Search results for: climate data validation

Authors: Sristi Silwal

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South Asian rivers support ecosystems and sustain well-being of thousands of riparian communities. Rivers however are also sources of conflict between countries and one of the contested issues between governments of the region. Governments have signed treaties to harness some of the rivers but their provisions have not been successful in improving the quality of life of those who depend on water as common property resources. This paper will present a case of the study of the status of the water commons along the lower command areas of Koshi, Gandka and Mahakali rivers. Nepal and India have signed treaties for development and management of these rivers in 1928, 1954 and 1966. The study investigated perceptions of the local community on climate-induced disasters, provision of the treaties such as water for irrigation, participation in decision-making and specific impact of women. It looked at how the local community coped with adversities. The study showed that the common pool resources are gradually getting degraded, flood events increasing while community blame ‘other state’ and state administration for exacerbating these ills. The level of awareness about provisions of existing treatise is poor. Ongoing approach to trans-boundary water management has taken inadequate cognizance of these realities as the dominant narrative perpetuates cooperation between the governments. The paper argues that on-going discourses on trans-boundary water development and management need to use a new metrics of taking cognizance of the condition of the commons and that of the people depended on them for sustenance. In absence of such narratives, the scale of degradation would increase making those already marginalized more vulnerable to impacts of global climate change.

Keywords: climate change vulnerability, conflict, cooperation, water commons

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Authors: Svetlana Pushkar, Oleg Verbitsky

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An energy-conscious design for a classroom in a hot-humid climate is reanalyzed. The hypothesis of this study is that use of photovoltaic (PV) electricity generation in building operation energy consumption will lead to re-analysis of the energy-conscious design. Therefore, the objective of this study is to reanalyze the energy-conscious design by evaluating the environmental impact of operational energy with PV electrical generation. Using the hierarchical design structure of Eco-indicator 99, the alternatives for energy-conscious variables are statistically evaluated by applying a two-stage nested (hierarchical) ANOVA. The recommendations for the preferred solutions for application of glazing types, wall insulation, roof insulation, window size, roof mass, and window shading design alternatives were changed (for example, glazing type recommendations were changed from low-emissivity glazing, green, and double- glazed windows to low-emissivity glazing only), whereas the applications for the lighting control system and infiltration are not changed. Such analysis of operational energy can be defined as environment-conscious analysis.

Keywords: ANOVA, Eco-Indicator 99, energy-conscious design, hot–humid climate, photovoltaic

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Authors: Mary Joy C. Montenegro, Voltaire M. Mistades

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This action research was implemented to enhance the teaching of linear motion and to improve students' conceptual understanding and engagement using a developed 7R-based module called 'module on vectors and one-dimensional kinematics' (MVOK). MVOK was validated in terms of objectives, contents, format, and language used, presentation, usefulness, and overall presentation. The validation process revealed a value of 4.7 interpreted as 'Very Acceptable' with a substantial agreement (0. 60) from the validators. One intact class of 46 Grade 12 STEM students from one of the public schools in Paranaque City served as the participants of this study. The students were taught using the module during the first semester of the academic year 2019–2020. Employing the mixed-method approach, quantitative data were gathered using pretest/posttest, activity sheets, problem sets, and survey form, while qualitative data were obtained from surveys, interviews, observations, and reflection log. After the implementation, there was a significant difference of 18.4 on students’ conceptual understanding as shown in their pre-test and post-test scores on the 24-item test with a moderate Hake gain equal to 0.45 and an effect size of 0.83. Moreover, the scores on activity and problem sets have a 'very good' to 'excellent' rating, which signifies an increase in the level of students’ conceptual understanding. There also exists a significant difference between the mean scores of students’ engagement overall (t= 4.79, p = 0.000, p < 0.05) and in the dimension of emotion (t = 2.51, p = 0.03) and participation/interaction (t = 5.75, p = 0.001). These findings were supported by gathered qualitative data. Positive views were elicited from the students since it is an accessible tool for learning and has well-detailed explanations and examples. The results of this study may substantiate that using MVOK will lead to better physics content understanding and higher engagement.

Keywords: conceptual understanding, engagement, linear motion, module

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Organizations, including governments, generate (big) data that are high in volume, velocity, veracity, and come from a variety of sources. Public Administrations are using (big) data, implementing base registries, and enforcing data sharing within the entire government to deliver (big) data related integrated services, provision of insights to users, and for good governance. Government (Big) data ecosystem actors represent distinct entities that provide data, consume data, manipulate data to offer paid services, and extend data services like data storage, hosting services to other actors. In this research work, we perform a systematic literature review. The key objectives of this paper are to propose a robust definition of government (big) data ecosystem and a classification of government (big) data ecosystem actors and their roles. We showcase a graphical view of actors, roles, and their relationship in the government (big) data ecosystem. We also discuss our research findings. We did not find too much published research articles about the government (big) data ecosystem, including its definition and classification of actors and their roles. Therefore, we lent ideas for the government (big) data ecosystem from numerous areas that include scientific research data, humanitarian data, open government data, industry data, in the literature.

