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Wireless control sterilization box prototype design using ultraviolet light C

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AIP Conference Proceedings 2022年第1期2543卷

作者： Zainuddin Arif Hidayat Hidayat Gunawan Muhammad Akil 1Remote Sensing and Technology Data Center Parepare Sulawesi Selatan Indonesia 91112 2Universitas Negeri Makassar Makassar Sulawesi Selatan Indonesia 90221

The Covid-19 outbreak has hit various countries. Indonesia is one of the countries that is hit by COVID-19. One of the media for transmitting this virus is through equipment that we use alternately. In performing the repairing and troubleshooting hardware an engineer uses the tools alternately. To reduce the spread of the COVID-19 virus, a device that can disinfect easily and efficiently is needed. Ultraviolet-C (UVC) rays have long been using to kill viruses and bacteria. This study aims to design a UV box control system as a sterilization medium. In this study, a disinfectant device was made using a glass material using ultraviolet-C light. Ultraviolet C rays can damage the skin and eyes. To avoid physical contact, control this device using Bluetooth wireless. The design of the UV box control system consists of 2 stages, namely, designing the hardware and software. The design is easy to use and can be applied in all business processes.

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ZenSVI: An Open-Source Software for the Integrated Acquisition, Processing and Analysis of Street View Imagery Towards Scalable Urban Science

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arXiv 2024年

作者： Ito, Koichi Zhu, Yihan Abdelrahman, Mahmoud Liang, Xiucheng Fan, Zicheng Hou, Yujun Zhao, Tianhong Ma, Rui Fujiwara, Kunihiko Ouyang, Jiani Quintana, Matias Biljecki, Filip Department of Architecture National University of Singapore 4 Architecture Drive Singapore117356 Singapore College of Big Data and Internet Shenzhen Technology University 3002 Lantian Road Shenzhen518118 China Department of Architecture and Civil Engineering City University of Hong Kong 999077 Hong Kong Research & Development Institute Takenaka Corporation 1-5-1 Otsuka Inzai Chiba270-1352 Japan State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430079 China Singapore-ETH Centre Future Cities Lab Global Programme CREATE campus 1 Create Way #06-01 CREATE Tower 138602 Singapore Department of Real Estate National University of Singapore 15 Kent Ridge Drive Singapore119245 Singapore

Street view imagery (SVI) has been instrumental in many studies in the past decade to understand and characterize street features and the built environment. Researchers across a variety of domains, such as transportation, health, architecture, human perception, and infrastructure have employed different methods to analyze SVI. However, these applications and image-processing procedures have not been standardized, and solutions have been implemented in isolation, often making it difficult for others to reproduce existing work and carry out new research. Using SVI for research requires multiple technical steps: accessing APIs for scalable data collection, preprocessing images to standardize formats, implementing computer vision models for feature extraction, and conducting spatial analysis. These technical requirements create barriers for researchers in urban studies, particularly those without extensive programming experience. We developed ZenSVI, a free and open-source Python package that integrates and implements the entire process of SVI analysis, supporting a wide range of use cases. Its end-to-end pipeline includes downloading SVI from multiple platforms (e.g., Mapillary and KartaView) efficiently, analyzing metadata of SVI, applying computer vision models to extract target features, transforming SVI into different projections (e.g., fish-eye and perspective) and different formats (e.g., depth map and point cloud), visualizing analyses with maps and plots, and exporting outputs to other software tools. We demonstrated its use in Singapore through a case study of data quality assessment and clustering analysis in a streamlined manner. Our software improves the transparency, reproducibility, and scalability of research relying on SVI and supports researchers in conducting urban analyses efficiently. Its modular design facilitates extensions of the package for new use cases. This package is openly available at https://***/koito19960406/ZenSVI, and it is supp

