Academic literature on the topic 'Environmental leverages'
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Journal articles on the topic "Environmental leverages"
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BILETSKYI, Ihor. "CLASSIFICATION OF LEVERAGES OF STATE REGULATION OF THE CONSTRUCTION SECTOR OF RESIDENTIAL REAL ESTATE." Ukrainian Journal of Applied Economics 6, no. 2 (June 30, 2021): 330–37. http://dx.doi.org/10.36887/2415-8453-2021-2-42.
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The construction industry in Ukraine is an important component of social production and a key basis for improving the quality of life and accelerating innovative economic development. State regulation of the construction sector of residential real estate can be carried out with the help of certain leverages. The effectiveness of public policy depends on the correct choice of a leverages or a combination of several tools. State regulation of the construction sector of residential real estate can be carried out with the help of certain leverages. The purpose of the study is scientific and theoretical substantiation of the leverages essence and leverages classification generalization of the construction sector state regulation in residential real estate, considering their impact. According to the results of the study, the peculiarities of the state regulation leverages of the construction sector in residential real estate are given and the concept of «leverages» is clarified, by which they are understood the means of direct and indirect influence of state authorities and local governments within their powers through the prism of the regulatory field in the context of the implementation of state housing policy. The leverages have the following characteristics: 1) the basis for the use of leverages is regulatory and legal support; 2) state regulation leverages are aimed at a specific object, process to achieve a certain result; 3) are used by public authorities and local governments. The prospect of further research may be to determine the impact of environmental factors on the use of leverages of state regulation of the construction sector of residential real estate. Keywords: state regulation, levers of state regulation, construction sector, housing construction, residential real estate.
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Nota, Giancarlo, and Alonso Toro Lazo. "Leveraging the GQM+ Strategy approach and Industry 4.0 technologies for environmental sustainability in manufacturing." Journal of Smart Environments and Green Computing 2, no. 3 (2022): 143–62. http://dx.doi.org/10.20517/jsegc.2022.13.
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Aim: In the last years, sustainability has been identified as an enormous problem, with many facets gaining increasing attention. In this broad scenario, the availability of models for environmental sustainability constitutes a conceptual tool to guide industries towards reducing the environmental impact deriving from production. This work aims to contribute to the research on environmental sustainability in manufacturing by proposing a model that leverages the Goal Question Metrics approach and technologies of Industry 4.0. Methods: The Goal Question Metrics approach and technologies of Industry 4.0 are leveraged by proposing a model that contributes to environmental sustainability in manufacturing. Results: A model is proposed that can be used as a conceptual tool to support improvement programs in environmental sustainability. Conclusion: The application of the Goal Question Metrics+ Strategies to a case study of an automotive industry shows how the approach, combined with the implementation of Industry 4.0 technologies, contributes to the efficient use of natural resources and also reduces the emissions in the atmosphere.
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Charlton, Julie A., Wiktor F. Młynarski, Yoon H. Bai, Ann M. Hermundstad, and Robbe L. T. Goris. "Environmental dynamics shape perceptual decision bias." PLOS Computational Biology 19, no. 6 (June 8, 2023): e1011104. http://dx.doi.org/10.1371/journal.pcbi.1011104.
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To interpret the sensory environment, the brain combines ambiguous sensory measurements with knowledge that reflects context-specific prior experience. But environmental contexts can change abruptly and unpredictably, resulting in uncertainty about the current context. Here we address two questions: how should context-specific prior knowledge optimally guide the interpretation of sensory stimuli in changing environments, and do human decision-making strategies resemble this optimum? We probe these questions with a task in which subjects report the orientation of ambiguous visual stimuli that were drawn from three dynamically switching distributions, representing different environmental contexts. We derive predictions for an ideal Bayesian observer that leverages knowledge about the statistical structure of the task to maximize decision accuracy, including knowledge about the dynamics of the environment. We show that its decisions are biased by the dynamically changing task context. The magnitude of this decision bias depends on the observer’s continually evolving belief about the current context. The model therefore not only predicts that decision bias will grow as the context is indicated more reliably, but also as the stability of the environment increases, and as the number of trials since the last context switch grows. Analysis of human choice data validates all three predictions, suggesting that the brain leverages knowledge of the statistical structure of environmental change when interpreting ambiguous sensory signals.
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Lamidi, Wasiu Adebayo, Adesola Olufunmilola Oluwatuyi, Tariro Masunda, and Adebayo Olagunju. "An Assessment of the Determinants of Environmental Costs of Listed Deposit Money Banks in Nigeria." International Journal of Business and Management Future 4, no. 1 (February 18, 2020): 12–20. http://dx.doi.org/10.46281/ijbmf.v4i1.483.
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This paper assesses the determinants of environmental costs of Nigerian banking institutions. Looking at the influence of profitability, company size and leverages on environmental cost such as donation, gift and developments, the population of the study are deposit money banks in Nigeria. Using purposive sampling technique, the study selected all fifteen (15) banks listed on the Nigerian Stock Exchange websites as at June 31, 2019 in which their annual reports are available to be extracted. The study utilized archival data i.e the annual report of listed banks from 2014 – 2017 to extract the needed information. Using STATA 14 software, the study conducts diagnostic tests such as heteroskedasticity, multicollinearity and Pearson correlation for data examination. Hence, multiple regression analysis was conducted to investigate the influence of profitability, company size and leverages on environmental costs. The analysis of the study showed that profitability, company size and leverages have positive and significant association with the environmental cost reported by these banks. Therefore, the study recommended that to adapt to the changing system of doing business, accountants ought to be equipped with skills and knowledge about environmental accounting and reporting, and in order to enhance competitiveness, banks must design and apply environmentally friendly strategies.
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Hutsaliuk, Oleksii, Nataliia Havrylova, Oksana Storozhuk, Yana Dovhenko, Snizhana Kovalenko, and Alla Navolokina. "Leverages of financial and environmental management in agricultural sector of the economy." E3S Web of Conferences 558 (2024): 01025. http://dx.doi.org/10.1051/e3sconf/202455801025.
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The article is aimed at determining theoretical views on processes of financial and environmental management of the agricultural sector. It analyzes the financial and environmental management of the agricultural sector of the economy, including the assessment of components of air, water, forest and land resources, crop and livestock production. The authors substantiate the system of ensuring the balanced development of the agricultural sector and examine measures to motivate the organization of eco-friendly agricultural production. The analysis of pollutant emissions into the atmosphere from stationary sources of pollution in Ukraine for 2017-2021 showed that the largest sources of pollution into the atmosphere in Ukraine for 2017-2021 were sulfur dioxide (25.7% in 2021), carbon monoxide into the atmosphere in Ukraine for 2017-2021 (31.4% in 2021) and methane (20.3% in 2021). The article defines the ways of state support for the agricultural sector of the economy and outlines the main principles of the agricultural sector development strategy. The revealed positive impact of the agricultural sector on the environment is ensured by two factors: financial and environmental responsibility manifested through management decision-making measures and financial and environmental motivation manifested through material, social and environmental values of the agricultural producer, consumer and society as a whole.
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Zaharkina, L., and O. Zaitsev. "FINANCIAL LEVERAGE ENVIRONMENTAL SECURITY AS A COMPONENT UKRAINE'S NATIONAL SECURITY." Vìsnik Sumsʹkogo deržavnogo unìversitetu, no. 1 (2019): 19–25. http://dx.doi.org/10.21272/1817-9215.2019.1-3.
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The article deals with the use of financial leverages to ensure environmental security as a component of Ukraine's national security. Scientific approaches to the concept and constituents of environmental security, peculiarities of its legislative regulation are analyzed. The dynamics of budget revenues using environmental taxation mechanisms have been investigated. The conclusions of its effectiveness are made. Structural analysis of the Consolidated Budget expenditures on environmental protection was also conducted. It is concluded that there is an imbalance in budgetary policy in the field of environmental security. And it is an indicator for decreasing the state's environmental security in the future.
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Selim, Mohamed S., Sherif A. El-Safty, Mohamed A. Shenashen, Shimaa A. Higazy, and Ahmed Elmarakbi. "Progress in biomimetic leverages for marine antifouling using nanocomposite coatings." Journal of Materials Chemistry B 8, no. 17 (2020): 3701–32. http://dx.doi.org/10.1039/c9tb02119a.
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Because of the environmental and economic casualties of biofouling on maritime navigation, modern studies have been devoted toward formulating advanced nanoscale composites in the controlled development of effective marine antifouling self-cleaning surfaces.
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DiSegni, Dafna M., Moshe Huly, and Sagi Akron. "Corporate social responsibility, environmental leadership and financial performance." Social Responsibility Journal 11, no. 1 (March 2, 2015): 131–48. http://dx.doi.org/10.1108/srj-02-2013-0024.
