Готові списки джерел за темами / Scale change

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Добірка наукової літератури з теми "Scale change"

Автор: Grafiati
Опубліковано: 10 вересня 2022
Оновлено: 18 вересня 2022

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Статті в журналах з теми "Scale change"

1

Mugiya, Davison, and Costa Hofisi. "Climate change adaptation challenges confronting small-scale farmers." Environmental Economics 8, no. 1 (April 12, 2017): 57–65. http://dx.doi.org/10.21511/ee.08(1).2017.06.

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Climate change adaptation issues have recently gained attention for the past few years in Zimbabwe. However, little has been done to explore the challenges, associated with climate change in the country. Therefore, this article explores the challenges affecting small-scale farmers in the Zvishavane District of Zimbabwe in coping with climate change vulnerability. The qualitative research methodology encompassing semi-structured interviews was used to collect data from small-scale farmers and other key informants in the study area. The study portrays that small-scale farmers are struggling to cope with climate change due to resource constraints, lack of access to credit and inputs, aid bottlenecks coupled with contradiction of programs among other critical issues.
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2

Střeleček, F., R. Zdeněk, and J. Lososová. "Influence of production change on return to scale." Agricultural Economics (Zemědělská ekonomika) 57, No. 4 (May 4, 2011): 159–68. http://dx.doi.org/10.17221/93/2010-agricecon.

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The paper deals with an assessment of cost efficiency of farms in 2006–2009 based on a sample of farms classified according to the cost/revenue ratio. The analysis of the sample of 101 farms revealed that the return to scale effect is not significant compared to other effects so that the real increase of the production volume may not determine the dynamic of the profit. The massive shift of farms with increasing cost efficiency to the category of the decreased cost efficiency reflects a significant influence of external conditions to the profit/loss of farms. A positive development of prices in 2007 has influenced an increased cost efficiency of the majority of sample farms. In 2008, the increased prices of agricultural inputs intensively influenced the development of the revenue function. The increase of variable costs influenced by increased input prices has wasted reserves resulted from the production use of fixed costs and the return to scale and caused a significant decrease of profit.
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3

Okhremchuk, І. "Modelling of climate change mitigation policies on national scale." Bìoresursi ì prirodokoristuvannâ 9, no. 3-4 (September 28, 2017): 34–39. http://dx.doi.org/10.31548/bio2017.03.005.

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4

Litzinger, William, Allan M. Mohrman, Susan Albers Mohrman, Gerald E. Ledford, Thomas G. Cummings, and Edward E. Lawler. "Large-Scale Organizational Change." Academy of Management Review 15, no. 4 (October 1990): 710. http://dx.doi.org/10.2307/258696.

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5

Markow, Cathie, and Elliott K. Main. "Creating Change at Scale." Obstetrics and Gynecology Clinics of North America 46, no. 2 (June 2019): 317–28. http://dx.doi.org/10.1016/j.ogc.2019.01.014.

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Makimoto, Naoki. "OPTIMAL TIME TO INVEST UNDER UNCERTAINTY WITH A SCALE CHANGE." Journal of the Operations Research Society of Japan 51, no. 3 (2008): 225–40. http://dx.doi.org/10.15807/jorsj.51.225.

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7

Nobles, Brittney M., and Steven R. Erickson. "Variations of a Commonly Used Medication Adherence Assessment Scale: Do Changes in Scale Change Structure Results?" Journal of Pharmacy Technology 34, no. 6 (August 30, 2018): 252–58. http://dx.doi.org/10.1177/8755122518796586.

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Background: Medication nonadherence is a major barrier to both patients and health care professionals when trying to manage medical conditions. An appropriate self-report adherence tool would be helpful in determining a patient’s medication adherence. Objectives: To observe variations in scale scores based on modifications to an Original Adherence Scale, with the hypothesis that making modifications to the Original Adherence Scale will create variations in the percentage of adherent patients. Methods: This cross-sectional study utilized mailed surveys to people identified in a prescription claims administrative dataset who had a pharmacy claim for at least 2 antihypertensive medications. One thousand people were equally divided and randomly placed in 1 of 4 groups: Original Adherence Scale Group, Time Reference Scale Group, 4-Point Likert-Type Scale Group, Multiple Medication Scales Group. Each scale underwent assessment of internal reliability using Cronbach’s α. Changes made to the Original 4-item scale included altering the time reference period from 3 months to 7 days, changing response options from Yes/No to a Likert-type scale, and incorporating multiple scales so that the respondent may report on up to 4 different options. Results: There were 437 surveys completed appropriately, yielding a 46.4% response rate. The overall scale scores indicating perfect adherence was 51.8% for the 4-Point Likert-Type Scale Group, 66.5% for the Multiple Medication Scales Group, 68.8% for the Original Adherence Scale Group, and 78.9% for the Time Reference Scale Group. Conclusion: When there are more selection options, a change in time reference, or more medications reported, the amount of adherent patients varied.
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8

