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Journal articles on the topic 'Impact of change'

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Author: Grafiati

Published: 4 June 2021

Last updated: 28 January 2023

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1

Gerstengarbe, Friedrich-Wilhelm, Fred Hattermann, and Peggy Gräfe. "German climate change impact study." Meteorologische Zeitschrift 24, no. 2 (April 13, 2015): 121–22. http://dx.doi.org/10.1127/metz/2015/0666.

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2

SUN, XIAOBING, BIXIN LI, WANZHI WEN, and SAI ZHANG. "ANALYZING IMPACT RULES OF DIFFERENT CHANGE TYPES TO SUPPORT CHANGE IMPACT ANALYSIS." International Journal of Software Engineering and Knowledge Engineering 23, no. 03 (April 2013): 259–88. http://dx.doi.org/10.1142/s0218194013500071.

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Software change impact analysis (CIA) is a key technique for identifying unpredicted and potential effects caused by changes made to software. Different changes have different ripple effects to other parts in the program, even some changes do not affect other entities in spite of some dependencies existing between these entities and the modified one. This induces imprecision if such a factor is neglected. This article proposes a static CIA technique which considers the impact rules of different change types to predict the change effects. Input of our CIA includes changed classes, class methods and class fields, and the output is composed of potentially affected classes, class methods, and class fields. Precision improvement of the CIA technique relies on three aspects: change types of a modified entity, dependencies between the modified entity and other entities, and a precise initial impact set (IIS), on which the final impact set (FIS) is computed. Experimental case studies demonstrate the effectiveness of our technique, and present its potential applications in software maintenance.

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3

Kumar, Kiran. "Impact of Climate Change on Human Health." Indian Journal of Applied Research 4, no. 1 (October 1, 2011): 309–11. http://dx.doi.org/10.15373/2249555x/jan2014/90.

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4

Ingole, Sangita P., and Aruna U. Kakde. "Global Warming and Climate Change: Impact on Biodiversity." International Journal of Scientific Research 2, no. 5 (June 1, 2012): 288–90. http://dx.doi.org/10.15373/22778179/may2013/96.

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5

Bertelsmeier, Cleo, Gloria M. Luque, and Franck Courchamp. "The impact of climate change changes over time." Biological Conservation 167 (November 2013): 107–15. http://dx.doi.org/10.1016/j.biocon.2013.07.038.

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6

Khanh Dam, Hoa. "Predicting change impact in Web service ecosystems." International Journal of Web Information Systems 10, no. 3 (August 12, 2014): 275–90. http://dx.doi.org/10.1108/ijwis-03-2014-0006.

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Purpose – The paper aims to address the issue of Web service providers facing a major issue of estimating the potential effects of changing a Web service to other services, especially in large ecosystems of Web services which have become more common nowadays. Web service providers make constant changes to their Web services to meet the ever-changing business requirements. Design/methodology/approach – The paper proposes an approach to predict change impact by mining a version history of a Web service ecosystem. The proposed approach extracts patterns of Web services that have been changed together from the version history by using association rule data mining techniques. The approach then uses this knowledge of co-changed patterns for predicting the impact of future changes based on the assumption that Web services which have been changed together frequently in the past will likely be changed together in future. Findings – An empirical validation based on the Amazon’s ecosystem of 46 Web services indicates the effectiveness of the proposed approach. After an initial change, the proposed approach can correctly predict up to 25 per cent of further Web services to be changed with the precision of up to 82 per cent. Originality/value – Traditional approaches to predict change impact in Web services tend to rely on having a dependency graph between Web services. However, in practice, building and maintaining inter-service dependencies that capture the precise semantics and behaviours of the Web services are challenging and costly. The proposed approach offers a novel alternative which only requires mining the existing version history of Web services.

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7

Smith, Sean. "Small Change, Big Impact." Theological Librarianship 12, no. 1 (April 24, 2019): 1–2. http://dx.doi.org/10.31046/tl.v12i1.536.

