Relevant bibliographies by topics / Generalized graphs

Academic literature on the topic 'Generalized graphs'

Author: Grafiati
Published: 8 June 2024

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Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Journal articles on the topic "Generalized graphs":

1

Sedláček, Jiří. "On generalized outerplanarity of line graphs." Časopis pro pěstování matematiky 115, no. 3 (1990): 273–77. http://dx.doi.org/10.21136/cpm.1990.118405.

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Samanta, Sovan, and Biswajit Sarkar. "Generalized fuzzy Euler graphs and generalized fuzzy Hamiltonian graphs." Journal of Intelligent & Fuzzy Systems 35, no. 3 (October 1, 2018): 3413–19. http://dx.doi.org/10.3233/jifs-17322.

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Das, Angsuman, Sucharita Biswas, and Manideepa Saha. "Generalized Andrásfai Graphs." Discussiones Mathematicae - General Algebra and Applications 42, no. 2 (2022): 449. http://dx.doi.org/10.7151/dmgaa.1401.

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Marušič, Dragan, Raffaele Scapellato, and Norma Zagaglia Salvi. "Generalized Cayley graphs." Discrete Mathematics 102, no. 3 (May 1992): 279–85. http://dx.doi.org/10.1016/0012-365x(92)90121-u.

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Zverovich, Igor E. "Generalized Matrogenic Graphs." Annals of Combinatorics 10, no. 2 (September 2006): 285–90. http://dx.doi.org/10.1007/s00026-006-0288-4.

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Lovász, László, and Vera T. Sós. "Generalized quasirandom graphs." Journal of Combinatorial Theory, Series B 98, no. 1 (January 2008): 146–63. http://dx.doi.org/10.1016/j.jctb.2007.06.005.

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Brand, Neal, and Margaret Morton. "Generalized steinhaus graphs." Journal of Graph Theory 20, no. 1 (August 1995): 47–58. http://dx.doi.org/10.1002/jgt.3190200105.

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Alon, Noga, and Edward R. Scheinerman. "Generalized sum graphs." Graphs and Combinatorics 8, no. 1 (March 1992): 23–29. http://dx.doi.org/10.1007/bf01271705.

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IRSİC, VESNA, SANDI KLAVZAR, and ELİF TAN. "Generalized Pell graphs." Turkish Journal of Mathematics 47, no. 7 (November 9, 2023): 1955–73. http://dx.doi.org/10.55730/1300-0098.3475.

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Limaye, N. B., and Mulupuri Shanthi C. Rao. "On $2$-extendability of generalized Petersen graphs." Mathematica Bohemica 121, no. 1 (1996): 77–81. http://dx.doi.org/10.21136/mb.1996.125939.

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Journal articles Dissertations / Theses Books

Dissertations / Theses on the topic "Generalized graphs":

1

Hennayake, Kamal P. "Generalized edge connectivity in graphs." Morgantown, W. Va. : [West Virginia University Libraries], 1998. http://etd.wvu.edu/templates/showETD.cfm?recnum=383.

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Thesis (Ph. D.)--West Virginia University, 1998.
Title from document title page. Document formatted into pages; contains v, 87 p. : ill. Includes abstract. Includes bibliographical references (p. 64-72).
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Pensaert, William. "Hamilton Paths in Generalized Petersen Graphs." Thesis, University of Waterloo, 2002. http://hdl.handle.net/10012/1198.

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This thesis puts forward the conjecture that for n > 3k with k > 2, the generalized Petersen graph, GP(n,k) is Hamilton-laceable if n is even and k is odd, and it is Hamilton-connected otherwise. We take the first step in the proof of this conjecture by proving the case n = 3k + 1 and k greater than or equal to 1. We do this mainly by means of an induction which takes us from GP(3k + 1, k) to GP(3(k + 2) + 1, k + 2). The induction takes the form of mapping a Hamilton path in the smaller graph piecewise to the larger graph an inserting subpaths we call rotors to obtain a Hamilton path in the larger graph.
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Ali, Seema. "Colouring generalized Kneser graphs and homotopy theory." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0014/MQ34938.pdf.

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Nukala, Murthy V. R. K. N. "Generalized models of design iteration using signal flow graphs." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11486.

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Werner, Rose-Line. "Concrete constructions of unbalanced bipartite expander graphs and generalized conductors." Zürich : ETH, Eidgenössische Technische Hochschule Zürich, Departement Informatik, Institut für Informationssysteme, 2008. http://e-collection.ethbib.ethz.ch/show?type=dipl&nr=389.

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Sanford, Alice Jewel. "Cycle spectra, automorphic uniqueness, and isomorphism classes of generalized Petersen graphs /." Full text available from ProQuest UM Digital Dissertations, 2005. http://0-proquest.umi.com.umiss.lib.olemiss.edu/pqdweb?index=0&did=1264606591&SrchMode=1&sid=3&Fmt=2&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1185199901&clientId=22256.

