous streams of high-dimensional time series that aggregate various data sources. In this context, decision-making processes frequently encompass multiple factors and criteria that demand forecasting these time series. This paper introduces MO-WMVFTS, a novel multiple-input multiple-output (MIMO) fuzzy time series (FTS) method for tackling this complex scenario. MO-WMVFTS is a hybrid forecasting method that fuses weighted multivariate FTS (WMVFTS) with embedding transformations, designed for IoT applications. To assess the performance of the proposed method, it was applied to the prediction of energy consumption in smart homes and air quality in smart cities. Here, three real-world datasets are used to assess the validity of our proposed approach, and the results obtained are highly competitive when compared to other existing methods. © 2024 IEEE.

关键词： Smart homes

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Characteristics Fluctuation of Sub-3-nm Bulk FinFET Devices Induced by Random Interface Traps

Characteristics Fluctuation of Sub-3-nm Bulk FinFET Devices ...

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IEEE Conference on Nanotechnology

作者： Sekhar Reddy Kola Min-Hui Chuang Yiming Li Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Electronics and Electrical Engineering Institute of Communications Engineering Institute of Biomedical Engineering Institute of Pioneer Semiconductor Innovation Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Hsinchu Taiwan

Three-dimensional (3D) bulk fin-typed field effect transistors (FinFETs) have emerged as key devices that can scale down the technology node beyond 22-nm. However, the scaled devices have created new sources of fluctuation inherent in 3D geometry. The interface trap is one such fluctuation that is caused by the trapping and de-trapping of charge carriers and has an adverse effect on device characteristics and variability. In this work, we study impacts of random interface traps (RITs) on electrical characteristic of bulk FinFETs by using a 3D quantum-mechanically corrected device simulation. RIT position effects on short channel effects (SCEs) are examined with physical governed influence to show the major fluctuations. More than 50% reductions of the RITs-induced characteristic fluctuation of the germanium (Ge) devices are observed, compared with Si devices. The Ge ones can reduce SCE variations and exhibit high immunity to RITs.

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Exploring 3D Reconstruction with Drone Images: Advances and Challenges in Urban Environments

Exploring 3D Reconstruction with Drone Images: Advances and ...

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Annual Conference of Industrial Electronics Society

作者： Thiago João Miranda Baldivieso Taise Grazielle Da Silva Batista Fabio Suim Chagas Luiz Carlos Pacheco Rodrigues Velho Paulo Fernando Ferreira Rosa Defense Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil State Institute of the Environment Inea/RJ Rio de Janeiro Brazil Department of Science and Industry Systems University of South-Eastern Norway Kongsberg Norway Department of Computer Graphics Institute for Pure and Applied Mathematics Rio de Janeiro Brazil Electrical Engineering Graduate Program Military Institute of Engineering Rio de Janeiro Brazil

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

This working-in-progress paper aims to present a three-dimensional reconstruction using aerial images in different environments. The experiments were conducted with aircraft in both external and internal settings, starting with image acquisition, followed by the application of specific photogrammetry software—both commercial and open-source—and concluding with a qualitative evaluation of the results.

关键词： Industrial electronics Three-dimensional displays Urban areas Aircraft Image reconstruction Photogrammetry Drones

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Joint Design of Spirograph Method and Reconfigurable Intelligent Surface for Future Communication Systems

Joint Design of Spirograph Method and Reconfigurable Intelli...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Balqis Yafis Jane-Hwa Huang Chih-Min Yu Li-Chun Wang EECS Int’l Graduate Program National Yang Ming Chiao Tung University Hsinchu Taiwan Dept. of Electrical Engineering National Chi Nan University Taiwan Department of Information and Computer Engineering Chung Yuan Christian University Taiwan Dept. of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Reconfigurable Intelligent Surface (RIS) is a transformative technology using the passive beamforming capabilities to create the programmable wireless environments. However, the control overhead is a challenging issue. The system needs to deliver the high-precision reflection coefficients to the RIS controller, for adjusting the phase shifts of the numerous RIS elements. Therefore, we propose a Spirograph-based discrete beamdirection strategy, which selects a set of non-uniformly distributed beam directions based on the generic patterns generated by the Spirograph (SG). We evaluate the achievable data rate and the number of controlling bits of SG-based method. We compare the SG-based method, the ideal continuous phase-shift method, and the SISO method. Simulation results show that with the properly-selected discrete beam directions, the SG-based method can achieve a comparable data rate as the ideal method, while having a lower control overhead.

