Search results for: Machine learning

Authors: Shamini Dhana, G. Subrahmanya VRK Rao

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The fashion industry is advancing towards a mindset of zero waste, personalization, creativity, and circularity. The trend of upcycling clothing and materials into personalized fashion is being demanded by the next generation. There is a need for a digital tool to accelerate the process towards mass customization. Dhana’s D/Sphere fashion technology platform uses digital tools to accelerate upcycling. In essence, advanced fashion garments can be designed and developed via reuse, repurposing, recreating activities, and using existing fabric and circulating materials. The D/Sphere platform has the following objectives: to provide (1) An opportunity to develop modern fashion using existing, finished materials and clothing without chemicals or water consumption; (2) The potential for an everyday customer and designer to use the medium of fashion for creative expression; (3) A solution to address the global textile waste generated by pre- and post-consumer fashion; (4) A solution to reduce carbon emissions, water, and energy consumption with the participation of all stakeholders; (5) An opportunity for brands, manufacturers, retailers to work towards zero-waste designs and as an alternative revenue stream. Other benefits of this alternative approach include sustainability metrics, trend prediction, facilitation of disassembly and remanufacture deep learning, and hyperheuristics for high accuracy. A design tool for mass personalization and customization utilizing existing circulating materials and deadstock, targeted to fashion stakeholders will lower environmental costs, increase revenues through up to date upcycled apparel, produce less textile waste during the cut-sew-stitch process, and provide a real design solution for the end customer to be part of circular fashion. The broader impact of this technology will result in a different mindset to circular fashion, increase the value of the product through multiple life cycles, find alternatives towards zero waste, and reduce the textile waste that ends up in landfills. This technology platform will be of interest to brands and companies that have the responsibility to reduce their environmental impact and contribution to climate change as it pertains to the fashion and apparel industry. Today, over 70% of the $3 trillion fashion and apparel industry ends up in landfills. To this extent, the industry needs such alternative techniques to both address global textile waste as well as provide an opportunity to include all stakeholders and drive circular fashion with new personalized products. This type of modern systems thinking is currently being explored around the world by the private sector, organizations, research institutions, and governments. This technological innovation using digital tools has the potential to revolutionize the way we look at communication, capabilities, and collaborative opportunities amongst stakeholders in the development of new personalized and customized products, as well as its positive impacts on society, our environment, and global climate change.

Keywords: circular fashion, deep learning, digital technology platform, personalization

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Authors: Csilla Paksi-Petró

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The Hungarian national public administration training system providing continuous, lifelong further training to some ten thousand executives in public administration was launched in 2014, adding skills and competency development to the previous training solutions, which had a mainly legal and professional approach. The executive training system is being continuously developed since tackling the existing qualitative, and quantitative challenges calls for the introduction of novel, innovative solutions. With a gap-filling character, this study presents, in brief, the last eight years of system of executive training in public administration, supported by the outcomes of the author's empirical research, makes suggestions for the possible directions of its further development. Through this article, the reader may obtain an overview of the current Hungarian civil service further training system, its institution system, the method of its application, its target groups, its results, and its development prospects. By reading the article, the reader will get acquainted with the good practices of the Hungarian civil service further training system.

Keywords: coaching, e-learning, executive development, further-training

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Authors: Saad Alkahtani

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This study aims to identify the extent to which the faculty members who teach Arabic to speakers of other languages in Arabic language institutes at Saudi universities use computer technologies such as language laboratories, websites, software programs, and learning management system (LMS). It also seeks to identify critical difficulties that hinder the use of these technologies by faculty members. The population of the study consisted of 103 faculty members in four Arabic language institutes at Saudi universities. The results of the study showed a disparity in the use of computer technologies in teaching Arabic to non-native speakers. The means of degree of use ranged from 1.20 through 2.83. The study also identified difficulties limiting the use of computer technology in teaching Arabic. And the means of averages of difficulty of use ranged from 1.50 to 2.89. The differences were not statistically significant among the institutes (at 0.05).

Keywords: Arabic language programs, computer technology, using technology in teaching Arabic language, Arabic as a second language, computer skills

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Authors: Swati Kapoor, Rajeev Upreti, Monica Mahajan, Abhaya Indrayan, Dinesh Srivastava

