Search results for: batch-constrained reinforcement learning

Authors: Amanda Watson

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The goal of this project is to create the conditions wherein every teacher, especially subjectarea experts, sees themselves as a teacher of language and vocabulary. Assessment and observational data suggest that students are not getting the support they need in vocabulary and reading comprehension, and secondary teachers do not currently have the confidence or expertise to provide this support. This study seeks to examine the impact of 10-20 minutes of daily, targeted instruction around orthography and vocabulary on student competence with the navigation of complex vocabulary and comprehension of subject-specific concepts and texts. The first phase of the pilot included 6 participating classroom teachers of grades 9 and 10 English (95 students in total) who administered an initial reading comprehension assessment. The results of this assessment indicated that the vast majority of students were reading below grade level. Teachers were then provided with a slide deck of complete lessons on orthography, vocabulary (etymology, roots and affixes) and reading comprehension strategies. For five weeks, teachers delivered lessons with their students, implementing the recommended evidence-based teaching strategies. Students and teachers completed surveys to provide feedback on the value and impact of the method. The results confirmed that this was new learning for the students and that the teaching strategies improved engagement. The lessons succeeded in providing equitable access to challenge by simultaneously offering theoretical learning to proficient readers, and exposure and practice to weaker readers. A second reading comprehension was administered after 5 weeks of daily instruction. Average scores increased by 41%, and almost every student experienced progress. The first phase was not long enough to measure the impact of the method on vocabulary acquisition or reading comprehension of subject-specific texts, however. The project will use the results of the first phase to design the second phase, and new teaching and learning strategies will be added. The goals of the second phases are to increase motivation, and to grow the daily practice beyond English class and into science and / or math. This team will continue to document a continuation of the daily lessons, Commented [E1]: Please do not use rhetorical questions in the abstract. measure the impact of the strategies, and address questions about the correlation between daily practice and improvements in the skills students need for vocabulary acquisition and disciplinary reading comprehension.

Keywords: adolescent, comprehension, orthography, reading, vocabulary, etymology, word study, disciplinary, teaching strategies

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Authors: Ezedin Geta Seid

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Slope failures are among the common geo-environmental natural hazards in the hilly and mountainous terrain of the world causing damages to human life and destruction of infrastructures. In Ethiopia, the demand for the construction of infrastructures, especially highways and railways, has increased to connect the developmental centers. However, the failure of roadside slopes formed due to the difficulty of geographical locations is the major difficulty for this development. As a result, a comprehensive site-specific investigation of destabilizing agents and a suitable selection of slope profiles are needed during design. Hence, this study emphasized the stability analysis and performance evaluation of slope profiles (single slope, multi-slope, and benched slope). The analysis was conducted for static and dynamic loading conditions using limit equilibrium (slide software) and finite element method (Praxis software). The analysis results in selected critical sections show that the slope is marginally stable, with FS varying from 1.2 to 1.5 in static conditions, and unstable with FS below 1 in dynamic conditions. From the comparison of analysis methods, the finite element method provides more valuable information about the failure surface of a slope than limit equilibrium analysis. Performance evaluation of geometric profiles shows that geometric modification provides better and more economical slope stability. Benching provides significant stability for cut slopes (i.e., the use of 2m and 3m bench improves the factor of safety by 7.5% and 12% from a single slope profile). The method is more effective on steep slopes. Similarly, the use of a multi-slope profile improves the stability of the slope in stratified soil with varied strength. The performance is more significant when it is used in combination with benches. The study also recommends drainage control and slope reinforcement as a remedial measure for cut slopes.

Keywords: slope failure, slope profile, bench slope, multi slope

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Authors: Theoktisti Makridou, Konstantinos Tsaprailis, George Arvanitakis, Charalampos Kontoes

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In the literature, the data-driven approaches for mosquito abundance prediction relaying on supervised machine learning models that get trained with historical in-situ measurements. The counterpart of this approach is once the model gets trained on pointlevel (specific x,y coordinates) measurements, the predictions of the model refer again to point-level. These point-level predictions reduce the applicability of those solutions once a lot of early warning and mitigation actions applications need predictions for an area level, such as a municipality, village, etc... In this study, we apply a data-driven predictive model, which relies on public-open satellite Earth Observation and geospatial data and gets trained with historical point-level in-Situ measurements of mosquito abundance. Then we propose a methodology to extract information from a point-level predictive model to a broader area-level prediction. Our methodology relies on the randomly spatial sampling of the area of interest (similar to the Poisson hardcore process), obtaining the EO and geomorphological information for each sample, doing the point-wise prediction for each sample, and aggregating the predictions to represent the average mosquito abundance of the area. We quantify the performance of the transformation from the pointlevel to the area-level predictions, and we analyze it in order to understand which parameters have a positive or negative impact on it. The goal of this study is to propose a methodology that predicts the mosquito abundance of a given area by relying on point-level prediction and to provide qualitative insights regarding the expected performance of the area-level prediction. We applied our methodology to historical data (of Culex pipiens) of two areas of interest (Veneto region of Italy and Central Macedonia of Greece). In both cases, the results were consistent. The mean mosquito abundance of a given area can be estimated with similar accuracy to the point-level predictor, sometimes even better. The density of the samples that we use to represent one area has a positive effect on the performance in contrast to the actual number of sampling points which is not informative at all regarding the performance without the size of the area. Additionally, we saw that the distance between the sampling points and the real in-situ measurements that were used for training did not strongly affect the performance.