Keywords: big data, big data ecosystem, classification of big data actors, big data actors roles, definition of government (big) data ecosystem, data-driven government, eGovernment, gaps in data ecosystems, government (big) data, public administration, systematic literature review

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Authors: Nowbuth Manta Devi, Rasmally Mohammed Hussein

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Flood is one of the most devastating climate impacts that many countries are facing. Many different causes have been associated with the intensity of floods being recorded over time. Unplanned development, low carrying capacity of drains, clogged drains, construction in flood plains or increasing intensity of rainfall events. While a combination of these causes can certainly aggravate the flood conditions, in many cases, increasing drainage capacity has not reduced flood risk to the level that was expected. The present study analyzed the extent to which land use is contributing to aggravating impacts of flooding in a city. Satellite images have been analyzed over a period of 20 years at intervals of 5 years. Both unsupervised and supervised classification methods have been used with the image processing module of ArcGIS. The unsupervised classification was first compared to the basemap available in ArcGIS to get a first overview of the results. These results also aided in guiding data collection on-site for the supervised classification. The island of Mauritius is small, and there are large variations in land use over small areas, both within the built areas and in agricultural zones involving food crops. Larger plots of agricultural land under sugar cane plantations are relatively more easily identified. However, the growth stage and health of plants vary and this had to be verified during ground truthing. The results show that although there have been changes in land use as expected over a span of 20 years, this was not significant enough to cause a major increase in flood risk levels. A digital elevation model was analyzed for further understanding. It could not be noted that overtime, development tampered with natural flow paths in addition to increasing the impermeable areas. This situation results in backwater flows, hence increasing flood risks.

Keywords: climate change, flood, natural flow paths, small islands

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Authors: Ejaz Ahmed, Huang Yong

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The operation of aero engines has a critical importance in the vicinity of lean blowout (LBO) limits. Lefebvre’s model of LBO based on empirical correlation has been extended to flame volume concept by the authors. The flame volume takes into account the effects of geometric configuration, the complex spatial interaction of mixing, turbulence, heat transfer and combustion processes inside the gas turbine combustion chamber. For these reasons, flame volume based LBO predictions are more accurate. Although LBO prediction accuracy has improved, it poses a challenge associated with Vf estimation in real gas turbine combustors. This work extends the approach of flame volume prediction previously based on fuel iterative approximation with cold flow simulations to reactive flow simulations. Flame volume for 11 combustor configurations has been simulated and validated against experimental data. To make prediction methodology robust as required in the preliminary design stage, reactive flow simulations were carried out with the combination of probability density function (PDF) and discrete phase model (DPM) in FLUENT 15.0. The criterion for flame identification was defined. Two important parameters i.e. critical injection diameter (Dp,crit) and critical temperature (Tcrit) were identified, and their influence on reactive flow simulation was studied for Vf estimation. Obtained results exhibit ±15% error in Vf estimation with experimental data.

Keywords: CFD, combustion, gas turbine combustor, lean blowout

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Authors: Ranjitkumar Patil

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Age estimation has importance in forensic dentistry. Dental age estimation has emerged as an alternative to skeletal age determination. The methods based on stages of tooth formation, as appreciated on radiographs, seem to be more appropriate in the assessment of age than those based on skeletal development. The study was done to evaluate dental age in the north Indian population using Cameriere’s method. Aims/Objectives: The study was conducted to assess the dental age of North Indian children using Cameriere’s method and to compare the chronological age and dental age for validation of the Cameriere’s method in the north Indian population. A comparative study of 02-year duration on the OPG (using PLANMECA Promax 3D) data of 497 individuals with ages ranging from 5 to 15 years was done based on simple random technique ethical approval obtained from institutional ethical committee. The data was obtained based on inclusion and exclusion criteria and was analyzed by software for dental age estimation. Statistical analysis: The student’s t-test was used to compare the morphological variables of males with those of females and to compare observed age with estimated age. The regression formula was also calculated. Results: Present study was a comparative study of 497 subjects with a distribution between males and females, with their dental age assessed by using a Panoramic radiograph, following the method described by Cameriere, which is widely accepted. Statistical analysis in our study indicated that gender does not have a significant influence on age estimation. (R2= 0.787). Conclusion: This infers that Cameriere’s method can be effectively applied to the north Indian population.