关键词： Wireless communication Quantization (signal) Array signal processing Simulation Design methodology Reconfigurable intelligent surfaces Reflection coefficient Global communication

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Adaptive Formation Learning Control for Cooperative AUVs under Complete Uncertainty

arXiv

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arXiv 2024年

作者： Jandaghi, Emadodin Zhou, Mingxi Stegagno, Paolo Yuan, Chengzhi Department of Mechanical Industrial and Systems Engineering University of Rhode Island KingstonRI United States Graduate School of Oceanography University of Rhode Island KingstonRI United States Department of Electrical Computer and Biomedical Engineering University of Rhode Island KingstonRI United States

This paper introduces an innovative two-layer control framework for Autonomous Underwater Vehicles (AUVs), tailored to master completely uncertain nonlinear system dynamics in the presence of challenging hydrodynamic forces and torques. Distinguishing itself from prior studies, which only regarded certain matrix coefficients as unknown while assuming the mass matrix to be known, this research significantly progresses by treating all system dynamics, including the mass matrix, as unknown. This advancement renders the controller fully independent of the robot’s configuration and the diverse environmental conditions encountered. The proposed framework is universally applicable across varied environmental conditions that impact AUVs, featuring a first-layer cooperative estimator and a second-layer decentralized deterministic learning (DDL) controller. This architecture not only supports robust operation under diverse underwater scenarios but also adeptly manages environmental effects such as changes in water viscosity and flow, which influence the AUV’s effective mass and damping dynamics. The first-layer cooperative estimator fosters seamless inter-agent communication by sharing crucial system estimates without the reliance on global information, while the second-layer DDL controller utilizes local feedback to precisely adjust each AUV’s trajectory, ensuring accurate formation control and dynamic adaptability. Furthermore, the capability for local learning and knowledge storage through radial basis function neural networks (RBF NNs) is pivotal, allowing AUVs to efficiently reapply learned dynamics following system restarts. Comprehensive simulations validate the effectiveness of our groundbreaking framework, highlighting its role as a major enhancement in the field of distributed adaptive control systems for AUVs. This approach not only bolsters operational flexibility and resilience but is also essential for navigating the unpredictable dynamics of marine environments

关键词： Radial basis function networks

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Multivariate Time-Series Deep Learning for Joint Prediction of Temperature and Relative Humidity in a Closed Space

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Procedia computer Science 2023年 227卷 1046-1053页

作者： Fergianto E. Gunawan Arief S. Budiman Bens Pardamean Endang Juana Sugiarto Romeli Tjeng W. Cenggoro Kartika Purwandari Alam A. Hidayat Anak. A.N.P. Redi Muhammad Asrol Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta 11440 Indonesia PT Impack Pratama Industri Jakarta 14350 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia Mathematics Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

An accurate predictive model of temperature and humidity plays a vital role in many industrial processes that utilize a closed space such as in agriculture and building management. With the exceptional performance of deep learning on time-series data, developing a predictive temperature and humidity model with deep learning is propitious. In this study, we demonstrated that deep learning models with multivariate time-series data produce remarkable performance for temperature and relative humidity prediction in a closed space. In detail, all deep learning models that we developed in this study achieve almost perfect performance with an R value over 0.99.

关键词： closed space deep learning humity prediction indoor temperature prediction

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Abnormal skeletal muscle and myocardial vasoreactivity manifests prior to heart failure in a diabetic cardiomyopathy rat model

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Discover medicine 2025年第1期2卷 2页

作者： Sadi Loai Hai-Ling Margaret Cheng Institute of Biomedical Engineering University of Toronto Toronto ON Canada. Translational Biology & Engineering Program Ted Rogers Centre for Heart Research 661 University Avenue Room 1433 Toronto ON M5G 1M1 Canada. The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto Toronto ON Canada.

Background:Microvascular dysfunction (MVD) is a recognized sign of disease in heart failure progression. Intact blood vessels exhibit abnormal vasoreactivity in early stage, subsequently deteriorating to rarefaction and reduced perfusion. In managing heart failure with preserved ejection fraction (HFpEF), earlier diagnosis is key to improving management. In this study, we applied a steady-state blood-pool magnetic resonance imaging (MRI) method to investigate if it can sensitively detect abnormal leg muscle vasoreactivity, a sign of MVD, posited to manifest before structural and functional cardiac changes emerge in a diabetes model of HFpEF. Methods:Male and female Sprague-Dawley rats were maintained on either a high-fat, high-sugar diet or a control diet for 6 months after the induction of diabetes ( = 5 per group). Beginning at month 1 or 2 post-diabetes and every 2 months thereafter, rats underwent steady-state blood-pool MRI to assess vasoreactivity in the heart or skeletal muscle, respectively. A T1-reducing blood-pool agent was administered and the T1 relaxation time dynamically measured as animals breathed in elevated CO levels to modulate vessels. Results:In male rats, the normally unresponsive heart to 10% CO revealed a pro-vasoconstriction response beginning at 5 months post-diabetes. Abnormal leg skeletal muscle vasoreactivity appeared even earlier, at 2 months: the usual vasodilatory response to 5% CO was interrupted with periods of vasoconstriction in diseased rats. In female rats, differences were observed between healthy and diseased animals only in the first 2 months post-diabetes and not later. In the heart, vasodilation to 10% CO seen in healthy females was abolished in diabetic females. In skeletal muscle, 5% CO was suboptimal in inducing reproducible vasoreactivity, but young diabetic females responded by vasodilation only. Conclusions:Abnormal vasoreactivity presented earlier than overt functional changes in both heart and skeletal muscle in dia

