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2022 International Conference on Trends in Electrical, Electronics, Computer engineering, TEECCON 2022

作者： Himaja Chowdary, K. Sai Kalaiyarasi, M. Saravanan, S. Amazon Development Center India Private Ltd Bangalore India V.S.B Engineering College Department of Electronics and Communication Engineering Karur India Bv Raju Institute of Technology Department of Electrical and Electronics Engineering Telangana India

ISBN: (数字)9781665483667

ISBN: (纸本)9781665483667

Satellite images are often volumetric, requiring a lot of storage and transmission space and time. In this paper, a Gated Recurrent Unit RNN based NTD method has been proposed for satellite image compression. RNN is used to convert spectral sensor into small scale spectral sensor. Entropy encoding is performed for final compression. The proposed method is compared to the standard NTD in the wavelet domain, the computing efficiency is improved by 56.40% while compromising just -0.58 dB of PSNR. © 2022 IEEE.

关键词： Recurrent neural networks

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Leveraging Neuromorphic Computing for Efficient and Scalable Data Analytics

Leveraging Neuromorphic Computing for Efficient and Scalable...

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Advancement in Computation & Computer Technologies (InCACCT), International Conference on

作者： Shubham Gupta Ishwar Bansal Geeta Geeta Model Institute of Engineering and Technology Jammu J&K India Software Developer Amazon Development Center Herndon USA School of Sciences Geeta University Panipat India

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

Neuromorphic computing is a new data analytical paradigm that mimics the behavior of biological neural systems to offer better computational power. State-of-the-art performance in conventional deep learning models (CNNs and transformers) comes at the expense of exorbitant energy and computation time. The real-time processing, low latency, and better energy efficiency make neuromorphic architectures to be a more appealing solution to kiosks where inferences on a large scale of data are being performed. In this paper, we discuss neuromorphic computing, how it can minimize data processing, its superiority compared to traditional AI models, and its future selection for diverse applications. Neuromorphic systems demonstrate a scalable way to the next-generation artificial intelligence by taking advantage of event-driven processing and dedicated hardware

关键词： Deep learning Data analysis Neuromorphic engineering Computational modeling Biological system modeling Computer architecture Real-time systems Energy efficiency Data models Artificial intelligence

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MambaBEV: An efficient 3D detection model with Mamba2

arXiv

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arXiv 2024年

作者： You, Zihan Wang, Ni Wang, Hao Zhao, Qichao Wang, Jinxiang School of Instrument Science and Engineering Southeast University China Amazon Development Center Germany GmbH Germany T3CAIC Technology China School of Mechanical Engineering Southeast University China

Accurate 3D object detection in autonomous driving relies on Bird’s Eye View (BEV) perception and effective temporal fusion. However, existing fusion strategies—based on convolutional layers or deformable self-attention—struggle with global context modeling in BEV space, leading to lower accuracy for large objects. To address this, we introduce MambaBEV, a novel BEV-based 3D object detection model that leverages Mamba2, an advanced state-space model (SSM) optimized for long-sequence processing. Our key contribution is TemporalMamba, a temporal fusion module that enhances global awareness by introducing a BEV feature discrete rearrangement mechanism tailored for Mamba’s sequential processing. Additionally, we propose Mamba-based-DETR as the detection head to improve multi-object representation. Evaluations on the nuScenes dataset demonstrate that MambaBEV-base achieves an NDS of 51.7% and an mAP of 42.7%. Furthermore, an end-to-end autonomous driving paradigm validates its effectiveness in motion forecasting and planning. Our results highlight the potential of SSMs in autonomous driving perception, particularly in enhancing global context understanding and large-object detection. Copyright © 2024, The Authors. All rights reserved.