Keywords: forensic, dental age, skeletal age, chronological age, Cameriere’s method

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Authors: Panasbodee Thachaopas, Duangdorm Gamnerdsap, Waraporn Inthip, Arissara Pungpa

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LDD’s IM Farm or Land Development Department’s Integrated Management Farm is the agricultural simulation application developed by Land Development Department relies on actual data in simulation game to grow 12 cash crops which are rice, corn, cassava, sugarcane, soybean, rubber tree, oil palm, pineapple, longan, rambutan, durian, and mangosteen. Launching in simulation game, players could select preferable areas for cropping from base map or Orthophoto map scale 1:4,000. Farm management is simulated from field preparation to harvesting. The system uses soil group, and present land use database to facilitate player to know whether what kind of crop is suitable to grow in each soil groups and integrate LDD’s data with other agencies which are soil types, soil properties, soil problems, climate, cultivation cost, fertilizer use, fertilizer price, socio-economic data, plant diseases, weed, pest, interest rate for taking on loan from Bank for Agriculture and Agricultural Cooperatives (BAAC), labor cost, market prices. These mentioned data affect the cost and yield differently to each crop. After completing, the player will know the yield, income and expense, profit/loss. The player could change to other crops that are more suitable to soil groups for optimal yields and profits.

Keywords: agricultural simulation, smart farmer, web application, factors of agricultural production

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Authors: Debanjana Chatterjee

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Vernacular settlements in India often take the form that is dictated by the climate they are in. India, with its vast cultural diversity and various climatic regions, offers a wide range of vernacular architecture. This paper focuses on two main geographical regions: Kashmir and Kerala. They bring together myriad challenges of climatic and social characteristics to incorporate into their vernacular architectures, which are still relevant despite the advent of globalization and modernization. Scholars like William Wurster and Catherine Bauer even claimed that all the traditional buildings in these places have the kind of urbanity, which is dignified and elegant but also lively and human that every architect would like to achieve if they knew how. With modernization, and with a greater ease of construction, a reduction in labor, and the apparent robustness of contemporary construction techniques, people have, however, become increasingly tentative in respect of vernacular architecture. And yet modern architecture has typically led to energize intensive structures without much consideration to the location and surroundings of the structure itself. In contrary, Laurie Baker, the British-born Indian architect, had shown us the way to integrate the knowledge of vernacular when he developed his designs based on the traditional architecture of Kerala, respecting the local climate and environment. This paper also explores his technical creativity in his design of Center for Development Studies (CDS) in Trivandrum. Hence, in order to protect and conserve our rich cultural and architectural heritage, the elements of vernacular should be incorporated into the contemporary planning and architecture for sustainable building design. The provision should be made to incorporate vernacular architecture and traditional knowledge in the policies. Ultimately, the policymakers, planners, and architects should consider this incorporation of traditional vernacular and contemporary sustainability in their work for the betterment of society now.

Keywords: vernacular, architecture, sustainable development, Kashmir and Kerala, climate, Laurie Baker

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Authors: Smart E. Amanfo

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Although the exact functional relationship between energy consumption and economic growth and development remains a complex social science, there is a sustained growing of agreement among energy economists and the likes on direct or indirect role of energy use in the development process, and as sustenance for many of societal achieved socio-economic and environmental developments in any economy. According to OECD, the world economy will double by 2050 in which the two members of BRICS (Brazil, Russia, India, China and South Africa) countries: China and India lead. There is a global apprehension that if countries constituting the epicenter of the present and future economic growth follow the same trajectory as during and after Industrial Revolution, involving higher energy throughputs, especially fossil fuels, the already known and models predicted threats of climate change and global warming could be exacerbated, especially in the developing economies. The international community’s challenge is how to address the trilemma of economic growth, social development, poverty eradication and stability of the ecological systems. This paper aims at providing the estimates of economic growth, energy consumption, and carbon dioxide emissions using BRICS members’ panel data from 1980 to 2017. The preliminary results based on fixed effect econometric model show positive significant relationship between energy consumption and economic growth. The paper further identified a strong relationship between economic growth and CO2 emissions which suggests that the global agenda of low-carbon-led growth and development is not a straight forward achievable The study therefore highlights the need for BRICS member states to intensify low-emissions-based production and consumption policies, increase renewables in order to avoid further deterioration of climate change impacts.

Keywords: BRICS, sustainability, sustainable development, energy consumption, economic growth

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Authors: Renata Martins Pacheco, João Claro

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Wildfires are becoming an increasing concern worldwide, causing substantial social, economic, and environmental disruptions. This situation is especially relevant in Mediterranean-climate regions, present in all the five continents of the world, in which fire is not only a natural component of the environment but also perhaps one of the most important evolutionary forces. The rise in wildfire occurrences and their associated impacts suggests the need for identifying knowledge gaps and enhancing the basis of scientific evidence on how managers and policymakers may act effectively to address them. Considering that the main goal of a systematic map is to collate and catalog a body of evidence to describe the state of knowledge for a specific topic, it is a suitable approach to be used for this purpose. In this context, the aim of this study is to systematically map the research trends in wildfire management practices in Mediterranean-climate regions. A total of 201 wildfire management studies were analyzed and systematically mapped in terms of their: Year of publication; Place of study; Scientific outlet; Research area (Web of Science) or Research field (Scopus); Wildfire phase; Central research topic; Main objective of the study; Research methods; and Main conclusions or contributions. The results indicate that there is an increasing number of studies being developed on the topic (most from the last 10 years), but more than half of them are conducted in few Mediterranean countries (60% of the analyzed studies were conducted in Spain, Portugal, Greece, Italy or France), and more than 50% are focused on pre-fire issues, such as prevention and fuel management. In contrast, only 12% of the studies focused on “Economic modeling” or “Human factors and issues,” which suggests that the triple bottom line of the sustainability argument (social, environmental, and economic) is not being fully addressed by fire management research. More than one-fourth of the studies had their objective related to testing new approaches in fire or forest management, suggesting that new knowledge is being produced on the field. Nevertheless, the results indicate that most studies (about 84%) employed quantitative research methods, and only 3% of the studies used research methods that tackled social issues or addressed expert and practitioner’s knowledge. Perhaps this lack of multidisciplinary studies is one of the factors hindering more progress from being made in terms of reducing wildfire occurrences and their impacts.

