Search results for: enhancing learning experience

Authors: Martha Wilson

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With the peak of Computer-Assisted Language Learning slowly coming to pass and Mobile-Assisted Language Learning, at times, a bit lacking in the communicative department, we are now faced with a challenging question: How can we engage the interest of our digital native students and, most importantly, sustain it? As previously mentioned, our classrooms are now experiencing an influx of “digital natives” – people who have grown up using and having unlimited access to technology. While modernizing our curriculum and digitalizing our classrooms are necessary in order to accommodate this new learning style, it is a huge financial burden and a massive undertaking for language institutes. Instead, opting for a more compact, simple, yet multidimensional pedagogical tool may be the solution to the issue at hand. This paper aims to give a brief overview into an existing device referred to as Student Response Systems (SRS) and to expand on this notion to include a new prototype of response system that will be designed as a mobile application to eliminate the need for costly hardware and software. Additionally, an analysis into recent attempts by other institutes to develop the Mobile Response System (MRS) and customer reviews of the existing MRSs will be provided, as well as the lessons learned from those projects. Finally, while the new model of MRS is still in its infancy stage, this paper will discuss the implications of incorporating such an application as a tool to support and to enrich traditional techniques and also offer practical classroom applications with the existing response systems that are immediately available on the market.

Keywords: app, clickers, mobile app, mobile response system, student response system

Procedia PDF Downloads 371

Authors: Marla Wendy Spergel

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The purpose of this qualitative study is to showcase graduated high school students’ to voice on the impact past teachers had on their motivation to learn, and if this impact has affected their post-high-school lives. Through a focus group strategy, 21 graduated high school alumni participated in three separate focus groups. Participants discussed their former teacher’s emotional intelligence skills, which influenced their motivation to learn or not. A focused review of the literature revealed that teachers are a major factor in a student’s motivation to learn. This research was guided by Bandura’s Social Cognitive Theory of Motivation and constructs related to learning and motivation from Carl Rogers’ Humanistic Views of Personality, and from Brain-Based Learning perspectives with a major focus on the area of Emotional Intelligence. Findings revealed that the majority of participants identified teachers who most motivated them to learn and demonstrated skills associated with emotional intelligence. An important and disturbing finding relates to the saliency of negative experiences. Further work is recommended to expand this line of study in Higher Education, perform a long-term study to better gain insight into long-term benefits attributable to experiencing positive teachers, study the negative impact teachers have on students’ motivation to learn, specifically focusing on student anxiety and acquired helplessness.

Keywords: emotional intelligence, learning, motivation, pedagogy

Procedia PDF Downloads 157

Authors: Duong Van Thanh

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Artificial Intelligence (AI) has been recently a new trend in Higher Education systems globally as well as in the Vietnamese Higher Education. This study explores the benefits and challenges in applications of AI in 02 selected universities, ie. Vietnam National Universities in Hanoi Capital and the University of Economics in Ho Chi Minh City. Particularly, this paper focuses on how the ethics of Artificial Intelligence have been addressed among faculty members at these two universities. The AI ethical issues include the access and inclusion, privacy and security, transparency and accountability. AI-powered educational technology has the potential to improve access and inclusion for students with disabilities or other learning needs. However, there is a risk that AI-based systems may not be accessible to all students and may even exacerbate existing inequalities. AI applications can be opaque and difficult to understand, making it challenging to hold them accountable for their decisions and actions. It is important to consider the benefits that adopting AI-systems bring to the institutions, teaching, and learning. And it is equally important to recognize the drawbacks of using AI in education and to take the necessary steps to mitigate any negative impact. The results of this study present a critical concern in higher education in Vietnam, where AI systems may be used to make important decisions about students’ learning and academic progress. The authors of this study attempt to make some recommendation that the AI-system in higher education system is frequently checked by a human in charge to verify that everything is working as it should or if the system needs some retraining or adjustments.

Keywords: artificial intelligence, ethics, challenges, vietnam

Procedia PDF Downloads 127

Authors: Bruce X. B. Yu, Yan Liu, Keith C. C. Chan

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We propose to record Activities of Daily Living (ADLs) of elderly people using a vision-based system so as to provide better assistive and personalization technologies. Current ADL-related research is based on data collected with help from non-elderly subjects in laboratory environments and the activities performed are predetermined for the sole purpose of data collection. To obtain more realistic datasets for the application, we recorded ADLs for the elderly with data collected from real-world environment involving real elderly subjects. Motivated by the need to collect data for more effective research related to elderly care, we chose to collect data in the room of an elderly person. Specifically, we installed Kinect, a vision-based sensor on the ceiling, to capture the activities that the elderly subject performs in the morning every day. Based on the data, we identified 12 morning activities that the elderly person performs daily. To recognize these activities, we created a HARELCARE framework to investigate into the effectiveness of existing Human Activity Recognition (HAR) algorithms and propose the use of a transfer learning algorithm for HAR. We compared the performance, in terms of accuracy, and training progress. Although the collected dataset is relatively small, the proposed algorithm has a good potential to be applied to all daily routine activities for healthcare purposes such as evidence-based diagnosis and treatment.

