Search results for: academic speed and accuracy

Authors: Richard Sogah

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The significance of transport infrastructure investments for economic growth and development has been central to the World Bank’s strategy for poverty reduction. Among the conventional surface transport infrastructures, road infrastructure is significant in facilitating the movement of human capital goods and services. When transport projects (i.e., roads, super-highways) are implemented, they come along with some negative social values (costs), such as increased noise and air pollution for local residents living near these facilities, displaced individuals, etc. However, these projects also facilitate better utilization of existing capital stock and generate other observable benefits that can be easily quantified. For example, the improvement or construction of roads creates employment, stimulates revenue generation (toll), reduces vehicle operating costs and accidents, increases accessibility, trade expansion, safety improvement, etc. Aside from these benefits, travel time savings (TTSs) which are the major economic benefits of urban and inter-urban transport projects and therefore integral in the economic assessment of transport projects, are often overlooked and omitted when estimating the benefits of transport projects, especially in developing countries. The absence of current and reliable domestic travel data and the inability of replicated models from the developed world to capture the actual value of travel time savings due to the large unemployment, underemployment, and other labor-induced distortions has contributed to the failure to assign value to travel time savings when estimating the benefits of transport schemes in developing countries. This omission of the value of travel time savings from the benefits of transport projects in developing countries poses problems for investors and stakeholders to either accept or dismiss projects based on schemes that favor reduced vehicular operating costs and other parameters rather than those that ease congestion, increase average speed, facilitate walking and handloading, and thus save travel time. Given the complex reality in the estimation of the value of travel time savings and the presence of widespread informal labour activities in Sub-Saharan Africa, we construct a “nationally ranked distribution of time values” and estimate the value of travel time savings based on the area beneath the distribution. Compared with other approaches, our method captures both formal sector workers and individuals/people who work outside the formal sector and hence changes in their time allocation occur in the informal economy and household production activities. The dataset for the estimations is sourced from the World Bank, the International Labour Organization, etc.

Keywords: road infrastructure, transport projects, travel time savings, congestion, Sub-Sahara Africa

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Authors: Songdi Li, Louise Spry, Tony Woodall

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Nowadays, Corporate Social responsibility (CSR) is becoming a buzz word, and more and more academics are putting efforts on CSR studies. It is believed that CSR could influence Corporate Reputation (CR), and they hold a favourable view that CSR leads to a positive CR. To be specific, the CSR related activities in the reputational context have been regarded as ways that associate to excellent financial performance, value creation, etc. Also, it is argued that CSR and CR are two sides of one coin; hence, to some extent, doing CSR is equal to establishing a good reputation. Still, there is no consensus of the CSR-CR relationship in the literature; thus, a systematic literature review is highly in need. This research conducts a systematic literature review with both bibliometric and content analysis. Data are selected from English language sources, and academic journal articles only, then, keyword combinations are applied to identify relevant sources. Data from Scopus and WoS are gathered for bibliometric analysis. Scopus search results were saved in RIS and CSV formats, and Web of Science (WoS) data were saved in TXT format and CSV formats in order to process data in the Bibexcel software for further analysis which later will be visualised by the software VOSviewer. Also, content analysis was applied to analyse the data clusters and the key articles. In terms of the topic of CSR-CR, this literature review with bibliometric analysis has made four achievements. First, this paper has developed a systematic study which quantitatively depicts the knowledge structure of CSR and CR by identifying terms closely related to CSR-CR (such as ‘corporate governance’) and clustering subtopics emerged in co-citation analysis. Second, content analysis is performed to acquire insight on the findings of bibliometric analysis in the discussion section. And it highlights some insightful implications for the future research agenda, for example, a psychological link between CSR-CR is identified from the result; also, emerging economies and qualitative research methods are new elements emerged in the CSR-CR big picture. Third, a multidisciplinary perspective presents through the whole bibliometric analysis mapping and co-word and co-citation analysis; hence, this work builds a structure of interdisciplinary perspective which potentially leads to an integrated conceptual framework in the future. Finally, Scopus and WoS are compared and contrasted in this paper; as a result, Scopus which has more depth and comprehensive data is suggested as a tool for future bibliometric analysis studies. Overall, this paper has fulfilled its initial purposes and contributed to the literature. To the author’s best knowledge, this paper conducted the first literature review of CSR-CR researches that applied both bibliometric analysis and content analysis; therefore, this paper achieves its methodological originality. And this dual approach brings advantages of carrying out a comprehensive and semantic exploration in the area of CSR-CR in a scientific and realistic method. Admittedly, its work might exist subjective bias in terms of search terms selection and paper selection; hence triangulation could reduce the subjective bias to some degree.

Keywords: corporate social responsibility, corporate reputation, bibliometric analysis, software program

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Authors: Geetanjali Gill

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International non-governmental organizations (INGOs) and development assistance donors have been implementing education projects in Sub-Saharan Africa and the global South that respond to gender-based inequities and that attempt to transform socio-cultural norms for greater gender equality in schools and communities. These efforts are in line with the United Nations Sustainable Development Goal number four, quality education, and goal number five, gender equality. Some INGOs and donors have also championed the use of play-based pedagogies for improved and more gender equal education outcomes. The study used the qualitative methods of life history interviews and focus groups to gauge social norm change amongst male and female adolescents, families, and teachers in primary schools that have been using gender-responsive play-based pedagogies in Rwanda, Ghana, and Mozambique. School administrators and project managers from the INGO Right to Play International were consulted in the selection of two primary schools per country (in both rural and urban contexts), as well as the selection of ten male and ten female students in grades four to six in each school, using specific parameters of social norm adherence. The parents (or guardians) and grandparents of four male and four female students in each school who were determined to be ‘outliers’ in their adherence to social norms were also interviewed. Additionally, sex-specific focus groups were held with thirty-six teachers. The study found that gender-responsive play-based pedagogies positively impactedsocio-cultural norms that shape gender relations amongst adolescents, their families, and teachers. Female and male students who spoke about their beliefs about gender equality in the roles and educational and career aspirations of men/boys and women/girls made linkages to the play-based pedagogies and approaches used by their teachers. Also, the parents and grandparents of these students were aware of generational differences in gender norms, and many were accepting of changed gender norms. Teachers who were effectively implementing gender-responsive play-based pedagogies in their classrooms spoke about changes to their own gender norms and how they were able to influence the gender norms of parents and community members. Life history interviews were found to be well-suited for the examination of changes to socio-cultural norms and gender relations. However, an appropriate framing of questions and topics specific to each target group was instrumental for the collection of data on socio-cultural norms and gender. The findings of this study can spur further academic inquiry of linkages between gender norms and education outcomes. The findings are also relevant for the work of INGOs and donors in the global South and for the development of gender-responsive education policies and programs.

Keywords: education, gender equality, ghana, international development, life histories, mozambique, rwanda, socio-cultural norms, sub-saharan africa, qualitative research

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Authors: Scott Rawlings

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Victoria’s first State of the Bays report is an historic baseline study of the health of Port Phillip Bay and Western Port. The report includes 50 assessments of 36 indicators across a broad array of topics from the nitrogen cycle and water quality to key marine species and habitats. This paper discusses the processes for determining and assessing the indicators and comments on future priorities identified to maintain and improve the health of these water ways. Victoria’s population is now at six million, and growing at a rate of over 100,000 people per year - the highest increase in Australia – and the population of greater Melbourne is over four million. Port Phillip Bay and Western Port are vital marine assets at the centre of this growth and will require adaptive strategies if they are to remain in good condition and continue to deliver environmental, economic and social benefits. In 2014, it was in recognition of these pressures that the incoming Victorian Government committed to reporting on the state of the bays every five years. The inaugural State of the Bays report was issued by the independent Victorian Commissioner for Environmental Sustainability. The report brought together what is known about both bays, based on existing research. It was a baseline on which future reports will build and, over time, include more of Victoria’s marine environment. Port Phillip Bay and Western Port generally demonstrate healthy systems. Specific threats linked to population growth are a significant pressure. Impacts are more significant where human activity is more intense and where nutrients are transported to the bays around the mouths of creeks and drainage systems. The transport of high loads of nutrients and pollutants to the bays from peak rainfall events is likely to increase with climate change – as will sea level rise. Marine pests are also a threat. More than 100 introduced marine species have become established in Port Phillip Bay and can compete with native species, alter habitat, reduce important fish stocks and potentially disrupt nitrogen cycling processes. This study confirmed that our data collection regime is better within the Marine Protected Areas of Port Phillip Bay than in other parts. The State of the Bays report is a positive and practical example of what can be achieved through collaboration and cooperation between environmental reporters, Government agencies, academic institutions, data custodians, and NGOs. The State of the Bays 2016 provides an important foundation by identifying knowledge gaps and research priorities for future studies and reports on the bays. It builds a strong evidence base to effectively manage the bays and support an adaptive management framework. The Report proposes a set of indicators for future reporting that will support a step-change in our approach to monitoring and managing the bays – a shift from reporting only on what we do know, to reporting on what we need to know.