Keywords: mosquito abundance, supervised machine learning, culex pipiens, spatial sampling, west nile virus, earth observation data

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Authors: Zikra Faiz, Zaheer Asghar, Nisar Abid

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Information and Communication Technologies (ICTs) includes computers, the Internet, and electronic delivery systems such as televisions, radios, multimedia, and overhead projectors etc. In the modern world, ICTs is considered as an essential element of the teaching-learning process. The study was aimed to discover the usage of ICTs in Special Education Institutions for Visually Impaired students, Lahore, Pakistan. Objectives of the study were to explore the problems faced by teachers while using ICT in the classroom. The study was phenomenology in nature; a qualitative survey method was used through a semi-structured interview protocol developed by the researchers. The sample comprised of eighty faculty members selected through a purposive sampling technique. Data were analyzed through thematic analysis technique with the help of open coding. The study findings revealed that multimedia, projectors, computers, laptops and LEDs are used in special education institutes to enhance the teaching-learning process. Teachers believed that ICTs could enhance the knowledge of visually impaired students and every student should use these technologies in the classroom. It was concluded that multimedia, projectors and laptops are used in classroom by teachers and students. ICTs can promote effectively through the training of teachers and students. It was suggested that the government should take steps to enhance ICTs in teacher training and other institutions by pre-service and in-service training of teachers.

Keywords: information and communication technologies, in-services teachers, special education institutions

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Authors: Alireza Behfar, Mohammad Mahdavi

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Nowadays, in the light of progress in the world of science, technology and communications, mastery of learning international languages is a sure and needful matter. In learning any language as a second language, progress and achieving a desirable level in speaking is indeed important for approximately all learners. In this research, we find out how preparation can influence L2 learners' oral fluency with respect to individual differences in working memory capacity. The participants consisted of sixty-one advanced L2 learners including MA students of TEFL at Isfahan University as well as instructors teaching English at Sadr Institute in Isfahan. The data collection consisted of two phases: A working memory test (reading span test) and a picture description task, with a one-month interval between the two tasks. Speaking was elicited through speech generation task in which the individuals were asked to discuss four topics emerging in two pairs. The two pairs included one simple and one complex topic and was accompanied by planning time and without any planning time respectively. Each topic was accompanied by several relevant pictures. L2 fluency was assessed based on preparation. The data were then analyzed in terms of the number of syllables, the number of silent pauses, and the mean length of pauses produced per minute. The study offers implications for strategies to improve learners’ both fluency and working memory.

Keywords: two factors, fluency, working memory capacity, preparation, L2 speech production reading span test picture description

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Authors: Tanyaporn Chairoch

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Introduction: Cannabis is a drug to treat patients with many diseases such as Multiple sclerosis, Alzheimer’s disease, and Epilepsy, where theycontain many active compounds such as delta-9 tetrahydrocannabinol (THC) and cannabidiol (CBD). Especially, THC is the primary psychoactive ingredient in cannabis and binds to cannabinoid 1 (CB1) receptors. Moreover, CB1 is located on the neocortex, hippocampus, basal ganglia, cerebellum, and brainstem. In previous study, we found the association between the variant of CB1recptors gene (rs2023239) and decreased effect of nicotine reinforcement in patients. However, there are no data describing whether the distribution of CB1 receptor gene is a genetic marker for Thai patients who are treated with cannabis. Objective: Thus, the aim of this study we want to investigate the frequency of the CB1 receptor gene in Thai patients. Materials and Methods: All of sixty Thai patients received the medical cannabis for treatment who were recruited in this study. DNA will be extracted from EDTA whole blood by Genomic DNA Mini Kit. The genotyping of CNR1 gene (rs 2023239) was genotyped by the TaqMan real time PCR assay (ABI, Foster City, CA, USA).and using the real-time PCR ViiA7 (ABI, Foster City, CA, USA). Results: We found thirty-eight (63.3%) Thai patients were female, and twenty-two (36.70%) were male in this study with median age of 45.8 (range19 – 87 ) years. Especially, thirty-two (53.30%) medical cannabis tolerant controls were female ( 55%) and median age of52.1 (range 27 – 79 ) years. The most adverse effects for medical cannabis treatment was tachycardia. Furthermore, the number of rs 2023239 (TT) carriers was 26 of 27 (96.29%) in medical cannabis-induced adverse effects and 32 of 33 (96.96%) in tolerant controls. Additionally, rs 2023239 (CT) variant was found just only one of twenty-seven (3.7%) in medical cannabis-induced adverse effects and 1 of 33 (3.03%) in tolerant controls. Conclusions: The distribution of genetic variant in CNR1 gene might serve as a pharmacogenetics markers for screening before initiating the therapy with medical cannabis in Thai patients.

Keywords: cannabis, pharmacogenetics, CNR1 gene, thai patient

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Authors: Karen Odendaal

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Accounting transactions are becoming more complex, and more extensive accounting guidance is provided on a continuous basis. It is widely perceived that conceptual teaching of accounting contributes to lifelong learning. Such a conceptual teaching approach also contributes to effective accounting problem-solving. This framework-based approach is rooted in educational psychologies such as constructivism and Ausubel’s subsumption theory. This study aimed at investigating the ability of students to solve complex accounting problems by using only concepts underlying the Conceptual Framework. An assignment was administered to pre-graduate students at a South African university and this study made use of an interpretative research design which implemented multiple research instruments to investigate the ability of students to solve complex accounting problems using only concepts underlying the Conceptual Framework. Student perceptions were analysed and were aided by a related reflective questionnaire. The importance of the study indicates the necessity of Accounting educators to enhance a conceptual understanding among students as a mechanism for problem-solving of accounting issues. The results indicate that the ability of students to solve accounting problems effectively using only the Conceptual Framework depends on the complexity of the scenario and the students’ familiarity with the problem. The study promotes a balanced and more conceptual (rather than only technical) preference to the problem-solving of complex accounting problems. The study indubitably promotes considerable emphasis on the importance of the Conceptual Framework in accounting education and the promotion of life-long learning in the subject field.