关键词： Object recognition

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Shock Data Loggers for Transport Applications 4

Shock Data Loggers for Transport Applications

引用

4th International Conference on Electronics, Communication and Aerospace Technology, ICECA 2020

作者： Prajwal, K T Nair, Swathy Roopini, C M S Ramaiah University of Applied Sciences Department of Electrical Engineering Bangalore India Amazon Development Center Bangalore India

ISBN: (纸本)9781728163871

There has been a rapid growth in the transport industry in the recent past. Owing to the aggregator-based model being followed currently, the transport companies have little control over the driving pattern of the driver which may be a decisive factor in the customer satisfaction and security of the goods that are being carried in the vehicles. Hence an urgent need for the development of a system that could detect the driving pattern is rapidly increasing. A low-cost shock data logger is designed in this literature using a low-cost accelerometer available. The proof of concept is carried out using a laboratory available accelerometer and a PC HyperTerminal. Results indicate the continuous monitoring of the driving pattern is possible and shock data can be recorded up to 10 g. © 2020 IEEE.

关键词： Accelerometers

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A Platform for Monitoring Student Commuting in the Use of School Transport in Smart Cities - A Facial Recognition Based Approach

A Platform for Monitoring Student Commuting in the Use of Sc...

引用

International Conference on Smart Communications and Networking (SmartNets)

作者： Jessé Da Costa Rocha Marcela Alves de Souza Evelin Helena Silva Cardoso Nandamudi Vijaykumar Jasmine Priscyla Leite de Araújo Renato Lisboa Francês Graduate Program in Electrical Engineering Institute of Technology Federal University of Pará (UFPA) Belém Pará Brazil Information and Communication Technology Center Federal University of the South and Southeast of Para (Unifesspa) Marabá Pará Brazil Department of Computer Science Federal Rural University of the Amazon (UFRA) Capitão Poço Pará Brazil Coordination of Applied Research and Technological Development National Institute for Space Research (INPE) São Paulo Brazil

This article proposes an intelligent platform for monitoring students' steps on their way to school until they leave the school to their homes. This platform can identify students and notify those responsible and competent authorities in various situations of school life, such as: entering and leaving the school bus, entering and leaving school, entering the school cafeteria, etc. The first application aims to control access to the school bus through facial recognition. In the tests carried out, the recognition system achieved excellent results in all metrics.

关键词：

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Muwos - Multiple Use Water Optimization System for the Power Generation and Navigation Trade-Offs Analysis

SSRN

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SSRN 2022年

作者： de Figueiredo, Nelio Moura Blanco, Claudio José Cavalcante Campos Filho, Lúcio Carlos Pinheiro Mesquita, André Luiz Amarante Technological Institute Federal University of Pará PA Brazil Rua Augusto Correa 01 Belém Brazil Technological Institute Federal University of Pará PA Brazil Rua Augusto Correa 01 Belém Brazil Waterway and Port Research Group Faculty of Naval Engineering Federal University of Pará Rua Augusto Correa 01 Belém Brazil Amazon Development Center in Engineering Federal University of Pará NIDAE CAMTUC UFPA Av. Brasília S/N - Vila Permanente Tucuruí-PA 68455-901 Brazil

Reservoir operation is one of the major challenges in water resources planning and usually involves trading-off competing objectives. From the knowledge of the main water uses related to a hydro power plant, it is necessary to understand how energy uses impacts others and how energy use itself is impacted. Using the Tapajos River basin, Brazil, as a case study, this article aims to analyze water trade-offs between power generation and navigation uses, related to gains or losses of downstream water depth and of river convoy cargo capacity. The analysis of water conflicts was performed developing a nonlinear programming-based computational model called MUWOS (Multiple Use Water Optimization System), for conflict mitigation and minimization from the modeling and operational optimization of hydropower plants, for different navigation and hydrological scenarios. The result analysis showed that the main goals were achieved, evidencing that the research can aid the mitigating impacts process linked to hydro power projects for which navigation is an important economic aspect of the analyzed area. The method produced trade-off analyses and graphs, enabling verification of extent to which the prioritization of one use influences another use. The results obtained from the case study are consistent and useful for water management. © 2022, The Authors. All rights reserved.

