Search results for: traditional learning approach

Authors: Hexiong Liu

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Powder metallurgy is the optimal method for the consolidation and preparation of W(Mo) alloys, which exhibit excellent application prospects at high temperatures. The properties of W(Mo) alloys are closely related to the sintered density. However, controlling the sintered density and porosity of these alloys is still challenging. In the past, the regulation methods mainly focused on time-consuming and costly trial-and-error experiments. In this study, the sintering data for more than a dozen W(Mo) alloys constituted a small-scale dataset, including both solid and liquid phases of sintering. Furthermore, simple descriptors were used to predict the sintered density of W(Mo) alloys based on the descriptor selection strategy and machine learning method (ML), where the ML algorithm included the least absolute shrinkage and selection operator (Lasso) regression, k-nearest neighbor (k-NN), random forest (RF), and multi-layer perceptron (MLP). The results showed that the interpretable descriptors extracted by our proposed selection strategy and the MLP neural network achieved a high prediction accuracy (R>0.950). By further predicting the sintered density of W(Mo) alloys using different sintering processes, the error between the predicted and experimental values was less than 0.063, confirming the application potential of the model.

Keywords: sintered density, machine learning, interpretable descriptors, W(Mo) alloy

Procedia PDF Downloads 85

Authors: S. Njoumi, L. Ben Haj Said, M. J. Amiot, S. Bellagha

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The main objective of this research was to establish the kinetics of variation of total polyphenol content (TPC) and total flavonoid content (TFC) in Tunisian Corchorus olitorius powder and in a traditional home cooked-meal (Molokheiya) when using stewing and stir-frying as cooking methods, but also to compare the effect of these two common cooking practices on water content, TPC, TFC and color. The L*, a* and b* coordinates values of the Molokheiya varied from 24.955±0.039 to 21.301±0.036, from -1.556±0.048 to 0.23±0.026 and from 5.675±0.052 to 6.313±0.103 when using stewing and from 21.328±0.025 to 20.56±0.021, from -1.093± 0.011to 0.121±0.007 and from 5.708±0.020 to 6.263±0.007 when using stir-frying, respectively. TPC and TFC increased during cooking. TPC of Molokheiya varied from 29.852±0.866 mg GAE/100 g to 220.416±0.519 mg GAE/100 g after 150 min of stewing and from 25.257±0.259 mg GAE/100 g to 208.897 ±0.173 mg GAE/100 g using stir-frying method during 150 min. TFC of Molokheiya varied from 48.229±1.47 mg QE/100 g to 843.802±1.841 mg QE/100 g when using stewing and from 37.031± 0.368 mg QE/100 g to 775.312±0.736 mg QE/100 g when using stir-frying. Kinetics followed similar curves in all cases but resulted in different final TPC and TFC. The shape of the kinetics curves suggests zero-order kinetics. The mathematical relations and the numerical approach used to model the kinetics of polyphenol and flavonoid contents in Molokheiya are described.

Keywords: Corchorus olitorius, Molokheiya, phenolic compounds, kinetic

Procedia PDF Downloads 357

Authors: My Hachem Aouragh, Hind Ragragui, Abdellah El-Hmaidi, Ali Essahlaoui, Abdelhadi El Ouali

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This study investigates soil erosion susceptibility in the Oued Mikkes watershed, located in the Meknes-Fez region of northern Morocco, utilizing advanced techniques such as deep learning algorithms and remote sensing integrated within Geographic Information Systems (GIS). Spanning approximately 1,920 km², the watershed is characterized by a semi-arid Mediterranean climate with irregular rainfall and limited water resources. The waterways within the watershed, especially the Oued Mikkes, are vital for agricultural irrigation and potable water supply. The research assesses the extent of erosion risk upstream of the Sidi Chahed dam while developing a spatial model of soil loss. Several important factors, including topography, land use/land cover, and climate, were analyzed, with data on slope, NDVI, and rainfall erosivity processed using deep learning models (DLNN, CNN, RNN). The results demonstrated excellent predictive performance, with AUC values of 0.92, 0.90, and 0.88 for DLNN, CNN, and RNN, respectively. The resulting susceptibility maps provide critical insights for soil management and conservation strategies, identifying regions at high risk for erosion across 24% of the study area. The most high-risk areas are concentrated on steep slopes, particularly near the Ifrane district and the surrounding mountains, while low-risk areas are located in flatter regions with less rugged topography. The combined use of remote sensing and deep learning offers a powerful tool for accurate erosion risk assessment and resource management in the Mikkes watershed, highlighting the implications of soil erosion on dam siltation and operational efficiency.