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Purpose – The purpose of this paper is to statistically assess the relationship between corporate characteristics, environmental contribution and financial performance. To this end, the authors compare the financial performance of all US corporations making up the Dow Jones Sustainability Indexes, being the most proactive companies in providing services and goods, while maintaining ethical responsibility and environmental sustainability. Design/methodology/approach – Various performance measures are compared to the mean performance of the related industry, sector and market portfolio. We employ an analysis for several time horizons of the financial measures. Findings – Analysis by the authors suggests that firms that are proactive in supporting social responsibility and environmental sustainability (SRES corporations) are characterized by significantly higher profit measures than the industry and the sector, though not higher than the entire market. They have lower short-term liquidity measures than those of the industry and related sector, and surprisingly, their long-term leverage is significantly higher. Strong SRES corporations are characterized by significantly higher managerial efficiency ratios than the respective industry and sector. Interestingly, however, the per-worker operating efficiency ratios are significantly lower than for all of the benchmarks. Practical implications – The revealed preference of corporations can be extracted from several horizon dependent financial measures. For instance, we could infer the corporate degree of SRES from their long-term capital structure, i.e. their long-term leverages and short-term liquidity measures. Originality/value – These results illustrate the strong relation between social and environmental sustainability, and long-term business plans in respect to the corporate capital structure.
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Fakhrul Yusuf, Muhammad, Hasbullah Ashari, and Mohd Rizal Razalli. "A Study on the Environmental Technological Innovation Strategy of a Malaysian Firm." International Journal of Engineering & Technology 7, no. 4.19 (November 27, 2018): 261–68. http://dx.doi.org/10.14419/ijet.v7i4.19.22064.
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Firms all over the world have pursued sustainable development to be competitive in the marketplace. The purpose of this case study is to examine the factors that enable a firm to pursue the environmental technological innovation (ET-innovation) strategies and how it effectively leverages its resources to achieve the environmental and business targets. This case study also wants to understand how well the firms ET-innovation activities can be explained by stakeholder theory, resource-based view and dynamic of innovation model. This paper uses a qualitative approach and the coding analysis was done on QSR NVivo. The data collection was done through interviews and also compared with other data sources (company brochures, reports, letters, speeches, memos, videos, newspaper articles, trade magazine articles, magazines articles, reports, website articles and technical reports) for triangulation purposes. This research showed that the ET-innovative firm in this case study has leveraged their employee technical abilities to be successful in their respective market. Another factor is the owner’s high interest in innovation and environmental protection, and involvement in the design and marketing of their eco-product. Despite stakeholders’ different targets, the case study firm manages to acquire support from their stakeholders through common objective which is to see a successful ET-innovation. Finally, it is proposed for the firm to be aware of the dynamics of eco-product lifecycle while also use current tools to manage their eco-product development especially in the earlier development stage. Â
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Leonardo Oliveira Santos de Santana, Jonatas de Oliveira Souza Cavalcante, Gustavo de Souza dos Santos, and Fernando Luiz Pellegrini Pessoa. "Seawater Refinary: A Pathway for Sustainable Metal Recovery and Green Hydrogen Production." JOURNAL OF BIOENGINEERING, TECHNOLOGIES AND HEALTH 7, no. 3 (December 14, 2024): 312–19. https://doi.org/10.34178/jbth.v7i3.418.
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With the growing environmental challenges of saltwater desalination, seawater mining is emerging as a sustainable alternative to traditional onshore mining. This paper explores the potential of recovering metals from seawater and producing green hydrogen, proposing a "seawater refinery" concept inspired by oil and biorefineries. The refinery leverages advanced separation technologies and "Zero Liquid Discharge" methods to convert brine into valuable products, including green hydrogen (H₂) while minimizing environmental impacts.
Dissertations / Theses on the topic "Environmental leverages"
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Miatke, Baxter G. "A Framework For Estimating Nutrient And Sediment Loads That Leverages The Temporal Variability Embedded In Water Monitoring Data." ScholarWorks @ UVM, 2016. http://scholarworks.uvm.edu/graddis/651.
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Rivers deliver significant macronutrients and sediments to lakes that can vary substantially throughout the year. These nutrient and sediment loadings, exacerbated by winter and spring runoff, impact aquatic ecosystem productivity and drive the formation of harmful algae blooms. The source, extent and magnitude of nutrient and sediment loading can vary drastically due to extreme weather events and hydrologic processes, such as snowmelt or high flow storm events, that dominate during a particular time period, making the temporal component (i.e., time over which the loading is estimated) critical for accurate forecasts. In this work, we developed a data-driven framework that leverages the temporal variability embedded in these complex hydrologic regimes to improve loading estimates. Identifying the "correct" time scale is an important first step for providing accurate estimates of seasonal nutrient and sediment loadings. We use water quality concentration and associated 15-minute discharge data from nine watersheds in Vermont's Lake Champlain Basin to test our proposed framework. Optimal time periods were selected using a hierarchical cluster analysis that uses the slope and intercept coefficients from individual load-discharge regressions to derive improved linear models. These optimized linear models were used to improve estimates of annual and "spring" loadings for total phosphorus, dissolved phosphorus, total nitrogen, and total suspended loads for each of the nine study watersheds. The optimized annual regression model performed ~20% better on average than traditional annual regression models in terms of Nash-Sutcliffe efficiency, and resulted in ~50% higher cumulative load estimates with the largest difference occurring in the "spring". In addition, the largest nutrient and sediment loadings occurred during the "spring" unit of time and were typically more than 40% of the total annual estimated load in a given year. The framework developed here is robust and may be used to analyze other units of time associated with hydrologic regimes of interest provided adequate water quality data exist. This, in turn, may be used to create more targeted and cost-effective management strategies for improved aquatic health in rivers and lakes.
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Ostapenco, Vladimir. "Modélisation, évaluation et orchestration des leviers hétérogènes pour la gestion des centres de données cloud à grande échelle." Electronic Thesis or Diss., Lyon, École normale supérieure, 2024. http://www.theses.fr/2024ENSL0096.
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Le secteur des Technologies de l’Information et de la Communication (TIC) est en pleine croissance en raison de l'augmentation du nombre d’utilisateurs d’Internet et de la démocratisation des services numériques, entraînant une empreinte carbone non négligeable et toujours croissante. La part des émissions de gaz à effet de serre (GES) liées aux TIC est estimée entre 1,8% et 3,9% des émissions mondiales en 2020, avec un risque de presque doubler et d’atteindre plus de 7% d'ici à 2025. Les datacenters sont au cœur de cette croissance, estimés d'être responsables d'une part importante des émissions de GES du secteur des TIC (allant de 17% à 45% en 2020) et à consommer environ 1% de l'électricité mondiale en 2018.De nombreux leviers existent et peuvent aider les fournisseurs de cloud et les gestionnaires de datacenters à réduire certains de ces impacts. Ces leviers peuvent opérer sur de multiples facettes telles que l’extinction de ressources inutilisées, le ralentissement de ressources pour s’adapter aux besoins réels des applications et services, l’optimisation ou la consolidation des services pour réduire le nombre de ressources physiques mobilisées. Ces leviers peuvent être très hétérogènes et impliquer du matériel informatique, des couches logicielles ou des contraintes plus logistiques à l’échelle des datacenters. Activer, désactiver et orchestrer ces leviers à grande échelle est un réel enjeu permettant des gains potentiels en termes de réduction de la consommation énergétique et des émissions de dioxyde de carbone.Dans cette thèse, nous abordons la modélisation, évaluation et gestion de leviers hétérogènes dans le contexte d'un datacenter cloud à grande échelle en proposant pour la première fois la combinaison de leviers hétérogènes : à la fois technologiques (allumage/extinction de ressources, migration, ralentissement) et logistiques (installation de nouvelles machines, décommissionnement, changement fonctionnels ou géographiques de ressources IT).Dans un premier temps, nous proposons une modélisation des leviers hétérogènes couvrant les impacts, les coûts et les combinaisons des leviers, les concepts de Gantt Chart environnemental contenant des leviers appliqués à l'infrastructure du fournisseur de cloud et d'un environnement logiciel de gestion des leviers qui vise à améliorer les performances énergétiques et environnementales globales de l'ensemble de l'infrastructure d'un fournisseur de cloud. Ensuite, nous abordons le suivi et la collecte de métriques, incluant des données énergétiques et environnementales. Nous discutons de la mesure de la puissance et de l’énergie et effectuons une comparaison expérimentale des wattmètres logiciels. Par la suite, nous étudions un levier technologique unique en effectuant une analyse approfondie du levier Intel RAPL à des fins de plafonnement de la puissance sur un ensemble de nœuds hétérogènes pour une variété de charges de travail gourmandes en CPU et en mémoire. Finalement, nous validons la modélisation des leviers hétérogènes proposée à grande échelle en explorant trois scénarios distincts qui montrent la pertinence de l’approche proposée en termes de gestion des ressources et de réduction des impacts potentielsThe Information and Communication Technology (ICT) sector is constantly growing due to the increasing number of Internet users and the democratization of digital services, leading to a significant and ever-increasing carbon footprint. The share of greenhouse gas (GHG) emissions related to ICT is estimated to be between 1.8% and 3.9% of global GHG emissions in 2020, with a risk of almost doubling and reaching more than 7% by 2025. Data centers are at the center of this growth, estimated to be responsible for a significant portion of the ICT industry's global GHG emissions (ranging from 17% to 45% in 2020) and to consume approximately 1% of global electricity in 2018.Numerous leverages exist and can help cloud providers and data center managers to reduce some of these impacts. These leverages can operate on multiple facets such as turning off unused resources, slowing down resources to adapt to the real needs of applications and services, optimizing or consolidating services to reduce the number of physical resources mobilized. These leverages can be very heterogeneous and involve hardware, software layers or more logistical constraints at the data center scale. Activating, deactivating and orchestrating these heterogeneous leverages on a large scale can be a challenging task, allowing for potential gains in terms of reducing energy consumption and GHG emissions.In this thesis, we address the modeling, evaluation and orchestration of heterogeneous leverages in the context of a large-scale cloud data center by proposing for the first time the combination of heterogeneous leverages: both technological (turning on/off resources, migration, slowdown) and logistical (installation of new machines, decommissioning, functional or geographical changes of IT resources).First, we propose a novel heterogeneous leverage modeling approach covering leverages impacts, costs and combinations, the concepts of an environmental Gantt Chart containing leverages applied to the cloud provider's infrastructure and of a leverage management framework that aims to improve the overall energy and environmental performance of a cloud provider's entire infrastructure. Then, we focus on metric monitoring and collection, including energy and environmental data. We discuss power and energy measurement and conduct an experimental comparison of software-based power meters. Next, we study of a single technological leverage by conducting a thorough analysis of Intel RAPL leverage for power capping purposes on a set of heterogeneous nodes for a variety of CPU- and memory-intensive workloads. Finally, we validate the proposed heterogeneous leverage modeling approach on a large scale by exploring three distinct scenarios that show the pertinence of the proposed approach in terms of resource management and potential impacts reduction
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Fior, Daniel. "Toward Environmental and Social Sustainability: in search of leverage points." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-254617.
