Search results for: urban travel indicators

Authors: Davaakhuu Vandannyam, Amarsaikhan Dashtseren, Oyungoo Badamdorj

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Background: Shift work and extended working hours are increasing in many industries and organization's in the world. Over a 24 hour period, the circadian clock regulates sleep/wake patterns, body temperature, hormone levels, digestion and many other functions. Depending on the time of day or night, the human body is programmed for periods of wakefulness and sleep, high and low body temperature, high and low digestive activity and so on. Shift work is highly prevalent in industrialized societies (>20%) but, when it includes night work, it has pronounced negative effects on sleep, subjective and physiological sleepiness, performance, accident risk, as well as on health outcomes such as cardiovascular disease and certain forms of cancer. Method: In this cross-sectional field study, 634 shift work and day work nurses from a plant were involved, with participation rate of 100% (634 nurses). The general health questionnaire (GHQ-28) and RLS, ESS, ISI, FSS were used to evaluate the level of insomnia, sleepiness, fatigue and restless legs syndrome, respectively. Results: As a result of research on some indicators of health risks caused from work shift, it was proven that prevalence of restless legs syndrome was at 5.5% and 25.9% are in risk of becoming sick, 42.3% are in fatigue, 3.5% in high stage of insomnia and 27.4% are sleepy on duty. Insomnia of nurses mainly affected from long-hour shift, dissatisfaction, workload, lose of focus and use of coffee. There is sleepiness lies in the workplace due to number of shifts, unsatisfactory performance and emergency calls between shifts. It has been determined that risk of sickness influenced by number of shifts in a month and long hour shift, dissatisfaction and use of coffee and divisions are causing restless legs syndrome. Conclusions: Among the nurses, it was found that the prevalence of insomnia is 31.6%, sleepiness 27.4%, fatigue 42.3%, restless legs syndrome 35% and stress 25.9%. These factors of shift work affecting health tend to go up as working hours increase and more common among shift work nurses.

Keywords: shiftwork, insomnia, sleepiness, restless

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Authors: Dalma Varga, Nora Hubayne H.

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Nowadays, among the measures taken to offset the consequences of climate change, water resources management is one of the key tools, which can include excess water management. As a result of climate change’s effects and as a result of the frequent inappropriate landuse, more and more areas are affected by the excess water inundation. Hungary is located in the deepest part of the Pannonian Basin, which is exposed to water damage – especially lowland areas that are endangered by floods or excess waters. The periodical presence of excess water creates specific habitats in a given area, which have ecological, functional, and aesthetic values. Excess water inundation affects approximately 74% of Hungary’s lowland areas, of which about 46% is also under nature protection (such as national parks, protected landscape areas, nature conservation areas, Natura 2000 sites, etc.). These data prove that areas exposed to excess water inundation – which are predominantly characterized by agricultural land uses – have an important ecological role. Other research works have confirmed the presence of numerous rare and endangered plant species in drainage canals, on grasslands exposed to excess water, and on special agricultural fields with mud vegetation. The goal of this research is to define and analyze ecosystem services of areas exposed to excess water inundation. In addition to this, it is also important to determine the quantified indicators of these areas’ natural and landscape values besides the presence of protected species and the naturalness of habitats, so all in all, to analyze the various nature protections related to excess water. As a result, a practice-orientated assessment method has been developed that provides the ecological water demand, assimilates to ecological and habitat aspects, contributes to adaptive excess water management, and last but not least, increases or maintains the share of the green infrastructure network. In this way, it also contributes to reduce and mitigate the negative effects of climate change.

Keywords: ecosystem services, landscape architecture, excess water management, green infrastructure planning

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Authors: Eva Maleviti, Evan Stamoulis

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This paper is part of a wider research project, on environmental management in aviation and aerospace industries. The core elements of this research are the level of knowledge, awareness, applicability of environmental management systems, according to employees’ perspectives. This paper focuses at employees’ level of environmental awareness. The main scope of this research is to evaluate the level of environmental awareness and the adoption of environmental management practices. The primary scope of the research is to define a method to quantify the key indicators that would improve the implementation of environmental management. The opinion of people employed in aviation industry is considered, based on the versatility of their working positions. Up to this stage, 330 respondents have participated globally in the current research. This study uses a questionnaire survey to gain an understanding of the views and attitudes of aerospace staff toward environmental management. The results are analyzed through a quantitative approach using SPSS. The statistical significance shows that the data could follow the same distribution as the distribution of the total population that the sample belongs. As of the above, the number of respondents constitutes a representative sample of the total population. A descriptive analysis is presented. According to the responses given in the survey, the data are analyzed according to the working positions and the characteristics of each position that all the respondents hold. The results demonstrate that the level of environmental awareness is immediately linked with the employees’ positions. Managerial/post holder positions, as expected have, a higher level of environmental awareness. However, the level of applicability of environmental practices by the same group is considered low. The other working groups show variability in environmental awareness, which also depends on their operating task and the applicability or not of environmental practices. Flight operations and engineering/maintenance employees, that their tasks involve higher safety considerations, there are more reluctant in applying environmental practices in their positions. In the current paper an analysis of the data collection is presented, correlating them with the working positions and responsibilities of respondents.

Keywords: environmental awareness, environmental management, sustainability, sustainable aviation

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Authors: Siyamthanda Makhwabe

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Tourism development and spatial planning within the broader spectrum of the Eastern Cape needs to be strategically integrated to give effectiveness to development planning within the province. Tourism was severely affected and limited by policies of the previous regime. Tourism development in the Eastern Cape has been identified as one of the underdeveloped sectors that have the potential to improve the province’s local economic development trajectory The proposed study reviews literature on tourism development in an urban/rural and regional context in the Eastern Cape province. The proposed study will therefore offer an in-depth literature review on issues pertaining to spatial planning, land use management policies and tourism development within the Eastern Cape using the scoping review method. The intention of the proposed study is to identify synergies between the intertwined municipalities within the Wild Coast region in order to create a tourism belt that would yield benefit from Coffee Bay to East London.