Prein, Andreas Franz, Andreas Gobiet, and Heimo Truhetz. "Analysis of uncertainty in large scale climate change projections over Europe." Meteorologische Zeitschrift 20, no. 4 (August 1, 2011): 383–95. http://dx.doi.org/10.1127/0941-2948/2011/0286.

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Northridge, Mary E. "Tempo and Scale of Change." American Journal of Public Health 91, no. 8 (August 2001): 1171. http://dx.doi.org/10.2105/ajph.91.8.1171.

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Armenakis, Achilles A., Jeremy B. Bernerth, Jennifer P. Pitts, and H. Jack Walker. "Organizational Change Recipients' Beliefs Scale." Journal of Applied Behavioral Science 43, no. 4 (December 2007): 481–505. http://dx.doi.org/10.1177/0021886307303654.

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Дисертації з теми "Scale change"

1

Hofer, Heiko. "Large-Scale Gradual Change Detection." Neubiberg Universitätsbibliothek der Universität der Bundeswehr, 2010. http://d-nb.info/1001920856/34.

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2

Eversole, Dolan. "Large-Scale Beach Change: Kaanapali, Hawai'i." Thesis, University of Hawaii at Manoa, 2002. http://hdl.handle.net/10125/6946.

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Using monthly beach profile surveys and historical aerial photographs, the seasonal and long-term (48 year) beach morphology for Kaanapali Beach, Maui is described. By identifying the shoreline position in historical aerial photographs it is determined that the Kaanapali area is subject to long periods of mild erosion and accretion punctuated by severe erosional events related to short-period Kona storms and hurricane waves. Increased Central Pacific tropical cyclone activity of the late 1950's and early 1960's and Hurricane Iniki in 1992 are identified as contributing factors to the observed volume change during these periods. Between these erosional periods the Kaanapali shoreline is relatively stable characterized by light erosion to moderate accretion suggesting the recovery time may be on the order of roughly 20 years. Over the 48-year period 1949 to 1997, the Kaanapali and Honokowai cells have experienced a net sediment volume loss of 43,000 ±730 m3 and 30,700 ±630 m3 respectively for a total net volume loss of 73,700 ± 990 m3. The Kona storms and hurricanes of the early 1960's and 1992 collectively account for 136,000 m3 of sediment lost or approximately 62% of the gross volume change for the entire period, revealing the significant erosional effect of these storms. Recovery after each of these storms accounts for 73,900 m3 or approximately 33% of the gross volume change. A residual loss of 10,600 m3 representing 5% of the gross volume change is inferred as chronic erosion and may be a product of relative sea-level rise (RSLR). An increase in short-period southwesterly wave energy during these erosional periods is well documented and may have transported beach sediment further offshore than normal (beyond the reef) and is identified as a possible mechanism for long-term erosion in this area. The spatial distribution of historical shoreline movement suggests the majority of sediment transport occurs in the central portion of Kaanapali near Kekaa and Hanakoo Point and is driven by longshore rather than cross-shore transport. Surveyed beach profiles reveal a strong seasonal variability with net erosion in the summer and accretion in the winter with an along the shore-alternating pattern of erosion and accretion. 65% of the net volume change occurs south of Kekaa Point confirming the more dynamic nature of the southern (Kaanapali Cell). Net beach profile volume change from the mean suggests that June and January are the most dynamic months each with approximately 14% of the total volume change. We attribute the significant and rapid erosion and accretion events due to wave-induced longshore transport of sediment. Field observations of monthly beach sediment impoundment in the Kaanapali cell are examined and compared to three models that predict longshore sediment transport (LST). Beach profile results indicate sediment impoundment occurs seasonally with a nearly balanced longshore sediment transport system between profile 5 and 9. Longshore transport rates are derived from seasonal cumulative net volume change in the middle of Kaanapali Beach at profile 7. Cumulative net sediment transport rates are 29,379 m3/yr ±15% to the north and 22,358 m3/yr ± 6% to the south for summer and winter respectively, a net annual rate of 7,021 m3/yr ± 10% to the north and a gross annual rate of 51,736 m3/yr ± 2%. Predictive transport formulas such as CERC (1984), CERC (1991) and Kamphius (1991) predict net annual transport rates at 3 x 103 percent, 77 percent and 6 x 103 percent of the observed transport rates respectively. The presence of fringing reef significantly effects the ability of the LST models to accurately predict sediment transport. When applying the CERC (1984, 1991) and Kamphius (1991) formulas, the functional beach profile area available for sediment transport is assumed much larger than actually exists in Kaanapali because of the presence of a fringing reef that truncates a portion of the sandy profile area. The CERC (1984, 1991) and Kamphius (1991) formulas don't account for the presence of a reef system which may contribute to the models overestimate of longshore sediment transport as they assume the entire profile is mobile sediment. However the fact that the CERC (1991) model underestimates