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It may be argued that ours is far away from a sustainable society. For all the technological wonders that we have been able to produce, some basic problems such as lack of universal access to the means to satisfy one's basic needs, human rights violations, systematic degradation of the environment, among others are still present. Not for a lack of effort, but scientific progress, political effort and economic growth appear to have real limitations in their capability to help us solve some of these problems that have endured through time. Donella Meadows, an expert in systems analysis, has developed a comprehensive list of points to intervene in a system in order to effect change. Using that framework as a basis, the present study aims to try to identify potential reasons for why most of the efforts conducted so far to solve some of the previously mentioned fundamental problems appear not to be so effective. Many of the fundamental assumptions of the mainstream economic school that heavily influence policy making and individual behavior to a large extent, have been identified as potentially important leverage points being pushed in the wrong direction! Economic powers and vested interests allow for the erosion of the self-controlling elements of the global political-economic system such as democratic institutions, what Meadows classifies as weakening of negative feedback loops. The mainstream economic models promoting "success to the successful" loops such as accumulation of resources in the hands of a few, all the while concentrating power can be pointed out as an example of a positive loop getting dangerously out of control. Uncontrolled positive loops inevitably lead to system collapse. Concentration of power is specially dangerous as it can bestow upon an elite the power to set the rules of the system, one of the most effective leverage points according to Meadows. Additionally, by curtailing biological, ideological and cultural diversity we are compromising one of the fundamental conditions for our systems to endure threatening changes, the ability to self-organize, or evolve. The most powerful leverage point is the paradigm out of which the whole system is constructed. The current mainstream economic thinking is fundamentally based on a single paradigmatic assumption of scarcity by mean of the supposed impossibility of satisfying human material wants, as 'new wants are always emerging'. In this mindset, it seems to make sense for the economic system to promote limitless growth and accumulation under the assumption of unlimited material wants. In the possibility to transcend such a paradigm lies an important potential for leverage in the efforts to solve the fundamental problems that still hold our society from attaining sustainability.
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Barrow, Charlotte, Stephanie Peterka, and Tuna Ozcuhadar. "Open Source as Leverage towards Sustainable Housing." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3576.
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Shelter poses global sustainability challenges, as the population increase accelerates and resources dwindle. It is crucial for initiatives addressing the growing housing demand to incorporate a sustainability perspective. Open source, a form of Internet information-sharing, is being utilised by various housing initiatives worldwide. However, a sustainability perspective is not always included in a robust and holistic way, despite the negative impacts for human needs and ecosystems resulting from many aspects of current housing practices. The Framework for Strategic Sustainable Development includes basic conditions for a sustainable society and a planning and decision-making methodology to move systematically towards sustainability. It provides a robust method for organizing, evaluating and using tools to aid in handling sustainability challenges effectively. This thesis aims to contribute to the development of affordable, sustainable design solutions, by modelling the incorporation of the FSSD into open source housing initiatives. A case study of a housing project under development in Ghana is used. Despite the complexity of the system under study, the research concludes that bringing a strategic sustainable development perspective to open source approaches can act as leverage for housing to move towards sustainability. Within this context, guidance is provided for approaching open source housing to contribute to SSD.charcolatebar@live.ca
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Chan, Shun-fong, and 陳信方. "A study on green housing management: how can housing managers best leverage green initiatives for sustainabledevelopment." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48339829.
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This research explores the current and potential green initiatives to advance the sustainability agenda in property management. It outlines the environmental protection strategies adopted in housing management in achieving sustainable development goals. This research also studies how eco-friendly objectives could tie in with other environmental and social goals in sustainable development. The research involves a review of available evidence in an attempt to identify and recognize good practice/instances where green measures are actively promoted in private housing estates.
The researcher tries to advance and examine the key issues and challenges that are at stake respecting sustainable development in the context of property-related decision making, and at the same time, suggests how environmental considerations can be integrated into all aspects of a housing project from planning to implementation. The study draws on evidences emerged from relevant literature reviews, interviews and a case study in exploring the role of housing management in promoting sustainability in the scope of realizing green measures. In addition, the researcher would mention the local policy background and discuss the efforts by the government in related to sustainable development. In the final section, the limitations followed by recommendations towards the subject matter would be revealed.published_or_final_version
Housing Management
Master
Master of Housing Management
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Mlambo, Shepherd. "Using social learning environments to leverage traditional supervision of research students: a community of practice perspective." Master's thesis, University of Cape Town, 2012. http://hdl.handle.net/11427/12358.
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Includes bibliographical references.South African higher education is plagued by student articulation gap, which is often attributed to insufficient knowledge production processes and surface approaches to learning. Unfortunately, supervisor-student model of supervision, one of the direct, personal interventions to address this challenge, is plagued by multiple flaws. The traditional supervisor-student model of knowledge generation may not be adequate in externalizing research processes to students. Yet, a social learning model potentially extends the traditional model by providing a social environment where students collectively generate knowledge through peer-based interactions. Mindful of supervision dilemmas namely, this study explores technology-enhanced social learning environments as complements to traditional supervision models.
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Anantarak, Sarin. "Economic Motivation of the Ex-Dividend Day Anomaly: Evidence from an Alternative Tax Environment." Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc103283/.
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Several studies have observed that stocks tend to drop by an amount that is less than the dividend on the ex-dividend day, the so-called ex-dividend day anomaly. However, there still remains a lack of consensus for a single explanation of this anomaly. Different from other studies, this dissertation attempts to answer the primary research question: How can investors make trading profits from the ex-dividend day anomaly and how much can they earn? With this goal, I examine the economic motivations of equity investors through four main hypotheses identified in the anomaly’s literature: the tax differential hypothesis, the short-term trading hypothesis, the tick size hypothesis, and the leverage hypothesis. While the U.S. ex-dividend anomaly is well studied, I examine a long data window (1975 to 2010) of Thailand data. The unique structure of the Thai stock market allows me to assess all four main hypotheses proposed in the literature simultaneously. Although I extract the sample data from two data sources, I demonstrate that the combined data are consistently sampled. I further construct three trading strategies: “daily return,” “lag one daily return,” and “weekly return” to alleviate the potential effect of irregular data observation. I find that the ex-dividend day anomaly exists in Thailand, is governed by the tax differential and is driven by short-term trading activities. That is, investors trade heavily around the ex-dividend day to reap the benefits of the tax differential. I find mixed results for the predictions of the tick size hypothesis and results that are inconsistent with the predictions of the leverage hypothesis. I conclude that, on the Stock Exchange of Thailand, juristic and foreign investors can profitably buy stocks cum-dividend and sell them ex-dividend while local investors should engage in short sale transactions. On average, investors who employ the daily return strategy have earned significant abnormal return up to 0.15% (45.66% annualized rate) and up to 0.17% (50.99% annualized rate) for the lag one daily return strategy. Investors can also make a trading profit by conducting the weekly return strategy and earn up to 0.59% (35.67% annualized rate), on average.