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Library assessment at the BU School of Theology Library identified one glaring weakness of our institution: the lack of useable collaborative/group study space. Staff identified one particular spot: a beautiful, but rarely used conference room for group study space, down a forbidding administrative hallway, as a short-term bandage for this weakness. Despite its deficiencies, this short-term solution it has become a popular spot in the library. Patron visits to the library increased over 10% during the first couple of months of the Fall 2018 semester. In an era of tightening library budgets for small, academic, and Theological libraries, aggressive data-collection and creative re-imagining of space can pay big dividends.

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8

Gupta, Chetna, and Varun Gupta. "Software Change Impact Analysis." International Journal of Systems and Service-Oriented Engineering 5, no. 2 (April 2015): 44–55. http://dx.doi.org/10.4018/ijssoe.2015040103.

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This paper presents an approach to prioritize program segments within the impact set computed using functional call graph to assist regression testing for test case prioritization. The presented technique will first categorize the type of impact propagation and then prioritize the impacted segments into higher and lower levels based on propagation categorization. This will help in saving maintenance cost and effort by allocating higher priority to those segments which are impacted more within the impacted set. Thus a software engineer can first run those test cases which cover segments with higher impacted priority to minimize regression test selection.

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9

Bruce, James P. "Impact of climate change." Nature 377, no. 6549 (October 1995): 472. http://dx.doi.org/10.1038/377472a0.

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10

Sundaraman, N. "Impact of climate change." Nature 377, no. 6549 (October 1995): 472. http://dx.doi.org/10.1038/377472b0.

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11

Bamane, B. D. "Impact of technological change." Technovation 14, no. 1 (February 1994): 3–5. http://dx.doi.org/10.1016/0166-4972(94)90065-5.

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12

Muhammad Ali, Nawazeesh. "Impact of climate change and natural catastrophe on the occupational changes in the coastal areas of Bangladesh: an empirical study." Environmental Economics 9, no. 1 (February 6, 2018): 22–37. http://dx.doi.org/10.21511/ee.09(1).2018.02.

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Occupation of the populace who live in the coastal areas of Bangladesh needs to be changed in the pattern of source of income owing to sea level rise and natural disaster in a cyclical manner and also irregular variations. This is now a great concern for Bangladesh especially in the country’s coastal regions. As such, the research question relates to assessing the impact of climate change and natural catastrophe on the occupational changes in the coastal areas of Bangladesh. This study explored using both primary and secondary sources. The study had been conducted from May to December 2017. The study found that climate change was causing sea level raising and created salinity problem in the coastal areas, which has caused change of the occupational changes. Salinity problem had caused damage of most of the agricultural production, fisheries and household. The binary logistic regression equation indicated that occupational change was due to climate change and natural catastrophe that also depend on socio-economic situation of the people of that area of the country. From another binary logistic regression equation, it was found that occupational change also depends on the various demographic factors and if the personal position of the respondents is changed then it will occur. Each year in coastal areas, people are permanently and temporarily dispersed because of global warming in Bangladesh. The country should take effective steps in the coastal areas to diminish climate change threat and also control over its phenomenon. Those who are responsible internally to increase climate change should be supported by creating employment opportunities for affecting community development as suggested by the researcher. To reduce natural catastrophe, more trees should be planted in the coastal regions, and there is a need in balanced development at urban and rural areas without destroying nature.

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13

Pooja, Pooja. "Impact of COVID-19 and Climate Change on Indian Agriculture." Emerging Trends in Climate Change 1, no. 1 (April 30, 2022): 29–36. http://dx.doi.org/10.18782/2583-4770.104.

