Search results for: learning loss

Authors: Surichai Butcha, Dararat Khampusaen

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As the Internet is recognized as a high potential and powerful educational tool to access sources of knowledge, plagiarism is an increasing unethical issue found in students’ writing. This paper is deriving from the 1st phase of an on-going study investigating the effects of the supplementary on citing sources on undergraduate students’ writing. The 40 participants were divided into 1 experimental group and 1 control group. Both groups were administered with a questionnaire on knowledge and an interview on attitude related to using sources in writing. Only the experimental group undertook the 4 lessons focusing on using outside sources and citing the original work (quoting, synthesizing, summarizing and paraphrasing) were delivered to them via e-learning tools throughout a semester. Participants were required to produce 4 writing tasks after each lesson. The results were concerned with types and factors on using outside sources in writing of Thai undergraduate EFL students from the survey. The interview results supported and clarified the survey result. In addition, the writing rubrics confirmed the types of plagiarism frequently occurred in students’ writing. The results revealed the types and factors on plagiarism including their perceptions on using the outside sources in their writing from the interview. The discussion shed the lights on cultural dimensions of plagiarism in student writing, roles of teachers, library, and university policy on the rate of plagiarism. Also, the findings promoted the awareness on ethics in writing and prevented the rate of potential unintentional plagiarism. Additionally, the results of this phase of study could lead to the appropriate contents to be considered for inclusion in the supplementary on using sources for writing for future research.

Keywords: citing source, EFL writing, e-learning, Internet, plagiarism

Procedia PDF Downloads 137

Authors: Nathaniel Carpenter

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Web-enabled systems for supporting youth mental health management in Australia are pioneering in their field; however, with their success, these systems are experiencing exponential growth in demand which is straining an already stretched service. Supporting youth mental is critical as the lack of support is associated with significant and lasting negative consequences. To meet this growing demand, and provide critical support, investigations are needed on evaluating and improving existing online support services. Improvements should focus on developing frameworks capable of augmenting and scaling service provisions. There are few investigations informing best-practice frameworks when implementing e-mental health support systems for youth mental health; there are fewer which implement machine learning or artificially intelligent systems to facilitate the delivering of services. This investigation will use a case study methodology to highlight the design features which are important for systems to enable young people to self-manage their mental health. The investigation will also highlight the current information system challenges, to include challenges associated with service quality, provisioning, and scaling. This work will propose methods of meeting these challenges through improved design, service augmentation and automation, service quality, and through artificially intelligent inspired solutions. The results of this study will inform a framework for supporting youth mental health with intelligent and scalable web-enabled technologies to support an ever-growing user base.

Keywords: artificial intelligence, information systems, machine learning, youth mental health

Procedia PDF Downloads 95

Authors: Molly Gerrish

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This work explores the physical, emotional, social, and cognitive risks and benefits related to nature-based teaching and highlights the importance of promoting a sustainable workforce within early childhood programs. Assessing and managing risks can help programs reimagine their approach to teaching, learning, recruitment, family connectivity, and staff motivation. The importance of staff sustainability and motivation/engagement related to social justice and the environment will be discussed. We will explore ways to manage fears and limitations faced by early childhood programs regarding nature experiences and risky play in a variety of locations using a lens of place-based learning. We will also examine the alignment of sustainability and social-emotional development, mental health supports, social awareness, and risk assessment. The work will discuss the varied perceptions of risk in diverse areas and the impact on the early childhood workforce. Motivational theory and compassion resiliency are hallmarks of both recruiting and retaining high-quality early childhood educators; the work will discuss how to balance programmatic constraints and healthy motivation for students and teachers while empowering individuals to advocate for their mental health and well-being. Finally, the work will highlight the positive impact of nature-based teaching practices and the overall benefit to young children and their educators.

Keywords: child’s rights, inclusion, nature-based education, risk assessment

Procedia PDF Downloads 45

Authors: Yibeltal Chanie Manie, Zebider Asire Munyelet

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5G and 6G technology offers enhanced quality of service with high data transmission rates, which necessitates the implementation of the Internet of Things (IoT) in 5G/6G architecture. In this paper, we proposed the integration of free space optical communication (FSO) with fiber sensor networks for IoT applications. Recently, free-space optical communications (FSO) are gaining popularity as an effective alternative technology to the limited availability of radio frequency (RF) spectrum. FSO is gaining popularity due to flexibility, high achievable optical bandwidth, and low power consumption in several applications of communications, such as disaster recovery, last-mile connectivity, drones, surveillance, backhaul, and satellite communications. Hence, high-speed FSO is an optimal choice for wireless networks to satisfy the full potential of 5G/6G technology, offering 100 Gbit/s or more speed in IoT applications. Moreover, machine learning must be integrated into the design, planning, and optimization of future optical wireless communication networks in order to actualize this vision of intelligent processing and operation. In addition, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. Moreover, we proposed deep learning techniques to estimate the strain changes and peak wavelength of multiple Fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment.