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Chen, Xiangtuo. "Statistical Learning Methodology to Leverage the Diversity of Environmental Scenarios in Crop Data : Application to the prediction of crop production at large-scale." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLC055.
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La prévision du rendement des cultures est toujours une question primordiale. De nombreuses recherches ont été menées avec cet objectif en utilisant diverses méthodologies. Généralement, les méthodes peuvent être classées en approches basées sur les modèles et en approches basées sur les données.Les approches basées sur les modèles reposent sur la modélisation mécaniste des cultures. Ils décrivent la croissance des cultures en interaction avec leur environnement comme systèmes dynamiques. Comme ces modèles sont basés sur la description mécanique des processus biophysiques, ils impliquent potentiellement un grand nombre de variables d'état et de paramètres, dont l'estimation n'est pas simple. En particulier, les problèmes d'estimation des paramètres résultant sont généralement non linéaires et conduisent à des problèmes d'optimisation non-convexes dans un espace multidimensionnel. De plus, l’acquisition de données est très difficile et nécessite un travail expérimental lourd afin d’obtenir les données appropriées pour l’identification du modèle.D'un autre côté, les approches basées sur les données pour la prévision du rendement nécessitent des données provenant d'un grand nombre de scénarios environnementaux, mais les données sont plus simples à obtenir: (données climatiques et rendement final). Cependant, les perspectives de ce type de modèles se limitent principalement à la prévision de rendement.La première contribution originale de cette thèse consiste à proposer une méthodologie statistique pour calibrer les modèles mécanistes potentiellement complexes, lorsque des ensembles de données avec différents scénarios environnementaux et rendements sont disponibles à grande échelle. Nous l'appellerons Méthodologie d'estimation de paramètres multi-scénarios (MuScPE). Les principales étapes sont les suivantes:Premièrement, nous tirons parti des connaissances préalables sur les paramètres pour leur attribuer des distributions a priori pertinentes et effectuons une analyse de sensibilité globale sur les paramètres du modèle afin de sélectionner les paramètres les plus importants à estimer en priorité.Ensuite, nous mettons en œuvre une méthode d’optimisation efficace non convexe, l’optimisation parallèle des essaims de particules, pour rechercher l’estimateur MAP (maximum a posteriori) des paramètres;Enfin, nous choisissons la meilleure configuration en ce qui concerne le nombre de paramètres estimés par les critères de sélection de modèles. Il y a en effet un compromis à trouver entre d’un côté l'ajustement aux données, et d'un autre côté la variance du modèle et la complexité du problème d'optimisation à résoudre.Cette méthodologie est d'abord testée avec le modèle CORNFLO, un modèle de culture fonctionnel pour le maïs.La seconde contribution de la thèse est la comparaison de cette méthode basée sur un modèle mécaniste avec des méthodes classiques d'apprentissage statistique basées sur les données. Nous considérons deux classes de méthodes de régression: d'une part, les méthodes statistiques dérivées de la régression linéaire généralisée qui permettent de simplifier le modèle par réduction dimensionnelle (régressions Ridge et Lasso, Régression par composantes principales ou régression partielle des moindres carrés) et d'autre part les méthode de régression de machine learning basée sur des modèles non-linéaires ou des techniques de ré-échantillonnage comme la forêt aléatoire, le réseau de neurones et la régression SVM.Enfin, une régression pondérée est appliquée pour prédire la production à grande échelle. La production de blé tendre, une culture de grande importance économique en France, est prise en exemple. Les approches basées sur les modèles et sur les données ont également été comparées pour déterminer leur performance dans la réalisation de cet objectif, ce qui est finalement la troisième contribution de cette thèseCrop yield prediction is a paramount issue in agriculture. Considerable research has been performed with this objective relying on various methodologies. Generally, they can be classified into model-driven approaches and data-driven approaches.The model-driven approaches are based on crop mechanistic modelling. They describe crop growth in interaction with their environment as dynamical systems. Since these models are based on the mechanical description of biophysical processes, they potentially imply a large number of state variables and parameters, whose estimation is not straightforward. In particular, the resulting parameter estimation problems are typically non-linear, leading to non-convex optimisation problems in multi-dimensional space. Moreover, data acquisition is very challenging and necessitates heavy specific experimental work in order to obtain the appropriate data for model identification.On the other hand, the data-driven approaches for yield prediction necessitate data from a large number of environmental scenarios, but with data quite easy to obtain: climatic data and final yield. However, the perspectives of this type of models are mostly limited to prediction purposes.An original contribution of this thesis consists in proposing a statistical methodology for the parameterisation of potentially complex mechanistic models, when datasets with different environmental scenarios and large-scale production records are available, named Multi-scenario Parameter Estimation Methodology (MuScPE). The main steps are the following:First, we take advantage of prior knowledge on the parameters to assign them relevant prior distributions and perform a global sensitivity analysis of the model parameters to screen the most important ones that will be estimated in priority;Then, we implement an efficient non-convex optimisation method, the parallel particle swarm optimisation, to search for the MAP (maximum a posterior) estimator of the parameters;Finally, we choose the best configuration regarding the number of estimated parameters by model selection criteria. Because when more parameters are estimated, theoretically, the calibrated model could explain better the variance of the output. Meanwhile, it increases also difficulty for optimization, which leads to uncertainty in calibration.This methodology is first tested with the CORNFLO model, a functional crop model for the corn.A second contribution of the thesis is the comparison of this model-driven method with classical data-driven methods. For this purpose, according to their different methodology in fitting the model complexity, we consider two classes of regression methods: first, Statistical methods derived from generalized linear regression that are good at simplifying the model by dimensional reduction, such as Ridge and Lasso Regression, Principal Components Regression or Partial Least Squares Regression; second, Machine Learning Regression based on re-sampling techniques like Random Forest, k-Nearest Neighbour, Artificial Neural Network and Support Vector Machine (SVM) regression.At last, a weighted regression is applied to large-scale yield prediction. Soft wheat production in France is taken as an example. Model-driven and data-driven approaches have also been compared for their performances in achieving this goal, which could be recognised as the third contribution of this thesis
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Giusti, Matteo. "Nature Routines of Children as Leverage Point for Sustainable Social-Ecological Urbanism : Connecting childhood and biosphere to design sustainable civilizations in the human habitat." Licentiate thesis, Stockholms universitet, Stockholm Resilience Centre, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-134601.
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Strong sustainability requires enhanced knowledge and understanding of complex social-ecological interactions, but it also implies a ‘novel’ conceptualization of the relationship between humans and nature, one in which individuals perceive themselves as embedded members of the Biosphere. The aim of this Licentiate thesis is to investigate the validity of a strategy that is centered on designing the urban green infrastructure to nurture such human-nature relationship in children’s attitudes. The research is framed by spatial cognition, conservation psychology, and social-ecological sustainability and it focuses on the validity of this strategy. Hence, the Licentiate analyzes how reoccurring experiences of nature that are situated in the everyday habitat (i.e. nature routines) affect personal human-nature attitudes and how these can be implemented as leverage points to change social-ecological systems using sustainable urbanism. Paper 1 tests the assumed link between the nature routines in Stockholm and preschool children’s development of cognitive and emotional affinity to nature. The results show that nature-rich routines over a period of four years are significantly correlated with the strength of preschooler’s affinity with nature. Paper 2 uses a mixed methods approach to evaluate changes in Connection To Nature (CTN) in 10 years olds who partake in a project of nature conservation. The results of Paper 2 show that there is an evaluative gap between theory and practice in connecting children with nature that impedes the evaluation of how children’s CTN changes over short periods of time and that impedes the creation of an evaluative framework for nature experiences. Paper 3 considers these empirical results in theorizing an approach to sustainable urban design based on social-ecological sustainability that includes CTN. In order to overcome existing limitations Paper 3 presents the concept of cognitive affordances as a theoretical tool to embed cognitive and emotional attitudes towards nature into the design of urban spaces. All combined these papers provide valid evidence that nature routines in cities, especially for children, can be a significant leverage point to enable future sustainable civilizations.
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Daily, Ellen Wilmoth Matthews. "Metro Environmental: The impact of training HVAC technicians using the SightPros-VirTechs system for remote, wireless, Internet video assistance." Thesis, University of North Texas, 2008. https://digital.library.unt.edu/ark:/67531/metadc12112/.