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Enteric Fever is caused by gram negative bacilli Salmonella typhi and paratyphi. It is associated with high morbidity and mortality worldwide. Timely initiation of treatment is a crucial step for prevention of any complications. Cultures of body fluids are diagnostic, but not always conclusive or practically feasible in most centers. Moreover, the results of cultures delay the treatment initiation. Serological tests lack diagnostic value. The blood counts can offer a promising option in diagnosis. A retrospective study to find out the relevance of leucopenia and eosinopenia was conducted on 203 culture proven enteric fever patients and 159 culture proven non-enteric fever patients in a tertiary care hospital in New Delhi. The patient details were retrieved from the electronic medical records section of the hospital. Absolute eosinopenia was considered as absolute eosinophil count (AEC) of less than 40/mm³ (normal level: 40-400/mm³) using LH-750 Beckman Coulter Automated machine. Leucopoenia was defined as total leucocyte count (TLC) of less than 4 X 10⁹/l. Blood cultures were done using BacT/ALERT FA plus automated blood culture system before first antibiotic dose was given. Case and control groups were compared using Pearson Chi square test. It was observed that absolute eosinophil count (AEC) of 0-19/mm³ was a significant finding (p < 0.001) in enteric fever patients, whereas leucopenia was not a significant finding (p=0.096). Using Receiving Operating Characteristic (ROC) curves, it was observed that patients with both AEC < 14/mm³ and TCL < 8 x 10⁹/l had 95.6% chance of being diagnosed as enteric fever and only 4.4% chance of being diagnosed as non-enteric fever. This result was highly significant with p < 0.001. This is a very useful association of AEC and TLC found in enteric fever patients of this study which can be used for the early initiation of treatment in clinically suspected enteric fever patients.

Keywords: absolute eosinopenia, absolute eosinophil count, enteric fever, leucopenia, total leucocyte count

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Authors: Zhengrong Wu, Haibo Yang

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In the context of escalating global climate change and environmental degradation, the complexity and frequency of natural disasters are continually increasing. Confronted with an abundance of information regarding natural disasters, traditional knowledge graph construction methods, which heavily rely on grammatical rules and prior knowledge, demonstrate suboptimal performance in processing complex, multi-source disaster information. This study, drawing upon past natural disaster reports, disaster-related literature in both English and Chinese, and data from various disaster monitoring stations, constructs question-answer templates based on large language models. Utilizing the P-Tune method, the ChatGLM2-6B model is fine-tuned, leading to the development of a disaster knowledge graph based on large language models. This serves as a knowledge database support for disaster emergency response.

Keywords: large language model, knowledge graph, disaster, deep learning

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Authors: Lukholo Raxangana

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Fourth Industrial Revolution (4IR)-era teaching offers in-service mathematics teachers opportunities to use blended approaches to engage learners while teaching mathematics. This study explores in-service high school teachers' experiences with a blended teaching approach to mathematics. This qualitative case study involved eight pre-service teachers from four selected schools in the Sedibeng West District of the Gauteng Province. The study used the community of inquiry model as its analytical framework for data analysis. Data collection was through semi-structured interviews and focus-group discussions to explore in-service teachers' experiences with the influence of blended teaching (BT) on learning mathematics. The study results are the impact of load-shedding, benefits of BT, and perceptions of in-service and hindrances of BT. Based on these findings, the study recommends that further research should focus on developing data-free BT tools to assist during load-shedding, regardless of location.

Keywords: bended teaching, teachers, in-service, and mathematics

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Authors: Yuichi Morita, Yoshiteru Nakamori

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In car dealer business of Japan, a sale professional is a key factor of company’s success. We hypothesize that, if a corporation knows what is the sales professionals’ trait of its corporation’s business field, it will be easier for a corporation to secure and nurture sales persons effectively. The lean human resources management will ensure business success and good performance of corporations, especially small and medium ones. The goal of the paper is to determine the traits of sales professionals for small-and medium-size car dealers, using chi-square test and the variable rough set model. As a result, the results illustrate that experience of job change, learning ability and product knowledge are important, and an academic background, building a career with internal transfer, experience of the leader and self-development are not important to be a sale professional. Also, we illustrate sales professionals’ traits are persistence, humility, improvisation and passion at business.

Keywords: traits of sales professionals, variable precision rough sets theory, sales professional, sales professionals

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Authors: Margarita Mayoral-Villa, J. Klapp, L. Di G. Sigalotti, J. E. V. Guzmán

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Automated learning techniques are widely applied in the energy sector to address challenging problems from a practical point of view. To this end, we discuss the implementation of a Message Passing algorithm (MPNN)within a Graph Neural Network(GNN)to leverage the neighborhood of a set of nodes during the aggregation process. This approach enables the characterization of multiphase diffusion processes in the reservoir, such that the flow paths underlying the interconnections between multiple wells may be inferred from previously available data on flow rates and bottomhole pressures. The results thus obtained compare favorably with the predictions produced by the Reduced Order Capacitance-Resistance Models (CRM) and suggest the potential of MPNNs to enhance the robustness of the forecasts while improving the computational efficiency.