Keywords: optical sensor, artificial Intelligence, Internet of Things, free-space optics

Procedia PDF Downloads 43

Authors: Y. Galerkin, K. Soldatova, A. Drozdov

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The 6th version of Universal modeling method for centrifugal compressor stage calculation is described. Identification of the new mathematical model was made. As a result of identification the uniform set of empirical coefficients is received. The efficiency definition error is 0,86 % at a design point. The efficiency definition error at five flow rate points (except a point of the maximum flow rate) is 1,22 %. Several variants of the stage with 3D impellers designed by 6th version program and quasi three-dimensional calculation programs were compared by their gas dynamic performances CFD (NUMECA FINE TURBO). Performance comparison demonstrated general principles of design validity and leads to some design recommendations.

Keywords: compressor design, loss model, performance prediction, test data, model stages, flow rate coefficient, work coefficient

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Authors: Malul Miki, Rafi Bar-El, Eithan Hourie

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In this article, we test the influence of an occupation as a calling on the value of job security and its connection with wage levels. Our sample consists of 495 workers in Israel from 10 occupations in the public sector, who are assumed to have a relatively high level of job security, and the private sector, who are assumed to have less job security or none at all. These 10 occupations are social workers, lecturers, lawyers, administration workers, accountants, high school teachers, bank workers, high-tech worker, nurses and psychologists. Using regression analysis, we find that those who have occupations that the literature has defined as a calling value job security less than those in ordinary employment. In addition, salary level has no effect on this relationship. Finally, those who work in occupations that are regarded as a calling have less status quo bias than those in ordinary employment.

Keywords: calling, loss aversion, job security, status quo bias

Procedia PDF Downloads 91

Authors: M. Djekoun, H. Berrebah, M. R. Djebar

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Fusarium wilt attacks the plants of major economic interest including wheat. This disease causes many problems for farmers and economic loss resulting are often very heavy. Chemical control is currently one of the most effective ways to fight against these diseases. In this study, the efficacy of three fungicides (tebuconazole, thiram and fludioxonil - difenoconazole mixture) was tested, in vitro, on the phytopathogenic Fusarium sp. isolated from seeds of wheat. The active ingredients were tested at different concentrations: 0.06, 1.39, 2.79, 5.58, and 11.16 mg/l for tebuconazole, 0.035, 0.052, 0.105, 0.21, and 0.42 mg/l for thiram and finally, for the mixture fludioxonil- difenoconazole 4 concentrations were tested : 0.05, 0.1, 0.5, and 1 mg/l. Toxicity responses were expressed as the effective concentration, which inhibits mycelial growth by 50%, (EC50). Of the three selected fungicides, thirame proved to be the most effective with EC50 value of the order of 0,15 mg/l followed by the mixture of fludioxonil- difenoconazole with 0,27 mg/l and finally tebuconazole with a value of 3.79 mg/l.

Keywords: Fusarium sp, thiram, tebuconazole, fludioxonil, difenoconazole, EC50

Procedia PDF Downloads 524

Authors: Zheng Wang, Zhenhong Li, Jon Mills

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Ground-based synthetic aperture radar (GBSAR) represents a powerful remote sensing tool for deformation monitoring towards various geohazards, e.g. landslides, mudflows, avalanches, infrastructure failures, and the subsidence of residential areas. Unlike spaceborne SAR with a fixed revisit period, GBSAR data can be acquired with an adjustable temporal resolution through either continuous or discontinuous operation. However, challenges arise from processing high temporal-resolution continuous GBSAR data, including the extreme cost of computational random-access-memory (RAM), the delay of displacement maps, and the loss of temporal evolution. Moreover, repositioning errors between discontinuous campaigns impede the accurate measurement of surface displacements. Therefore, a versatile package with two complete chains is developed in this study in order to process both continuous and discontinuous GBSAR data and address the aforementioned issues. The first chain is based on a small-baseline subset concept and it processes continuous GBSAR images unit by unit. Images within a window form a basic unit. By taking this strategy, the RAM requirement is reduced to only one unit of images and the chain can theoretically process an infinite number of images. The evolution of surface displacements can be detected as it keeps temporarily-coherent pixels which are present only in some certain units but not in the whole observation period. The chain supports real-time processing of the continuous data and the delay of creating displacement maps can be shortened without waiting for the entire dataset. The other chain aims to measure deformation between discontinuous campaigns. Temporal averaging is carried out on a stack of images in a single campaign in order to improve the signal-to-noise ratio of discontinuous data and minimise the loss of coherence. The temporal-averaged images are then processed by a particular interferometry procedure integrated with advanced interferometric SAR algorithms such as robust coherence estimation, non-local filtering, and selection of partially-coherent pixels. Experiments are conducted using both synthetic and real-world GBSAR data. Displacement time series at the level of a few sub-millimetres are achieved in several applications (e.g. a coastal cliff, a sand dune, a bridge, and a residential area), indicating the feasibility of the developed GBSAR data processing package for deformation monitoring of a wide range of scientific and practical applications.

