Search results for: differential learning

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: Hudson Akewe

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This research presents complementary results with wider applications on convergence and rate of convergence of classical fixed point theory in Banach spaces to the world of the theory of fixed points of mappings defined in classes of spaces of measurable functions, known in the literature as modular function spaces. The study gives a comprehensive survey of various iterative fixed point results for the classes of multivalued ρ-contractive-like, ρ-quasi-contractive-like, ρ-quasi-contractive, ρ-Zamfirescu and ρ-contraction mappings in the framework of modular function spaces. An example is presented to demonstrate the applicability of the implicit-type iterative schemes to the system of ordinary differential equations. Furthermore, numerical examples are given to show the rate of convergence of the various explicit Kirk-type and implicit Kirk-type iterative schemes under consideration. Our results complement the results obtained on normed and metric spaces in the literature. Also, our methods of proof serve as a guide to obtain several similar improved results for nonexpansive, pseudo-contractive, and accretive type mappings.

Keywords: implicit Kirk-type iterative schemes, multivalued mappings, convergence results, fixed point

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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: Felix Givois, Nicolas R. Gauger, Matthias Kabel

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The efficient digital material characterization is of great interest to many fields of application. It consists of the following three steps. First, a 3D reconstruction of 2D scans must be performed. Then, the resulting gray-value image of the material sample is enhanced by image processing methods. Finally, partial differential equations (PDE) are solved on the segmented image, and by averaging the resulting solutions fields, effective properties like stiffness or conductivity can be computed. Due to the high resolution of current CT images, the latter is typically performed with matrix-free solvers. Among them, a solver that uses the explicit formula of the Green-Eshelby operator in Fourier space has been proposed by Moulinec and Suquet. Its algorithmic, most complex part is the Fast Fourier Transformation (FFT). In our talk, we will discuss the potential quantum advantage that can be obtained by replacing the FFT with the Quantum Fourier Transformation (QFT). We will especially show that the data transfer for noisy intermediate-scale quantum (NISQ) devices can be improved by using appropriate boundary conditions for the PDE, which also allows using semi-classical versions of the QFT. In the end, we will compare the results of the QFT-based algorithm for simple geometries with the results of the FFT-based homogenization method.

Keywords: most likelihood amplitude estimation (MLQAE), numerical homogenization, quantum Fourier transformation (QFT), NISQ devises

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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: Rajeswari Raguraman, Sowmya Parameswaran, Krishnakumar Subramanian, Jagat Kanwar, Rupinder Kanwar

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Background: Tumor microenvironment has been implicated in several cancers to regulate cell growth, invasion and metastasis culminating in outcome of therapy. Tumor stroma consists of multiple cell types that are in constant cross-talk with the tumor cells to favour a pro-tumorigenic environment. Not much is known about the existence of tumor microenvironment in the pediatric intraocular malignancy, Retinoblastoma (RB). In the present study, we aim to understand the multiple stromal cellular subtypes and tumor stromal interactions expressed in RB tumors. Materials and Methods: Immunohistochemistry for stromal cell markers CD31, CD68, alpha-smooth muscle (α-SMA), vimentin and glial fibrillary acidic protein (GFAP) was performed on formalin fixed paraffin embedded tissues sections of RB (n=12). The differential expression of stromal target molecules; fibroblast activation protein (FAP), tenascin-C (TNC), osteopontin (SPP1), bone marrow stromal antigen 2 (BST2), stromal derived factor 2 and 4 (SDF2 and SDF4) in primary RB tumors (n=20) and normal retina (n=5) was studied by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) and Western blotting. The differential expression was correlated with the histopathological features of RB. The interaction between RB cell lines (Weri-Rb-1, NCC-RbC-51) and Bone marrow stromal cells (BMSC) was also studied using direct co-culture and indirect co-culture methods. The functional effect of the co-culture methods on the RB cells was evaluated by invasion and proliferation assays. Global gene expression was studied by using Affymetrix 3’ IVT microarray. Pathway prediction was performed using KEGG and the key molecules were validated using qRT-PCR. Results: The immunohistochemistry revealed the presence of several stromal cell types such as endothelial cells (CD31+;Vim+/-); macrophages (CD68+;Vim+/-); Fibroblasts (Vim+; CD31-;CD68- );myofibroblasts (α-SMA+/ Vim+) and invading retinal astrocytes/ differentiated retinal glia (GFAP+; Vim+). A characteristic distribution of these stromal cell types was observed in the tumor microenvironment, with endothelial cells predominantly seen in blood vessels and macrophages near actively proliferating tumor or necrotic areas. Retinal astrocytes and glia were predominant near the optic nerve regions in invasive tumors with sparse distribution in tumor foci. Fibroblasts were widely distributed with rare evidence of myofibroblasts in the tumor. Both gene and protein expression revealed statistically significant (P<0.05) up-regulation of FAP, TNC and BST2 in primary RB tumors compared to the normal retina. Co-culture of BMSC with RB cells promoted invasion and proliferation of RB cells in direct and indirect contact methods respectively. Direct co-culture of RB cell lines with BMSC resulted in gene expression changes in ECM-receptor interaction, focal adhesion, IL-8 and TGF-β signaling pathways associated with cancer. In contrast, various metabolic pathways such a glucose, fructose and amino acid metabolism were significantly altered under the indirect co-culture condition. Conclusion: The study suggests that the close interaction between RB cells and the stroma might be involved in RB tumor invasion and progression which is likely to be mediated by ECM-receptor interactions and secretory factors. Targeting the tumor stroma would be an attractive option for redesigning treatment strategies for RB.