Keywords: development, Eastern Cape, policies, spatial planning, tourism

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Authors: Olga A. Burukina

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Tourism is a complex socio-economic phenomenon, partly regulated by national tourism industries. The sustainable development of tourism in a region, country or in tourist destination depends on a number of factors (political, economic, social, cultural, legal and technological), the understanding and correct interpretation of which is invariably anthropocentric. It is logical that for the successful functioning of a tour operating company, it is necessary to ensure its sustainable development. Sustainable tourism is defined as tourism that fully considers its current and future economic, social and environmental impacts, taking into account the needs of the industry, the environment and the host communities. For the business enterprise, sustainable development is defined as adopting business strategies and activities that meet the needs of the enterprise and its stakeholders today while protecting, sustaining and enhancing the human and natural resources that will be needed in the future. In addition to a systemic approach to the analysis of tourist destinations, each tourism project can and should be considered as a system characterized by a very high degree of variability, since each particular case of its implementation differs from the previous and subsequent ones, sometimes in a cardinal way. At the same time, it is important to understand that this variability is predominantly of anthropogenic nature (except for force majeure situations that are considered separately and afterwards). Knowledge management is the process of creating, sharing, using and managing the knowledge and information of an organization. It refers to a multidisciplinary approach to achieve organisational objectives by making the best use of knowledge. Knowledge management is seen as a key systems component that allows obtaining, storing, transferring, and maintaining information and knowledge in particular, in a long-term perspective. The study aims, firstly, to identify (1) the dynamic changes in the Italian travel industry in the last 5 years before the COVID19 pandemic, which can be considered the scope of force majeure circumstances, (2) the impact of the pandemic on the industry and (3) efforts required to restore it, and secondly, how project management tools can help to improve knowledge management in tour operating companies to maintain their sustainability, diminish potential risks and restore their pre-pandemic performance level as soon as possible. The pilot research is based upon a systems approach and has employed a pilot survey, semi-structured interviews, prior research analysis (aka literature review), comparative analysis, cross-case analysis, and modelling. The results obtained are very encouraging: PM tools can improve knowledge management in tour operating companies and secure the more sustainable development of the Italian tourism industry based on proper knowledge management and risk management.

Keywords: knowledge management, project management, sustainable development, tourism industr

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Authors: Anka Gorgiev, Chris Martin, Nikolaos Dimitriadis, Dimitrios V. Nikolaidis

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This paper is part of a doctoral research study aimed to identify behavioral indicators for the existence of the new marketing paradigm. Neuromarketing is becoming a growing trend in the marketing industry worldwide and it is capturing a lot of interest among the members of academia and the practitioner community. However, it is still not very clear how big of an impact neuromarketing might have in the following years. In an effort to get closer to an answer, this study investigates behavioral intentions and willingness to adopt neuromarketing and its practices by the marketing professionals, including academics, practitioners, students, researchers, experts and journal editors. The participants in the study include marketing professionals at different levels of neuromarketing fluency with residency in the United States of America and the South East Europe. The total of 19 participants participated in the interviews, all of whom belong to more than one group of marketing professionals. The authors use qualitative research approach and open-ended interview questions specifically developed to assess ideas, beliefs and opinions that marketing professionals hold towards neuromarketing. In constructing the interview questions, the authors have used the theory of planned behavior, the prototype willingness model and the technology acceptance model as a theoretical framework. Previous studies have not explicitly investigated the behavioral intentions of marketing professionals to engage in neuromarketing behavior, which is described here as a tendency to apply neuromarketing assumptions and tools in usual marketing practices. This study suggests that the marketing professionals believe that neuromarketing can contribute to the business in a positive way and outlines the main advantages and disadvantages of adopting neuromarketing as identified by the participants. In addition, the study reveals an emerging image of an exemplar company that is perceived to be using neuromarketing, including the most common characteristics and attributes. These findings are believed to be crucial in facilitating a way for neuromarketing field to have a broader impact than it currently does by recognizing and understanding the limitations that such exemplars imply and how that has an effect on the decision-making of marketing professionals.

Keywords: behavioral intentions, marketing paradigm, neuromarketing adoption, theory of planned behavior

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Authors: Edward W. Staley, Corban G. Rivera, Ashley J. Llorens

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Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains. An emerging landscape of development environments is making powerful RL techniques more accessible for a growing community of researchers. However, most existing frameworks do not directly address the problem of learning in complex operating environments, such as dense urban settings or defense-related scenarios, that incorporate distributed, heterogeneous teams of agents. To help enable AI research for this important class of applications, we introduce the AI Arena: a scalable framework with flexible abstractions for distributed multi-agent reinforcement learning. The AI Arena extends the OpenAI Gym interface to allow greater flexibility in learning control policies across multiple agents with heterogeneous learning strategies and localized views of the environment. To illustrate the utility of our framework, we present experimental results that demonstrate performance gains due to a distributed multi-agent learning approach over commonly-used RL techniques in several different learning environments.

Keywords: reinforcement learning, multi-agent, deep learning, artificial intelligence

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Authors: Emma Pope, Demos Parapanos