Keywords: daily activity recognition, healthcare, IoT sensors, transfer learning

Procedia PDF Downloads 132

Authors: Ahcene Habbi, Yassine Boudouaoui

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This paper deals with the problem of automatic rule generation for fuzzy systems design. The proposed approach is based on hybrid artificial bee colony (ABC) optimization and weighted least squares (LS) method and aims to find the structure and parameters of fuzzy systems simultaneously. More precisely, two ABC based fuzzy modeling strategies are presented and compared. The first strategy uses global optimization to learn fuzzy models, the second one hybridizes ABC and weighted least squares estimate method. The performances of the proposed ABC and ABC-LS fuzzy modeling strategies are evaluated on complex modeling problems and compared to other advanced modeling methods.

Keywords: automatic design, learning, fuzzy rules, hybrid, swarm optimization

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Authors: Luís Rocha, Adam Gąska, Enrico Savio, Michael Marxer, Christoph Battaglia

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The changes observed in the last years in the field of manufacturing and production engineering, popularly known as "Fourth Industry Revolution", utilizes the achievements in the different areas of computer sciences, introducing new solutions at almost every stage of the production process, just to mention such concepts as mass customization, cloud computing, knowledge-based engineering, virtual reality, rapid prototyping, or virtual models of measuring systems. To effectively speed up the production process and make it more flexible, it is necessary to tighten the bonds connecting individual stages of the production process and to raise the awareness and knowledge of employees of individual sectors about the nature and specificity of work in other stages. It is important to discover and develop a suitable education method adapted to the specificities of each stage of the production process, becoming an extremely crucial issue to exploit the potential of the fourth industrial revolution properly. Because of it, the project “Train4Dim” (T4D) intends to develop complex training material for digital manufacturing, including content for design, manufacturing, and quality control, with a focus on coordinate metrology and portable measuring systems. In this paper, the authors present an approach to using an active learning methodology for digital manufacturing. T4D main objective is to develop a multi-degree (apprenticeship up to master’s degree studies) and educational approach that can be adapted to different teaching levels. It’s also described the process of creating the underneath methodology. The paper will share the steps to achieve the aims of the project (training model for digital manufacturing): 1) surveying the stakeholders, 2) Defining the learning aims, 3) producing all contents and curriculum, 4) training for tutors, and 5) Pilot courses test and improvements.

Keywords: learning, Industry 4.0, active learning, digital manufacturing

Procedia PDF Downloads 97

Authors: Sobia Rana

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The study intends to explain the problems of English collocational use faced by college students in Rawalpindi, Pakistan and recommends some authentic ways that will help in removing the learning barriers in light of the concerning methodological issues. It will not only help the students to improve their knowledge of the phenomena but will also enlighten the target teachers about the significance of authentic collocational use and how it naturalizes both written and spoken expressions. Data from both the students and teachers have been collected with the help of open/close-ended questionnaires to unearth the genuine cause/s and supplement them with the required solutions rooted in the actual problems. The students fail to use authentic collocations owing to multiple reasons: lack of awareness about English collocational use, improper teaching methodologies, and inexpert teachers.

Keywords: English collocational use, teaching methodologies, English learning barriers, vocabulary acquisition, college students of Rawalpindi

Procedia PDF Downloads 82

Authors: Akeel A. Shah, Tong Zhang

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Computational approaches to learning the properties of materials are commonplace, motivated by the need to screen or design materials for a given application, e.g., semiconductors and energy storage. Experimental approaches can be both time consuming and costly. Unfortunately, computational approaches such as ab-initio electronic structure calculations and classical or ab-initio molecular dynamics are themselves can be too slow for the rapid evaluation of materials, often involving thousands to hundreds of thousands of candidates. Machine learning assisted approaches have been developed to overcome the time limitations of purely physics-based approaches. These approaches, on the other hand, require large volumes of data for training (hundreds of thousands on many standard data sets such as QM7b). This means that they are limited by how quickly such a large data set of physics-based simulations can be established. At high fidelity, such as configuration interaction, composite methods such as G4, and coupled cluster theory, gathering such a large data set can become infeasible, which can compromise the accuracy of the predictions - many applications require high accuracy, for example band structures and energy levels in semiconductor materials and the energetics of charge transfer in energy storage materials. In order to circumvent this problem, multi-fidelity approaches can be adopted, for example the Δ-ML method, which learns a high-fidelity output from a low-fidelity result such as Hartree-Fock or density functional theory (DFT). The general strategy is to learn a map between the low and high fidelity outputs, so that the high-fidelity output is obtained a simple sum of the physics-based low-fidelity and correction, Although this requires a low-fidelity calculation, it typically requires far fewer high-fidelity results to learn the correction map, and furthermore, the low-fidelity result, such as Hartree-Fock or semi-empirical ZINDO, is typically quick to obtain, For high-fidelity outputs the result can be an order of magnitude or more in speed up. In this work, a new multi-fidelity approach is developed, based on a graph convolutional network (GCN) combined with semi-supervised learning. The GCN allows for the material or molecule to be represented as a graph, which is known to improve accuracy, for example SchNet and MEGNET. The graph incorporates information regarding the numbers of, types and properties of atoms; the types of bonds; and bond angles. They key to the accuracy in multi-fidelity methods, however, is the incorporation of low-fidelity output to learn the high-fidelity equivalent, in this case by learning their difference. Semi-supervised learning is employed to allow for different numbers of low and high-fidelity training points, by using an additional GCN-based low-fidelity map to predict high fidelity outputs. It is shown on 4 different data sets that a significant (at least one order of magnitude) increase in accuracy is obtained, using one to two orders of magnitude fewer low and high fidelity training points. One of the data sets is developed in this work, pertaining to 1000 simulations of quinone molecules (up to 24 atoms) at 5 different levels of fidelity, furnishing the energy, dipole moment and HOMO/LUMO.