Keywords: accounting education, conceptual teaching, constructivism, framework-based, problem-solving

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Authors: Cristóbal Moënne-Loccoz, Rodrigo C. Vergara, Vladimir López, Domingo Mery, Diego Cosmelli

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Our daily interaction with computational interfaces is plagued of situations in which we go from inexperienced users to experts through self-motivated exploration of the same task. In many of these interactions, we must learn to find our way through a sequence of decisions and actions before obtaining the desired result. For instance, when drawing cash from an ATM machine, choices are presented in a step-by-step fashion so that a specific sequence of actions must be performed in order to produce the expected outcome. But, as they become experts in the use of such interfaces, do users adopt specific search and learning strategies? Moreover, if so, can we use this information to follow the process of expertise development and, eventually, predict future actions? This would be a critical step towards building truly adaptive interfaces that can facilitate interaction at different moments of the learning curve. Furthermore, it could provide a window into potential mechanisms underlying decision-making behavior in real world scenarios. Here we tackle this question using a simple game interface that instantiates a 4-level binary decision tree (BDT) sequential decision-making task. Participants have to explore the interface and discover an underlying concept-icon mapping in order to complete the game. We develop a Hidden Markov Model (HMM)-based approach whereby a set of stereotyped, hierarchically related search behaviors act as hidden states. Using this model, we are able to track the decision-making process as participants explore, learn and develop expertise in the use of the interface. Our results show that partitioning the problem space into such stereotyped strategies is sufficient to capture a host of exploratory and learning behaviors. Moreover, using the modular architecture of stereotyped strategies as a Mixture of Experts, we are able to simultaneously ask the experts about the user's most probable future actions. We show that for those participants that learn the task, it becomes possible to predict their next decision, above chance, approximately halfway through the game. Our long-term goal is, on the basis of a better understanding of real-world decision-making processes, to inform the construction of interfaces that can establish dynamic conversations with their users in order to facilitate the development of expertise.

Keywords: behavioral modeling, expertise acquisition, hidden markov models, sequential decision-making

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Authors: Amin Kaveh Boukani

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Foreign language learning is not straightforward and can be affected by numerous factors, among which personality features like tolerance of ambiguity (TA) are so well-known and important. Such characteristics yet can be affected by other factors like learning additional languages. The current investigation, thus, opted to explore the possible effect of linguistic background (being bilingual or trilingual) on the tolerance of ambiguity (TA) of Iranian EFL learners. Furthermore, the possible mediating effect of TA on multilingual learners' language performance (listening comprehension in this study) was expounded. This research involved 68 EFL learners (32 bilinguals, 29 trilinguals) with the age range of 19-29 doing their degrees in the Department of English Language and Literature of Urmia University. A set of questionnaires, including tolerance of ambiguity (Herman et. al., 2010) and linguistic background information (Modirkhameneh, 2005), as well as the IELTS listening comprehension test, were used for data collection purposes. The results of a set of independent samples t-test and mediation analysis (Hayes, 2022) showed that (1) linguistic background (being bilingual or trilingual) had a significant direct effect on EFL learners' TA, (2) Linguistic background had a significant direct influence on listening comprehension, (3) TA had a substantial direct influence on listening comprehension, and (4) TA moderated the influence of linguistic background on listening comprehension considerably. These results suggest that multilingualism may be considered as an advantageous asset for EFL learners and should be a prioritized characteristic in EFL instruction in multilingual contexts. Further pedagogical implications and suggestions for research are proposed in light of effective EFL instruction in multilingual contexts.

Keywords: tolerance of ambiguity, listening comprehension, multilingualism, bilingual, trilingual

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Authors: Sonia Pajaron, Flaviano Sentina, Ranulfo Etulle

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Learning a second language calls for a total commitment from the learner whose response is necessary to successfully send and receive linguistic messages. It is relevant to virtually every aspect of human behaviour which is even more challenging when the components on -affective domains- are involved in second language learning. This study investigated the association between the identified affective attributes and second language performance of the one hundred seventeen (117) randomly selected third year maritime students. A descriptive-correlational method was utilized to generate data on their affective attributes while composition writing (2 series) and IELTS-based interview was done for speaking test. Additionally, to establish the respondents’ English language profile, data on their high school grades (GPA), entrance exam results in English subject (written) as well as in the interview was extracted as baseline information. Data were subjected to various statistical treatment (average means, percentages and pearson-r moment coefficient correlation) and found out that, Nautical Science and Marine Engineering students were found to have average high school grade, entrance test results, both written and in the interview turned out to be very satisfactory at 50% passing percentage. Varied results were manifested in their affective attributes towards learning the second language. On attitude, nautical science students had true positive attitude while marine engineering had only a moderate positive one. Secondly, the former were positively motivated to learn English while the latter were just moderately motivated. As regards anxiety, both groups embodied a moderate level of anxiety in the English language. Finally, data showed that nautical science students exuded real confidence while the marine engineering group had only moderate confidence with the second language. Respondents’ English academic achievement (GWA) was significantly correlated with confidence and speaking with anxiety towards the second language among the students from the nautical science group with moderate positive and low negative degree of correlation, respectively. On the other hand, the marine engineering students’ speaking test result was significantly correlated with anxiety and self-confidence with a moderate negative and low positive degree of correlation, respectively while writing was significantly correlated with motivation bearing a low positive degree of correlation.