Keywords: coastal science, marine science, Port Phillip Bay, state of the environment, Western Port

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Authors: Thomas Folegot, Arnaud Levaufre, Léna Bourven, Nicolas Kermagoret, Alexis Caillard, Roger Gallou

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Concern for negative impacts of anthropogenic noise on the ocean’s ecosystems has increased over the recent decades. This concern leads to a similar increased willingness to regulate noise-generating activities, of which shipping is one of the most significant. Dealing with ship noise requires not only knowledge about the noise from individual ships, but also how the ship noise is distributed in time and space within the habitats of concern. Marine mammals, but also fish, sea turtles, larvae and invertebrates are mostly dependent on the sounds they use to hunt, feed, avoid predators, during reproduction to socialize and communicate, or to defend a territory. In the marine environment, sight is only useful up to a few tens of meters, whereas sound can propagate over hundreds or even thousands of kilometers. Directive 2008/56/EC of the European Parliament and of the Council of June 17, 2008 called the Marine Strategy Framework Directive (MSFD) require the Member States of the European Union to take the necessary measures to reduce the impacts of maritime activities to achieve and maintain a good environmental status of the marine environment. The Ocean-Planner is a web-based platform that provides to regulators, managers of protected or sensitive areas, etc. with a decision support tool that enable to anticipate and quantify the effectiveness of management measures in terms of reduction or modification the distribution of underwater noise, in response to Descriptor 11 of the MSFD and to the Marine Spatial Planning Directive. Based on the operational sound modelling tool Quonops Online Service, Ocean-Planner allows the user via an intuitive geographical interface to define management measures at local (Marine Protected Area, Natura 2000 sites, Harbors, etc.) or global (Particularly Sensitive Sea Area) scales, seasonal (regulation over a period of time) or permanent, partial (focused to some maritime activities) or complete (all maritime activities), etc. Speed limit, exclusion area, traffic separation scheme (TSS), and vessel sound level limitation are among the measures supported be the tool. Ocean Planner help to decide on the most effective measure to apply to maintain or restore the biodiversity and the functioning of the ecosystems of the coastal seabed, maintain a good state of conservation of sensitive areas and maintain or restore the populations of marine species.

Keywords: underwater noise, marine biodiversity, marine spatial planning, mitigation measures, prediction

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Authors: Mamunur Rashid, Jialin Yan

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The current years have witnessed a rapid evolution and integration of artificial intelligence (AI) in various fields, prominently influencing the education industry. Acknowledging this transformative wave, AI tools like ChatGPT and Grammarly have undeniably introduced perspectives and skills, enriching the educational experiences of higher education students. The prevalence of AI utilization in higher education also drives an increasing number of researchers' attention in various dimensions. Departments, offices, and professors in universities also designed and released a set of policies and guidelines on using AI effectively. In regard to this, the study targets exploring and analyzing graduate students' perspectives regarding AI guidelines set by teachers. A mixed-methods study will be mainly conducted in this study, employing in-depth interviews and focus groups to investigate and collect students' perspectives. Relevant materials, such as syllabi and course instructions, will also be analyzed through the documentary analysis to facilitate understanding of the study. Surveys will also be used for data collection and students' background statistics. The integration of both interviews and surveys will provide a comprehensive array of student perspectives across various academic disciplines. The study is anchored in the theoretical framework of self-determination theory (SDT), which emphasizes and explains the students' perspective under the AI guidelines through three core needs: autonomy, competence, and relatedness. This framework is instrumental in understanding how AI guidelines influence students' intrinsic motivation and sense of empowerment in their learning environments. Through qualitative analysis, the study reveals a sense of confusion and uncertainty among students regarding the appropriate application and ethical considerations of AI tools, indicating potential challenges in meeting their needs for competence and autonomy. The quantitative data further elucidates these findings, highlighting a significant communication gap between students and educators in the formulation and implementation of AI guidelines. The critical findings of this study mainly come from two aspects: First, the majority of graduate students are uncertain and confused about relevant AI guidelines given by teachers. Second, this study also demonstrates that the design and effectiveness of course materials, such as the syllabi and instructions, also need to adapt in regard to AI policies. It indicates that certain of the existing guidelines provided by teachers lack consideration of students' perspectives, leading to a misalignment with students' needs for autonomy, competence, and relatedness. More emphasize and efforts need to be dedicated to both teacher and student training on AI policies and ethical considerations. To conclude, in this study, graduate students' perspectives on teacher-provided AI guidelines are explored and reflected upon, calling for additional training and strategies to improve how these guidelines can be better disseminated for their effective integration and adoption. Although AI guidelines provided by teachers may be helpful and provide new insights for students, educational institutions should take a more anchoring role to foster a motivating, empowering, and student-centered learning environment. The study also provides some relevant recommendations, including guidance for students on the ethical use of AI and AI policy training for teachers in higher education.

Keywords: higher education policy, graduate students’ perspectives, higher education teacher, AI guidelines, AI in education

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Authors: Kumar Shashvat, Amol P. Bhondekar

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In the midst of the five senses, odor is the most reminiscent and least understood. Odor testing has been mysterious and odor data fabled to most practitioners. The delinquent of recognition and classification of odor is important to achieve. The facility to smell and predict whether the artifact is of further use or it has become undesirable for consumption; the imitation of this problem hooked on a model is of consideration. The general industrial standard for this classification is color based anyhow; odor can be improved classifier than color based classification and if incorporated in machine will be awfully constructive. For cataloging of odor for peas, trees and cashews various discriminative approaches have been used Discriminative approaches offer good prognostic performance and have been widely used in many applications but are incapable to make effectual use of the unlabeled information. In such scenarios, generative approaches have better applicability, as they are able to knob glitches, such as in set-ups where variability in the series of possible input vectors is enormous. Generative models are integrated in machine learning for either modeling data directly or as a transitional step to form an indeterminate probability density function. The algorithms or models Linear Discriminant Analysis and Naive Bayes Classifier have been used for classification of the odor of cashews. Linear Discriminant Analysis is a method used in data classification, pattern recognition, and machine learning to discover a linear combination of features that typifies or divides two or more classes of objects or procedures. The Naive Bayes algorithm is a classification approach base on Bayes rule and a set of qualified independence theory. Naive Bayes classifiers are highly scalable, requiring a number of restraints linear in the number of variables (features/predictors) in a learning predicament. The main recompenses of using the generative models are generally a Generative Models make stronger assumptions about the data, specifically, about the distribution of predictors given the response variables. The Electronic instrument which is used for artificial odor sensing and classification is an electronic nose. This device is designed to imitate the anthropological sense of odor by providing an analysis of individual chemicals or chemical mixtures. The experimental results have been evaluated in the form of the performance measures i.e. are accuracy, precision and recall. The investigational results have proven that the overall performance of the Linear Discriminant Analysis was better in assessment to the Naive Bayes Classifier on cashew dataset.