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Sharifiyazdi, Elham [Verfasser]. "The clique number of generalized Hamming graphs / submitted by Elham Sharifiyazdi." [Clausthal-Zellerfeld] : [Univ.-Bibliothek], 2007. http://d-nb.info/986579076/34.

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Knechtel, lessa Micheli. "Extended Generalized Blockmodeling." Thesis, Avignon, 2021. http://www.theses.fr/2021AVIG0281.

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Le blockmodeling est un ensemble de techniques initialement conçues pour analyser les réseaux sociaux mais dont l’intérêt pratique devient plus grand, comme nous le verrons plus loin dans cette thèse pour les graphes terminologiques. L’undesobjectifsdublockmodelingestderéduireungrandréseaupotentiellement incohérent en une structure compréhensible plus petite qui peut être interprétée plus facilement. Il y a un grand intérêt à capturer la structure de cluster d’un réseau en termes d’équivalences, de blocs et de partitions. Jusqu’à présent, la plupart des méthodes de modélisationparblocsvisentàadapterlastructureduréseauàunseultypedemodèle de structure. La question de recherche est de savoir comment gérer les situations où un analyste a plusieurs types de relations pour un ensemble d’acteurs. Ainsi, nous proposons un modèle d’optimisation, que nous appelons le extended generalized blockmodeling. Le principal objectif de extended generalized blockmodeling est de trouver la taille de la partition et l’ensemble de modèles qui a la meilleure représentation de la structure du réseau. Le extended generalized blockmodeling élargit les possibilités du framework, permettant d’analyser les réseaux sans aucune connaissance préalable à leur sujet. Leextendedgeneralizedblockmodelingappartientàlaclassedesproblèmeshautementcombinatoires,laméthodeexacteneconvientquepourlespetitsréseaux, doncla deuxièmequestionestdesavoircommentrendrecetteapprocheviablepourlesréseaux moyens et grands. Par conséquent, nous proposons la première approche non exacte pour le extended generalized blockmodeling, basée sur l’algorithme VNS comme alternative pour les réseaux de taille moyenne. Même si les résultats trouvés par l’heuristique ne sont peut-êtrepaslameilleuredetouteslessolutionsauproblème,lesexpériencesmontrent qu’elle converge vers un résultat satisfaisant dans un temps qui n’est pas prohibitif. La troisième question, que nous abordons dans cette thèse, est le extended generalized blockmodeling, une approche appropriée dans le domaine de la bibliométrie et du traitement du langage naturel. Pour ce faire, nous analysons le réseau de termes concernant la recherche sur le terrorisme. Pour toutes ces questions, nous démontrons les résultats numériques, basés sur des benchmarks de jeux de données artificiels et réels. Ces résultats permettent d’explorer lesopportunitésd’applicationdelamodélisationdeblocgénéraliséeétendueainsique ses limites
Blockmodeling is a set of techniques initially designed to analyse social networks but whose practical interest becomes larger, as we will see further in this thesis for terminology graphs. One of the goals of blockmodeling is to reduce a large, potentially incoherent network to a smaller comprehensible structure that can be interpreted more readily. There is great interest in capturing the cluster structure of a network in terms of equivalences, blocks and partitions. Up to now, most blockmodeling methods are focused in fitting the network structure to only one type of structure pattern. However, there are a variety of social networking applications in which it is interesting to consider more than one type of pattern simultaneously, so that the structure of the network can take the form of several indicators for underlying relationships. The research question is, how to deal with the situations where an analyst has several relations types of relations for a set of actors. Thus, we propose an optimization model, which we call the extended generalized blockmodeling. The main objective of extended generalized blockmodeling is to find the partition size and the set of patterns that has the best representation of the network structure. The extended generalized blockmodeling expands the possibilities of the framework, making it possible to analyze networks without any prior knowledge about them. The extended generalized block modeling belongs to the class of highly combinatorial problems, the exact method is only suitable for small networks, so the second question is how to make this approach viable for medium and large networks. Therefore, we propose the first non-exact approach to generalized extended block modeling, based on the VNS algorithm as an alternative for medium-sized networks. Even though the results found by the heuristic may not be the best of all the solutions to the problem, the experiments show that it converges to a satisfactory result in a not prohibitively long time. The third question, which we address in this thesis, is the extended generalized blockmodeling a suitable approach in the field of bibliometrics and Natural Language processing. To do so, we analyse the network of terms concerning terrorism research. For all these questions, we demonstrate the numerical results, based on artificial and real datasets benchmarks. These results allow the exploration of the application opportunities of the extended generalized block modeling as well as it’s limitations
9

Djang, Claire. "Two-Coloring Cycles In Complete Graphs." Oberlin College Honors Theses / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=oberlin1370618319.

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Mooney, Christopher Park. "Generalized factorization in commutative rings with zero-divisors." Thesis, The University of Iowa, 2013. http://pqdtopen.proquest.com/#viewpdf?dispub=3595128.