Keywords: soil erosion, GIS, remote sensing, deep learning, Mikkes Watershed, Morocco

Procedia PDF Downloads 26

Authors: Emily Cherono Sawe, Elisha Ondieki Makori

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Knowledge and digital economies have brought challenges and potential opportunities for universities to innovate and improve the quality of learning. Disruption technologies and information dynamics continue to transform and change the landscape in teaching, scholarship, and research activities across universities. Digital literacy is a fundamental and imperative element in higher education and training, as witnessed during the new norm. COVID-19 caused unprecedented disruption in universities, where teaching and learning depended on digital innovations and applications. Academic services and activities were provided online, including library information services. Information professionals were forced to adopt various digital platforms in order to provide information services to patrons. University libraries’ roles in fulfilling educational responsibilities continue to evolve in response to changes in pedagogy, technology, economy, society, policies, and strategies of parent institutions. Libraries are currently undergoing considerable transformational change as a result of the inclusion of a digital environment. Academic libraries have been at the forefront of providing online learning resources and online information services, as well as supporting students and staff to develop digital literacy skills via online courses, tutorials, and workshops. Digital literacy transformation and information staff are crucial elements reminiscent of the prioritization of skills and knowledge for lifelong learning. The purpose of this baseline research is to assess the implications of digital literacy transformation in institutions of higher learning in Kenya and share appropriate strategies to leverage and sustain teaching and research. Objectives include examining the leverage and preparedness of the digital literacy environment in streamlining learning in the universities, exploring and benchmarking imperative digital competence for information professionals, establishing the perception of information professionals towards digital literacy skills, and determining lessons, best practices, and strategies to accelerate digital literacy transformation for effective research and learning in the universities. The study will adopt a descriptive research design using questionnaires and document analysis as the instruments for data collection. The targeted population is librarians and information professionals, as well as academics in public and private universities teaching information literacy programmes. Data and information are to be collected through an online structured questionnaire and digital face-to-face interviews. Findings and results will provide promising lessons together with best practices and strategies to transform and change digital literacies in university libraries in Kenya.

Keywords: digital literacy, digital innovations, information professionals, librarians, higher education, university libraries, digital information literacy

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Authors: Marcin Michalak

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Due to the increasing efforts on saving our natural environment a change in the structure of energy resources can be observed - an increasing fraction of a renewable energy sources. In many countries traditional underground coal mining loses its significance but there are still countries, like Poland or Germany, in which the coal based technologies have the greatest fraction in a total energy production. This necessitates to make an effort to limit the costs and negative effects of underground coal mining. The longwall complex is as essential part of the underground coal mining. The safety and the effectiveness of the work is strongly dependent of the diagnostic state of powered roof supports. The building of a useful and reliable diagnostic system requires a lot of data. As the acquisition of a data of any possible operating conditions it is important to have a possibility to generate a demanded artificial working characteristics. In this paper a new approach of modelling a leg pressure in the single unit of powered roof support. The model is a result of the analysis of a typical working cycles.

Keywords: machine modelling, underground mining, coal mining, structure

Procedia PDF Downloads 370

Authors: Alexandra Leukauf, Alexander Schirrer, Emir Talic

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Numerical computation of wave propagation in a large domain usually requires significant computational effort. Hence, the considered domain must be truncated to a smaller domain of interest. In addition, special boundary conditions, which absorb the outward travelling waves, need to be implemented in order to describe the system domains correctly. In this work, the linear one dimensional wave equation is approximated by utilizing the Fourier Galerkin approach. Furthermore, the artificial boundaries are realized with absorbing boundary conditions. Within this work, a systematic work flow for setting up the wave problem, including the absorbing boundary conditions, is proposed. As a result, a convenient modal system description with an effective absorbing boundary formulation is established. Moreover, the truncated model shows high accuracy compared to the global domain.

Keywords: absorbing boundary conditions, boundary control, Fourier Galerkin approach, modal approach, wave equation

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Authors: Bowen Ding, Yihao Kuang

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In recent years, with the development of large-scale pre-trained lan-guage models, building vector representations of text through deep neural network models has become a standard practice for natural language processing tasks. From the performance on downstream tasks, we can know that the text representation constructed by these models contains linguistic information, but its encoding mode and extent are unclear. In this work, a structural probe is proposed to detect whether the vector representation produced by a deep neural network is embedded with a syntax tree. The probe is trained with the deep metric learning method, so that the distance between word vectors in the metric space it defines encodes the distance of words on the syntax tree, and the norm of word vectors encodes the depth of words on the syntax tree. The experiment results on ELMo and BERT show that the syntax tree is encoded in their parameters and the word representations they produce.

Keywords: deep metric learning, syntax tree probing, natural language processing, word representations

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Authors: Kamel Laidi, Khelifa Benmansour, Ouahid Bouchhida

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Neural networks-based approach for 2-cells serial converter has been developed and implemented. The approach is based on a behavioural description of the different operating modes of the converter. Each operating mode represents a well-defined configuration, and for which is matched an operating zone satisfying given invariance conditions, depending on the capacitors' voltages and the load current of the converter. For each mode, a control vector whose components are the control signals to be applied to the converter switches has been associated. Therefore, the problem is reduced to a classification task of the different operating modes of the converter. The artificial neural nets-based approach, which constitutes a powerful tool for this kind of task, has been adopted and implemented. The application to a 2-cells chopper has allowed ensuring efficient and robust control of the load current and a high capacitors voltages balancing.