Keywords: odor classification, generative models, naive bayes, linear discriminant analysis

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Authors: Oshma Chakoory, Sophie Comtet-Marre, Pierre Peyret

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Metagenomic classifiers are widely used for the taxonomic profiling of metagenomic data and estimation of taxa relative abundance. Small subunit rRNA genes are nowadays a gold standard for the phylogenetic resolution of complex microbial communities, although the power of this marker comes down to its use as full-length. We benchmarked the performance and accuracy of rRNA-specialized versus general-purpose read mappers, reference-targeted assemblers and taxonomic classifiers. We then built a pipeline called RiboTaxa to generate a highly sensitive and specific metataxonomic approach. Using metagenomics data, RiboTaxa gave the best results compared to other tools (Kraken2, Centrifuge (1), METAXA2 (2), PhyloFlash (3)) with precise taxonomic identification and relative abundance description, giving no false positive detection. Using real datasets from various environments (ocean, soil, human gut) and from different approaches (metagenomics and gene capture by hybridization), RiboTaxa revealed microbial novelties not seen by current bioinformatics analysis opening new biological perspectives in human and environmental health. In a study focused on corals’ health involving 20 metagenomic samples (4), an affiliation of prokaryotes was limited to the family level with Endozoicomonadaceae characterising healthy octocoral tissue. RiboTaxa highlighted 2 species of uncultured Endozoicomonas which were dominant in the healthy tissue. Both species belonged to a genus not yet described, opening new research perspectives on corals’ health. Applied to metagenomics data from a study on human gut and extreme longevity (5), RiboTaxa detected the presence of an uncultured archaeon in semi-supercentenarians (aged 105 to 109 years) highlighting an archaeal genus, not yet described, and 3 uncultured species belonging to the Enorma genus that could be species of interest participating in the longevity process. RiboTaxa is user-friendly, rapid, allowing microbiota structure description from any environment and the results can be easily interpreted. This software is freely available at https://github.com/oschakoory/RiboTaxa under the GNU Affero General Public License 3.0.

Keywords: metagenomics profiling, microbial diversity, SSU rRNA genes, full-length phylogenetic marker

Procedia PDF Downloads 126

Authors: D. M. Koers, A. J. Groen, P. D. Englis, R. Harms

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We are witnessing the largest level of displacement of people since World War II. Refugees want to become independent as quickly as possible and build a new, safe future; however, access to the labor market is difficult and they face many problems that are not easily solved. This makes self-employment including social entrepreneurship a valuable alternative. Our research studied refugee-based entrepreneurship and examined whether prior knowledge, unmet personal needs and contextual factors influence how refugees recognize opportunities and if this influences their social orientation. In addition, we examine the barriers refugees face when starting up a company in the Netherlands. We use a case study design with a mixed-method approach, combining in-depth interviews and survey data. Data was collected from two Dutch entrepreneurial training programs in the Netherlands. We have a sample size of 27 latent refugee entrepreneurs. Our results show that refugees score high on the social entrepreneurial measures. They perceive themselves as having a strong social vision and are determined to defend a social need. They also score high on sustainability and state that their business ideas improve the quality of life on the long run. Based on these findings, we did not expect that only 5 participants had business ideas with a social orientation. In this group, 37,5% started a company before and 77.8% used their personal experience to come up with this business idea. Another 70,3% had the higher professional education or academic education. In the interviews, we found that they often copy and paste their gained experience from a previous profession on their new context and expect that it would work well. The social aspect lies in their cultural values and personal beliefs but is not reflected in their business models. One of the reasons could be that the context in which the refugee operates as a moderator suppressing the social mission and social value creation opportunities. Refugees are first and foremost focused on their survival. They do not want to be on social welfare and feel a strong need to be independent. Since they cannot access the labor market easily and face labor market discrimination they want to start a company. Another factor that explains lack of the social orientation in their business ideas is that social entrepreneurship is not a known concept in their home countries. Their idea of entrepreneurship differs substantially. We found that a huge barrier for refugees is their expectations about setting up a business, which are often not realistic because they have little knowledge about the system, institutions and corresponding red tape. In those instances, can the institutional configuration of a country, cultural differences, and perspective on entrepreneurship hinders social entrepreneurship. In conclusion, there might be latent potential for social entrepreneurship in refugees but there are many barriers to overcome. Overcoming these barriers can enhance local communities and enhance integration. In addition it has a positive financial impact on the host country because it reduces the pressure on the social system and stimulate the economy.

Keywords: immigrant entrepreneurship, refugee entrepreneurship, social entrepreneurship, prior experience, opportunity recognition

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Authors: Alexandra Emmanuelle Membangbi, Jacky Njiki Bikoï, Esther Del-florence Moni Ndedi, Marie Joseph Nkodo Mindimi, Donatien Serge Mbaga, Elsa Nguiffo Makue, André Chris Mikangue Mbongue, Martha Mesembe, George Ikomey Mondinde, Eric Walter Perfura-yone, Sara Honorine Riwom Essama

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Background: Tuberculosis (TB) is one of the top lethal infectious diseases worldwide. In recent years, interferon-γ (INF-γ) release assays (IGRAs) have been established as routine tests for diagnosing TB infection. However, produced INF-γ assessment failed to distinguish active TB (ATB) from latent TB infection (LTBI), especially in TB epidemic areas. In addition to IFN-γ, interleukin-2 (IL-2), another cytokine secreted by activated T cells, is also involved in immune response against Mycobacterium tuberculosis. The aim of the study was to assess the capacity of IFN-γ and IL2 to evaluate the therapeutic response of patients on anti-tuberculosis treatment. Material and Methods: We conducted a cross-sectional study in the Pneumonology Departments of the Jamot Hospital in Yaoundé between May and August 2021. After signed the informed consent, the sociodemographic data, as well as 5 mL of blood, were collected in the crook of the elbow of each participant. Sixty-one subjects were selected (n= 61) and divided into 4 groups as followed: group 1: resistant tuberculosis (n=13), group 2: active tuberculosis (n=19), group 3 cured tuberculosis (n=16), and group 4: presumed healthy persons (n=13). The cytokines of interest were determined using an indirect Enzyme-linked Immuno-Sorbent Assay (ELISA) according to the manufacturer's recommendations. P-values < 0.05 were interpreted as statistically significant. All statistical calculations were performed using SPSS version 22.0 Results: The results showed that men were more 14/61 infected (31,8%) with a high presence in active and resistant TB groups. The mean age was 41.3±13.1 years with a 95% CI = [38.2-44.7], the age group with the highest infection rate was ranged between 31 and 40 years. The IL-2 and INF-γ means were respectively 327.6±160.6 pg/mL and 26.6±13.0 pg/mL in active tuberculosis patients, 251.1±30.9 pg/mL and 21.4±9.2 pg/mL in patients with resistant tuberculosis, while it was 149.3±93.3 pg/mL and 17.9±9.4 pg/mL in cured patients, 15.1±8.4 pg/mL and 5.3±2.6 pg/mL in participants presumed healthy (p <0.0001). Significant differences in IFN-γ and IL-2 rates were observed between the different groups. Conclusion: Monitoring the serum levels of INF-γ and IL-2 would be useful to evaluate the therapeutic response of anti-tuberculosis patients, particularly in the both cytokines association case, that could improve the accuracy of routine examinations.