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Rural tourism has become more obvious and prevalent, with tourists’ increasingly seeking authentic experiences. This movement accelerated post-Covid, putting destinations in danger of reaching levels of saturation called ‘overtourism’. Whereas the phenomenon of overtourism has been frequently discussed in the urban context by academics and practitioners over recent years, it has hardly been referred to in the context of rural tourism, where perhaps it is even more difficult to manage. Rural tourism was historically considered small-scale, marked by its traditional character and by having little impact on nature and rural society. The increasing number of rural areas experiencing overtourism, however, demonstrates the need for new approaches, especially as the impacts and enablers of overtourism are context specific. Cumbria, with approximately 47 million visitors each year, and 23,000 operational enterprises, is one of these rural areas experiencing overtourism in the UK. Using the county of Cumbria as an example, this paper aims to explore better planning and management in rural destinations by clustering the area into rural and ‘urban-rural’ tourism zones. To achieve the aim, this study uses secondary data from a variety of sources to identify variables relating to visitor economy development and demand. These data include census data relating to population and employment, tourism industry-specific data including tourism revenue, visitor activities, and accommodation stock, and big data sources such as Trip Advisor and All Trails. The combination of these data sources provides a breadth of tourism-related variables. The subsequent analysis of this data draws upon various validated models. For example, tourism and hospitality employment density, territorial tourism pressure, and accommodation density. In addition to these statistical calculations, other data are utilized to further understand the context of these zones, for example, tourist services, attractions, and activities. The data was imported into ARCGIS where the density of the different variables is visualized on maps. This study aims to provide an understanding of the geographical context of visitor economy development and tourist behavior in rural areas. The findings contribute to an understanding of the spatial dynamics of tourism within the region of Cumbria through the creation of thematized maps. Different zones of tourism industry clusters are identified, which include elements relating to attractions, enterprises, infrastructure, tourism employment and economic impact. These maps visualize hot and cold spots relating to a variety of tourism contexts. It is believed that the strategy used to provide a visual overview of tourism development and demand in Cumbria could provide a strategic tool for rural areas to better plan marketing opportunities and avoid overtourism. These findings can inform future sustainability policy and destination management strategies within the areas through an understanding of the processes behind the emergence of both hot and cold spots. It may mean that attract and disperse needs to be reviewed in terms of a strategic option. In other words, to use sector or zonal policies for the individual hot or cold areas with transitional zones dependent upon local economic, social and environmental factors.

Keywords: overtourism, rural tourism, sustainable tourism, tourism planning, tourism zones

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Authors: Teklay Tesfay, Gebreyesus Brhane Tesfahunegn, Abadi Berhane, Selemawit Girmay

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Adjusting the proper sowing date of a crop at a particular location with a changing climate is an essential management option to maximize crop yield. However, determining the optimum sowing date for rainfed maize production through field experimentation requires repeated trials for many years in different weather conditions and crop management. To avoid such long-term experimentation to determine the optimum sowing date, crop models such as AquaCrop are useful. Therefore, the overall objective of this study was to evaluate the performance of AquaCrop model in simulating maize productivity under varying sowing dates. A field experiment was conducted for two consecutive cropping seasons by deploying four maize seed sowing dates in a randomized complete block design with three replications. Input data required to run this model are stored as climate, crop, soil, and management files in the AquaCrop database and adjusted through the user interface. Observed data from separate field experiments was used to calibrate and validate the model. AquaCrop model was validated for its performance in simulating the green canopy and aboveground biomass of maize for the varying sowing dates based on the calibrated parameters. Results of the present study showed that there was a good agreement (an overall R2 =, Ef= d= RMSE =) between measured and simulated values of the canopy cover and biomass yields. Considering the overall values of the statistical test indicators, the performance of the model to predict maize growth and biomass yield was successful, and so this is a valuable tool help for decision-making. Hence, this calibrated and validated model is suggested to use for determining optimum maize crop sowing date for similar climate and soil conditions to the study area, instead of conducting long-term experimentation.

Keywords: AquaCrop model, calibration, validation, simulation

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Authors: Maroua Sbiti, Karim Beddiar, Djaoued Beladjine, Romuald Perrault

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Productivity is decreasing in construction compared to the manufacturing industry. It seems that the sector is suffering from organizational problems and have low maturity regarding technological advances. High international competition due to the growing context of globalization, complex projects, and shorter deadlines increases these challenges. Field employees are more exposed to coordination problems than design officers. Execution collaboration is then a major issue that can threaten the cost, time, and quality completion of a project. Initially, this paper will try to identify field professional requirements as to address building management process weaknesses such as the unreliability of scheduling, the fickleness of monitoring and inspection processes, the inaccuracy of project’s indicators, inconsistency of building documents and the random logistic management. Subsequently, we will focus our attention on providing solutions to improve scheduling, inspection, and hours tracking processes using emerging lean tools and field mobility applications that bring new perspectives in terms of cooperation. They have shown a great ability to connect various field teams and make informations visual and accessible to planify accurately and eliminate at the source the potential defects. In addition to software as a service use, the adoption of the human resource module of the Enterprise Resource Planning system can allow a meticulous time accounting and thus make the faster decision making. The next step is to integrate external data sources received from or destined to design engineers, logisticians, and suppliers in a holistic system. Creating a monolithic system that consolidates planning, quality, procurement, and resources management modules should be our ultimate target to build the construction industry supply chain.

Keywords: lean, last planner system, field mobility applications, construction productivity

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Authors: David Gamboa, Bernardo Herrera, Karen Cacua

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Nanomaterials have been explored as alternatives to reduce particulate matter from diesel engines, which is one of the most common pollutants of the air in urban centers. However, the use of nanomaterials as additives for diesel has to overcome the instability of the dispersions to be considered viable for commercial use. In this work, functionalization of carbon nanotubes with amide groups was performed to improve the stability of these nanomaterials in a mix of 90% petroleum diesel and 10% palm oil biodiesel (B10) in concentrations of 50 and 100 ppm. The resulting nano fuel was used as the fuel for a stationary internal combustion engine, where the particulate matter, NOx, and CO were measured. The results showed that the use of amide groups significantly enhances the time for the carbon nanotubes to remain suspended in the fuel, and at the same time, these nanomaterials helped to reduce the particulate matter and NOx emissions. However, the CO emissions with nano fuel were higher than those ones with the combustion of B10. These results suggest that carbon nanotubes have thermal and catalytic effects on the combustion of B10.

