Search results for: machine learning in finance

Authors: Gary Pattemore, Michael Edgar, Andrew Job, Marina Auad, Kathryn Job

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As critical commodities become more scarce, significant time and resources have been used to better understand complicated ore bodies and extract their full potential. These challenging ore bodies provide several pain points for geologists and engineers to overcome, poor handling of these issues flows downs stream to the processing plant affecting throughput rates and recovery. Many open cut mines utilise blast hole drilling to extract additional information to feed back into the modelling process. This method requires samples to be collected during or after blast hole drilling. Samples are then sent for assay with turnaround times varying from 1 to 12 days. This method is time consuming, costly, requires human exposure on the bench and collects elemental data only. To address this challenge, research has been undertaken to utilise hyperspectral imaging across a broad spectrum to scan samples, collars or take down hole measurements for minerals and moisture content and grade abundances. Automation of this process using unmanned vehicles and on-board processing reduces human in pit exposure to ensure ongoing safety. On-board processing allows data to be integrated into modelling workflows with immediacy. The preliminary results demonstrate numerous direct and indirect benefits from this new technology, including rapid and accurate grade estimates, moisture content and mineralogy. These benefits allow for faster geo modelling updates, better informed mine scheduling and improved downstream blending and processing practices. The paper presents recommendations for implementation of the technology in open cut mining environments.

Keywords: grade control, hyperspectral scanning, artificial intelligence, autonomous mining, machine learning

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Authors: Aboagye Boye Gilbert

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Teaching and learning (Education), not only in Ghana but the whole world is regarded as the (Stepping stone) vehicle to accelerate the country’s economy, development and social growth. Basically the ingredients for human development and the country in general is Vocational and Technical education and this has been stressed in Ghana’s education system since Pre-independence. To this effect, this research seeks to determine using demonstration method of Teachings sewing to improve the skills of form 3 Fashion Designing students of Baworo Integrated Community Centre for Employable Skills. In this research, reviewed literature on opinions of other researchers and what other people have done and said on related articles or topics, analyzed the research design used, translate the data gathered in the study. The study was design to gather information from the school on how they use Teaching methods to teach sewing. The targeted respondent contacted to give assistance Consist of students from BICCES, fashion teachers and tailored garment makers. The sample size consisted of 5 teachers, 20 students and 5 tailors were selected to answer questionnaire items that were used to gather the data for the study. The study revealed that most teachers and students agreed to the fact that demonstration, teaching and learning materials had a positive attitude towards the students in learning sewing. The study recommends that there should be more mechanisms in place to serve as a guide.

Keywords: VOTEC, BECE, BICCES, SHS

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Authors: Hammad Riaz, Abubakr Saeed

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Environmental Management System (EMS), i.e., ISO 14001 helps to build corporate reputation, legitimacy and can also be considered as firms’ strategic response to institutional pressure to reduce the impact of business activity on natural environment. The financial outcomes of certifying with ISO 14001 are still unclear and equivocal. Drawing on institutional and market learning theories, the impact of ISO 14001 on firms’ market performance is examined for Chinese firms. By employing rigorous event study approach, this paper compared ISO 14001 certified firms with non-certified counterpart firms based on different matching criteria that include size, return on assets and industry. The results indicate that the ISO 14001 has been negatively signed by the investors both in the short and long-run. This paper suggested implications for policy makers, managers, and other nonprofit organizations.

Keywords: ISO 14001, legitimacy, institutional forces, event study approach, emerging markets

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Authors: Redouane Larbi Boufeniza, Jing-Jia Luo

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This study assesses the suitability of deep learning (DL) for downscaling sea surface temperature (SST) over the Mediterranean Sea in the context of seasonal forecasting. We design a set of experiments that compare different DL configurations and deploy the best-performing architecture to downscale one-month lead forecasts of June–September (JJAS) SST from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for the period of 1982–2020. We have also introduced predictors over a larger area to include information about the main large-scale circulations that drive SST over the Mediterranean Sea region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results showed that the convolutional neural network (CNN)-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme SST spatial patterns. Besides, the CNN-based downscaling yields a much more accurate forecast of extreme SST and spell indicators and reduces the significant relevant biases exhibited by the raw model predictions. Moreover, our results show that the CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of the Mediterranean Sea. The results demonstrate the potential usefulness of CNN in downscaling seasonal SST predictions over the Mediterranean Sea, particularly in providing improved forecast products.

