01422aam 2200373I 450 991071021170332120160318082757.0GOVPUB-C13-3467b2f26b6a71b1500ad1d6ff2885b3(CKB)5470000002477174(OCoLC)945070823(EXLCZ)99547000000247717420160318d1983 ua 0engrdacontentrdamediardacarrierRecommended practice for measuring net benefits and internal rates of return for investments in buildings and building systems /Harold E. MarshallGaithersburg, MD :U.S. Dept. of Commerce, National Institute of Standards and Technology,1983.1 online resourceNBSIR ;83-26571983.Contributed record: Metadata reviewed, not verified. Some fields updated by batch processes.Title from PDF title page.Includes bibliographical references.Marshall Harold E1389866Marshall Harold E1389866United States.National Bureau of Standards.NBSNBSGPOBOOK9910710211703321Recommended practice for measuring net benefits and internal rates of return for investments in buildings and building systems3532711UNINA03888nam 22006975 450 991098332800332120250107115225.09783031786570303178657210.1007/978-3-031-78657-0(CKB)37155876700041(DE-He213)978-3-031-78657-0(MiAaPQ)EBC32007795(Au-PeEL)EBL32007795(OCoLC)1483759196(EXLCZ)993715587670004120250107d2025 u| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierNile Water Conflict and the Grand Ethiopian Renaissance Dam /by Wossenu Abtew1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Springer,2025.1 online resource (XVIII, 191 p. 110 illus., 81 illus. in color.) Springer Geography,2194-31689783031786563 3031786564 Introduction and Overview of the Nile Basin -- The Nile Basin and Water Stress -- Rainfed Agriculture and Climate Change in the Nile Basin -- Climate Change and the Nile Basin -- The Grand Ethiopian Renaissance Dam (GERD) Site and Ethiopian Ethnic Politics -- Grand Ethiopian Renaissance Dam (GERD) Negotiations -- TThe Grand Ethiopian Renaissance Dam (GERD) Filling and Operation -- The Hydro-Politics of Green, Blue, Virtual Water and Water Footprint in the Nile Basin -- The Everglades Drainage: A Lesson for Regional Wetlands -- The Sudd Marshes: A Threat to Regional Wetland Drainage.The book follows on from “The Grand Ethiopian Renaissance Dam on the Blue Nile” GERD. It will have a good background introduction on the Nile basin. The value of Nile water will be presented in view of the global water stress facing mankind and the region. International importance of Nile waters will be presented with food insecurity of regions outside the basin. Food and energy demand in the upper basin and potential upstream irrigation demand on Nile waters will be presented. Analysis of the GERD three years of filling, remaining filling years, and modes of operation will be presented along with the water conflict. Climate change and climate variation (droughts and floods) impacts on the water control of 56 percent of the Nile flow (the Blue Nile and the GERD), and ensuing water war require analysis and publication. One of the major features of the Nile is the Sudd marshes in South Sudan. The importance of wetlands in the hydroclimate of the Nile basin and the merit and demerits of draining the Sudd, to get more water on the short term, will be presented. The Everglades in the United States will be presented as a global experience in regional wetland drainage and its impact on regional hydroclimate.Springer Geography,2194-3168WaterHydrologyEnvironmental managementEnergy policyEnergy policyWater-powerWaterEnvironmental ManagementEnergy Policy, Economics and ManagementHydroenergyWater.Hydrology.Environmental management.Energy policy.Energy policy.Water-power.Water.Environmental Management.Energy Policy, Economics and Management.Hydroenergy.551.48Abtew Wossenuauthttp://id.loc.gov/vocabulary/relators/aut979421MiAaPQMiAaPQMiAaPQBOOK9910983328003321Nile Water Conflict and the Grand Ethiopian Renaissance Dam4317548UNINA06300nam 22006615 450 99666035860331620250513130314.03-031-92744-310.1007/978-3-031-92744-7(CKB)38776276600041(DE-He213)978-3-031-92744-7(MiAaPQ)EBC32110183(Au-PeEL)EBL32110183(OCoLC)1524424145(EXLCZ)993877627660004120250513d2025 u| 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierRough Sets International Joint Conference, IJCRS 2025, Chongqing, China, May 11–13, 2025, Proceedings, Part II /edited by Qinghua Zhang, Christopher Henry, Richard Jensen, Xinbo Gao, Guoyin Wang, JingTao Yao, Chris Cornelis, Shuyin Xia1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Springer,2025.1 online resource (XIX, 454 p. 146 illus., 78 illus. in color.) Lecture Notes in Artificial Intelligence,2945-9141 ;157093-031-92743-5 -- Rough Set Applications. -- Comparison of Complexity of Regular and Oblivious Decision Trees for Decision Tables from Closed Classes. -- Applying Rough Set based Feature Selection Method to Spam Classification. -- What Is Inside Agent Brain: Application of Learning from Examples Using Rough Sets (LEM2) Rule Induction Algorithm to Explain Actions of Vision based Machine Learning Agents Trained with Proximal Policy Optimization. -- Quick Neighborhood Rough Set for Hierarchical Classification. -- (θ，θ*) Operator Driven Intuitionistic Fuzzy Matrix Composite Operation and Its Optimal Application in Medical Diagnosis. -- User and Item sub contexts Induced Fuzzy Concept Set for Recommendation. -- Rough Set Theory Applied to Feature Selection. -- Fusing Land Use Knowledge with Multi granularity Temporal and Spatial Dependencies for Traffic Accident Prediction. -- A Hybrid Multi attribute Group Decision making Method Using Normal Cloud Model and Multi granularity Information. -- Anomaly Detection Using Fuzzy Information Entropy for Incomplete Data. -- Feature Selection and Knowledge Discovery. -- Feature Selection Based on Cross Neighborhood Granular Ball Layer. -- A Dynamic Unsupervised Feature Selection Method Based on Information Sets and Fuzzy Rough Sets. -- Distance guided Pseudo Label Graph Clustering Network. -- Robust Feature Selection Based on Intuitionistic Hesitant Fuzzy Cross Correlation and Manifold Learning. -- Adaptive Correlation Incorporated Latent Feature Analysis for Online Sparse Streaming Feature Selection. -- Accelerated Feature Selection Based on Granular ball Rough Sets. -- Online Multi label Stream Feature Selection Based on Neighborhood Approximation Error Rate and Label Correlation. -- Cross view Fuzziness and Intra view Uncertainty based Weight Reconstruction for Multi view Feature Selection. -- Finding Consistent Pairwise Comparisons with Genetic Algorithms. -- Multi view Unsupervised Feature Selection Guided by Diversity and Consensus Structure. -- Cognitive Computing. -- Legal Similar Case Retrieval Model Based on Concept Tree and Optimal Transport. -- Enhancing Knowledge Tracing via Random Layer wise Adversarial Training. -- Incomplete Multi view Clustering Based on Joint Concept Decomposition and Anchor Graph Learning. -- Frequency sensitive Sparse Transformer with Multi Granularity Refinement Network for Image Restoration. -- TSKE: A Dual Branch Model for Knowledge Graph Embedding with Joint Textual and Structural Information. -- Efficient Local Causal Structure Learning with Privacy Preservation. -- The Connections Between Approximate Three way Concept Lattice and Three way Approximate Concept Lattices. -- Concept Oriented Attribute Reduction in Three way Concept Analysis. -- Deterministic and Nondeterministic Decision Trees for Recognition of Properties of Decision Rule Systems. -- Concept Reduction Method Based on Attribute (Object) Reduction.This three-volume set LNAI 15708-15709-15110 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2025, held in Chongqing, China, during May 11–13, 2025. The 90 full papers included in these volumes were carefully reviewed and selected from 187 submissions. They are organized in topical sections as follows: Part I: Rough Set Models and Foundations; Fuzzy Rough Sets and Rough Fuzzy Sets; and Granular Computing. Part II: Rough Set Applications; Feature Selection and Knowledge Discovery; and Cognitive Computing. Part III: Three-way Data Analytics and Decision; Medicine and Health Data Mining; and Applications of Deep Learning and Soft Computing.Lecture Notes in Artificial Intelligence,2945-9141 ;15709Artificial intelligenceData miningSocial sciencesData processingArtificial IntelligenceData Mining and Knowledge DiscoveryComputer Application in Social and Behavioral SciencesArtificial intelligence.Data mining.Social sciencesData processing.Artificial Intelligence.Data Mining and Knowledge Discovery.Computer Application in Social and Behavioral Sciences.006.3Zhang Qinghuaedthttp://id.loc.gov/vocabulary/relators/edtHenry Christopheredthttp://id.loc.gov/vocabulary/relators/edtJensen Richardedthttp://id.loc.gov/vocabulary/relators/edtGao Xinboedthttp://id.loc.gov/vocabulary/relators/edtWang Guoyin1970-edthttp://id.loc.gov/vocabulary/relators/edtYao JingTaoedthttp://id.loc.gov/vocabulary/relators/edtCornelis Chrisedthttp://id.loc.gov/vocabulary/relators/edtXia Shuyinedthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK996660358603316Rough Sets2569547UNISA