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This qualitative study explored the overall impact of training HVAC technicians using the SightPros-VirTechs system for remote, wireless, internet video assistance at a small HVAC company, Metro Environmental. John Thomason, the president/co-owner developed a website and a new SightPros communication tool that allows wireless, one-on-one, just-in-time, high-quality, video-monitored instructions between an expert at one site and a technician at another site. Metro Environmental successfully used the SightPros-VirTechs system to train a new apprentice remotely. The apprentice and expert changed their normal and routine physical activities because the expert worked remotely and the apprentice worked on-site. Within just a few months, the apprentice proved competent enough to go to customer accounts without more experienced technicians nearby. The technicians express excitement about the SightPros communication tool as a way to contact remote experts whenever needed. The customer and business contacts also give good reviews and suggest other benefits. The expert permanently captures the communications so the company can use the saved video for many applications, especially training. The dissertation provides a list of recommendations to trainers/educators for similar applications.
Books on the topic "Environmental leverages"
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Lawrence, Lederman, and Nussbaum Martin 1947-, eds. Acquisitions in a deleveraging environment. New York, N.Y. (810 7th Ave., New York 10019): Practising Law Institute, 1992.
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John, Ganzi, and World Resources Institute, eds. Leverage for the environment: A guide to the private financial services industry. Washington, D.C: World Resources Institute, 1998.
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Council, Corporate Leadership. Engaging the workforce: Focusing on the leverage points to drive employee engagement. Washington, D.C: Corporate Executive Board, 2004.
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New, England Business and Securities Law Conference (6th 1988 Boston Mass ). 6th Annual New England Business and Securities Law Conference, 1988: After the crash--dealing with the new environment. Boston, Mass. (20 West St., Boston 02111): Massachusetts Continuing Legal Education, 1988.
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National Conference on the Uses of Government Procurement Leverage to Benefit Taxpayers, Consumers, and the Environment (1988 Washington, D.C.). The stimulation effect: Proceedings of a National Conference on the Uses of Government Procurement Leverage to Benefit Taxpayers, Consumers, and the Environment, May 23-24, 1988, Embassy Row Hotel, Washington, DC. Washington, DC: The Center, 1990.
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Knaack, Ulrich, and Jens Schneider. POWERSKIN CONFERENCE PROCEEDINGS. Edited by Thomas Auer. TU Delft Open, 2021. http://dx.doi.org/10.47982/bookrxiv.27.
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The building skin has evolved enormously over the past decades. The energy performance and environmental quality of both the interior and exterior of buildings are primarily determined by the building envelope. The façade has experienced a change in its role as an adaptive climate control system that leverages the synergies between form, material, mechanical and energy systems towards an architectural integration of energy generation. The PowerSKIN Conference aims to address the role of building skins to accomplish a carbonneutral building stock. The focus of the PowerSKIN issue 2021 deals with the question of whether simplicity and robustness stay in contradiction to good performance of buildings skins or whether they even complement each other: simplicity vs performance? As an international scientific event - usually held at the BAU trade fair in Munich - the PowerSKIN Conference builds a bridge between science and practice, between research and construction, and between the latest developments and innovations for the façade of the future. Topics such as building operation, embodied energy, energy generation and storage in the context of the three conference sessions envelope, energy and environment are considered: – Envelope: The building envelope as an interface for the interaction between indoor and outdoor environment. This topic is focused on function, technical development and material properties. – Energy: New concepts, accomplished projects, and visions for the interaction between building structure, envelope and energy technologies. – Environment: Façades or elements of façades, which aim to provide highly comfortable surroundings where environmental control strategies as well as energy generation and/or storage are an integrated part of an active skin. The Technical University of Munich, TU Darmstadt, and TU Delft are signing responsible for the organisation of the conference. It is the third event of a biennial series: April 9th 2021, architects, engineers, and scientists present their latest developments and research projects for public discussion and reflection. For the first time, the conference will be a virtual event. On the one hand, this is a pity, as conferences are also about meeting people and social interaction; on the other hand, it offers the possibility that we can reach more people who connect from all over the world.
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Kay, Tamara, and R. L. Evans. Using Institutional Leverage to Influence the Side Agreements. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190847432.003.0006.
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This chapter explores how activists used institutional channels to influence the side agreements. It reveals, through documented interactions, the cat-and-mouse game between activists and the state as they responded to each other’s maneuvering and changed their strategies in relationship to each other. It shows how activists and their legislative allies applied pressure on negotiators, who ultimately succumbed to pressure by strengthening environmental and labor protections at multiple points during negotiations. The chapter also analyzes the unexpected ability of environmentalists to push for and obtain stronger protections in the environmental side agreement than labor activists achieved in the labor side agreement. This is particularly surprising because unions were stronger and had substantially more political and financial resources to draw upon than did environmentalists.
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Progressive environmental management: Leveraging regulatory and voluntary action. [Washington, D.C.?]: U.S. Environmental Protection Agency, Office of the Administrator, 1993.
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Leverage of the Weak: Labor and Environmental Movements in Taiwan and South Korea. University of Minnesota Press, 2015.
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Leverage of the Weak: Labor and Environmental Movements in Taiwan and South Korea. Univ Of Minnesota Press, 2015.
Find full textBook chapters on the topic "Environmental leverages"
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Logan, Kate. "Extending Enforcement: How the Institute of Public and Environmental Affairs Leverages Public Information to Strengthen Environmental Governance." In Governing China in the 21st Century, 151–90. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6594-0_6.
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Hu, Ming, Chaoli Wang, Siavash Ghorbany, Siyuan Yao, and Ali Nouri. "Machine Learning Integration in LCA: Addressing Data Deficiencies in Embodied Carbon Assessment." In Lecture Notes in Civil Engineering, 927–40. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-69626-8_78.
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AbstractLife Cycle Assessment (LCA) is an essential tool for quantifying the environmental burdens of products and processes, critical for advancing sustainability goals. Central to the effectiveness of LCA is the Life Cycle Inventory (LCI) phase, which requires reliable data to reflect the environmental footprint of products accurately. However, LCA practitioners often encounter data gaps that can compromise the assessment’s accuracy. To address this, we explore the integration of Machine Learning (ML) to enhance LCA data quality, particularly in the LCI stages B to D, which focus on product use, end-of-life, and beyond-life phases. This chapter introduces a novel framework that leverages ML to overcome LCI data challenges, emphasizing reducing the embodied carbon of construction products. We extract existing data from the Environment Product Declaration online library and apply natural language processing to interpret this unstructured data. Subsequently, we employ a random forest algorithm, a robust ensemble tree-based ML method, to refine the data analysis. We present a pilot study that validates the feasibility of our ML-enhanced framework. The incorporation of ML addresses the voluminous data in LCA. It augments the analytical capacity, thereby improving the precision and reliability of both LCI and Life Cycle Impact Assessment (LCIA) datasets. Consequently, our approach yields higher quality LCA outcomes, offering a more reliable basis for environmental impact evaluation. In summary, the successful application of ML in this research bridges the critical data gap in LCI for construction products, paving the way for a more sustainable industry through improved accuracy in environmental impact assessments and more informed decision-making in green product innovation.
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Lanzendorf, Tami, and Lusine Margaryan. "Environmental leverage through sport event portfolios." In The Routledge Handbook of Events and Sustainability, 174–86. London: Routledge, 2024. http://dx.doi.org/10.4324/9781003269311-19.
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Subramanian R, Kannan. "As-Is Environment – Noninterest Cost Management." In Improving Operating Leverage Using Hyperautomation, 67–147. Berkeley, CA: Apress, 2024. https://doi.org/10.1007/979-8-8688-0896-8_2.
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State, Talida, Barbara S. Mitchell, and Joseph Wehby. "Consistent, Organized, Respectful Learning Environment." In High Leverage Practices for Inclusive Classrooms, 105–18. 2nd ed. New York: Routledge, 2022. http://dx.doi.org/10.4324/9781003148609-12.
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Cascone, Stefano. "Integrating Green Roofs into Building Information Modeling (BIM): A Computational Approach for Sustainable Building Design." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality, 988–97. Florence: Firenze University Press, 2023. http://dx.doi.org/10.36253/979-12-215-0289-3.99.