Keywords: wildfire, Mediterranean-climate regions, management, policy

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Authors: Jamil Hijazi, Stirling Howieson

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Over one-quarter of the Kingdom of Saudi Arabia’s total oil production (2.8 million barrels a day) is used for electricity generation. The built environment is estimated to consume 77% of the total energy production. Of this amount, air conditioning systems consume about 80%. Apart from considerations surrounding global warming and CO2 production it has to be recognised that oil is a finite resource and the KSA like many other oil rich countries will have to start to consider a horizon where hydro-carbons are not the dominant energy resource. The employment of hybrid ground cooling pipes in combination with black body solar collection and radiant night cooling systems may have the potential to displace a significant proportion of oil currently used to run conventional air conditioning plant. This paper presents an investigation into the viability of such hybrid systems with the specific aim of reducing carbon emissions while providing all year round thermal comfort in a typical Saudi Arabian urban housing block. At the outset air and soil temperatures were measured in the city of Jeddah. A parametric study then was carried out by computational simulation software (Design Builder) that utilised the field measurements and predicted the cooling energy consumption of both a base case and an ideal scenario (typical block retro-fitted with insulation, solar shading, ground pipes integrated with hypocaust floor slabs/ stack ventilation and radiant cooling pipes embed in floor).Initial simulation results suggest that careful ‘ecological design’ combined with hybrid radiant and ground pipe cooling techniques can displace air conditioning systems, producing significant cost and carbon savings (both capital and running) without appreciable deprivation of amenity.

Keywords: energy efficiency, ground pipe, hybrid cooling, radiative cooling, thermal comfort

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Authors: Marlon P. Perez

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The study intended to determine the level of occupational stress that was experienced by faculty members of private and public business schools in Batangas City with the end in view of proposing organizational development interventions in managing occupational stressors. Stressors such as factors intrinsic to the job, role in the organization, relationships at work, career development and organizational structure and climate were used as determinants of occupational stress level. Descriptive method of research was used as its research design. There were only 64 full-time faculty members coming from private and public business schools in Batangas City – University of Batangas, Lyceum of the Philippines University-Batangas, Golden Gate Colleges, Batangas State University and Colegio ng Lungsod ng Batangas. Survey questionnaire was used as data gathering instrument. It was found out that all occupational stressors were assessed stressful when grouped according to its classification of tertiary schools while response of subject respondents differs on their assessment of occupational stressors. Age variable has become significantly related to respondents’ assessments on factors intrinsic to the job and career development; however, it was not significantly related to role in the organization, relationships at work and organizational structure and climate. On the other hand, gender, marital status, highest educational attainment, employment status, length of service, area of specialization and classification of tertiary school were revealed to be not significantly related to all occupational stressors. Various organizational development interventions have been proposed to manage the occupational stressors that are experienced by business faculty members in the institution.

Keywords: occupational stress, business school, organizational development, intervention, stressors, faculty members, assessment, manage

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Authors: Abdullah Pandang, Mantasiah Rivai, Nur Fadhilah Umar, Azam Arifyadi

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This study aims to measure the validity of the politeness behaviour scale and obtain a model that fits the scale. The researcher developed the Politeness Behavior on Communicating (PBC) scale. The research method uses descriptive quantitative by developing the PBC scale. The population in this study were students in three provinces, namely South Sulawesi, West Sulawesi, and Central Sulawesi, recorded in the 2022/2023 academic year. The sampling technique used stratified random sampling by determining the number of samples using the Slovin formula. The sample of this research is 1200 students. This research instrument uses the PBC scale, which consists of 5 (five) indicators: self-regulation of compensation behaviour, self-efficacy of compensation behaviour, fulfilment of social expectations, positive feedback, and no strings attached. The PBC scale consists of 34 statement items. The data analysis technique is divided into two types: the validity test on the correlated item values and the item reliability test referring to Cronbach's and McDonald's alpha standards using the JASP application. Furthermore, the data were analyzed using confirmatory factor analysis (CFA) and exploratory factor analysis (EFA). The results showed that the adaptation of the Politeness Behavior on Communicating (PBC) scale was on the Fit Index with a chi-square value (711,800/375), RMSEA (0.53), GFI (0.990), CFI (0.987), GFI (0.985).