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The study of factorization in integral domains has a long history. Unique factorization domains, like the integers, have been studied extensively for many years. More recently, mathematicians have turned their attention to generalizations of this such as Dedekind domains or other domains which have weaker factorization properties. Many authors have sought to generalize the notion of factorization in domains. One particular method which has encapsulated many of the generalizations into a single study is that of τ-factorization, studied extensively by A. Frazier and D.D. Anderson.

Another generalization comes in the form of studying factorization in rings with zero-divisors. Factorization gets quite complicated when zero-divisors are present due to the existence of several types of associate relations as well as several choices about what to consider the irreducible elements.

In this thesis, we investigate several methods for extending the theory of τ-factorization into rings with zero-divisors. We investigate several methods including: 1) the approach used by A.G. Agˇargün and D.D. Anderson, S. Chun and S. Valdes-Leon in several papers; 2) the method of U-factorization developed by C.R. Fletcher and extended by M. Axtell, J. Stickles, and N. Baeth and 3) the method of regular factorizations and 4) the method of complete factorizations.

This thesis synthesizes the work done in the theory of generalized factorization and factorization in rings with zero-divisors. Along the way, we encounter several nice applications of the factorization theory. Using τ z-factorizations, we discover a nice relationship with zero-divisor graphs studied by I. Beck as well as D.D. Anderson, D.F. Anderson, A. Frazier, A. Lauve, and P. Livingston. Using τ-U-factorization, we are able to answer many questions that arise when discussing direct products of rings.

There are several benefits to the regular factorization factorization approach due to the various notions of associate and irreducible coinciding on regular elements greatly simplifying many of the finite factorization property relationships. Complete factorization is a very natural and effective approach taken to studying factorization in rings with zero-divisors. There are several nice results stemming from extending τ-factorization in this way. Lastly, an appendix is provided in which several examples of rings satisfying the various finite factorization properties studied throughout the thesis are given.

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Books on the topic "Generalized graphs":

1

Mikov, Aleksandr. Generalized graphs and grammars. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1013698.

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The textbook deals with ordinary graphs and their generalizations-hypergraphs, hierarchical structures, geometric graphs, random and dynamic graphs. Graph grammars are considered in detail. Meets the requirements of the federal state educational standards of higher education of the latest generation. For master's students studying in the areas of the 02.00.00 group "Computer and Information Sciences", and can also be used in senior bachelor's courses and other areas in the field of computer science and computer engineering.
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Li, Xueliang, and Yaping Mao. Generalized Connectivity of Graphs. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33828-6.

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Jong, Gjalt Gerrit de. Generalized data flow graphs: Theory and applications : proefschrift. [S.l: s.n.,], 1993.

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Brown, Jason Ira. A theory of generalized graph colourings. Toronto: [s.n.], 1987.

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Fidanova, Stefka. Generalized nets in artificial intelligence: Generalized nets and ant colony optimization. Sofia: Academic Publishing House "Prof. Marin Drinov", 2011.

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Institute for Computer Applications in Science and Engineering., ed. Graph embeddings, symmetric real matrices, and generalized inverses. Hampton, VA: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1998.

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Institute for Computer Applications in Science and Engineering., ed. Graph embeddings, symmetric real matrices, and generalized inverses. Hampton, VA: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 1998.

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Morvan, J. M. Generalized curvatures. Berlin: Springer, 2008.

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Koi, Dennis Brian. Generalized geographic mapping system for computer graphics. Galveston, Tex: National Oceanic and Atmospheric Administration, National Marine Fisheries Service, Southeast Fisheries Center, Galveston Laboratory, 1985.

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Ghosh, Diptesh. A probabilistic tabu search algorithm for the generalized minimum spanning tree problem. Ahmedabad: Indian Institute of Management, 2003.

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Book chapters on the topic "Generalized graphs":

1

Kimoto, Kazufumi. "Generalized Group–Subgroup Pair Graphs." In International Symposium on Mathematics, Quantum Theory, and Cryptography, 169–85. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5191-8_14.

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Abstract A regular finite graph is called a Ramanujan graph if its zeta function satisfies an analog of the Riemann Hypothesis. Such a graph has a small second eigenvalue so that it is used to construct cryptographic hash functions. Typically, explicit family of Ramanujan graphs are constructed by using Cayley graphs. In the paper, we introduce a generalization of Cayley graphs called generalized group–subgroup pair graphs, which are a generalization of group–subgroup pair graphs defined by Reyes-Bustos. We study basic properties, especially spectra of them.
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Anderson, David F., T. Asir, Ayman Badawi, and T. Tamizh Chelvam. "Generalized Total Graphs." In Graphs from Rings, 401–35. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88410-9_9.

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Arnþórsson, Ívar Marrow, Steven Chaplick, Jökull Snær Gylfason, Magnús M. Halldórsson, Jökull Máni Reynisson, and Tigran Tonoyan. "Generalized Disk Graphs." In Lecture Notes in Computer Science, 115–28. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-83508-8_9.