关键词： Blood-pool T1 imaging Diabetes Gadofosveset Heart Hypercapnia Microvascular dysfunction Skeletal muscle Vasoreactivity

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A multimodal integrative approach to model transcriptional addiction of thyroid cancer on RUNX2

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Cancer Communications 2022年第9期42卷 892-896页

作者： Emanuele Vitale Elisabetta Sauta Mila Gugnoni Federica Torricelli Veronica Manicardi Alessia Ciarrocchi Laboratory of Translational Research Azienda Unità Sanitaria Locale-IRCCS di Reggio EmiliaReggio Emilia 42123Italy Clinical and Experimental Medicine PhD Program University of Modena and Reggio EmiliaModena 41121Italy Department of Electrical Computer and Biomedical EngineeringUniversity of PaviaPavia 27100Italy

Dear Editor Aberrant gene expression sustains massive proliferation and stress adaptation under the regulation of oncogenic transcription factors(TFs)whose binding across the genome orchestrates in space and time *** dependency defines the addiction of cancer cells to TFs on top of the regulatory hierarchy governing cancer dysregulated programs[1].These factors and their dependent mechanisms are an attractive and unexplored reservoir of potential targets for new anticancer ***,while the transcriptional landscape of many cancer-supportive TFs has been revealed,this information remains purely descriptive and confined to in vitro *** foster transferability,new approaches that integrate clinical data into the transcriptional networks are needed.

关键词： addiction modal reservoir

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Outcomes of pediatric community-acquired pneumonia before and after national pneumococcal immunization in Taiwan

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Pediatric Pulmonology 2023年第11期58卷 3246-3254页

作者： Chang, I-Fan Lin, I-Fan Liu, Yun-Chung Chou, Chia-Ching Chang, Tu-Hsuan Yen, Ting-Yu Lu, Chun-Yi Chang, Luan-Yin Lai, Feipei Huang, Li-Min Department of Pediatrics Taipei Hospital Ministry of Health and Welfare New Taipei City Taiwan Department of Pediatrics College of Medicine National Taiwan University Hospital National Taiwan University Taipei Taiwan Institute of Applied Mechanics National Taiwan University Taipei Taiwan Department of Pediatrics Chi-Mei Medical Center Tainan Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan

Objective: In Taiwan, the incidence of invasive pneumococcal disease (IPD) in children declined after the catch-up primary vaccination programs and the full national immunization program (NIP) with PCV13. The objective of the study was to investigate the clinical outcomes of pediatric community-acquired pneumonia (CAP) before and after the NIP. Methods: The study included patients aged 3 months to 17 years who were diagnosed with CAP and treated at the National Taiwan University Hospital between 2007 and 2019. Patients were assigned to three birth cohorts according to their birth years and vaccination eligibility: non-NIP, catch-up, and full NIP. We compared the rates of severe outcomes, including case fatality and pathogens. Results: A total of 6557 patients who met the CAP criteria were enrolled during the study period. The case-fatality rate decreased from 3.2% (94/2984) in the non-NIP cohort to 0.3% (7/2176) in the catch-up cohort and 0.8% (11/1397) in the full NIP cohort (p < 0.001). Furthermore, there was a significant decrease in invasive ventilation from the non-NIP (17.9%) to both catch-up (6.8%) and full NIP cohorts (9.1%). The rate of IPD declined from the non-NIP cohort to the catch-up cohort (1.8% vs. 0.6%, p < 0.001) and from the catch-up to the full NIP cohort (0.6% vs. 0.07%, p = 0.014). In contrast, the rates of infections with other pathogens increased after NIP. Conclusion: The introduction of PCV13 showed significant reduction in case-fatality and IPD rates. The increasing rates of other pathogens warrant further surveillance for their clinical significance. © 2023 Wiley Periodicals LLC.

关键词： immunization outcome pneumonia Streptococcus pneumonia

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