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Climate change and pandemics both disrupt global food supply chains on their own. Natural and human disasters, such as droughts, cyclones and pandemics, have become more common in the twenty-first century. Their combined effects can result in severe economic stress and malnutrition, especially in developing nations. Understanding how climate change and pandemics interact and developing strategies to address them both together and separately is critical to ensuring a stable global food supply. This paper examines the consequences of these disasters in terms of food and agriculture and then discusses how they are compounded. We discuss the implication of policy and suggest research topics for the future.

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14

ESTRADA, FRANCISCO, and RICHARD S. J. TOL. "TOWARD IMPACT FUNCTIONS FOR STOCHASTIC CLIMATE CHANGE." Climate Change Economics 06, no. 04 (November 2015): 1550015. http://dx.doi.org/10.1142/s2010007815500153.

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Most functions of economic impact assume that climate change is smooth. We here propose impact functions that have stochastic climate change as an input. These functions are identical in shape and have similar parameters as do deterministic impact functions. The mean stochastic impacts are thus similar to deterministic impacts. Welfare effects are larger, and the stochasticity premium is larger than the risk premium. Results suggest that stochasticity is more important for past impacts than for future impacts. This outcome is partly caused by an underestimation of natural variability in the 21st century climate projections.

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15

DE, U. S. "Climate change impact : Regional scenario." MAUSAM 52, no. 1 (December 29, 2021): 201–12. http://dx.doi.org/10.54302/mausam.v52i1.1688.

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Climate change and global warming are going to be the major issues for the 21st century. Their impacts on agriculture, water availability and other natural resources are of serious concern. The paper briefly summarizes the existing information on global warming, past climatic anomalies and occurrence of extreme events vis-a-vis their impact on south Asia in general and Indian in particular. Use of GCM models in conjunction with crop simulation models for impact assessment in agriculture are briefly touched upon. The impact on hydrosphere in terms of water availability and on the forests in India are also discussed. A major shift in our policy makers paradigm is needed to make development sustainable in the face of climate change, global warming and sea level rise.

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16

Andréasson, Johan, Sten Bergström, Bengt Carlsson, L. Phil Graham, and Göran Lindström. "Hydrological Change – Climate Change Impact Simulations for Sweden." AMBIO: A Journal of the Human Environment 33, no. 4 (June 2004): 228–34. http://dx.doi.org/10.1579/0044-7447-33.4.228.

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17

Raineri, Andrés B. "Change management practices: Impact on perceived change results." Journal of Business Research 64, no. 3 (March 2011): 266–72. http://dx.doi.org/10.1016/j.jbusres.2009.11.011.

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18

Hemed, Ahmed, Latifa Ouadif, Lahcen Bahi, and Abdelaziz Lahmili. "Impact of climate change on pavements." E3S Web of Conferences 150 (2020): 01008. http://dx.doi.org/10.1051/e3sconf/202015001008.

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Climate change is reflected in changes in average weather conditions and the more frequent occurrence of extreme conditions. It also affects the field of road transport and shows impacts both on traffic and road users as well as on the road infrastructure itself. The main objective of this work is therefore to evaluate the impact of climate change on the performance of road infrastructure (pavements) and to educe recommendations through proposals for adaptation measures. The impacts of climate change on road infrastructure result in changes in some road design parameters (average temperatures, radiation index, etc.). The different cases of cracking (fatigue or other) are assessed separately using degradation indices for each layer composing a pavement (surface layer, base layer, stabilized layer, etc.)

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19

Chuen Khee, Pek. "The economic impact of climate change on food security in Malaysia." International Journal of Academic Research 6, no. 3 (May 30, 2014): 195–99. http://dx.doi.org/10.7813/2075-4124.2014/6-3/b.29.

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20

Vranová, V., P. Formánek, K. Rejšek, and M. Pavelka. "Impact of land-use change on proteolytic activity of mountain meadows." Soil and Water Research 4, No. 3 (September 22, 2009): 122–25. http://dx.doi.org/10.17221/16/2009-swr.