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Anderson, David F., T. Asir, Ayman Badawi, and T. Tamizh Chelvam. "Generalized Zero-divisor Graphs." In Graphs from Rings, 173–237. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88410-9_5.

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Li, Xueliang, and Yaping Mao. "Maximum Generalized Local Connectivity." In Generalized Connectivity of Graphs, 89–112. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33828-6_8.

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Li, Xueliang, and Yaping Mao. "Introduction." In Generalized Connectivity of Graphs, 1–13. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33828-6_1.

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Li, Xueliang, and Yaping Mao. "Results for Some Graph Classes." In Generalized Connectivity of Graphs, 15–29. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33828-6_2.

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Li, Xueliang, and Yaping Mao. "Algorithm and Complexity." In Generalized Connectivity of Graphs, 31–39. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33828-6_3.

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Li, Xueliang, and Yaping Mao. "Sharp Bounds of the Generalized (Edge-)Connectivity." In Generalized Connectivity of Graphs, 41–57. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33828-6_4.

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Li, Xueliang, and Yaping Mao. "Graphs with Given Generalized Connectivity." In Generalized Connectivity of Graphs, 59–66. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33828-6_5.

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Conference papers on the topic "Generalized graphs":

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Matz, Gerald. "On Generalized Signature Graphs." In ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2024. http://dx.doi.org/10.1109/icassp48485.2024.10446569.

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Huang, Zhichao, Xutao Li, Yunming Ye, and Michael K. Ng. "MR-GCN: Multi-Relational Graph Convolutional Networks based on Generalized Tensor Product." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/175.

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Graph Convolutional Networks (GCNs) have been extensively studied in recent years. Most of existing GCN approaches are designed for the homogenous graphs with a single type of relation. However, heterogeneous graphs of multiple types of relations are also ubiquitous and there is a lack of methodologies to tackle such graphs. Some previous studies address the issue by performing conventional GCN on each single relation and then blending their results. However, as the convolutional kernels neglect the correlations across relations, the strategy is sub-optimal. In this paper, we propose the Multi-Relational Graph Convolutional Network (MR-GCN) framework by developing a novel convolution operator on multi-relational graphs. In particular, our multi-dimension convolution operator extends the graph spectral analysis into the eigen-decomposition of a Laplacian tensor. And the eigen-decomposition is formulated with a generalized tensor product, which can correspond to any unitary transform instead of limited merely to Fourier transform. We conduct comprehensive experiments on four real-world multi-relational graphs to solve the semi-supervised node classification task, and the results show the superiority of MR-GCN against the state-of-the-art competitors.
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Ebner, Dietmar, Florian Brandner, Bernhard Scholz, Andreas Krall, Peter Wiedermann, and Albrecht Kadlec. "Generalized instruction selection usingSSA-graphs." In the 2008 ACM SIGPLAN-SIGBED conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1375657.1375663.

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Seenuvasan, P. "Generalized sum connectivity invariant of graphs." In RECENT TRENDS IN PURE AND APPLIED MATHEMATICS. AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5135262.

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Bekos, M. A., M. Kaufmann, and C. N. Raftopoulou. "AVDTC of generalized 3-Halin graphs." In 2016 7th International Conference on Information, Intelligence, Systems & Applications (IISA). IEEE, 2016. http://dx.doi.org/10.1109/iisa.2016.7785421.

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Mukherjee, Lopamudra, Vikas Singh, Jiming Peng, Jinhui Xu, Michael J. Zeitz, and Ronald Berezney. "Generalized Median Graphs: Theory and Applications." In 2007 IEEE 11th International Conference on Computer Vision. IEEE, 2007. http://dx.doi.org/10.1109/iccv.2007.4408966.

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Angel, D., I. Annammal Arputhamary, R. Revathi, and M. Nirmala. "Secure Node Covering of Cocktail Party Graphs and Generalized Fan Graphs." In 2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT). IEEE, 2022. http://dx.doi.org/10.1109/icicict54557.2022.9918002.

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Prasanna, G. N. Srinivasa, and Bruce R. Musicus. "Generalized multiprocessor scheduling for directed acylic graphs." In the 1994 ACM/IEEE conference. New York, New York, USA: ACM Press, 1994. http://dx.doi.org/10.1145/602770.602812.

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Li, Shengyu, Dengxin Li, and Xiaomin Li. "Survivable Nets and the Generalized Permutation Graphs." In 2009 First International Conference on Information Science and Engineering. IEEE, 2009. http://dx.doi.org/10.1109/icise.2009.1153.

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Garetto, Michele, Emilio Leonardi, and Giovanni Luca Torrisi. "Generalized Threshold-Based Epidemics in Random Graphs." In SIGMETRICS '16: SIGMETRICS/PERFORMANCE Joint International Conference on Measurement and Modeling of Computer Systems. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2896377.2901455.