关键词： Open source software

Better, Not Just More: data-Centric Machine Learning for Earth Observation

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arXiv 2023年

作者： Roscher, Ribana Rußwurm, Marc Gevaert, Caroline Kampffmeyer, Michael dos Santos, Jefersson A. Vakalopoulou, Maria Hänsch, Ronny Hansen, Stine Nogueira, Keiller Prexl, Jonathan Tuia, Devis Data Science for Crop Systems Group Forschungszentrum Jülich GmbH Wilhelm-Johnen-Straße Jülich52428 Germany Remote Sensing Group University of Bonn Niebuhrstr. 1a Bonn53113 Germany Laboratory of Geo-information Science and Remote Sensing Wageningen University Droevendaalsesteeg 3 Wageningen Gelderland6708 PB Netherlands Department of Earth Observation Science Faculty ITC University of Twente Drienerlolaan 5 Enschede Overijssel7522 NB Netherlands Department of Physics and Technology UiT The Arctic University of Norway Klokkargårdsbakken 35 Tromsø9019 Norway Department of Computer Science University of Sheffield Sheffield City Centre 211 Portobello SheffieldS1 4DP United Kingdom Münchner Str. 20 Oberpfaffenhofen-Wessling82234 Germany Computing Science and Mathematics University of Stirling StirlingFK9 4LA United Kingdom Department of Aerospace Engineering University of the Bundeswehr Munich Werner-Heisenberg-Weg 39 Neubiberg Bavaria85579 Germany Ronquos 86 Sion1951 Switzerland

Recent developments and research in modern machine learning have led to substantial improvements in the geospatial field. Although numerous deep learning architectures and models have been proposed, the majority of them have been solely developed on benchmark datasets that lack strong real-world relevance. Furthermore, the performance of many methods has already saturated on these datasets. We argue that a shift from a model-centric view to a complementary data-centric perspective is necessary for further improvements in accuracy, generalization ability, and real impact on end-user applications. Furthermore, considering the entire machine learning cycle—from problem definition to model deployment with feedback—is crucial for enhancing machine learning models that can be reliable in unforeseen situations. This work presents a definition as well as a precise categorization and overview of automated data-centric learning approaches for geospatial data. It highlights the complementary role of data-centric learning with respect to model-centric in the larger machine learning deployment cycle. We review papers across the entire geospatial field and categorize them into different groups. A set of representative experiments shows concrete implementation examples. These examples provide concrete steps to act on geospatial data with data-centric machine learning approaches. © 2023, CC BY.

关键词： Deep learning

Satellite image catalog system improvement based on process innovation method

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AIP Conference Proceedings 2018年第1期1977卷

作者： Andie Setiyoko Ruci Meiyanti Nurbojatmiko Syamsudin Dana Indra Sensuse Handrie Noprisson 1Remote Sensing Technology and Data Centre LAPAN Indonesia 2e-Government and e-Business Research Lab Faculty of Computer Science University of Indonesia Indonesia 3Department of Information System Faculty of Computer Science Mercu Buana University Indonesia

Satellite imagery catalog system is developed for the user’s need regarding with the utilization of satellite imagery for various applications. The aim of the system development is the dissemination of data, particularly at the national scope. The system has been established and continuously operated until recently. In order to maintain the customer loyalty and to raise customer satisfaction, the system improvement is required. Based on user requirement analysis, the system should be improved in terms of three factors, i.e. transaction time, product derivations, and additional data processing service. The existing business process will be analyzed by adopting the system improvement. The process is categorized as business process improvement. The new version of business processes will be operated in the catalog system by applying the developed information system methods. Various methods classified as organizational-approach were analyzed in this research, and the most suitable method for improving the system is process innovation method, considering the urgent user need for regional development planning and rapid development of satellite imagery technology. The objective of this research was the improvement of satellite image catalog system by using the most suitable process innovation method for the case study. The expected result is to increase the time efficiency of satellite image data service and its processing.