Keywords: affective attributes, second language, second language performance, anxiety, attitude, self-confidence and motivation

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Authors: Maria Luiza Fulga, Georgeta Truca, Mihaela Alexandru, Andriescu Mariana, Crin Marcean

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The significance of nursing as a subject in the post-secondary healthcare curriculum is a major. We aimed to enable our students to assess the patient's risk, to establish prevention measures and to adapt to a specific learning context, in order to acquire the skills and abilities necessary for the nursing profession. In order to achieve these objectives, during the three years of study, teachers put an emphasis on acquiring communication skills, because in our country after the first cycle of hospital accreditation concluded in 2016, the National Authority for Quality of Health Management has introduced the criteria for the implementation and application of the nursing process according to the accreditation standards. According to these requirements, the nurse has to carry out the nursing assessment, based on communication as a distinct component, so that they can identify nursing diagnoses and implement the nursing plan. In this respect, we, the teachers, have refocused, by approaching various teaching strategies and preparing students for the real context of learning and applying what they learn. In the educational process, the tutors in the hospitals have an important role to play in acquiring professional skills. Students perform their activity in the hospital in accordance with the curriculum, in order to verify the practical applicability of the theoretical knowledge acquired in the school classes and also have the opportunity to acquire their skills in a real learning context. In clinical education, the student nurse learns in the middle of a guidance team which includes a practice tutor, who is a nurse that takes responsibility for the practical/clinical learning of the students in their field of activity. In achieving this objective, the tutor's abilities involve pedagogical knowledge, knowledge for the good of the individual and nursing theory, in order to be able to guide clinical practice in accordance with current requirements. The aim of this study is to find out the students’ confidence level in practice tutors in hospitals, the students’ degree of satisfaction in the pedagogical skills of the tutors and the practical applicability of the theoretical knowledge. In this study, we used as a method of investigation a student satisfaction questionnaire regarding the clinical practice in the hospital and the sample of the survey consisted of 100 students aged between 20 and 50 years, from the first, second and third year groups, with the General Nurse specialty (nurses responsible for general care), from 'Fundeni' Healthcare Post-Secondary School, Bucharest, Romania. Following the analysis of the data provided, we arrived the conclusion that the hospital tutor needs to improve his/her pedagogical skills, the knowledge of nursing diagnostics, and the implementation of the nursing plan, so that the applicability of the theoretical notions would be increased. Future plans include the pedagogical training of the medical staff, as well as updating the knowledge needed to implement the nursing process in order to meet current requirements.

Keywords: clinical training, nursing process, pedagogical skills, tutor

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Authors: Shelley Harrington

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As a result of increasingly dynamic business environments, the creation and fostering of dynamic capabilities, [those capabilities that enable sustained competitive success despite of dynamism through the awareness and reconfiguration of internal and external competencies], supported by organisational learning [a dynamic capability] has gained increased and prevalent momentum in the research arena. Presenting findings funded by the Economic Social Research Council, this paper investigates the extent to which Senior Management Team (SMT) personality (at the trait and facet level) is associated with the creation of dynamic managerial capabilities at the team level, and effective organisational learning/knowledge sharing within the firm. In doing so, this research highlights the importance of micro-foundations in organisational psychology and specifically dynamic capabilities, a field which to date has largely ignored the importance of psychology in understanding these important and necessary capabilities. Using a direct measure of personality (NEO PI-3) at the trait and facet level across 32 high technology and finance firms in the UK, their CEOs (N=32) and their complete SMTs [N=212], a new measure of dynamic managerial capabilities at the team level was created and statistically validated for use within the work. A quantitative methodology was employed with regression and gap analysis being used to show the empirical foundations of personality being positioned as a micro-foundation of dynamic capabilities. The results of this study found that personality homogeneity within the SMT was required to strengthen the dynamic managerial capabilities of sensing, seizing and transforming, something which was required to reflect strong organisational learning at middle management level [N=533]. In particular, it was found that the greater the difference [t-score gaps] between the personality profiles of a Chief Executive Officer (CEO) and their complete, collective SMT, the lower the resulting self-reported nature of dynamic managerial capabilities. For example; the larger the difference between a CEOs level of dutifulness, a facet contributing to the definition of conscientiousness, and their SMT’s level of dutifulness, the lower the reported level of transforming, a capability fundamental to strategic change in a dynamic business environment. This in turn directly questions recent trends, particularly in upper echelons research highlighting the need for heterogeneity within teams. In doing so, it successfully positions personality as a micro-foundation of dynamic capabilities, thus contributing to recent discussions from within the strategic management field calling for the need to empirically explore dynamic capabilities at such a level.

Keywords: dynamic managerial capabilities, senior management teams, personality, dynamism

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Authors: Mihail Nagea, Olivera Lupescu, Elena Taina Avramescu, Cristina Patru

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Classical education of orthopedic surgeons involves lectures, self study, workshops and cadaver dissections, and sometimes supervised practical training within surgery, which quite seldom gives the young surgeons the feeling of being unable to apply what they have learned especially in surgical practice. The purpose of this paper is to present a different approach from the classical one, which enhances the practical skills of the orthopedic trainees and prepare them for future practice. The paper presents the content of the research project 2015-1-RO01-KA202-015230, ERASMUS+ VET ‘Collaborative learning for enhancing practical skills for patient-focused interventions in gait rehabilitation after orthopedic surgery’ which, using e learning as a basic tool , delivers to the trainees not only courses, but especially practical information through videos and case scenarios including gait analysis in order to build patient focused therapeutic plans, adapted to the characteristics of each patient. The outcome of this project is to enhance the practical skills in orthopedic surgery and the results are evaluated following the answers to the questionnaires, but especially the reactions within the case scenarios. The participants will thus follow the idea that any mistake within solving the cases might represent a failure of treating a real patient. This modern approach, besides using interactivity to evaluate the theoretical and practical knowledge of the trainee, increases the sense of responsibility, as well as the ability to react properly in real cases.

