Search results for: digital learning environment

Authors: Saimir Heta, Ilma Robo, Rialda Xhizdari, Kers Kapaj

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The stability of an ideal disinfectant should be constant regardless of the change in the atmospheric conditions of the environment where it is kept. If the conditions such as temperature or humidity change, it is understood that it will also be necessary to approach possible changes in the holding materials such as plastic or glass bottles with the aim of protecting, for example, the disinfectant from the excessive lighting of the environment, which can also be translated as an increase in the temperature of disinfectant as a fluid. Material and Methods: In this study, an attempt was made to find the most recent published data about the best possible combination of disinfectants indicated for use after dental procedures. This purpose of the study was realized by comparing the basic literature that is studied in the field of dentistry by students with the most published data in the literature of recent years about this topic. Each disinfectant is represented by a number called the disinfectant count, in which different factors can influence the increase or reduction of variables whose production remains a specific statistic for a specific disinfectant. Results: The changes in the atmospheric conditions where the disinfectant is deposited and stored in the environment are known to affect the stability of the disinfectant as a fluid; this fact is known and even cited in the leaflets accompanying the manufactured boxes of disinfectants. It is these cares, in the form of advice, which are based not only on the preservation of the disinfectant but also on the application in order to have the desired clinical result. Aldehydes have the highest constant among the types of disinfectants, followed by acids. The lowest value of the constant belongs to the class of glycols, the predecessors of which were the halogens, in which class there are some representatives with disinfection applications. The class of phenols and acids have almost the same intervals of constants. Conclusions: If the goal were to find the ideal disinfectant among the large variety of disinfectants produced, a good starting point would be to find something unchanging or a fixed, unchanging element on the basis of which the comparison can be made properties of different disinfectants. Precisely based on the results of this study, the role of the specific constant according to the specific disinfectant is highlighted. Finding an ideal disinfectant, like finding a medication or the ideal antibiotic, is an ongoing but unattainable goal.

Keywords: different disinfectants, ideal, specific constant, dental procedures

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Authors: Yetunde I. Bulu, Moses B. Adewole, Julius O. Faluyi

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This study investigates the effect of aggressive application of herbicide on weed succession in an urban environment in Ile-Ife, Osun State. An inspection of the communities was carried out to identify sites maintained by herbicides (test plots) and those without herbicide history (control plots). Four different experimental plots located at Olasode, Eleweran, Ife City and Parakin within Ile-Ife town were monitored during the study. Comprehensive enumeration and identification of plant populations to species level was carried out on each of the plots and at every visit to determine the direction of succession. Index of similarities was used to determine the relationship in plant species composition between plots treated with herbicide and the untreated plots. The trend of increasing plant species was observed in all the study plots. Low Similarity Index between the treated plots and the control vegetation was observed at all visitations. Low similarity was also observed between the above-ground vegetation and the seed bank in all the plots. The study concluded that the weed population observed from the experimental plots showed an increase in species richness and diversity when the plots were left to recover compared to the control plots.

Keywords: herbicide, index of similarity, population, soil seed bank, succession

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Authors: Wajahat Ali, Shakeel Javaid

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In this study, we have developed a mathematical programming model for a solid transportation problem with three objective functions arranged in hierarchical order. The mathematical programming models with more than one objective function to be solved in hierarchical order is termed as a multi-level programming model. Our study explores a Multi-Level Solid Transportation Problem with Uncertain Parameters (MLSTPWU). The proposed MLSTPWU model consists of three objective functions, viz. minimization of transportation cost, minimization of total transportation time, and minimization of deterioration during transportation. These three objective functions are supposed to be solved by decision-makers at three consecutive levels. Three constraint functions are added to the model, restricting the total availability, total demand, and capacity of modes of transportation. All the parameters involved in the model are assumed to be uncertain in nature. A solution method based on fuzzy logic is also discussed to obtain the compromise solution for the proposed model. Further, a simulated numerical example is discussed to establish the efficiency and applicability of the proposed model.

Keywords: solid transportation problem, multi-level programming, uncertain variable, uncertain environment

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Authors: Trilochana Dash, Chandan Kumar Sahoo

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In today's environment of intensive industrialization, the role of business in societal modernization is critical. The concept of corporate social responsibility (CSR) arose due to rising societal awareness of company conduct. Corporations that practice CSR devote a portion of their profits to society’s sustainable development (SD). The concept of CSR and SD has increased the impact of industries on society. In this study, bibliometric analysis was conducted using the “R” programming language to determine the comprehensiveness of CSR and SD. From 2003 to 2022, bibliometric data was collected from two databases: Scopus and Web of Science (WOS). According to the findings, CSR and SD research has risen exponentially in the past two decades, and “Corporate Social Responsibility and Environment Management” emerged as the most influential journal in this field. The findings also show that relatively very few researchers collaborate in CSR and SD research in the last twenty years. It is widely acknowledged that most CSR and SD research is conducted in developed countries and developing countries undergoing fast industrialization. Thematic evolution and cluster analysis clearly show that the notion of CSR and SD among scholars has been quite popular over the last two decades. Finally, limitations and future directions are discussed.

Keywords: corporate social responsibility, sustainable development, bibliometric analysis, “R” programming language, visualization, holistic picture

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Authors: Olufemi Sunday Onabajo

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Radio according to communication scholars is a veritable instrument of mass education. However, its full potentials in boosting higher education have not been realized because of the commercial nature of radio stations in Nigeria. The licensing of campus radio for disseminating information on university curricular is aimed at reinforcing information shared during face to face teaching. This study anchored on Agenda Setting and Technology determinism theories seeks to find out the extent to which university students in Lead City University and University of Ibadan, Nigeria have keyed-in to the philosophy of their campus radio – Lead City FM and Diamond FM in making information dissemination in their domiciled universities less cumbersome. The study employs both qualitative and quantitative methods though the use of depth interview for ten (10) academic staff and five (5) radio personnel of both radio stations; and a questionnaire addressed to 200 students of both institutions using the systematic random sampling technique. The data collected was analyzed using simple percentage and chi-square one tail test, and it was discovered that students of both universities and their radio personnel are yet to realize the potentials of campus radio as a resource alternative to effective learning, and recommends the coming together of all stakeholders to articulate the way forward.