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The construction industry is currently witnessing a transformative period characterized by the convergence of the green and digital transitions. The green transition seeks to address environmental challenges such as climate change and resource depletion, while the digital transition leverages advanced technologies to enhance construction processes. This paper specifically explores the integration of green roofs, as component of sustainable buildings, into the Building Information Modeling (BIM) framework, a key enabler of the digital transition. Green roofs, known for their environmental benefits, consist of layers that contribute to energy efficiency, stormwater management, and biodiversity enhancement. To optimize their design and performance, this research employs Dynamo Visual Programming Language (VPL) within Autodesk Revit to create parametric models of green roofs. These models facilitate the evaluation of thermal and structural characteristics under varying water content conditions (dry and saturated). Results reveal that the choice of substrate and drainage materials significantly impacts thermal resistance, particularly in dry conditions. However, in saturated conditions, the influence on thermal performance converges, emphasizing the importance of structural considerations in both scenarios. The research also highlights various limitations and outlines avenues for future studies, including expanding the range of materials, exploring additional performance metrics, and incorporating AI and machine learning techniques. By addressing these aspects, this research contributes to a comprehensive understanding of the integration of green roofs and BIM. It provides designers and researchers with a practical tool for optimizing green roof designs, aligning with contemporary sustainable construction practices, and promoting the holistic development of green buildings
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Cascone, Stefano. "Integrating Green Roofs into Building Information Modeling (BIM): A Computational Approach for Sustainable Building Design." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality, 988–97. Florence: Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.99.
Full textAbstract:
The construction industry is currently witnessing a transformative period characterized by the convergence of the green and digital transitions. The green transition seeks to address environmental challenges such as climate change and resource depletion, while the digital transition leverages advanced technologies to enhance construction processes. This paper specifically explores the integration of green roofs, as component of sustainable buildings, into the Building Information Modeling (BIM) framework, a key enabler of the digital transition. Green roofs, known for their environmental benefits, consist of layers that contribute to energy efficiency, stormwater management, and biodiversity enhancement. To optimize their design and performance, this research employs Dynamo Visual Programming Language (VPL) within Autodesk Revit to create parametric models of green roofs. These models facilitate the evaluation of thermal and structural characteristics under varying water content conditions (dry and saturated). Results reveal that the choice of substrate and drainage materials significantly impacts thermal resistance, particularly in dry conditions. However, in saturated conditions, the influence on thermal performance converges, emphasizing the importance of structural considerations in both scenarios. The research also highlights various limitations and outlines avenues for future studies, including expanding the range of materials, exploring additional performance metrics, and incorporating AI and machine learning techniques. By addressing these aspects, this research contributes to a comprehensive understanding of the integration of green roofs and BIM. It provides designers and researchers with a practical tool for optimizing green roof designs, aligning with contemporary sustainable construction practices, and promoting the holistic development of green buildings
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Guo, Kevin, and Tim Leung. "Understanding the Tracking Errors of Commodity Leveraged ETFs." In Commodities, Energy and Environmental Finance, 39–63. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2733-3_2.
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Walker, Virginia, and Sheldon Loman. "Establish a Consistent, Organized, and Respectful Learning Environment." In High Leverage Practices and Students with Extensive Support Needs, 79–94. New York: Routledge, 2022. http://dx.doi.org/10.4324/9781003175735-8.
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Heyman, Sofie, Toon Jansen, Wanda Sass, Nele Michels, Jelle Boeve-de Pauw, Peter Van Petegem, and Hans Keune. "How Education Can Be Leveraged to Foster Adolescents’ Nature Connection." In Outdoor Environmental Education in the Contemporary World, 83–94. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-29257-6_5.
Full textConference papers on the topic "Environmental leverages"
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Luo, Kang, Yuanshao Zhu, Wei Chen, Kun Wang, Zhengyang Zhou, Sijie Ruan, and Yuxuan Liang. "Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. California: International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/248.
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Trajectory modeling refers to characterizing human movement behavior, serving as a pivotal step in understanding mobility patterns. Nevertheless, existing studies typically ignore the confounding effects of geospatial context, leading to the acquisition of spurious correlations and limited generalization capabilities. To bridge this gap, we initially formulate a Structural Causal Model (SCM) to decipher the trajectory representation learning process from a causal perspective. Building upon the SCM, we further present a Trajectory modeling framework (TrajCL) based on Causal Learning, which leverages the backdoor adjustment theory as an intervention tool to eliminate the spurious correlations between geospatial context and trajectories. Extensive experiments on two real-world datasets verify that TrajCL markedly enhances performance in trajectory classification tasks while showcasing superior generalization and interpretability.
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Zhu, Fengda, Vincent CS Lee, Xiaojun Chang, and Xiaodan Liang. "Vision Language Navigation with Knowledge-driven Environmental Dreamer." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/204.
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Vision-language navigation (VLN) requires an agent to perceive visual observation in a house scene and navigate step-by-step following natural language instruction. Due to the high cost of data annotation and data collection, current VLN datasets provide limited instruction-trajectory data samples. Learning vision-language alignment for VLN from limited data is challenging since visual observation and language instruction are both complex and diverse. Previous works only generate augmented data based on original scenes while failing to generate data samples from unseen scenes, which limits the generalization ability of the navigation agent. In this paper, we introduce the Knowledge-driven Environmental Dreamer (KED), a method that leverages the knowledge of the embodied environment and generates unseen scenes for a navigation agent to learn. Generating an unseen environment with texture consistency and structure consistency is challenging. To address this problem, we incorporate three knowledge-driven regularization objectives into the KED and adopt a reweighting mechanism for self-adaptive optimization. Our KED method is able to generate unseen embodied environments without extra annotations. We use KED to successfully generate 270 houses and 500K instruction-trajectory pairs. The navigation agent with the KED method outperforms the state-of-the-art methods on various VLN benchmarks, such as R2R, R4R, and RxR. Both qualitative and quantitative experiments prove that our proposed KED method is able to high-quality augmentation data with texture consistency and structure consistency.
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Beveridge, Ivana, and John Yamokoski. "Case Study: Space-Industry Robotics Technology Leveraged to Realize Significant Improvements in Offshore Safety and Sustainability." In Offshore Technology Conference. OTC, 2024. http://dx.doi.org/10.4043/35085-ms.
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Abstract Historically, subsea vehicles were controlled by communications through a tether, which presents several challenges including a limited range of motion, deployment and retrieval, cost and logistics, and environmental impact. These challenges inspired the development of a new generation of robotic solutions seeking to transform the industry into an economically efficient and environmentally sustainable model. Autonomous systems are increasingly providing economic and environmental value, such as intelligent robots with subsea applications in energy, defense, transportation, and aquaculture. Combined with AI capabilities, these robots can make subsea work more sustainable. The paper presents findings from a robotics company established in 2014 in Texas by NASA-bred entrepreneurs. Today, the company exports its robotic services and vehicles internationally. Findings offer a first-hand insight into the development of the interconnected, purpose-built ecosystem of surface and subsea robots. The technology leverages autonomous behaviors, acoustic communications, over-the-horizon networking, force/torque controllable electric manipulation, AI and machine learning, and multimodal 3D workspace sensors. It is inspired by NASA's command and control approach for robots in space. When this framework is applied to subsea systems, it removes the need for the tether through the autonomous capabilities onboard the robotic assets. Removing the tether has a cascading effect on support infrastructure and ultimately results in a reduction of on-site human support, thereby making operations safer. This new subsea robotics approach helps deliver an economically viable and environmentally sustainable model that significantly reduces operational footprints, operating costs, and GHG emissions, while improving offshore health, safety, and environmental exposure. New approaches to subsea technology could help develop complex autonomous ecosystems and serve as proof of concept for developing commercially viable technologies.
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Lee, Jeehwan, and Sanghyun Lee. "IEQ Visual Data to Building Occupants for Personal Control of Indoor Environmental Quality." In AHFE 2023 Hawaii Edition. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004248.
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Indoor Environmental Quality (IEQ) profoundly influences occupants' health, productivity, and comfort in built environments. Effective interaction with occupants to comprehend and control IEQ conditions is crucial in human-centered design for IEQ optimization. This paper presents a preliminary study that leverages three-dimensional (3D) virtual space to deliver IEQ data to occupants, enabling them to understand indoor conditions better and exercise personal control of IEQ. A survey was conducted with participants in a virtually simulated educational environment. For a comparative study, participants experienced 3D virtual space with and without IEQ data information on IEQ variables such as temperature, humidity, air quality, lighting, and noise levels. The proposed framework addresses the effectiveness of IEQ visual data on occupants' responses to ways of indoor environmental controls. Regarding the effectiveness of IEQ visual data for occupants' engagement in IEQ controls, the percentage of positive tendency, that responses strongly agree and agree, ranges from 86 to 88% for thermal comfort, from 84 to 92% for visual comfort, from 71 to 81% for acoustic comfort, and 85% for indoor air quality. Findings also show that specific directions on pictograms would help participants take active engagement to improve comfort levels rather than visual data solely. In conclusion, this paper indicates a preliminary approach utilizing 3D virtual space to determine how participants respond to IEQ visual data for personal control of IEQ. By merging immersive visualization with interactive control, our framework bridges human factors and indoor design for occupants' comfort and productivity. The demand for human-centered design continues to expand to IEQ management with emerging technologies such as electroencephalography, resulting in the design of optimized, healthier, productive, and energy-efficient indoor spaces.