Keywords: interdisciplinary approach, gait analysis, orthopedic surgery, vocational training

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Authors: Nadir Ali Mugheri, Shaukat Ali Lohar

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In a multilingual society like Pakistan, code switching is commonly observed in different contexts. Mostly people use L1 (Native Languages) and L2 for common communications and L3 (i.e. English, Urdu, Sindhi) in formal contexts and for academic writings. Such a frequent code switching does affect EFL learners' acquisition of grammar and lexis of the target language which in the long run result in different types of errors in their writings. The current study is to investigate and identify common elements of L1 and L2 (spoken by students of the Universities in Pakistan) which create hindrances for EFL learners. Case study method was used for this research. Formal writings of 400 EFL learners (as participants from various Universities of the country) were observed. Among 400 participants, 200 were female and 200 were male EFL learners having different academic backgrounds. Errors found were categorized into different types according to grammatical items, the difference in meanings, structure of sentences and identifiers of tenses of L1 or L2 in comparison with those of the target language. The findings showed that EFL learners in Pakistani varsities have serious problems in their writings and they committed serious errors related to the grammar and meanings of the target language. After analysis of the committed errors, the results were found in the affirmation of the hypothesis that L1 or L2 does affect EFL learners. The research suggests in the end to adopt natural ways in pedagogy like task-based learning or communicative methods using contextualized material so as to avoid impediments of L1 or L2 in acquisition the target language.

Keywords: multilingualism, L2 acquisition, code switching, language acquisition, communicative language teaching

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Authors: Edison E. Haro, Akindele G. Odeshi, Jerzy A. Szpunar

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Hybrid bio-composites are developed for use in protective armor through positive hybridization offered by reinforcement of high-density polyethylene (HDPE) with Kevlar short fibers and palm wood micro-fillers. The manufacturing process involved a combination of extrusion and compression molding techniques. The mechanical behavior of Kevlar fiber reinforced HDPE with and without palm wood filler additions are compared. The effect of the weight fraction of the added palm wood micro-fillers is also determined. The Young modulus was found to increase as the weight fraction of organic micro-particles increased. However, the flexural strength decreased with increasing weight fraction of added micro-fillers. The interfacial interactions between the components were investigated using scanning electron microscopy. The influence of the size, random alignment and distribution of the natural micro-particles was evaluated. Ballistic impact and dynamic shock loading tests were performed to determine the optimum proportion of Kevlar short fibers and organic micro-fillers needed to improve impact strength of the HDPE. These results indicate a positive hybridization by deposition of organic micro-fillers on the surface of short Kevlar fibers used in reinforcing the thermoplastic matrix leading to enhancement of the mechanical strength and dynamic impact behavior of these materials. Therefore, these hybrid bio-composites can be promising materials for different applications against high velocity impacts.

Keywords: hybrid bio-composites, organic nano-fillers, dynamic shocking loading, ballistic impacts, energy absorption

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Authors: Anantdeep Kaur, Sharanjeet Singh

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Early childhood education and assessment of children is a very essential tool that helps them in their growth and development. Techniques should be developed, and tools should be created in this field as it is a very important learning phase of life. Some information and sources are included for student assessment to provide a record of growth in all developmental areas cognitive, physical, Language, social-emotional, and approaches to learning. As an early childhood educator, it is very important to identify children who need special support and counseling to improve them because they are not mentally mature to discuss with the teacher their problems and needs. It is the duty and responsibility of the educator to assess children from their body language, behavior, and their routine actions about their skills that can be improved and which can take them forward in their future life. And also, children should be assessed with their weaker points because this is the right time to correct them, and they be improved with certain methods and tools by working on them constantly. Observing children regularly with all their facets of development, including intellectual, linguistic, social-emotional, and physical development. Every day, a physical education class should be regulated to check their physical growth activities, which can help to assess their physical activeness and motor abilities. When they are outside on the playgrounds, it is very important to instill environmental understanding among them so that they should know that they are very part of this nature, and it will help them to be one with the universe rather than feeling themselves individually. This technique assists them in living their childhood full of energy all the time. All types of assessments have unique purposes. It is important first to determine what should be measured, then find the program that best assesses those.

Keywords: special needs, motor ability, environmental understanding, physical development

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Authors: Michael Flannery, Annie ó Breacháin

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Teaching the creative arts in preservice teacher education can be challenging. Some students find artistic self-expression and its related creative processes overwhelming. Low creative self-efficacy levels and creative habits of mind can impede their levels of motivation, engagement and persistence. For some, creative arts engagement can induce a state of anxiety and distress as opposed to flow. Flow theory posits that learners are happiest when they are learning in a state of flow. During the flow state, students feel, think and perform their best. They become so involved in the learning experience that nothing else seems to matter. The creative flow state is a crucial conduit of artistic processes to enable learners to explore and produce their best work. Despite the research conducted on flow state across several contexts, the phenomenon of personal flow state remains quite elusive. While some research has examined flow in relation to characteristics, conditions and personality traits, no research has investigated individuals' personal experiences of flow in a visual and tangible manner nor explored a relationship between flow state and teachers’ artistic development. This explorative case study explores preservice teachers’ impressions of flow using an arts-based approach. It identifies, categorizes and discusses patterns of commonality and difference. Grounded by theory concerning flow, self-efficacy and creative habits, this study ponders how emerging findings regarding flow impressions might aid teacher arts educators in helping preservice teachers who struggle with creative self-expression.