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Casein-protease activity assessed at 50°C and with adjustment of optimum pH conditions (PA), and casein-protease activity near soil pH and at field soil temperature (LPA) were studied one vegetation period in mountain meadow soils covered with moderately mown vegetation, and over which vegetation had been abandoned for thirteen years. PA peaked in the first part of the vegetation season whereas LPA increased throughout the season; in addition, LPA was not linearly related to temperature (r = 0.127 resp. 0.312; P > 0.05). The combined effect of field soil temperature and pH decreased a casein-protease activity by > 98.4%. A management of meadows had no significant (P > 0.05) effect on PA and LPA.

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21

Barimah, Prince Twum. "Impact of climate change on maize production in Ghana. A review." Journal of Agricultural Science and Applications 03, no. 04 (December 31, 2014): 89–93. http://dx.doi.org/10.14511/jasa.2014.030402.

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22

Hollý, Ján, and Adela Palková. "Climate change impact – residential unit." MATEC Web of Conferences 279 (2019): 03007. http://dx.doi.org/10.1051/matecconf/201927903007.

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The issue of climate change is undeniably demonstrating its presence. Consequently, there is a rising need to be prepared for upcoming threats by any means possible. One of the precautions includes obtaining the information characterizing the expected impact of global warming. This will allow authorities and other stakeholders to act accordingly in time. The article presents the assessment of the extent of impact of energy-related construction solutions in dwelling type unit situated in Central Europe region under the 21st century climate conditions. The findings represent eventual demands of energy for cooling and heating and its prospective savings. This is conducted by consecutively and automatically changing the parameters in individual simulation runs. As a basis for simulations, regionally scaled weather data of three different climate areas are used. These data are based on the emission scenarios by IPCC and are reaching to the year 2100. The selection of assessed parameters and climate data application are briefly explained in the article. The results of simulations are evaluated and recommended solutions are stated in regard to the specific energy-related construction changes. The aim is to successfully mitigate and adapt to the climate change phenomenon.

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23

Liu, Alex X. "Firewall policy change-impact analysis." ACM Transactions on Internet Technology 11, no. 4 (March 2012): 1–24. http://dx.doi.org/10.1145/2109211.2109212.

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24

Hilbrink, J. O. "Economic impact and technical change." IEEE Transactions on Engineering Management 36, no. 1 (1989): 37–46. http://dx.doi.org/10.1109/17.19981.

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25

Foster, Sam. "Assessing the impact of change." British Journal of Nursing 27, no. 12 (June 28, 2018): 721. http://dx.doi.org/10.12968/bjon.2018.27.12.721.

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26

Tyson, J. D. "Prioritising economic impact of change." Veterinary Record 157, no. 4 (July 23, 2005): 123. http://dx.doi.org/10.1136/vr.157.4.123.

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27

Doarn, Charles R., and Ronald C. Merrell. "Recognizing Change and Measuring Impact." Telemedicine and e-Health 22, no. 3 (March 2016): 181–82. http://dx.doi.org/10.1089/tmj.2016.29003.crd.

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28

Frybourg, M. "The Impact of Technological Change." Environment and Planning C: Government and Policy 6, no. 2 (June 1988): 145–52. http://dx.doi.org/10.1068/c060145.

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How can technology be better utilized to meet socioeconomic needs? Technological change is closely related to societal change. At the level of the firm, technology is a tool to achieve and sustain competitive advantage but radical innovation is system oriented and involves infrastructure. The paramount role of information technology has to be emphasised. Two new concepts are emerging; Just in Time/Total Quality Control (JIT/TQC) and Electronic Data Interchange (EDI). So-called value-added-networks or VANs are catching on in Western countries. The bottlenecks are the costs, the externalities, the lack of standardization, and the system incoherence. Brief case-studies are developed: The new generation of metros, high speed trains, the motor industry, and intermodalism with utilization of High-Cube containers. The findings of these studies show that organizational innovation has to go along with technological innovation.