Keywords: neural nets, control, multicellular converters, 2-cells chopper

Procedia PDF Downloads 839

Authors: Kumar Sambhav Pandey, Anamika Singh

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The continuous researches in the field of computer architecture basically aims at accelerating the computational speed and to gain enhanced performance. In this era, the superscalar, sub-scalar concept has not gained enough attention for improving the computation performance. In this paper, we have presented a sub-scalar approach to utilize the parallelism present with in the data while processing. The main idea is to split the data into individual smaller entities and these entities are processed with a defined known set of instructions. This sub-scalar approach to the MIPS architecture can bring out significant improvement in the computational speedup. MIPS-I is the basic design taken in consideration for the development of sub-scalar MIPS64 for increasing the instruction level parallelism (ILP) and resource utilization.

Keywords: dataword, MIPS, processor, sub-scalar

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Authors: Gangmin Li, Fan Yang

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Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behaviour data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification, etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: personalized recommendation, generative user modelling, user intention identification, large language models, chain-of-thought prompting

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Authors: Anil Kumar Baral

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The research introduces a ground-breaking approach to waste management, emphasizing innovation, education, and transformation. Using Chandragiri Municipality as a case study, the study advocates a shift from traditional to progressive waste management strategies, contributing an inventive waste framework, sustainability advocacy, and a transformative blueprint. The waste composition analysis highlights Chandragiri's representative profile, leading to a comprehensive plan addressing challenges and recommending a transition to a profitable waste treatment model, supported by relevant statistics. The data-driven approach incorporates the official data of waste Composition from Chandragiri Municipality as secondary data and incorporates the primary data from Chandragiri households, ensuring a nuanced perspective. Discussions on implementation, viability, and environmental preservation underscore the dual benefit of sustainability. The study includes a comparative analysis, monitoring, and evaluation framework, examining international relevance and collaboration, and conducting a social and environmental impact assessment. The results indicate the necessity for creative changes in Chandragiri's waste practices, recommending separate treatment centers in wards level rather than Municipal level, composting machines, and a centralized waste treatment plant. Educational reforms involve revising school curricula and awareness campaigns. The transformation's success hinges on reducing waste size, efficient treatment center operation, and ongoing public literacy. The conclusion summarizes key findings, envisioning a future with sustainable waste management practices deeply embedded in the community fabric.

Keywords: innovate, educate, transform, municipality, method

Procedia PDF Downloads 49

Authors: Sélima Baccar, Ephraim Clark

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This paper can be considered as a new perspective to analyse credit spreads. A comprehensive empirical analysis of conditional variance of credit spreads indices is performed using various GARCH models. Based on a comparison between traditional and asymmetric GARCH models with alternative functional forms of the conditional density, we intend to identify what macroeconomic and financial factors have driven daily changes in the US Dollar credit spreads in the period from January 2011 through January 2013. The results provide a strong interdependence between credit spreads and the explanatory factors related to the conditions of interest rates, the state of the stock market, the bond market liquidity and the exchange risk. The empirical findings support the use of asymmetric GARCH models. The AGARCH and GJR models outperform the traditional GARCH in credit spreads modelling. We show, also, that the leptokurtic Student-t assumption is better than the Gaussian distribution and improves the quality of the estimates, whatever the rating or maturity.

Keywords: corporate bonds, default risk, credit spreads, asymmetric garch models, student-t distribution

Procedia PDF Downloads 477

Authors: Surajbhan Sevda

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Metal containing wastewater is generated in large quintiles due to rapid industrialization. Generally, the metal present in wastewater is not biodegradable and can be accumulated in living animals, humans and plant tissue, causing disorder and diseases. The conventional metal recovery methods include chemical, physical and biological methods, but these are chemical and energy intensive. The recent development in microbial fuel cell (MFC) technology provides a new approach for metal recovery; this technology offers a flexible platform for both reduction and oxidation reaction oriented process. The use of MFCs will be a new platform for more efficient and low energy approach for metal recovery from the wastewater. So far metal recover was extensively studied using chemical, physical and biological methods. The MFCs present a new and efficient approach for removing and recovering metals from different wastewater, suggesting the use of different electrode for metal recovery can be a new efficient and effective approach.

Keywords: metal recovery, microbial fuel cell, wastewater, bioelectricity

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Authors: Yuet Wah Echo Yeung

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Working with people from minority ethnic groups, refugees and asylum seeking communities who have limited proficiency in the language of the host country often presents a major challenge for social workers. Because of language differences, social workers need to work with interpreters to ensure accurate information is collected for their assessment and intervention. Drawing from social learning theory, this paper discusses how role play was used as an experiential learning exercise in a training session to help social work students develop skills when working with interpreters. Social learning theory posits that learning is a cognitive process that takes place in a social context when people observe, imitate and model others’ behaviours. The roleplay also helped students understand the role of the interpreter and the challenges they may face when they rely on interpreters to communicate with service users and their family. The first part of the session involved role play. A tutor played the role of social worker and deliberately behaved in an unprofessional manner and used inappropriate body language when working alongside the interpreter during a home visit. The purpose of the roleplay is not to provide a positive role model for students to ‘imitate’ social worker’s behaviours. Rather it aims to active and provoke internal thinking process and encourages students to critically consider the impacts of poor practice on relationship building and the intervention process. Having critically reflected on the implications for poor practice, students were then asked to play the role of social worker and demonstrate what good practice should look like. At the end of the session, students remarked that they learnt a lot by observing the good and bad example; it showed them what not to do. The exercise served to remind students how practitioners can easily slip into bad habits and of the importance of respect for the cultural difference when working with people from different cultural backgrounds.

