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المؤلفون: Theradapuzha Mathew, Ninan, 1989, Svanberg, Mattias, Sjöholm, Jenny, Johansson, Björn, 1975
المصدر: BOOST – Big Data för industriell konkurrenskraft och uppkopplad smart industri 56th CIRP International Conference on Manufacturing Systems, CIRP CMS 2023, Cape Town, South Africa Procedia CIRP. 120:834-839
مصطلحات موضوعية: production planning and scheduling, ETO, rescheduling, engineer-to-order, one-of-a-kind, replanning, flexibility, resilient manufacturing systems
وصف الملف: electronic
الوصول الحر: https://research.chalmers.se/publication/539940Test
https://research.chalmers.se/publication/539940/file/539940_Fulltext.pdfTest -
2دورية أكاديمية
المؤلفون: Chiheng Dang, Hongbo Zhang, Congcong Yao, Dengrui Mu, Fengguang Lyu, Yu Zhang, Shuqi Zhang
المصدر: Agricultural Water Management, Vol 291, Iss , Pp 108643- (2024)
مصطلحات موضوعية: Irrigation water requirement, Bias correction, ETo, LSTM, QTM, Agriculture (General), S1-972, Agricultural industries, HD9000-9495
وصف الملف: electronic resource
العلاقة: http://www.sciencedirect.com/science/article/pii/S0378377423005085Test; https://doaj.org/toc/1873-2283Test
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3دورية أكاديمية
المؤلفون: Khalid Hamad, Sujith Konan
المصدر: Arthroplasty, Vol 4, Iss 1, Pp 1-5 (2022)
مصطلحات موضوعية: ETO, Extended trochanteric osteotomy, Revision hip arthroplasty, ETO union rate, Aseptic loosening, Prosthetic joint infection, Orthopedic surgery, RD701-811
وصف الملف: electronic resource
العلاقة: https://doaj.org/toc/2524-7948Test
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4دورية أكاديمية
المؤلفون: Silva, Lucas Augusto Pereira, souza, Cristiano Marcelo Pereira de, Silva, Claudionor Ribeiro, Filgueiras, Roberto, Sena-Souza, João Paulo, Fernandes Filho, Elpídio Inácio, Leite, Marcos Esdras
المساهمون: FAPEMIG, CAPES, CNPQ
المصدر: Brazilian Journal of Physical Geography; v. 16, n. 2 (2023): Revista Brasileira de Geografia Fisica; 1001-1012 ; Revista Brasileira de Geografia Física; v. 16, n. 2 (2023): Revista Brasileira de Geografia Fisica; 1001-1012 ; 1984-2295
مصطلحات موضوعية: Geoprocessamento, Cubist, Spatial Prediction, ETo, Semiarid zone and Brazil, Environmental Monitoring
جغرافية الموضوع: Semiárido Brasileiro, Futuro
وصف الملف: application/pdf
العلاقة: https://periodicos.ufpe.br/revistas/rbgfe/article/view/256247/43770Test; https://periodicos.ufpe.br/revistas/rbgfe/article/downloadSuppFile/256247/42411Test; https://periodicos.ufpe.br/revistas/rbgfe/article/downloadSuppFile/256247/42412Test; Althoff, D., Bazame, H.C., Filgueiras, R., Dias, S.H.B., 2018. Heuristic methods applied in reference evapotranspiration modeling. Ciência e Agrotecnologia 42, 314–324. Althoff, D., Dias, S.H.B., Filgueiras, R., Rodrigues, L.N., 2020. ETo‐Brazil: A Daily Gridded Reference Evapotranspiration Data Set for Brazil (2000–2018). Water Resources Research 56, 1–24. https://doi.org/10.1029/2020WR027562Test. Breiman, L., 2001. Random forests. Machine learning 45, 5–32. Burrell, A.L., Evans, J.P., De Kauwe, M.G., 2020. Anthropogenic climate change has driven over 5 million km2 of drylands towards desertification. Nat Commun 11, 3853. https://doi.org/10.1038/s41467-020-17710-7Test Castro