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A, Suguna, Pradeep Kumar T K, and Nithiya S. "H-IoT for Asthma Anticipated Effects Prediction Using Machine Learning Algorithm." In International Conference on Recent Trends in Computing & Communication Technologies (ICRCCT’2K24). International Journal of Advanced Trends in Engineering and Management, 2024. http://dx.doi.org/10.59544/zssn7179/icrcct24p16.
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Asthma affects millions worldwide, presenting significant challenges in symptom prediction and management. The rapid advancement of Healthcare Internet of Things (H-IoT) technology has enabled continuous monitoring of physiological and environmental factors relevant to asthma. This paper presents an approach that leverages H-IoT data and machine learning (ML) algorithms to predict asthma related effects, allowing for timely intervention and management. Using real time physiological data, environmental metrics, and historical health records, we train predictive ML models to anticipate asthma episodes and exacerbations. Our results show high accuracy in episode prediction, demonstrating the potential of combining H-IoT and ML for improved asthma management.
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Paredes, Ana, Eva Balsa-Canto, and Julio R. Banga. "Mathematical Modeling of Microbial Community Dynamics." In VII Congreso XoveTIC: impulsando el talento científico, 245–52. Servizo de Publicacións. Universidade da Coruña, 2024. https://doi.org/10.17979/spudc.9788497498913.35.
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Microbial communities act as complex ecological networks, crucial in diverse natural and engineered settings. These communities consist of bacteria, fungi, viruses, and other microorganisms that interact with one another and their environment. They perform essential functions such as nutrient cycling, degradation of pollutants, and maintaining the health of plants, animals, and humans. Systems biology leverages mathematical models to study these communities in a systematic and quantitative manner. Our work concentrates on calibrating nonlinear models in Ordinary Differential Equations (ODEs), evaluating both structural and practical identifiability properties to verify if model parameters can be uniquely estimated from the available data. This is crucial to ensure model reliability, enhancing our understanding of how microbial ecosystems work, and providing us with tools for optimal design and management of microbial ecosystems for applications in health and environmental science.
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Xiao, Yao, Shuang Huang, Hongjian Wang, Dan Yu, Ling Chu, Yutong Huang, and Jinmu Tian. "A Deep Learning Method for UUV to Detect Undersea Landform Features." In ASME 2024 43rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/omae2024-129780.
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Abstract Marine topography refers to the configuration and composition of underwater landscapes, which holds significant importance for marine resource exploration and environmental research. However, conventional methods for detecting terrain and geomorphology in marine environments often struggle to accurately identify these features due to the intricate nature of the marine setting and data interference. To tackle this challenge, a proposal is made to leverage deep learning techniques for exploring ocean terrain and geomorphology. As the utilization of Side-scan Sonar (SSS) in underwater settings becomes increasingly prevalent, the study of sonar image processing is becoming more comprehensive. This study introduces a feature extraction approach for Unmanned Underwater Vehicle (UUV) SSS images based on a multi-layer feature fusion structure of a lightweight Fully Convolutional Network (FCN). The method aims to address issues such as low precision in feature extraction, inadequate boundary coherence, and suboptimal edge detail in existing methods for extracting features from SSS images. Recognizing the abundance of convolution parameters in the fully connected layer leading to network model complexity and information loss, a lightweight FCN is devised to reduce computational load, simplify the network model, and prevent information loss due to large dimension spans. Experimental findings demonstrate that this method not only ensures adequate network training but also leverages information correlation across different convolution layers to enhance the network’s ability to capture and fuse effective feature information, thereby improving the integrity of feature extraction edges in SSS images.
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BOUAICHA, Alaoua. "Numerical investigation of the seismic bearing capacity of offshore skirted foundations installed in sand using finite element limit analysis." In Civil and Environmental Engineering for Resilient, Smart and Sustainable Solutions, 161–70. Materials Research Forum LLC, 2025. https://doi.org/10.21741/9781644903414-19.
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Abstract. Within the scope of offshore infrastructure, skirted foundations have emerged as an innovative technical solution, offering significant advantages in optimizing the bearing capacity of structures. These foundations not only enhance resistance to vertical loading but also provide more effective control over settlements, ensuring greater stability and durability of marine structures. This study leverages Finite Element Limit Analysis (FELA) to conduct an in-depth assessment of the bearing capacity of a strip skirted foundation installed in sandy soil, subjected to seismic conditions. By employing a pseudo-static approach, the analysis meticulously examines several critical parameters, such as the embedment depth of the foundation (Ds), the internal friction angle of the sand (φ), and the horizontal seismic coefficient (kh). These variables are rigorously analyzed to understand their impact on the overall behavior of the foundation under dynamic loads. The results, derived from detailed numerical analyses, highlight the effectiveness and resilience of a strip skirted foundation in sandy soil, particularly under seismic loading. The effects of seismic forces have been precisely quantified using the Bearing Capacity Ratio (BCR), which shows a significant improvement when vertical skirts are incorporated into the foundation design. Additionally, the study reveals that variations in the horizontal seismic coefficient (kh) and the embedment depth (Ds) significantly influence the BCR. To provide a broader context, these results have been compared with previous studies available in the scientific literature, thereby validating the findings and contributing to the existing body of knowledge on the subject.
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Chen, Debbie. "Drawdown: Play to Enter - Representing Climate Activism Through Gameplay." In 111th ACSA Annual Meeting Proceedings. ACSA Press, 2023. http://dx.doi.org/10.35483/acsa.am.111.10.
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“Drawdown: Play to Enter” is a cooperative game designed tosimulate the joys of negotiation and collective action required to work through climate strategy and resource management in the built environment. Disciplinary approaches to representingclimate activism often focus on a fixed condition of intervention (before vs. after), whereas game design embodies the active qualities of negotiation, compromise, balance, and incremental progress that occur in the in-between. By introducing the concept of interplay1 to architectural frameworks on the climate,game design expands the territory of architectural agency to model complex mechanisms of environmental stewardship that engage in scientific processes and stakeholder ecologies.The project leverages the fundamental principles of games as a medium of agency.2 Using the large table game board as a representational tool for our shared domain, players in DRAWDOWN are tasked with the shared responsibility of mitigating carbon outputs through the introduction of drawdown technologies while maintaining critical public programs.
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Sun, Qiming, and Sharon Hsiao. "Supporting Informal Sustainability Learning with AI-assisted Educational Technology." In 2024 AHFE International Conference on Human Factors in Design, Engineering, and Computing (AHFE 2024 Hawaii Edition). AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1005567.
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This paper presents Waste Genie (WG), a novel web-based educational platform designed to enhance learning about sustainable waste management. WG employs bite-sized interactive content and leverages artificial intelligence to support sustainability education. To assess WG's efficacy, we conducted a user study involving 21 college students. The study aimed to evaluate improvements in sustainability awareness, waste sorting skills, and overall user experience. Results showed a notable increase in participants' understanding of waste management practices and their ability to correctly classify waste items. This research demonstrates the potential of combining emerging technologies like large language models with interactive learning approaches to address environmental education challenges.
Reports on the topic "Environmental leverages"
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Christie, Benjamin, Osama Ennasr, and Garry Glaspell. Autonomous navigation and mapping in a simulated environment. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/42006.
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Unknown Environment Exploration (UEE) with an Unmanned Ground Vehicle (UGV) is extremely challenging. This report investigates a frontier exploration approach, in simulation, that leverages Simultaneous Localization And Mapping (SLAM) to efficiently explore unknown areas by finding navigable routes. The solution utilizes a diverse sensor payload that includes wheel encoders, three-dimensional (3-D) LIDAR, and Red, Green, Blue and Depth (RGBD) cameras. The main goal of this effort is to leverage frontier-based exploration with a UGV to produce a 3-D map (up to 10 cm resolution). The solution provided leverages the Robot Operating System (ROS).
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Ennasr, Osama, Brandon Dodd, Michael Paquette, Charles Ellison, and Garry Glaspell. Low size, weight, power, and cost (SWaP-C) payload for autonomous navigation and mapping on an unmanned ground vehicle. Engineer Research and Development Center (U.S.), September 2023. http://dx.doi.org/10.21079/11681/47683.
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Autonomous navigation and unknown environment exploration with an unmanned ground vehicle (UGV) is extremely challenging. This report investigates a mapping and exploration solution utilizing low size, weight, power, and cost payloads. The platform presented here leverages simultaneous localization and mapping to efficiently explore unknown areas by finding navigable routes. The solution utilizes a diverse sensor payload that includes wheel encoders, 3D lidar, and red-green-blue and depth cameras. The main goal of this effort is to leverage path planning and navigation for mapping and exploration with a UGV to produce an accurate 3D map. The solution provided also leverages the Robot Operating System.