Keywords: .materials screening, computational materials, machine learning, multi-fidelity, graph convolutional network, semi-supervised learning

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Authors: Mst Shapna Akter, Hossain Shahriar

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Neural network approaches are machine learning methods used in many domains, such as healthcare and cyber security. Neural networks are mostly known for dealing with image datasets. While training with the images, several fundamental mathematical operations are carried out in the Neural Network. The operation includes a number of algebraic and mathematical functions, including derivative, convolution, and matrix inversion and transposition. Such operations require higher processing power than is typically needed for computer usage. Central Processing Unit (CPU) is not appropriate for a large image size of the dataset as it is built with serial processing. While Graphics Processing Unit (GPU) has parallel processing capabilities and, therefore, has higher speed. This paper uses advanced Neural Network techniques such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST-VGG16, and our proposed models to compare CPU and GPU resources. A system for classifying autism disease using face images of an autistic and non-autistic child was used to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It has been observed that GPU runs faster than the CPU in all tests performed. Moreover, the performance of the Neural Network models in terms of accuracy increases on GPU compared to CPU.

Keywords: autism disease, neural network, CPU, GPU, transfer learning

Procedia PDF Downloads 118

Authors: Marta Merkl

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The ongoing project what the paper will present is about how the author introduces chefs to the history of art through a selected piece of art. The author is originally an art historian, but since 2019 she has been working on her PhD research topic related to designing dining experiences in the restaurant context, including the role of sensory experiences and storytelling. Due to a scholarship, she can participate in the re-design of a fine dining restaurant called Onyx in Budapest, which was awarded two Michelin stars before the pandemic caused by COVID-19. The management of the restaurant wants to broaden the chefs' horizons and develop their creativity by introducing them to each chapter of the visual arts. There is a kind of polyphony in the mass of information about what should a chef, a food designer, or anybody who make food in everyday basis use as a source of inspiration for inventing and preparing new dishes: nostalgia, raw material, cookbooks, etc. In today's world of fine dining, nature is the main inspiration for outstanding achievements, as exemplified by the Slovenian restaurant Hiša Franko** and its chef Ana Roš. The starting point for the project and the research was the idea of using art history as an inspiration for gastronomy. The research relies on data collection via interviews, ethnography, and autoethnography. In this case, the reflective introspection of the researcher is also relevant because the researcher is an important part of the process (GOULD, 1995). The paper overviews the findings of the autoethnography literature relevant to our topic. In the literature review, it will be also pointed out that sustainability, eating as an experience, and the world of art can be linked. As ERDMANN and co-authors (1999) argues that the health dimension of sustainability has a component called 'joy of eating,' which implies strong ties to the experiential nature of eating. Therefore, it is worth to compare with PINE and GILMORE's (1998) theory of experience economy and with CSÍKSZENTMIHÁLYI's (1999) concept of flow, which give examples of gastronomy and art. The aim of the research is to map experiences of the pilot project, the discourse between the art world and the gastronomy actors. Another noteworthy aspect is whether the chefs are willing to use art history as an inspiration.

Keywords: art history, autoethnography, chef, education, experience, food preparation, inspiration, sustainability

Procedia PDF Downloads 143

Authors: Ehsan Yadegari

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While there are several metaheuristics and exact approaches to solving the Supply Chain Network Design (SCND) problem, there still remains an unfilled gap in using the Teaching-Learning-Based Optimization (TLBO) algorithm. The algorithm has demonstrated desirable results with problems with complicated combinational optimization. The present study introduces a Discrete Self-Study TLBO (DSS-TLBO) with priority-based solution representation that can solve a supply chain network configuration model to lower the total expenses of establishing facilities and the flow of materials. The network features four layers, namely suppliers, plants, distribution centers (DCs), and customer zones. It is designed to meet the customer’s demand through transporting the material between layers of network and providing facilities in the best economic Potential locations. To have a higher quality of the solution and increase the speed of TLBO, a distinct operator was introduced that ensures self-adaptation (self-study) in the algorithm based on the four types of local search. In addition, while TLBO is used in continuous solution representation and priority-based solution representation is discrete, a few modifications were added to the algorithm to remove the solutions that are infeasible. As shown by the results of experiments, the superiority of DSS-TLBO compared to pure TLBO, genetic algorithm (GA) and firefly Algorithm (FA) was established.