Keywords: disseminating information, effective learning, resource alternative, utilizing radio

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Authors: Linda Fellag, Arlene Caney

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E-learning has earned an essential place in academia because it promotes learner autonomy, student engagement, and technological aptitude, and allows for flexible learning. However, despite advantages, educators have been slower to embrace e-learning for ESL and other non-traditional students for fear that such students will not succeed without the direct faculty contact and academic support of face-to-face classrooms. This study aims to determine if a non-traditional student-friendly online course can produce student retention and performance rates that compare favorably with those of students in standard online sections of the same course aimed at traditional college-level students. One Music faculty member is currently collaborating with an English instructor to redesign an online college-level Music Appreciation course for non-traditional college students. At Community College of Philadelphia, Introduction to Music Appreciation was recently designated as one of the few college-level courses that advanced ESL, and developmental English students can take while completing their language studies. Beginning in Fall 2017, the course will be critical for international students who must maintain full-time student status under visa requirements. In its current online format, however, Music Appreciation is designed for traditional college students, and faculty who teach these sections have been reluctant to revise the course to address the needs of non-traditional students. Interestingly, presenters maintain that the online platform is the ideal place to develop language and college readiness skills in at-risk students while maintaining the course's curricular integrity. The two faculty presenters describe how curriculum rather than technology drives the redesign of the digitized music course, and self-study materials, guided assignments, and periodic assessments promote independent learning and comprehension of material. The 'scaffolded' modules allow ESL and developmental English students to build on prior knowledge, preview key vocabulary, discuss content, and complete graded tasks that demonstrate comprehension. Activities and assignments, in turn, enhance college success by allowing students to practice academic reading strategies, writing, speaking, and student-faculty and peer-peer communication and collaboration. The course components facilitate a comparison of student performance and retention in sections of the redesigned and existing online sections of Music Appreciation as well as in previous sections with at-risk students. Indirect, qualitative measures include student attitudinal surveys and evaluations. Direct, quantitative measures include withdrawal rates, tests of disciplinary knowledge, and final grades. The study will compare the outcomes of three cohorts in the two versions of the online course: ESL students, at-risk developmental students, and college-level students. These data will also be compared with retention and student outcomes data of the three cohorts in f2f Music Appreciation, which permitted non-traditional student enrollment from 1998-2005. During this eight-year period, the presenter addressed the problems of at-risk students by adding language and college success support, which resulted in strong retention and outcomes. The presenters contend that the redesigned course will produce favorable outcomes among all three cohorts because it contains components which proved successful with at-risk learners in f2f sections of the course. Results of their study will be published in 2019 after the redesigned online course has met for two semesters.

Keywords: college readiness, e-learning, music appreciation, online courses

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Authors: Maria Barriga

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The article focuses on the analysis of three images of the last five years that represent different visions of social groups in the context of the so call “Conflicto Mapuche” in la Araucanía, Chile. Using a multimodal social semiotic approach, we analyze the meaning making of these images and the social groups strategies to achieve visibility and recognition in political contexts. We explore the making and appropriation of symbols and concepts and analyze the different strategies that groups use to built hegemonic views. Among these strategies, we compare the use of digital technologies in design these images and the influence of Chilean Estate's vision on the Mapuche political conflict. Finally, we propose visual strategies to improve basic conditions for dialogue and recognition among these groups.

Keywords: visual culture, power, conflict, indigenous people

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Authors: Ai Chin Wong, Wan Ahmad Jaafar Wan Yahaya, Balakrishnan Muniandy

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This study aims to explore the impact of Virtual Reality (VR) using visual signaling principles in learning about the science laboratory safety guide; this study involves students with different spatial ability. There are two types of science laboratory safety lessons, which are Virtual Reality with Signaling (VRS) and Virtual Reality Non Signaling (VRNS). This research has adopted a 2 x 2 quasi-experimental factorial design. There are two types of variables involved in this research. The two modes of courseware form the independent variables with the spatial ability as the moderator variable. The dependent variable is the students’ performance. This study sample consisted of 141 students. Descriptive and inferential statistics were conducted to analyze the collected data. The major effects and the interaction effects of the independent variables on the independent variable were explored using the Analyses of Covariance (ANCOVA). Based on the findings of this research, the results exhibited low spatial ability students in VRS outperformed their counterparts in VRNS. However, there was no significant difference in students with high spatial ability using VRS and VRNS. Effective learning in students with different spatial ability can be boosted by implementing the Virtual Reality with Signaling (VRS) in the design as well as the development of Virtual Science Laboratory (ViSLab).