Keywords: gene expression profiles, retinoblastoma, stromal cells, tumor microenvironment

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Authors: A. Alvaredo , R. Guzman De Villoria, P. Castell, Juan P. Fernandez-Blazquez

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Since graphene was discovered in 2004, has been considered as superb material, due to its outstanding mechanical, electrical and thermal properties. Graphene has been incorporated as reinforcement in several high performance polymers in order to obtain a good balance of properties and to get new properties as thermal or electric conductivity. As well known, the properties of semicrystalline polymer and its composites depends heavily on degree of crystallinity. In this context, our research group has studied the crystallization behavior from amorphous state of PEEK/GNP composites. The monitoring of cold crystallization processes studied by time-resolved simultaneous wide-angle X-ray scattering (WAXS) and small-angle X-ray scattering (SAXS). These techniques allowed to get an extremely relevant information about the evolution of the morphology of the PEEK/GNP composites. In addition, the thermal evolution of cold crystallization was followed by differential scanning calorimetry (DSC) as well. The experimental results showed changes in crystallization kinetics and c parameter unit cell when adding graphene. The main aim of this work is to produce PEEK/GNP composites and characterize their morphology, unit cell parameters and crystallization kinetic.

Keywords: PEEK, graphene, synchrotron, cold crystallization

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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: 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: Awni Alkhazaleh

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Latent heat storage using Phase Change Materials (PCMs) has attracted growing attention recently in the renewable energy utilization and building energy efficiency. Paraffin (PA) of low melting temperature, which is close to human comfort temperature in the range of 24-28 °C has been considered to be used in building applications. A form-stable composite Paraffin/Expanded perlite (PA-EP) has been prepared by retaining PA into porous particles of EP. DSC (Differential scanning calorimeter) is used to measure the thermal properties of PA in the form-stable composite with/without building materials. TGA (Thermal gravimetric analysis) shows that the composite is thermally stable. SEM (Scanning electron microscope) demonstrates that the layer structure of the EP particles is uniformly absorbed by PA. The mechanical properties in flexural mode have been discussed. The thermal energy storage performance has been evaluated using a small test room (100 mm ×100 mm ×100 mm) with thickness 10 mm. The flammability test of modified sample has been discussed using a cone calorimeter. The results confirm that the form-stable composite PA has the function of reducing building energy consumption.

Keywords: flammability, latent heat storage, paraffin, plasterboard

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Authors: Guillaume Morin-Duponchelle, Ahmed Nait Chabane, Benoit Zerr, Pierre Schoesetters

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Industrial inspection can be achieved through robotic systems, allowing visual and chemical servoing. A popular scheme for visual servo-controlled robotic is the image-based servoing sys-tems. In this paper, an approach of visual and chemical servoing of a hexapod robot using a visual and chemical Jacobian matrix are proposed. The basic idea behind the visual Jacobian matrix is modeling the differential relationship between the camera system and the robotic control system to detect and track accurately points of interest in confined environments. This approach allows the robot to easily detect and navigates to the QR code or seeks a gas source localization using surge cast algorithm. To track the QR code target, a visual servoing based on Jacobian matrix is used. For chemical servoing, three gas sensors are embedded on the hexapod. A Jacobian matrix applied to the gas concentration measurements allows estimating the direction of the main gas source. The effectiveness of the proposed scheme is first demonstrated on simulation. Finally, a hexapod prototype is designed and built and the experimental validation of the approach is presented and discussed.