关键词： Nonlinear programming

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Muwos - Multiple Use Water Optimization System for the Power Generation and Navigation Trade-Offs Analysis

SSRN

引用

SSRN 2022年

作者： de Figueiredo, Nelio Moura Blanco, Claudio José Cavalcante Campos Filho, Lúcio Carlos Pinheiro Mesquita, André Luiz Amarante Technological Institute Federal University of Pará PA Brazil Rua Augusto Correa 01 Belém PA Belém Brazil Technological Institute Federal University of Pará PA Brazil Rua Augusto Correa 01 PA Belém Belém Brazil Waterway and Port Research Group Faculty of Naval Engineering Federal University of Pará Rua Augusto Correa 01 PA Belém Brazil Amazon Development Center in Engineering Federal University of Pará NIDAE CAMTUC UFPA Av. Brasília S/N - Vila Permanente Tucuruí-PA 68455-901 Brazil

关键词： Nonlinear programming

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Energetic electron precipitation driven by electromagnetic ion cyclotron waves from ELFIN’s low altitude perspective

arXiv

引用

arXiv 2022年

作者： Angelopoulos, V. Zhang, X.-J. Artemyev, A.V. Mourenas, D. Tsai, E. Wilkins, C. Runov, A. Liu, J. Turner, D.L. Li, W. Khurana, K. Wirz, R.E. Sergeev, V.A. Meng, X. Wu, J. Hartinger, M.D. Raita, T. Shen, Y. An, X. Shi, X. Bashir, M.F. Shen, X. Gan, L. Qin, M. Capannolo, L. Ma, Q. Russell, C.L. Masongsong, E.V. Caron, R. He, I. Iglesias, L. Jha, S. King, J. Kumar, S. Le, K. Mao, J. McDermott, A. Nguyen, K. Norris, A. Palla, A. Roosnovo Tam, J. Xie, E. Yap, R.C. Ye, S. Young, C. Adair, L.A. Shaffer, C. Chung, M. Cruce, P. Lawson, M. Leneman, D. Allen, M. Anderson, M. Arreola-Zamora, M. Artinger, J. Asher, J. Branchevsky, D. Cliffe, M. Colton, K. Costello, C. Depe, D. Domae, B.W. Eldin, S. Fitzgibbon, L. Flemming, A. Frederick, D.M. Gilbert, A. Hesford, B. Krieger, R. Lian, K. McKinney, E. Miller, J.P. Pedersen, C. Qu, Z. Rozario, R. Rubly, M. Seaton, R. Subramanian, A. Sundin, S.R. Tan, A. Thomlinson, D. Turner, W. Wing, G. Wong, C. Zarifian, A. Earth Planetary and Space Sciences Department Institute of Geophysics and Planetary Physics University of California Los Angeles Los AngelesCA90095 United States University of Texas at Dallas RichardsonTX75080 United States CEA DAM DIF Arpajon France Atmospheric and Oceanic Sciences Departments University of California Los AngelesCA United States Johns Hopkins University Applied Physics Laboratory LaurelMD United States Department of Astronomy Center for Space Physics Boston University BostonMA United States Mechanical and Aerospace Engineering Department Henry Samueli School of Engineering University of California Los AngelesCA90095 United States School of Mechanical Industrial Manufacturing Engineering Oregon State University CorvallisOR97331 United States University of St. Petersburg St. Petersburg Russia Jet Propulsion Laboratory California Institute of Technology PasadenaCA91109 United States Space Science Institute BoulderCO80301 United States Sodankylä Geophysical Observatory University of Oulu Sodankylä Finland Materials Science and Engineering Department Henry Samueli School of Engineering University of California Los AngelesCA90095 United States Deloitte Consulting New YorkNY10112 United States Computer Science Department Henry Samueli School of Engineering University of California Los AngelesCA90095 United States Microsoft RedmondWA98052 United States Physics and Astronomy Department University of California Los AngelesCA90095 United States Department of Astronomy and Astrophysics The University of Chicago ChicagoIL60637 United States Raybeam Inc. Mountain ViewCA94041 United States SpaceX HawthorneCA90250 United States Reliable Robotics Corporation Mountain ViewCA94043 United States Los Alamos National Laboratory Los AlamosNM87545 United States Mathematics Department University of California Los AngelesCA90095 United States Planet Labs PBC San FranciscoCA94107 United States KSAT Inc. De