Keywords: spatial ability, science laboratory safety, visual signaling principles, virtual reality

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Authors: John Paul Q. Tomas, Mark Wilson L. de los Reyes, Kirsten Joyce P. Vasquez

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The most frequent type of fracture is a wrist fracture, which often makes it difficult for medical professionals to find and locate. In this study, fractures in wrist x-ray pictures were located and identified using deep learning and computer vision. The researchers used image filtering, masking, morphological operations, and data augmentation for the image preprocessing and trained the RetinaNet and Faster R-CNN models with ResNet50 backbones and Adam optimizers separately for each image filtering technique and projection. The RetinaNet model with Anisotropic Diffusion Smoothing filter trained with 50 epochs has obtained the greatest accuracy of 99.14%, precision of 100%, sensitivity/recall of 98.41%, specificity of 100%, and an IoU score of 56.44% for the Posteroanterior projection utilizing augmented data. For the Lateral projection using augmented data, the RetinaNet model with an Anisotropic Diffusion filter trained with 50 epochs has produced the highest accuracy of 98.40%, precision of 98.36%, sensitivity/recall of 98.36%, specificity of 98.43%, and an IoU score of 58.69%. When comparing the test results of the different individual projections, models, and image filtering techniques, the Anisotropic Diffusion filter trained with 50 epochs has produced the best classification and regression scores for both projections.

Keywords: Artificial Intelligence, Computer Vision, Wrist Fracture, Deep Learning

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Authors: Pooja Khanal, Huaming Zhang

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Labeling of issues/bugs, also known as bug classification, plays a vital role in software engineering. Some known labels/classes of bugs are 'User Interface', 'Security', and 'API'. Most of the time, when a reporter reports a bug, they try to assign some predefined label to it. Those issues are reported for a project, and each project is a repository in GitHub/GitLab, which contains multiple issues. There are many software project repositories -ranging from individual projects to commercial projects. The labels assigned for different repositories may be dependent on various factors like human instinct, generalization of labels, label assignment policy followed by the reporter, etc. While the reporter of the issue may instinctively give that issue a label, another person reporting the same issue may label it differently. This way, it is not known mathematically if a label in one repository is similar or different to the label in another repository. Hence, the primary goal of this research is to find the semantic differences between bug labeling of different repositories via machine learning. Independent optimal classifiers for individual repositories are built first using the text features from the reported issues. The optimal classifiers may include a combination of multiple classifiers stacked together. Then, those classifiers are used to cross-test other repositories which leads the result to be deduced mathematically. The produce of this ongoing research includes a formalized open-source GitHub issues database that is used to deduce the similarity of the labels pertaining to the different repositories.

Keywords: bug classification, bug labels, GitHub issues, semantic differences

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Authors: Marzieh Eshaghi Koupaei

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By cultivating mealworm, we reduce greenhouse gases and avoid the use of transgenic products such as soybeans, and we provide food resources rich in protein, amino acids, minerals, etc. for humans and animals, and it has created employment and entrepreneurship. We serve the environment by producing oil from mealworm in the cosmetic industry, using its waste as organic fertilizer and its powder in bodybuilding, and by breaking down plastic by mealworm. The production and breeding of mealworm requires very little infrastructure and does not require much trouble, and requires very little food, and reproduces easily and quickly, and a mealworm production workshop is noiseless, odorless, and pollution-free And the costs are very low. It is possible to use third grade fruits and unsalable fruits of farmers to feed the mealworms, which is completely economical and cost-effective. Mealworms can break down plastic in their intestines and turn it into carbon dioxide. . This process was done in only 16 days, which is a very short time compared to several centuries for plastic to decompose. By producing mealworm, we have helped to preserve the environment and provided the source of protein needed by humans and animals. This industrial insect has the ability and value of commercialization and creates employment and helps the economy of the society.

Keywords: breeding, production of insects, mealworms, research, animal feed, human feed

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Authors: José María Renteria, Vania Salas

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This study explores the impact of inclusive education on the educational outcomes of students without Special Educational Needs (non-SEN) in Peru, utilizing official Ministry of Education data and implementing cross-sectional regression analyses. Inclusive education is a complex issue that, without appropriate adaptations and comprehensive understanding, can present substantial challenges to the educational community. While prior research from developed nations offers diverse perspectives on the effects of inclusive education on non-SEN students, limited evidence exists regarding its impact in developing countries. Our study addresses this gap by examining inclusive education in Peru and its effects on non-SEN students, thereby contributing to the existing literature. the findings reveal that, on average, the presence of SEN students in regular classrooms does not significantly affect their non-SEN counterparts. However, we uncover heterogeneous effects contingent on the specific type of SEN and students’ academic placement. These results emphasize the importance of targeted resources, specialized teachers, and parental involvement in facilitating successful inclusive education, particularly for specific SEN types and students positioned at the lower end of the academic achievement spectrum. In summary, this study underscores the need for tailored strategies and additional resources to foster the success of inclusive education and calls for further research in this field to expand our understanding and enhance educational policy.

Keywords: inclusive education, special educational needs, learning achievement, Peru, Basic education

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Authors: Marcia Figueira

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Context: Positivist transformations in agriculture were responsible for top-down – often coercive – mechanisms of uniformed modernization that weathered local diversities and agency. New development pathways need to now shift according to comprehensive integrations of knowledge - scientific, indigenous, and local, and to be sustained on political interventions, bottom-up change, and social learning if climate goals are to be met – both in mitigation and adaptation. Objectives The objectives of this research are to understand how social-ecological and socio-technical systems characterisation can be nested to bridge scientific research/knowledge into a local context and knowledge system; and, with it, stem sustainable innovation. Methods To do so, we conducted a scoping review to explore theoretical and empirical works linked to Ostrom’s Social-Ecological Systems framework and Geels’ multi-level perspective of socio-technical systems transformations in the context of agriculture. Results As a result, we were able to identify key variables and connections to 1- understand the rules in use and the community attributes influencing resource management; and 2- how they are and have been shaped and shaping systems innovations. Conclusion Based on these results, we discuss how to leverage action research for mutual learning toward a replicable but highly place-based agriculture transformation frame.