the observed transport implies that additional environmental parameters (such as wave height, direction and period) playa more substantial role than the influence of the reef in the model results. The CERC (1991) Genesis model is found to be superior in fitting the observed longshore transport at Kaanapali Beach. The success of the Genesis model is partly attributed to its' ability to account for short-term changes in near-shore parameters such as wave shoaling, refraction, bathymetry, antecedent conditions and several other shore face parameters not accounted for in the CERC (1984) or Kamphius (1991) formulas. The use of the CERC (1984) formula is prone to practical errors in its' application particularly in the use of the recommended "K" coefficient and wave averaging that may a significantly overestimate the LST. A better fit to the observed LST is achieved with the CERC (1984) if the K value is decreased by an order of magnitude from 0.77 to 0.07. The Kamphius (1991) formula is especially sensitive to extremes in wave period and tends to deviate from observed transport estimates for unusually high wave periods (this study) and approximates observations nicely in areas with low wave periods (Ping Wang et al. (1998). Many of the studied predictive LST formulas are prone to overestimate transport and thus their use requires a comprehensive understanding of the complexities and errors associated with employing them. Great care must be used when applying LST models in areas with significant hard bottom or shallow reefs that alter the beach profile shape. Due to these errors, the use of the CERC (1984) and Kamphius (1991) formulas are better suited as a qualitative interpretative tool of transport direction rather than magnitude.
ix, 62 leaves
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3

McChesney, Ronald John. "A Three Scale Metropolitan Change Model." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1209393707.

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4

Harden, Tamara Shank. "Changes of University of Rhode Island Change Assessment Over Time Associated with Stages of Change." University of Toledo / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1492972365458096.

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5

Cogan, Richard Brian. "Large-scale computer implementations and systemic organizational change." Case Western Reserve University School of Graduate Studies / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=case1054672515.

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6

Rowlands, Daniel James. "Quantifying uncertainty in projections of large scale climate change." Thesis, University of Oxford, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.555296.

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Анотація:
A systematic approach to quantifying uncertainty in climate projections is through the application of observational constraints to an ensemble of climate model simulations. In this thesis we investigate how large perturbed physics ensembles of atmosphere-ocean general circulation model (AOGCM) simulations can be used to represent modelling uncertainty in climate projections. We start by considering the challenges involved in ensemble design owing to the high dimensional parameter space in AOGCMs, introducing the technique of emulation that can be used to efficiently target regions of parameter space having properties of interest for a particular research question. We then present results from the climateprediction.net BBC climate change experiment (BBC CCE), the first multi-thousand member coupled AOGCM ensemble exploring un- certainties in the transient response. We find a "likely" range (66% confidence interval) of 1.4-3K for global mean warming by 2050 relative to 1961-1990 under a mid-range emissions scenario. The range is larger than observed in multi-model ensembles of opportunity, especially at the upper end and is more consistent with the subjective estimate given in the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4). The results provide the first direct AOGCM evidence of high response worlds that are consistent with the recent observed warming, providing an additional set of physically coherent input scenarios that can support climate impact assessments. Application of observational constraints in calculating model error requires a met- ric to weight individual components, often through an inverse covariance matrix. We demonstrate how the sample covariance matrix is a poor estimator in many situations faced in climate research and follow up previous work introducing regularized covariance estimation, which is applied to the analysis of the BBC CCE. This stabilises uncertainty estimates removing the need for empirical choices of the truncation in the model error calculation. Finally we introduce objective Bayesian statistics as a methodology to address some of the difficulties faced when specifying prior distributions for AOGCM parameters. Results from applying Jeffreys' prior to a simplified energy balance model of the climate system suggest the approach can be applied to complex AOGCMs and therefore provides a complementary alternative to more traditional subjective Bayesian methods. However, we conclude that the probabilistic framework adopted in quantifying uncertainty should be partially motivated by the forecast of interest and strength of relevant observational constraints in the climate system.
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7