Keywords: creative arts, flow theory, presence, self-efficacy, teacher education

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Authors: Mateusz Frydrych

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The construction of diaphragm walls as excavation shoring as well as part of deep foundations is widely used in geotechnical engineering. Today's design challenges lie in the optimal dimensioning of the cross-section, which is demanded by technological considerations. Also in force is the issue of optimization and sustainable use of construction materials, including reduction of carbon footprint, which is currently a relevant challenge for the construction industry. The author presents the concept of an approach to achieving increased efficiency of diaphragm wall excavation shoring by using structural compression technology. The author proposes to implement prestressed tendons in a non-linear manner in the reinforcement cage. As a result bending moment is reduced, which translates into a reduction in the amount of steel needed in the section, a reduction in displacements, and a reduction in the scratching of the casing, including the achievement of better tightness. This task is rarely seen and has not yet been described in a scientific way in the literature. The author has developed a dynamic numerical model that allows the dimensioning of the cross-section of a prestressed shear wall, as well as the study of casing displacements and cross-sectional forces in any defined computational situation. Numerical software from the Sofistik - open source development environment - was used for the study, and models were validated in Plaxis software . This is an interesting idea that allows for optimizing the execution of construction works and reducing the required resources by using fewer materials and saving time. The author presents the possibilities of a prestressed diaphragm wall, among others, using. The example of a diaphragm wall working as a cantilever at the height of two underground floors without additional strutting or stability protection by using ground anchors. This makes the execution of the work more criminal for the contractor and, as a result, cheaper for the investor.

Keywords: prestressed diaphragm wall, Plaxis, Sofistik, innovation, FEM, optimisation

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Authors: Pitigalage Chamath Chandira Peiris

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A widely researched domain in the field of image processing in recent times has been single image super-resolution, which tries to restore a high-resolution image from a single low-resolution image. Many more single image super-resolution efforts have been completed utilizing equally traditional and deep learning methodologies, as well as a variety of other methodologies. Deep learning-based super-resolution methods, in particular, have received significant interest. As of now, the most advanced image restoration approaches are based on convolutional neural networks; nevertheless, only a few efforts have been performed using Transformers, which have demonstrated excellent performance on high-level vision tasks. The effectiveness of CNN-based algorithms in image super-resolution has been impressive. However, these methods cannot completely capture the non-local features of the data. Enhancer is a simple yet powerful Transformer-based approach for enhancing the resolution of images. A method for single image super-resolution was developed in this study, which utilized an efficient and effective transformer design. This proposed architecture makes use of a locally enhanced window transformer block to alleviate the enormous computational load associated with non-overlapping window-based self-attention. Additionally, it incorporates depth-wise convolution in the feed-forward network to enhance its ability to capture local context. This study is assessed by comparing the results obtained for popular datasets to those obtained by other techniques in the domain.

Keywords: single image super resolution, computer vision, vision transformers, image restoration

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Authors: Medha Talpade, Salil Talpade

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The intent of this quantitative project was to compare the values and perceptions of students from a predominantly white college (PWI) to those from a historically black college (HBCU) about culturally relevant teaching and learning practices in the academic realm. The reason for interrelating student culture with teaching practices is to enable a pedagogical response to the low retention rates of African American students and first generation Caucasian students in high schools, colleges, and their low rates of social mobility and educational achievement. Culturally relevant pedagogy, according to related research, is deemed rewarding to students, teachers, the local and national community. Critical race theory (CRT) is the main framework used in this project to explain the ubiquity of a culturally relevant pedagogy. The purpose of this quantitative study was to test the critical race theory that relates the presence of the factors associated with culturally relevant teaching strategies with perceived relevance. The culturally relevant teaching strategies were identified based on the recommendations and findings of past research. Participants in this study included approximately 145 students from a HBCU and 55 students from the PWI. A survey consisting of 37 items related to culturally relevant pedagogy was administered. The themes used to construct the items were: Use of culturally-specific examples in class whenever possible; use of culturally-specific presentational models, use of relational reinforcers, and active engagement. All the items had a likert-type response scale. Participants reported their degree of agreement (5-point scale ranging from strongly disagree to strongly agree) and importance (3-point scale ranging from not at all important to very important) with each survey item. A new variable, Relevance was formed based on the multiplicative function of importance and presence of a teaching and learning strategy. A set of six demographic questions were included in the survey. A consent form based on NIH and APA ethical standards was distributed prior to survey administration to the volunteers. Results of a Factor Analyses on the data from the PWI and the HBCU, and a ANOVA indicated significant differences on ‘Relevance’ related to specific themes. Results of this study are expected to inform educational practices and improve teaching and learning outcomes.