Keywords: Mediterranean Sea, sea surface temperature, seasonal forecasting, downscaling, deep learning

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Authors: Anne Tan, Kok-Sing Tang, Audrey Cooke

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Play has always been a prominent pedagogy in early childhood. However, there is growing evidence of success in students’ learning using explicit instruction, especially in literacy in the early years. There is also limited research using explicit instruction in early childhood mathematics, and play is usually prominently mentioned. This proposed research aims to investigate the possibilities and benefits of integrating guided play with explicit instruction in early childhood mathematics education. While play has traditionally been a prominent pedagogy in early childhood, there is growing evidence of success in student learning through explicit instruction, particularly in literacy. However, limited research exists on the integration of explicit instruction in early childhood mathematics, where play remains prominently mentioned. This study utilises a multiple case study methodology to gather data and provide immediate opportunities for curriculum improvement. The research will commence with semi-structured interviews to gain insights into educators' background knowledge. Highly structured observations will be conducted to record the frequency and manner in which guided play is integrated with specific elements of explicit instruction during mathematics teaching in early childhood. To enhance the observations, video recordings will be made using cameras with video settings and Microsoft Teams meeting recordings. In addition to interviews and observations, educators will maintain journals and use the Microsoft Teams platform for self-reflection on the integration of guided play and explicit instruction in their classroom practices and experiences. The study participants will include educators with early childhood degrees and students in years one and two. The primary goal of this research is to inform the benefits of integrating two high-impact pedagogies, guided play, and explicit instruction, for enhancing student learning outcomes in mathematics education. By exploring the integration of these pedagogical approaches, this study aims to contribute to the development of effective instructional strategies in early childhood mathematics education.

Keywords: early childhood, early childhood mathematics, early childhood numbers, guided play, play-based learning, explicit instruction

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Authors: Rachelly Ashwall, Ephraim Tabory

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In an attempt to reduce the level of a major identity-based conflict in Israel between Ultra-orthodox and secular Jews, several initiatives in recent years have tried to bring members of the two societies together in facilitated joint discussion forums. Our study analyzes the impact of two types of such programs: joint mediation training classes and confrontation-based learning programs that are designed to facilitate discussions over controversial issues. These issues include claims about an unequal shouldering of national obligations such as military service, laws requiring public observance of the Sabbath, and discrimination against women, among others. The study examines the factors that enabled the two groups to reduce their social distance, and increase their understanding of each other, and develop a recognition and tolerance of the other group's particular social identity. The research conducted over a course of two years involved observations of the activities of the groups, interviews with the participants, and analysis of the social media used by the groups. The findings demonstrate the progression from a mutual initial lack of knowledge about habits, norms, and attitudes of the out-group to an increasing desire to know, understand and more readily accept the identity of a previously rejected outsider. Participants manifested more respect, concern for and even affection for those whose identity initially led them to reject them out of hand. We discuss the implications for seemingly intractable identity-based conflict in fragile societies.

Keywords: identity-based conflict, intergroup relations, joint mediation learning, out-group recognition, social identity

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Authors: J. S. Dhillon, K. K. Dhaliwal

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In almost all the digital filtering applications the digital infinite impulse response (IIR) filters are preferred over finite impulse response (FIR) filters because they provide much better performance, less computational cost and have smaller memory requirements for similar magnitude specifications. However, the digital IIR filters are generally multimodal with respect to the filter coefficients and therefore, reliable methods that can provide global optimal solutions are required. The artificial bee colony (ABC) algorithm is one such recently introduced meta-heuristic optimization algorithm. But in some cases it shows insufficiency while searching the solution space resulting in a weak exchange of information and hence is not able to return better solutions. To overcome this deficiency, the opposition based learning strategy is incorporated in ABC and hence a modified version called oppositional artificial bee colony (OABC) algorithm is proposed in this paper. Duplication of members is avoided during the run which also augments the exploration ability. The developed algorithm is then applied for the design of optimal and stable digital IIR filter structure where design of low-pass (LP) and high-pass (HP) filters is carried out. Fuzzy theory is applied to achieve maximize satisfaction of minimum magnitude error and stability constraints. To check the effectiveness of OABC, the results are compared with some well established filter design techniques and it is observed that in most cases OABC returns better or atleast comparable results.