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Reports on the topic "Generalized graphs":

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Nieto-Castanon, Alfonso. CONN functional connectivity toolbox (RRID:SCR_009550), Version 18. Hilbert Press, 2018. http://dx.doi.org/10.56441/hilbertpress.1818.9585.

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CONN is a Matlab-based cross-platform software for the computation, display, and analysis of functional connectivity in fMRI (fcMRI). Connectivity measures include seed-to-voxel connectivity maps, ROI-to- ROI connectivity matrices, graph properties of connectivity networks, generalized psychophysiological interaction models (gPPI), intrinsic connectivity, local correlation and other voxel-to-voxel measures, independent component analyses (ICA), and dynamic component analyses (dyn-ICA). CONN is available for resting state data (rsfMRI) as well as task-related designs. It covers the entire pipeline from raw fMRI data to hypothesis testing, including spatial coregistration, ART-based scrubbing, aCompCor strategy for control of physiological and movement confounds, first-level connectivity estimation, and second-level random-effect analyses and hypothesis testing.
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Nieto-Castanon, Alfonso. CONN functional connectivity toolbox (RRID:SCR_009550), Version 20. Hilbert Press, 2020. http://dx.doi.org/10.56441/hilbertpress.2048.3738.

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CONN is a Matlab-based cross-platform software for the computation, display, and analysis of functional connectivity in fMRI (fcMRI). Connectivity measures include seed-to-voxel connectivity maps, ROI-to- ROI connectivity matrices, graph properties of connectivity networks, generalized psychophysiological interaction models (gPPI), intrinsic connectivity, local correlation and other voxel-to-voxel measures, independent component analyses (ICA), and dynamic component analyses (dyn-ICA). CONN is available for resting state data (rsfMRI) as well as task-related designs. It covers the entire pipeline from raw fMRI data to hypothesis testing, including spatial coregistration, ART-based scrubbing, aCompCor strategy for control of physiological and movement confounds, first-level connectivity estimation, and second-level random-effect analyses and hypothesis testing.
3

Nieto-Castanon, Alfonso. CONN functional connectivity toolbox (RRID:SCR_009550), Version 19. Hilbert Press, 2019. http://dx.doi.org/10.56441/hilbertpress.1927.9364.

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CONN is a Matlab-based cross-platform software for the computation, display, and analysis of functional connectivity in fMRI (fcMRI). Connectivity measures include seed-to-voxel connectivity maps, ROI-to- ROI connectivity matrices, graph properties of connectivity networks, generalized psychophysiological interaction models (gPPI), intrinsic connectivity, local correlation and other voxel-to-voxel measures, independent component analyses (ICA), and dynamic component analyses (dyn-ICA). CONN is available for resting state data (rsfMRI) as well as task-related designs. It covers the entire pipeline from raw fMRI data to hypothesis testing, including spatial coregistration, ART-based scrubbing, aCompCor strategy for control of physiological and movement confounds, first-level connectivity estimation, and second-level random-effect analyses and hypothesis testing.
4

Chen, Huiru, Youjia Qiu, Zilan Wang, Zhouqing Chen, Yan Kong, and Zhong Wang. Efficacy and Safety of the Innovative Monoclonal Antibodies in Adults with Generalized Myasthenia Gravis: a Bayesian Network Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, July 2023. http://dx.doi.org/10.37766/inplasy2023.7.0112.

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Letcher, Theodore, Julie Parno, Zoe Courville, Lauren Farnsworth, and Jason Olivier. A generalized photon-tracking approach to simulate spectral snow albedo and transmittance using X-ray microtomography and geometric optics. Engineer Research and Development Center (U.S.), June 2023. http://dx.doi.org/10.21079/11681/47122.

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A majority of snow radiative transfer models (RTMs) treat snow as a collection of idealized grains rather than an organized ice–air matrix. Here we present a generalized multi-layer photon-tracking RTM that simulates light reflectance and transmittance of snow based on X-ray micro- tomography images, treating snow as a coherent 3D structure rather than a collection of grains. The model uses a blended approach to expand ray-tracing techniques applied to sub-1 cm3 snow samples to snowpacks of arbitrary depths. While this framework has many potential applications, this study’s effort is focused on simulating reflectance and transmittance in the visible and near infrared (NIR) through thin snow- packs as this is relevant for surface energy balance and remote sensing applications. We demonstrate that this framework fits well within the context of previous work and capably reproduces many known optical properties of a snow surface, including the dependence of spectral reflectance on the snow specific surface area and incident zenith angle as well as the surface bidirectional reflectance distribution function (BRDF). To evaluate the model, we compare it against reflectance data collected with a spectroradiometer at a field site in east-central Vermont. In this experiment, painted panels were inserted at various depths beneath the snow to emulate thin snow. The model compares remarkably well against the reflectance measured with a spectroradiometer, with an average RMSE of 0.03 in the 400–1600 nm range. Sensitivity simulations using this model indicate that snow transmittance is greatest in the visible wavelengths, limiting light penetration to the top 6 cm of the snowpack for fine-grain snow but increasing to 12 cm for coarse-grain snow. These results suggest that the 5% transmission depth in snow can vary by over 6 cm according to the snow type.
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Wells, Aaron, Tracy Christopherson, Gerald Frost, Matthew Macander, Susan Ives, Robert McNown, and Erin Johnson. Ecological land survey and soils inventory for Katmai National Park and Preserve, 2016–2017. National Park Service, September 2021. http://dx.doi.org/10.36967/nrr-2287466.