Keywords: culturally relevant pedagogy, college students, cross-cultural, applied psychology

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Authors: Larry Audet

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Creativity is suddenly and fortunately a new educational focus in the United Arab Emirates and around the world. Yet still today many leaders of creativity are not sure how to introduce it to their teachers. It is impossible to simultaneously introduce every aspect of creativity into a work climate and reach any degree of organizational coherence. The number of alternatives to explore is so great; the information teachers need to learn is so vast, that even an approximation to including every concept and theory of creativity into the school organization is hard to conceive. Effective leaders of creativity need evidence-based and practical guidance for introducing and stimulating creativity in others. Machine learning models reveal new findings from KEYS Survey© data about teacher perceptions of stimulants and barriers to their individual and collective creativity. Findings from predictive and causal models provide leaders with a rational for decision-making when introducing creativity into their organization. Leaders should focus on management practices first. Analyses reveal that creative outcomes are more likely to occur when teachers perceive supportive management practices: providing teachers with challenging work that calls for their best efforts; allowing freedom and autonomy in their practice of work; allowing teachers to form creative work-groups; and, recognizing them for their efforts. Once management practices are in place, leaders should focus their efforts on modeling risk-taking, providing optimal amounts of preparation time, and evaluating teachers fairly.

Keywords: creativity, leadership, KEYS survey, teaching, work climate

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Authors: Jinming Du

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With the COVID-19 pandemic beginning in 2020, many higher education institutions and education systems are turning to hybrid or fully distance online courses to maintain social distance and provide a safe virtual space for learning and teaching. However, the majority of faculty members were not well prepared for the shift to blended or distance learning. Communication frustrations are prevalent in both hybrid and full-distance courses. A systematic literature review was conducted by a comprehensive analysis of 1688 publications that focused on the application of the adoption of chatbots in education. This study aimed to explore instructors' experiences with chatbots in online and blended undergraduate English courses. Language learners are overwhelmed by the variety of information offered by many online sites. The recently emerged chatbots (e.g.: ChatGPT) are slightly superior in performance as compared to those traditional through previous technologies such as tapes, video recorders, and websites. The field of chatbots has been intensively researched, and new methods have been developed to demonstrate how students can best learn and practice a new language in the target language. However, it is believed that among the many areas where chatbots are applied, while chatbots have been used as effective tools for communicating with business customers, in consulting and targeting areas, and in the medical field, chatbots have not yet been fully explored and implemented in the field of language education. This issue is challenging enough for language teachers; they need to study and conduct research carefully to clarify it. Pedagogical chatbots may alleviate the perception of a lack of communication and feedback from instructors by interacting naturally with students through scaffolding the understanding of those learners, much like educators do. However, educators and instructors lack the proficiency to effectively operate this emerging AI chatbot technology and require comprehensive study or structured training to attain competence. There is a gap between language teachers’ perceptions and recent advances in the application of AI chatbots to language learning. The results of the study found that although the teachers felt that the chatbots did the best job of giving feedback, the teachers needed additional training to be able to give better instructions and to help them assist in teaching. Teachers generally perceive the utilization of chatbots to offer substantial assistance to English language instruction.

Keywords: artificial intelligence in education, chatbots, education and technology, education system, pedagogical chatbot, chatbots and language education

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Authors: Ferah Tesfaye Admasu

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Autism Spectrum Disorder (ASD) often presents significant communication challenges, particularly for non-verbal individuals who struggle to express their needs and emotions effectively. Assistive technologies (AT) have emerged as vital tools in enhancing communication abilities for this population. Recent advancements in artificial intelligence (AI) hold the potential to revolutionize the design and functionality of these technologies. This study explores the application of AI in developing intelligent, adaptive, and user-centered assistive technologies for non-verbal individuals with autism. Through a review of current AI-driven tools, including speech-generating devices, predictive text systems, and emotion-recognition software, this research investigates how AI can bridge communication gaps, improve engagement, and support independence. Machine learning algorithms, natural language processing (NLP), and facial recognition technologies are examined as core components in creating more personalized and responsive communication aids. The study also discusses the challenges and ethical considerations involved in deploying AI-based AT, such as data privacy and the risk of over-reliance on technology. Findings suggest that integrating AI into assistive technologies can significantly enhance the quality of life for non-verbal individuals with autism, providing them with greater opportunities for social interaction and participation in daily activities. However, continued research and development are needed to ensure these technologies are accessible, affordable, and culturally sensitive.

Keywords: artificial intelligence, autism spectrum disorder, non-verbal communication, assistive technology, machine learning

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Authors: Arif Ahmed Mohammed Al-Ahdal

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Poetry, tales, and fables have always been a part of the L1 repertoire and one that takes the learners to another amazing and fascinating world of imagination. The storytelling class and the genre of poems are activities greatly enjoyed by all age groups. The very significant idea behind their inclusion in the language curriculum is to sensitize young minds to a wide range of human emotions that are believed to greatly contribute to building their social resilience, emotional stability, empathy towards fellow creatures, and literacy. Quite certainly, the learning objective at this stage is not language acquisition (though it happens as an automatic process) but getting the young learners to be acquainted with an entire spectrum of what may be called the ‘noble’ abilities of the human race. They enrich their very existence, inspiring them to unearth ‘selves’ that help them as adults and enable them to co-exist fruitfully and symbiotically with their fellow human beings. By extension, ‘higher’ training in these literature genres shows the universality of human emotions, sufferings, aspirations, and hopes. The current study is anchored on the Reader-Response-Theory in literature learning, which suggests that the reader reconstructs work and re-enacts the author's creative role. Reiteratingly, literary works provide clues or verbal symbols in a linguistic system, widely accepted by everyone who shares the language, but everyone reads their own life experiences and situations into them. The significance of words depends on the reader, even if they have a typical relationship. In every reading, there is an interaction between the reader and the text. The process of reading is an experience in which the reader tries to comprehend the literary work, which surpasses its full potential since it provides emotional and intellectual reactions that are not anticipated from the document but cannot be affirmed just by the reader as a part of the text. The idea is that the text forms the basis of a unifying experience. A reinterpretation of the literary text may transform it into a guiding principle to respond to actual experiences and personal memories. The impulses delivered to the reader vary according to poetry or texts; nevertheless, the readers differ considerably even with the same material. Previous studies confirm that poetry is a useful tool for learning a language. This present paper works on these hypotheses and proposes to study the impetus given to L2 learning as a factor of exposure to poetry and meaningful stories in L1. The driving force behind the choice of this topic is the first-hand experience that the researcher had while teaching a literary text to a group of BA students who, as a reaction to the text, initially burst into tears and ultimately turned the class into an interactive session. The study also intends to compare the performance of male and female students post intervention using pre and post-tests, apart from undertaking a detailed inquiry via interviews with college learners of English to understand how L1 literature plays a great role in the acquisition of L2.