Keywords: ground-based synthetic aperture radar, interferometry, small baseline subset algorithm, deformation monitoring

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Authors: Jarrod Sio Jyh Lih

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This paper discusses the factors contributing to student achievement in literacy and numeracy in primary schools within Sibu division. The study involved 694 level 1 primary schoolteachers. Using descriptive statistics, the study observed high levels of practice for teacher efficacy, instructional leadership and professional learning communities (PLCs). The differences between gender, teaching experience and academic qualification were analyzed using the t-test and one-way analysis of variance (ANOVA). The study reported significant differences in respondent perceptions based on teaching experience vis-à-vis teacher efficacy. Here, the post hoc Tukey test revealed that efficaciousness grows with experience. A correlation test observed positive and significant correlations between all independent variables. Binary logistic regression was applied to predict the independent variables’ influence on student achievement. The findings revealed that a dimension of instructional leadership – ‘monitoring student progress’ - emerged as the best predictor of student achievement for literacy and numeracy. The result indicated the students were more than 4 times more likely to achieve the national key performance index for both literacy and numeracy when student progress was monitored. In conclusion, ‘monitoring student progress’ had a positive influence on students’ achievement for literacy and numeracy, hence making it a possible course of action for school heads. However, more comprehensive studies are needed to ascertain its consistency within the context of Malaysia.

Keywords: efficacy, instructional, literacy, numeracy

Procedia PDF Downloads 246

Authors: Muhammad Nur Hidayat, Muksalmina, Chairul Fajar

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An alternative to improve the quality of asphalt as a pavement material is to use modified asphalt with the addition of cocoa shell ash as a filler. This research aims to determine the effect of asphalt mixture and cocoa shell ash after testing the physical properties of asphalt. The method used was experimental by testing the physical properties of asphalt. The results showed that the optimum asphalt content of the cocoa husk ash mixture was 2%, with an asphalt penetration value of 60.03 mm. The result of the asphalt softening point test was 51.0°C. Asphalt ductility test results in 144 cm. Asphalt specific gravity test result 1.076 gr/ml. Asphalt weight loss test results in 0.0183%. In conclusion, cocoa shell ash has an effect on asphalt characteristics, namely increasing stability, flexibility and fatigue resistance.

Keywords: cocoa husk ash, asphalt characteristics, physical properties testing, filler

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Authors: Zehra Gencel Efe, Fatma Susam Ozsayın, Satı Tas

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Background and Aim: It is not possible to teach all the knowledge related to operating room nursing in the nursing education process. Certified courses are organized by the Ministry of Health to compensate the lack of postgraduate training and the theoretical and practical training needs of working nurses. In this study; It is aimed to investigate the participants’ opinions and recommendations attending the certified course of operating room nursing that organized in İKCU AtaturkTraining and Research Hospital. Method: Two operating room nursing courses were organized in 2016. The 1st Operating Room Nursing Certified Course Program was organized between March 07, 2016 and April 6, 2016and the 2nd Operating Room Nursing Certified Course Program was organized between 07 November 2016 - 06 December 2016 at the İKCU Ataturk Training and Research Hospital. The first program was accepted for 29 participants, the second program was accepted for 30 participants. In the collection of the data, the 'Operating Room Nursing Certified Training Program Evaluation Form', 'Operating Room Nursing Certified Training Program Theoretical Training Evaluation Form' were used. Three point Likert-type scale is used for responses in the 'Operating Room Nursing Certified Training Program Evaluation Form’ (1=verygood, 2=good, 3=poor). Data is collected in five areas related to training program, operation room practice, communication, responsibility, experiences of learning. Four point Likert-type scale is used for responses in the 'Operating Room Nursing Certified Training Program Theoretical Training Evaluation Form' (1=verysatisfied, 2=quitesatisfied, 3=satisfied, 4=dissatisfied). Data is collected in two areas include presentation and content. Data were analyzed with SPSS 16 program. Findings and Conclusion: It was found that 93,22% of participants were female in addition, 62,7% had bachelor degree. It was seen that 33,87% of the work group had 1-5 years of experience in their field. It was found that; 88% of trainees participating in the first group to the operating room nursing-certified course program stated the training program was very good, 12% of them stated the training program was good. Nobody was signed the ‘poor’ choice. 81% of the trainees who participated in the 2nd group to the operating room nursing-certified course program stated the training program was very good, 19% of them stated the training program was good. Nobody was signed the ‘poor’ choice. It was found that there was no meaningful difference between the achievement ratios of the trainees and the learning status of the trainees when compared with the t test in the groups with success level of the operating room nursing certified course program according to the learning status of the participants (p ˃ 0,05). The trainees noted that the course was satisfied with theoretical and practical steps but the support services (lunch, coffee breaks etc.) were in adequate.