Keywords: role play, social learning theory, social work practice, working with interpreters

Procedia PDF Downloads 183

Authors: Ikechukwu Ogeze Ukeje, Chinyere Ori Elom, Chukwudum Collins Umoke

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This study explores the challenges in the integration of Artificial Intelligence (AI) and Information and Communication Technology (ICT) practices in enhancing governance and sustainable solution modeling in higher education, focusing on Alex Ekwueme Federal University Ndufu-Alike (AE-FUNAI), Nigeria. In the context of a developing country like Nigeria, leveraging AI and ICT tools presents a unique opportunity to improve teaching, learning, administrative processes, and governance. The research aims to evaluate how AI and ICT technologies can contribute to sustainable educational practices, enhance decision-making processes, and improve engagement among key stakeholders: students, lecturers, and administrative staff. Students are involved to provide insights into their interactions with AI and ICT tools, particularly in learning and participation in governance. Lecturers’ perspectives will offer a view into how these technologies influence teaching, research, and curriculum development. Administrative staff will provide a crucial understanding of how AI and ICT tools can streamline operations, support data-driven governance, and enhance institutional efficiency. This study will use a mixed-method approach to collect both qualitative and quantitative data. The finding of this study is geared towards shaping the future of education in Nigeria and beyond by developing an Inclusive AI-governance Integration Framework (I-AIGiF) for enhanced performance in the system. Examining the roles of these stakeholder groups, this research could guide the development of policies for more effective AI and ICT integration, leading to sustainable educational innovation and governance.

Keywords: university administration, AI, higher education governance, education sustainability, ICT challenges

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Authors: Mohammed Fayez Al Rez

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Nowadays, there is an unmet clinical need for new small-diameter vascular grafts to overcome the drawbacks of traditional methods used for treatment of widespread cardiovascular diseases. Vascular tissue engineering (VTE) is a promising approach that can be utilized to develop viable vascular grafts by in vitro seeding of functional cells onto a scaffold allowing them to attach, proliferate and differentiate. To achieve this purpose, the scaffold should provide cells with the initial necessary extracellular matrix environment and structure until being able to reconstruct the required vascular tissue. Therefore, producing scaffolds with suitable features is crucial for guiding cells properly to develop the desired tissue-engineered vascular grafts for clinical applications. The main objective of this work is fabrication and characterization of tubular small-diameter ( < 6 mm) bilayered scaffolds for VTE. The scaffolds were prepared via mixing electrospinning approach of biodegradable poly(ε-caprolactone) (PCL) polymer – due to its favorable physicochemical properties – to mimic the natural environment-extracellular matrix. Firstly, tubular nanofibrous construct with inner diameter of 3, 4 or 5 mm was electrospun as inner layer, and secondly, microfibrous construct was electrospun as outer layer directly on the first produced inner layer. To improve the biological properties of PCL, a group of the electrospun scaffolds was immersed in type-1 collagen solution. The morphology and structure of the resulting fibrous scaffolds were investigated by scanning electron microscope. The electrospun nanofibrous inner layer contained fibers measuring 219±35 nm in diameter, while the electrospun microfibrous outer layer contained fibers measuring 1011 ± 150 nm. Furthermore, mechanical, thermal and physical tests were conducted with both electrospun bilayered scaffold types where revealed improved properties. Biological investigations using endothelial, smooth muscle and fibroblast cell line showed good biocompatibility of both tested electrospun scaffolds. Better attachment and proliferation were obviously found when cells were cultured on the scaffolds immersed with collagen due to increasing the hydrophilicity of the PCL. The easy, inexpensive and versatile electrospinning approach used in this work was able to successfully produce double layered tubular elastic structures containing both nanofibers and microfibers to imitate the native vascular structure. The PCL – as a suitable and approved biomaterial for many biomedical and tissue engineering applications – can ensure favorable mechanical properties of scaffolds used for VTE. The VTE approach using electrospun bilayered scaffolds offers optimal solutions and holds significant promises for treatment of many cardiovascular diseases.

Keywords: electrospinning, poly(ε-caprolactone) (PCL), tissue-engineered vascular graft, tubular bilayered scaffolds, vascular cells

Procedia PDF Downloads 297

Authors: Andi Intan Purnamasari, Supriyadi, Sulbadana, Aminuddin Kasim

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Law functions as social control. Providing arrangements not only for legal certainty, but also in the scope of justice and expediency. The three values ​​achieved by law essentially function to bring comfort to each individual in carrying out daily activities. However, it is undeniable that global conditions have changed the orientation of people's lifestyles. Some people want to ensure their existence in the digital world which is popularly known as the metaverse. Some countries even project their city to be a metaverse city. The order of life is no longer limited to the real space, but also to the cyber world. Not infrequently, legal events that occur in the cyber world also force the law to position its position and even prevent crime in cyberspace. Through this research, conceptually it provides a view of the legal position in crime prevention in the Metaverse world. when the law acts to regulate the situation in the virtual world, of course some people will feel disturbed, this is due to the thought that the virtual world is a world in which an avatar can do things that cannot be done in the real world, or can be called a world without boundaries. Therefore, when the law is present to provide boundaries, of course the concept of the virtual world itself becomes no longer a cyber world that is not limited by space and time, it becomes a new order of life. approach, approach, approach, approach, and approach will certainly be the method used in this research.