Keywords: supply chain network design, teaching–learning-based optimization, improved metaheuristics, discrete solution representation

Procedia PDF Downloads 52

Authors: M. Tomaschko

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The integration of technology in educational settings has gained a lot of interest. Especially the use of mobile devices and accompanying mobile applications can offer great potentials to complement traditional education with new technologies and enrich students’ learning in various ways. Nevertheless, the usability of the deployed mathematics application is an indicative factor to exploit the full potential of technology enhanced learning because directing cognitive load toward using an application will likely inhibit effective learning. For this reason, the purpose of this research study is the identification of possible usability issues of the mobile GeoGebra Graphing Calculator application. Therefore, eye tracking in combination with task scenarios, think aloud method, and a SUS questionnaire were used. Based on the revealed usability issues, the mobile application was iteratively redesigned and assessed in order to verify the success of the usability improvements. In this paper, the identified usability issues are presented, and recommendations on how to overcome these concerns are provided. The main findings relate to the conception of a mathematics keyboard and the interaction design in relation to an equation editor, as well as the representation of geometrical construction tools. In total, 12 recommendations were formed to improve the usability of a mobile graphing calculator application. The benefit to be gained from this research study is not only the improvement of the usability of the existing GeoGebra Graphing Calculator application but also to provide helpful hints that could be considered from designers and developers of mobile math applications.

Keywords: GeoGebra, graphing calculator, math education, smartphone, usability

Procedia PDF Downloads 134

Authors: Tessa Verhallen, Mama Africa

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By co-constructing personal narratives of sex workers in Namibia this paper represents how sex workers experience their violation of rights in Namibia. It is written from an emic (as an advisor for a sex worker-led organization named Rights not Rescue Trust) and an etic (as an ethnographer) point of view, in collaboration with the staff of the organization Rights not Rescue Trust. This organization represents circa 3000 members. The paper describes the current deplorable situation of sex workers in Namibia, encompassing the stigma and discrimination they face, their struggle to have their work decriminalized and their urge to advocate for human rights and the end of violations. Based on a triangular research design (ethnography, narratives, literature study, human rights’ training and counseling sessions) the authors show that sex workers, particularly LGBTI sex workers, are extremely vulnerable to emotional, physical, and sexual violence in Namibia. The main perpetrators of violence turn out to be not only clients and intimate partners but also law enforcement officers and health care workers who are supposed to protect and support sex workers. The sex workers’ narratives voice their disgraceful circumstances regarding how their rights are violated. It also highlights their importance to fight for their rights and access to health care, legal services and education in order to improve the sexual reproductive health of sex workers.

Keywords: HIV/aids, LGBTI, methodological innovative, sex work

Procedia PDF Downloads 312

Authors: Monika Ksiezopolska-Gocalska, Pawel Albrycht, Robert Holyst

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Surface Enhanced Raman Spectroscopy (SERS) is a technique used to analyze very low concentrations of substances in solutions, even in aqueous solutions - which is its advantage over IR. This technique can be used in the pharmacy (to check the purity of products); forensics (whether at a crime scene there were any illegal substances); or medicine (serving as a medical test) and lots more. Due to the high potential of this technique, its increasing popularity in analytical laboratories, and simultaneously - the absence of appropriate platforms enhancing the SERS signal (crucial to observe the Raman effect at low analyte concentration in solutions (1 ppm)), we decided to invent our own SERS platforms. As an enhancing layer, we have chosen gold and silver nanoparticles, because these two have the best SERS properties, and each has an affinity for the other kind of particles, which increases the range of research capabilities. The next step was to commercialize them, which resulted in the creation of the company ‘SERSitive.eu’ focusing on production of highly sensitive (Ef = 10⁵ – 10⁶), homogeneous and reproducible (70 - 80%) substrates. SERStive SERS substrates are made using the electrodeposition of silver or silver-gold nanoparticles technique. Thanks to a very detailed analysis of data based on studies optimizing such parameters as deposition time, temperature of the reaction solution, applied potential, used reducer, or reagent concentrations using a standardized compound - p-mercaptobenzoic acid (PMBA) at a concentration of 10⁻⁶ M, we have developed a high-performance process for depositing precious metal nanoparticles on the surface of ITO glass. In order to check a quality of the SERSitive platforms, we examined the wide range of the chemical compounds and the biological substances. Apart from analytes that have great affinity to the metal surfaces (e.g. PMBA) we obtained very good results for those fitting less the SERS measurements. Successfully we received intensive, and what’s more important - very repetitive spectra for; amino acids (phenyloalanine, 10⁻³ M), drugs (amphetamine, 10⁻⁴ M), designer drugs (cathinone derivatives, 10⁻³ M), medicines and ending with bacteria (Listeria, Salmonella, Escherichia coli) and fungi.