Keywords: antibiotic therapy, interferon gamma, interleukin 2, tuberculosis

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Authors: T. Kuchukhidze, N. Jalagonia, T. Archuadze, G. Bokuchava

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The growing scientific-technological progress in modern civilization causes actuality of producing construction materials which can successfully work in conditions of high temperature, radiation, pressure, speed, and chemically aggressive environment. Such extreme conditions can withstand very few types of materials and among them, ceramic materials are in the first place. Corundum ceramics is the most useful material for creation of constructive nodes and products of various purposes for its low cost, easy accessibility to raw materials and good combination of physical-chemical properties. However, ceramic composite materials have one disadvantage; they are less plastics and have lower toughness. In order to increase the plasticity, the ceramics are reinforced by various dopants, that reduces the growth of the cracks. It is shown, that adding of even small amount of carbon fibers and carbon nanotubes (CNT) as reinforcing material significantly improves mechanical properties of the products, keeping at the same time advantages of alundum ceramics. Graphene in composite material acts in the same way as inorganic dopants (MgO, ZrO2, SiC and others) and performs the role of aluminum oxide inhibitor, as it creates shell, that gives possibility to reduce sintering temperature and at the same time it acts as damper, because scattering of a shock wave takes place on carbon structures. Application of different structural modification of carbon (graphene, nanotube and others) as reinforced material, gives possibility to create multi-purpose highly requested composite materials based on alundum ceramics. In the present work offers simplified technology for obtaining of aluminum oxide ceramics, reinforced with carbon nanostructures, during which chemical modification with doping carbon nanostructures will be implemented in the process of synthesis of final powdery composite – Alumina. In charge doping carbon nanostructures connected to matrix substance with C-O-Al bonds, that provide their homogeneous spatial distribution. In ceramic obtained as a result of consolidation of such powders carbon fragments equally distributed in the entire matrix of aluminum oxide, that cause increase of bending strength and crack-resistance. The proposed way to prepare the charge simplifies the technological process, decreases energy consumption, synthesis duration and therefore requires less financial expenses. In the implementation of this work, modern instrumental methods were used: electronic and optical microscopy, X-ray structural and granulometric analysis, UV, IR, and Raman spectroscopy.

Keywords: ceramic materials, α-Al₂O₃, carbon nanostructures, composites, characterization, hot-pressing

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Authors: Farhina Haque, Chanyeop Park

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The high efficiency, high field, and high power density provided by wide bandgap (WBG) semiconductors and advanced power electronic converter (PEC) topologies enabled the dynamic control of power in medium to high voltage systems. Although WBG semiconductors outperform the conventional Silicon based devices in terms of voltage rating, switching speed, and efficiency, the increased voltage handling properties, high dv/dt, and compact device packaging increase local electric fields, which are the main causes of partial discharge (PD) in the advanced medium and high voltage applications. PD, which occurs actively in voids, triple points, and airgaps, is an inevitable dielectric challenge that causes insulation and device aging. The aging process accelerates over time and eventually leads to the complete failure of the applications. Hence, it is critical to mitigating PD. Sharp edges, airgaps, triple points, and bubbles are common defects that exist in any medium to high voltage device. The defects are created during the manufacturing processes of the devices and are prone to high-electric-field-induced PD due to the low permittivity and low breakdown strength of the gaseous medium filling the defects. A contemporary approach of mitigating PD by neutralizing electric fields in high power density applications is introduced in this study. To neutralize the locally enhanced electric fields that occur around the triple points, airgaps, sharp edges, and bubbles, electrets are developed and incorporated into high voltage applications. Electrets are electric fields emitting dielectric materials that are embedded with electrical charges on the surface and in bulk. In this study, electrets are fabricated by electrically charging polyvinylidene difluoride (PVDF) films based on the widely used triode corona discharge method. To investigate the PD mitigation performance of the fabricated electret films, a series of PD experiments are conducted on both the charged and uncharged PVDF films under square voltage stimuli that represent PWM waveform. In addition to the use of single layer electrets, multiple layers of electrets are also experimented with to mitigate PD caused by higher system voltages. The electret-based approach shows great promise in mitigating PD by neutralizing the local electric field. The results of the PD measurements suggest that the development of an ultimate solution to the decades-long dielectric challenge would be possible with further developments in the fabrication process of electrets.

Keywords: electrets, high power density, partial discharge, triode corona discharge

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Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

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When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

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Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper discusses the recent advances and future prospects of spacecraft position and attitude control using Model Predictive Control (MPC). First, the challenges of the space missions are summarized, in particular, taking into account the errors, uncertainties, and constraints imposed by the mission, spacecraft and, onboard processing capabilities. The summary of space mission errors and uncertainties provided in categories; initial condition errors, unmodeled disturbances, sensor, and actuator errors. These previous constraints are classified into two categories: physical and geometric constraints. Last, real-time implementation capability is discussed regarding the required computation time and the impact of sensor and actuator errors based on the Hardware-In-The-Loop (HIL) experiments. The rationales behind the scenarios’ are also presented in the scope of space applications as formation flying, attitude control, rendezvous and docking, rover steering, and precision landing. The objectives of these missions are explained, and the generic constrained MPC problem formulations are summarized. Three key design elements used in MPC design: the prediction model, the constraints formulation and the objective cost function are discussed. The prediction models can be linear time invariant or time varying depending on the geometry of the orbit, whether it is circular or elliptic. The constraints can be given as linear inequalities for input or output constraints, which can be written in the same form. Moreover, the recent convexification techniques for the non-convex geometrical constraints (i.e., plume impingement, Field-of-View (FOV)) are presented in detail. Next, different objectives are provided in a mathematical framework and explained accordingly. Thirdly, because MPC implementation relies on finding in real-time the solution to constrained optimization problems, computational aspects are also examined. In particular, high-speed implementation capabilities and HIL challenges are presented towards representative space avionics. This covers an analysis of future space processors as well as the requirements of sensors and actuators on the HIL experiments outputs. The HIL tests are investigated for kinematic and dynamic tests where robotic arms and floating robots are used respectively. Eventually, the proposed algorithms and experimental setups are introduced and compared with the authors' previous work and future plans. The paper concludes with a conjecture that MPC paradigm is a promising framework at the crossroads of space applications while could be further advanced based on the challenges mentioned throughout the paper and the unaddressed gap.

Keywords: convex optimization, model predictive control, rendezvous and docking, spacecraft autonomy

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Authors: Victoria C. Valdebenito

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Located within the context of accelerating globalization in the 21^st-century knowledge society, this paper focuses on one selected university in Chile at which radical curriculum policy changes have been taking place, diverging from the traditional curriculum in Chile at the undergraduate level as a section of a larger investigation. Using a ‘policy trajectory’ framework, and guided by the interpretivist approach to research, interview transcripts and institutional documents were analyzed in relation to the meso (university administration) and the micro (academics) level. Inside the case study, participants from the university administration and academic levels were selected both via snow-ball technique and purposive selection, thus they had different levels of seniority, with some participating actively in the curriculum reform processes. Guided by an interpretivist approach to research, documents and interview transcripts were analyzed to reveal major themes emerging from the data. A further ‘bigger picture’ analysis guided by critical theory was then undertaken, involving interrogation of underlying ideologies and how political and economic interests influence the cultural production of policy. The case-study university was selected because it represents a traditional and old case of university setting in the country, undergoing curriculum changes based on international trends such as the competency model and the liberal arts. Also, it is representative of a particular socioeconomic sector of the country. Access to the university was gained through email contact. Qualitative research methods were used, namely interviews and analysis of institutional documents. In all, 18 people were interviewed. The number was defined by when the saturation criterion was met. Semi-structured interview schedules were based on the four research questions about influences, policy texts, policy enactment and longer-term outcomes. Triangulation of information was used for the analysis. While there was no intention to generalize the specific findings of the case study, the results of the research were used as a focus for engagement with broader themes, often evident in global higher education policy developments. The research results were organized around major themes in three of the four contexts of the ‘policy trajectory’. Regarding the context of influences and the context of policy text production, themes relate to hegemony exercised by first world countries’ universities in the higher education field, its associated neoliberal ideology, with accountability and the discourse of continuous improvement, the local responses to those pressures, and the value of interdisciplinarity. Finally, regarding the context of policy practices and effects (enactment), themes emerged around the impacts of the curriculum changes on university staff, students, and resistance amongst academics. The research concluded with a few recommendations that potentially provide ‘food for thought’ beyond the localized settings of this study, as well as possibilities for further research.