Keywords: certified courses, nursing certified courses, operating room nursing, training program

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Authors: S. Selman, T. Gout

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Microbial keratitis is a serious complication of contact lens wear that can be vision and eye-threatening. Diverse presentations relating to contact lens wear include dry corneal surface, corneal infiltrate, ulceration, scarring, and complete corneal melt leading to perforation. Contact lens wear is a major risk factor and, as such, is an important consideration in any patient presenting with a red eye in the primary care setting. This paper aims to provide an overview of the risk factors, common organisms, and spectrum of contact lens-associated keratitis (CLAK) complications. It will highlight some of the salient points relevant to the assessment and workup of patients suspected of CLAK in the emergency department based on the recent literature and therapeutic guidelines. An overview of the management principles will also be provided.

Keywords: microbial keratitis, corneal pathology, contact lens-associated complications, painful vision loss

Procedia PDF Downloads 93

Authors: J. Knight, E. Barberà

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Language learning strategies have been defined as thoughts and actions, consciously chosen and operationalized by language learners, to help them in carrying out a multiplicity of tasks from the very outset of learning to the most advanced levels of target language performance. While research in the field of Second Language Acquisition has focused on ‘good’ language learners, the effectiveness of strategy-use and orchestration by effective learners in face-to-face classrooms much less research has attended to learner strategies in online contexts, particular strategies in relation to technological tool use which can be part of a task design. In addition, much research on learner strategies and strategy use has been explored focusing on cognitive, attitudinal and metacognitive behaviour with less research focusing on the social aspect of strategies. This study focuses on how learners mediate with a technological tool designed to support synchronous spoken interaction and how this shape their spoken interaction in the opening of their talk. A case study approach is used incorporating notions from communities of practice theory to analyse and understand learner strategies of dyads carrying out a role play task. The study employs analysis of transcripts of spoken interaction in the openings of the talk along with log files of tool use. The study draws on results of previous studies pertaining to the same tool as a form of triangulation. Findings show how learners gain pre-task planning time through technological tool control. The strategies involving learners’ choices to enter and exit the tool shape their spoken interaction qualitatively, with some cases demonstrating long silences whilst others appearing to start the pedagogical task immediately. Who/what learners orientate to in the openings of the talk: an audience (i.e. the teacher), each other and/or screen-based signifiers in the opening moments of the talk also becomes a focus. The study highlights how tool use as a social practice should be considered a learning strategy in online contexts whereby different usages may be understood in the light of the more usual asynchronous social practices of the online community. The teachers’ role in the community is also problematised as the evaluator of the practices of that community. Results are pertinent for task design for synchronous speaking tasks. The use of community of practice theory supports an understanding of strategy use that involves both metacognition alongside social context revealing how tool-use strategies may need to be orally (socially) negotiated by learners and may also differ from an online language community.

Keywords: learner strategy, tool use, community of practice, speaking task

Procedia PDF Downloads 330

Authors: John Gibbs, Benjamin Flanders, Dylan Pozorski, Weixuan Liu

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Weight Painting–adjusting the influence a skeletal joint has on a given vertex in a character mesh–is an arduous and time con- suming part of the 3D animation pipeline. This process generally requires a trained technical animator and many hours of work to complete. Our skiNNer plug-in, which works within Autodesk’s Maya 3D animation software, uses Machine Learning and data pro- cessing techniques to create a deep neural network model that can accomplish the weight painting task in seconds rather than hours for bipedal quasi-humanoid character meshes. In order to create a properly trained network, a number of challenges were overcome, including curating an appropriately large data library, managing an arbitrary 3D mesh size, handling arbitrary skeletal architectures, accounting for extreme numeric values (most data points are near 0 or 1 for weight maps), and constructing an appropriate neural network model that can properly capture the high frequency alter- ation between high weight values (near 1.0) and low weight values (near 0.0). The arrived at neural network model is a cross between a traditional CNN, deep residual network, and fully dense network. The resultant network captures the unusually hard-edged features of a weight map matrix, and produces excellent results on many bipedal models.

Keywords: 3d animation, animation, character, rigging, skinning, weight painting, machine learning, artificial intelligence, neural network, deep neural network

Procedia PDF Downloads 251

Authors: Farhad Shafiepour Motlagh, Narges Salehi

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Purpose: The aim of the present study was a paradigm model of educational policy review strategies for the development of Professional schools in Iran. Research Methodology: The research method was based on Grounded theory. The statistical population included all articles of the ten years 2022-2010 and the method of sampling in a purposeful manner to the extent of theoretical saturation to 31 articles. For data analysis, open coding, axial coding and selective coding were used. Results: The results showed that causal conditions include social requirements (social expectations, educational justice, social justice); technology requirements (use of information and communication technology, use of new learning methods), educational requirements (development of educational territory, Development of educational tools and development of learning methods), contextual conditions including dual dimensions (motivational-psychological context, context of participation and cooperation), strategic conditions including (decentralization, delegation, organizational restructuring), intervention conditions (poor knowledge) Human resources, centralized system governance) and outcomes (school productivity, school professionalism, graduate entry into the labor market) were obtained. Conclusion: A review of educational policy is necessary to develop Iran's Professional schools, and this depends on decentralization, delegation, and, of course, empowerment of school principals.