Keywords: crime, cyber, metaverse, law

Procedia PDF Downloads 153

Authors: Suffian Hadi Ayub, Mohammad Rezal Hamzah, Nor Hafizah Abdullah, Sharipah Nur Mursalina Syed Azmy, Hishamuddin Salim

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The liberalisation of the education industry has exposed the institute of higher learning (IHL) in Malaysia to the financial challenges. Without good financial standing, public institution will rely on the government funding. Ostensibly, this contradicts with the government’s aspiration to make universities self-sufficient. With stiff competition from private institutes of higher learning, IHL need to be prepared at the forefront level. The corporate identity itself is the entrance to the world of higher learning and it is in this uniqueness, it will be able to distinguish itself from competitors. This paper examined the perception of the stakeholders at one of the public universities in the east coast region in Malaysia on the perceived reputation and how the university communicate its preparedness for self-sustainability through corporate identity. The findings indicated while the stakeholders embraced the challenges in facing the stiff competition and struggling market conditions, most of them felt the university should put more efforts in mobilising the corporate identity to its constituencies.

Keywords: communication, corporate identity, market conditions, universities

Procedia PDF Downloads 319

Authors: Steven W. Carruthers

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The purpose of the present research is to equate two test forms as part of a study to evaluate the educational effectiveness of the ARTé: Mecenas art history learning game. The researcher applied Item Response Theory (IRT) procedures to calculate item, test, and mean-sigma equating parameters. With the sample size n=134, test parameters indicated “good” model fit but low Test Information Functions and more acute than expected equating parameters. Therefore, the researcher applied equipercentile equating and linear equating to raw scores and compared the equated form parameters and effect sizes from each method. Item scaling in IRT enables the researcher to select a subset of well-discriminating items. The mean-sigma step produces a mean-slope adjustment from the anchor items, which was used to scale the score on the new form (Form R) to the reference form (Form Q) scale. In equipercentile equating, scores are adjusted to align the proportion of scores in each quintile segment. Linear equating produces a mean-slope adjustment, which was applied to all core items on the new form. The study followed a quasi-experimental design with purposeful sampling of students enrolled in a college level art history course (n=134) and counterbalancing design to distribute both forms on the pre- and posttests. The Experimental Group (n=82) was asked to play ARTé: Mecenas online and complete Level 4 of the game within a two-week period; 37 participants completed Level 4. Over the same period, the Control Group (n=52) did not play the game. The researcher examined between group differences from post-test scores on test Form Q and Form R by full-factorial Two-Way ANOVA. The raw score analysis indicated a 1.29% direct effect of form, which was statistically non-significant but may be practically significant. The researcher repeated the between group differences analysis with all three equating methods. For the IRT mean-sigma adjusted scores, form had a direct effect of 8.39%. Mean-sigma equating with a small sample may have resulted in inaccurate equating parameters. Equipercentile equating aligned test means and standard deviations, but resultant skewness and kurtosis worsened compared to raw score parameters. Form had a 3.18% direct effect. Linear equating produced the lowest Form effect, approaching 0%. Using linearly equated scores, the researcher conducted an ANCOVA to examine the effect size in terms of prior knowledge. The between group effect size for the Control Group versus Experimental Group participants who completed the game was 14.39% with a 4.77% effect size attributed to pre-test score. Playing and completing the game increased art history knowledge, and individuals with low prior knowledge tended to gain more from pre- to post test. Ultimately, researchers should approach test equating based on their theoretical stance on Classical Test Theory and IRT and the respective  assumptions. Regardless of the approach or method, test equating requires a representative sample of sufficient size. With small sample sizes, the application of a range of equating approaches can expose item and test features for review, inform interpretation, and identify paths for improving instruments for future study.

Keywords: effectiveness, equipercentile equating, IRT, learning games, linear equating, mean-sigma equating

Procedia PDF Downloads 196

Authors: Shilpa Murthy, Hazlina Binti Abu Bakar, Juliet Mathew, Chandrashekhar Thummala Hlly Sreerama Reddy, Pathiyil Ravi Shankar