Keywords: digital infinite impulse response filter, artificial bee colony optimization, opposition based learning, digital filter design, multi-parameter optimization

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Authors: L. Freeborn

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Recent years have seen an increasing number of neuroimaging studies related to language learning as imaging techniques such as fMRI and EEG have become more widely accessible to researchers. By using a variety of structural and functional neuroimaging techniques, these studies have already made considerable progress in terms of our understanding of neural networks and processing related to first and second language acquisition. However, the methodological designs employed in neuroimaging studies to test language learning have been questioned by applied linguists working within the field of second language acquisition (SLA). One of the major criticisms is that tasks designed to measure language learning gains rarely have a communicative function, and seldom assess learners’ ability to use the language in authentic situations. This brings the validity of many neuroimaging tasks into question. The fundamental reason why people learn a language is to communicate, and it is well-known that both first and second language proficiency are developed through meaningful social interaction. With this in mind, the SLA field is in agreement that second language acquisition and proficiency should be measured through learners’ ability to communicate in authentic real-life situations. Whilst authenticity is not always possible to achieve in a classroom environment, the importance of task authenticity should be reflected in the design of language assessments, teaching materials, and curricula. Tasks that bear little relation to how language is used in real-life situations can be considered to lack construct validity. This paper first describes the typical tasks used in neuroimaging studies to measure language gains and proficiency, then analyses to what extent these tasks can validly assess these constructs.

Keywords: neuroimaging studies, research design, second language acquisition, task validity

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Authors: Ahlam A. Alghamdi

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For many years and until now, education based on gendered division is endorsed in the public Saudi schools starting from the primary grades (1,2, 3rd grades). Although preschool has no boys and girls segregation restrictions, children from first grade starting their first form of cultural ideology based on gender. Ensuring high-quality education serving all children -both boys and girls- is an aim for policymakers and early learning professionals in Saudi Arabia. The past five years have witnessed a major change in terms of shifting the paradigm to educating young children in the country. In May 2018, the Ministry of Education (MoE) had declared a commencement decision of inclusion schools serve both girls and boys in primary grades with a high-quality early learning opportunity. This study sought to shed light on one of the earliest schools that have implemented the inclusion experience. The methodological approach adopted is based on the qualitative inquiry of case study to investigate complex phenomena within the contexts of inclusion school. Data collection procedures included on-site visitations and semi-structured interviews with the teachers to document their thoughts, narratives, and living experiences. The findings of this study identified three themes based on cultural, educational, and professional interpretations. An overview of recommendations highlighted the benefits and possible challenges of future implementations of inclusion schools in Saudi Arabia.

Keywords: early learning, gender division, inclusion school, Saudi Arabia

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Authors: Angela Yicely Castro Garces

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Aware of the relevance that intercultural education has gained in foreign language learning and teaching, and acknowledging the need to make it part of our classroom practices, this literature review explores studies that have been published in the Colombian context from the years 2012 to 2019. The inquiry was done in six national peer-reviewed journals, in order to examine the population benefited, types of studies and most recurrent topics of concern for educators. The findings present a promising panorama as teacher educators from public universities are leading the way in conducting research projects aimed at fostering intercultural awareness and building a critical intercultural discourse. Nonetheless, more studies that involve the different stakeholders and contexts need to be developed, in order to make intercultural education more visible in Colombian elementary and high school classrooms.

Keywords: Colombian scholarship, foreign language learning, foreign language teaching, intercultural awareness

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Authors: Pankaj Dhiman, Simranjeet Kaur

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This research paper presents a comprehensive sentiment analysis of social media responses to videos on Facebook, YouTube, Twitter, and Instagram during the 2024 Indian general elections. The study focuses on the sentiment patterns of voters towards the National Democratic Alliance (NDA) and The Indian National Developmental Inclusive Alliance (INDIA) on these platforms. The analysis aims to understand the impact of social media on voter sentiment and its correlation with the election outcome. The study employed a mixed-methods approach, combining both quantitative and qualitative methods. With a total of 200 posts analysed during general election-2024 final phase, the sentiment analysis was conducted using natural language processing (NLP) techniques, including sentiment dictionaries and machine learning algorithms. The results show that NDA received significantly more positive sentiment responses across all platforms, with a positive sentiment score of 47% compared to INDIA's score of 38.98 %. The analysis also revealed that Twitter and YouTube were the most influential platforms in shaping voter sentiment, with 60% of the total sentiment score coming from these two platforms. The study's findings suggest that social media sentiment analysis can be a valuable tool for understanding voter sentiment and predicting election outcomes. The results also highlight the importance of social media in shaping public opinion and the need for political parties to engage effectively with voters on these platforms. The study's implications are significant, as they indicate that social media can be a key factor in determining the outcome of elections. The findings also underscore the need for political parties to develop effective social media strategies to engage with voters and shape public opinion.