Keywords: polite behavior in communicating, positive communication, exploration factor analysis, confirmatory factor analysis

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Authors: Foroozan Sadri, Mohammadmehdi Moulaii, Farkhondeh Vahdati

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Smart materials can create a great revolution in our built environment, as living systems do. In this research, the optimal structure of healthcare building envelopes is analyzed in terms of thickness according to the utility of the smart-nano materials as nontoxic substances in the region. The research method in this paper is based on library studies and simulation. Grasshopper program is employed to simulate thermal characteristics to achieve the optimum U-value in Semnan desert climate, according to Iranian national standards. The potential of healthcare envelope layouts in thermal properties development (primarily U-value) of these buildings is discussed due to the high thermal loads of healthcare buildings and also toxicity effects of conventional materials. As a result, envelope thicknesses are calculated, and the performance of the nano-PCM and gypsum wallboards are compared. A solution with comparable performance using smart-nano materials instead of conventional materials would determine a decrease in wall thickness.

Keywords: energy saving, exterior envelope, smart-nano materials, thermal performance, U-value

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Authors: Ozden Saygili, Eser Cakti

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The masonry building stock in Istanbul and in other cities of Turkey are exposed to significant earthquake hazard. Determination of the safety of masonry structures against earthquakes is a complex challenge. This study deals with experimental tests and non-linear dynamic analysis of masonry structures modeled through discrete element method. The 1:10 scale model of Mustafa Paşa Mosque was constructed and the data were obtained from the sensors on it during its testing on the shake table. The results were used in the calibration/validation of the numerical model created on the basis of the 1:10 scale model built for shake table testing. 3D distinct element model was developed that represents the linear and nonlinear behavior of the shake table model as closely as possible during experimental tests. Results of numerical analyses with those from the experimental program were compared and discussed.

Keywords: dynamic analysis, non-linear modeling, shake table tests, masonry

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Authors: Zografou Konstantina, Anagnostellis Konstantinos, Brokaki Marina, Kaltsouni Eleftheria, Dimaki Maria, Kati Vassiliki

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Body size is crucial to ecology, influencing everything from individual reproductive success to the dynamics of communities and ecosystems. Understanding how temperature affects variations in body size is vital for both theoretical and practical purposes, as changes in size can modify trophic interactions by altering predator-prey size ratios and changing the distribution and transfer of biomass, which ultimately impacts food web stability and ecosystem functioning. Notably, a decrease in body size is frequently mentioned as the third "universal" response to climate warming, alongside shifts in distribution and changes in phenology. This trend is backed by ecological theories like the temperature-size rule (TSR) and Bergmann's rule, which have been observed in numerous species, indicating that many species are likely to shrink in size as temperatures rise. However, the thermal responses related to body size are still contradictory, and further exploration is needed. To tackle this challenge, we developed the MEIOSIS project, aimed at providing valuable insights into the relationship between the body size of species, species’ traits, environmental factors, and their response to climate change. We combined a digitized collection of butterflies from the Swiss Federal Institute of Technology in Zürich with our newly digitized butterfly collection from Goulandris Natural History Museum in Greece to analyse trends in time. For a total of 23868 images, the length of the right forewing was measured using ImageJ software. Each forewing was measured from the point at which the wing meets the thorax to the apex of the wing. The forewing length of museum specimens has been shown to have a strong correlation with wing surface area and has been utilized in prior studies as a proxy for overall body size. Temperature data corresponding to the years of collection were also incorporated into the datasets. A second dataset was generated when a custom computer vision tool was implemented for the automated morphological measuring of samples for the digitized collection in Zürich. Using the second dataset, we corrected manual measurements with ImageJ, and a final dataset containing 31922 samples was used for analysis. Setting time as a smoother variable, species identity as a random factor, and the length of right-wing size (a proxy for body size) as the response variable, we ran a global model for a maximum period of 110 years (1900 – 2010). Then, we investigated functional variability between different terrestrial biomes in a second model. Both models confirmed our initial hypothesis and resulted in a decreasing trend in body size over the years. We expect that this first output can be provided as basic data for the next challenge, i.e., to identify the ecological traits that influence species' temperature-size responses, enabling us to predict the direction and intensity of a species' reaction to rising temperatures more accurately.