Keywords: school productivity, professional schools, educational policy, paradigm

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Authors: Oluwaseun Ijiwade, Chris Davison, Kelvin Gregory

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In Australia, like other parts of the world, the debate on how to enhance teachers using assessment data to inform teaching and learning of English as an Additional Language (EAL, Australia) or English as a Foreign Language (EFL, United States) have occupied the centre of academic scholarship. Traditionally, this approach was conceptualised as ‘Formative Assessment’ and, in recent times, ‘Assessment for Learning (AfL)’. The central problem is that teacher-made tests are limited in providing data that can inform teaching and learning due to variability of classroom assessments, which are hindered by teachers’ characteristics and assessment literacy. To address this concern, scholars in language education and testing have proposed a uniformed large-scale computer-based assessment program to meet the needs of teachers and promote AfL in language education. In Australia, for instance, the Victoria state government commissioned a large-scale project called 'Tools to Enhance Assessment Literacy (TEAL) for Teachers of English as an additional language'. As part of the TEAL project, a tool called ‘Reading and Vocabulary assessment for English as an Additional Language (RVEAL)’, as a diagnostic language assessment (DLA), was developed by language experts at the University of New South Wales for teachers in Victorian schools to guide EAL pedagogy in the classroom. Therefore, this study aims to provide qualitative evidence for understanding beliefs about the diagnostic language assessment (DLA) among EAL teachers in primary and secondary schools in Victoria, Australia. To realize this goal, this study raises the following questions: (a) How do teachers use large-scale assessment data for diagnostic purposes? (b) What skills do language teachers think are necessary for using assessment data for instruction in the classroom? and (c) What factors, if any, contribute to teachers’ beliefs about diagnostic assessment in a large-scale assessment? Semi-structured interview method was used to collect data from at least 15 professional teachers who were selected through a purposeful sampling. The findings from the resulting data analysis (thematic analysis) provide an understanding of teachers’ beliefs about DLA in a classroom context and identify how these beliefs are crystallised in language teachers. The discussion shows how the findings can be used to inform professional development processes for language teachers as well as informing important factor of teacher cognition in the pedagogic processes of language assessment. This, hopefully, will help test developers and testing organisations to align the outcome of this study with their test development processes to design assessment that can enhance AfL in language education.

Keywords: beliefs, diagnostic language assessment, English as an additional language, teacher cognition

Procedia PDF Downloads 186

Authors: Zikra Faiz, Nisar Abid, Muhammad Waqas

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This study aim to examine the challenges faced by teachers during teaching to those students who are intellectually disable, suffering from autism spectrum disorder, learning disability, and ADHD at the primary level. The descriptive research design of quantitative approach was adopted to conduct this study; a cross-sectional survey method was used to collect data. The sample was comprised of 258 (43 male and 215 female) teachers who teach at special education institutes of Lahore district selected through proportionate stratified random sampling technique. Self-developed questionnaire was used which was comprised of 22 closed-ended items. Collected data were analyzed through descriptive and inferential statistical techniques by using Statistical Package for Social Sciences (SPSS) version 21. Results show that teachers faced problems during group activities, to handle bad behavior and different disabilities of students. It is concluded that there was a significant difference between male and female teachers perceptions about challenges faced during teaching with developmental disable students. Furthermore, there was a significant difference exist in the perceptions of teachers regarding challenges faced during teaching to students with developmental disabilities in term of teachers’ age and area of specialization. It is recommended that developmentally disable student require extra attention so that, teacher should trained through pre-service and in-service training to teach developmentally disabled students.

Keywords: intellectual disability, autism spectrum disorder, ADHD, learning disability

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Authors: Bongs Lainjo

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Educational institutions and authorities that are mandated to run education systems in various countries need to implement a curriculum that considers the possibility and existence of elementary school dropouts. This research focuses on elementary school dropout rates and the ability to replicate various predictive models carried out globally on selected Elementary Schools. The study was carried out by comparing the classical case studies in Africa, North America, South America, Asia and Europe. Some of the reasons put forward for children dropping out include the notion of being successful in life without necessarily going through the education process. Such mentality is coupled with a tough curriculum that does not take care of all students. The system has completely led to poor school attendance - truancy which continuously leads to dropouts. In this study, the focus is on developing a model that can systematically be implemented by school administrations to prevent possible dropout scenarios. At the elementary level, especially the lower grades, a child's perception of education can be easily changed so that they focus on the better future that their parents desire. To deal effectively with the elementary school dropout problem, strategies that are put in place need to be studied and predictive models are installed in every educational system with a view to helping prevent an imminent school dropout just before it happens. In a competency-based curriculum that most advanced nations are trying to implement, the education systems have wholesome ideas of learning that reduce the rate of dropout.