We review comprehensive observations of electromagnetic ion cyclotron (EMIC) wave-driven energetic electron precipitation using data from the energetic electron detector on the Electron Losses and Fields InvestigatioN (ELFIN) mission, two polar-orbiting low-altitude spinning CubeSats, measuring 50-5000 keV electrons with good pitch-angle and energy resolution. EMIC wave-driven precipitation exhibits a distinct signature in energy-spectrograms of the precipitating-to-trapped flux ratio: peaks at >0.5 MeV which are abrupt (bursty) (lasting ∼17s, or ∆L ∼ 0.56) with significant substructure (occasionally down to sub-second timescale). We attribute the bursty nature of the precipitation to the spatial extent and structuredness of the wave field at the equator. Multiple ELFIN passes over the same MLT sector allow us to study the spatial and temporal evolution of the EMIC wave - electron interaction region. Case studies employing conjugate ground-based or equatorial observations of the EMIC waves reveal that the energy of moderate and strong precipitation at ELFIN approximately agrees with theoretical expectations for cyclotron resonant interactions in a cold plasma. Using 2 years of ELFIN data uniformly distributed in local time, we assemble a statistical database of ∼50 events of strong EMIC wave-driven precipitation. Most reside at L ∼ 5 − 7 at dusk, while a smaller subset exists at L ∼ 8 − 12 at post-midnight. The energies of the peak-precipitation ratio and of the half-peak precipitation ratio (our proxy for the minimum resonance energy) exhibit an L-shell dependence in good agreement with theoretical estimates based on prior statistical observations of EMIC wave power spectra. The precipitation ratio’s spectral shape for the most intense events has an exponential falloff away from the peak (i.e., on either side of ∼ 1.45 MeV). It too agrees well with quasi-linear diffusion theory based on prior statistics of wave spectra. It should be noted though that this diffusive

关键词： Radiation belts

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2-Dimensional and 3-Dimensional Navigation

2-Dimensional and 3-Dimensional Navigation

引用

IEEE International Conference on Power, Control, Signals and Instrumentation engineering

作者： P. Asha Kavitha Esther Rajakumari R. Abhilash Department of Computer Science and Engineering Sathyabama University Chennai Amazon Development Center Chennai

ISBN: (纸本)9781538608159

The 2-Dimensional and 3-Dimensional navigation system makes the users to determine and it specifies the exact places in the map. This proposal deals with the mechanisms of the navigation technologies used to develop the 2-Dimensional and 3-Dimensional models. This makes the navigation easy and effective for the users to travel to their desired locations. The 2-D & 3-D navigation is much simple as the google maps, this requires the base map of the specified location to be designed. The 2-D navigation is much easier for the users to understand, since it is of uncomplicated format. When this comes to the 3-D navigation, this makes the users to experience that they travel in reality.

关键词： Navigation 2-Dimensional models 3-Dimensional models Maps

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Addressing climate change with behavioral science: A global intervention tournament in 63 countries

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Science Advances 2024年第6期10卷 eadj5778页