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Simulation is defined as a technique that replaces or expands real experiences with guided experiences that interactively imitate real-world processes or systems. Simulation enables learners to train in a safe and non-threatening environment. For decades, simulation has been considered an integral part of clinical teaching and learning strategy in medical education. The several types of simulation used in medical education and the clinical environment can be applied to several models, including full-body mannequins, task trainers, standardized simulated patients, virtual or computer-generated simulation, or Hybrid simulation that can be used to facilitate learning. Simulation allows healthcare practitioners to acquire skills and experience while taking care of patient safety. The recent COVID pandemic has also led to an increase in simulation use, as there were limitations on medical student placements in hospitals and clinics. The learning is tailored according to the educational needs of students to make the learning experience more valuable. Simulation in the pre-clinical years has challenges with resource constraints, effective curricular integration, student engagement and motivation, and evidence of educational impact, to mention a few. As instructors, we may have more reliance on the use of simulation for pre-clinical students while the students’ confidence levels and perceived competence are to be evaluated. Our research question was whether the implementation of simulation-based learning positively influences preclinical medical students' confidence levels and perceived competence. This study was done to align the teaching activities with the student’s learning experience to introduce more low-fidelity simulation-based teaching sessions for pre-clinical years and to obtain students’ input into the curriculum development as part of inclusivity. The study was carried out at International Medical University, involving pre-clinical year (Medical) students who were started with low-fidelity simulation-based medical education from their first semester and were gradually introduced to medium fidelity, too. The Student Satisfaction and Self-Confidence in Learning Scale questionnaire from the National League of Nursing was employed to collect the responses. The internal consistency reliability for the survey items was tested with Cronbach’s alpha using an Excel file. IBM SPSS for Windows version 28.0 was used to analyze the data. Spearman’s rank correlation was used to analyze the correlation between students’ satisfaction and self-confidence in learning. The significance level was set at p value less than 0.05. The results from this study have prompted the researchers to undertake a larger-scale evaluation, which is currently underway. The current results show that 70% of students agreed that the teaching methods used in the simulation were helpful and effective. The sessions are dependent on the learning materials that are provided and how the facilitators engage the students and make the session more enjoyable. The feedback provided inputs on the following areas to focus on while designing simulations for pre-clinical students. There are quality learning materials, an interactive environment, motivating content, skills and knowledge of the facilitator, and effective feedback.

Keywords: low-fidelity simulation, pre-clinical simulation, students satisfaction, self-confidence

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Authors: Terence Soule, Tami Al Ghamdi

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To study how the partial knowledge transfer may affect the Genetic Algorithm (GA) performance, we model the Transfer Learning (TL) process using GA as the model solver. The objective of the TL is to transfer the knowledge from one problem to another related problem. This process imitates how humans think in their daily life. In this paper, we proposed to study a case where the knowledge transferred from the S problem has less information than what the T problem needs. We sampled the transferred population using different strategies of TL. The results showed transfer part of the knowledge is helpful and speeds the GA process of finding a solution to the problem.

Keywords: transfer learning, partial transfer, evolutionary computation, genetic algorithm

Procedia PDF Downloads 136

Authors: Sondos M. Hammad, Sherin M. ElGokhy, Mahmoud M. Fahmy, Elsayed A. Sallam

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In this paper, an ensemble-based Support Vector Machine (SVM) classification approach is proposed. It is used for miRNA prediction. Three problems, commonly associated with previous approaches, are alleviated. These problems arise due to impose assumptions on the secondary structural of premiRNA, imbalance between the numbers of the laboratory checked miRNAs and the pseudo-hairpins, and finally using a training data set that does not consider all the varieties of samples in different species. We aggregate the predicted outputs of three well-known SVM classifiers; namely, Triplet-SVM, Virgo and Mirident, weighted by their variant features without any structural assumptions. An additional SVM layer is used in aggregating the final output. The proposed approach is trained and then tested with balanced data sets. The results of the proposed approach outperform the three base classifiers. Improved values for the metrics of 88.88% f-score, 92.73% accuracy, 90.64% precision, 96.64% specificity, 87.2% sensitivity, and the area under the ROC curve is 0.91 are achieved.

Keywords: MiRNAs, SVM classification, ensemble algorithm, assumption problem, imbalance data

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Authors: H. Nakamura

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This study analyzes international strategic alliances in the information industry. The purpose of this study is to clarify the strategic intention of an international alliance. Secondly, it investigates the influence of differences in the target markets of partner companies on alliances. Using an international strategy theory approach to analyze the global strategies of global companies, the study compares a database business and an electronic publishing business. In particular, these cases emphasized factors attributable to "people" and "learning", reliability and communication between organizations and the evolution of the IT infrastructure. The theory evolved in this study validates the effectiveness of these strategies.

Keywords: database business, electronic library, international strategic alliances, partner selection

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Authors: Sara J. Mills, Sally Howell