Keywords: curriculum, global-local dynamics, higher education, policy, sociology of education

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Authors: Eleni Maistrou, D. Kosmopoulos, Carolina Moretti, Amalia Konidi, Katerina Boulougoura

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InterArch is an ongoing research project that has been running since September 2020. It aims to propose the design of a site-based digital application for archaeological sites and outdoor guided tours, supporting virtual and augmented reality technology. The research project is co‐financed by the European Union and Greek national funds, through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH - CREATE – INNOVATE (project code: Τ2ΕΔΚ-01659). It involves mutual collaboration between academic and cultural institutions and the contribution of an IT applications development company. The research will be completed by July 2023 and will run as a pilot project for the city of Ancient Messene, a place of outstanding natural beauty in the west of Peloponnese, which is considered one of the most important archaeological sites in Greece. The applied research project integrates an interactive approach to the natural environment, aiming at a manifold sensory experience. It combines the physical space of the archaeological site with the digital space of archaeological and cultural data while at the same time, it embraces storytelling processes by engaging an interdisciplinary approach that familiarizes the user with multiple semantic interpretations. The mingling of the real-world environment with its digital and cultural components by using augmented reality techniques could potentially transform the visit on-site into an immersive multimodal sensory experience. To this purpose, an extensive spatial analysis along with a detailed evaluation of the existing digital and non-digital archives is proposed in our project, intending to correlate natural landscape morphology (including archaeological material remains and environmental characteristics) with the extensive historical records and cultural digital data. On-site research was carried out, during which visitors’ itineraries were monitored and tracked throughout the archaeological visit using GPS locators. The results provide our project with useful insight concerning the way visitors engage and interact with their surroundings, depending on the sequence of their itineraries and the duration of stay at each location. InterArch aims to propose the design of a site-based digital application for archaeological sites and outdoor guided tours, supporting virtual and augmented reality technology. Extensive spatial analysis, along with a detailed evaluation of the existing digital and non-digital archives, is used in our project, intending to correlate natural landscape morphology with the extensive historical records and cultural digital data. The results of the on-site research provide our project with useful insight concerning the way visitors engage and interact with their surroundings, depending on the sequence of their itineraries and the duration of stay at each location.

Keywords: archaeological site, digital space, semantic interpretations, cultural heritage

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Authors: Sarah Faulkner, Patrick Faulkner, Caroline Ellison

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Improved mental and physical health, community connection, and increased life satisfaction has been strongly associated with bike riding for those with and without a disability. However, much evidence suggests that people living with a disability face increased barriers to engaging in cycling compared to members of the general population. People with an intellectual disability often live more sedentary and socially isolated lives that negatively impact their mental and physical health, as well as life satisfaction. This paper is based on preliminary findings from a three-year intervention cycling project funded by the South Australian Government. The cycling project was developed in partnership with community stakeholders that provided weekly instruction, training, and support to individuals living with intellectual disabilities to increase their capacity in cycling. This project aimed to support people living with intellectual disabilities to foster and facilitate improved physical and mental health, confidence, and independence and enhance social networking through their engagement in community cycling. The program applied principles of social role valorisation (SRV) theory as its guiding framework. Preliminary data collected is based on qualitative interviews with over 50 program participants, results from two participant wellness questionnaires, as well as a perceptually regulated exercise test administered throughout the project implementation. Preliminary findings are further supplemented with ethnographic analyses by the researchers who took a phenology of life experience approach. Preliminary findings of the program suggest a variety of social motivations behind participants' desire to learn cycling that acknowledges previous barriers to engagement and cycling’s role to address feelings of loneliness and social isolation. Meaningful health benefits can be achieved as demonstrated by increases in predicted V02 max measures, suggesting that physical intervention can not only improve physical health outcomes but also provide a variety of other social benefits. Initial engagement in the project has demonstrated an increase in participants' sense of confidence, well-being, and physical fitness. Implementation of the project in partnership with a variety of community stakeholders has identified a number of critical factors and processes necessary for future service replication, sustainability, and success. Findings from this intervention study contribute to the development of a knowledge base on how best to support individuals living with an intellectual disability to partake in bike riding and increase positive outcomes associated with their capacity building, social interaction, increased physical activity, physical health, and mental well-being. The initial findings of this study provide critical academic insights into the social and physical benefits of cycling for people living with a disability, as well as practical advice for future human service applications.

Keywords: cycling, disability, social inclusion, capacity building

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Authors: Neveen AlQasas, Daniel Johnson

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Membranes for water treatment are an established technology that attracts great attention due to its simplicity and cost effectiveness. However, membranes in operation suffer from the adverse effect of membrane fouling. Bio-fouling is a phenomenon that occurs at the water-membrane interface, and is a dynamic process that is initiated by the adsorption of dissolved organic material, including biomacromolecules, on the membrane surface. After initiation, attachment of microorganisms occurs, followed by biofilm growth. The biofilm blocks the pores of the membrane and consequently results in reducing the water flux. Moreover, the presence of a fouling layer can have a substantial impact on the membrane separation properties. Understanding the mechanism of the initiation phase of biofouling is a key point in eliminating the biofouling on membrane surfaces. The adhesion and attachment of different fouling materials is affected by the surface properties of the membrane materials. Therefore, surface properties of different polymeric materials had been studied in terms of their surface energies and Hansen solubility parameters (HSP). The difference between the combined HSP parameters (HSP distance) allows prediction of the affinity of two materials to each other. The possibilities of measuring the HSP of different polymer films via surface measurements, such as contact angle has been thoroughly investigated. Knowing the HSP of a membrane material and the HSP of a specific foulant, facilitate the estimation of the HSP distance between the two, and therefore the strength of attachment to the surface. Contact angle measurements using fourteen different solvents on five different polymeric films were carried out using the sessile drop method. Solvents were ranked as good or bad solvents using different ranking method and ranking was used to calculate the HSP of each polymeric film. Results clearly indicate the absence of a direct relation between contact angle values of each film and the HSP distance between each polymer film and the solvents used. Therefore, estimating HSP via contact angle alone is not sufficient. However, it was found if the surface tensions and viscosities of the used solvents are taken in to the account in the analysis of the contact angle values, a prediction of the HSP from contact angle measurements is possible. This was carried out via training of a neural network model. The trained neural network model has three inputs, contact angle value, surface tension and viscosity of solvent used. The model is able to predict the HSP distance between the used solvent and the tested polymer (material). The HSP distance prediction is further used to estimate the total and individual HSP parameters of each tested material. The results showed an accuracy of about 90% for all the five studied films

Keywords: surface characterization, hansen solubility parameter estimation, contact angle measurements, artificial neural network model, surface measurements

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Authors: Rui Teixeira, Alan O’Connor, Maria Nogal

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The statistical theory of extreme events is progressively a topic of growing interest in all the fields of science and engineering. The changes currently experienced by the world, economic and environmental, emphasized the importance of dealing with extreme occurrences with improved accuracy. When it comes to the design of offshore structures, particularly offshore wind turbines, the importance of efficiently characterizing extreme events is of major relevance. Extreme events are commonly characterized by extreme values theory. As an alternative, the accurate modeling of the tails of statistical distributions and the characterization of the low occurrence events can be achieved with the application of the Peak-Over-Threshold (POT) methodology. The POT methodology allows for a more refined fit of the statistical distribution by truncating the data with a minimum value of a predefined threshold u. For mathematically approximating the tail of the empirical statistical distribution the Generalised Pareto is widely used. Although, in the case of the exceedances of significant wave data (H_s) the 2 parameters Weibull and the Exponential distribution, which is a specific case of the Generalised Pareto distribution, are frequently used as an alternative. The Generalized Pareto, despite the existence of practical cases where it is applied, is not completely recognized as the adequate solution to model exceedances over a certain threshold u. References that set the Generalised Pareto distribution as a secondary solution in the case of significant wave data can be identified in the literature. In this framework, the current study intends to tackle the discussion of the application of statistical models to characterize exceedances of wave data. Comparison of the application of the Generalised Pareto, the 2 parameters Weibull and the Exponential distribution are presented for different values of the threshold u. Real wave data obtained in four buoys along the Irish coast was used in the comparative analysis. Results show that the application of the statistical distributions to characterize significant wave data needs to be addressed carefully and in each particular case one of the statistical models mentioned fits better the data than the others. Depending on the value of the threshold u different results are obtained. Other variables of the fit, as the number of points and the estimation of the model parameters, are analyzed and the respective conclusions were drawn. Some guidelines on the application of the POT method are presented. Modeling the tail of the distributions shows to be, for the present case, a highly non-linear task and, due to its growing importance, should be addressed carefully for an efficient estimation of very low occurrence events.