Graham, Tabitha. "INVESTIGATION OF MEDIA INGREDIENTS AND WATER SOURCES FOR ALGAE CO2 CAPTURE AT DIFFERENT SCALES TO DEMONSTRATE THE CORRELATIONS BETWEEN LAB-SCALE AND LARGE-SCALE GROWTH." UKnowledge, 2013. http://uknowledge.uky.edu/bae_etds/16.

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As energy use increases globally the environmental burdens increase alike. Many accusations have been made that carbon dioxide is a culprit of climate change. The University of Kentucky and Duke Energy Power have partnered to test carbon capture technology in a large scale project. To this end, the objective of this thesis is to investigate potential water media sources and nutrient sources at different volume scales for algae cultivation to help create a more environmentally viable and economically feasible solution. This work will conduct a life cycle assessment of water media sources and the effects of the inputs and outputs needed for each medium. The up-scaling objective of the research is to identify which parameters vary as a result of up-scaling and how to maintain a culture at the large scale that is standardized to the lab scale culture.
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8

Hwang, Anthony D. "Classifying Symptom Change in Eating Disorders: Clinical Significance Metrics for the Change in Eating Disorder Symptoms Scale." BYU ScholarsArchive, 2010. https://scholarsarchive.byu.edu/etd/2563.

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Despite well-established diagnostic measures and measures of specific dimensions of eating disorder symptomatology, little work has been done to develop a brief, comprehensive, and valid measure for assessing change in eating disorder symptoms. Further, empirically-supported change indices to assess treatment progression and outcome have not yet been developed. The Change in Eating Disorder Symptoms Scale (CHEDS) is a new comprehensive measure designed to assess progress and change during treatment in persons with diagnoses on the eating disorder spectrum. Previous studies have demonstrated the subscale structure, reliability, and validity of the CHEDS. This study determined clinically significant change criteria for the CHEDS to complement the studies that have supported the CHEDS as a reliable and valid measure of eating disorder symptomatology. The CHEDS was also compared to a life functioning scale, the Clinical Impairment Assessment. A reliable change index (RCI) was developed, which generated an inferential statistic that estimates the magnitude of change in a score necessary for a change score to be considered statistically reliable. A cutscore was also developed, which differentiates between functional and dysfunctional populations, between eating disordered clinical subjects and non-clinical subjects. Trajectories were identified using hierarchical linear modeling methods for use in conjunction with clinical significance criteria to aid in the tracking of symptoms during treatment, treatment decision-making, and tailoring treatment according to expected and observed progress. The clinical significance change criteria were then applied to the clinical sample to determine change patterns descriptive of recovered, reliable improvement, deterioration, and no change. Finally, a scoring program with clinical significance change criteria and trajectory analyses for total and subscale scores was developed.
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9

Osofsky, Hari. "Scales of Law: Rethinking Climate Change Governance." Thesis, University of Oregon, 2013. http://hdl.handle.net/1794/13297.

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The international treaty regime on climate change is failing to address this problem adequately and cannot fully capture the scales of the problem or of efforts to address it. This dissertation draws from geographic conceptions of scale and legal governance theory to: (1) argue for the value of polycentric, multi-scalar approaches to climate change governance, (2) explore the nuances of what such approaches entail, and (3) propose strategies for improving their effectiveness. It does so by applying these theoretical approaches to three case studies: climate change litigation, federal climate change regulation, and suburban action on climate change. For each of these case studies, it demonstrates the complexity of defining scales and scalar dynamics and considers how the activity being described does and should fit into multi-scalar governance approaches. It concludes by reflecting upon the lessons from the case studies for how to understand the geography of multi-level governance approaches and to approach its core principles of hybridity, multi-scalar, and inclusion. This dissertation includes previously published material.
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Askari, Mina. "Information Theoretic Evaluation of Change Prediction Models for Large-Scale Software." Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/1139.