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The field of special education has long struggled to bridge the research to practice gap. There is ample evidence from research of effective strategies for students with special needs, but these strategies are not routinely implemented in schools in ways that yield positive results for students. In recent years, the field of special education has turned its focus to implementation science. That is, discovering effective methods of implementing evidence-based practices in school settings. Teacher training is a critical factor in implementation. This study aimed to successfully implement Schema-Based Instruction (SBI) for math problem solving in four classrooms in a special primary school serving students with language deficits, including students with Autism Spectrum Disorders (ASD) and Intellectual Disabilities (ID). Using an action research design that allowed for adjustments and modification to be made over the year-long study, two cohorts of teachers across the school were trained and supported in six-week learning cycles to implement SBI in their classrooms. The learning cycles included a one-day training followed by six weeks of one-on-one or team coaching and three fortnightly cohort group meetings. After the first cohort of teachers completed the learning cycle, modifications and adjustments were made to lesson materials in an attempt to improve their effectiveness with the second cohort. Fourteen teachers participated in the study, including master special educators (n=3), special education instructors (n=5), and classroom assistants (n=6). Thirty-one students participated in the study (21 boys and 10 girls), ranging in age from 5 to 12 years (M = 9 years). Twenty-one students had a diagnosis of ASD, 20 had a diagnosis of mild or moderate ID, with 13 of these students having both ASD and ID. The remaining students had diagnosed language disorders. To evaluate the effectiveness of the implementation approach, both student and teacher data was collected. Student data included pre- and post-tests of math word problem solving. Teacher data included fidelity of treatment checklists and pre-post surveys of teacher attitudes and efficacy for teaching problem solving. Finally, artifacts were collected throughout the learning cycle. Results from cohort 1 and cohort 2 revealed similar outcomes. Students improved in the number of word problems they answered correctly and in the number of problem-solving steps completed independently. Fidelity of treatment data showed that teachers implemented SBI with acceptable levels of fidelity (M = 86%). Teachers also reported increases in the amount of time spent teaching problem solving, their confidence in teaching problem solving and their perception of students’ ability to solve math word problems. The artifacts collected during instruction indicated that teachers made modifications to allow their students to access the materials and to show what they knew. These findings are in line with research that shows student learning can improve when teacher professional development is provided over an extended period of time, actively involves teachers, and utilizes a variety of learning methods in classroom contexts. Further research is needed to evaluate whether these gains in teacher instruction and student achievement can be maintained over time once the professional development is completed.

Keywords: implementation science, mathematics problem solving, research-to-practice gap, schema based instruction

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Authors: Juliet Ramohai

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This paper explores how women departmental heads in higher education experience leadership in a time of the COVID-19 crises. The focus is mostly on their care and coping as they work in virtual spaces. Most scholars have looked at the effects and challenges that different employees face while working from home during a lockdown. However, very few take a dedicated focus on women in leadership and the coping mechanisms and resources that they use for effective leadership during this difficult time. The paper draws on two aspects of Sen’s Capabilities approach, functionings, and agency, to cast a closer understanding of the institutional and individual coping mechanisms that might be at these women's disposal. The qualitative approach used for this paper and a feminist lens provides a critical and in-depth understanding of the real-life stories of the women and how they make sense of their virtual leadership. Data for this paper was collected through semi-structured interviews with 10 women in the positions of head of departments and analysed thematically using capabilities approach concepts as an analytical tool. The findings in this paper indicate that functionings and freedoms are tightly linked to institutional ethnographies. These ethnographies might support or hamper coping for women leaders, especially during times of crisis.

Keywords: capability approach, women leaders, higher education, COVID-19

Procedia PDF Downloads 189

Authors: Mohamed Rehan, Gamil E. Ibrahim, Mohamed S. Abdel-Aziz, Shaimaa R. Ibrahim, Tawfik A. Khattab

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The utilization of natural products in finishing textiles toward multifunctional applications without side effects is an extremely motivating goal. Hibiscus sabdariffa usually has been used for many traditional medicine applications. To develop an additional use for Hibiscus sabdariffa, an extraction of bioactive compounds from Hibiscus sabdariffa followed by finishing on cellulosic fibers was designed to cleaner production of the value-added textiles fibers with multifunctional applications. The objective of this study is to explore, identify, and evaluate the bioactive compound extracted from Hibiscus sabdariffa by different solvent via ultrasonic technique as a potential eco-friendly agent for multifunctional cellulosic fabrics via two approaches. In the first approach, Hibiscus sabdariffa extract was used as a source of sustainable eco-friendly for simultaneous coloration and multi-finishing of cotton fabrics via in situ incorporations of nanoparticles (silver and metal oxide). In the second approach, the micro-capsulation of Hibiscus sabdariffa extracts was followed by coating onto cotton gauze to introduce multifunctional healthcare applications. The effect of the solvent type was accelerated by ultrasonic on the phytochemical, antioxidant, and volatile compounds of Hibiscus sabdariffa. The surface morphology and elemental content of the treated fabrics were explored using Fourier transform infrared spectroscopy (FT-IR), scanning electron microscope (SEM), and energy-dispersive X-ray spectroscopy (EDX). The multifunctional properties of treated fabrics, including coloration, sensor properties and protective properties against pathogenic microorganisms and UV radiation as well as wound healing property were evaluated. The results showed that the water, as well as ethanol/water, was selected as a solvent for the extraction of natural compounds from Hibiscus Sabdariffa with high in extract yield, total phenolic contents, flavonoid contents, and antioxidant activity. These natural compounds were utilized to enhance cellulosic fibers functionalization by imparting faint/dark red color, antimicrobial against different organisms, and antioxidants as well as UV protection properties. The encapsulation of Hibiscus Sabdariffa extracts, as well as wound healing, is under consideration and evaluation. As a result, the current study presents a sustainable and eco-friendly approach to design cellulosic fabrics for multifunctional medical and healthcare applications.