Keywords: SLA, literary text, poetry, tales, affective factors

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Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Norah Alosayl

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English is considered the most important foreign language in the Kingdom of Saudi Arabia (KSA) because of the usefulness of English as a global language compared to Arabic. As students’ desire to improve their English language skills has grown, English writing has been identified as the most difficult problem for Saudi students in their language learning. Although the English language in Saudi Arabia is taught beginning in the seventh grade, many students have problems at the university level, especially in writing, due to a gap between what is taught in secondary and high schools and university expectations- pupils generally study English at school, based on one book with few exercises in vocabulary and grammar exercises, and there are no specific writing lessons. Moreover, from personal teaching experience at King Saud bin Abdulaziz University, students face real problems with their writing. This paper revolves around the blackboard-based collaborative writing to help the undergraduate Saudi EFL students, in their first year enrolled in two sections of ENGL 101 in the first semester of 2021 at King Saud bin Abdulaziz University, practice the most difficult skill they found in their writing through a small group. Therefore, a sequential mixed methods design will be suited. The first phase of the study aims to highlight the most difficult skill experienced by students from an official writing exam that is evaluated by their teachers through an official rubric used in King Saud bin Abdulaziz University. In the second phase, this study will intend to investigate the benefits of social interaction on the process of learning writing. Students will be provided with five collaborative writing tasks via discussion feature on Blackboard to practice a skill that they found difficult in writing. the tasks will be formed based on social constructivist theory and pedagogic frameworks. The interaction will take place between peers and their teachers. The frequencies of students’ participation and the quality of their interaction will be observed through manual counting, screenshotting. This will help the researcher understand how students actively work on the task through the amount of their participation and will also distinguish the type of interaction (on task, about task, or off-task). Semi-structured interviews will be conducted with students to understand their perceptions about the blackboard-based collaborative writing tasks, and questionnaires will be distributed to identify students’ attitudes with the tasks.

Keywords: writing difficulties, blackboard-based collaborative writing, process of learning writing, interaction, participations

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Authors: Shohreh Ghasemi

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Introduction: Melanoma is a complex disease with various clinical and histopathological features that impact prognosis and treatment decisions. Traditional methods of melanoma prognosis involve manual examination and interpretation of clinical and histopathological data by dermatologists and pathologists. However, the subjective nature of these assessments can lead to inter-observer variability and suboptimal prognostic accuracy. AI, with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool for improving melanoma prognosis. Methods: A comprehensive literature search was conducted to identify studies that employed AI techniques for melanoma prognosis. The search included databases such as PubMed and Google Scholar, using keywords such as "artificial intelligence," "melanoma," and "prognosis." Studies published between 2010 and 2022 were considered. The selected articles were critically reviewed, and relevant information was extracted. Results: The review identified various AI methodologies utilized in melanoma prognosis, including machine learning algorithms, deep learning techniques, and computer vision. These techniques have been applied to diverse data sources, such as clinical images, dermoscopy images, histopathological slides, and genetic data. Studies have demonstrated the potential of AI in accurately predicting melanoma prognosis, including survival outcomes, recurrence risk, and response to therapy. AI-based prognostic models have shown comparable or even superior performance compared to traditional methods.

Keywords: artificial intelligence, melanoma, accuracy, prognosis prediction, image analysis, personalized medicine

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Authors: Kumar Shashvat, Amol P. Bhondekar

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

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

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: Ainur Bulasheva

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During the last decade, the dual learning system (DLS) has been actively introduced in various industries in Kazakhstan, including both vocational, post-secondary, and higher education levels. It is a relatively new practice-oriented approach to training qualified personnel in Kazakhstan, officially introduced in 2012. Dual learning was integrated from the German vocational education and training system, combining practical training with part-time work in production and training in an educational institution. The policy of DLS has increasingly focused on decreasing youth unemployment and the shortage of mid-level professionals by providing incentives for employers to involve in this system. By participating directly in the educational process, the enterprise strives to train its future personnel to meet fast-changing market demands. This study examines the effectiveness of DLS from the perspective of employers to understand the motivations of businesses to participate (invest) in this program. The human capital theory of Backer, which predicts that employers will invest in training their workers (in our case, dual students) when they expect that the return on investment will be greater than the cost - acts as a starting point. Further extensionists of this theory will be considered to understand investing intentions of businesses. By comparing perceptions of DLS employers and non-dual practices, this study determines the efficiency of promoted training approach for enterprises in the Kazakhstan agri-food industry.

Keywords: vocational and technical education, dualeducation, human capital theory, argi-food industry

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