Oliveira, G., Arruda, D.M., Fernandes Filho, E.I., Veloso, G.V., Francelino, M.R., Schaefer, C.E.G.R., 2021. Soil predictors are crucial for modelling vegetation distribution and its responses to climate change. Science of The Total Environment 146680. https://doi.org/10.1016/j.scitotenv.2021.146680Test. Costa, J.F.C.B., Silva, R.M., Santos, C.A.G., Silva, A.M., Vianna, P.C.G., 2021. Analysis of the response of the Epitácio Pessoa reservoir (Brazilian semi-arid region) to potential future drought, water transfer and LULC scenarios. Natural Hazards 1–25. https://dx.doi.org/10.1007/s11069-021-04736-3Test. Cunha, A.P.M., Alvalá, R.C., Nobre, C.A., Carvalho, M.A., 2015. Monitoring vegetative drought dynamics in the Brazilian semi-arid region. Agricultural and forest meteorology 214, 494–505. https://doi.org/10.1016/j.agrformet.2015.09.010Test. Del Cerro, R.T.G., Subathra, M.S.P., Kumar, N.M., Verrastro, S., George, S.T., 2021. Modelling the daily reference evapotranspiration in semi-arid region of South India: A case study comparing ANFIS and empirical models. Information Processing in Agriculture 8, 173–184. https://dx.doi.org/10.1016/j.inpa.2020.02.003Test. Dias, H.B., Sentelhas, P.C., 2021. Assessing the performance of two gridded weather data for sugarcane crop simulations with a process-based model in Center-South Brazil. International Journal of Biometeorology 1–13. https://dx.doi.org/10.1007/s00484-021-02145-6Test. Dias, S.H.B., Filgueiras, R., Fernandes Filho, E.I., Arcanjo, G.S., Silva, G.H. da, Mantovani, E.C., Cunha, F.F. da, 2021. Reference evapotranspiration of Brazil modeled with machine learning techniques and remote sensing. Plos one 16, e0245834. https://dx.doi.org/10.1371/journal.pone.0245834Test. Fan, J., Wu, L., Zhang, F., Xiang, Y., Zheng, J., 2016. Climate change effects on reference crop evapotranspiration across different climatic zones of China during 1956–2015. Journal of Hydrology 542, 923–937. https://doi.org/10.1016/j.jhydrol.2016.09.060Test. Fick, S.E. and R.J. Hijmans, 2017. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37 (12): 4302-4315. Gao, W., Zheng, C., Liu, X., Lu, Y., Chen, Y., Wei, Y., Ma, Y., 2022. NDVI-based vegetation dynamics and their responses to climate change and human activities from 1982 to 2020: A case study in the Mu Us Sandy Land, China. Ecological Indicators 137, 108745. Gomes, L.C., Faria, R.M., Souza, E., Veloso, G.V., Schaefer, C.E.G.R., Fernandes-Filho, E.I., 2019. Modelling and mapping soil organic carbon stocks in Brazil. Geoderma 340, 337–350. https://doi.org/10.1016/j.geoderma.2019.01.007Test Grünzweig, J.M., Boeck, H.J., Rey, A., Santos, M.J., Adam, O., Bahn, M., Belnap, J., Deckmyn, G., Dekker, S.C., Flores, O., 2022. Dryland mechanisms could widely control ecosystem functioning in a drier and warmer world. Nature Ecology & Evolution 1–13. Hausfather, Z., Marvel, K., Schmidt, G.A., Nielsen-Gammon, J.W., Zelinka, M., 2022. Climate simulations: Recognize the ‘hot model’problem. Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G., Jarvis, A., 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology: A Journal of the Royal Meteorological Society 25, 1965–1978. https://doi.org/10.1002/joc.1276Test. Houborg, R., McCabe, M.F., 2018. A hybrid training approach for leaf area index estimation via Cubist and random forests machine-learning. ISPRS Journal of Photogrammetry and Remote Sensing 135, 173–188. Huang, J., Ji, M., Xie, Y., Wang, S., He, Y., Ran, J., 2016. Global semi-arid climate change over last 60 years. Climate Dynamics 46, 1131–1150. https://doi.org/10.1007/s00382-015-2636-8Test. Jiang, F., Xie, X., Liang, S., Wang, Y., Zhu, B., Zhang, X., Chen, Y., 2021. Loess Plateau evapotranspiration intensified by land surface radiative forcing associated with ecological restoration. Agricultural and Forest Meteorology 311, 108669. Kang, Z., Qiu, B., Xiang, Z., Liu, Y., Lin, Z., Guo, W., 2022. Improving simulations of vegetation dynamics over the Tibetan Plateau: Role of atmospheric forcing data and spatial resolution. Advances in Atmospheric Sciences 39, 1115–1132. Kim, J., Choi, J., Choi, C., Park, S., 2013. Impacts of changes in climate and land use/land cover under IPCC RCP scenarios on streamflow in the Hoeya River Basin, Korea. Science of the Total Environment 452, 181–195. https://doi.org/10.1016/j.scitotenv.2013.02.005Test. Kuhn, M., Johnson, K., 2013. Applied predictive modeling. Springer. https://dx.doi.org/10.1007/978-1-4614-6849-3Test. Kuhn, M., Quinlan, R., 2018. Cubist: Rule-and instance-based regression modeling. R package version 0.2. 2. Kuhn, M., Wing, J., Weston, S., Williams, A., Keefer, C., Engelhardt, A., Cooper, T., Mayer, Z., Kenkel, B., Team, R.C., 2020. Package ‘caret.’ The R Journal 223, 7. Leal Filho, W., Totin, E., Franke, J.A., Andrew, S.M., Abubakar, I.R., Azadi, H., Nunn, P.D., Ouweneel, B., Williams, P.A., Simpson, N.P., 2022. Understanding responses to climate-related water scarcity in Africa. Science of the Total Environment 806, 150420. Li, M., Chu, R., Sha, X., Islam, A.R.M.T., Jiang, Y., Shen, S., 2022. How Has the Recent Climate Change Affected the Spatiotemporal Variation of Reference Evapotranspiration in a Climate Transitional Zone of Eastern China? ISPRS International Journal of Geo-Information 11, 300. Liu, Y., Yao, X., Wang, Q., Yu, J., Jiang, Q., Jiang, W., Li, L., 2021. Differences in reference evapotranspiration variation and climate-driven patterns in different altitudes of the Qinghai–Tibet plateau (1961–2017). Water 13, 1749. Marengo, J.A., Galdos, M.V., Challinor, A., Cunha, A.P., Marin, F.R., Vianna, M. dos S., Alvala, R.C., Alves, L.M., Moraes, O.L., Bender, F., 2022. Drought in Northeast Brazil: A review of agricultural and policy adaptation options for food security. Climate Resilience and Sustainability 1, e17. Milborrow, S., Tibshirani, R., 2019. Package ‘earth’: Multivariate Adaptive Regression Splines. Nooni, I.K., Hagan, D.F.T., Wang, G., Ullah, W., Lu, J., Li, S., Dzakpasu, M., Prempeh, N.A., Lim Kam Sian, K.T., 2021. Future Changes in Simulated Evapotranspiration across Continental Africa Based on CMIP6 CNRM-CM6. International Journal of Environmental Research and Public Health 18, 6760. Núñez-López, J.M., Cansino-Loeza, B., Sánchez-Zarco, X.G., Ponce-Ortega, J.M., 2022. Involving resilience in assessment of the water–energy–food nexus for arid and semi-arid regions. Clean Technologies and Environmental Policy 1–13. Oliver, M.A., Webster, R. (1990). Kriging: a method of interpolation for geographical information systems. International Journal