Keywords: butterflies, shrinking body size, museum specimens, climate change

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Authors: Yevheniia Varyvoda, Douglas Taren

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At the aggregate level, climate variability, the rising number of active violent conflicts, globalization and industrialization of agriculture, the loss in diversity of crop species, the increase in demand for agricultural production, and the adoption of healthy and sustainable dietary patterns are exacerbating factors of food system destabilization. The importance of pseudocereals to fuel and sustain resilient food systems is recognized by leading organizations working to end hunger, particularly for their critical capability to diversify livelihood portfolios and provide plant-sourced healthy nutrition in the face of systemic shocks and stresses. Amaranth, buckwheat, and quinoa are the most promising and used pseudocereals for ensuring food system resilience in the reality of climate change due to their high nutritional profile, good digestibility, palatability, medicinal value, abiotic stress tolerance, pest and disease resistance, rapid growth rate, adaptability to marginal and degraded lands, high genetic variability, low input requirements, and income generation capacity. The study provides the rationale and examples of advancing local and regional food systems' resilience by scaling up the utilization of amaranth, buckwheat, and quinoa along all components of food systems to architect indirect nutrition interventions and climate-smart approaches. Thus, this study aims to explore the drivers for ancient pseudocereal utilization, the potential resilience benefits that can be derived from using them, and the challenges and opportunities for pseudocereal utilization within the food system components. The PSALSAR framework regarding the method for conducting systematic review and meta-analysis for environmental science research was used to answer these research questions. Nevertheless, the utilization of pseudocereals has been slow for a number of reasons, namely the increased production of commercial and major staples such as maize, rice, wheat, soybean, and potato, the displacement due to pressure from imported crops, lack of knowledge about value-adding practices in food supply chain, limited technical knowledge and awareness about nutritional and health benefits, absence of marketing channels and limited access to extension services and information about resilient crops. The success of climate-resilient pathways based on pseudocereal utilization underlines the importance of co-designed activities that use modern technologies, high-value traditional knowledge of underutilized crops, and a strong acknowledgment of cultural norms to increase community-level economic and food system resilience.

Keywords: resilience, pseudocereals, food system, climate change

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Authors: Kenan Morani, Esra Kaya Ayana

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This study aimed to develop a novel pipeline for COVID-19 detection using a large and rigorously annotated database of computed tomography (CT) images. The pipeline consists of UNet-based segmentation, lung extraction, and a classification part, with the addition of optional slice removal techniques following the segmentation part. In this work, a batch normalization was added to the original UNet model to produce lighter and better localization, which is then utilized to build a full pipeline for COVID-19 diagnosis. To evaluate the effectiveness of the proposed pipeline, various segmentation methods were compared in terms of their performance and complexity. The proposed segmentation method with batch normalization outperformed traditional methods and other alternatives, resulting in a higher dice score on a publicly available dataset. Moreover, at the slice level, the proposed pipeline demonstrated high validation accuracy, indicating the efficiency of predicting 2D slices. At the patient level, the full approach exhibited higher validation accuracy and macro F1 score compared to other alternatives, surpassing the baseline. The classification component of the proposed pipeline utilizes a convolutional neural network (CNN) to make final diagnosis decisions. The COV19-CT-DB dataset, which contains a large number of CT scans with various types of slices and rigorously annotated for COVID-19 detection, was utilized for classification. The proposed pipeline outperformed many other alternatives on the dataset.

Keywords: classification, computed tomography, lung extraction, macro F1 score, UNet segmentation

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Authors: Seung-Min Ko, Seung-Jai Choi, Gun Jung, Jang-Ho Jay Kim

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Although extensive explosion-related research has been performed in the past several decades, almost no research has focused on internal blasts. However, internal blast research is needed to understand about the behavior of a containment structure or building under internal blast loading, as in the case of the Chornobyl and Fukushima nuclear accidents. Therefore, the internal blast study concentrated on RC and PSC structures is performed. The test data obtained from reinforced concrete (RC) and prestressed concrete (PSC) tubular structures applied with an internal explosion using ammonium nitrate/fuel oil (ANFO) charge are used to assess their deformation resistance and ultimate failure load based on the structural stiffness change under various charge weight. For the internal blast charge weight, ANFO explosive charge weights of 15.88, 20.41, 22.68 and 24.95 kg were selected for the RC tubular structures, and 22.68, 24.95, 27.22, 29.48, and 31.75 kg were selected for PSC tubular structures, which were detonated at the center of cross section at the mid-span with a standoff distance of 1,000mm to the inner wall surface. Then, the test data were used to predict the internal charge weight required to fail a real scale reinforced concrete containment vessels (RCCV) and prestressed concrete containment vessel (PCCV). Then, the analytical results based on the experimental data were derived using the simple assumptions of the models, and another approach using the stiffness, deformation and explosion weight relationship was used to formulate a general method for analyzing internal blasted tubular structures. A model of the internal explosion of a steel tube was used as an example for validation. The proposed method can be used generically, using factors according to the material characteristics of the target structures. The results of the study are discussed in detail in the paper.

Keywords: internal blast, reinforced concrete, RCCV, PCCV, stiffness, blast safety

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Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Harsha B. R., Anil Kumar K. S.