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This study was conducted to inventory, classify, and map soils and vegetation within the ecosystems of Katmai National Park and Preserve (KATM) using an ecological land survey (ELS) approach. The ecosystem classes identified in the ELS effort were mapped across the park, using an archive of Geo-graphic Information System (GIS) and Remote Sensing (RS) datasets pertaining to land cover, topography, surficial geology, and glacial history. The description and mapping of the landform-vegetation-soil relationships identified in the ELS work provides tools to support the design and implementation of future field- and RS-based studies, facilitates further analysis and contextualization of existing data, and will help inform natural resource management decisions. We collected information on the geomorphic, topographic, hydrologic, pedologic, and vegetation characteristics of ecosystems using a dataset of 724 field plots, of which 407 were sampled by ABR, Inc.—Environmental Research and Services (ABR) staff in 2016–2017, and 317 were from existing, ancillary datasets. ABR field plots were located along transects that were selected using a gradient-direct sampling scheme (Austin and Heligers 1989) to collect data for the range of ecological conditions present within KATM, and to provide the data needed to interpret ecosystem and soils development. The field plot dataset encompassed all of the major environmental gradients and landscape histories present in KATM. Individual state-factors (e.g., soil pH, slope aspect) and other ecosystem components (e.g., geomorphic unit, vegetation species composition and structure) were measured or categorized using standard classification systems developed for Alaska. We described and analyzed the hierarchical relationships among the ecosystem components to classify 92 Plot Ecotypes (local-scale ecosystems) that best partitioned the variation in soils, vegetation, and disturbance properties observed at the field plots. From the 92 Plot Ecotypes, we developed classifications of Map Ecotypes and Disturbance Landscapes that could be mapped across the park. Additionally, using an existing surficial geology map for KATM, we developed a map of Generalized Soil Texture by aggregating similar surficial geology classes into a reduced set of classes representing the predominant soil textures in each. We then intersected the Ecotype map with the General-ized Soil Texture Map in a GIS and aggregated combinations of Map Ecotypes with similar soils to derive and map Soil Landscapes and Soil Great Groups. The classification of Great Groups captures information on the soil as a whole, as opposed to the subgroup classification which focuses on the properties of specific horizons (Soil Survey Staff 1999). Of the 724 plots included in the Ecotype analysis, sufficient soils data for classifying soil subgroups was available for 467 plots. Soils from 8 orders of soil taxonomy were encountered during the field sampling: Alfisols (<1% of the mapped area), Andisols (3%), Entisols (45%), Gelisols (<1%), Histosols (12%), Inceptisols (22%), Mollisols (<1%), and Spodosols (16%). Within these 8 Soil Orders, field plots corresponded to a total of 74 Soil Subgroups, the most common of which were Typic Cryaquents, Typic Cryorthents, Histic Cryaquepts, Vitrandic Cryorthents, and Typic Cryofluvents.
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Monetary Policy Report - January 2023. Banco de la República, June 2023. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr1-2023.