Keywords: multiphase diffusion, message passing neural network, well interconnection, interwell connectivity, graph neural network, capacitance-resistance models

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Authors: Henry Nicholas Lee, George Thomas, Juliana Johari, Carmilla Freddie, Caroline Val Madin

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Research in comparative and international education often provides value-laden views of an education system within and in between other countries. These views are frequently used by policy makers or educators to explore similarities and differences for, among others, benchmarking purposes. In this study, a comparison is made between Malaysia and England, focusing on the process of writing children went through to create a text, using a multimodal theoretical framework to analyse this comparison. The main purpose is political in nature as it served as an answer to Malaysia’s call for benchmarking of best practices for language learning. Furthermore, the focus on writing in this study adds into more empirical findings about early writers’ writing development and writing improvement, especially for children at the ages of 5-9. In research, comparative studies in English as a Second Language (ESL) writing pedagogy – particularly in Malaysia since the introduction of the Standard- based English Language Curriculum (KSSR) in 2011 as a draft and its full implementation in 2017; reviewed 2018 KSSR-CEFR aligned – has not been done comparatively. In theory, a multimodal theoretical framework somehow allows a logical comparison between first language and ESL which would provide useful insights to illuminate the writing process between Malaysia and England. The comparisons are not representative because of the different school systems in both countries. So far, the literature informs us that the curriculum for language learning is very much emphasised on children’s linguistic abilities, which include their proficiency and mastery of the language, its conventions, and technicalities. However, recent empirical findings suggested that literacy in its concepts and characters need change. In view of this suggestion, the comparison will look at how the process of writing is implemented through the five modes of communication: linguistic, visual, aural, spatial, and gestural. This project draws on data from Malaysia and England, involving 10 teachers, 26 classroom observations, 20 lesson plans, 20 interviews, and 20 brief conversations with teachers. The research focused upon 20 primary children of different genders aged 5-9, and in addition to primary data descriptions, 40 children’s works, 40 brief classroom conversations, 30 classroom photographs, and 30 school compound photographs were undertaken to investigate teachers and children’s use of modes and semiotic resources to design a text. The data were analysed by means of within-case analysis, cross-case analysis, and constant comparative analysis, with an initial stage of data categorisation, followed by general and specific coding, which clustered the data into thematic groups. The study highlights the importance of teachers’ and children’s engagement and interaction with various modes of communication, an adaptation from the English approaches to teaching writing within the KSSR framework and providing ‘voice’ to ESL writers to ensure that both have access to the knowledge and skills required to make decisions in developing multimodal texts and artefacts.

Keywords: comparative education, early writers, KSSR, multimodal theoretical framework, writing development

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Authors: Brahim El Fadil

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The nature of science as a solution (NOS) to life problems is well established in school activities the world over. However, this study reveals the lack of representation of the NOS in science textbooks used in Quebec Province. A content analysis method was adopted to analyze the NOS in relation to optics knowledge and teaching-learning activities in Grade 9 science and technology textbooks and Grade 11 physics textbooks. The selected textbooks were approved and authorized by the Provincial Ministry of Education. Our analysis points out that most of these editions provided a poor representation of NOS. None of them indicates that scientific knowledge is subject to change, even though the history of optics reveals evolutionary and revolutionary changes. Moreover, the analysis shows that textbooks place little emphasis on the discussion of scientific laws and theories. Few of them argue that scientific inquiries are required to gain a deep understanding of scientific concepts. Moreover, they rarely present empirical evidence to support their arguments.

Keywords: nature of science, history of optics, geometrical theory of optics, wave theory of optics

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Authors: Nellie Nosisi Feza

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Developing young students' number sense is a priority if the aim is to build a rich mathematical foundation for successful schooling and future innovative careers. Capturing students’ interests is crucial while mediating counting concepts. This paper reports South African young children number concepts demonstrated before entering the reception class. It indicates the diverse knowledge attained in different settings before entering formal schooling. The findings indicate that their start is uneven with fully and partly attained number concepts. The findings suggest pre-schooling stimulation that provides rich mathematical experiences and purposeful play towards the attainment of core foundational concepts. Literature directs practice on important core concepts that are foundational in developing number sense.

Keywords: numeracy, learning trajectories, innate abilities, counting, Grade R/reception class

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Authors: N. Alhazmi

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Knowing the thermodynamics properties of hydrocarbons is vital when it comes to analyzing the related chemical reaction outcomes and understanding the reaction process, especially in terms of petrochemical industrial applications, combustions, and catalytic reactions. However, measuring the thermodynamics properties experimentally is time-consuming and costly. In this paper, Gaussian process regression (GPR) has been used to directly predict the main thermodynamic properties - standard enthalpy of formation, standard entropy, and heat capacity -for more than 360 cyclic and non-cyclic alkanes, alkenes, and alkynes. A simple workflow has been proposed that can be applied to directly predict the main properties of any hydrocarbon by knowing its descriptors and chemical structure and can be generalized to predict the main properties of any material. The model was evaluated by calculating the statistical error R², which was more than 0.9794 for all the predicted properties.