of Geographical Information System, 4(3), 313-332. Orimoloye, I.R., Belle, J.A., Orimoloye, Y.M., Olusola, A.O., Ololade, O.O., 2022. Drought: A common environmental disaster. Atmosphere 13, 111. Pielke Jr, R., Burgess, M.G., Ritchie, J., 2022. Plausible 2005–2050 emissions scenarios project between 2° C and 3° C of warming by 2100. Environmental Research Letters 17, 024027. Rodriguez, P.P., Gianola, D., 2016. BRNN: Bayesian regularization for feed-forward neural networks. R package version 0.6. Salas-Martínez, F., Valdés-Rodríguez, O.A., Palacios-Wassenaar, O.M., Márquez-Grajales, A., 2021. Analysis of the Evolution of Drought through SPI and Its Relationship with the Agricultural Sector in the Central Zone of the State of Veracruz, Mexico. Agronomy 11, 2099. Santos, T.G., Battisti, R., Casaroli, D., Alves, J., Evangelista, A.W.P., 2021. Assessment of agricultural efficiency and yield gap for soybean in the Brazilian Central Cerrado biome. Bragantia 80, 1–11. https://doi.org/10.1590/1678-4499.20200352Test. Scott, R.L., Biederman, J.A., Hamerlynck, E.P., Barron‐Gafford, G.A., 2015. The carbon balance pivot point of southwestern US semi-arid ecosystems: Insights from the 21st century drought. Journal of Geophysical Research: Biogeosciences 120, 2612–2624. Shi, L., Feng, P., Wang, B., Liu, D.L., Yu, Q., 2020. Quantifying future drought change and associated uncertainty in southeastern Australia with multiple potential evapotranspiration models. Journal of Hydrology 590, 125394. https://doi.org/10.1016/j.jhydrol.2020.125394Test Silveira, S.M.B., Silva, M.G., 2019. Conflitos socioambientais por água no Nordeste brasileiro: expropriações contemporâneas e lutas sociais no campo. Revista Katálysis 22, 342–352. Souza, C.M.P., Veloso, G.V., Mello, C.R., Ribeiro, R.P., Silva, L.A.P., Leite, M.E., Fernandes Filho, E.I., 2022. Spatiotemporal prediction of rainfall erosivity by machine learning in southeastern Brazil. Geocarto International 1–19. https://doi.org/10.1080/10106049.2022.2060318Test Silva, C., Teixeira, A.C., Manzione, R., 2020. Utilização de Redes Neurais com Regularização Bayesiana na Modelagem de Evapotranspiração de Referência em Agroecossistemas Semiáridos. Revista Brasileira de Engenharia de Biossistemas 14, 73–84. Van Vuuren, D.P., Riahi, K., Calvin, K., Dellink, R., Emmerling, J., Fujimori, S., Kc, S., Kriegler, E., O’Neill, B., 2017. The Shared Socio-economic Pathways: Trajectories for human development and global environmental change. Global Environmental Change 42, 148–152. https://doi.org/10.1016/j.gloenvcha.2016.10.009Test Wendt, K.A., Häuselmann, A.D., Fleitmann, D., Berry, A.E., Wang, X., Auler, A.S., Cheng, H., Edwards, R.L., 2019. Three-phased Heinrich Stadial 4 recorded in NE Brazil stalagmites. Earth and Planetary Science Letters 510, 94–102. https://doi.org/10.1016/j.epsl.2018.12.025Test.; Wu, T., Zhang, W., Jiao, X., Guo, W., Hamoud, Y.A., 2021. Evaluation of stacking and blending ensemble learning methods for estimating daily reference evapotranspiration.Computers and Electronics in Agriculture 184, 106039. https://doi.org/10.1016/j.compag.2021.10603Test Xavier, A.C., King, C.W., Scanlon, B.R., 2016. Daily gridded meteorological variables in Brazil (1980–2013). International Journal of Climatology 36, 2644–2659. https://doi.org/10.1002/joc.4518Test. Xing, X., Qian, J., Chen, X., Chen, C., Sun, J., Wei, S., Yimamaidi, D., Zhanar, Z., 2022. Analysis of Effects of Recent Changes in Hydrothermal Conditions on Vegetation in Central Asia. Land 11, 327. Yoo, J., Kwon, H.