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29

Jänicke, Martin, Harald Mönch, Thomas Ranneberg, and Udo E. Simonis. "Structural change and environmental impact." Intereconomics 24, no. 1 (January 1989): 24–35. http://dx.doi.org/10.1007/bf02928545.

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30

Begum, Mahima. "Impact of Climate Change on Agriculture and Its Allied Sectors: An Overview." Emerging Trends in Climate Change 1, no. 1 (April 30, 2022): 19–28. http://dx.doi.org/10.18782/2583-4770.103.

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Global climate change is one of the rising international issues of modern civilization. It has impacted the way of living of each and every organism. The agricultural sector is one such highly impaired sector that has been affected by climate change. With the rise of atmospheric temperature, soil conditions get worsened; the normal physiology of plants has also changed, ultimately resulting in lesser yield as compared to yield potential yield. The agricultural sector has a significant impact on the Economy of the country. The reduction in yield due to climate change has resulted in a decrease in monetary return. The impaired quality of the product in terms of nutrients, minerals, antioxidants, and other biochemical content has induced various diseases and deficiencies in plants and animals. The plant becomes highly susceptible to pests and pathogens. Other allied sectors like animal husbandry, fishery, poultry etc., also get affected due to the changes in weather parameters. Climate change has a clear and profound impact on the food web, health and Economy of every living being on the Earth. Researches and experiments should be conducted to find out future trends and mitigation techniques to cope with global climate change.

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31

Mengel, Matthias, Simon Treu, Stefan Lange, and Katja Frieler. "ATTRICI v1.1 – counterfactual climate for impact attribution." Geoscientific Model Development 14, no. 8 (August 20, 2021): 5269–84. http://dx.doi.org/10.5194/gmd-14-5269-2021.

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Abstract. Attribution in its general definition aims to quantify drivers of change in a system. According to IPCC Working Group II (WGII) a change in a natural, human or managed system is attributed to climate change by quantifying the difference between the observed state of the system and a counterfactual baseline that characterizes the system's behavior in the absence of climate change, where “climate change refers to any long-term trend in climate, irrespective of its cause” (IPCC, 2014). Impact attribution following this definition remains a challenge because the counterfactual baseline, which characterizes the system behavior in the hypothetical absence of climate change, cannot be observed. Process-based and empirical impact models can fill this gap as they allow us to simulate the counterfactual climate impact baseline. In those simulations, the models are forced by observed direct (human) drivers such as land use changes, changes in water or agricultural management but a counterfactual climate without long-term changes. We here present ATTRICI (ATTRIbuting Climate Impacts), an approach to construct the required counterfactual stationary climate data from observational (factual) climate data. Our method identifies the long-term shifts in the considered daily climate variables that are correlated to global mean temperature change assuming a smooth annual cycle of the associated scaling coefficients for each day of the year. The produced counterfactual climate datasets are used as forcing data within the impact attribution setup of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). Our method preserves the internal variability of the observed data in the sense that factual and counterfactual data for a given day have the same rank in their respective statistical distributions. The associated impact model simulations allow for quantifying the contribution of climate change to observed long-term changes in impact indicators and for quantifying the contribution of the observed trend in climate to the magnitude of individual impact events. Attribution of climate impacts to anthropogenic forcing would need an additional step separating anthropogenic climate forcing from other sources of climate trends, which is not covered by our method.

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32

Vieira, Andreza, and Franklin Ramalho. "Towards Measuring the Change Impact in ATL Model Transformations." International Journal of Software Engineering and Knowledge Engineering 26, no. 02 (March 2016): 153–81. http://dx.doi.org/10.1142/s021819401650008x.