Keywords: agriculture systems innovations, social-ecological systems, socio-technical systems, action research

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Authors: Shan Zhang, Peter Suechting

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Predicting trade patterns is critical to decision-making in public and private domains, especially in the current context of trade disputes among major economies. In the past, U.S. recycling has relied heavily on strong demand for recyclable materials overseas. However, starting in 2017, a series of new recycling policies (bans and higher inspection standards) was enacted by multiple countries that were the primary importers of recyclables from the U.S. prior to that point. As the global trade flow of recycling shifts, some new importers, mostly developing countries in South and Southeast Asia, have been overwhelmed by the sheer quantities of scrap materials they have received. As the leading exporter of recyclable materials, the U.S. now has a pressing need to build its recycling industry domestically. With respect to the global trade in scrap materials used for recycling, the interest in this paper is (1) predicting how the export of recyclable materials from the U.S. might vary over time, and (2) predicting how international trade flows for recyclables might change in the future. Focusing on three major recyclable materials with a history of trade, this study uses data-driven and machine learning (ML) algorithms---supervised (shrinkage and tree methods) and unsupervised (neural network method)---to decipher the international trade pattern of recycling. Forecasting the potential trade values of recyclables in the future could help importing countries, to which those materials will shift next, to prepare related trade policies. Such policies can assist policymakers in minimizing negative environmental externalities and in finding the optimal amount of recyclables needed by each country. Such forecasts can also help exporting countries, like the U.S understand the importance of healthy domestic recycling industry. The preliminary result suggests that gravity models---in addition to particular selection macroeconomic predictor variables--are appropriate predictors of the total export value of recyclables. With the inclusion of variables measuring aspects of the political conditions (trade tariffs and bans), predictions show that recyclable materials are shifting from more policy-restricted countries to less policy-restricted countries in international recycling trade. Those countries also tend to have high manufacturing activities as a percentage of their GDP.

Keywords: environmental economics, machine learning, recycling, international trade

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Authors: Laura Otto

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Sargasso algae currently threatens both livelihoods and marine eco systems along the Riviera Maya in Mexico. While the area was previously known for its white beaches, pristine waters, and intact, colorful reefs, the algae has turned the beaches into ‘stinky stretches of sand,’ made the water brown, and has led to reef degradation causing coral colonies to die off in vast amounts. Drawing on ethnographic research in the area, this paper shows how the reef was exploited for tourism before the Sargasso algae landed, and reef protection played a minor role among hoteliers, tourists, and tour operators. However, since Sargasso began arriving in large quantities, the reef has taken on new significance. Both natural science research and the everyday handling of Sargasso along the coast show that an intact reef provides a natural barrier for the algae and keeps them from reaching the beaches. Clean beaches are important to various local actors–among them, hotel operators, tourists, environmentalists – and against the backdrop of beach commodification, reefs are now taking on new meaning. The paper consequently discusses the commodification of beaches as more-than-human entanglements and illuminates which new human-environment relationships are currently emerging in the Anthropocene.

Keywords: anthropocene, human-environment-relations, fieldwork, mexico

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Authors: Sneha Shankar, Orlando Buendia, Will Evans

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Alpha-1 antitrypsin deficiency (AATD) is a rare, genetic, and multisystemic condition. Underdiagnosis is common, leading to chronic pulmonary and hepatic complications, increased resource utilization, and additional costs to the healthcare system. Currently, there is limited evidence of the direct medical costs of AATD diagnosis in the UK. This study explores the economic impact of AATD patients during the 3 years before diagnosis and to identify the major cost drivers using primary and secondary care electronic health record (EHR) data. The 3 years before diagnosis time period was chosen based on the ability of our tool to identify patients earlier. The AATD algorithm was created using published disease criteria and applied to 148 known AATD patients’ EHR found in a primary care database of 936,148 patients (413,674 Biobank and 501,188 in a single primary care locality). Among 148 patients, 9 patients were flagged earlier by the tool and, on average, could save 3 (1-6) years per patient. We analysed 101 of the 148 AATD patients’ primary care journey and 20 patients’ Hospital Episode Statistics (HES) data, all of whom had at least 3 years of clinical history in their records before diagnosis. The codes related to laboratory tests, clinical visits, referrals, hospitalization days, day case, and inpatient admissions attributable to AATD were examined in this 3-year period before diagnosis. The average cost per patient was calculated, and the direct medical costs were modelled based on the mean prevalence of 100 AATD patients in a 500,000 population. A deterministic sensitivity analysis (DSA) of 20% was performed to determine the major cost drivers. Cost data was obtained from the NHS National tariff 2020/21, National Schedule of NHS Costs 2018/19, PSSRU 2018/19, and private care tariff. The total direct medical cost of one hundred AATD patients three years before diagnosis in primary and secondary care in the UK was £3,556,489, with an average direct cost per patient of £35,565. A vast majority of this total direct cost (95%) was associated with inpatient admissions (£3,378,229). The DSA determined that the costs associated with tier-2 laboratory tests and inpatient admissions were the greatest contributors to direct costs in primary and secondary care, respectively. This retrospective study shows the role of EHRs in calculating direct medical costs and the potential benefit of new technologies for the early identification of patients with AATD to reduce the economic burden in primary and secondary care in the UK.

Keywords: alpha-1 antitrypsin deficiency, costs, digital health, early diagnosis

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Authors: Felicia Titilayo Olanrewaju

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Folktales are a subclass of folklores which are verbally told and passed down from one generation to another, from the elderly ones to their children, usually at moonlight. These tales are heavily laden with moral lessons of what should be done and what not within the society. Though these are oftentimes heavily embellished yet are related to guide, guard, train, and dishing out moral attributes and mores worthwhile for ethical progression of the young minds within our traditional settings. With the rapid advancement of technological know-how, the existence of most of these moral-inclined stories becomes questionable; hence this study appraised the influences of these traditional storytellings have in the upgrading of moral learning of ethical behavioral traits acceptable among the Yoruba people. Oral interviews couples with recording gadgets were used to collate both sample parents' and children’s responses within a particular community in Owo (ute) local government area of Owo Ondo State, Nigeria. Findings reveal that diverse tales told at moonlight periods have an untold impact on the speedy growth of the children intellectually than the modern happenings around them. These telltale stories become powerful aids in learning goodly traits and eschewing bad manners. It is recommended that folk stories be told within the household among the family after hard labour in the evenings as this would help develop human relationships and brings about a strong sense of community bindings.

