317 research outputs found
Natural and Technological Hazards in Urban Areas
Natural hazard events and technological accidents are separate causes of environmental impacts. Natural hazards are physical phenomena active in geological times, whereas technological hazards result from actions or facilities created by humans. In our time, combined natural and man-made hazards have been induced. Overpopulation and urban development in areas prone to natural hazards increase the impact of natural disasters worldwide. Additionally, urban areas are frequently characterized by intense industrial activity and rapid, poorly planned growth that threatens the environment and degrades the quality of life. Therefore, proper urban planning is crucial to minimize fatalities and reduce the environmental and economic impacts that accompany both natural and technological hazardous events
Multicriteria Decision Making in Sustainable Tourism and Low-Carbon Tourism Research: A Systematic Literature Review
Multicriteria Decision Making (MCDM) is increasingly being utilized as an analytical research tool for sectors that require decision-making with specific objectives and constraints, such as the tourism industry. Sustainable tourism, which examines the balance of numerous aspects, including stakeholders’ interests, is the critical feature propelling the increased usage of MCDM. This paper explores the use of Multicriteria Decision Making (MCDM) methods applied in studies of sustainable tourism and its derivative term, low-carbon tourism, using a systematic literature review (SLR) search from the Scopus database. The analysis has identified 189 relevant studies published between 1987 to April 2022. After selection, screening, and synthesizing processes, we selected 135 pertinent studies, which were analysed in general descriptive data, citation impacts, geographical categorization, categorization of the methodologies’ objectives, and possible trajectories of similar research in the future. We find that highly cited authors and articles are related to sustainable tourism indicators\u27 development and case studies. Furthermore, most relevant studies are concentrated in Asia and Europe rather than other regions. We also categorize the reviewed studies into six classifications depending on each method\u27s intended usage and further suggest four contexts for the studies’ future trajectory
Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5
This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered.
First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes.
Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification.
Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well
Landslide Susceptibility Assessment of a Part of the Western Ghats (India) Employing the AHP and F-AHP Models and Comparison with Existing Susceptibility Maps
Landslides are prevalent in the Western Ghats, and the incidences that happened in 2021 in the Koottickal area of the Kottayam district (Western Ghats) resulted in the loss of 10 lives. The objectives of this study are to assess the landslide susceptibility of the high-range local self-governments (LSGs) in the Kottayam district using the analytical hierarchy process (AHP) and fuzzy-AHP (F-AHP) models and to compare the performance of existing landslide susceptible maps. This area never witnessed any massive landslides of this dimension, which warrants the necessity of relooking into the existing landslide-susceptible models. For AHP and F-AHP modeling, ten conditioning factors were selected: slope, soil texture, land use/land cover (LULC), geomorphology, road buffer, lithology, and satellite image-derived indices such as the normalized difference road landslide index (NDRLI), the normalized difference water index (NDWI), the normalized burn ratio (NBR), and the soil-adjusted vegetation index (SAVI). The landslide-susceptible zones were categorized into three: low, moderate, and high. The validation of the maps created using the receiver operating characteristic (ROC) technique ascertained the performances of the AHP, F-AHP, and TISSA maps as excellent, with an area under the ROC curve (AUC) value above 0.80, and the NCESS map as acceptable, with an AUC value above 0.70. Though the difference is negligible, the map prepared using the TISSA model has better performance (AUC = 0.889) than the F-AHP (AUC = 0.872), AHP (AUC = 0.867), and NCESS (AUC = 0.789) models. The validation of maps employing other matrices such as accuracy, mean absolute error (MAE), and root mean square error (RMSE) also confirmed that the TISSA model (0.869, 0.226, and 0.122, respectively) has better performance, followed by the F-AHP (0.856, 0.243, and 0.147, respectively), AHP (0.855, 0.249, and 0.159, respectively), and NCESS (0.770, 0.309, and 0.177, respectively) models. The most landslide-inducing factors in this area that were identified through this study are slope, soil texture, LULC, geomorphology, and NDRLI. Koottickal, Poonjar-Thekkekara, Moonnilavu, Thalanad, and Koruthodu are the LSGs that are highly susceptible to landslides. The identification of landslide-susceptible areas using diversified techniques will aid decision-makers in identifying critical infrastructure at risk and alternate routes for emergency evacuation of people to safer terrain during an exigency
Assessing the water-energy-food nexus and resource sustainability in the Ardabil Plain : a system dynamics and HWA approach
Ardabil Plain, which holds significant political and economic importance in agricultural production in Iran, has faced various challenges including climate change, economic sanctions, and limited access to global trade. Ensuring food security has become a key priority for the region. The main objective of this research is to identify a suitable crop for this critical region with regard to future climate change conditions. This study employs a new framework of the system dynamics model (SDM) and the Hybrid Weighted Averaging (HWA) method to assess the Water–Energy–Food (WEF) nexus and resource sustainability in the Ardabil Plain under different climate change scenarios (RCP 2.6, RCP 4.5, and RCP 8.5). The research addresses current and future water challenges, emphasizing the need for additional energy and selecting optimal crops. Using the SDM, the study analyzes the impact of water supply fluctuations on agriculture, economic gain, and energy consumption from 2021 to 2050. The results indicate that barley is the most suitable crop for the Ardabil Plain in the near future, based on the overall ranking derived from the HWA method, which is as follows: barley > wheat > soybeans > potatoes > pears. The study highlights the significant challenges in energy supply for agriculture due to declining water levels and the increased force required by pumps to supply water to farms. These findings provide valuable insights for policymakers and stakeholders to make informed decisions in addressing water scarcity and rising energy demands in the Ardabil Plain