Keywords: carbon nanotubes, diesel, internal combustion engine, particulate matter

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Authors: Maja Martinovic, Valentina Zarkovic, Hrvoje Maljak

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Europe is one of the most popular tourist destinations in the world, in which tourism occupies a significant place among the most relevant economic activities, and this applies to the Republic of Croatia as well. Based on this study, the authors intended to encourage and support the creation of an effective tourism policy in Croatia that would be based on the profiling of certain target groups. Another objective was to compare the results obtained from the customer analysis with the market analysis of the tourism industry in Croatia. The objective is to adapt the current tourist offer according to the identified needs and expectations of a particular tourist group in order to increase the attractiveness of Croatia as a tourist destination and motivate greater attendance of the targeted tourist groups. The current research was oriented towards the Russian market as the target group. Therefore, the authors wanted to encourage a discussion on how to attract more Russian guests. Consequently, the intention of the research was a detailed analysis of Russian tourists, in order to gain a better understanding of their travelling motives and tendencies. Furthermore, attention was paid to the expectations of Russian customers and to compare them with the Croatian tourist offer, and to determine whether there is a possibility for an overlap. The method used to obtain the information required was a survey conducted among Russian citizens about their travelling habits. The research was carried out on the basis of 166 participants of different age, gender, profession and income group. The sampling and distribution of the survey took place between May and July 2016. The results provided from the research indicate that Croatian tourism has certain unrealized potential considering the popularization of Croatia as a tourist destination, and there is a capacity for increasing the revenues within the group of Russian tourists. Such a conclusion is based on the fact that the Croatian tourist offer and the preferences of the Russian guests are compatible, i.e. they overlap in many aspects. The results demonstrate that beautiful nature, cultural and historical heritage as well as the sun and sea, play a leading role in attracting more Russian tourists. It is precisely these elements that form the three pillars of the Croatian tourist offer. On the other hand, the profiling revealed that the most desirable destinations for the Russian guests are Italy and Spain, both of which provide the same main tourist attractions as Croatia. Therefore, the focus of the strategic ideas given in the paper shifted to other tourism segments, such as type of accommodation, sales channels, travel motives, additional offer and seasonality etc., in order to gain advantage in the Russian market, the Mediterranean region and tourism in general. The purpose of the research is to serve as a foundation for analysing the attractiveness of the other tourist destinations in the Russian market, as well as to be a general basis for a more detailed profiling of the various specific target groups of the Russian and other tourist groups.

Keywords: Croatia, Russian market, target groups, tourism, tourist destination

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Authors: M. Meftahi, M. Hoseinzadeh, S. A. Naeini

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Selection of soil bearing capacity is an important issue that should be investigated under different conditions. The bearing capacity of foundation around of soil slope is based on the active and passive forces. On the other hand, due to extension of urban structures, it is inevitable to put the foundations together. Concerning the two cases mentioned above, investigating the behavior of adjacent foundations which are constructed besides soil slope is essential. It should be noted that, according to the conditions, the bearing capacity of adjacent foundations can be less or more than mat foundations. Also, soil reinforcement increases the bearing capacity of adjacent foundations, and the amount of its increase depends on the distance between foundations. In this research, based on numerical studies, a method is presented for evaluating ultimate bearing capacity of adjacent foundations at different intervals. In the present study, the effect of foundation width, the center to center distance of adjacent foundations and reinforced soil has been investigated on the bearing capacity of adjacent foundations beside soil slope. The results indicate that, due to interference of failure surfaces created under foundation, it depends on their intervals and the ultimate bearing capacity of foundation varies.

Keywords: adjacent foundation, bearing capacity, reinforcements, settlement, numerical analysis

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Authors: Victoria Bila, Iryna Ventskivska, Oleksandra Zahorodnia

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The goal of the study: To study the distribution of patients of the Kiyv Perinatal Center according to the Robson system and compare it with world data. Materials and methods: a comparison of the distribution of patients of Kiyv Perinatal center according to the Robson system for 2 periods - the first quarter of 2019 and 2020. For each group, 3 indicators were analyzed - the share of this group in the overall structure of patients of the Perinatal Center for the reporting period, the frequency of abdominal delivery in this group, as well as the contribution of this group to the total number of abdominal delivery. Obtained data were compared with those of the WHO in the guidelines for the implementation of the Robson system in 2017. Results and its discussion: The distribution of patients of the Perinatal Center into groups in the Robson classification is not much different from that recommended by the author. So, among all women, patients of group 1 dominate; this indicator does not change in dynamics. A slight increase in the share of group 2 (6.7% in 2019 and 9.3% - 2020) was due to an increase in the number of labor induction. At the same time, the number of patients of groups 1 and 2 in the Perinatal Center is greater than in the world population, which is determined by the hospitalization of primiparous women with reproductive losses in the past. The Perinatal Center is distinguished from the world population and the proportion of women of group 5 - it was 5.4%, in the world - 7.6%. The frequency of caesarean section in the Perinatal Center is within limits typical for most countries (20.5-20.8%). Moreover, the dominant groups in the structure of caesarean sections are group 5 (21-23.3%) and group 2 (21.9-22.9%), which are the reserve for reducing the number of abdominal delivery. In group 2, certain results have already been achieved in this matter - the frequency of cesarean section in 2019 here amounted to 67.8%, in the first quarter of 2020 - 51.6%. This happened due to a change in the leading method of induction of labor. Thus, the Robson system is a convenient and affordable tool for assessing the structure of caesarean sections. The analysis showed that, in general, the structure of caesarean sections in the Perinatal Center is close to world data, and the identified deviations have explanations related to the specialization of the Center.

Keywords: cesarian section, Robson system, Kyiv Perinatal Center, labor induction

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Authors: Martina Perinkova, Lenka Kolarcikova, Marketa Twrda

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Brownfields are one of the most important problems that must be solved by today's cities. The topic of this article is description of developing a comprehensive transformation of post-industrial area of the former iron factory national cultural heritage Lower Vítkovice. City of Ostrava used to be industrial superpower of the Czechoslovak Republic, especially in the area of coal mining and iron production, after declining industrial production and mining in the 80s left many unused areas of former factories generally brownfields and backfields. Since the late 90s we are observing how the city officials or private entities seeking to remedy this situation. Regeneration of brownfields is a very expensive and long-term process. The area is now rebuilt for tourists and residents of the city in the entertainment, cultural, and social center. It was necessary do the reconstruction of the industrial monuments. Equally important was the construction of new buildings, which helped reusing of the entire complex. This is a unique example of transformation of technical monuments and completion of necessary new objects, so that the area could start working again and reintegrate back into the urban system.