Keywords: Indian Elections-2024, NDA, INDIA, sentiment analysis, social media, democracy

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Authors: Sumeyra Karatas, Veysel Karatas, Reyhan Safak, Gamze Bulut-Ozturk, Ozgul Kartal

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Productive struggle entails a student's cognitive exertion to comprehend mathematical concepts and uncover solutions not immediately apparent. The significance of productive struggle in learning mathematics is accentuated by influential educational theorists, emphasizing its necessity for learning mathematics with understanding. Consequently, supporting productive struggle in learning mathematics is recognized as a high-leverage and effective mathematics teaching practice. In this study, the investigation into the role of productive struggle in learning mathematics led to the development of a comprehensive rubric for productive struggle pedagogy through an exhaustive literature review. The rubric consists of eight primary criteria and 37 sub-criteria, providing a detailed description of teacher actions and pedagogical choices that foster students' productive struggles. These criteria encompass various pedagogical aspects, including task design, tool implementation, allowing time for struggle, posing questions, scaffolding, handling mistakes, acknowledging efforts, and facilitating discussion/feedback. Utilizing this rubric, a team of researchers and teachers designed eight 90-minute lesson plans, employing a productive struggle pedagogy, for a two-week unit on solving systems of linear equations. Simultaneously, another set of eight lesson plans on the same topic, featuring identical content and problems but employing a traditional lecture-and-practice model, was designed by the same team. The objective was to assess the impact of supporting productive struggle on students' mathematics learning, defined by the strands of mathematical proficiency. This quasi-experimental study compares the control group, which received traditional lecture- and practice instruction, with the treatment group, which experienced a productive struggle in pedagogy. Sixty-six 10th and 11th-grade students from two algebra classes, taught by the same teacher at a high school, underwent either the productive struggle pedagogy or lecture-and-practice approach over two-week eight 90-minute class sessions. To measure students' learning, an assessment was created and validated by a team of researchers and teachers. It comprised seven open-response problems assessing the strands of mathematical proficiency: procedural and conceptual understanding, strategic competence, and adaptive reasoning on the topic. The test was administered at the beginning and end of the two weeks as pre-and post-test. Students' solutions underwent scoring using an established rubric, subjected to expert validation and an inter-rater reliability process involving multiple criteria for each problem based on their steps and procedures. An analysis of covariance (ANCOVA) was conducted to examine the differences between the control group, which received traditional pedagogy, and the treatment group, exposed to the productive struggle pedagogy, on the post-test scores while controlling for the pre-test. The results indicated a significant effect of treatment on post-test scores for procedural understanding (F(2, 63) = 10.47, p < .001), strategic competence (F(2, 63) = 9.92, p < .001), adaptive reasoning (F(2, 63) = 10.69, p < .001), and conceptual understanding (F(2, 63) = 10.06, p < .001), controlling for pre-test scores. This demonstrates the positive impact of supporting productive struggle in learning mathematics. In conclusion, the results revealed the significance of the role of productive struggle in learning mathematics. The study further explored the practical application of productive struggle through the development of a comprehensive rubric describing the pedagogy of supporting productive struggle.

Keywords: effective mathematics teaching practice, high school algebra, learning mathematics, productive struggle

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Authors: Dayo Samuel Banjo, Connice Trimmingham, Niloofar Yousefi, Nitin Agarwal

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Technological advancement and its omnipresent connection have pushed humans past the boundaries and limitations of a computer screen, physical state, or geographical location. It has provided a depth of avenues that facilitate human-computer interaction that was once inconceivable such as audio and body language detection. Given the complex modularities of emotions, it becomes vital to study human-computer interaction, as it is the commencement of a thorough understanding of the emotional state of users and, in the context of social networks, the producers of multimodal information. This study first acknowledges the accuracy of classification found within multimodal emotion detection systems compared to unimodal solutions. Second, it explores the characterization of multimedia content produced based on their emotions and the coherence of emotion in different modalities by utilizing deep learning models to classify emotion across different modalities.

Keywords: affective computing, deep learning, emotion recognition, multimodal

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Authors: Jeff A. Tysinger, Dawn P. Tysinger

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There has been considerable growth in online learning. Researchers continue to explore the impact various methods of delivery. Podcasting is a popular method for sharing information. The purpose of this study was to examine the impact of student motivation and the perception of the acquisition of knowledge in an online environment of a skill-based class. 25 students in a school psychology graduate class completed a pretest and posttest examining podcast use and familiarity. In addition, at the completion of the course they were administered a modified version of the Instructional Materials Motivation Survey. The four subscales were examined (attention, relevance, confidence, and satisfaction). Results indicated that students are motivated, they perceive podcasts as positive instructional tools, and students are successful in acquiring the needed information. Additional benefits of using podcasts and recommendations in school psychology training are discussed.