Keywords: thermodynamic, Gaussian process regression, hydrocarbons, regression, supervised learning, entropy, enthalpy, heat capacity

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Authors: Kirsi Korkealehto

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The purpose of this research was to investigate how the peer evaluation concept was perceived by language teachers developing online language courses. The online language courses in question were developed in language teacher teams within a nationwide KiVAKO-project funded by the Finnish Ministry of Education and Culture. The participants of the project were 86 language teachers of 26 higher education institutions in Finland. The KiVAKO-project aims to strengthen the language capital at higher education institutions by building a nationwide online language course offering on a shared platform. All higher education students can study the courses regardless of their home institutions. The project covers the following languages: Chinese, Estonian, Finnish Sign Language, French, German, Italian, Japanese, Korean, Portuguese, Russian, and Spanish on the levels CEFR A1-C1. The courses were piloted in the autumn term of 2019, and an online peer evaluation session was organised for all project participating teachers in spring 2020. The peer evaluation utilised the quality criteria for online implementation, which was developed earlier within the eAMK-project. The eAMK-project was also funded by the Finnish Ministry of Education and Culture with the aim to improve higher education institution teachers’ digital and pedagogical competences. In the online peer evaluation session, the teachers were divided into Zoom breakout rooms, in each of which two pilot courses were presented by their teachers dialogically. The other language teachers provided feedback on the course on the basis of the quality criteria. Thereafter good practices and ideas were gathered to an online document. The breakout rooms were facilitated by one teacher who was instructed and provided a slide-set prior to the online session. After the online peer evaluation sessions, the language teachers were asked to respond to an online questionnaire for feedback. The questionnaire included three multiple-choice questions using the Likert-scale rating and two open-ended questions. The online questionnaire was answered after the sessions immediately, the questionnaire link and the QR-code to it was on the last slide of the session, and it was responded at the site. The data comprise online questionnaire responses of the peer evaluation session and the researcher’s observations during the sessions. The data were analysed with a qualitative content analysis method with the help of Atlas.ti programme, and the Likert scale answers provided results per se. The observations were used as complementary data to support the primary data. The findings indicate that the working in the breakout rooms was successful, and the workshops proceeded smoothly. The workshops were perceived as beneficial in terms of improving the piloted courses and developing the participants’ own work as teachers. Further, the language teachers stated that the collegial discussions and sharing the ideas were fruitful. The aspects to improve the workshops were to give more time for free discussions and the opportunity to familiarize oneself with the quality criteria and the presented language courses beforehand. The quality criteria were considered to provide a suitable frame for self- and peer evaluations.

Keywords: higher education, language learning, online learning, peer-evaluation

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Authors: W. Thepsuwan, N. Monmaturapoj

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Calcium phosphate cements (CPCs) is one of the most attractive bioceramics due to its moldable and shape ability to fill complicated bony cavities or small dental defect positions. In this study, CPCs were produced by using mixtures of tetracalcium phosphate (TTCP, Ca4O(PO4)2) and dicalcium phosphate anhydrous (DCPA, CaHPO4) in equimolar ratio (1/1) with aqueous solutions of acetic acid (C2H4O2) and disodium hydrogen phosphate dehydrate (Na2HPO4.2H2O) in combination with sodium alginate in order to improve theirs moldable characteristic. The concentrations of the aqueous solutions and sodium alginate were varied to investigate the effects of different aqueous solution and alginate on properties of the cements. The cement paste was prepared by mixing cement powder (P) with aqueous solution (L) in a P/L ratio of 1.0 g/ 0.35 ml. X-ray diffraction (XRD) was used to analyses phase formation of the cements. Setting times and compressive strength of the set CPCs were measured using the Gilmore apparatus and Universal testing machine, respectively. The results showed that CPCs could be produced by using both basic (Na2HPO4.2H2O) and acidic (C2H4O2) solutions. XRD results show the precipitation of hydroxyapatite in all cement samples. No change in phase formation among cements using difference concentrations of Na2HPO4.2H2O solutions. With increasing concentration of acidic solutions, samples obtained less hydroxyapatite with a high dicalcium phosphate dehydrate leaded to a shorter setting time. Samples with sodium alginate exhibited higher crystallization of hydroxyapatite than that of without alginate as a result of shorten setting time in basic solution but a longer setting time in acidic solution. The stronger cement was attained from samples using acidic solution with sodium alginate; however it was lower than using the basic solution.

Keywords: calcium phosphate cements, TTCP, DCPA, hydroxyapatite, properties

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Authors: Alfred M. Caronia

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The aim of this pilot study was to explore an NCAA Division 1 female volleyball players’ experience of a strength and conditioning program and the result this has on self-efficacy of sport skill performance. This phenomenological study comprised of 10 college aged participants that have strength training program experience. Data was collected using semi-structured interviews and a reflective journal; the transcribed interviews were analyzed using qualitative content analysis. From the analysis, four themes emerged: performance enhancement, injury prevention, motivational experience, and learning experience. From the players’ perspective, care needs to be taken to explain the purpose of an exercise and the benefit it will have for a play performance. Other factors that play an important role in a strength training program are team motivation, individual goal setting, bonding, and communication with the strength coach, as all these items appear to be fundamentals of coaching.