Keywords: nanoparticles, Raman spectroscopy, SERS, SERS applications, SERS substrates, SERSitive

Procedia PDF Downloads 151

Authors: Shogo Nagano, Yusuke Tanigaki, Hirokazu Fukuda

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Vegetables harvested early in the morning or late in the afternoon are valued in plant production, and so the time of harvest is important. The biological functions known as circadian clocks have a significant effect on this harvest timing. The purpose of this study was to non-destructively estimate the circadian clock and so construct a method for determining a suitable harvest time. We took eight samples of green busil (Perilla frutescens var. crispa) every 4 hours, six times for 1 day and analyzed all samples at the same time. A hyperspectral camera was used to collect spectrum intensities at 141 different wavelengths (350–1050 nm). Calculation of correlations between spectrum intensity of each wavelength and harvest time suggested the suitability of the hyperspectral camera for non-destructive estimation. However, even the highest correlated wavelength had a weak correlation, so we used machine learning to raise the accuracy of estimation and constructed a machine learning model to estimate the internal time of the circadian clock. Artificial neural networks (ANN) were used for machine learning because this is an effective analysis method for large amounts of data. Using the estimation model resulted in an error between estimated and real times of 3 min. The estimations were made in less than 2 hours. Thus, we successfully demonstrated this method of non-destructively estimating internal time.

Keywords: artificial neural network (ANN), circadian clock, green busil, hyperspectral camera, non-destructive evaluation

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Authors: M. A. Zaki Ewiss, S. Afifi

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Nahda University (NUB) believes that internationalisation of higher educational is able to provide global society with an education that meets current needs and that can respond efficiently to contemporary demands and challenges, which are characterized by globalisation, interdependence, and multiculturalism. In this paper, we will discuss the the challenges of the Egyptian Higher Education system and the future vision to improve this system> In this report, the following issues will be considered: Increasing knowledge on the development of specialized programs of study at the university. Developing international cooperation programs, which focus on the development of the students and staff skills, and providing academic culture and learning opportunities. Increasing the opportunities for student mobility, and research projects for faculty members. Increased opportunities for staff, faculty and students to continue to learn foreign universities, and to benefit from scholarships in various disciplines. Taking the advantage of the educational experience and modern teaching methods; Providing the opportunities to study abroad without increasing the period of time required for graduation, and through greater integration in the curricula and programs; More cultural interaction through student exchanges.Improving and providing job opportunities for graduates through participation in the global labor market. This document sets out NUB strategy to move towards that vision. We are confident that greater explicit differentiation, greater freedom and greater collaboration are the keys to delivering the further improvement in quality we shall need to retain and strengthen our position as one of the world’s leading higher education systems.

Keywords: technology transfer higher education, knowledge transfer, internationalisation, mobility

Procedia PDF Downloads 439

Authors: Se-Hwa Park, En-Kyung Han, Jae-Young Lim, Hye-Jung Ahn

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Purpose: The objective of this study is to provide basic data for understanding the substance of inpatient life with CRPS (Complex Regional Pain Syndrome) and developing efficient and effective nursing intervention. Methods: From September 2018 to November, we have interviewed 10 CRPS patients about inpatient experiences. To understand the implication of inpatient life experiences with CRPS and intrinsic structure, we have used the question: 'How about the inpatient experiences with CRPS'. For data analysis, the method suggested by Colaizzi was applied as a phenomenological method. Results: According to the analysis, the study participants' inpatient life process was structured in six categories: (a) breakthrough pain experience (b) the limitation of pain treatment, (c) worsen factors of pain during inpatient period, (d) treat method for pain, (e) positive experience for inpatient period, (f) requirements for medical team, family and people in hospital room. Conclusion: Inpatient with CRPS have experienced the breakthrough pain. They had expected immediate treatment for breakthrough pain, but they experienced severe pain because immediate treatment was not implemented. Pain-worsening factors which patients with CRPS are as follows: personal factors from negative emotions such as insomnia, stress, sensitive character, pain part touch or vibration stimulus on the bed, physical factors from high threshold or rapid speed during fast transfer, conflict with other people, climate factors such as humidity or low temperature, noise, smell, lack of space because of many visitors. Patients actively manage the pain committing into another tasks or diversion. And also, patients passively manage the pain, just suppress, give-up. They think positively about rehabilitation treatment. And they require the understanding and sympathy for other people, and emotional support, immediate intervention for medical team. Based on the results of this study, we suppose the guideline of systematic breakthrough pain management for the relaxation of sudden pain, using notice of informing caution for touch or vibration. And we need to develop non-medicine pain management nursing intervention.