Keywords: motivation, online learning, pedagogy, podcast

Procedia PDF Downloads 118

Authors: Davut Disci

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Objective: to measure the factors affecting expectations and intentions of using mobile phone in educational contexts by university students, using advanced equations and modeling techniques. Design and Methodology: According to the literature, Mobile Addiction, Parental Surveillance-Safety/Security, Social Relations, and Mobile Behavior are most used terms of defining mobile use of people. Therefore, these variables are tried to be measured to find and estimate their effects on expectations and intentions of using mobile phone in educational context. 421 university students participated in this study and there are 229 Female and 192 Male students. For the purpose of examining the mobile behavior and educational expectations and intentions, a questionnaire is prepared and applied to the participants who had to answer all the questions online. Furthermore, responses to close-ended questions are analyzed by using The Statistical Package for Social Sciences(SPSS) software, reliabilities are measured by Cronbach’s Alpha analysis and hypothesis are examined via using Multiple Regression and Linear Regression analysis and the model is tested with Structural Equation Modeling (SEM) technique which is important for testing the model scientifically. Besides these responses, open-ended questions are taken into consideration. Results: When analyzing data gathered from close-ended questions, it is found that Mobile Addiction, Parental Surveillance, Social Relations and Frequency of Using Mobile Phone Applications are affecting the mobile behavior of the participants in different levels, helping them to use mobile phone in educational context. Moreover, as for open-ended questions, participants stated that they use many mobile applications in their learning environment in terms of contacting with friends, watching educational videos, finding course material via internet. They also agree in that mobile phone brings greater flexibility to their lives. According to the SEM results the model is not evaluated and it can be said that it may be improved to show in SEM besides in multiple regression. Conclusion: This study shows that the specified model can be used by educationalist, school authorities to improve their learning environment.

Keywords: learning technology, instructional technology, mobile learning, technology

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Authors: Eunice Tan

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The purpose of this presentation is to look at an alternative to the approach and methodologies of working with special needs. The strength-based approach to education embodies a paradigm shift. It is a strategy to move away from a deficit-based methodology which inadvertently may lead to an extensive list of things that the child cannot do or is unable to do. Today, many parents of individuals with special needs are focused on the child’s deficits rather than on his or her strengths. Even when parents Recognise and identify their child’s strengths to be valuable and wish to develop their abilities, they face the challenge that there are insufficient programs committed to supporting the development and improvement of such abilities. What is a strength-based approach in education? A strength-based approach in education focuses on students' positive qualities and contributions to class instead of the skills and abilities they may not have. Many schools are focused on the child’s special educational needs rather than the whole child. Parents interviewed have said that they have to engage external tutors to help hone in on their child’s interests and strengths.

Keywords: differential learning needs, special needs, instructional style, talents

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Authors: Bekkem Chakradhar Reddy, Y. Soni Priya, Mathivanan G., L. K. Joshila Grace, N. Srinivasan, Asha P.

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Currently, there are a lot of problems related to marking attendance in schools, offices, or other places. Organizations tasked with collecting daily attendance data have numerous concerns. There are different ways to mark attendance. The most commonly used method is collecting data manually by calling each student. It is a longer process and problematic. Now, there are a lot of new technologies that help to mark attendance automatically. It reduces work and records the data. We have proposed to implement attendance marking using the latest technologies. We have implemented a system based on face identification and analyzing faces. The project is developed by gathering faces and analyzing data, using deep learning algorithms to recognize faces effectively. The data is recorded and forwarded to the host through mail. The project was implemented in Python and Python libraries used are CV2, Face Recognition, and Smtplib.

Keywords: python, deep learning, face recognition, CV2, smtplib, Dlib.

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Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lorenço

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The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in a smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore relying on fixed operational models would be inappropriate. This paper presents a study on developing an Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose an Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

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Authors: Gae Hee Song

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This paper aims to address the evolution of public-private partnerships for mainstreaming an evaluation approach in the community-based education project. It examines the distinctive features of Save the Children’s School Me project in terms of empowerment evaluation principles introduced by David M. Fetterman, especially community ownership, capacity building, and organizational learning. School Me is a Save the Children Korea funded-project, having been implemented in Cote d’Ivoire and Sierra Leone since 2016. The objective of this project is to reduce gender-based disparities in school completion and learning outcomes by creating an empowering learning environment for girls and boys. Both quasi-experimental and experimental methods for impact evaluation have been used to explore changes in learning outcomes, gender attitudes, and learning environments. To locate School Me in the public-private partnership framework for community empowerment and sustainability, the data have been collected from School Me progress/final reports, baseline, and endline reports, fieldwork observations, inter-rater reliability of baseline and endline data collected from a total of 75 schools in Cote d’Ivoire and Sierra Leone. The findings of this study show that School Me project has a significant evaluation component, including qualitative exploratory research, participatory monitoring, and impact evaluation. It strongly encourages key actors, girls, boys, parents, teachers, community leaders, and local education authorities, to participate in the collection and interpretation of data. For example, 45 community volunteers collected baseline data in Cote d’Ivoire; on the other hand, three local government officers and fourteen enumerators participated in the follow-up data collection of Sierra Leone. Not only does this public-private partnership improve local government and community members’ knowledge and skills of monitoring and evaluation, but the evaluative findings also help them find their own problems and solutions with a strong sense of community ownership. Such community empowerment enables Save the Children country offices and member offices to gain invaluable experiences and lessons learned. As a result, empowerment evaluation leads to community-oriented governance and the sustainability of the School Me project.