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COSMOS2020: A panchromatic view of the universe to z ∼ 10 from two complementary catalogs

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arXiv 2021年

作者： Weaver, John R. Kauffmann, O.B. Ilbert, O. McCracken, H.J. Moneti, A. Toft, S. Brammer, G. Shuntov, M. Davidzon, I. Hsieh, B.C. Laigle, C. Anastasiou, A. Jespersen, C.K. Vinther, J. Capak, P. Casey, C.M. McPartland, C.J.R. Milvang-Jensen, B. Mobasher, B. Sanders, D.B. Zalesky, L. Arnouts, S. Aussel, H. Dunlop, J.S. Faisst, A. Franx, M. Furtak, L.J. Fynbo, J.P.U. Gould, K.M.L. Greve, T.R. Gwyn, S. Kartaltepe, J.S. Kashino, D. Koekemoer, A.M. Kokorev, V. Le Fèvre, O. Lilly, S. Masters, D. Magdis, G. Mehta, V. Peng, Y. Riechers, D.A. Salvato, M. Sawicki, M. Scarlata, C. Scoville, N. Shirley, R. Sneppen, A. Smolčić, V. Steinhardt, C. Stern, D. Tanaka, M. Taniguchi, Y. Teplitz, H.I. Vaccari, M. Wang, W.-H. Zamorani, G. Niels Bohr Institute University of Copenhagen Jagtvej 128 Copenhagen2200 Denmark Aix Marseille Univ CNRS LAM Laboratoire d’Astrophysique de Marseille Marseille France Institut d’Astrophysique de Paris UMR 7095 CNRS Sorbonne Université 98 bis boulevard Arago Paris75014 France Institute of Astrophysics & Astronomy Academia Sinica Taipei10617 Taiwan The University of Texas at Austin 2515 Speedway Blvd Stop C1400 AustinTX78712 United States Institute for Astronomy University of Hawaii 2680 Woodlawn Drive HonoluluHI96822 United States Department of Physics and Astronomy University of California Riverside 900 University Avenue RiversideCA92521 United States AIM UMR 7158 CEA CNRS Université Paris-Saclay Université Paris Diderot Sorbonne Paris Cité Gif-sur-YvetteF-91191 France Institute for Astronomy University of Edinburgh Royal Observatory EdinburghEH9 3HJ United Kingdom Infrared Processing and Analysis Center California Institute of Technology 1200 E. California Blvd PasadenaCA91125 United States Leiden Observatory Leiden University P.O.Box 9513 LeidenNL-2300 AA Netherlands DTU-Space Technical University of Denmark Elektrovej 327 Kgs. LyngbyDK2800 Denmark Department of Physics and Astronomy University College London Gower Place LondonWC1E 6BT United Kingdom Herzberg Astronomy and Astrophysics National Research Council of Canada 5071 West Saanich Rd. VictoriaBCV9E 2E7 Canada School of Physics and Astronomy Institute of Technology 84 Lomb Memorial Drive RochesterNY14623 United States Department of Physics ETH Zürich Wolfgang-Pauli-Strasse 27 Zurich8093 Switzerland Institute for Advanced Research Nagoya University Furocho Chikusa Aichi Nagoya464-8602 Japan Space Telescope Science Institute 3700 San Martin Dr. BaltimoreMD21218 United States Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive PasadenaCA91109 United States Institute for Astronomy Astrophysics Space Applications and Remo

The Cosmic Evolution Survey (COSMOS) has become a cornerstone of extragalactic astronomy. Since the last public catalog in 2015, a wealth of new imaging and spectroscopic data has been collected in the COSMOS field. This paper describes the collection, processing, and analysis of this new imaging data to produce a new reference photometric redshift catalog. Source detection and multi-wavelength photometry is performed for 1.7 million sources across the 2 deg2 of the COSMOS field, ∼966 000 of which are measured with all available broad-band data using both traditional aperture photometric methods and a new profile-fitting photometric extraction tool, The Farmer, which we have developed. A detailed comparison of the two resulting photometric catalogs is presented. Photometric redshifts are computed for all sources in each catalog utilizing two independent photometric redshift codes. Finally, a comparison is made between the performance of the photometric methodologies and of the redshift codes to demonstrate an exceptional degree of self-consistency in the resulting photometric redshifts. The i © 2021, CC BY.