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During software development and maintenance, as a software system evolves, changes are made and bugs are fixed in various files. In large-scale systems, file histories are stored in software repositories, such as CVS, which record modifications. By studying software repositories, we can learn about open source software development rocesses. Knowing where these changes will happen in advance, gives power to managers and developers to concentrate on those files. Due to the unpredictability in software development process, proposing an accurate change prediction model is hard. It is even harder to compare different models with the actual model of changes that is not available.

In this thesis, we first analyze the information generated during the development process, which can be obtained through mining the software repositories. We observe that the change data follows a Zipf distribution and exhibits self-similarity. Based on the extracted data, we then develop three probabilistic models to predict which files will have changes or bugs. One purpose of creating these models is to rank the files of the software that are most susceptible to having faults.

The first model is Maximum Likelihood Estimation (MLE), which simply counts the number of events i. e. , changes or bugs that occur in to each file, and normalizes the counts to compute a probability distribution. The second model is Reflexive Exponential Decay (RED), in which we postulate that the predictive rate of modification in a file is incremented by any modification to that file and decays exponentially. The result of a new bug occurring to that file is a new exponential effect added to the first one. The third model is called RED Co-Changes (REDCC). With each modification to a given file, the REDCC model not only increments its predictive rate, but also increments the rate for other files that are related to the given file through previous co-changes.

We then present an information-theoretic approach to evaluate the performance of different prediction models. In this approach, the closeness of model distribution to the actual unknown probability distribution of the system is measured using cross entropy. We evaluate our prediction models empirically using the proposed information-theoretic approach for six large open source systems. Based on this evaluation, we observe that of our three prediction models, the REDCC model predicts the distribution that is closest to the actual distribution for all the studied systems.
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Книги з теми "Scale change"

1

Dannemiller, Kathleen D. Whole-scale change. San Francisco, Calif: Berrett Koehler Communications, 1999.

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2

The scale of change. Newcastle upon Tyne: Flambard Press, 2011.

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3

Escalona, Julio, and Andrew Reynolds, eds. Scale and Scale Change in the Early Middle Ages. Turnhout: Brepols Publishers, 2011. http://dx.doi.org/10.1484/m.tmc-eb.6.09070802050003050302030904.

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4

Jean-François, Laugel, ed. Large scale organizational change: An executive's guide. Boston: Butterworth-Heinemann, 2000.

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5

Climate change at the city scale: Impacts, mitigation and adaptation in Cape Town. Abingdon, Oxon, UK: Earthscan, 2012.

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6

Museum of Modern Art (New York, N.Y.), ed. Small scale, big change: New architectures of social engagement. New York: Museum of Modern Art, 2010.

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7

Keith, Pocklington, ed. Managing complex educational change: Large-scale reorganisation of schools. London: RoutledgeFalmer, 2002.

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8

Vláčil, Jan. Large-scale privatization: Social conflict and consensus. Praha: Institute of Sociology, Academy of Sciences of the Czech Republic, 1994.

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9

Leithwood, Kenneth A. Large-scale reform: What works? [Toronto]: s.n., 1999.

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10

No local: Why small-scale alternatives won't change the world. Winchester, UK: Zero Books, 2012.

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Частини книг з теми "Scale change"

1

Frankman, Myron J. "Steering and Scale Change." In World Democratic Federalism, 29–54. London: Palgrave Macmillan UK, 2004. http://dx.doi.org/10.1057/9780230500174_2.

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Mitra, Dana L. "Sustainability and Scale." In Educational Change and the Political Process, 232–49. 2nd ed. New York: Routledge, 2022. http://dx.doi.org/10.4324/9781003212294-16.

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Götz, Georg. "The Large Scale Dynamics Are Reasonably Well Understood, Un-Certainty Lies in the Parametrization of Small-Scale Processes." In Global Change, 25–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-23444-6_4.

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4

Pujar, Narahari, Duncan Low, and Rhona O'Leary. "ANTIBODY PURIFICATION: DRIVERS OF CHANGE." In Process Scale Purification of Antibodies, 699–716. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119126942.ch32.