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The Model-Driven Development (MDD) approach shifts the focus on code to models in the software development process. In MDD, model transformations are elements that play an important role. MDD-based projects evolve along their lifecycle in a way that changes in their transformations are frequent. Before applying changes it is important to measure their impacts within the transformation. However, currently no technique helps practitioners in this direction. We propose an approach to measure the change impact in ATL model transformations. Based on static analysis, it detects the elements impacted by a change and calculates the change impact value through three metrics we defined. By using our approach, practitioners can (i) save effort and development time since the elements impacted with the change are automatically detected and (ii) better schedule and prioritize changes according to the impact value. To empirically evaluate our approach we conducted a case study.

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33

Soeparno, Koentjoro, and Budi Andayani. "Social and Climate Change: Impact on Human Behavior." ANIMA Indonesian Psychological Journal 30, no. 1 (October 25, 2014): 1–7. http://dx.doi.org/10.24123/aipj.v30i1.531.

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The nature of social change occurs at the center of human consciousness and based on a commitment, it cannot be reversed, rejected, or canceled (Vago, 2004). Therefore, there are economic and political orders as a result of conflict of ideologies within society. Historically, global social change is caused by the Industrial Revolution and Ideology and Gender Revolution. The invention of telegraph was the beginning of globalization, identified by the 4T revolution (Telecommunications, Transport, Tourism and Transparency). The revolution in agriculture, mining, manufacturing and industry results changes in lifestyle and exploitation of natural resources that can cause climate change. The second source of social change is the revolution of ideology and gender. When colonialism, slavery and deprivation of human rights occurred, the movement to struggle for human rights as its counterculture appeared, resulting in 1980 the pro-human right movement products. The sexual revolution in the 1960s in the USA demanded for equal rights between men and women. The 1975 UNFPA population convention held in Cairo have made an agreement to restrict population growth using contraception, resulting later-on the concept that sex is no longer for reproductive purpose but for recreation. People’s lifestyle has changed since then.

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34

German, Daniel M., Ahmed E. Hassan, and Gregorio Robles. "Change impact graphs: Determining the impact of prior codechanges." Information and Software Technology 51, no. 10 (October 2009): 1394–408. http://dx.doi.org/10.1016/j.infsof.2009.04.018.

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35

Moselhi, Osama, Charles Leonard, and Paul Fazio. "Impact of change orders on construction productivity." Canadian Journal of Civil Engineering 18, no. 3 (June 1, 1991): 484–92. http://dx.doi.org/10.1139/l91-059.

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In construction projects it is virtually certain that there will be changes made during the course of the work, and that the owner (or design professional) and the contractor will seldom agree on the cost and schedule impact of the changes. This is particularly so on fast track construction, where design and construction are overlapped to accelerate the delivery of projects. Without a doubt, the most contentious area of impact of change orders is their effect on the productivity of the contractor's labour force. This paper presents the quantitative results of a comprehensive field investigation using 90 cases drawn from 57 different construction projects to identify the effects of change orders on productivity. The results indicate a significant direct correlation between the labour component of change orders and the loss of productivity, for both civil/architectural and electrical/mechanical works. These losses are exacerbated by the added presence of other major causes of productivity losses such as acceleration and inadequate scheduling and coordination. Regression models are developed for the direct estimation of productivity losses due to change orders, incurred both independently and in conjunction with other major causes of productivity loss. Key words: construction, productivity, change orders, contemplated changes, impact cost, quantitative models.

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36

Hakim, Dani Lukman, and Dedi Herdiansah. "Food Security Production Challenges in Indonesia as Impact of Global Climate Change." International Journal of Environmental and Agriculture Research 3, no. 8 (July 31, 2017): 26–33. http://dx.doi.org/10.25125/agriculture-journal-ijoear-jul-2017-2.

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37

Singh, Nayanika, and S. K. Srivastava S. K. Srivastava. "Climate Change and Children; Impact on Health and Wellbeing – A Comprehensive Overview." Indian Journal of Applied Research 3, no. 2 (October 1, 2011): 326–29. http://dx.doi.org/10.15373/2249555x/feb2013/112.