关键词： Photometry

Authenticating the presence of a relativistic massive black hole binary in OJ 287 using its general relativity centenary flare: improved orbital parameters

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arXiv 2018年

作者： Dey, Lankeswar Valtonen, M.J. Gopakumar, A. Zola, S. Hudec, R. Pihajoki, P. Ciprini, S. Matsumoto, K. Sadakane, K. Kidger, M. Nilsson, K. Mikkola, S. Sillanpää, A. Takalo, L.O. Lehto, H.J. Berdyugin, A. Piirola, V. Jermak, H. Baliyan, K.S. Pursimo, T. Caton, D.B. Alicavus, F. Baransky, A. Blay, P. Boumis, P. Boyd, D. Torrent, M. Campas Campos, F. Gómez, J. Carrillo Chandra, S. Chavushyan, V. Dalessio, J. Debski, B. Drozdz, M. Er, H. Erdem, A. Pérez, A. Escartin Ramazani, V. Fallah Filippenko, A.V. Gafton, E. Ganesh, S. Garcia, F. Gazeas, K. Godunova, V. Pinilla, F. Gómez Gopinathan, M. Haislip, J.B. Harmanen, J. Hurst, G. Janík, J. Jelinek, M. Joshi, A. Kagitani, M. Karjalainen, R. Kaur, N. Keel, W.C. Kouprianov, V.V. Kundera, T. Kurowski, S. Kvammen, A. LaCluyze, A.P. Lee, B.C. Liakos, A. Lindfors, E. de Haro, J. Lozano Mugrauer, M. Nogues, R. Naves Neely, A.W. Nelson, R.H. Ogloza, W. Okano, S. Pajdosz-Smierciak, U. Pandey, J.C. Perri, M. Poyner, G. Provencal, J. Raj, A. Reichart, D.E. Reinthal, R. Reynolds, T. Saario, J. Sadegi, S. Sakanoi, T. González, J.-L. Salto Sameer Schweyer, T. Simon, A. Siwak, M. Alfaro, F.C. Soldán Sonbas, E. Steele, I. Stocke, J.T. Strobl, J. Tomov, T. Espasa, L. Tremosa Valdes, J.R. Pérez, J. Valero Verrecchia, F. Vasylenko, V. Webb, J.R. Department of Astronomy and Astrophysics Tata Institute of Fundamental Research Mumbai400005 India Finnish Centre for Astronomy with ESO University of Turku Finland Tuorla Observatory Department of Physics and Astronomy University of Turku Finland Astronomical Observatory Jagiellonian University ul. Orla 171 CracowPL-30-244 Poland Mt. Suhora Astronomical Observatory Pedagogical University ul. Podchorazych 2 CracowPL30-084 Poland Czech Technical University in Prague Faculty of Electrical Engineering Technicka 2 Prague166 27 Czech Republic Engelhardt Astronomical observatory Kazan Federal University Kremlyovskaya street 18 Kazan420008 Russia Department of Physics University of Helsinki Gustaf Hällströmin katu 2a HelsinkiFI-00560 Finland Space Science Data Center - Agenzia Spaziale Italiana via del Politecnico snc RomaI-00133 Italy Instituto Nazionale di Fisica Nucleare Sezione di Perugia PerugiaI-06123 Italy Astronomical Institute Osaka Kyoiku University 4-698 Asahigaoka Kashiwara Osaka582-8582 Japan Herschel Science Centre ESAC European Space Agency Villanueva de la CañadaMadrid28691 Spain Tuorla Observatory Department of Physics and Astronomy University of Turku Finland Astrophysics Research Institute Liverpool John Moores University IC2 Liverpool Science Park Brownlow HillL3 5RF United Kingdom Physical Research Laboratory Ahmedabad380009 India Nordic Optical Telescope Apartado 474 Santa Cruz de La PalmaE-38700 Spain Dark Sky Observatory Department of Physics and Astronomy Appalachian State University BooneNC28608 United States Department of Physics Faculty of Arts and Sciences Canakkale Onsekiz Mart University CanakkaleTR-17100 Turkey Astrophysics Research Center Ulupinar Observatory Canakkale Onsekiz Mart University TR-17100 Canakkale Turkey Astronomical Observatory of Taras Shevshenko National University of Kyiv Observatorna str. 3 Kyiv04053 Ukraine Valencian International University Valencia46002 Spain Institute for