Application of Business Analytics Approaches to Address Climate-Change-Related Challenges
Climate change is an existential threat facing humanity, civilization, and the natural world. It poses many multi-layered challenges that call for enhanced data-driven decision support methods to help inform society of ways to address the deep uncertainty and incomplete knowledge on climate change issues. This research primarily aims to apply management, decision, information, and data science theories and techniques to propose, build, and evaluate novel data-driven methodologies to improve understanding of climate-change-related challenges. Given that we pursue this work in the College of Management, each essay applies one or more of the three distinct business analytics approaches (i.e., descriptive, prescriptive, and predictive analysis) to aid in developing decision support capabilities. Given the rapid growth in data availability, we evaluate important data characteristics for each analysis, focusing on the data source, granularity, volume, structure, and quality. The final analysis consideration is the methods used on the data output to help coalesce the various model outputs into understandable visualizations, tables, and takeaways. We pursue three distinct business analytics challenges. First, we start with a natural language processing analysis to gain insights into the evolving climate change adaptation discussion in the scientific literature. We then create a stochastic network optimization model with recourse to provide coastal decision-makers with a cost-benefit analysis tool to simultaneously assess risks and costs to protect their community against rising seas. Finally, we create a decision support tool for helping organizations reduce greenhouse gas emissions through strategic sustainable energy purchasing. Although the three essays vary on their specific business analysis approaches, they all have a common theme of applying business analytics techniques to analyze, evaluate, visualize, and understand different facets of the climate change threat
モンゴル国ウランバートル市の持続的廃棄物管理の改善のためのLCAと多基準意思決定分析
In last years, as the lifestyle and socio-economic situation of the citizens is changing, in this regards amount of the municipal waste and type of waste are also increasing in the Ulaanbaatar city. This research analyzed each of the four waste disposal methods, to develop and select the waste management best option. To estimates economic efficiency Life cycle cost analysis methods based on the municipal waste disposal budget data; used tool a Cost-benefit analysis of each scenario explores opportunities to increase waste revenues and reduce annual costs. Also analyzes Life cycle impact assessment for each waste treatment option and includes a Life cycle assessment that considers direct and indirect GHG emissions during landfilling, waste incineration, composting, recycling, or energy consumption from waste treatment in Ulaanbaatar city. This research was conducted based on the Multi criteria decision analysis method for evaluating the performance of each scenario considered hereafter as well as interviews with experts. These interviews were used to identify key ideas related to waste management. These issues have been considered using Technique for order preference by similarity to ideal solution analysis to determine the potential impacts of environmental, economic, technical, and social factors, which were analyzed for each waste disposal method to develop and select the best option. As the result, MBT plant has not been advantageous considering all criteria. However, waste incineration is the most cost-effective option in Ulaanbaatar city in terms of saving coal resources and reducing coal production.北九州市立大
Trends in Science and Technology for Sustainable Living
Dalam buku ini, dibahas mengenai perkembangan tren
kajian dalam sains dan teknologi yang mendukung pembangunan
berkelanjutan untuk mewujudkan kehidupan berkelanjutan.
Pembangunan berkelanjutan mempunyai prinsip pembangunan
yang bertujuan memenuhi kebutuhan generasi saat ini tetapi
tidak mengurangi ataupun mengorbankan kemampuan generasi
selanjutnya dalam memenuhi kebutuhan mereka; sehingga
kehidupan yang baik akan terus berlanjut dalam waktu yang
lama. Pembangunan berkelanjutan saat ini berfokus pada tiga
hal, yaitu pembangunan keberlanjutan ekonomi dan sosial, serta perlindungan terhadap lingkungan untuk generasi mendatang.
Ketiganya saling berhubungan dan mendukung dalam mencapai
tujuan pembangunan serta stabilitas lingkungan dan sosial. Oleh karena itu, keseimbangan yang baik dalam aspek lingkungan,ekonomi, dan sosial harus dicapai untuk membentuk kehidupan berkelanjutan
Changing Priorities. 3rd VIBRArch
In order to warrant a good present and future for people around the planet and to safe the care of the planet itself, research in architecture has to release all its potential. Therefore, the aims of the 3rd Valencia International Biennial of Research in Architecture are:
- To focus on the most relevant needs of humanity and the planet and what architectural research can do for solving them.
- To assess the evolution of architectural research in traditionally matters of interest and the current state of these popular and widespread topics.
- To deepen in the current state and findings of architectural research on subjects akin to post-capitalism and frequently related to equal opportunities and the universal right to personal development and happiness.
- To showcase all kinds of research related to the new and holistic concept of sustainability and to climate emergency.
- To place in the spotlight those ongoing works or available proposals developed by architectural researchers in order to combat the effects of the COVID-19 pandemic.
- To underline the capacity of architectural research to develop resiliency and abilities to adapt itself to changing priorities.
- To highlight architecture's multidisciplinarity as a melting pot of multiple approaches, points of view and expertise.
- To open new perspectives for architectural research by promoting the development of multidisciplinary and inter-university networks and research groups.
For all that, the 3rd Valencia International Biennial of Research in Architecture is open not only to architects, but also for any academic, practitioner, professional or student with a determination to develop research in architecture or neighboring fields.Cabrera Fausto, I. (2023). Changing Priorities. 3rd VIBRArch. Editorial Universitat Politècnica de València. https://doi.org/10.4995/VIBRArch2022.2022.1686
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