Keywords: community empowerment, Cote d’Ivoire, empowerment evaluation, public-private partnership, save the children, school me, Sierra Leone, sustainability

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Authors: M. M. Essa, S. Subash, M. Akbar, S. Al-Adawi, A. Al-Asmi, G. J. Guillemein

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Transgenic (tg) mice which contain an amyloid precursor protein (APP) gene mutation, develop extracellular amyloid beta (Aβ) deposition in the brain, and severe memory and behavioral deficits with age. These mice serve as an important animal model for testing the efficacy of novel drug candidates for the treatment and management of symptoms of Alzheimer's disease (AD). Several reports have suggested that oxidative stress is the underlying cause of Aβ neurotoxicity in AD. Date palm fruits contain very high levels of antioxidants and several medicinal properties that may be useful for improving the quality of life in AD patients. In this study, we investigated the effect of dietary supplementation of Omani date palm fruits on the memory, anxiety and learning skills along with inflammation in an AD mouse model containing the double Swedish APP mutation (APPsw/Tg2576). The experimental groups of APP-transgenic mice from the age of 4 months were fed custom-mix diets (pellets) containing 2% and 4% Date palm fruits. We assessed spatial memory and learning ability, psychomotor coordination, and anxiety-related behavior in Tg and wild-type mice at the age of 4-5 months and 18-19 months using the Morris water maze test, rota rod test, elevated plus maze test, and open field test. Further, inflammatory parameters also analyzed. APPsw/Tg2576 mice that were fed a standard chow diet without dates showed significant memory deficits, increased anxiety-related behavior, and severe impairment in spatial learning ability, position discrimination learning ability and motor coordination along with increased inflammation compared to the wild type mice on the same diet, at the age of 18-19 months In contrast, PPsw/Tg2576 mice that were fed a diet containing 2% and 4% dates showed a significant improvements in memory, learning, locomotor function, and anxiety with reduced inflammatory markers compared to APPsw/Tg2576 mice fed the standard chow diet. Our results suggest that dietary supplementation with dates may slow the progression of cognitive and behavioral impairments in AD. The exact mechanism is still unclear and further extensive research needed.

Keywords: Alzheimer's disease, date palm fruits, Oman, cognitive decline, memory loss, anxiety, inflammation

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Authors: Cheyne Kirkpatrick

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In an attempt to make the university intensive English program more worthwhile for students, many English language programs are redesigning curriculum to offer for-credit English for Academic Purposes classes, sometimes marketed as “bridge” courses. These programs are designed to be accredited to national language standards, provide communicative language learning, and give students the opportunity to simultaneously earn university language credit while becoming proficient in academic English. This presentation will discuss the curriculum design of one such program in the United States at a large private university that created its own for-credit “bridge” program. The planning, development, piloting, teaching, and challenges of designing this type of curriculum will be presented along with the aspects of accreditation, communicative language learning, and integration within various university programs. Attendees will learn about how such programs are created and what types of objectives and outcomes are included in American EAP classes.

Keywords: IEP, AEP, Curriculum, CEFR, University Credit, Bridge

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Authors: Dario Barsi, Marina Ubaldi, Pietro Zunino, Robert Fink

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A design and optimization procedure is proposed and developed to provide the geometry of a high efficiency compact hydraulic propeller turbine for low head. For the preliminary design of the machine, classic design criteria, based on the use of statistical correlations for the definition of the fundamental geometric parameters and the blade shapes are used. These relationships are based on the fundamental design parameters (i.e., specific speed, flow coefficient, work coefficient) in order to provide a simple yet reliable procedure. Particular attention is paid, since from the initial steps, on the correct conformation of the meridional channel and on the correct arrangement of the blade rows. The preliminary geometry thus obtained is used as a starting point for the hydrodynamic optimization procedure, carried out using a CFD calculation software coupled with a genetic algorithm that generates and updates a large database of turbine geometries. The optimization process is performed using a commercial approach that solves the turbulent Navier Stokes equations (RANS) by exploiting the axial-symmetric geometry of the machine. The geometries generated within the database are therefore calculated in order to determine the corresponding overall performance. In order to speed up the optimization calculation, an artificial neural network (ANN) based on the use of an objective function is employed. The procedure was applied for the specific case of a propeller turbine with an innovative design of a modular type, specific for applications characterized by very low heads. The procedure is tested in order to verify its validity and the ability to automatically obtain the targeted net head and the maximum for the total to total internal efficiency.