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38

Badri, Linda, Mourad Badri, and Nicolas Joly. "Towards a Change Impact Analysis Model for Java Programs: An Empirical Evaluation." Journal of Software 10, no. 4 (April 2015): 441–53. http://dx.doi.org/10.17706/jsw.10.4.441-453.

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39

Veerabhadrannavar, Shilpa A., and B. Venkatesh. "Assessment of Impact of Climate Change in the Western Ghats Region, India." Indian Journal Of Science And Technology 15, no. 30 (August 13, 2022): 1466–72. http://dx.doi.org/10.17485/ijst/v15i30.676.

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40

Pavlović, Aleksandra, Ana Frank, Andrea Ivanišević, and Ivana Katić. "The Impact of Climate Change on Sustainable Development: The Case of Vojvodina." International Journal of Industrial Engineering and Management 12, no. 2 (June 30, 2021): 141–50. http://dx.doi.org/10.24867/ijiem-2021-2-283.

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41

Kocmánková, E., M. Trnka, J. Juroch, M. Dubrovský, D. Semerádová, M. Možný, and Z. Žalud. "Impact of climate change on the occurrence and activity of harmful organisms." Plant Protection Science 45, Special Issue (January 3, 2010): S48—S52. http://dx.doi.org/10.17221/2835-pps.

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Climate conditions exert a significant influence over the spreading, life cycle duration, infestation pressure and the overall occurrence of majority of agricultural pests and diseases. Recently there is paid a big attention to possible climate change and its impacts resulting the threat to the controlled agro ecosystems. In the context of actual climate change there is likely the shift in the occurrence of some pests and diseases and at the same time also the change of the spectrum of harmful organisms. Direct results of the effect of higher temperatures on the pests’ lifecycle can involve the acceleration of pests’ development due to the faster achieving of number of degree-days which can result the shift of pests to higher altitudes. There is likely the increase of the number of generations of some pests and higher population density in the consequence of prolonged growing season and the period favourable for reproduction. Changed conditions during the period of overwintering could be the determining factor for population dynamic of insect and fungi.

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42

Mitchell, Jamie A., Philip E. Bett, Helen M. Hanlon, and Andrew Saulter. "Investigating the impact of climate change on the UK wave power climate." Meteorologische Zeitschrift 26, no. 3 (June 14, 2017): 291–306. http://dx.doi.org/10.1127/metz/2016/0757.

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43

Schoetter, Robert, David Grawe, Peter Hoffmann, Peter Kirschner, Angelika Grätz, and K. Heinke Schlünzen. "Impact of local adaptation measures and regional climate change on perceived temperature." Meteorologische Zeitschrift 22, no. 2 (April 1, 2013): 117–30. http://dx.doi.org/10.1127/0941-2948/2013/0381.

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44

R.SONA, R. SONA, and G. MURALI MANOHARI. "An Observational Study on Millennial Trends and its Impact on Organizational Change." Global Journal For Research Analysis 3, no. 6 (June 15, 2012): 1–2. http://dx.doi.org/10.15373/22778160/june2014/88.

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45

Singh, Priyanka, and Dr Madan Lal Dr Madan Lal. "Structural Change in India: The Impact of Technology on The Textile Industry." Global Journal For Research Analysis 3, no. 3 (June 15, 2012): 144–45. http://dx.doi.org/10.15373/22778160/mar2014/66.

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Haasnoot, Marjolijn, and D. T. Van der Molen. "Impact of climate change on ecotopes of the rivers Rhine and Meuse." Large Rivers 15, no. 1-4 (December 19, 2003): 53–61. http://dx.doi.org/10.1127/lr/15/2003/53.

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Semadeni-Davies, A. "Response surfaces for climate change impact assessments in urban areas." Water Science and Technology 48, no. 9 (November 1, 2003): 165–75. http://dx.doi.org/10.2166/wst.2003.0518.