Keywords: chemical servoing, hexapod robot, Jacobian matrix, visual servoing, navigation

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Authors: Nor Khaizan Anuar, Nur Karimah Aziz, Tin Wui Wong, Ahmad Sazali Hamzah, Wan Rozita Wan Engah

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The physicochemical attributes and wound healing activity of pectin hydrogel in rat models, following partial thickness thermal injury were investigated. The pectin hydrogel was prepared by solvent evaporation method with the aid of glutaraldehyde as crosslinking agent and glycerol as plasticizer. The physicochemical properties were mainly evaluated using differential scanning calorimetry (DSC) and Fourier transform infrared (FTIR) spectroscopy, while the wound healing activity was examined by the macroscopic images, wound size reduction and histological evaluation using haematoxylin and eosin (H&E) stain for 14 days. The DSC and FTIR analysis suggested that pectin hydrogel exhibited higher extent of polymer-polymer interaction at O-H functional group in comparison to the unprocessed pectin. This was indicated by the increase of endothermic enthalpy values from 139.35 ± 13.06 J/g of unprocessed pectin to 156.23 ± 2.86 J/g of pectin hydrogel, as well as the decrease of FTIR wavenumber corresponding to O-H at 3432.07 ± 0.49 cm-1 of unprocessed pectin to 3412.62 ± 13.06 cm-1 of pectin hydrogel. Rats treated with pectin hydrogel had significantly smaller wound size (Student’s t-test, p<0.05) when compared to the untreated group starting from day 7 until day 14. H&E staining indicated that wounds received pectin hydrogel had more fibroblasts, blood vessels and collagen bundles on day 14 in comparison to the untreated rats.

Keywords: pectin, physicochemical, rats, wound

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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: Yuanhao Gao, Pin Lin, Kees Weijer

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In this paper, we will determine the external body force distribution with analysis of stokes fluid motion using mathematical modelling and numerical approaching. The body force distribution is regarded as the unknown variable and could be determined by the idea of optimal control theory. The Stokes flow motion and its velocity are generated by given forces in a unit square domain. A regularized objective functional is built to match the numerical result of flow velocity with the generated velocity data. So that the force distribution could be determined by minimizing the value of objective functional, which is also the difference between the numerical and experimental velocity. Then after utilizing the Lagrange multiplier method, some partial differential equations are formulated consisting the optimal control system to solve. Finite element method and conjugate gradient method are used to discretize equations and deduce the iterative expression of target body force to compute the velocity numerically and body force distribution. Programming environment FreeFEM++ supports the implementation of this model.

Keywords: optimal control model, Stokes equation, finite element method, conjugate gradient method

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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: Agnes Simone

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A 52-year-old male with unknown psychiatric and medical history was brought to the Psychiatric Emergency Room by ambulance directly from jail. He had been detained for three weeks for possession of a firearm while intoxicated. On initial evaluation, the patient was unable to provide a reliable history. He presented with odd jerking movements of his extremities and catatonic features, including mutism and stupor. His vital signs were stable. Patient was transferred to the medical emergency department for work-up of altered mental status. Due to suspicion for opioid overdose, the patient was given naloxone (Narcan) with no improvement. Laboratory work-up included complete blood count, comprehensive metabolic panel, thyroid stimulating hormone, vitamin B12, folate, magnesium, rapid plasma reagin, HIV, blood alcohol level, aspirin, and Tylenol blood levels, urine drug screen, and urinalysis, which were all negative. CT head and chest X-Ray were also negative. With this negative work-up, the medical team concluded there was no organic etiology and requested inpatient psychiatric admission. Upon re-evaluation by psychiatry, it was evident that the patient continued to have an altered mental status. Of note, the medical team did not include substance withdrawal in the differential diagnosis due to stable vital signs and a negative urine drug screen. The psychiatry team decided to check California's prescription drug monitoring program (CURES) and discovered that the patient was prescribed benzodiazepine alprazolam (Xanax) 2mg BID, a sedative-hypnotic, and hydrocodone/acetaminophen 10mg/325mg (Norco) QID, an opioid. After a thorough chart review, his daughter's contact information was found, and she confirmed his benzodiazepine and opioid use, with recent escalation and misuse. It was determined that the patient was experiencing alprazolam withdrawal, given this collateral information, his current symptoms, negative urine drug screen, and recent abrupt discontinuation of medications while incarcerated. After admission to the medical unit and two doses of alprazolam 2mg, the patient's mental status, alertness, and orientation improved, but he had no memory of the events that led to his hospitalization. He was discharged with a limited supply of alprazolam and a close follow-up to arrange a taper. Accompanying this case report, a qualitative review of presentations with alprazolam withdrawal was completed. This case and the review highlights: (1) Alprazolam withdrawal can occur at low doses and within just one week of use. (2) Alprazolam withdrawal can present without any vital sign instability. (3) Alprazolam withdrawal does not respond to short-acting benzodiazepines but does respond to certain long-acting benzodiazepines due to its unique chemical structure. (4) Alprazolam withdrawal is distinct from and more severe than other benzodiazepine withdrawals. This case highlights (1) the importance of physician utilization of drug-monitoring programs. This case, in particular, relied on California's drug monitoring program. (2) The importance of obtaining collateral information, especially in cases in which the patient is unable to provide a reliable history. (3) The importance of including substance intoxication and withdrawal in the differential diagnosis even when there is a negative urine drug screen. Toxidrome of withdrawal can be delayed. (4) The importance of discussing addiction and withdrawal risks of medications with patients.