Keywords: elementary school, predictive models, machine learning, risk factors, data mining, classifiers, dropout rates, education system, competency-based curriculum

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Authors: Danuta Szwajca

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Image is a very important intangible asset of a contemporary enterprise, especially, in case of a bank as a public trust institution. A positive, demanded image may effectively distinguish the bank among the competition and build the customer confidence and loyalty. PKO BP is the biggest and largest bank functioning on the Polish financial market. Within the years not a very nice image of the bank has been embedded in the customers’ minds as an old-fashioned, stagnant, resistant to changes institution, what result in the customer loss, and ageing. For this reason, in 2010, the bank launched a campaign of radical image change along with a strategy of branches modernization and improvement of the product offer. The objective of the article is to make an attempt of effectiveness assessment of the brand repositioning campaign that lasted three years. The foundations of the assessment are the results of the questionnaire research concerning the way of bank’s perception before and after the campaign.

Keywords: advertising campaign, brand repositioning, image of the bank, repositioning

Procedia PDF Downloads 405

Authors: Kanika Gupta, Ashok Kumar

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Biofilms are dense, highly hydrated cell clusters that are irreversibly attached to a substratum, to an interface or to each other, and are embedded in a self-produced gelatinous matrix composed of extracellular polymeric substances. Research in biofilm field has become very significant, as biofilm has shown high mechanical resilience and resistance to antibiotic treatment and constituted as a significant problem in both healthcare and other industry related to microorganisms. The massive information both stated and hidden in the biofilm literature are growing exponentially therefore it is not possible for researchers and practitioners to automatically extract and relate information from different written resources. So, the current work proposes and discusses the use of text mining techniques for the extraction of information from biofilm literature corpora containing 34306 documents. It is very difficult and expensive to obtain annotated material for biomedical literature as the literature is unstructured i.e. free-text. Therefore, we considered unsupervised approach, where no annotated training is necessary and using this approach we developed a system that will classify the text on the basis of growth and development, drug effects, radiation effects, classification and physiology of biofilms. For this, a two-step structure was used where the first step is to extract keywords from the biofilm literature using a metathesaurus and standard natural language processing tools like Rapid Miner_v5.3 and the second step is to discover relations between the genes extracted from the whole set of biofilm literature using pubmed.mineR_v1.0.11. We used unsupervised approach, which is the machine learning task of inferring a function to describe hidden structure from 'unlabeled' data, in the above-extracted datasets to develop classifiers using WinPython-64 bit_v3.5.4.0Qt5 and R studio_v0.99.467 packages which will automatically classify the text by using the mentioned sets. The developed classifiers were tested on a large data set of biofilm literature which showed that the unsupervised approach proposed is promising as well as suited for a semi-automatic labeling of the extracted relations. The entire information was stored in the relational database which was hosted locally on the server. The generated biofilm vocabulary and genes relations will be significant for researchers dealing with biofilm research, making their search easy and efficient as the keywords and genes could be directly mapped with the documents used for database development.

Keywords: biofilms literature, classifiers development, text mining, unsupervised learning approach, unstructured data, relational database

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Authors: Ibrahim Ozkan

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In this study, a cross-layer design which combines adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) techniques for a cooperative wireless network is investigated analytically. Previous analyses of such systems in the literature are confined to the case where the fading channel is independent at each retransmission, which can be unrealistic unless the channel is varying very fast. On the other hand, temporal channel correlation can have a significant impact on the performance of HARQ systems. In this study, utilizing a Markov channel model which accounts for the temporal correlation, the performance of non-cooperative and cooperative networks are investigated in terms of packet loss rate and throughput metrics for Chase combining HARQ strategy.

Keywords: cooperative network, adaptive modulation and coding, hybrid ARQ, correlated fading

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Authors: Craig Jantzen, Tim Abram, Dirk Engelberg, Hugues Lambert, Daniel Cooper

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Molten salts are of high interest for use as coolants in nuclear reactors due to favourable high temperature and thermodynamic properties. The corrosive behaviour of molten salts however pose a materials integrity challenge. Three Ni / Ni-Fe based and two Mo based alloys have been exposed to molten eutectics (LiCl-KCl at 59.5:40.5 mol% and KCl-MgCl2 at 68:32 mol%) at 600°C and 800°C for durations up to 500hrs. Corrosion was observed to preferentially attack alloy constituents in order of their reactivity, with chromium the most vulnerable and depleted element. Alloy weight-loss per unit area was calculated to give linear corrosion rates, discounting any initial rapid corrosion of impurities. Further analysis was carried out using ICP-MS, SEM and EDX techniques to give a more detailed view of the corrosion mechanisms.