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Climate and soils are the two most dynamic entities among the factors affecting growth and grapes productivity. Studying of prevailing climate over the years in a region provides sufficient information related to management practices to be carried out in vineyards. Evaluating the suitability of vineyard soils under different climatic conditions serves as the yardstick to analyse the performance of grapevines. This study was formulated to study the climate and evaluate the site-suitability of soils in vineyards of southern Karnataka, which has registered its superiority in the quality production of wine. Ten soil profiles were excavated for suitability evaluation of soils, and six taluks were studied for climatic analysis. In almost all the regions studied, recharge starts at the end of the May or June months, peaking in either September or October months. Soil Starts drying from mid of December months in the taluks studied. Bangalore North (Rajanukunte) soils were highly suited for grapes cultivation with no or slight limitations. Bangalore North (GKVK Farm) was moderately suited with slight to moderate limitations of slope and available nitrogen content. Moderate suitability was observed in the rest of the profiles studied in Eastern dry zone soils with the slight to moderate limitations of either organic carbon or available nitrogen or both in the Eastern dry zone. Magadi (Southern dry zone) soils were moderately suitable with slight to moderate limitations of graveliness, available nitrogen, organic carbon, and exchangeable sodium percentage. Sustainable performance of vineyards in terms of yield can be achieved in these taluks by managing the constraints existing in soils.

Keywords: climatic analysis, dry zone, water recharge, growing period, suitability, sustainability

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Authors: Aptin Rahnavard, Ghavamaldin Asadian, Khalil Pourshamsian, Mariamalsadat Taghavi

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Dog rose is one of the important rose species in Iran that the distant past had been considered due to nutritional value and medicinal. Despite its long history of use, due to poor information on the genetic modification of plants has been done resources inheritance. In this study was to assess the genetic diversity. Total of 30 genotypes Dog rose from areas of northern Iran in the Caspian region (provinces of Guilan and Mazandaran) were evaluated using 25 RAPD primers. The number of bands produced total of 202 and for each primer were measured in a bands with an average 8-band .The number of polymorphic bands per primer ranged from 1 to 13 and the bands were in the range of 300 to 3000 bp. Based on the results OPA-04 primer with 13 bands and PRA-1, E-09 and A-04 with 5-band were created maximum and minimum number of amplified fragments. Molecular marker genotypes showed a high degree of polymorphism. Studied genotypes based on RAPD results were divided into 2 groups and 2 subgroups. Most similar in subgroups A2 and B group was the lowest.

Keywords: rosa canina spp., RAPD marker, genetic variation, caspian climate

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Authors: Salma Maher, Ahmed Elseragy, Sally Eldeeb

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Nowadays, Urbanism and climate change lead to the rapid growth in energy consumption and the increase of using air-conditioning for cooling. In a hot climate area, there is a need for a new sustainable alternative that is more convenient for an existing situation. The Building envelope controls the heat transfer between the outside and inside the building. While the building façade is the most critical part, types of façade material play a vital role in influences of the energy demand for heating and cooling due to exposure to direct solar radiation throughout the day. Since the beginning of the twentieth century, the use of curtain walls in office buildings façades started to increase rapidly, which lead to more cooling loads in energy consumption. Integrating the living wall system in urban areas as a sustainable renovation and energy-saving method for the built environment will reduce the energy demand of buildings and will also provide environmental benefits. Also, it will balance the urban ecology and enhance urban life quality. The results show that the living wall systems reduce the internal temperature up to 4.0 °C. This research carries on an analytical study by highlighting the different types of living wall systems and verifying their thermal performance, energy-saving, and life potential on the building. These assessing criteria include the reason for using the Living wall systems in the building façade as well as the effect it has upon the surrounding environment. Finally, the paper ends with concluding the effect of using living wall systems on building. And, it suggests a system as long-lasting, and energy-efficient solution to be applied in curtain wall façades in a hot climate area.

Keywords: living wall systems, energy consumption, curtain walls, energy-saving, sustainability, urban life quality

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Authors: Pamela Del Rosario, Elisabetta Palumbo, Marzia Traverso

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The building sector plays an important role in addressing pressing environmental issues such as climate change and resource scarcity. The energy performance of buildings is considerably affected by the external envelope. In fact, a considerable proportion of the building energy demand is due to energy losses through the windows. Nevertheless, according to literature, to pay attention only to the contribution of windows to the building energy performance, i.e., their influence on energy use during building operation, could result in a partial evaluation. Hence, it is important to consider not only the building energy performance but also the environmental performance of windows, and this not only during the operational stage but along its complete life cycle. Life Cycle Assessment (LCA) according to ISO 14040:2006 and ISO 14044:2006+A1:2018 is one of the most adopted and robust methods to evaluate the environmental performance of products throughout their complete life cycle. This life-cycle based approach avoids the shift of environmental impacts of a life cycle stage to another, allowing to allocate them to the stage in which they originated and to adopt measures that optimize the environmental performance of the product. Moreover, the LCA method is widely implemented in the construction sector to assess whole buildings as well as construction products and materials. LCA is regulated by the European Standards EN 15978:2011, at the building level, and EN 15804:2012+A2:2019, at the level of construction products and materials. In this work, the environmental performance of wooden windows was assessed by implementing the LCA method and adopting primary data. More specifically, the emphasis is given to embedded and operational impacts. Furthermore, correlations are made between these environmental impacts and aspects such as type of wood and window transmittance. In the particular case of the operational impacts, special attention is set on the definition of suitable maintenance scenarios that consider the potential climate influence on the environmental impacts. For this purpose, a literature review was conducted, and expert consultation was carried out. The study underlined the variability of the embedded environmental impacts of wooden windows by considering different wood types and transmittance values. The results also highlighted the need to define appropriate maintenance scenarios for precise assessment results. It was found that both the service life and the window maintenance requirements in terms of treatment and its frequency are highly dependent not only on the wood type and its treatment during the manufacturing process but also on the weather conditions of the place where the window is installed. In particular, it became evident that maintenance-related environmental impacts were the highest for climate regions with the lowest temperatures and the greatest amount of precipitation.