Keywords: addiction risk of benzodiazepines, alprazolam withdrawal, altered mental status, benzodiazepines, drug monitoring programs, sedative-hypnotics, substance use disorder

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Authors: Zubier Arfan, Paul Johnson

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The electronification of financial markets and the rise of algorithmic trading has sparked a lot of interest from the mathematical community, for the market making-problem in particular. The research presented in this short paper solves the classic stochastic control problem in order to derive the strategy for a market-maker. It also shows how to calibrate and simulate the strategy with real limit order book data for back-testing. The ambiguity of limit-order priority in back-testing is dealt with by considering optimistic and pessimistic priority scenarios. The model, although it does outperform a naive strategy, assumes constant volatility, therefore, is not best suited to the LOB data. The Heston model is introduced to describe the price and variance process of the asset. The Trader's constant absolute risk aversion utility function is optimised by numerically solving a 3-dimensional Hamilton-Jacobi-Bellman partial differential equation to find the optimal limit order quotes. The results show that the stochastic volatility market-making model is more suitable for a risk-averse trader and is also less sensitive to calibration error than the constant volatility model.

Keywords: market-making, market-microsctrucure, stochastic volatility, quantitative trading

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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: Bandari Shankar, Yohannes Yirga

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In this paper, the problem of heat and mass transfer in unsteady MHD boundary-layer flow of nanofluids over stretching sheet with a non uniform heat source/sink is considered. The unsteadiness in the flow and temperature is caused by the time-dependent stretching velocity and surface temperature. The unsteady boundary layer equations are transformed to a system of non-linear ordinary differential equations and solved numerically using Keller box method. The velocity, temperature, and concentration profiles were obtained and utilized to compute the skin-friction coefficient, local Nusselt number, and local Sherwood number for different values of the governing parameters viz. solid volume fraction parameter, unsteadiness parameter, magnetic field parameter, Schmidt number, space-dependent and temperature-dependent parameters for heat source/sink. A comparison of the numerical results of the present study with previously published data revealed an excellent agreement

Keywords: unsteady, heat and mass transfer, manetohydrodynamics, nanofluid, non-uniform heat source/sink, stretching sheet

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Authors: Maryam Khazaei Pool, Lori Lewis

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This is a summary of articles based on higher order B-splines methods and the variation of B-spline methods such as Quadratic B-spline Finite Elements Method, Exponential Cubic B-Spline Method, Septic B-spline Technique, Quintic B-spline Galerkin Method, and B-spline Galerkin Method based on the Quadratic B-spline Galerkin method (QBGM) and Cubic B-spline Galerkin method (CBGM). In this paper, we study the B-spline methods and variations of B-spline techniques to find a numerical solution to the Burgers’ equation. A set of fundamental definitions, including Burgers equation, spline functions, and B-spline functions, are provided. For each method, the main technique is discussed as well as the discretization and stability analysis. A summary of the numerical results is provided, and the efficiency of each method presented is discussed. A general conclusion is provided where we look at a comparison between the computational results of all the presented schemes. We describe the effectiveness and advantages of these methods.

Keywords: Burgers’ equation, Septic B-spline, modified cubic B-spline differential quadrature method, exponential cubic B-spline technique, B-spline Galerkin method, quintic B-spline Galerkin method

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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

Procedia PDF Downloads 110