Keywords: renewable energy conversion, hydraulic turbines, low head hydraulic energy, optimization design

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Authors: Emilee M. Cruz

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Teachers take part in short-term teaching fellowships abroad, and their preparation before, during, and after the experience is critical to affecting teachers’ feelings of success in the international classroom. A program evaluation of the teacher preparation within TALMA: The Israel Program for Excellence in English (TALMA) full-year teaching fellowship was conducted. A questionnaire was developed that examined professional development, deliberate reflection, and cultural and language immersion offered before, during, and after the short-term experience. The evaluation also surveyed teachers’ feelings of preparedness for the Israeli classroom and any recommendations they had for future teacher preparation within the fellowship program. The review suggests the TALMA program includes integrated professional learning communities between fellows and Israeli co-teachers, more opportunities for immersive Hebrew language learning, a broader professional network with Israelis, and opportunities for guided discussion with the TALMA community continued participation in TALMA events and learning following the full-year fellowship. Similar short-term international programs should consider the findings in the design of their participation preparation programs. The review also offers direction for future program evaluation of short-term participant preparation, including the need for frequent response item updates to match current offerings and evaluation of participant feelings of preparedness before, during, and after the full-year fellowship.

Keywords: educational program evaluation, international teaching, short-term teaching, teacher beliefs, teaching fellowship, teacher preparation

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Authors: Juan Pablo Botero Torres, Alba Avila, Luis Felipe Giraldo

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Independent navigation and mobility through unknown spaces pose a challenge for the autonomy of visually impaired people (VIP), who have relied on the use of traditional assistive tools like the white cane and trained dogs. However, emerging visually assistive technologies (VAT) have proposed several human-machine interfaces (HMIs) that could improve VIP’s ability for self-guidance. Hereby, we introduce the design and implementation of a visually assistive device, Anajaa – Visual Substitution System (AVSS). This system integrates ultrasonic sensors with custom electronics, and computer vision models (convolutional neural networks), in order to achieve a robust system that acquires information of the surrounding space and transmits it to the user in an intuitive and efficient manner. AVSS consists of two modules: the sensing and the actuation module, which are fitted to a chest mount and belt that communicate via Bluetooth. The sensing module was designed for the acquisition and processing of proximity signals provided by an array of ultrasonic sensors. The distribution of these within the chest mount allows an accurate representation of the surrounding space, discretized in three different levels of proximity, ranging from 0 to 6 meters. Additionally, this module is fitted with an RGB-D camera used to detect potentially threatening obstacles, like staircases, using a convolutional neural network specifically trained for this purpose. Posteriorly, the depth data is used to estimate the distance between the stairs and the user. The information gathered from this module is then sent to the actuation module that creates an HMI, by the means of a 3x2 array of vibration motors that make up the tactile display and allow the system to deliver haptic feedback. The actuation module uses vibrational messages (tactones); changing both in amplitude and frequency to deliver different awareness levels according to the proximity of the obstacle. This enables the system to deliver an intuitive interface. Both modules were tested under lab conditions, and the HMI was additionally tested with a focal group of VIP. The lab testing was conducted in order to establish the processing speed of the computer vision algorithms. This experimentation determined that the model can process 0.59 frames per second (FPS); this is considered as an adequate processing speed taking into account that the walking speed of VIP is 1.439 m/s. In order to test the HMI, we conducted a focal group composed of two females and two males between the ages of 35-65 years. The subject selection was aided by the Colombian Cooperative of Work and Services for the Sightless (COOTRASIN). We analyzed the learning process of the haptic messages throughout five experimentation sessions using two metrics: message discrimination and localization success. These correspond to the ability of the subjects to recognize different tactones and locate them within the tactile display. Both were calculated as the mean across all subjects. Results show that the focal group achieved message discrimination of 70% and a localization success of 80%, demonstrating how the proposed HMI leads to the appropriation and understanding of the feedback messages, enabling the user’s awareness of its surrounding space.

