IDENTIFYING KNOWLEDGE BASE DEFICIENCIES BY OBSERVING USER BEHAVIOR11This work was supported in part by the Learning System Pilot Aiding contract from the Wright Research and Development Center (Contract Number F33615-88-C-1739). We are pleased to acknowledge the support of our technical monitor, Mr. Gurdial Saini, and our previous technical monitor Captain John Ferrante. We have also benefitted from the assistance of Tim Ayers, Becky Burnard, Gary Edwards, Norm Geddes, John Halpin, Belinda Hoshstrasser, Mark Hoffmann, Leila Johnannesen, David M. Smith, Tim Whiffen and Ed Wisniewski; and from the advice of Jerry DeJong, John Laird, Paul Scott, and David C. Wilkins.

Author(s):  
Keith R. Levi ◽  
Valerie L. Shalin ◽  
David L. Perschbacher
2021 ◽  
Author(s):  

Knowledge management is vital to successfully executing research and development programs within the U.S. Army Engineer Research and Development Center (ERDC). Experimental knowledge management initiatives over the years led to discoveries about the best ways to store and access ERDC’s vast knowledge base. This document highlights several of the effective knowledge management tools that evolved from these discoveries, helping you to find and share knowledge!


2018 ◽  
Vol 1 (29) ◽  
pp. 72-81
Author(s):  
Hop Van Nguyen ◽  
Tinh Huu Nguyen ◽  
Hoa Van Tran ◽  
Kinh Van La

The objective of the study is to compare the practical results with the predicted results by Crossbreeding Effects (CBE) software on pig crossbred based on daily gain, backfat thickness and feed conversion ratio. Another purpose of this study is to predict those three traits among some expected hybridization. This research was conducted on pig farm at Binh Thang Research and Development center from 2013 to 2017. In this study, for each pair of purebred Duroc and Pietrain, Duroc and Landrace, Pietrain and Landrace, twelve hybridizations were analyzed, nine unhybridizations were predicted by CBE software. The results showed that there was no significant difference between the predicted and actual data. With some unhybridization crossbred , the predictions showed high reliability (P<0.05). Based on the predicted data of CBE software , some traits of the crossbred animals would not be improved, therefore, it was not necessary to conduct these hybridizations


2008 ◽  
Vol 43 (6) ◽  
pp. 781-782 ◽  
Author(s):  
Rogério Faria Vieira ◽  
José Eustáquio Souza Carneiro ◽  
Trazilbo José de Paula Júnior ◽  
Roberto Fontes Araújo

Mungbean cultivar MGS Esmeralda was developed by Asian Vegetable Research and Development Center (Shanhua, Taiwan), as a result of crossing between the lines VC 1973A and VC 2768A. In ten trials conducted in the State of Minas Gerais, Brazil, it produced 13.5% more grains than 'Ouro Verde MG-2' (control cultivar), and its highest yield was 2,550 kg ha-1. The cultivar MGS Esmeralda is more susceptible to lodging, and its pods mature more uniformly than Ouro Verde MG-2 pods. One hundred-seed mass of 'MGS Esmeralda' ranged between 5.5 and 6.8 g. Both cultivars are susceptible to powdery mildew and cercospora leaf spot.


2021 ◽  
Vol 905 (1) ◽  
pp. 011002

All papers published in this volume of IOP Conference Series: Earth and Environmental Science have been peer-reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Double-blind with the opportunity to resubmit after revisions • Conference submission management system: Microsoft’s Conference Management Toolkit (Microsoft CMT). The submission url is https://cmt3.research.microsoft.com/User/Login?ReturnUrl=%2FICSAE2021 • Number of submissions received: 224 • Number of submissions sent for review: 198 • Number of submissions accepted: 148 • Acceptance Rate (Number of Submissions Accepted/Number of Submissions Received X 100): 66.07% • Average number of reviews per paper: 2 • Total number of reviewers involved: 18 • Any additional info on the review process: all papers were checked for its similarity using Turnitin, and 25% similar was set as maximum threshold. • Contact person for queries: Name: Prof. Sri Hartati Affiliation: Research and Development Center for Biotechnology and Biodiversity (P3BB) Universitas Sebelas Maret Email: [email protected]


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