Keywords: breakthrough pain, CRPS, complex regional pain syndrome, inpatient life experiences, phenomenological method

Procedia PDF Downloads 129

Authors: Soowon Park, Min-Ji Kim, Jun-Young Lee

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Motivation: The stigma of mental illness has been studied in many disciplines, including social psychology, counseling psychology, sociology, psychiatry, public health care, and related areas, because individuals labeled as ‘mentally ill’ are often deprived of their rights and their life opportunities. To understand the factors that deepen the stigma of mental illness, it is important to understand the influencing factors of the stigma. Problem statement: Depression is a common disorder in adults, but the incidence of help-seeking is low. Researchers have believed that this poor help-seeking behavior is related to the stigma of mental illness, which results from low mental health literacy. However, it is uncertain that increasing mental health literacy decreases mental health stigmatization. Furthermore, even though decreasing stigmatization is important, the stigma of mental illness is still a stable and long-lasting phenomenon. Thus, factors other than knowledge about mental disorders have the power to maintain the stigma. Investigating the influencing factors that facilitate the stigma of psychiatric disease could help lower the social stigmatization. Approach: Face-to-face interviews were conducted with a multi-clustering sample. A total of 700 Korean participants (38% male), ranging in age from 18 to 78 (M(SD)age= 48.5(15.7)) answered demographical questions, Korean version of Link’s Perceived Devaluation and Discrimination (PDD) scale for the assessment of social stigmatization against depression, and the Korean version of the WHO-Composite International Diagnostic Interview for the assessment of mental disorders. Multiple-regression was conducted to find the predicting factors of social stigmatization against depression. Ages, sex, years of education, income, living location, and experience of mental illness were used as the predictors. Results: Predictors accounted for 14% of the variance in the stigma of depressive disorders (F(6, 693) = 20.27, p < .001). Among those, only age, years of education, and experience of mental illness significantly predicted social stigmatization against depression. The standardized regression coefficient of age had a negative association with stigmatization (β = -.20, p < .001), but years of education (β = .20, p < .001) and experience of mental illness (β = .08, p < .05) positively predicted depression stigmatization. Conclusions: The present study clearly demonstrates the association between personal factors and depressive disorder stigmatization. Younger age, more education, and self-stigma appeared to increase the stigmatization. Young, highly educated, and mentally ill people tend to reject patients with depressive disorder as friends, teachers, or babysitters; they also tend to think that those patients have lower intelligence and abilities. These results suggest the possibility that people from a high social class, or highly educated people, who have the power to make decisions, help maintain the social stigma against mental illness patients. To increase the awareness that people from high social classes have more stigmatization against depressive disorders will help decrease the biased attitudes against mentally ill patients.

Keywords: depressive disorder stigmatization, age, education, self-stigma

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Authors: Jane E. Hill

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Quality of life is an important component for many. With that in mind, everyone will experience some type of loss within his or her lifetime. A person can experience loss due to break up, separation, divorce, estrangement, or death. An individual may experience loss of a job, loss of capacity, or loss caused by human or natural-caused disasters. An individual’s response to such a loss is unique to them, and not everyone will seek services to assist them with their grief due to loss. Counseling can promote positive outcomes for clients that are grieving by addressing the client’s personal loss and helping the client process their grief. However, a lack of understanding on the part of counselors of how people grieve may result in negative client outcomes such as poor health, psychological distress, or an increased risk of depression. Education and training in grief counseling can improve counselors’ problem recognition and skills in treatment planning. The purpose of this study was to examine whether the Council for Accreditation of Counseling and Related Educational Programs (CACREP) master’s degree counseling students view themselves as having been adequately trained in grief theories and skills. Many people deal with grief issues that prevent them from having joy or purpose in their lives and that leaves them unable to engage in positive opportunities or relationships. This study examined CACREP-accredited master’s counseling students’ self-reported competency, training, and education in providing grief counseling. The implications for positive social change arising from the research may be to incorporate and promote education and training in grief theories and skills in a majority of counseling programs and to provide motivation to incorporate professional standards for grief training and practice in the mental health counseling field. The theoretical foundation used was modern grief theory based on John Bowlby’s work on Attachment Theory. The overall research question was how competent do master’s-level counselors view themselves regarding the education or training they received in grief theories or counseling skills in their CACREP-accredited studies. The author used a non-experimental, one shot survey comparative quantitative research design. Cicchetti’s Grief Counseling Competency Scale (GCCS) was administered to CACREP master’s-level counseling students enrolled in their practicum or internship experience, which resulted in 153 participants. Using a MANCOVA, there was significance found for relationships between coursework taken and (a) perceived assessment skills (p = .029), (b) perceived treatment skills (p = .025), and (c) perceived conceptual skills and knowledge (p = .003). Results of this study provided insight for CACREP master’s-level counseling programs to explore and discuss curriculum coursework inclusion of education and training in grief theories and skills.