Keywords: computer vision on embedded systems, electronic trave aids, human-machine interface, haptic feedback, visual assistive technologies, vision substitution systems

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Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lourenço

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The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore, relying on fixed operational models would be inappropriate. This paper presents a study on developing a Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose a Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

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Authors: Ksheeraj Sai Vepuri, Nada Attar

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We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: facial expression recognittion, image preprocessing, deep learning, CNN

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Authors: Yasaman Azarmjoo

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Since ancient times, it has been said that mathematics is the mother of all sciences and the foundation of basic concepts in every field and profession. It would be great if, after learning this subject, we could enable students to create games and activities based on the same mathematical concepts. This article explores the design of various mathematical activities in the form of games, utilizing different mathematical topics such as algebra, equations, binary systems, and one-to-one correspondence. The theoretical significance of this article lies in uncovering alternative approaches to teaching and learning mathematics. By employing creative and interactive methods such as game design, it challenges the traditional perception of mathematics as a difficult and laborious subject. The theoretical significance of this article lies in demonstrating that mathematics can be made more accessible and enjoyable, which can result in heightened interest and engagement in the subject. In general, this article reveals another aspect of mathematics.

Keywords: playing with mathematics, algebra and equations, binary systems, one-to-one correspondence

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Authors: Adeep Hande, Shubham Agarwal

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This paper presents a study on identifying sexism in online texts using various state-of-the-art deep learning models based on BERT. We experimented with different feature sets and model architectures and evaluated their performance using precision, recall, F1 score, and accuracy metrics. We also explored the use of pseudolabeling technique to improve model performance. Our experiments show that the best-performing models were based on BERT, and their multilingual model achieved an F1 score of 0.83. Furthermore, the use of pseudolabeling significantly improved the performance of the BERT-based models, with the best results achieved using the pseudolabeling technique. Our findings suggest that BERT-based models with pseudolabeling hold great promise for identifying sexism in online texts with high accuracy.

Keywords: large language models, semi-supervised learning, sexism detection, data sparsity

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Authors: Ruby A. L. Espineli

Abstract:

The study assessed the Philippine National Police strategies in the implementation of ‘Peace and Order Agenda for Transformation and Upholding of the Rule-of-Law’ P.A.T.R.O.L Plan 2030. Its operational roadmap presents four perspectives which include resource management, learning and growth, process excellence; and community. Focused group discussion, observation, and distribution of survey questionnaire to selected PNP officers and community members were done to identify and describe the implementation, problems encountered and measures to address the problems of the PNP P.A.T.R.O.L Plan 2030. In resource management, PNP allocates most sufficient funds in providing service firearms, patrol vehicle, and internet connections. In terms of learning and growth, the attitude of PNP officers is relatively higher than their knowledge and skills. Moreover, in terms of process excellence, the PNP use several crime preventions and crime solution strategies to deliver an immediate response to calls of the community. As regards, community perspective, PNP takes effort in establishing partnership with community. It is also interesting to note that PNP officers and community were both undecided on the existence of problems encountered in the implementation of P.A.T.R.O.L Plan 2030. But, they had proactive behavior as they agreed on all the specified measures to address the problems encountered in implementation of PNP P.A.T.R.O.L. Plan 2030. A strategic framework, based on the findings was formulated in this study that could improve and entrench the harmonious working relationship between the PNP and stakeholders in the enhancement of the implementation of PNP P.A.T.R.O.L. Plan 2030.

Keywords: community perspectives, learning and growth, process excellence, resource management

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Authors: Dirson Santos De Campos, Deller James Ferreira, Anderson Cavalcante Gonçalves, Uyara Ferreira Silva

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Rubrics to learning research provide many evaluation criteria and expected performance standards linked to defined student activity for learning and pedagogical objectives. Despite the rubric being used in education at all levels, academic literature on rubrics as a tool to support research in SQL Education is quite rare. There is a large class of SQL queries is syntactically correct, but certainly, not all are semantically correct. Detecting and correcting errors is a recurring problem in SQL education. In this paper, we usthe Rubric Abstract Framework (RAF), which consists of steps, that allows us to map the information to measure student performance guided by didactic objectives defined by the teacher as long as it is contextualized domain modeling by rubric. An empirical study was done that demonstrates how rubrics can mitigate student difficulties in finding logical errors and easing teacher workload in SQL education. Detecting and correcting logical errors is an important skill for students. Researchers have proposed several ways to improve SQL education because understanding this paradigm skills are crucial in software engineering and computer science. The RAF instantiation was using in an empirical study developed during the COVID-19 pandemic in database course. The pandemic transformed face-to-face and remote education, without presential classes. The lab activities were conducted remotely, which hinders the teaching-learning process, in particular for this research, in verifying the evidence or statements of knowledge, skills, and abilities (KSAs) of students. Various research in academia and industry involved databases. The innovation proposed in this paper is the approach used where the results obtained when using rubrics to map logical errors in query formulation have been analyzed with gains obtained by students empirically verified. The research approach can be used in the post-pandemic period in both classroom and distance learning.

Keywords: rubric, logical error, structured query language (SQL), empirical study, SQL education

Procedia PDF Downloads 175