Keywords: brown fields, conversion, historical and industrial buildings, reconstruction

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Authors: Ignatius Madu

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The study aims at assessing the environmental and socioeconomic determinants of climate change resilience in rural Nigeria. This is necessary because researches and development efforts on building climate change resilience of rural areas in developing countries are usually made without the knowledge of the impacts of the inherent rural characteristics that determine resilient capacities of the households. This has, in many cases, led to costly mistakes, delayed responses, inaccurate outcomes, and other difficulties. Consequently, this assessment becomes crucial not only to policymakers and people living in risk-prone environments in rural areas but also to fill the research gap. To achieve the aim, secondary data were obtained from the Annual Abstract of Statistics 2017, LSMS-Integrated Surveys on Agriculture and General Household Survey Panel 2015/2016, and National Agriculture Sample Survey (NASS), 2010/2011.Resilience was calculated by weighting and adding the adaptive, absorptive and anticipatory measures of households variables aggregated at state levels and then regressed against rural environmental and socioeconomic characteristics influencing it. From the regression, the coefficients of the variables were used to compute the impacts of the variables using the Stochastic Regression of Impacts on Population, Affluence and Technology (STIRPAT) Model. The results showed that the northern States are generally low in resilient indices and are impacted less by the development indicators. The major determining factors are percentage of non-poor, environmental protection, road transport development, landholding, agricultural input, population density, dependency ratio (inverse), household asserts, education and maternal care. The paper concludes that any effort to a successful resilient building in rural areas of the country should first address these key factors that enhance rural development and wellbeing since it is better to take action before shocks take place.

Keywords: climate change resilience; spatial impacts; STIRPAT model; Nigeria

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Authors: D. Tedesco, G. Feletti, P. Trucco

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The present study aims to develop a Decision Support System (DSS) to support the operational decision of the Emergency Medical Service (EMS) regarding the assignment of medical emergency requests to Emergency Departments (ED). In the literature, this problem is also known as “hospital selection” and concerns the definition of policies for the selection of the ED to which patients who require further treatment are transported by ambulance. The employed research methodology consists of the first phase of revision of the technical-scientific literature concerning DSSs to support the EMS management and, in particular, the hospital selection decision. From the literature analysis, it emerged that current studies are mainly focused on the EMS phases related to the ambulance service and consider a process that ends when the ambulance is available after completing a request. Therefore, all the ED-related issues are excluded and considered as part of a separate process. Indeed, the most studied hospital selection policy turned out to be proximity, thus allowing to minimize the transport time and release the ambulance in the shortest possible time. The purpose of the present study consists in developing an optimization model for assigning medical emergency requests to the EDs, considering information relating to the subsequent phases of the process, such as the case-mix, the expected service throughput times, and the operational capacity of different EDs in hospitals. To this end, a Discrete Event Simulation (DES) model was created to evaluate different hospital selection policies. Therefore, the next steps of the research consisted of the development of a general simulation architecture, its implementation in the AnyLogic software and its validation on a realistic dataset. The hospital selection policy that produced the best results was the minimization of the Time To Provider (TTP), considered as the time from the beginning of the ambulance journey to the ED at the beginning of the clinical evaluation by the doctor. Finally, two approaches were further compared: a static approach, which is based on a retrospective estimate of the TTP, and a dynamic approach, which is based on a predictive estimate of the TTP determined with a constantly updated Winters model. Findings reveal that considering the minimization of TTP as a hospital selection policy raises several benefits. It allows to significantly reduce service throughput times in the ED with a minimum increase in travel time. Furthermore, an immediate view of the saturation state of the ED is produced and the case-mix present in the ED structures (i.e., the different triage codes) is considered, as different severity codes correspond to different service throughput times. Besides, the use of a predictive approach is certainly more reliable in terms of TTP estimation than a retrospective approach but entails a more difficult application. These considerations can support decision-makers in introducing different hospital selection policies to enhance EMSs performance.

Keywords: discrete event simulation, emergency medical services, forecast model, hospital selection

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Authors: Getaneh Berie Tarekegn

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Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.

Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles

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Authors: R. Odoh, M. S. Dauda, E. A. Kamba, N. C. Igwemmar

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Honey and honey trade is an important economic activity for many tropical rural and urban areas worldwide. In West Africa and other part of the world, honey and honey products holds high socio–cultural, religious, medicinal and traditional values. Therefore, to maximize benefits or to enhance profit, a variety of components are added to the raw, fresh and unprocessed honey, introducing the possibility of heavy metals contaminants. Therefore the honey sold in various places, markets and shops in some states in Northern Nigeria (Benue, Nassarawa and Taraba) including Abuja FCT, in Nigeria was analyzed to determine the level of heavy metals (Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn). All the honey samples contain heavy metals. The results ranged from 0.028–0.070, 0.023–0.058, 0.042–0.092, 4.231–8.589, 8.115–14.892, 0.078–0.922, 0.044–0.092, 0.041–0.087 and 18.234–28.654 μg/L for Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn respectively. The mean concentration (μg/L) of the heavy metals Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn of the regularly marketed honey is significantly higher than the mean concentration observed in raw, fresh and unprocessed honey. However, continued consumption of honey with high heavy metal content might lead to exposure to chronic heavy metal poisoning.

Keywords: honey, health, mineral profile adulteration, contamination

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Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl

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Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.