Keywords: self-efficacy, skill performance, sports performance, strength training

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Authors: Marut Phichetvit

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The research objective aims to search information about storytelling and fable associated with fireflies in Amphawa community, in order to design and create a story book which is appropriate for the interests of children in early childhood. This book should help building the development of learning about the natural environment, imagination, and creativity among children, which then, brings about the promotion of the development, conservation and dissemination of cultural values and uniqueness of the Amphawa community. The population used in this study were 30 students in early childhood aged between 6-8 years-old, grade 1-3 from the Demonstration School of Suan Sunandha Rajabhat University. The method used for this study was purposive sampling and the research conducted by the query and analysis of data from both the document and the narrative field tales and fable associated with the fireflies of Amphawa community. Then, using the results to synthesize and create a conceptual design in a form of 8 visual images which were later applied to 1 illustrated children’s book and presented to the experts to evaluate and test this media.

Keywords: children’s illustrated book, fireflies, Amphawa

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Authors: Jordan Shuler

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The goal of this study is to determine whether real-time language translation benefits ESL learners by contributing to overall equity in the classroom. Equity will be measured quantitatively through assessment performance and qualitatively through student survey. Two separate sections of students studying the same course will receive identical curriculum: one group, the control, will be taught in English and the other group in English with real-time translation into the students' first languages. The professor will use Microsoft Translator during lectures, in-class discussions, and Q&A time. The college is committed to finding new ways of teaching and learning, as outlined in Strategy 2022. If this research finds a positive relationship between language translation and student academic success, the technology will surely be encouraged for adoption by all George Brown College faculty. With greater acceptance, this technology could influence equity and pedagogy in the larger educational community.

Keywords: ESL learners, equity, innovative teaching strategies, language translation

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Authors: Raymond Dominic Uzoh

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Starch fillers were extracted from three plant sources namely amora tuber (a wild variety of Irish potato), sweet potato and yam starch and their particle size, pH, amylose, and amylopectin percentage decomposition determined accordingly by high performance liquid chromatography (HPLC). The starch was introduced into natural rubber in liquid phase (through gelatinization) by the latex compounding method and compounded according to standard method. The prepared starch/natural rubber composites was characterized by Instron Universal testing machine (UTM) for tensile mechanical properties. The composites was further characterized by x-ray diffraction and crosslink density analysis. The particle size determination showed that amora starch granules have the highest particle size (156 × 47 μm) followed by yam starch (155× 40 μm) and then the sweet potato starch (153 × 46 μm). The pH test also revealed that amora starch has a near neutral pH of 6.9, yam 6.8, and sweet potato 5.2 respectively. Amylose and amylopectin determination showed that yam starch has a higher percentage of amylose (29.68), followed by potato (22.34) and then amora starch with the lowest value (14.86) respectively. The tensile mechanical properties testing revealed that yam starch produced the best tensile mechanical properties followed by amora starch and then sweet potato starch. The structure, crystallinity/amorphous nature of the product composite was confirmed by x-ray diffraction, while the nature of crosslinking was confirmed by swelling test in toluene solvent using the Flory-Rehner approach. This research study has rendered a workable strategy for enhancing interfacial interaction between a hydrophilic filler (starch) and hydrophobic polymeric matrix (natural rubber) yielding moderately good tensile mechanical properties for further exploitation development and application in the rubber processing industry.

Keywords: natural rubber, fillers, starch, amylose, amylopectin, crosslink density