作者： Vlasceanu, Madalina Doell, Kimberly C. Bak-Coleman, Joseph B. Todorova, Boryana Berkebile-Weinberg, Michael M. Grayson, Samantha J. Patel, Yash Goldwert, Danielle Pei, Yifei Chakroff, Alek Pronizius, Ekaterina van den Broek, Karlijn L. Vlasceanu, Denisa Constantino, Sara Morais, Michael J. Schumann, Philipp Rathje, Steve Fang, Ke Aglioti, Salvatore Maria Alfano, Mark Alvarado-Yepez, Andy J. Andersen, Angélica Anseel, Frederik Apps, Matthew A.J. Asadli, Chillar Awuor, Fonda Jane Azevedo, Flavio Basaglia, Piero Bélanger, Jocelyn J. Berger, Sebastian Bertin, Paul Bialek, Michal Bialobrzeska, Olga Blaya-Burgo, Michelle Bleize, Daniëlle N.M. Bø, Simen Boecker, Lea Boggio, Paulo S. Borau, Sylvie Bos, Björn Bouguettaya, Ayoub Brauer, Markus Brick, Cameron Brik, Tymofii Briker, Roman Brosch, Tobias Buchel, Ondrej Buonauro, Daniel Butalia, Radhika Carvacho, Héctor Chamberlain, Sarah A.E. Chan, Hang-Yee Chow, Dawn Chung, Dongil Cian, Luca Cohen-Eick, Noa Contreras-Huerta, Luis Sebastian Contu, Davide Cristea, Vladimir Cutler, Jo D'Ottone, Silvana De Keersmaecker, Jonas Delcourt, Sarah Delouvée, Sylvain Diel, Kathi Douglas, Benjamin D. Drupp, Moritz A. Dubey, Shreya Ekmanis, Jānis Elbaek, Christian T. Elsherif, Mahmoud Engelhard, Iris M. Escher, Yannik A. Etienne, Tom W. Farage, Laura Farias, Ana Rita Feuerriegel, Stefan Findor, Andrej Freira, Lucia Friese, Malte Gains, Neil Philip Gallyamova, Albina Geiger, Sandra J. Genschow, Oliver Gjoneska, Biljana Gkinopoulos, Theofilos Goldberg, Beth Goldenberg, Amit Gradidge, Sarah Grassini, Simone Gray, Kurt Grelle, Sonja Griffin, Siobhán M. Grigoryan, Lusine Grigoryan, Ani Grigoryev, Dmitry Gruber, June Guilaran, Johnrev Hadar, Britt Hahnel, Ulf J.J. Halperin, Eran Harvey, Annelie J. Haugestad, Christian A.P. Herman, Aleksandra M. Hershfield, Hal E. Himichi, Toshiyuki Hine, Donald W. Hofmann, Wilhelm Howe, Lauren Huaman-Chulluncuy, Enma T. Huang, Guanxiong Ishii, Tatsunori Ito, Ayahito Jia, Fanli Jost, John T. Jovanović, Veljko Jurgiel, Dominika Kácha, Ondřej Kankaanpää, Reeta Kant Department of Psychology New York University New YorkNY10003 United States Department of cognition emotion and Methods in Psychology Faculty of Psychology University of Vienna Vienna1010 Austria Craig newmark center for Journalism ethics and Security Columbia University New YorkNY10018 United States Institute for Rebooting Social Media Harvard University CambridgeMA02138 United States Department of Psychology Stanford University StanfordcA94305 United States San luis Obispo cA93405 United States Copernicus institute of Sustainable development Utrecht University Utrecht3584 cB Netherlands Department of Psychology University of Pittsburgh PittsburghPA15260 United States School of Public Policy and Urban Affairs Northeastern University BostonMA02115 United States Department of Psychology Northeastern University BostonMA02115 United States Amazon SeattleWA98109 United States Department of Psychology Carl von Ossietzky University of Oldenburg Oldenburg26129 Germany Santa lucia Foundation IRccS Rome179 Italy Department of Psychology Sapienza University of Rome Rome185 Italy Department of Philosophy Macquarie University SydneynSW2000 Australia Universidad Peruana cayetano heredia San Martín de Porres15102 Peru Post-Graduation Program in linguistics Federal University of Paraná Curitiba80060150 Brazil UnSW Business School University of new South Wales SydneynSW2052 Australia Centre for human Brain health School of Psychology University of Birmingham BirminghamB15 2tt United Kingdom Psychology Scientific Research institute Baku Azerbaijan Kenya Marine and Fisheries Research institute Kisumu1881-40100 Kenya Department of Psychology University of Groningen Groningen9712tS Netherlands Department of economics University of hamburg Hamburg20146 Germany De-partment of Psychology New York University Abu dhabi Abu dhabi129188 United Arab Emirates Department of Sociology University of Bern Bern3012 Switzerland LAPcOS Univers

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors. © 2024 American Association for the Advancement of Science. All rights reserved.

关键词： Climate change

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