Keywords: folktales, folklores, impact, advancement, ethical progression

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Authors: Kharina Budiman, Adinda Syifa Azhari, Eleonora Agustine

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Industrial activities get increase in this globalization era, one of the major impacts of industrial activities is a problem to the environment. This can happen because at the industrial production term will bring out pollutant in the shape of solid, liquid or gas. Normally this pollutant came from some dangerous materials for environment. However not every industry produces the same amount of pollutant, every industry produces different kind of pollution. To compare the pollution impact of industrial activities, soil sample has been taken around the animal feed industry and the fertilizer industry. This study applied the rock magnetic method and used Bartington MS2B to measured magnetic susceptibility (χ) as the physical parameter. This study tested soil samples using the value of susceptibility low frequency (χ lf) and Frequency Dependent (χ FD). Samples only taken in the soil surface with 0-5 cm depth and sampling interval was 20 cm. The animal feed factory has susceptibility low frequency (χ lf) = 111,9 – 325,7 and Frequency Dependent (χ FD) = 0,8 – 3,57 %. And the fertilizer factory has susceptibility low frequency (χ lf) = 187,1 – 494,8 and Frequency Dependent (χ FD) = 1,37 – 2,46 %. Based on the results, the highest value of susceptibility low frequency (χ lf) is the fertilizer factory, but the highest value of Frequency Dependent (FD) is the animal feed factory.

Keywords: industrial, pollution, magnetic susceptibility, χlf, χfd, animal feed industry and fertilizer industry

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Authors: Schröde C., Rodriguez D., Sánchez A., Abdul Malak, Churchill J., Boksmati T., Alharbi, Alsulmi H., Maghrabi S., Mowalad, Mutwalli R., Abualnaja Y.

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Formulating a strategy for sustainable development of the Kingdom of Saudi Arabia’s coastal and marine environment is at the core of the “Marine and Coastal Protection Assessment Study for the Kingdom of Saudi Arabia Coastline (MCEP)”; that was set up in the context of the Vision 2030 by the Saudi Arabian government and aimed at providing a first comprehensive ‘Status Quo Assessment’ of the Kingdom’s marine environment to inform a sustainable development strategy and serve as a baseline assessment for future monitoring activities. This baseline assessment relied on scientific evidence of the drivers, pressures and their impact on the environments of the Red Sea and Arabian Gulf. A key element of the assessment was the cumulative pressure hotspot analysis developed for both national waters of the Kingdom following the principles of the Driver-Pressure-State-Impact-Response (DPSIR) framework and using the cumulative pressure and impact assessment methodology. The ultimate goals of the analysis were to map and assess the main hotspots of environmental pressures, and identify priority areas for further field surveillance and for urgent management actions. The study identified maritime transport, fisheries, aquaculture, oil, gas, energy, coastal industry, coastal and maritime tourism, and urban development as the main drivers of pollution in the Saudi Arabian marine waters. For each of these drivers, pressure indicators were defined to spatially assess the potential influence of the drivers on the coastal and marine environment. A list of hotspots of 90 locations could be identified based on the assessment. Spatially grouped the list could be reduced to come up with of 10 hotspot areas, two in the Arabian Gulf, 8 in the Red Sea. The hotspot mapping revealed clear spatial patterns of drivers, pressures and hotspots within the marine environment of waters under KSA’s maritime jurisdiction in the Red Sea and Arabian Gulf. The cascading assessment approach based on the DPSIR framework ensured that the root causes of the hotspot patterns, i.e. the human activities and other drivers, can be identified. The adapted CPIA methodology allowed for the combination of the available data to spatially assess the cumulative pressure in a consistent manner, and to identify the most critical hotspots by determining the overlap of cumulative pressure with areas of sensitive biodiversity. Further improvements are expected by enhancing the data sources of drivers and pressure indicators, fine-tuning the decay factors and distances of the pressure indicators, as well as including trans-boundary pressures across the regional seas.

Keywords: Arabian Gulf, DPSIR, hotspot, red sea

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Authors: Angela Vacaro de Souza, Fernando Ferrari Putti

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One of the main plants cultivated in protected environment is tomato crop, which presents significant growth in its demand, because it is a tasty fruit, rich in nutrients and of high added value, however, poor management of fertilizers induces the process of soil salinization, causing several consequences, from reduced productivity to even soil infertility. These facts are derived from the increased concentration of salts, which hampers the process of water absorption by the plant, resulting in a biochemical and nutritional imbalance in the plant. Thus, this study aimed to investigate the effects of untreated and electromagnetically treated water in salinized soils on physical, physicochemical, and biochemical parameters in tomato fruits. The experiment was conducted at the Faculty of Science and Engineering, Tupã Campus (FCE/UNESP). A randomized complete block design with two types of treated water was adopted, with five different levels of initial salinity (0; 1.5; 2.5; 4; 5.5; 7 dS m⁻¹) by fertigation. Although the effects of salinity on fruit quality parameters are evident, no beneficial effects on increasing or maintaining postharvest quality of fruits whose plants were treated with electromagnetized water were evidenced.