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Authors: Valeria Cotza

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School drop-out is a multifactorial phenomenon that in Italy concerns all those underage students who, at different school stages (up to 16 years old) or training (up to 18 years old), manifest educational difficulties from dropping out of compulsory education without obtaining a qualification to repetition rates and absenteeism. From the 1980s to the 2000s, there was a progressive attenuation of the economic and social model towards a multifactorial reading of the phenomenon, and the European Commission noted the importance of learning about the phenomenon through approaches able to integrate large-scale quantitative surveys with qualitative analyses. It is not a matter of identifying the contextual factors affecting the phenomenon but problematising them by means of systemic and comprehensive in-depth analysis. So, a privileged point of observation and field of intervention are those schools that propose alternative models of teaching and learning to the traditional ones, such as popular and second-chance schools. Alternative schools and interventions grew in these years in Europe as well as in the US and Latin America, working in the direction of greater equity to create the conditions (often absent in conventional schools) for everyone to achieve educational goals. Against extensive Anglo-Saxon and US literature on this topic, there is yet no unambiguous definition of alternative education, especially in Europe, where second-chance education has been most studied. There is little literature on a second chance in Italy and almost none on alternative education (with the exception of method schools, to which in Italy the concept of “alternative” is linked). This research aims to fill the gap by systematically surveying the alternative interventions in the area and beginning to explore some models of popular and second-chance schools and experiences through a mixed methods approach. So, the main research objectives concern the spread of alternative education in the Lombardy region, the main characteristics of these schools and interventions, and their effectiveness in terms of students’ well-being and school results. This paper seeks to answer the first point by presenting the preliminary results of the first phase of the project dedicated to mapping. Through the Google Forms platform, a questionnaire is being distributed to all schools in Lombardy and some schools in the rest of Italy to map the presence of alternative schools and interventions and their main characteristics. The distribution is also taking place thanks to the support of the Milan Territorial and Lombardy Regional School Offices. Moreover, other social realities outside the school system (such as cooperatives and cultural associations) can be questioned. The schools and other realities to be questioned outside Lombardy will also be identified with the support of INDIRE (Istituto Nazionale per Documentazione, Innovazione e Ricerca Educativa, “National Institute for Documentation, Innovation and Educational Research”) and based on existing literature and the indicators of “Futura” Plan of the PNRR (Piano Nazionale di Ripresa e Resilienza, “National Recovery and Resilience Plan”). Mapping will be crucial and functional for the subsequent qualitative and quantitative phase, which will make use of statistical analysis and constructivist grounded theory.

Keywords: school drop-out, alternative education, popular and second-chance schools, map

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Authors: Dongwon Lee, Sunmyeng Kim

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Underwater acoustic networks (UANs) have become a very active research area in recent years. Compared with wireless networks, UANs are characterized by the limited bandwidth, long propagation delay and high channel dynamic in acoustic modems, which pose challenges to the design of medium access control (MAC) protocol. The characteristics severely affect network performance. In this paper, we study a MS-MAC (Multi-Sender MAC) protocol in order to improve network performance. The proposed protocol exploits temporal reuse by learning the propagation delays to neighboring nodes. A source node locally calculates the transmission schedules of its neighboring nodes and itself based on the propagation delays to avoid collisions. Performance evaluation is conducted using simulation, and confirms that the proposed protocol significantly outperforms the previous protocol in terms of throughput.

Keywords: acoustic channel, MAC, temporal reuse, UAN

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Authors: Saeid Gharechelou, Stuart Green, Fiona Cawkwell

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Hedgerow has an important role for a wide range of ecological habitats, landscape, agriculture management, carbon sequestration, wood production. Hedgerow detection accurately using satellite imagery is a challenging problem in remote sensing techniques, because in the special approach it is very similar to line object like a road, from a spectral viewpoint, a hedge is very similar to a forest. Remote sensors with very high spatial resolution (VHR) recently enable the automatic detection of hedges by the acquisition of images with enough spectral and spatial resolution. Indeed, recently VHR remote sensing data provided the opportunity to detect the hedgerow as line feature but still remain difficulties in monitoring the characterization in landscape scale. In this research is used the TerraSAR-x Spotlight and Staring mode with 3-5 m resolution in wet and dry season in the test site of Fermoy County, Ireland to detect the hedgerow by acquisition time of 2014-2015. Both dual polarization of Spotlight data in HH/VV is using for detection of hedgerow. The varied method of SAR image technique with try and error way by integration of classification algorithm like texture analysis, support vector machine, k-means and random forest are using to detect hedgerow and its characterization. We are applying the Shannon entropy (ShE) and backscattering analysis in single and double bounce in polarimetric analysis for processing the object-oriented classification and finally extracting the hedgerow network. The result still is in progress and need to apply the other method as well to find the best method in study area. Finally, this research is under way to ahead to get the best result and here just present the preliminary work that polarimetric image of TSX potentially can detect the hedgerow.

Keywords: TerraSAR-X, hedgerow detection, high resolution SAR image, dual polarization, polarimetric analysis

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Authors: Amir Mirzaei

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The powertrain system is one of the most basic and essential components in a machine. The occurrence of motion is practically impossible without the presence of this system. When power is generated by the engine, it is transmitted by the powertrain system to the wheels, which are the last parts of the system. Powertrain system has different components according to the type of use and design. When the force generated by the engine reaches to the wheels, the amount of frictional force between the tire and the ground determines the amount of traction and non-slip or the amount of slip. At various levels, such as icy, muddy, and snow-covered ground, the amount of friction coefficient between the tire and the ground decreases dramatically and considerably, which in turn increases the amount of force loss and the vehicle traction decreases drastically. This condition is caused by the phenomenon of slipping, which, in addition to the waste of energy produced, causes the premature wear of driving tires. It also causes the temperature of the transmission oil to rise too much, as a result, causes a reduction in the quality and become dirty to oil and also reduces the useful life of the clutches disk and plates inside the transmission. this issue is much more important in road construction and mining machinery than passenger vehicles and is always one of the most important and significant issues in the design discussion, in order to overcome. One of these methods is the automatic spin regulator system which is abbreviated as ASR. The importance of this method and its structure and function have solved one of the biggest challenges of the powertrain system in the field of construction and mining machinery. That this research is examined.