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1. Macroeconomic Summary In December, headline inflation (13.1%) and the average of the core inflation measures (10.3%) continued to trend upward, posting higher rates than those estimated by the Central Bank's technical staff and surpassing the market average. Inflation expectations for all terms exceeded the 3.0% target. In that month, every major group in the Consumer Price Index (CPI) registered higher-than-estimated increases, and the diffusion indicators continued to show generalized price hikes. Accumulated exchange rate pressures on prices, indexation to high inflation rates, and several food supply shocks would explain, in part, the acceleration in inflation. All of this is in a context of significant surplus demand, a tight labor market, and inflation expectations at different terms that exceed the 3.0% target. Compared to the October edition of the Monetary Policy Report, the forecast path for headline and core inflation (excluding food and regulated items: EFR) increased (Graphs 1.1 and 1.2), reflecting heightened accumulated exchange rate pressures, price indexation to a higher inflation rate (CPI and the producer price index: PPI), and the rise in labor costs attributed to a larger-than-estimated adjustment in the minimum wage. Nevertheless, headline inflation is expected to begin to ease by early 2023, although from a higher level than had been estimated in October. This would be supported initially by the slowdown forecast for the food CPI due to a high base of comparison, the end anticipated for the shocks that have affected the prices of these products, and the estimated improvement in external and domestic supply in this sector. In turn, the deterioration in real household income because of high inflation and the end of the effects of pent-up demand, plus tighter external and domestic financial conditions would contribute to diluting surplus demand in 2023 and reducing inflation. By the end of 2023, both headline and core (EFR) inflation would reach 8.7% and would be 3.5% and 3.8%, respectively, by December 2024. These forecasts are subject to a great deal of uncertainty, especially concerning the future behavior of international financial conditions, the evolution of the exchange rate, the pace of adjustment in domestic demand, the extent of indexation of nominal contracts, and the decisions taken regarding the domestic price of fuel and electricity. In the third quarter, economic activity surprised again on the upside and the growth projection for 2022 rose to 8.0% (previously 7.9%). However, it declined to 0.2% for 2023 (previously 0.5%). With this, surplus demand continues to be significant and is still expected to weaken during the current year. Annual economic growth in the third quarter (7.1 % SCA)1 was higher than estimated in October (6.4 % SCA), given stronger domestic demand specifically because of higher-than-expected investment. Private consumption fell from the high level witnessed a quarter earlier and net exports registered a more negative contribution than anticipated. For the fourth quarter, economic activity indicators suggest that gross domestic product (GDP) would have remained high and at a level similar to that observed in the third quarter, with an annual variation of 4.1%. Domestic demand would have slowed in annual terms, although at levels that would have remained above those for output, mainly because of considerable private consumption. Investment would have declined slightly to a value like the average observed in 2019. The real trade deficit would have decreased due to a drop in imports that was more pronounced than the estimated decline in exports. On the forecast horizon, consumption is expected to decline from current elevated levels, partly because of tighter domestic financial conditions and a deterioration in real income due to high inflation. Investment would also weaken and return to levels below those seen before the pandemic. In real terms, the trade deficit would narrow due to a lower momentum projection for domestic demand and higher cumulative real depreciation. In sum, economic growth for all of 2022, 2023, and 2024 would stand at 8.0%, 0.2% and 1.0%, respectively (Graph 1.3). Surplus demand remains high (as measured by the output gap) and is expected to decline in 2023 and could turn negative in 2024 (Graph 1.4). Although the macroeconomic forecast includes a marked slowdown in the economy, an even greater adjustment in domestic absorption cannot be ruled out due to the cumulative effects of tighter external and domestic financial conditions, among other reasons. These estimates continue to be subject to a high degree of uncertainty, which is associated with factors such as global political tensions, changes in international interest rates and their effects on external demand, global risk aversion, the effects of the approved tax reform, the possible impact of reforms announced for this year (pension, health, and labor reforms, among others), and future measures regarding hydrocarbon production. In 2022, the current account deficit would have been high (6.3 % of GDP), but it would be corrected significantly in 2023 (to 3.9 % of GDP) given the expected slowdown in domestic demand. Despite favorable terms of trade, the high external imbalance that would occur during 2022 would be largely due to domestic demand growth, cost pressures associated with high freight rates, higher external debt service payments, and good performance in terms of the profits of foreign companies.2 By 2023, the adjustment in domestic demand would be reflected in a smaller current account deficit especially due to fewer imports, a global moderation in prices and cost pressures, and a reduction in profits remitted abroad by companies with foreign direct investment (FDI) focused on the local market. Despite this anticipated correction in the external imbalance, its level as a percentage of GDP would remain high in the context of tight financial conditions. In the world's main economies, inflation forecasts and expectations point to a reduction by 2023, but at levels that still exceed their central banks' targets. The path anticipated for the Federal Reserve (Fed) interest rate increased and the forecast for global growth continues to be moderate. In the fourth quarter of 2022, logistics costs and international prices for some foods, oil and energy declined from elevated levels, bringing downward pressure to bear on global inflation. Meanwhile, the higher cost of financing, the loss of real income due to high levels of global inflation, and the persistence of the war in Ukraine, among other factors, have contributed to the reduction in global economic growth forecasts. In the United States, inflation turned out to be lower than estimated and the members of the Federal Open Market Committee (FOMC) reduced the growth forecast for 2023. Nevertheless, the actual level of inflation in that country, its forecasts, and expectations exceed the target. Also, the labor market remains tight, and fiscal policy is still expansionary. In this environment, the Fed raised the expected path for policy interest rates and, with this, the market average estimates higher levels for 2023 than those forecast in October. In the region's emerging economies, country risk premia declined during the quarter and the currencies of those countries appreciated against the US dollar. Considering all the above, for the current year, the Central Bank's technical staff increased the path estimated for the Fed's interest rate, reduced the forecast for growth in the country's external demand, lowered the expected path of oil prices, and kept the country’s risk premium assumption high, but at somewhat lower levels than those anticipated in the previous Monetary Policy Report. Moreover, accumulated inflationary pressures originating from the behavior of the exchange rate would continue to be important. External financial conditions facing the economy have improved recently and could be associated with a more favorable international context for the Colombian economy. So far this year, there has been a reduction in long-term bond interest rates in the markets of developed countries and an increase in the prices of risky assets, such as stocks. This would be associated with a faster-than-expected reduction in inflation in the United States and Europe, which would allow for a less restrictive course for monetary policy in those regions. In this context, the risks of a global recession have been reduced and the global appetite for risk has increased. Consequently, the risk premium continues to decline, the Colombian peso has appreciated significantly, and TES interest rates have decreased. Should this trend consolidate, exchange rate inflationary pressures could be less than what was incorporated into the macroeconomic forecast. Uncertainty about external forecasts and their impact on the country remains high, given the unpredictable course of the war in Ukraine, geopolitical tensions, local uncertainty, and the extensive financing needs of the Colombian government and the economy. High inflation with forecasts and expectations above 3.0%, coupled with surplus demand and a tight labor market are compatible with a contractionary stance on monetary policy that is conducive to the macroeconomic adjustment needed to mitigate the risk of de-anchoring inflation expectations and to ensure that inflation converges to the target. Compared to the forecasts in the October edition of the Monetary Policy Report, domestic demand has been more dynamic, with a higher observed level of output exceeding the productive capacity of the economy. In this context of surplus demand, headline and core inflation continued to trend upward and posted surprising increases. Observed and expected international interest rates increased, the country’s risk premia lessened (but remains at high levels), and accumulated exchange rate pressures are still significant. The technical staff's inflation forecast for 2023 increased and inflation expectations remain well above 3.0%. All in all, the risk of inflation expectations becoming unanchored persists, which would accentuate the generalized indexation process and push inflation even further away from the target. This macroeconomic context requires consolidating a contractionary monetary policy stance that aims to meet the inflation target within the forecast horizon and bring the economy's output to levels closer to its potential. 1.2 Monetary Policy Decision At its meetings in December 2022 and January 2023, Banco de la República’s Board of Directors (BDBR) agreed to continue the process of normalizing monetary policy. In December, the BDBR decided by a majority vote to increase the monetary policy interest rate by 100 basis points (bps) and in its January meeting by 75 bps, bringing it to 12.75% (Graph 1.5). 1/ Seasonally and calendar adjusted. 2/ In the current account aggregate, the pressures for a higher external deficit come from those companies with FDI that are focused on the domestic market. In contrast, profits in the mining and energy sectors are more than offset by the external revenue they generate through exports. Box 1 - Electricity Rates: Recent Developments and Indexation. Author: Édgar Caicedo García, Pablo Montealegre Moreno and Álex Fernando Pérez Libreros Box 2 - Indicators of Household Indebtedness. Author: Camilo Gómez y Juan Sebastián Mariño
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Monetary Policy Report - January 2021. Banco de la República de Colombia, March 2021. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr1.-2021.