Keywords: counselor education and training, grief education and training, grief and loss, quality of life

Procedia PDF Downloads 191

Authors: Omid Pourabdollah, Mohsen Misaghian

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Overtopping is known as one the most important reasons for the failure of earth dams. In some cases, it has resulted in heavy damages and losses. Therefore, enhancing the safety of earth dams against overtopping has received much attention in the past four decades. In this paper, at first, the overtopping phenomena and its destructive consequences will be introduced. Then, overtopping failure mechanism of embankments will be described. Finally, different types of protection systems for stabilization of earth dams against overtopping will be presented. These include timber cribs, riprap and gabions, reinforced earth, roller compacted concrete, and the precast concrete blocks.

Keywords: embankment dam, overtopping, roller compacted concrete, wedge concrete block

Procedia PDF Downloads 161

Authors: Goldie Lynn Diaz, Ma. Teresa Tricia G. Bautista, Elisabeth Engeljakob, Mary Glaze Rosal

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Introduction: Residents are expected to convey unfavorable news, discuss prognoses, and relieve suffering, and address do-not-resuscitate orders, yet some report a lack of competence in providing this type of care. Recognizing this need, Family Medicine residency programs are incorporating end-of-life care from symptom and pain control, counseling, and humanistic qualities as core proficiencies in training. Objective: This study determined the competency of Family Medicine Residents from various institutions in Metro Manila on rendering care for the dying. Materials and Methods: Trainees completed a Palliative Care Evaluation tool to assess their degree of confidence in patient and family interactions, patient management, and attitudes towards hospice care. Results: Remarkably, only a small fraction of participants were confident in performing independent management of terminal delirium and dyspnea. Fewer than 30% of residents can do the following without supervision: discuss medication effects and patient wishes after death, coping with pain, vomiting and constipation, and reacting to limited patient decision-making capacity. Half of the respondents had confidence in supporting the patient or family member when they become upset. Majority expressed confidence in many end-of-life care skills if supervision, coaching and consultation will be provided. Most trainees believed that pain medication should be given as needed to terminally ill patients. There was also uncertainty as to the most appropriate person to make end-of-life decisions. These attitudes may be influenced by personal beliefs rooted in cultural upbringing as well as by personal experiences with death in the family, which may also affect their participation and confidence in caring for the dying. Conclusion: Enhancing the quality and quantity of end-of-life care experiences during residency with sufficient supervision and role modeling may lead to knowledge and skill improvement to ensure quality of care. Fostering bedside learning opportunities during residency is an appropriate venue for teaching interventions in end-of-life care education.

Keywords: end of life care, geriatrics, palliative care, residency training skill

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Authors: Jazim Sohail, Filipe Teixeira-Dias

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Mild traumatic brain injury (mTBI) within non-helmeted contact sports is a growing concern due to the serious risk of potential injury. Extensive research is being conducted looking into head kinematics in non-helmeted contact sports utilizing instrumented mouthguards that allow researchers to record accelerations and velocities of the head during and after an impact. This does not, however, allow the location of the impact on the head, and its magnitude and orientation, to be determined. This research proposes and validates two methods to quantify impact locations from instrumented mouthguard kinematic data, one using rigid body dynamics, the other utilizing machine learning. The rigid body dynamics technique focuses on establishing and matching moments from Euler’s and torque equations in order to find the impact location on the head. The methodology is validated with impact data collected from a lab test with the dummy head fitted with an instrumented mouthguard. Additionally, a Hybrid III Dummy head finite element model was utilized to create synthetic kinematic data sets for impacts from varying locations to validate the impact location algorithm. The algorithm calculates accurate impact locations; however, it will require preprocessing of live data, which is currently being done by cross-referencing data timestamps to video footage. The machine learning technique focuses on eliminating the preprocessing aspect by establishing trends within time-series signals from instrumented mouthguards to determine the impact location on the head. An unsupervised learning technique is used to cluster together impacts within similar regions from an entire time-series signal. The kinematic signals established from mouthguards are converted to the frequency domain before using a clustering algorithm to cluster together similar signals within a time series that may span the length of a game. Impacts are clustered within predetermined location bins. The same Hybrid III Dummy finite element model is used to create impacts that closely replicate on-field impacts in order to create synthetic time-series datasets consisting of impacts in varying locations. These time-series data sets are used to validate the machine learning technique. The rigid body dynamics technique provides a good method to establish accurate impact location of impact signals that have already been labeled as true impacts and filtered out of the entire time series. However, the machine learning technique provides a method that can be implemented with long time series signal data but will provide impact location within predetermined regions on the head. Additionally, the machine learning technique can be used to eliminate false impacts captured by sensors saving additional time for data scientists using instrumented mouthguard kinematic data as validating true impacts with video footage would not be required.