Keywords: average run length (ARL), bernoulli cusum (BC) chart, beta binomial posterior predictive (BBPP) distribution, clinical indicator (CI), healthcare organization (HCO), highest posterior density (HPD) interval

Procedia PDF Downloads 189

Authors: Velimir "monty" Vesselinov, Trais Kliplhuis, Hope Jasperson

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Artificial intelligence (AI) is a powerful tool in the geothermal energy sector, aiding in both exploration and utilization. Identifying promising geothermal sites can be challenging due to limited surface indicators and the need for expensive drilling to confirm subsurface resources. Geothermal reservoirs can be located deep underground and exhibit complex geological structures, making traditional exploration methods time-consuming and imprecise. AI algorithms can analyze vast datasets of geological, geophysical, and remote sensing data, including satellite imagery, seismic surveys, geochemistry, geology, etc. Machine learning algorithms can identify subtle patterns and relationships within this data, potentially revealing hidden geothermal potential in areas previously overlooked. To address these challenges, a SIML (Science-Informed Machine Learning) technology has been developed. SIML methods are different from traditional ML techniques. In both cases, the ML models are trained to predict the spatial distribution of an output (e.g., pressure, temperature, heat flux) based on a series of inputs (e.g., permeability, porosity, etc.). The traditional ML (a) relies on deep and wide neural networks (NNs) based on simple algebraic mappings to represent complex processes. In contrast, the SIML neurons incorporate complex mappings (including constitutive relationships and physics/chemistry models). This results in ML models that have a physical meaning and satisfy physics laws and constraints. The prototype of the developed software, called GeoTGO, is accessible through the cloud. Our software prototype demonstrates how different data sources can be made available for processing, executed demonstrative SIML analyses, and presents the results in a table and graphic form.

Keywords: science-informed machine learning, artificial inteligence, exploration, utilization, hidden geothermal

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Authors: Mohan Kotamrazu

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Tall buildings block and divert strong upper level winds to the ground. These high velocity winds many a time create adverse wind effects at ground level which can be uncomfortable and even compromise the safety of pedestrians and people who frequent the spaces in the vicinity of tall buildings. Discomfort can be experienced around the entrances and corners of tall buildings. Activities such as strolling or sitting in a park, waiting for a bus near a tall building can become highly unpleasant. For the elderly unpleasant conditions can also become dangerous leading to accidents and injuries. Today there is a growing concern among architects, planners and urban designers about the wind environment in the vicinity of tall building. Regulating authorities insist on wind tunnel testing of tall buildings in cities such as Wellington, Auckland, Boston, San Francisco, etc. prior to granting permission for their construction The present paper examines the different ways that tall buildings can induce strong winds at pedestrian level and their impact on people who frequent the spaces around tall buildings.

Keywords: tall buildings, wind effects, wind comfort, wind safety

Procedia PDF Downloads 355

Authors: Kevin Potoczny, Katsuichiro Goda

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The St. Lawrence lowlands extend from Ottawa to Quebec City and are known for large deposits of sensitive Leda clay. Leda clay deposits are responsible for many large landslides, such as the 1993 Lemieux and 2010 St. Jude (4 fatalities) landslides. Due to the large extent and sensitivity of Leda clay, regional hazard analysis for landslides is an important tool in risk management. A 2018 regional study by Farzam et al. on the susceptibility of Leda clay slopes to landslide hazard uses 1 arc second topographical data. A qualitative method known as Hazus is used to estimate susceptibility by checking for various criteria in a location and determine a susceptibility rating on a scale of 0 (no susceptibility) to 10 (very high susceptibility). These criteria are slope angle, geological group, soil wetness, and distance from waterbodies. Given the flat nature of St. Lawrence lowlands, the current assessment fails to capture local slopes, such as the St. Jude site. Additionally, the data did not allow one to analyze failure planes accurately. This study majorly improves the analysis performed by Farzam et al. in two aspects. First, regional assessment with high resolution data allows for identification of local locations that may have been previously identified as low susceptibility. This then provides the opportunity to conduct a more refined analysis on the failure plane of the slope. Slopes derived from 1 arc second data are relatively gentle (0-10 degrees) across the region; however, the 1- and 2-meter resolution 2022 HRDEM provided by NRCAN shows that short, steep slopes are present. At a regional level, 1 arc second data can underestimate the susceptibility of short, steep slopes, which can be dangerous as Leda clay landslides behave retrogressively and travel upwards into flatter terrain. At the location of the St. Jude landslide, slope differences are significant. 1 arc second data shows a maximum slope of 12.80 degrees and a mean slope of 4.72 degrees, while the HRDEM data shows a maximum slope of 56.67 degrees and a mean slope of 10.72 degrees. This equates to a difference of three susceptibility levels when the soil is dry and one susceptibility level when wet. The use of GIS software is used to create a regional susceptibility map across the St. Lawrence lowlands at 1- and 2-meter resolutions. Failure planes are necessary to differentiate between small and large landslides, which have so far been ignored in regional analysis. Leda clay failures can only retrogress as far as their failure planes, so the regional analysis must be able to transition smoothly into a more robust local analysis. It is expected that slopes within the region, once previously assessed at low susceptibility scores, contain local areas of high susceptibility. The goal is to create opportunities for local failure plane analysis to be undertaken, which has not been possible before. Due to the low resolution of previous regional analyses, any slope near a waterbody could be considered hazardous. However, high-resolution regional analysis would allow for more precise determination of hazard sites.

Keywords: hazus, high-resolution DEM, leda clay, regional analysis, susceptibility

Procedia PDF Downloads 55

Authors: Li-Fang CHou, Chun-Jung Tseng, Sung-Chun Tsai

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Zhong-Yong represents unique values and cognitive beliefs of Chinese culture. Zhong-Yong thinking emphasizes (a) holistic thinking and perspective taking, (b) tolerance of contradictions, and (c) pursuance of a person’s interpersonal and inner harmony. With a unique way of naïve dialectical thinking based on Chinese culture, previous studies have found that people with higher Zhong-Yong thinking have more cognitive resources and resilience to make decision for dilemmas and cope stresses. Creativity is defined as the behavior to create novel and value products and viewed as the most important capital for individuals and enterprises. However, the relationship between Zhong-Yong thinking and creativity is still remaining to be unexplored. Three studies were conducted to explore the effects of Zhong-Yong thinking on creativity. In Study1, with 87 undergraduate students from a university in southern Taiwan as participants, we used questionnaire to measure Zhong-Yong thinking and processed creative task (unusual uses task) to get indicators of fluency and flexibility. After controlling background and openness to experience of Big five, the results showed that Zhong-Yong thinking had significant positive effects on fluency and flexibility. In Study 2, 97 undergraduate students were recruited to do Zhong-Yong thinking task and creative task. The result showed that, compared with control group, the participants had higher creative performance after being primed with Zhong-Yong thinking. In Study 3, we adopted questionnaire survey and took 397 employees from private enterprises in Taiwan as sample. Besides the main effects of Zhong-Yong thinking, the moderating effects on the relationship between leadership behavior and employee’s creative performance were also investigated. We found that (a) Zhong-Yong thinking was positively associated to creative performance; (b) Zhong-Yong thinking strengthened the positive effects of transformational and authoritative leadership on creative performance. Finally, the implications of theory/practice and limitations/future directions were also discussed.