Keywords: extreme events, offshore structures, peak-over-threshold, significant wave data

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Authors: Bernard Nnamdi Emenyeonu

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The study of communication as a fully-fledged discipline in institutions of higher education in the Sultanate of Oman is relatively young. Its evolution is associated with Oman's Renaissance beginning from 1970, which ushered in an era of modernization in which education, industrialization, expansion, and liberalization of the mass media, provision of infrastructure, and promotion of multilateral commercial ventures were considered among the top priorities of national development plans. Communication studies were pioneered by the sole government university, Sultan Qaboos University, in the 1990s, but so far, the program is taught in Arabic only. In recognition of the need to produce professionals suitably equipped to fit into the expanding media establishments in the Sultanate as well as the widening global market, the government decided to establish programs in which communication would be taught in English language. Under the supervision of the Ministry of Higher Education, six Colleges of Applied Sciences were established in Oman in 2007. These colleges offer a 4-year Bachelor degree program in communication studies that comprises six areas of specialization: Advertising, Digital Media, International Communication, Journalism, Media Management and Public Relations. Over the years, a trend has emerged where students tend to flock to particular specializations such as Public Relations and Digital Media, while others, such as Advertising and Journalism, continue to draw the least number of students. In some instances, some specializations have had to be frozen due to the dire lack of interest among new students. It has also been observed that female students are more likely to be more biased in choice of specializations. It was therefore the task of this paper to establish, through a survey and focus group interviews, the factors that influence choice of communication studies as well as particular specializations, among Omani Communication Studies undergraduates. Results of the study show that prior to entering into the communication studies program, the majority of students had no idea of what the field entailed. Whatever information they had about communication studies was sourced from friends and relatives rather than more reliable sources such as career fairs or guidance counselors. For the most part, the choice of communication studies as a major was also influenced by factors such as family, friends and prospects for jobs. Another significant finding is the strong association between gender and choice of specializations within the program, with females flocking to digital media while males tended to prefer public relations. Reasons for specialization preferences dwelt strongly on expectations of a good GPA and the promise of a good salary after graduation. Regardless of gender, most students identified careers in news reporting, public relations and advertising as unsuitable for females. Teaching and program presentation were identified as the most suitable for females. Based on these and other results, the paper not only examined the social and cultural factors that are likely to have influenced the respondent's attitude to communication studies, but also discussed the implication for curriculum development and career development in a developing society such as Oman.

Keywords: career choice, communication specialization, media education, Oman

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Authors: Stefano Iannello, Massimiliano Materazzi

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Fluidized bed reactor technologies are one of the most valuable pathways for thermochemical conversions of biogenic fuels due to their good operating flexibility. Nevertheless, there are still issues related to the mixing and separation of heterogeneous phases during operation with highly volatile feedstocks, including biomass and waste. At high temperatures, the volatile content of the feedstock is released in the form of the so-called endogenous bubbles, which generally exert a “lift” effect on the particle itself by dragging it up to the bed surface. Such phenomenon leads to high release of volatile matter into the freeboard and limited mass and heat transfer with particles of the bed inventory. The aim of this work is to get a better understanding of the behaviour of a single reacting particle in a hot fluidized bed reactor during the devolatilization stage. The analysis has been undertaken at different fluidization regimes and temperatures to closely mirror the operating conditions of waste-to-energy processes. Beechwood and polypropylene particles were used to resemble the biomass and plastic fractions present in waste materials, respectively. The non-invasive X-ray technique was coupled to particle tracking algorithms to characterize the motion of a single feedstock particle during the devolatilization with high resolution. A high-energy X-ray beam passes through the vessel where absorption occurs, depending on the distribution and amount of solids and fluids along the beam path. A high-speed video camera is synchronised to the beam and provides frame-by-frame imaging of the flow patterns of fluids and solids within the fluidized bed up to 72 fps (frames per second). A comprehensive mathematical model has been developed in order to validate the experimental results. Beech wood and polypropylene particles have shown a very different dynamic behaviour during the pyrolysis stage. When the feedstock is fed from the bottom, the plastic material tends to spend more time within the bed than the biomass. This behaviour can be attributed to the presence of the endogenous bubbles, which drag effect is more pronounced during the devolatilization of biomass, resulting in a lower residence time of the particle within the bed. At the typical operating temperatures of thermochemical conversions, the synthetic polymer softens and melts, and the bed particles attach on its outer surface, generating a wet plastic-sand agglomerate. Consequently, this additional layer of sand may hinder the rapid evolution of volatiles in the form of endogenous bubbles, and therefore the establishment of a poor drag effect acting on the feedstock itself. Information about the mixing and segregation of solid feedstock is of prime importance for the design and development of more efficient industrial-scale operations.

Keywords: fluidized bed, pyrolysis, waste feedstock, X-ray

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Authors: Yagya Murti Aryal, Bipin Adhikari, Pradeep Gyawali

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The Lesser Himalaya zone of Nepal consists of thrusting and folding belts, which play an important role in the sustainable management of groundwater in the Himalayan regions. The study area is located in the Dolakha and Ramechhap Districts of Bagmati Province, Nepal. Geologically, these districts are situated in the Lesser Himalayas and partly encompass the Higher Himalayan rock sequence, which includes low-grade to high-grade metamorphic rocks. Following the Gorkha Earthquake in 2015, numerous springs dried up, and many others are currently experiencing depletion due to the distortion of the natural groundwater flow. The primary objective of this study is to identify potential groundwater areas and determine suitable sites for artificial groundwater recharge. Two distinct statistical approaches were used to develop models: The Frequency Ratio (FR) and Shannon Entropy (SE) methods. The study utilized both primary and secondary datasets and incorporated significant role and controlling factors derived from field works and literature reviews. Field data collection involved spring inventory, soil analysis, lithology assessment, and hydro-geomorphology study. Additionally, slope, aspect, drainage density, and lineament density were extracted from a Digital Elevation Model (DEM) using GIS and transformed into thematic layers. For training and validation, 114 springs were divided into a 70/30 ratio, with an equal number of non-spring pixels. After assigning weights to each class based on the two proposed models, a groundwater potential map was generated using GIS, classifying the area into five levels: very low, low, moderate, high, and very high. The model's outcome reveals that over 41% of the area falls into the low and very low potential categories, while only 30% of the area demonstrates a high probability of groundwater potential. To evaluate model performance, accuracy was assessed using the Area under the Curve (AUC). The success rate AUC values for the FR and SE methods were determined to be 78.73% and 77.09%, respectively. Additionally, the prediction rate AUC values for the FR and SE methods were calculated as 76.31% and 74.08%. The results indicate that the FR model exhibits greater prediction capability compared to the SE model in this case study.

Keywords: groundwater potential mapping, frequency ratio, Shannon’s Entropy, Lesser Himalaya Zone, sustainable groundwater management

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Authors: Jaana Sepp, Ulvi Kõrgemaa, Kristi Puusepp, Õie Tähtla

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COVID-19 was officially recognized as a pandemic in late 2019 by the WHO, and it has led to changes in the education sector. Educational institutions were closed, and most schools adopted distance learning. Estonia is known as a digitally well-developed country. Based on that, in the pandemic time, nursing education continued, and new technological solutions were implemented. To provide nursing education, special focus was paid on quality and flexibility. The aim of this paper is to present administrative, digital, and technological solutions which support Estonian nursing educators to continue the study process in the pandemic time and to develop a sustainable solution for nursing education for the future. This paper includes the authors’ analysis of the documents and decisions implemented in the institutions through the pandemic time. It is a case study of Estonian nursing educators. Results of the analysis show that the implementation of distance learning principles challenges the development of innovative strategies and technics for the assessment of student performance and educational outcomes and implement new strategies to encourage student engagement in the virtual classroom. Additionally, hospital internships were canceled, and the simulation approach was deeply implemented as a new opportunity to develop and assess students’ practical skills. There are many other technical and administrative changes that have also been carried out, such as students’ support and assessment systems, the designing and conducting of hybrid and blended studies, etc. All services were redesigned and made more available, individual, and flexible. Hence, the feedback system was changed, the information was collected in parallel with educational activities. Experiences of nursing education during the pandemic time are widely presented in scientific literature. However, to conclude our study, authors have found evidence that solutions implemented in Estonian nursing education allowed the students to graduate within the nominal study period without any decline in education quality. Operative information system and flexibility provided the minimum distance between the students, support, and academic staff, and likewise, the changes were implemented quickly and efficiently. Institution memberships were updated with the appropriate information, and it positively affected their satisfaction, motivation, and commitment. We recommend that the feedback process and the system should be permanently changed in the future to place all members in the same information area, redefine the hospital internship process, implement hybrid learning, as well as to improve the communication system between stakeholders inside and outside the organization. The main limitation of this study relates to the size of Estonia. Nursing education is provided by two institutions only, and similarly, the number of students is low. The result could be generated to the institutions with a similar size and administrative system. In the future, the relationship between nurses’ performance and organizational outcomes should be deeply investigated and influences of the pandemic time education analyzed at workplaces.