Keywords: embedded impacts, environmental performance, life cycle assessment, LCA, maintenance stage, operational impacts, wooden windows

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Authors: Syed Iftikhar Hussain Shah, Vasilis Peristeras, Ioannis Magnisalis

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Data that is high in volume, velocity, veracity and comes from a variety of sources is usually generated in all sectors including the government sector. Globally public administrations are pursuing (big) data as new technology and trying to adopt a data-centric architecture for hosting and sharing data. Properly executed, big data and data analytics in the government (big) data ecosystem can be led to data-driven government and have a direct impact on the way policymakers work and citizens interact with governments. In this research paper, we conduct a systematic literature review. The main aims of this paper are to highlight essential aspects of the government (big) data ecosystem and to explore the most critical socio-technical factors that contribute to the successful implementation of government (big) data ecosystem. The essential aspects of government (big) data ecosystem include definition, data types, data lifecycle models, and actors and their roles. We also discuss the potential impact of (big) data in public administration and gaps in the government data ecosystems literature. As this is a new topic, we did not find specific articles on government (big) data ecosystem and therefore focused our research on various relevant areas like humanitarian data, open government data, scientific research data, industry data, etc.

Keywords: applications of big data, big data, big data types. big data ecosystem, critical success factors, data-driven government, egovernment, gaps in data ecosystems, government (big) data, literature review, public administration, systematic review

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Authors: F. Sahnoune, M. Madani, M. Zelmat, M. Belhamel

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Home heating and generation of domestic hot water are nowadays important items of expenditure and energy consumption. These are also a major source of pollution and emission of greenhouse gases (GHG). Algeria, like other countries of the southern shore of the Mediterranean has an enormous solar potential (more than 3000 hours of sunshine/year). This potential can be exploited in reducing GHG emissions and contribute to climate change adaptation. This work presents the environmental impact of introduction of solar heating in an individual house in Algerian climate conditions. For this purpose, we determined energy needs for heating and domestic hot water taking into account the thermic heat losses of the no isolated house. Based on these needs, sizing of the solar system was carried out. To compare the performances of solar and classic systems, we conducted also an economic evaluation what is very important for countries like Algeria where conventional energy is subsidized. The study clearly show that environmental and economic benefits are in favor of solar heating development in particular in countries where the thermal insulation of the building and energy efficiency are poorly developed.

Keywords: CO2 mitigation, solar energy, solar heating, environmental impact

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Authors: See-Yuan Cheng, Kwang-Yhee Chin, Shuhaimi Mansor

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Rear-roof spoiler is commonly used for improving the aerodynamic performance of road vehicles. This study aims to investigate the effect of yaw angle on the effectiveness of strip-type rear-roof spoiler in providing lower drag and lift coefficients of a hatchback model. A computational fluid dynamics (CFD) method was used. The numerically obtained results were compared to the experimental data for validation of the CFD method. At increasing yaw angle, both the drag and lift coefficients of the model were to increase. In addition, the effectiveness of spoiler was deteriorated. These unfavorable effects were due to the formation of longitudinal vortices around the side edges of the model that had caused the surface pressure of the model to drop. Furthermore, there were significant crossflow structures developed behind the model at larger yaw angle, which were associated with the drop in the surface pressure of the rear section of the model and cause the drag coefficient to rise.

Keywords: Ahmed model, aerodynamics, spoiler, yaw angle

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Authors: Anli Du Preez, James Bekker

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Data is currently one of the most critical and influential emerging technologies. However, the true potential of data is yet to be exploited since, currently, about 1% of generated data are ever actually analyzed for value creation. There is a data gap where data is not explored due to the lack of data analytics infrastructure and the required data analytics skills. This study developed a decision support framework for data analytics by following Jabareen’s framework development methodology. The study focused on machine learning algorithms, which is a subset of data analytics. The developed framework is designed to assist data analysts with little experience, in choosing the appropriate machine learning algorithm given the purpose of their application.

Keywords: Data analytics, Industrial engineering, Machine learning, Value creation

Procedia PDF Downloads 168