Keywords: Zhong-Yong thinking, creativity and creative performance, unusual uses task, transformational leadership, authoritative leadership

Procedia PDF Downloads 556

Authors: J. Urban, Á. S. Botella, L. E. Robaina, A. Bárta, P. Souček, P. Císař, Š. Papáček, L. M. Domínguez

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Skin coloration in fish is of great physiological, behavioral and ecological importance and can be considered as an index of animal welfare in aquaculture as well as an important quality factor in the retail value. Currently, in order to compare color in animals fed on different diets, biochemical analysis, and colorimetry of fished, mildly anesthetized or dead body, are very accurate and meaningful measurements. The noninvasive method using digital images of the fish body was developed as a standalone application. This application deals with the computation burden and memory consumption of large input files, optimizing piece wise processing and analysis with the memory/computation time ratio. For the comparison of color distributions of various experiments and different color spaces (RGB, CIE L*a*b*) the comparable semi-equidistant binning of multi channels representation is introduced. It is derived from the knowledge of quantization levels and Freedman-Diaconis rule. The color calibrations and camera responsivity function were necessary part of the measurement process.

Keywords: color distribution, fish skin color, piecewise transformation, object to background segmentation

Procedia PDF Downloads 242

Authors: Tomasz Zarebski

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A very important element of the education system is its evaluation procedure. Each education system should be systematically evaluated and improved. Among the criteria subject to evaluation, attention should be paid to the following: structure of the study programme, implementation of the study programme, admission to studies, verification of learning outcomes achievement by students, giving credit for individual semesters and years, and awarding diplomas, competence, experience, qualifications and the number of staff providing education, staff development, and in-service training, education infrastructure, cooperation with social and economic stakeholders on the development, conditions for and methods of improving the internationalisation of education provided as part of the degree programme, supporting learning, social, academic or professional development of students and their entry on the labour market, public access to information about the study programme and quality assurance policy. Concerning the assessment process and the individual assessment indicators, the participation of students in these processes is essential. The purpose of this paper is to analyse the rules of student participation in accreditation processes on the example of individual countries in Europe. The rules of students' participation in the work of accreditation committees and their influence on the final grade of the committee were analysed. Most of the higher education institutions follow similar rules for accreditation. The general model gives the individual institution freedom to organize its own quality assurance, as long as the system lives up to the criteria for quality and relevance laid down in the particular provisions. This point also applies to students. The regulations of the following countries were examined in the legal-comparative aspect: Poland (Polish Accreditation Committee), Denmark (The Danish Accreditation Institution), France (High Council for the Evaluation of Research and Higher Education), Germany (Agency for Quality Assurance through Accreditation of Study Programmes) and Italy (National Agency for the Evaluation of Universities and Research Institutes).

Keywords: accreditation, student, study programme, quality assurance in higher education

Procedia PDF Downloads 147

Authors: Baishali Deb, Hari Om Pandey, Shrilla Elangbam, Mukesh Singh, Ayon Tarafdar, A. K. S. Tomar, A. K. Pandey, Triveni Dutt

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The goal of the present investigation was to determine the impact of social stress on behavioural characteristics, physiological responses, and haemato-biochemical indicators under various social environments in Tharparkar cattle. Serum cortisol and faecal cortisol metabolites analysis were used to determine the stress level of Tharparkar cattle. Social isolation and social mixing were the two different social circumstances used to evaluate the animals. In both the experiments i.e., social isolation and social mixing, the lying period of animals decreased significantly (p<0.05) while standing period significantly (p<0.05) increased. Frequency and duration of activities like idling, walking, exploration, oral manipulation, and elimination increased significantly (p<0.05) in Tharparkar cattle after being subjected to social isolation and social mixing. Time spent in grooming (self-grooming and allo-grooming) in respect to social isolation significantly increased during isolation and post-reunion, whereas there was a significant (p<0.05) decline in the grooming behaviour especially allo-grooming during mixing of the animals. Feeding and rumination time also decreased significantly (p<0.05) in animals during both the experiments. Physiological parameters such as respiration rate, heart rate and pulse rate increased during the treatment periods. There was no significant difference in the haematological parameters for both the experiments. There was significant (p<0.05) increase in serum cortisol and faecal cortisol metabolites (FCM) concentration in animals subjected to social stress. Therefore, it can be concluded that social stress strongly impacts the behaviour and physiological parameters of the animals, causing stress and nervousness, proving that social stress is a valid psychological stress in animals. The higher concentration of FCM in Tharparkar cattle subjected to social stress, further supported by higher serum cortisol and behaviour manifestations, suggest that FCM could be used to assess stress response as a non-invasive method.