Keywords: hybrid learning, nursing education, nursing, COVID-19

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Authors: Oluwafunmibi Omotayo Fasanya, Augustine Kena Adjei

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Diabetic nephropathy (DN) is a major complication of diabetes, with fibrosis and propionate metabolism playing critical roles in its progression. Identifying biomarkers linked to these pathways may provide novel insights into DN diagnosis and treatment. This study aims to identify biomarkers associated with fibrosis and propionate metabolism in DN. Analyze the biological pathways and regulatory mechanisms of these biomarkers. Develop a machine learning model to predict DN-related biomarkers and validate their functional roles. Publicly available transcriptome datasets related to DN (GSE96804 and GSE104948) were obtained from the GEO database (https://www.ncbi.nlm.nih.gov/gds), and 924 propionate metabolism-related genes (PMRGs) and 656 fibrosis-related genes (FRGs) were identified. The analysis began with the extraction of DN-differentially expressed genes (DN-DEGs) and propionate metabolism-related DEGs (PM-DEGs), followed by the intersection of these with fibrosis-related genes to identify key intersected genes. Instead of relying on traditional models, we employed a combination of deep neural networks (DNNs) and ensemble methods such as Gradient Boosting Machines (GBM) and XGBoost to enhance feature selection and biomarker discovery. Recursive feature elimination (RFE) was coupled with these advanced algorithms to refine the selection of the most critical biomarkers. Functional validation was conducted using convolutional neural networks (CNN) for gene set enrichment and immunoinfiltration analysis, revealing seven significant biomarkers—SLC37A4, ACOX2, GPD1, ACE2, SLC9A3, AGT, and PLG. These biomarkers are involved in critical biological processes such as fatty acid metabolism and glomerular development, providing a mechanistic link to DN progression. Furthermore, a TF–miRNA–mRNA regulatory network was constructed using natural language processing models to identify 8 transcription factors and 60 miRNAs that regulate these biomarkers, while a drug–gene interaction network revealed potential therapeutic targets such as UROKINASE–PLG and ATENOLOL–AGT. This integrative approach, leveraging deep learning and ensemble models, not only enhances the accuracy of biomarker discovery but also offers new perspectives on DN diagnosis and treatment, specifically targeting fibrosis and propionate metabolism pathways.

Keywords: diabetic nephropathy, deep neural networks, gradient boosting machines (GBM), XGBoost

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Authors: Priya Saha, Sourav Dey Roy Jr., Debotosh Bhattacharjee, Mita Nasipuri, Barin Kumar De, Mrinal Kanti Bhowmik

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Biometric face recognition technology (FRT) has gained a lot of attention due to its extensive variety of applications in both security and non-security perspectives. It has come into view to provide a secure solution in identification and verification of person identity. Although other biometric based methods like fingerprint scans, iris scans are available, FRT is verified as an efficient technology for its user-friendliness and contact freeness. Accurate facial feature localization plays an important role for many facial analysis applications including biometrics and emotion recognition. But, there are certain factors, which make facial feature localization a challenging task. On human face, expressions can be seen from the subtle movements of facial muscles and influenced by internal emotional states. These non-rigid facial movements cause noticeable alterations in locations of facial landmarks, their usual shapes, which sometimes create occlusions in facial feature areas making face recognition as a difficult problem. The paper proposes a new hybrid based technique for automatic landmark detection in both neutral and expressive frontal and near frontal face images. The method uses the concept of thresholding, sequential searching and other image processing techniques for locating the landmark points on the face. Also, a Graphical User Interface (GUI) based software is designed that could automatically detect 16 landmark points around eyes, nose and mouth that are mostly affected by the changes in facial muscles. The proposed system has been tested on widely used JAFFE and Cohn Kanade database. Also, the system is tested on DeitY-TU face database which is created in the Biometrics Laboratory of Tripura University under the research project funded by Department of Electronics & Information Technology, Govt. of India. The performance of the proposed method has been done in terms of error measure and accuracy. The method has detection rate of 98.82% on JAFFE database, 91.27% on Cohn Kanade database and 93.05% on DeitY-TU database. Also, we have done comparative study of our proposed method with other techniques developed by other researchers. This paper will put into focus emotion-oriented systems through AU detection in future based on the located features.

Keywords: biometrics, face recognition, facial landmarks, image processing

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Authors: Mohammad Khoshini, Arman Khoshghalb, Meghdad Payan, Nasser Khalili

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Most of the Earth’s crust surface rocks are technically categorized as weak rocks or weakly bonded geomaterials. Deeply weathered, weakly cemented, friable and easily erodible, they demonstrate complex material behaviour and understanding the overlooked mechanical behaviour of such materials is of particular importance in geotechnical engineering practice. Weakly bonded geomaterials are so susceptible to surface shear and moisture that conventional methods of core drilling fail to extract high-quality undisturbed samples out of them. Moreover, most of these geomaterials are of high heterogeneity rendering less reliable and feasible material characterization. In order to compensate for the unpredictability of the material response, either numerous experiments are needed to be conducted or large factors of safety must be implemented in the design process. However, none of these approaches is sustainable. In this study, a method for dry core drilling of such materials is introduced to take high-quality undisturbed core samples. By freezing the material at certain moisture content, a secondary structure is developed throughout the material which helps the whole structure to remain intact during the core drilling process. Moreover, to address the heterogeneity issue, the natural material was reconstructed artificially to obtain a homogeneous material with very high similarity to the natural one in both micro and macro-mechanical perspectives. The method is verified for both micro and macro scale. In terms of micro-scale analysis, using Scanning Electron Microscopy (SEM), pore spaces and inter-particle bonds were investigated and compared between natural and artificial materials. X-Ray Diffraction, XRD, analyses are also performed to control the chemical composition. At the macro scale, several uniaxial compressive strength tests, as well as triaxial tests, were performed to verify the similar mechanical response of the materials. A high level of agreement is observed between micro and macro results of natural and artificially bonded geomaterials. The proposed methods can play an important role to cut down the costs of experimental programs for material characterization and also to promote the accuracy of the numerical modellings based on the experimental results.