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Macroeconomic Summary Overall inflation (1.61%) and core inflation (excluding food and regulated items) (1.11%) both declined beyond the technical staff’s expectations in the fourth quarter of 2020. Year-end 2021 forecasts for both indicators were revised downward to 2.3% and 2.1%, respectively. Market inflation expectations also fell over this period and suggested inflation below the 3% target through the end of this year, rising to the target in 2022. Downward pressure on inflation was more significant in the fourth quarter than previously projected, indicating weak demand. Annual deceleration among the main groups of the consumer price index (CPI) was generalized and, except for foods, was greater than projected in the October report. The CPI for goods (excluding foods and regulated items) and the CPI for regulated items were subject to the largest decelerations and forecasting discrepancies. In the first case, this was due in part to a greater-than-expected effect on prices from the government’s “VAT-fee day” amid weak demand, and from the extension of some price relief measures. For regulated items, the deceleration was caused in part by unanticipated declines in some utility prices. Annual change in the CPI for services continued to decline as a result of the performance of those services that were not subject to price relief measures, in particular. Although some of the overall decline in inflation is expected to be temporary and reverse course in the second quarter of 2021, various sources of downward pressure on inflation have become more acute and will likely remain into next year. These include ample excesses in capacity, as suggested by the continued and greater-than-expected deceleration in core inflation indicators and in the CPI for services excluding price relief measures. This dynamic is also suggested by the minimal transmission of accumulated depreciation of the peso on domestic prices. Although excess capacity should fall in 2021, the decline will likely be slower than projected in the October report amid additional restrictions on mobility due to a recent acceleration of growth in COVID-19 cases. An additional factor is that low inflation registered at the end of 2020 will likely be reflected in low price adjustments on certain indexed services with significant weight in the CPI, including real estate rentals and some utilities. These factors should keep inflation below the target and lower than estimates from the previous report on the forecast horizon. Inflation is expected to continue to decline to levels near 1% in March, later increasing to 2.3% at the end of 2021 and 2.7% at year-end 2022 (Graph 1.1). According to the Bank’s most recent survey, market analysts expect inflation of 2.7% and 3.1% in December 2021 and 2022, respectively. Expected inflation derived from government bonds was 2% for year-end 2021, while expected inflation based on bonds one year forward from that date (FBEI 1-1 2022) was 3.2%.

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