Keywords: automatic spin regulator, ASR, methods of reducing slipping, methods of preventing the reduction of the useful life of clutches disk and plate, methods of preventing the premature dirtiness of transmission oil, method of preventing the reduction of the useful life of tires

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Authors: Joshna Rani S., Ahmadi Banu

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Artificial Intelligence (AI) has a significant task to carry out in the medical care contributions of things to come. As AI, it is the essential capacity behind the advancement of accuracy medication, generally consented to be a painfully required development in care. Albeit early endeavors at giving analysis and treatment proposals have demonstrated testing, we anticipate that AI will at last dominate that area too. Given the quick propels in AI for imaging examination, it appears to be likely that most radiology, what's more, pathology pictures will be inspected eventually by a machine. Discourse and text acknowledgment are now utilized for assignments like patient correspondence and catch of clinical notes, and their utilization will increment. The best test to AI in these medical services areas isn't regardless of whether the innovations will be sufficiently skilled to be valuable, but instead guaranteeing their appropriation in day by day clinical practice. For far reaching selection to happen, AI frameworks should be affirmed by controllers, coordinated with EHR frameworks, normalized to an adequate degree that comparative items work likewise, instructed to clinicians, paid for by open or private payer associations, and refreshed over the long haul in the field. These difficulties will, at last, be survived, yet they will take any longer to do as such than it will take for the actual innovations to develop. Therefore, we hope to see restricted utilization of AI in clinical practice inside 5 years and more broad use inside 10 years. It likewise appears to be progressively evident that AI frameworks won't supplant human clinicians for a huge scope, yet rather will increase their endeavors to really focus on patients. Over the long haul, human clinicians may advance toward errands and work plans that draw on remarkably human abilities like sympathy, influence, and higher perspective mix. Maybe the lone medical services suppliers who will chance their professions over the long run might be the individuals who will not work close by AI

Keywords: artificial intellogence, health care, breast cancer, AI applications

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Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

Abstract:

The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

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Authors: Getaneh Berie Tarekegn

Abstract:

A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. It also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 57

Authors: O. Lasaga

Abstract:

Defining professional objectives and the search for work are some of the greatest stress factors for final year university students and recent graduates. To manage correctly the stress brought about by the uncertainty, confusion and frustration this process often generates, a course to control stress based on mindfulness has been designed and taught. This course provides tools based on relaxation, mindfulness and meditation that enable students to address personal and professional challenges in the transition to the job market, eliminating or easing the anxiety involved. The course is extremely practical and experiential, combining theory classes and practical classes of relaxation, meditation and mindfulness, group dynamics, reflection, application protocols and session integration. The evaluation of the courses highlighted on the one hand the high degree of satisfaction and, on the other, the usefulness for the students in becoming aware of stressful situations and how these affect them and learning new coping techniques that enable them to reach their goals more easily and with greater satisfaction and well-being.

Keywords: employability, meditation, mindfulness, relaxation techniques, stress

Procedia PDF Downloads 385

Authors: Fulya Gokalp Yavuz, Mark Daniel Ward

Abstract:

This study focuses on a contemporary and inevitable topic of Data Science and its exemplary application for early career building: Big Data and Leaving Learning Community (LLC). ‘Academia’ and ‘Industry’ have a common sense on the importance of Big Data. However, both of them are in a threat of missing the training on this interdisciplinary area. Some traditional teaching doctrines are far away being effective on Data Science. Practitioners needs some intuition and real-life examples how to apply new methods to data in size of terabytes. We simply explain the scope of Data Science training and exemplified its early stage application with LLC, which is a National Science Foundation (NSF) founded project under the supervision of Prof. Ward since 2014. Essentially, we aim to give some intuition for professors, researchers and practitioners to combine data science tools for comprehensive real-life examples with the guides of mentees’ feedback. As a result of discussing mentoring methods and computational challenges of Big Data, we intend to underline its potential with some more realization.

Keywords: Big Data, computation, mentoring, training

Procedia PDF Downloads 361

Authors: Abdallah Al-ZoubI, Mamoun Dmour

Abstract:

The spectrum of IoT devices is becoming widely diversified, entering almost all possible fields and finding applications in industry, health, finance, logistics, education, to name a few. The IoT active endpoint sensors and devices exceeded the 12 billion mark in 2021 and are expected to reach 27 billion in 2025, with over $34 billion in total market value. This sheer rise in numbers and use of IoT devices bring with it considerable concerns regarding data storage, analysis, manipulation and protection. IoT Blockchain-based systems have recently been proposed as a decentralized solution for large-scale data storage and protection. COVID-19 has actually accelerated the desire to utilize IoT devices as it impacted both demand and supply and significantly affected several regions due to logistic reasons such as supply chain interruptions, shortage of shipping containers and port congestion. An IoT-blockchain system is proposed to handle big data generated by a distributed network of sensors and controllers in an interactive manner. The system is designed using the Ethereum platform, which utilizes smart contracts, programmed in solidity to execute and manage data generated by IoT sensors and devices. such as Raspberry Pi 4, Rasbpian, and add-on hardware security modules. The proposed system will run a number of applications hosted by a local machine used to validate transactions. It then sends data to the rest of the network through InterPlanetary File System (IPFS) and Ethereum Swarm, forming a closed IoT ecosystem run by blockchain where a number of distributed IoT devices can communicate and interact, thus forming a closed, controlled environment. A prototype has been deployed with three IoT handling units distributed over a wide geographical space in order to examine its feasibility, performance and costs. Initial results indicated that big IoT data retrieval and storage is feasible and interactivity is possible, provided that certain conditions of cost, speed and thorough put are met.

Keywords: IoT devices, blockchain, Ethereum, big data

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Authors: F. B. Masok, S. S Songdeg, R. R. Dawam

Abstract:

Vision is an important process for learning and communication as man depends greatly on vision to sense his environment. Prevalence and variation of refractive errors conducted between December 2010 and May 2011 in Jos, revealed that 735 (77.50%) out 950 subjects examined for refractive error had various refractive errors. Myopia was observed in 373 (49.79%) of the subjects, the error in the right eyes was 263 (55.60%) while the error in the left was 210(44.39%). The mean myopic error was found to be -1.54± 3.32. Hyperopia was observed in 385 (40.53%) of the sampled population comprising 203(52.73%) of the right eyes and 182(47.27%). The mean hyperopic error was found to be +1.74± 3.13. Astigmatism accounted for 359 (38.84%) of the subjects, out of which 193(53.76%) were in the right eyes while 168(46.79%) were in the left eyes. Presbyopia was found in 404(42.53%) of the subjects, of this figure, 164(40.59%) were in the right eyes while 240(59.41%) were in left eyes. The number of right eyes and left eyes with refractive errors was observed in some age groups to increase with age and later had its peak within 60 – 69 age groups. This pattern of refractive errors could be attributed to exposure to various forms of light particularly the ultraviolet rays (e.g rays from television and computer screen). There was no remarkable differences between the mean Myopic error and mean Hyperopic error in the right eyes and in the left eyes which suggest the right eye and the left eye are similar.

Keywords: left eye, refractive errors, right eye, variation

Procedia PDF Downloads 430

Authors: Carina Hermansson

Abstract:

This presentation focuses a development project aiming at developing and documenting the steps taken at a multilingual, multicultural K-5 school, with the aim to improve the achievement levels of the pupils by focusing language and literacy development across the schedule in a digital classroom, and in all units of the school. This pre-formulated aim, thus, may be said to adhere to neoliberal educational and accountability policies in terms of its focus on digital learning, learning results, and national curriculum standards. In particular the project aimed at improving the collaboration between the teachers, the leisure time unit, the librarians, the mother tongue teachers and bilingual study counselors. This is a school environment characterized by cultural, ethnic, linguistic, and professional pluralization. The overarching aims of the research project were to scrutinize and analyze the factors enabling and obstructing the implementation of the Language Policy in a digital classroom. Theoretical framework: We apply multi-level perspectives in the analyses inspired by Uljens’ ideas about interactive and interpersonal first order (teacher/students) and second order(principal/teachers and other staff) educational leadership as described within the framework of discursive institutionalism, when we try to relate the Language Policy, educational policy, and curriculum with the administrative processes. Methodology/research design: The development project is based on recurring research circles where teachers, leisure time assistants, mother tongue teachers and study counselors speaking the mother tongue of the pupils together with two researchers discuss their digital literacy practices in the classroom. The researchers have in collaboration with the principal developed guidelines for the work, expressed in a Language Policy document. In our understanding the document is, however, only a part of the concept, the actions of the personnel and their reflections on the practice constitute the major part of the development project. One and a half years out of three years have now passed and the project has met with a row of difficulties which shed light on factors of importance for the progress of the development project. Field notes and recordings from the research circles, a survey with the personnel, and recorded group interviews provide data on the progress of the project. Expected conclusions: The problems experienced deal with leadership, curriculum, interplay between aims, technology, contents and methods, the parents as customers taking their children to other schools, conflicting values, and interactional difficulties, that is, phenomena on different levels, ranging from school to a societal level, as for example teachers being substituted as a result of the marketization of schools. Also underlying assumptions from actors at different levels create obstacles. We find this study and the problems we are facing utterly important to share and discuss in an era with a steady flow of refugees arriving in the Nordic countries.

Keywords: early childhood education, language policy, multicultural school, school development project

Procedia PDF Downloads 144