Keywords: molten salt, salt, corrosion, high temperature, licl, KCL, MgCl, molybdenum, nickel, superalloys

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: deep learning, artificial neural networks, energy price forecasting, turkey

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Authors: Hategekimana Jean Paul, Irakoze Josiane, Ishimweyizerwe Valentin, Iradukunda Dieudonne, Uwanyirigira Jeannette

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Orange fleshed sweet potatoes (OFSP) are highly grown and are available plenty in rural and urban local markets and its contribution in reduction of food insecurity in Rwanda is considerable. But the postharvest loss of this commodity is a critical challenge due to its high perishability. Several research activities have been conducted on how fresh food commodities can be transformed into extended shelf life food products for prevention of post-harvest losses. However, such activity was not yet well studied in Rwanda. The aim of the present study was the processing of backed products from (OFSP)combined with wheat composite flour and assess the nutritional content and consumer acceptability of new developed products. The perishability of OFSP and their related lack during off season can be eradicated by producing cake, doughnut and bread with OFSP puree or flour. The processing for doughnut and bread were made by making OFSP puree and other ingredients then a dough was made followed by frying and baking while for cake OFSP was dried through solar dryer to have a flour together with wheat flour and other ingredients to make dough cake and baking. For each product, one control and three experimental samples, (three products in three different ratios (30,40 and50%) of OFSP and the remaining percentage of wheat flour) were prepared. All samples including the control were analyzed for the consumer acceptability (sensory attributes). Most preferred samples (One sample for each product with its control sample and for each OFSP variety) were analyzed for nutritional composition along with control sample. The Cake from Terimbere variety and Bread from Gihingumukungu supplemented with 50% OFSP flour or Puree respectively were most acceptable except Doughnut from Vita variety which was highly accepted at 50% of OFSP supplementation. The moisture, ash, protein, fat, fiber, Total carbohydrate, Vitamin C, reducing sugar and minerals (Sodium, Potassium and Phosphorus.) content was different among products. Cake was rich in fibers (14.71%), protein (6.590%), and vitamin c(19.988mg/100g) compared to other samples while bread found to be rich in reducing sugar with 12.71mg/100g compared to cake and doughnut. Also doughnut was found to be rich in fat content with 6.89% compared to other samples. For sensory analysis, doughnut was highly accepted in ratio of 60:40 compared to other products while cake was least accepted at ratio of 50:50. The Proximate composition and minerals content of all the OFSP products were significantly higher as compared to the control samples.

Keywords: post-harvest loss, OFSP products, wheat flour, sensory evaluation, proximate composition

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Authors: Alain Kusmoko, Druce Dunne, Huijun Li

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Stellite 6 was deposited by laser cladding on a chromium bearing substrate (P91) with energy inputs of 1 kW (P91-1) and 1.8 kW (P91-1.8). The chemical compositions and microstructures of these coatings were characterized by atomic absorption spectroscopy, optical microscopy and scanning electron microscopy. The microhardness of the coatings was measured and the wear mechanism of the coatings was assessed using a pin-on-plate (reciprocating) wear testing machine. The results showed less cracking and pore development for Stellite 6 coatings applied to the P91 steel substrate with the lower heat input (P91-1). Further, the Stellite coating for P91-1 was significantly harder than that obtained for P91-1.8. The wear test results indicated that the weight loss for P91-1 was much lower than for P91-1.8. It is concluded that the lower hardness of the coating for P91-1.8, together with the softer underlying substrate structure, markedly reduced the wear resistance of the Stellite 6 coating.

Keywords: friction and wear, laser cladding, P91 steel, Stellite 6 coating

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Authors: Nasser Ghassembaglou, Abdullah Bolek, Oktay Yilmaz, Ertan Oznergiz, Hikmet Kocabas, Safak Yilmaz

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Nanofibers are effective material which have frequently been investigated to produce high quality air filters. As an environmental approach our aim is to achieve nanofibers by melting. In spun-bond systems extruder, spin-pump, nozzle package and attenuator are used. Molten polymer which flows from extruder is made steady by spin-pump. Regular melt passes through nozzle holes and forms fibers under high pressure. The fibers pulled from nozzle are shrunk to micron size by an attenuator, after solidification they are collected on a conveyor. In this research different designs of attenuator system have been studied and also CFD analysis have been done on them. Afterwards, one of these designs tested and finally some optimizations have been done to reduce pressure loss and increase air velocity.