-H., Lee, J.-H., Kim, T.-W., 2016. Influence of evapotranspiration on future drought risk using bivariate drought frequency curves. KSCE Journal of Civil Engineering 20, 2059–2069. https://doi.org/10.1007/s12205-015-0078-9Test. Zhang, G., Gan, T.Y., Su, X., 2022. Twenty-first century drought analysis across China under climate change. Climate Dynamics 59, 1665–1685.; https://periodicos.ufpe.br/revistas/rbgfe/article/view/256247Test
الإتاحة: https://doi.org/10.26848/rbgf.v16.2.p1001-1012Test
https://doi.org/10.1029/2020WR027562Test
https://doi.org/10.1016/j.compag.2021.10603Test
https://periodicos.ufpe.br/revistas/rbgfe/article/view/256247Test -
5دورية أكاديمية
المؤلفون: Petros Ismailidis, Annegret Mündermann, Karl Stoffel
المصدر: Journal of Clinical Medicine; Volume 12; Issue 8; Pages: 2947
مصطلحات موضوعية: extended trochanteric osteotomy, ETO, trochanteric escape, revision total hip arthroplasty
وصف الملف: application/pdf
العلاقة: Orthopedics; https://dx.doi.org/10.3390/jcm12082947Test
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6دورية أكاديمية
المصدر: Revista de Gestão de Água da América Latina, Vol 19, Iss 2022 (2022)
مصطلحات موضوعية: Evapotranspiração diária, ETo, Penman-Monteith., Hydraulic engineering, TC1-978, Environmental technology. Sanitary engineering, TD1-1066
وصف الملف: electronic resource
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7دورية أكاديمية
المؤلفون: Rodrigues, Thiago F., Cunha, Fernando F. da, Silva, Gustavo H. da, Condé, Saulo B., Silva, Francisco C. dos S.
المصدر: Advances in Weed Science. January 2021 39
مصطلحات موضوعية: Crop coefficient – Kc, ETo, Evapotranspiration, Drainage lysimeter, Vegetation index
وصف الملف: text/html
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8دورية أكاديمية
المؤلفون: Bartosz CIESLA, Janusz MLECZKO
المصدر: Applied Computer Science, Vol 17, Iss 1, Pp 17-25 (2021)
مصطلحات موضوعية: production control, smes, eto, mass customization, fuzzy logic, Information technology, T58.5-58.64, Electronic computers. Computer science, QA75.5-76.95
وصف الملف: electronic resource
العلاقة: http://acs.pollub.pl/pdf/v17n1/2.pdfTest; https://doaj.org/toc/1895-3735Test; https://doaj.org/toc/2353-6977Test
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9دورية أكاديمية
المصدر: Revista Ingeniería UC, Vol 28, Iss 3 (2021)
مصطلحات موضوعية: dosis de riego, Kc, frijol Canario Centenario, ETc, ETo, Engineering (General). Civil engineering (General), TA1-2040, Technology (General), T1-995
وصف الملف: electronic resource
العلاقة: https://revistascientificasuc.org/index.php/revinguc/article/view/44Test; https://doaj.org/toc/1316-6832Test; https://doaj.org/toc/2610-8240Test
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10دورية أكاديمية
المؤلفون: Yanhui Jia, Xiaojun Shen, Ruochen Yi, Ni Song
المصدر: Agriculture, Vol 12, Iss 9, p 1380 (2022)
مصطلحات موضوعية: climate change, ETo, yield response factor, irrigation water requirement, cotton, Xinjiang, Agriculture (General), S1-972
وصف الملف: electronic resource