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Assessment of the impacts of climate change in real-world water systems, such as urban drainage networks, is a research priority for IPCC (Intergovernmental Panel of Climate Change). The usual approach is to force a hydrological transformation model with a changed climate scenario. To tackle uncertainty, the model should be run with at least high, middle and low change scenarios. This paper shows the value of response surfaces for displaying multiple simulated responses to incremental changes in air temperature and precipitation. The example given is inflow, related to sewer infiltration, at the Lycksele waste water treatment plant. The range of plausible changes in inflow is displayed for a series of runs for eight GCMs (Global Circulation Model; ACACIA; Carter, 2002, pers. comm.). These runs are summarised by climate envelopes, one for each prediction time-slice (2020, 2050, 2080). Together, the climate envelopes and response surfaces allow uncertainty to be easily seen. Winter inflows are currently sensitive to temperature, but if average temperature rises to above zero, inflow will be most sensitive to precipitation. Spring inflows are sensitive to changes in winter snow accumulation and melt. Inflow responses are highly dependent on the greenhouse gas emission scenario and GCM chosen.

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Thorne, O. M., and R. A. Fenner. "Risk-based climate-change impact assessment for the water industry." Water Science and Technology 59, no. 3 (February 1, 2009): 443–51. http://dx.doi.org/10.2166/wst.2009.877.

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In response to a rapidly changing and highly variable climate, engineers are being asked to perform climate-change impact assessments on existing water industry systems. There is currently no single method of best practice for engineers to interpret output from global climate models (GCMs) and calculate probabilistic distributions of future climate changes as required for risk-based impact assessments. The simplified climate change impact assessment tool (SCIAT) has been developed to address the specific needs of the water industry and provides a tool to translate climate change projections into ‘real world’ impacts or for detailed statistical analysis. Through the use of SCIAT, water system operators are provided with knowledge of potential impacts and an associated probability of occurrence, enabling them to make informed, risk-based adaptation and planning decisions. This paper demonstrates the application of SCIAT to the consideration of the impacts of climate change on reservoir water quality under future climate scenarios.

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Zevallos, Jose, and Waldo Lavado-Casimiro. "Climate Change Impact on Peruvian Biomes." Forests 13, no. 2 (February 4, 2022): 238. http://dx.doi.org/10.3390/f13020238.

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The biodiversity present in Peru will be affected by climatic and anthropogenic changes; therefore, understanding these changes will help generate biodiversity conservation policies. This study analyzes the potential distributions of biomes (B) in Peru under the effects of climate change. The evaluation was carried out using the random forest (RF) method, six bioclimatic variables, and digital topography for the classification of current B in Peru. Subsequently, the calibrated RF model was assimilated to three downscaled regional climate models to project future B distributions for the 2035–2065 horizon. We evaluated possible changes in extension and elevation as well as most susceptible B. Our projections show that future scenarios agreed that 82% of current B coverage will remain stable. Approximately 6% of the study area will change its current conditions to conditions of higher humidity; 4.5% will maintain a stable physiognomy, but with an increase in humidity; and finally, 6% will experience a decrease in humidity but maintain its appearance. Additionally, glaciers and swamps are indicated as the most vulnerable B, with probable losses greater than 50% of their current area. These results demonstrate the need to generate public policies for the adaptation and mitigation of climate effects on B at a national scale.

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Frankel, Ernst G. "Impact of Technological Change on Shipbuilding Productivity." Journal of Ship Production 1, no. 03 (August 1, 1985): 204–11. http://dx.doi.org/10.5957/jsp.1985.1.3.174.

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Technological change has resulted in major productivity gains in some shipbuilding countries, while others such as the United States have lagged behind, although a large proportion of these technological changes originated in the United States. In this paper, we evaluate the gains from the factors which play a role in assuring significant productivity gains from technological changes in shipbuilding production processes, and evaluate the effect of industry participation in research and development of process and product technology, the timing of application of new process technology, and the influence of worker incentives and training on the attainment of significant productivity gains through technological change.

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