Keywords: Artificial geomaterial, core drilling, macro-mechanical behavior, micro-scale, sample preparation, SEM photography, weakly bonded geomaterials

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Authors: Milos Beran, Josef Drahorad, Ondrej Vltavsky, Martin Fronek, Jiri Sova

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While most nanofibers are produced using electrospinning, this technique suffers from several drawbacks, such as the requirement for specialized equipment, high electrical potential, and electrically conductive targets. Consequently, recent years have seen the increasing emergence of novel strategies in generating nanofibers in a larger scale and higher throughput manner. The centrifugal spinning is simple, cheap and highly productive technology for nanofiber production. In principle, the drawing of solution filament into nanofibers using centrifugal spinning is achieved through the controlled manipulation of centrifugal force, viscoelasticity, and mass transfer characteristics of the spinning solutions. Engineering efforts of researches of the Food research institute Prague and the Czech Technical University in the field the centrifugal nozzleless spinning led to introduction of a pilot plant demonstrator NANOCENT. The main advantages of the demonstrator are lower investment cost - thanks to simpler construction compared to widely used electrospinning equipments, higher production speed, new application possibilities and easy maintenance. The centrifugal nozzleless spinning is especially suitable to produce submicron fibers from polymeric solutions in highly volatile solvents, such as chloroform, DCM, THF, or acetone. To date, submicron fibers have been prepared from PS, PUR and biodegradable polyesters, such as PHB, PLA, PCL, or PBS. The products are in form of 3D structures or nanofiber membranes. Unique self-supporting nanofiber membranes were prepared from the biodegradable polyesters in different mixtures. The nanofiber membranes have been tested for different applications. Filtration efficiencies for water solutions and aerosols in air were evaluated. Different active inserts were added to the solutions before the spinning process, such as inorganic nanoparticles, organic precursors of metal oxides, antimicrobial and wound healing compounds or photocatalytic phthalocyanines. Sintering can be subsequently carried out to remove the polymeric material and transfer the organic precursors to metal oxides, such as Si02, or photocatalytic Zn02 and Ti02, to obtain inorganic nanofibers. Electrospinning is more suitable technology to produce membranes for the filtration applications than the centrifugal nozzleless spinning, because of the formation of more homogenous nanofiber layers and fibers with smaller diameters. The self-supporting nanofiber membranes prepared from the biodegradable polyesters are especially suitable for medical applications, such as wound or burn healing dressings or tissue engineering scaffolds. This work was supported by the research grants TH03020466 of the Technology Agency of the Czech Republic.

Keywords: polymeric nanofibers, self-supporting nanofiber membranes, biodegradable polyesters, active inserts

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Authors: Ayesha M. Facey

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The evaluation sought to determine the factors associated with the high failure rate among students taking a first-year introductory statistics course. By utilizing Tyler’s Objective Based Model, the main objectives were: to assess the effectiveness of the lecturer’s teaching strategies; to determine the proportion of students who attends lectures and tutorials frequently and to determine the impact of infrequent attendance on performance; to determine how the assigned activities assisted in students understanding of the course content; to ascertain the possible issues being faced by students in understanding the course material and obtain possible solutions to the challenges and to determine whether the learning outcomes have been achieved based on an assessment of the second in-course examination. A quantitative survey research strategy was employed and the study population was students enrolled in semester one of the academic year 2015/2016. A convenience sampling approach was employed resulting in a sample of 98 students. Primary data was collected using self-administered questionnaires over a one-week period. Secondary data was obtained from the results of the second in-course examination. Data were entered and analyzed in SPSS version 22 and both univariate and bivariate analyses were conducted on the information obtained from the questionnaires. Univariate analyses provided description of the sample through means, standard deviations and percentages while bivariate analyses were done using Spearman’s Rho correlation coefficient and Chi-square analyses. For secondary data, an item analysis was performed to obtain the reliability of the examination questions, difficulty index and discriminant index. The examination results also provided information on the weak areas of the students and highlighted the learning outcomes that were not achieved. Findings revealed that students were more likely to participate in lectures than tutorials and that attendance was high for both lectures and tutorials. There was a significant relationship between participation in lectures and performance on examination. However, a high proportion of students has been absent from three or more tutorials as well as lectures. A higher proportion of students indicated that they completed the assignments obtained from the lectures sometimes while they rarely completed tutorial worksheets. Students who were more likely to complete their assignments were significantly more likely to perform well on their examination. Additionally, students faced a number of challenges in understanding the course content and the topics of probability, binomial distribution and normal distribution were the most challenging. The item analysis also highlighted these topics as problem areas. Problems doing mathematics and application and analyses were their major challenges faced by students and most students indicated that some of the challenges could be alleviated if additional examples were worked in lectures and they were given more time to solve questions. Analysis of the examination results showed that a number of learning outcomes were not achieved for a number of topics. Based on the findings recommendations were made that suggested adjustments to grade allocations, delivery of lectures and methods of assessment.

Keywords: evaluation, item analysis, Tyler’s objective based model, university statistics

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Authors: Suleyman Ogul Ertugrul, Mustafa Turgut, Serkan Inandı, Mustafa Gorkem Coban, Mustafa Kıgılı, Ali Mert, Oguzhan Kesmez, Murat Ozancı, Caglar Uyulan

Abstract:

In high-performance automotive engineering, the realistic simulation of suspension systems is crucial for enhancing vehicle dynamics and handling. This study focuses on the double wishbone suspension system, prevalent in racing vehicles due to its superior control and stability characteristics. Utilizing MATLAB and Adams Car simulation software, we conduct a comprehensive analysis of displacement behaviors and damper sizing under various dynamic conditions. The initial phase involves using MATLAB to simulate the entire suspension system, allowing for the preliminary determination of damper size based on the system's response under simulated conditions. Following this, manual calculations of wheel loads are performed to assess the forces acting on the front and rear suspensions during scenarios such as braking, cornering, maximum vertical loads, and acceleration. Further dynamic force analysis is carried out using MATLAB Simulink, focusing on the interactions between suspension components during key movements such as bumps and rebounds. This simulation helps in formulating precise force equations and in calculating the stiffness of the suspension springs. To enhance the accuracy of our findings, we focus on a detailed kinematic and dynamic analysis. This includes the creation of kinematic loops, derivation of relevant equations, and computation of Jacobian matrices to accurately determine damper travel and compression metrics. The calculated spring stiffness is crucial in selecting appropriate springs to ensure optimal suspension performance. To validate and refine our results, we replicate the analyses using the Adams Car software, renowned for its detailed handling of vehicular dynamics. The goal is to achieve a robust, reliable suspension setup that maximizes performance under the extreme conditions encountered in racing scenarios. This study exemplifies the integration of theoretical mechanics with advanced simulation tools to achieve a high-performance suspension setup that can significantly improve race car performance, providing a methodology that can be adapted for different types of racing vehicles.

Keywords: FSAE, suspension system, Adams Car, kinematic

Procedia PDF Downloads 56

Authors: Erva Akin

Abstract:

– The use of copyrighted material for machine learning purposes is a challenging issue in the field of artificial intelligence (AI). While machine learning algorithms require large amounts of data to train and improve their accuracy and creativity, the use of copyrighted material without permission from the authors may infringe on their intellectual property rights. In order to overcome copyright legal hurdle against the data sharing, access and re-use of data, the use of copyrighted material for machine learning purposes may be considered permissible under certain circumstances. For example, if the copyright holder has given permission to use the data through a licensing agreement, then the use for machine learning purposes may be lawful. It is also argued that copying for non-expressive purposes that do not involve conveying expressive elements to the public, such as automated data extraction, should not be seen as infringing. The focus of such ‘copy-reliant technologies’ is on understanding language rules, styles, and syntax and no creative ideas are being used. However, the non-expressive use defense is within the framework of the fair use doctrine, which allows the use of copyrighted material for research or educational purposes. The questions arise because the fair use doctrine is not available in EU law, instead, the InfoSoc Directive provides for a rigid system of exclusive rights with a list of exceptions and limitations. One could only argue that non-expressive uses of copyrighted material for machine learning purposes do not constitute a ‘reproduction’ in the first place. Nevertheless, the use of machine learning with copyrighted material is difficult because EU copyright law applies to the mere use of the works. Two solutions can be proposed to address the problem of copyright clearance for AI training data. The first is to introduce a broad exception for text and data mining, either mandatorily or for commercial and scientific purposes, or to permit the reproduction of works for non-expressive purposes. The second is that copyright laws should permit the reproduction of works for non-expressive purposes, which opens the door to discussions regarding the transposition of the fair use principle from the US into EU law. Both solutions aim to provide more space for AI developers to operate and encourage greater freedom, which could lead to more rapid innovation in the field. The Data Governance Act presents a significant opportunity to advance these debates. Finally, issues concerning the balance of general public interests and legitimate private interests in machine learning training data must be addressed. In my opinion, it is crucial that robot-creation output should fall into the public domain. Machines depend on human creativity, innovation, and expression. To encourage technological advancement and innovation, freedom of expression and business operation must be prioritised.

Keywords: artificial intelligence, copyright, data governance, machine learning

Procedia PDF Downloads 89