Keywords: Solanum lycopersicum, soil salinization, protected environment, fertigation

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Authors: Christopher Thornton, Niina Kolehmainen, Kianoush Nazarpour

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Background: Accelerometers are widely used to measure physical activity behavior, including in children. The traditional method for processing acceleration data uses cut points, relying on calibration studies that relate the quantity of acceleration to energy expenditure. As these relationships do not generalise across diverse populations, they must be parametrised for each subpopulation, including different age groups, which is costly and makes studies across diverse populations difficult. A data-driven approach that allows physical activity intensity states to emerge from the data under study without relying on parameters derived from external populations offers a new perspective on this problem and potentially improved results. We evaluated the data-driven approach in a diverse population with a range of rapidly evolving physical and mental capabilities, namely very young children (9-38 months old), where this new approach may be particularly appropriate. Methods: We applied an unsupervised machine learning approach (a hidden semi-Markov model - HSMM) to segment and cluster the accelerometer data recorded from 275 children with a diverse range of physical and cognitive abilities. The HSMM was configured to identify a maximum of six physical activity intensity states and the output of the model was the time spent by each child in each of the states. For comparison, we also processed the accelerometer data using published cut points with available thresholds for the population. This provided us with time estimates for each child’s sedentary (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA). Data on the children’s physical and cognitive abilities were collected using the Paediatric Evaluation of Disability Inventory (PEDI-CAT). Results: The HSMM identified two inactive states (INS, comparable to SED), two lightly active long duration states (LAS, comparable to LPA), and two short-duration high-intensity states (HIS, comparable to MVPA). Overall, the children spent on average 237/392 minutes per day in INS/SED, 211/129 minutes per day in LAS/LPA, and 178/168 minutes in HIS/MVPA. We found that INS overlapped with 53% of SED, LAS overlapped with 37% of LPA and HIS overlapped with 60% of MVPA. We also looked at the correlation between the time spent by a child in either HIS or MVPA and their physical and cognitive abilities. We found that HIS was more strongly correlated with physical mobility (R²HIS =0.5, R²MVPA= 0.28), cognitive ability (R²HIS =0.31, R²MVPA= 0.15), and age (R²HIS =0.15, R²MVPA= 0.09), indicating increased sensitivity to key attributes associated with a child’s mobility. Conclusion: An unsupervised machine learning technique can segment and cluster accelerometer data according to the intensity of movement at a given time. It provides a potentially more sensitive, appropriate, and cost-effective approach to analysing physical activity behavior in diverse populations, compared to the current cut points approach. This, in turn, supports research that is more inclusive across diverse populations.

Keywords: physical activity, machine learning, under 5s, disability, accelerometer

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Authors: Rungpansa Noichan, Bart Julian Dewancker

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The conservation and regeneration of historical industrial building is one of the most important issues to be solved in today’s urban development in the world. There are growing numbers of industrial building in which promoting heritage conservation maybe a helpful tool for a sustainable city in social, urban restructuring, environmental and economic component. This paper identifies the key attributes of conservation and regeneration industrial building from the literature, were discussed by reviewing its development at home and abroad. The authors have investigated 93 industrial buildings, which were used as industrial building before and reused into buildings with another function afterward. The data to be discussed below were mainly collected from various publications but also from available internet sources. This study focuses on green transformation, historical culture heritage, transformation techniques, and urban regeneration based on the empirical researches on the historical industrial building and site. Moreover, we focus on social, urban environment and sustainable development. The implications of the study provide suggestions for future improvements in the conservation and regeneration of historical industrial building, and inspire new ways of use, so the building becomes flexible and can consequently be adaptable to changes in order to survive time. Therefore, the building does not take into account only its future impact in the environment and society. Instead, it focuses on its entire life cycle.

Keywords: industrial building, heritage conservation, green transformation, regeneration, sustainable development

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Authors: Alexandra P. Alexandropoulou, Andreas Fousteris, Eleni Didaskalou, Dimitrios A. Georgakellos

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As urbanization is becoming a major stress factor not only for the urban environment but also for the wellbeing of city dwellers, incorporating the issues of urban health in strategic city planning and policy-making has never been more relevant. The impact of urbanization can vary from low to severe and relates to all non-communicable diseases caused by the different functions of cities. Air pollution, noise pollution, water and soil pollution, availability of open green spaces, and urban heat island are the major factors that can compromise citizens' health. Urban health describes the effects of the social environment, the physical environment, and the availability and accessibility to health and social services. To assess the quality of urban wellbeing, all urban characteristics that might have an effect on citizens' health must be considered, evaluated, and introduced in integrated local planning. A series of indices and indicators can be used to better describe these effects and set the target values in policy making. Local strategic planning is one of the most valuable development tools a local city administration can possess; thus, it has become mandatory under Greek law for all municipalities. It involves a two-stage procedure; the first aims to collect, analyse and evaluate data on the current situation of the city (administrative data, population data, environmental data, social data, swot analysis), while the second aims to introduce a policy vision described and supported by distinct (nevertheless integrated) actions, plans and measures to be implemented with the aim of city development and citizen wellbeing. In this procedure, the element of health is often neglected or under-evaluated. A relative survey was conducted among all Greek local authorities in order to shed light on the current situation. Evidence shows that the rate of incorporation of health in strategic planning is lacking behind. The survey also highlights key hindrances and concerns raised by local officials and suggests a path for the way forward.

