Search Results - "learning"

Farm machinery use and the agricultural machinery industries in India: Status, evolution, implications, and lessons learned by Bhattarai, Madhusudan, Singh, Gajendra, Takeshima, Hiroyuki, Shekhawat, Ravindra S.

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Implementer-Led Evaluation and Learning (IMPEL) evaluation of SPIR II RFSA - Midline survey report by Gilligan, Daniel O., Hirvonen, Kalle, Leight, Jessica, Tesfaye, Haleluya

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Bounded learning-by-doing and sources of firm level productivity growth in colombian food manufacturing industry by Shee, Apurba, Stefanou, Spiro E.

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Lessons learned from the evaluation of Helen Keller International’s enhanced homestead food production program by Olney, Deanna K., Dillon, Andrew, Ruel, Marie T., Nielsen, Jennifer

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Using participatory learning and action to empower women’s groups to improve feeding practices in Madhya Pradesh by Kanani, Shubhada, Singh, Rachna, Baqar, Syed, Mahajan, Uma, Belwal, L.M.

“…Participatory learning and action (PLA) is a promising approach to promote infant and young children feeding (IYCF) and other health, nutrition, water sanitation, and hygiene (HNWASH) practices. …”
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Female social networks and learning about a new technology in eastern Uttar Pradesh, India by Magnan, Nicholas, Spielman, David J., Gulati, Kajal

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Selecting sites to prove the concept of IAR4D in the Lake Kivu Pilot Learning Site by Farrow, Andrew, Opondo, Chris, Rao, K. P. C., Tenywa, Moses, Njeru, Rose, Kashaija, Imelda, Kamugisha, Rick, Ramazani, Michel, Nkonya, Ephraim M., Kayiranga, Didace, Lubanga, Lunze, Nabahungu, Leon, Kamale, Kambale, Mugabo, Josaphat, Mutabazi, Sunday

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Adaptive e-learning to improve dietary behaviour: A systematic review and cost-effectiveness analysis by Harris, Jody, Felix, L., Miners, A., Murray, E., Michie, S., Ferguson, Elaine L., Free, C., Lock, K., Landon, J., Edwards, P.

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Do crowded classrooms crowd out learning?: evidence from the Food for Education Programme in Bangladesh by Ahmed, Akhter, Arends-Kuenning, Mary

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Do crowded classrooms crowd out learning?: evidence from the Food for Education Programme in Bangladesh by Ahmed, Akhter, Arends-Kuenning, Mary

“…The concern that learning performance may be adversely affected by increased class size appears to be unfounded. …”
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Do crowded classrooms crowd out learning?: evidence from the Food for Education Programme in Bangladesh by Ahmed, Akhter, Arends-Kuenning, Mary

“…The concern that learning performance may be adversely affected by increased class size appears to be unfounded. …”
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Theory of Change for five learning labs - vegetable and maize-legume cropping systems in Ethiopia and Kenya by Nchanji, Eileen, Cosmas, Lutomia, Ketema, Dessalegn, Ayuya, Oscar, Nyamolo, Victor, Jong, Arnold

“…A comprehensive ToC is driven by analysis of current program implementation, consultation with key stakeholders and learning what works and what does not for the target groups.…”
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AI-powered high-throughput phenotyping of seed yield in Urochloa: a deep learning approach by Arrechea Castillo, Darwin Alexis, Espitia Buitrago, Paula, Arboleda, Ronald David, Florian Vargas, David, Jauregui, Rosa Noemi, Cardoso, Juan Andres

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Social learning, neighborhood effects, and investment in human capital: evidence from Green-Revolution India by Yamauchi, Futoshi

Subjects: “…social learning…”
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Social learning, neighborhood effects, and investment in human capital: evidence from Green-Revolution India by Yamauchi, Futoshi

Subjects: “…social learning…”
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Identification of influential weather parameters and seasonal drought prediction in Bangladesh using machine learning algorithm by Al Mamun, Md. Abdullah, Sarker, Mou Rani, Sarkar, Md. Abdur Rouf, Roy, Sujit Kumar, Nihad, Sheikh Arafat Islam, McKenzie, Andrew M., Hossain, Md. Ismail, Kabir, Md. Shahjahan

“…With a period of forty years (1981–2020) of weather data, sophisticated machine learning (ML) methods were employed to classify 35 agroclimatic regions into dry or wet conditions using nine weather parameters, as determined by the Standardized Precipitation Evapotranspiration Index (SPEI). …”
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Automated machine learning: A case study of genomic "image-based" prediction in maize hybrids by Galli, Giovanni, Sabadin, Felipe, Yassue, Rafael Massahiro, Galves, Cassia, Carvalho, Humberto Fanelli, Crossa, José, Montesinos-López, Osval Antonio, Fritsche-Neto, Roberto

“…Machine learning methods such as multilayer perceptrons (MLP) and Convolutional Neural Networks (CNN) have emerged as promising methods for genomic prediction (GP). …”
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Report on the monitoring, evaluation, learning and impact assessment (MELIA) of the circular bioeconomy innovation hub in Ghana by Amoah, P, Drechsel, Pay

Subjects: “…learning…”
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Event rewind: Learning support for a multi-country climate resilience programme for food security by Hassain, Arif, van Gilst, Daniel, Leight, Jessica, de Brauw, Alan, Laderach, Peter, Mekuria, Wolde, Kamau, David, Grassini, Christian, Philip, Serene, Timothy, Adeyinka Jacob, Ochuma, Lynett, Kosec, Katrina, Gilligan, Daniel O., Ruckstuhl, Sandra

“…Organized by CGIAR with support from World Food Programme (WFP) and The Norwegian Agency for Development Cooperation (Norad) The Learning Support for a Sub-Saharan Africa Multi-Country Climate Resilience Program for Food Security, launched in 2023, aims to enhance food security and climate resilience across 14 African countries. …”
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Knowledge centers in the Pilot Learning Woradas of Improving Productivity and Market Success Project: Utilization, relevance by Lemma, T., Sehai, Ermias, Hoekstra, Dirk

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