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Lawson, Andrew B. "Ecological Analysis and Scale Change." In Statistical Methods in Spatial Epidemiology, 247–68. West Sussex, England: John Wiley & Sons, Ltd., 2013. http://dx.doi.org/10.1002/9780470035771.ch9.

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Patwardhan, Savita, K. P. Sooraj, Hamza Varikoden, S. Vishnu, K. Koteswararao, M. V. S. Ramarao, and D. R. Pattanaik. "Synoptic Scale Systems." In Assessment of Climate Change over the Indian Region, 143–54. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4327-2_7.

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Cebe, Emine, and Mustafa Cebe. "The Study of Energy Change in Radical Systems." In Large-Scale Molecular Systems, 407–12. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4684-5940-1_31.

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8

Prentice, I. Colin, Robert A. Monserud, Thomas M. Smith, and William R. Emanuel. "Modeling Large-Scale Vegetation Dynamics." In Vegetation Dynamics & Global Change, 235–50. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-2816-6_12.

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Batra, Geeta, Jeneen Garcia, and Kseniya Temnenko. "Transformational Change for Achieving Scale: Lessons for a Greener Recovery." In Transformational Change for People and the Planet, 27–38. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-78853-7_3.

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AbstractAchieving transformational changes that can be then effectively scaled up requires ambition in design, a supportive policy environment, sound project design and implementation, partnerships, and multistakeholder participation. This chapter presents a framework that can be applied at the design stage to plan for change and scaling up and provides relevant lessons based on GEF interventions. Achieving change and scale can be an iterative and a continuous process until impacts are generated at the magnitude and scope of the targeted scale. Successful transformations typically adopt a systems approach and address multiple constraints to attain environmental and other socioeconomic impacts.
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Laprise, René, Dragana Kornic, Maja Rapaić, Leo Šeparović, Martin Leduc, Oumarou Nikiema, Alejandro Di Luca, et al. "Considerations of Domain Size and Large-Scale Driving for Nested Regional Climate Models: Impact on Internal Variability and Ability at Developing Small-Scale Details." In Climate Change, 181–99. Vienna: Springer Vienna, 2012. http://dx.doi.org/10.1007/978-3-7091-0973-1_14.

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Тези доповідей конференцій з теми "Scale change"

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"Alpine Resources - Use, valorisation and management from local to macro-regional scale." In Global Change Programme. Wien: Verlag der Österreichischen Akademie der Wissenschaften, 2015. http://dx.doi.org/10.1553/forumalpinum2014s1.

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MURRAY, A. B., E. D. LAZARUS, L. J. MOORE, J. LIGHTFOOT, A. D. ASHTON, D. E. MCNAMARA, and K. ELLS. "DECADAL SCALE SHORELINE CHANGE ARISES FROM LARGE-SCALE INTERACTIONS, WHILE SMALL-SCALE CHANGES ARE FORGOTTEN: OBSERVATIONAL EVIDENCE." In Coastal Sediments 2015. WORLD SCIENTIFIC, 2015. http://dx.doi.org/10.1142/9789814689977_0226.

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Mohammed, Murtala Ahmed, Kenneth S. Sorbie, and A. G. Shepherd. "Thermodynamic Modelling of Naphthenate Formation and Related pH Change Experiments." In SPE International Oilfield Scale Conference. Society of Petroleum Engineers, 2008. http://dx.doi.org/10.2118/114034-ms.

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"Multi-scale satellite assessment of water availability and agricultural drought:from field to global scales." In ASABE 1st Climate Change Symposium: Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152123964.

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Eklund, Neil H. W., and Xiao Hu. "Multi-Scale Rank-Permutation Change Localization." In 2007 IEEE Aerospace Conference. IEEE, 2007. http://dx.doi.org/10.1109/aero.2007.352847.

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Ito, Masahiro, and Yoshito Tsuchiya. "Time Scale for Modeling Beach Change." In 20th International Conference on Coastal Engineering. New York, NY: American Society of Civil Engineers, 1987. http://dx.doi.org/10.1061/9780872626003.088.

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KARUNARATHNA, HARSHINIE, YOSHIAKI KURIYAMA, HAJIME MASE, JOSE HORRILLO-CARABALLO, and DOMINIC E. REEVE. "MODELLING INTER-ANNUAL SCALE BEACH CHANGE." In Coastal Sediments 2015. WORLD SCIENTIFIC, 2015. http://dx.doi.org/10.1142/9789814689977_0037.