Keywords: urban health, strategic planning, local authorities, integrated development

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Authors: Jutharat Sunprasert, Ekapong Hirunsirisawat, Narongrit Waraporn, Somporn Peansukmanee

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Metal Ship and Robotic Car is one of the hands-on activities in the course, the Fundamental of Engineering that can be divided into three parts. The first part, the metal ships, was made by using engineering drawings, physics and mathematics knowledge. The second part is where the students learned how to construct a robotic car and control it using computer programming. In the last part, the students had to combine the workings of these two objects in the final testing. This aim of study was to investigate the effectiveness of hands-on activity by integrating Science, Technology, Engineering and Mathematics (STEM) concepts to develop scientific and engineering skills. The results showed that the majority of students felt this hands-on activity lead to an increased confidence level in the integration of STEM. Moreover, 48% of all students engaged well with the STEM concepts. Students could obtain the knowledge of STEM through hands-on activities with the topics science and mathematics, engineering drawing, engineering workshop and computer programming; most students agree and strongly agree with this learning process. This indicated that the hands-on activity: “Metal Ship and Robotic Car” is a useful tool to integrate each aspect of STEM. Furthermore, hands-on activities positively influence a student’s interest which leads to increased learning achievement and also in developing scientific and engineering skills.

Keywords: hands-on activity, STEM education, computer programming, metal work

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Authors: Essam Gooda, Chadi Abdallah, Hamdi Seif, Safaa Baydoun, Rouya Hdeib, Hilal Obeid

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Floods are common natural disaster occurring in semi-arid regions in Lebanon. This results in damage to human life and deterioration of environment. Despite their destructive nature and their immense impact on the socio-economy of the region, flash floods have not received adequate attention from policy and decision makers. This is mainly because of poor understanding of the processes involved and measures needed to manage the problem. The current understanding of flash floods remains at the level of general concepts; most policy makers have yet to recognize that flash floods are distinctly different from normal riverine floods in term of causes, propagation, intensity, impacts, predictability, and management. Flash floods are generally not investigated as a separate class of event but are rather reported as part of the overall seasonal flood situation. As a result, Lebanon generally lacks policies, strategies, and plans relating specifically to flash floods. Main objective of this research is to improve flash flood prediction by providing new knowledge and better understanding of the hydrological processes governing flash floods in the East Catchments of El Assi River. This includes developing rainstorm time distribution curves that are unique for this type of study region; analyzing, investigating, and developing a relationship between arid watershed characteristics (including urbanization) and nearby villages flow flood frequency in Ras Baalbeck and Fekha. This paper discusses different levels of integration approach¬es between GIS and hydrological models (HEC-HMS & HEC-RAS) and presents a case study, in which all the tasks of creating model input, editing data, running the model, and displaying output results. The study area corresponds to the East Basin (Ras Baalbeck & Fakeha), comprising nearly 350 km2 and situated in the Bekaa Valley of Lebanon. The case study presented in this paper has a database which is derived from Lebanese Army topographic maps for this region. Using ArcMap to digitizing the contour lines, streams & other features from the topographic maps. The digital elevation model grid (DEM) is derived for the study area. The next steps in this research are to incorporate rainfall time series data from Arseal, Fekha and Deir El Ahmar stations to build a hydrologic data model within a GIS environment and to combine ArcGIS/ArcMap, HEC-HMS & HEC-RAS models, in order to produce a spatial-temporal model for floodplain analysis at a regional scale. In this study, HEC-HMS and SCS methods were chosen to build the hydrologic model of the watershed. The model then calibrated using flood event that occurred between 7th & 9th of May 2014 which considered exceptionally extreme because of the length of time the flows lasted (15 hours) and the fact that it covered both the watershed of Aarsal and Ras Baalbeck. The strongest reported flood in recent times lasted for only 7 hours covering only one watershed. The calibrated hydrologic model is then used to build the hydraulic model & assessing of flood hazards maps for the region. HEC-RAS Model is used in this issue & field trips were done for the catchments in order to calibrated both Hydrologic and Hydraulic models. The presented models are a kind of flexible procedures for an ungaged watershed. For some storm events it delivers good results, while for others, no parameter vectors can be found. In order to have a general methodology based on these ideas, further calibration and compromising of results on the dependence of many flood events parameters and catchment properties is required.

Keywords: flood risk management, flash flood, semi arid region, El Assi River, hazard maps

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Authors: Tahmina Huq

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This paper presents the findings of an action research study that aimed to investigate the efficacy of a visual dialogue strategy in assisting autistic students with intellectual disabilities in managing their immediate emotions and improving their academic achievements. The research sought to explore the effectiveness of teaching self-regulation techniques as an alternative to traditional approaches involving segregation. The study identified visual dialogue as a valuable tool for promoting self-regulation in this specific student population. Action research was chosen as the methodology due to its suitability for immediate implementation of the findings in the classroom. Autistic students with intellectual disabilities often face challenges in controlling their emotions, which can disrupt their learning and academic progress. Conventional methods of intervention, such as isolation and psychologist-assisted approaches, may result in missed classes and hindered academic development. This study introduces the utilization of visual dialogue between students and teachers as an effective self-regulation strategy, addressing the limitations of traditional approaches. Action research was employed as the methodology for this study, allowing for the direct application of the findings in the classroom. The study observed two 15-year-old autistic students with intellectual disabilities who exhibited difficulties in emotional regulation and displayed aggressive behaviors. The research question focused on the effectiveness of visual dialogue in managing the emotions of these students and its impact on their learning outcomes. Data collection methods included personal observations, log sheets, personal reflections, and visual documentation. The study revealed that the implementation of visual dialogue as a self-regulation strategy enabled the students to regulate their emotions within a short timeframe (10 to 30 minutes). Through visual dialogue, they were able to express their feelings and needs in socially appropriate ways. This finding underscores the significance of visual dialogue as a tool for promoting emotional regulation and facilitating active participation in classroom activities. As a result, the students' learning outcomes and social interactions were positively impacted. The findings of this study hold significant implications for educators working with autistic students with intellectual disabilities. The use of visual dialogue as a self-regulation strategy can enhance emotional regulation skills and improve overall academic progress. The action research approach outlined in this paper provides practical guidance for educators in effectively implementing self-regulation strategies within classroom settings. In conclusion, the study demonstrates that visual dialogue is an effective strategy for enhancing emotional regulation in autistic students with intellectual disabilities. By employing visual communication, students can successfully regulate their emotions and actively engage in classroom activities, leading to improved learning outcomes and social interactions. This paper underscores the importance of implementing self-regulation strategies in educational settings to cater to the unique needs of autistic students.