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Tong, Hui, and Shang-Jin Wei. Endogenous Corporate Leverage Response to a Safer Macro Environment: The Case of Foreign Exchange Reserve Accumulation. Cambridge, MA: National Bureau of Economic Research, December 2019. http://dx.doi.org/10.3386/w26545.
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McFee, Erin. Research Brief: Environmental Peacebuilding with Formerly Armed Actors. Trust After Betrayal, February 2024. http://dx.doi.org/10.59498/21970.
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Environmental Peacebuilding (EPB) is an approach seeking to leverage shared environmental challenges in conflict zones to foster cooperation, trust, and sustainable peace. This Research Brief highlights the potential role of formerly armed actors (FAAs) as key stakeholders in this process, positing that, under specific conditions, they can be leaders in restorative actions for enduring conflict transformation and security building. It also addresses crucial concerns in implementing EPB like the depoliticisation of its processes, displacement of populations, the deligimisation of the state and the reproduction of existing power imbalances. Moreover, it delves into the risks that involving FAAs in this delicate process yields, and proposes ways to incorporate them as equal actors in a democratised multi-level and multistakeholder EPB.
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Wille, Christina, and Alfredo Malaret Baldo. Menu of Indicators to Measure the Reverberating Effects on Civilians from the Use of Explosive Weapons in Populated Areas. UNIDIR, February 2021. http://dx.doi.org/10.37559/caap/21/pacav/01.
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The impacts of explosive weapons use in populated areas are much wider and longer lasting than the shock waves of the explosive blast. The use of explosive weapons sets in motion a series of complex knock-on effects that spread out over time and space in urban ecosystems, with negative consequences for civilian well-being and the environment in which people live. These “reverberating effects” manifest across a wide range of interlinked sectors, including urban infrastructure, public health, education, culture and heritage, food security, economic prospects, and adverse environmental impacts. The purpose of this research framework is to offer indicators to document knock-on effects and potentially inform and influence the policy and practice of parties to conflict. This document aims to shed light on the generalized pattern of harm from the use of explosive weapons in populated areas (EWIPA). By using a standardized set of indicators, the data generated can be leveraged to build a comparable evidence base reflecting the consequences to civilian well-being of the use of EWIPA and to inform high-level decision-making on policy and practice.
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Böhle, Ann-Sophie, and Kheira Tarif. Cultivating Change: Regenerative Agriculture and Peacebuilding in South-central Somalia. Stockholm International Peace Research Institute, November 2024. http://dx.doi.org/10.55163/tasy8060.
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In Somalia, climate change disproportionately disrupts agricultural and pastoral livelihoods, driving harmful practices, such as resource over-exploitation, which exacerbate conflicts. To address these challenges, the International Organization for Migration (IOM) promotes regenerative agriculture as a part of a broader environmental peacebuilding approach aiming to replace negative coping strategies with sustainable practices for long-term resilience. This SIPRI Policy Brief explores the IOM’s approach to regenerative agriculture as a tool for environmental peacebuilding in south-central Somalia. It focuses on analysing how the approach has been designed and highlights elements of the approach that can build resilient livelihoods, encourage cooperation over natural resources and strengthen social cohesion. The policy brief also offers recommendations for donors and implementing organizations to effectively leverage regenerative agriculture for environmental peacebuilding efforts.
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Akinleye, Taiwo, Idil Deniz Akin, Amanda Hohner, Indranil Chowdhury, Richards Watts, Xianming Shi, Brendan Dutmer, James Mueller, and Will Moody. Evaluation of Electrochemical Treatment for Removal of Arsenic and Manganese from Field Soil. Illinois Center for Transportation, June 2021. http://dx.doi.org/10.36501/0197-9191/21-019.
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Soils containing inorganic compounds are frequently encountered by transportation agencies during construction within the right-of-way, and they pose a threat to human health and the environment. As a result, construction activities may experience project delays and increased costs associated with management of inorganic compounds containing soils required to meet environmental regulations. Recalcitrance of metal-contaminated soils toward conventional treatment technologies is exacerbated in clay or organic content-rich fine-grained soils with low permeability and high sorption capacity because of increased treatment complexity, cost, and duration. The objective of this study was to develop an accelerated in situ electrochemical treatment approach to extract inorganic compounds from fine-grained soils, with the treatment time comparable to excavation and off-site disposal. Three reactor experiments were conducted on samples collected from two borehole locations from a field site in Illinois that contained arsenic (As)(~7.4 mg/kg) and manganese (Mn)(~700 mg/kg). A combination of hydrogen peroxide (H2O2) and/or citrate buffer solution was used to treat the soils. A low-intensity electrical field was applied to soil samples using a bench-scale reactor that resembles field-scale in situ electrochemical systems. For the treatment using 10% H2O2 and citrate buffer solution, average removal of 23% and 8% were achieved for Mn and As, respectively. With 4% H2O2 and citrate buffer, 39% and 24% removal were achieved for Mn and As; while using only citrate buffer as the electrolyte, 49% and 9% removal were achieved for Mn and As, respectively. All chemical regimes adopted in this study reduced the inorganic compound concentrations to below the maximum allowable concentration for Illinois as specified by the Illinois Environmental Protection Agency. The results from this work indicate that electrochemical systems that leverage low concentrations of hydrogen peroxide and citrate buffer can be effective for remediating soils containing manganese and arsenic.
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Hall, David, and Sam Lindsay. Scaling Climate Finance: Forest Finance Instruments. Auckland University of Technology, February 2020. http://dx.doi.org/10.24135/10292/17992.
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The Lab’s inaugural concept paper, Scaling Climate Finance: Forest Finance Instruments, proposes seven innovative instruments, each ranked in respect to impact strategy and additionality. The paper analyses an environmental impact bond, a leveraged carbon fund, a green covered bond, an equity fund designed to upscale continuous cover forestry, risk-adjusted loans, and an exchange for investing in Nature-Based Solutions. Each concept was developed by reviewing international innovations, adapting promising structures to the unique local context of Aotearoa New Zealand, and conducting workshops and reviews with sector experts and government observers to test, refine and validate the structure. The paper also identifies relevant indicators for impact assessment, such as IRIS metrics, and potential regulatory changes to support the delivery of more sustainable forest outcomes.
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Mekonnen, Bisrat, Benjamin Christie, Michael Paquette, and Garry Glaspell. 3D mapping and navigation using MOVEit. Engineer Research and Development Center (U.S.), June 2023. http://dx.doi.org/10.21079/11681/47179.
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Until recently, our focus has been primarily on the development of a low SWAP-C payload for deployment on a UGV that leverages 2D mapping and navigation. Due to these efforts, we are able to autonomously map and navigate very well within flat indoor environments. This report will explore the implementation of 3D mapping and navigation to allow unmanned vehicles to operate on a variety of terrains, both indoor and outdoor. The method we followed uses MOVEit, a motion planning framework. The MOVEit application is typically used in the control of robotic arms or manipulators, but its handling of 3D perception using OctoMaps makes it a promising software for robots in general. The challenges of using MOVEit outside of its intended use case of manipulators are discussed in this report.
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Alwosheel, Abdulrahman, and Michael Samsu Koroma. Environmental Performance of Passenger Cars in the KSA: Comparison of Different Technologies via a Life Cycle Assessment Approach. King Abdullah Petroleum Studies and Research Center, December 2024. https://doi.org/10.30573/ks--2024-dp69.
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Analyzing the environmental performance of alternative vehicle technologies in the current energy landscape of the Kingdom of Saudi Arabia (KSA) is very important given their expected role in future transportation systems. This study presents a comprehensive life cycle assessment (LCA) of sedans and sport utility vehicles (SUVs) powered by different propulsion systems to analyze their environmental performance in the KSA context. The LCA examines multiple impact categories, with a particular focus on global warming potential (GWP). The results reveal that hybrid electric vehicles (HEVs), fuel cell electric vehicles (FCEVs), and plug-in hybrid electric vehicles (PHEVs) consistently demonstrate the lowest GWP across both sedan and SUV vehicle classes, achieving reductions of approximately 30%, 28%, and 22%, respectively, compared with the baseline gasoline-powered internal combustion engine vehicles (ICEVs). Battery electric vehicles (BEVs) also exhibit lower GWP (approximately 16%) than do conventional ICEVs but to a lesser extent than do other advanced powertrains. The energy supply chain plays a crucial role for BEVs, including FCEVs and PHEVs, underscoring the importance of decarbonizing electricity and hydrogen (H2) production to realize the full environmental advantages of these technologies in the KSA. In terms of deployment feasibility, PHEVs and HEVs have a distinct advantage over FCEVs, as they can leverage the existing electricity grid and fueling infrastructure, making them a more practical and readily available solution for reducing near-term emissions in the KSA transportation sector. Policymakers and industry stakeholders are encouraged to develop targeted incentives, regulations, and support mechanisms to accelerate the market penetration of these technologies while also considering strategies to address their multifaceted environmental implications.