Keywords: attenuator, nanofiber, spun-bond, extruder

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Authors: Sedat Simsek, Tugay Arat

Abstract:

Today's communication concept, which has a great revolution with the printing press which has been found by Gutenberg, has no boundary thanks to advanced communication devices and the internet. It is possible to take advantage in many areas, such as from medicine to social sciences or from mathematics to education, from the computers that was first produced for the purpose of military services. The use of these developing technologies in the field of education has created a great vision changes in both training and having education. Materials, which can be considered as basic communication resources and used in traditional education has begun to lose its significance, and some technologies have begun to replace them such as internet, computers, smart boards, projection devices and mobile phone. On the other hand, the programs and applications used in these technologies have also been developed. University students use virtual books instead of the traditional printed book, use cell phones instead of note books, use the internet and virtual databases instead of the library to research. They even submit their homework with interactive methods rather than printed materials. The traditional education system, these technologies, which increase productivity, have brought a new dimension to education. The aim of this study is to determine the influence of technologies in the learning process of students and to find whether is there any similarities and differences that arise from the their faculty that they have been educated and and their learning process. In addition to this, it is aimed to determine the level of ICT usage of students studying at the university level. In this context, the advantages and conveniences of the technology used by students are also scrutinized. In this study, we used surveys to collect data. The data were analyzed by using SPSS 16 statistical program with the appropriate testing.

Keywords: education, communication technologies, role of technology, teaching

Procedia PDF Downloads 291

Authors: M. Kharrat, G. Moreau, Z. Aboura

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The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

Procedia PDF Downloads 145

Authors: Hasti Ebrahimi

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This study sheds light on the challenges and difficulties caused by the Iranian clerical system’s intervention in the country’s school education during the COVID-19 pandemic, when schools remained closed for almost two years. The pandemic brought Iranian elementary school education to a standstill for almost 6 months before the country developed a nationwide learning platform – a customized television network. While the initiative seemed to have been welcomed by the majority of Iranian parents, it resented some of the more traditional strata of the society, including the influential Friday Prayer Leaders who found the televised version of the elementary education ‘less spiritual’ and ‘more ‘material’ or science-based. That prompted the Iranian Channel of Education, the specialized television network that had been chosen to serve as a nationally televised school during the pandemic, to try to redefine much of its online elementary school educational content within the religious ideology of the Islamic Republic of Iran. As a result, young clergies appeared on the television screen as preachers of Islamic morality, religious themes and even sociology, history, and arts. The present research delves into the consequences of such an intervention, how it might have impacted the infrastructure of Iranian elementary education and whether or not the new ideology-infused curricula would withstand the opposition of students and mainstream teachers. The main methodology used in this study is Critical Discourse Analysis with a cognitive approach. It systematically finds and analyzes the alternative ideological structures of discourse in the Iranian Channel of Education from September 2021 to July 2022, when the clergy ‘teachers’ replaced ‘regular’ history and arts teachers on the television screen for the first time. It has aimed to assess how the various uses of the alternative ideological discourse in elementary school content have influenced the processes of learning: the acquisition of knowledge, beliefs, opinions, attitudes, abilities, and other cognitive and emotional changes, which are the goals of institutional education. This study has been an effort aimed at understanding and perhaps clarifying the relationships between the traditional textual structures and processing on the one hand and socio-cultural contexts created by the clergy teachers on the other. This analysis shows how the clerical portion of elementary education on the Channel of Education that seemed to have dominated the entire televised teaching and learning process faded away as the pandemic was contained and mainstream classes were restored. It nevertheless reflects the deep ideological rifts between the clerical approach to school education and the mainstream teaching process in Iranian schools. The semantic macrostructures of social content in the current Iranian elementary school education, this study suggests, have remained intact despite the temporary ideological intervention of the ruling clerical elite in their formulation and presentation. Finally, using thematic and schematic frameworks, the essay suggests that the ‘clerical’ social content taught on the Channel of Education during the pandemic cannot have been accepted cognitively by the channel’s target audience, including students and mainstream teachers.

Keywords: televised elementary school learning, Covid 19, critical discourse analysis, Iranian clerical ideology

Procedia PDF Downloads 37

Authors: Martin Lauzier, Benjamin Lafreniere-Carrier, Nathalie Delobbe

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Supervisor support is one of the main levers to foster transfer of training. Although past and current studies voice its effects, few have sought to identify the factors that may explain why supervisors offer support to their subordinates when they return from training. Based on Goal Orientation Theory and following the principles of supportive supervision, this study aims to improve our understanding of the factors that influence supervisors’ involvement in the transfer process. More specifically, this research seeks to verify the influence of supervisors’ goal orientation on the adoption of post-training support behaviors. This study also assesses the mediating role of the supervisors’ interest in subordinates’ development on this first relationship. Conducted in two organizations (Canadian: N₁ = 292; Belgian: N₂ = 80), the results of this study revealed three main findings. First, supervisors’ who adopt learning mastery goal orientation also tend to adopt more post-training supportive behaviors. Secondly, regression analyses (using the bootstrap method) show that supervisors' interest in developing their subordinates’ skills mediate the relationship between supervisors’ goal orientation and post-training supportive behaviors. Thirdly, the observed mediation effects are consistent in both samples, regardless of supervisors’ gender or age. Overall, this research is part of the limited number of studies that have focused on the determining factors supervisors’ involvement in the learning transfer process.

Keywords: supervisor support, transfer of training, goal orientation, interest in the development of subordinates’ skills

Procedia PDF Downloads 173