Keywords: action research, self-regulation, autism, visual communication

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Authors: Yash Bingi, Yiqiao Yin

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Reduction of child mortality is an ongoing struggle and a commonly used factor in determining progress in the medical field. The under-5 mortality number is around 5 million around the world, with many of the deaths being preventable. In light of this issue, Cardiotocograms (CTGs) have emerged as a leading tool to determine fetal health. By using ultrasound pulses and reading the responses, CTGs help healthcare professionals assess the overall health of the fetus to determine the risk of child mortality. However, interpreting the results of the CTGs is time-consuming and inefficient, especially in underdeveloped areas where an expert obstetrician is hard to come by. Using a support vector machine (SVM) and oversampling, this paper proposed a model that classifies fetal health with an accuracy of 99.59%. To further explain the CTG measurements, an algorithm based on Randomized Input Sampling for Explanation ((RISE) of Black-box Models was created, called Feature Alteration for explanation of Black Box Models (FAB), and compared the findings to Shapley Additive Explanations (SHAP) and Local Interpretable Model Agnostic Explanations (LIME). This allows doctors and medical professionals to classify fetal health with high accuracy and determine which features were most influential in the process.

Keywords: machine learning, fetal health, gradient boosting, support vector machine, Shapley values, local interpretable model agnostic explanations

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Authors: Merina Islam

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There are many environmental problems. Various counter measures have been taken for environmental problems. Philosophy is an important contributor to environmental studies as it takes deep interest in meaning analysis of the concept environment and other related concepts. The Buddhist frame, which is virtue ethical, remains a better alternative to the traditional environmental outlook. Granting the unique role of man in immoral deliberations, the Buddhist approach, however, maintains a holistic concept of ecological harmony. Buddhist environmental ethics is more concerned about the complete moral community, the total ecosystem, than any particular species within the community. The moral reorientation proposed here has resemblance to the concept of 'deep ecology. Given the present day prominence of virtue ethics, we need to explore further into the Buddhist virtue theory, so that a better framework to treat the natural world would be ensured. Environment has turned out to be one of the most widely discussed issues in the recent times. Buddhist concepts such as Pratityasamutpadavada, Samvrit Satya, Paramartha Satya, Shunyata, Sanghatvada, Bodhisattva, Santanvada and others deal with interdependence in terms of both internal as well external ecology. The internal ecology aims at mental well-being whereas external ecology deals with physical well-being. The fundamental Buddhist concepts for dealing with environmental Problems are where the environment has the same value as humans as from the two Buddhist doctrines of the Non-duality of Life and its Environment and the Origination in Dependence; and the inevitability of overcoming environmental problems through the practice of the way of the Bodhisattva, because environmental problems are evil for people and nature. Buddhism establishes that there is a relationship among all the constituents of the world. There is nothing in the world which is independent from any other thing. Everything is dependent on others. The realization that everything in the universe is mutually interdependent also shows that the man cannot keep itself unaffected from ecology. This paper would like to focus how the Buddhist’s identification of nature and the Dhamma can contribute toward transforming our understanding, attitudes, and actions regarding the care of the earth. Environmental Ethics in Buddhism presents a logical and thorough examination of the metaphysical and ethical dimensions of early Buddhist literature. From the Buddhist viewpoint, humans are not in a category that is distinct and separate from other sentient beings, nor are they intrinsically superior. All sentient beings are considered to have the Buddha-nature, that is, the potential to become fully enlightened. Buddhists do not believe in treating of non-human sentient beings as objects for human consumption. The significance of Buddhist theory of interdependence can be understood from the fact that it shows that one’s happiness or suffering originates from ones realization or non-realization respectively of the dependent nature of everything. It is obvious, even without emphasis, which in the context of deep ecological crisis of today there is a need to infuse the consciousness of interdependence.

Keywords: Buddhism, deep ecology, environmental problems, Pratityasamutpadavada

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Authors: Akpokiere Ugbede Roseline

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Chemistry is an activity oriented subject in which many students achievement over the years are not encouraging. Among the reasons found to be responsible for student’s poor performance in chemistry are ineffective teaching strategies. This study, therefore, sought to determine the effect of guided inquiry, guided inquiry with demonstration, and demonstration with conventional approach on pre-service teachers’ cognitive attainment and practical skills acquisition on stoichiometry and chemical reactions in practical chemistry, Two research questions and hypotheses were each answered and tested respectively. The study was a quasi-experimental research involving 50 students in each of the experimental groups and 50 students in the control group. Out of the five instruments used for the study, three were on stimulus and two on response (Test of Cognitive Attainment and Test of Practical Skills in Chemistry) instruments administered, and dataobtained were analyzed with t-test and Analysis of Variance. Findings revealed, among others, that there was a significant effect of treatments on students' cognitive attainment and on practical skills acquisition. Students exposed to guided inquiry (with/without demonstration) strategies achieved better than those exposed to demonstration with conventional strategy. It is therefore recommended, among others, that Lecturers in Colleges of Education should utilize the guided inquiry strategy for teaching concepts in chemistry.

Keywords: instructional strategy, practical chemistry, learning outcomes, pre-service teachers

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Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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