Results from regular monitoring of relativistic compact binaries like PSR 1913+16 are consistent with the dominant (quadrupole) order emission of gravitational waves (GWs). We show that observations associated with the binary black hole central engine of blazar OJ 287 demand the inclusion of gravitational radiation reaction effects beyond the quadrupolar order. It turns out that even the effects of certain hereditary contributions to GW emission are required to predict impact flare timings of OJ 287. We develop an approach that incorporates this effect into the binary black hole model for OJ 287. This allows us to demonstrate an excellent agreement between the observed impact flare timings and those predicted from ten orbital cycles of the binary black hole central engine model. The deduced rate of orbital period decay is nine orders of magnitude higher than the observed rate in PSR 1913+16, demonstrating again the relativistic nature of OJ 287’s central engine. Finally, we argue that precise timing of the predicted 2019 impact flare should allow a test of the celebrated black hole "no-hair theorem" at the 10% level. Copyright © 2018, The Authors. All rights reserved.

关键词： Relativity

The enerMENA meteorological network – Solar radiation measurements in the MENA region

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AIP Conference Proceedings 2016年第1期1734卷

作者： D. Schüler S. Wilbert N. Geuder R. Affolter F. Wolfertstetter C. Prahl M. Röger M. Schroedter-Homscheidt G. Abdellatif A. Allah Guizani M. Balghouthi A. Khalil A. Mezrhab A. Al-Salaymeh N. Yassaa F. Chellali D. Draou P. Blanc J. Dubranna O. M. K. Sabry DLR German Aerospace Center Institute of Solar Research Plataforma Solar de Almeria 04200 Tabernas Spain CSP Services 04001 Almería Spain and 51143 Cologne Germany University of Applied Sciences Stuttgart Schellingstr. 24 70147 Stuttgart Germany Institut de Recherche en Energie Solaire et Energies Nouvelles IRESEN Rabat Morocco Centre de Recherches et des Technologies de l’Energie Technopole CRTEn Borj Cédria B.P N°95 - 2050 Hammam-Lif Tunisia Cairo University Faculty of Engineering Orman Giza Egypt Université Mohammed 1 Hay El Qods 60000 Oujda Morocco Mechanical Engineering Department Faculty of Engineering & Technology The University of Jordan Amman 11924 Jordan Centre de Developpement des Energies Renouvelables BP. 62 Route de l’Observatoire Bouzareah 16340 Algiers Algeria O.I.E. Centre Observation Impacts Energy MINES ParisTech PSL – Research University Rue Claude Daunesse CS 10207 06904 Sophia Antipolis cedex France New & Renewable Energy Authority NREA El Naga Street Nasr City Cairo Egypt DLR German Aerospace Center German Remote Sensing Data Center 82234 Wessling Germany

For solar resource assessment of solar power plants and adjustment of satellite data, high accuracy measurement data of irradiance and ancillary meteorological data is needed. For the MENA region (Middle East and Northern Africa), which is of high importance for concentrating solar power applications, so far merely 2 publicly available ground measurement stations existed (BSRN network). This gap has been filled by ten stations in Morocco, Algeria, Tunisia, Egypt and Jordan. In this publication the data quality is analyzed by evaluating data completeness and the cleanliness of irradiance sensors in comparison for all of the stations. The pyrheliometers have an average cleanliness of 99.2 % for week-daily cleaning. This is a 5 times higher effort than for Rotating Shadowband Irradiometer (RSI) stations which even have a slightly higher average cleanliness of 99.3 % for weekly cleaning. Furthermore, RSI stations show a data completeness of 99.4 % compared to 93.6 % at the stations equipped with thermal sensors. The results of this analysis are used to derive conclusions concerning instrument choice and are hence also applicable to other solar radiation measurements outside the enerMENA network. It turns out that RSIs are the more reliable and robust choice in cases of high soiling, rare station visits for cleaning and maintenance, as usual in desert sites. Furthermore, annual direct normal and global horizontal irradiation as well as average meteorological parameters are calculated for all of the stations.

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