Keywords: social stress, fecal cortisol metabolites, non-invasive, animal welfare, behaviour

Procedia PDF Downloads 90

Authors: Carolina Mayen Huerta, Clara Ivanescu, Paloma Marcos

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Due to their unique geographic challenges and the imperative to combat climate change, Small Island Developing States (SIDS) are experiencing rapid growth in the renewable energy (RE) sector. However, women's representation in formal employment within this burgeoning field remains significantly lower than their male counterparts. Conventional methodologies often overlook critical geographic data that influence women's job prospects. To address this gap, this paper introduces a Multicriteria Evaluation (MCE) framework designed to identify spatially enabling environments and restrictions affecting women's access to formal employment and business opportunities in the SIDS' RE sector. The proposed MCE framework comprises 24 key factors categorized into four dimensions: Individual, Contextual, Accessibility, and Place Characterization. "Individual factors" encompass personal attributes influencing women's career development, including caregiving responsibilities, exposure to domestic violence, and disparities in education. "Contextual factors" pertain to the legal and policy environment, influencing workplace gender discrimination, financial autonomy, and overall gender empowerment. "Accessibility factors" evaluate women's day-to-day mobility, considering travel patterns, access to public transport, educational facilities, RE job opportunities, healthcare facilities, and financial services. Finally, "Place Characterization factors" enclose attributes of geographical locations or environments. This dimension includes walkability, public transport availability, safety, electricity access, digital inclusion, fragility, conflict, violence, water and sanitation, and climatic factors in specific regions. The analytical framework proposed in this paper incorporates a spatial methodology to visualize regions within countries where conducive environments for women to access RE jobs exist. In areas where these environments are absent, the methodology serves as a decision-making tool to reinforce critical factors, such as transportation, education, and internet access, which currently hinder access to employment opportunities. This approach is designed to equip policymakers and institutions with data-driven insights, enabling them to make evidence-based decisions that consider the geographic dimensions of disparity. These insights, in turn, can help ensure the efficient allocation of resources to achieve gender equity objectives.

Keywords: gender, women, spatial analysis, renewable energy, access

Procedia PDF Downloads 44

Authors: Carolina Mayen Huerta, Clara Ivanescu, Paloma Marcos

Abstract:

Due to their unique geographic challenges and the imperative to combat climate change, Small Island Developing States (SIDS) are experiencing rapid growth in the renewable energy (RE) sector. However, women's representation in formal employment within this burgeoning field remains significantly lower than their male counterparts. Conventional methodologies often overlook critical geographic data that influence women's job prospects. To address this gap, this paper introduces a Multicriteria Evaluation (MCE) framework designed to identify spatially enabling environments and restrictions affecting women's access to formal employment and business opportunities in the SIDS' RE sector. The proposed MCE framework comprises 24 key factors categorized into four dimensions: Individual, Contextual, Accessibility, and Place Characterization. "Individual factors" encompass personal attributes influencing women's career development, including caregiving responsibilities, exposure to domestic violence, and disparities in education. "Contextual factors" pertain to the legal and policy environment, influencing workplace gender discrimination, financial autonomy, and overall gender empowerment. "Accessibility factors" evaluate women's day-to-day mobility, considering travel patterns, access to public transport, educational facilities, RE job opportunities, healthcare facilities, and financial services. Finally, "Place Characterization factors" enclose attributes of geographical locations or environments. This dimension includes walkability, public transport availability, safety, electricity access, digital inclusion, fragility, conflict, violence, water and sanitation, and climatic factors in specific regions. The analytical framework proposed in this paper incorporates a spatial methodology to visualize regions within countries where conducive environments for women to access RE jobs exist. In areas where these environments are absent, the methodology serves as a decision-making tool to reinforce critical factors, such as transportation, education, and internet access, which currently hinder access to employment opportunities. This approach is designed to equip policymakers and institutions with data-driven insights, enabling them to make evidence-based decisions that consider the geographic dimensions of disparity. These insights, in turn, can help ensure the efficient allocation of resources to achieve gender equity objectives.

Keywords: gender, women, spatial analysis, renewable energy, access

Procedia PDF Downloads 58

Authors: Luis Castiella, Mariano Rueda, Catalina Palacio

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The world’s rapid urbanisation represents an excellent opportunity to implement initiatives that are oriented towards a country’s general development. However, this phenomenon has created considerable pressure on current urban models, pushing them nearer to a crisis. As a result, several factors usually associated with underdevelopment have been steadily rising. Moreover, actions taken by public authorities have not been able to keep up with the speed of urbanisation, which has impeded them from meeting the demands of society, responding with reactionary policies instead of with coordinated, organised efforts. In contrast, the concept of a Smart City which emerged around two decades ago, in principle, represents a city that utilises innovative technologies to remedy the everyday issues of the citizen, empowering them with the newest available technology and information. This concept has come to adopt a wider meaning, including human and social capital, as well as productivity, economic growth, quality of life, environment and participative governance. These developments have also disrupted the management of institutions such as academia, which have become key in generating scientific advancements that can solve pressing problems, and in forming a specialised class that is able to follow up on these breakthroughs. In this light, the Ministry of Modernisation of the Argentinian Nation has created a model that is rooted in the concept of a ‘Smart City’. This effort considered all the dimensions that are at play in an urban environment, with careful monitoring of each sub-dimensions in order to establish the government’s priorities and improving the effectiveness of its operations. In an attempt to ameliorate the overall efficiency of the country’s economic and social development, these focused initiatives have also encouraged citizen participation and the cooperation of the private sector: replacing short-sighted policies with some that are coherent and organised. This process was developed gradually. The first stage consisted in building the model’s structure; the second, at applying the method created on specific case studies and verifying that the mechanisms used respected the desired technical and social aspects. Finally, the third stage consists in the repetition and subsequent comparison of this experiment in order to measure the effects on the ‘treatment group’ over time. The first trial was conducted on 717 municipalities and evaluated the dimension of Governance. Results showed that levels of governmental maturity varied sharply with relation to size: cities with less than 150.000 people had a strikingly lower level of governmental maturity than cities with more than 150.000 people. With the help of this analysis, some important trends and target population were made apparent, which enabled the public administration to focus its efforts and increase its probability of being successful. It also permitted to cut costs, time, and create a dynamic framework in tune with the population’s demands, improving quality of life with sustained efforts to develop social and economic conditions within the territorial structure.

Keywords: composite index, comprehensive model, smart cities, strategic framework

Procedia PDF Downloads 162