Keywords: cellulosic fibers, Hibiscus sabdariffa extract, multifunctional application, nanoparticles

Procedia PDF Downloads 150

Authors: Leah Burton, Sara Cumming, Julianne DiSanto

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Homelessness is a widespread and complex problem in Canada and around the globe. Many Canadians will face homelessness at least once in their lifetime, with several experiencing subsequent bouts or cyclical patterns of housing precarity. While a Housing First approach to homelessness is a long-standing and widely accepted best practice, it is also recognized that the acquisition of life skills is an effective way to reduce cycles of homelessness. Indeed, when individuals are provided with a range of life skills—such as (but not limited to) financial literacy, household management, interpersonal skills, critical thinking, and resource management—they are given the tools required to maintain long-term Housing for a lifetime; thus reducing a repetitive need for services. However, there is limited research regarding the best ways to teach life skills, a problem that has been further complicated in a post-pandemic world, where services are being delivered online or in a hybrid model of care. More than this, it is difficult to provide life skills on a large scale without losing a client-centered approach to services. This lack of client-centeredness is also seen in the lack of attention to culturally sensitive life skills, which consider the diverse needs of individuals and imbed equity, diversity, and inclusion (EDI) within the skills being taught. This study aims to fill these identified gaps in the literature by employing a community-engaged (CER) approach. Academic, government, funders, front-line staff, and clients at 15 not-for-profits from across the Greater Toronto Area in Ontario, Canada, collaborated to co-create a virtual, client-centric, EDI-informed life skill learning management system. A triangulation methodology was utilized for this research. An environmental scan was conducted for current best practices, and over 100 front-line staff (including workers, managers, and executive directors who work with homeless populations) participated in two separate Creative Problem Solving Sessions. Over 200 individuals with experience in homelessness completed quantitative and open-ended surveys. All sections of this research aimed to discover the areas of skills that individuals need to maintain Housing and to ascertain what a more client-driven EDI approach to life skills training should include. This presentation will showcase the findings on which life skills are deemed essential for homeless and precariously housed individuals.

Keywords: homelessness, housing first, life skills, community engaged research, client- centered

Procedia PDF Downloads 105

Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

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Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

Procedia PDF Downloads 143

Authors: Sadeq Al Yaari, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaari

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Objective: The aim of the study is to examine the relationship between visual agnosia and learning delay in Yemeni children. Method: A total of 80 subjects (experimental group= 60, 30 males and 30 females and control group= 20, 10 males and 10 females) in two institutions (old and new). The age of all subjects at hand ranges between 6- and 12 years old. Pre and post-tests were administered. Results: Outline results show severe effects on the performance of the children due to visual agnosia this effect was benign in the group that received the treatment, and this can be clearly seen in their results in the post-test compared to the other group that did not receive the treatment and outcomes in general can be better understood in light of the control group.

Keywords: visual, agnosia, linguistics, abilities, effects, psychoneurolinguistics

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Authors: Ramesh Joshi, Nisha Khatik

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Murraya koenigii (L.) Spreng locally known as “Curry patta” or “Meetha neem” belonging to the family Rutaceae that grows wildly in Southern Asia. Its aromatic leaves are commonly used as the raw material for traditional medicinal formulations in India. The leaves contain essential oil and also used as a condiment. Several monomeric and binary carbazol alkaloids present in the various plant parts. These alkaloids have been reported to possess anti-microbial, mosquitocidal, topo-isomerase inhibition and antioxidant properties. Some of the alkaloids reported in this plant have showed anti carcinogenic and anti-diabetic properties. The conventional method of propagation of this tree is limited to seeds only, which retain their viability for only a short period. Hence, a biotechnological approach might have an advantage edging over traditional breeding as well as the genetic improvement of M. koenigii within a short period. The development of a reproducible regeneration protocol is the prerequisite for ex situ conservation and micropropagation. An efficient protocol for high frequency regeneration of in vitro plants of Murraya koenigii via different explants such as- nodal segments, intermodal segments, leaf, root segments, hypocotyle, cotyledons and cotyledonary node explants is described. In the present investigation, assessment of clonal fidelity in the micropropagated plantlets of Murraya koenigii was attempted using RAPD and ISSR markers at different pathways of plant tissue culture technique. About 20 ISSR and 40 RAPD primers were used for all the samples. Genomic DNA was extracted by CTAB method. ISSR primer were found to be more suitable as compared to RAPD for the analysis of clonal fidelity of M. koenigii. The amplifications however, were finally performed using RAPD, ISSR markers owing to their better performance in terms of generation of amplification products. In RAPD primer maximum 75% polymorphism was recorded in OPU-2 series which exhibited out of 04 scorable bands, three bands were polymorphic with a band range of size 600-1500 bp. In ISSR primers the UBC 857 showed 50% polymorphism with 02 band were polymorphic of band range size between 400-1000 bp.

Keywords: genetic fidelity, Murraya koenigii, aromatic plants, ISSR primers

Procedia PDF Downloads 506