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Fennell, Jon. "Water in a Changing Climate: Understanding&Adapting at the Basin Scale." In 2006 IEEE EIC Climate Change Conference. IEEE, 2006. http://dx.doi.org/10.1109/eicccc.2006.277250.

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Durrani, Tariq S., and Sheila Forbes. "Creating change and developing large-scale organisations." In 2007 IEEE International Engineering Management Conference - EM 2007 (IEMC). IEEE, 2007. http://dx.doi.org/10.1109/iemc.2007.5235056.

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Kim, Euyoung, and Kyoung Mu Lee. "Scale-change aware locally adaptive optical flow." In 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA). IEEE, 2016. http://dx.doi.org/10.1109/apsipa.2016.7820725.

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Звіти організацій з теми "Scale change"

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A., Casson, Muliastra Y.I.K.D., and Obidzinski K. Large-scale plantations, bioenergy developments and land use change in Indonesia. Center for International Forestry Research (CIFOR), 2014. http://dx.doi.org/10.17528/cifor/005434.

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Nemoto, Jiro, and Mika Goto. Productivity, Efficiency, Scale Economies and Technical Change: A New Decomposition Analysis. Cambridge, MA: National Bureau of Economic Research, May 2005. http://dx.doi.org/10.3386/w11373.

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Blackford, Johanna. Paradigm Shifts in Large-Scale Educational Change: Uncovering the Oregon Education Investment Board's Theory of Change-in-Action. Portland State University Library, February 2020. http://dx.doi.org/10.15760/etd.7293.

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Kunreuther, Howard, and Erwann Michel-Kerjan. Climate Change, Insurability of Large-scale Disasters and the Emerging Liability Challenge. Cambridge, MA: National Bureau of Economic Research, January 2007. http://dx.doi.org/10.3386/w12821.

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Bishop, David, and Robert Fuller. Resilience in Nicaragua: Impact evaluation of climate change adaptation among small scale producers. Oxfam GB, December 2015. http://dx.doi.org/10.21201/2015.583534.

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Daniels, R. C., R. A. Houghton, and J. L. Hackler. Continental scale estimastes of the biotic carbon flux from land cover change: 1850 to 1980. Office of Scientific and Technical Information (OSTI), March 1995. http://dx.doi.org/10.2172/80344.

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Lee-Gammage, Samuel. What is land use and land use change? Edited by Tara Garnett. Food Climate Research Network, February 2018. http://dx.doi.org/10.56661/4af265b4.

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Human use and alteration of land has profound effects on the environment, both locally where it takes place, and at the planetary scale via climate change and other mechanisms. This building block explains what is meant by land use and land use change, both direct and indirect.
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Guerzovich, Florencia, Tom Aston, Brian Levy, Paula Chies Schommer, Rebecca Haines, Sue Cant, and Grazielli Faria Zimmer Santos. How do we shape and navigate pathways to social accountability scale? Introducing a middle-level Theory of Change. Centre for Excellence and Development Impact and Learning (CEDIL), February 2022. http://dx.doi.org/10.51744/crpp1.

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This CEDIL Research project paper, ‘How do we shape and navigate pathways to social accountability scale? Introducing a middle-level Theory of Change’, argues that practitioners can pursue at least three pathways to scale: the replication of best practice, through leveraging the countervailing power of resistance, and seeking resonance with existing public sector efforts.
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D’Souza, Marcella, Arjuna Srinidhi, Shreya Banerjee, Abha Indurkar, Eshwer Kale, Larissa Stiem-Bhatia, and Naman Gupta. Scaling Ecosystem-based Adaptation to Climate Change in Maharashtra, India. TMG Research gGmbH, May 2020. http://dx.doi.org/10.35435/1.2020.1.

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Lindquist, W. Brent, Keith W. Jones, Wooyong Um, mark Rockhold, Catherine A. Peters, and Michael A. Celia. EFFECTS OF PORE STRUCTURE CHANGE AND MULTI-SCALE HETEROGENEITY ON CONTAMINANT TRANSPORT AND REACTION RATE UPSCALING. Office of Scientific and Technical Information (OSTI), February 2013. http://dx.doi.org/10.2172/1125009.

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