Keywords: head impacts, impact location, instrumented mouthguard, machine learning, mTBI

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Authors: Ricardo Merlo

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In this paper, we analyzed the different didactic proposals for teaching about the free fall motion of bodies available online. An important aspect was the interpretation of the direction and sense of the acceleration of gravity and of the falling velocity of a body, which is why we found different applications of the Cartesian reference system used and also different graphical presentations of the velocity as a function of time and of the distance traveled vertically by the body in the period of time that it was dropped from a height h0. In this framework, a survey of previous concepts was applied to a voluntary group of first-year university students of an Engineering degree before and after the development of the class of the subject in question. Then, Hake's index (0.52) was determined, which resulted in an average learning gain from the meaningful use of the reference system and the respective graphs of v=ƒ (t) and h=ƒ (t).

Keywords: didactic gain, free–fall, physics teaching, previous knowledge

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Authors: Luedech Girdwichai, Witthaya Mekhum

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This research analyses the factors affecting the success and develops a guideline for self- reliance planning of the entrepreneurs for effective implementation. Samples in this study included 42 awarded winners from the 2nd Sufficiency Economics Philosophy (SEP) National Contest arranged by Office of the Royal Development Projects Board. The results revealed 4 main factors affecting the success as follows: 1) there is a need to encourage unity and cooperation in the enterprise in conducting development plan. 2) The entrepreneur must be a knowledge seeker and lead by example on SEP life. 3) The entrepreneur must be able to apply traditional local wisdom with his present experience and knowledge in defining product identity. 4) The entrepreneur should provide career training for the staffs to develop their competencies. The guideline for self-reliance planning consisted of 4 aspects: 1) Human resource development: the enterprise should develop its staffs especially on integrity, honesty, and public minded. 2) Local community development: there should be a clear target for the local community development. 3) Local community economic development: by encouraging additional incomes through experience sharing. 4) Enterprise development planning: by arranging monthly meeting to conduct the development plan including analysing problems and synthesizing data.

Keywords: potential development, SME entrepreneurs, sufficiency economics philosophy, finance, management

Procedia PDF Downloads 345

Authors: Kim Hyekyoung, Au Yunkyung

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As media plays an increasingly important role in our lives, the age at which media usage begins is getting younger worldwide. Particularly, young children are exposed to media at an early age, making early childhood media literacy education an essential task. However, most existing early childhood media literacy education programs focus solely on teaching children how to use media, and practical implementation and application are challenging. Therefore, this study aims to develop a play-based early childhood media literacy education program utilizing topic-based media content and explore the potential application and impact of this program on young children's media literacy learning. Based on theoretical and literature review on media literacy education, analysis of existing educational programs, and a survey on the current status and teacher perceptions of media literacy education for preschool children, this study developed a media literacy education program for preschool children, considering the components of media literacy (understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, and social communication). To verify the effectiveness of the program, 20 preschool children aged 5 from C City M Kindergarten were chosen as participants, and the program was implemented from March 28th to July 4th, 2022, once a week for a total of 7 sessions. The program was developed based on Gallenstain's (2003) iterative learning model (participation-exploration-explanation-extension-evaluation). To explore the quantitative changes before and after the program, a repeated measures analysis of variance was conducted, and qualitative analysis was employed to examine the observed process changes. It was found that after the application of the education program, media literacy levels such as understanding media characteristics, self-regulation, self-expression, critical understanding, ethical norms, and social communication significantly improved. The recursive learning-based early childhood media literacy education program developed in this study can be effectively applied to young children's media literacy education and help enhance their media literacy levels. In terms of observed process changes, it was confirmed that children learned about various topics, expressed their thoughts, and improved their ability to communicate with others using media content. These findings emphasize the importance of developing and implementing media literacy education programs and can contribute to empowering young children to safely and effectively utilize media in their media environment. The results of this study, exploring the potential application and impact of the recursive learning-based early childhood media literacy education program on young children's media literacy learning, demonstrated positive changes in young children's media literacy levels. These results go beyond teaching children how to use media and can help foster their ability to safely and effectively utilize media in their media environment. Additionally, to enhance young children's media literacy levels and create a safe media environment, diverse content and methodologies are needed, and the continuous development and evaluation of education programs should be conducted.

Keywords: young children, media literacy, recursive learning, education program

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Authors: Secil Kaya Gulen

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Face to face and virtual classrooms that came up with different conditions and environments, but similar purposes have different characteristics. Although virtual classrooms have some similar facilities with face-to-face classes such as program, students, and administrators, they have no walls and corridors. Therefore, students can attend the courses from a distance and can control their own learning spaces. Virtual classrooms defined as simultaneous online environments where students in different places come together at the same time with the guidance of a teacher. Distance education and virtual classes require different intellectual and managerial skills and models. Therefore, for effective use of virtual classrooms, the virtual property should be taken into consideration. One of the most important factors that affect the spread and effective use of the virtual classrooms is the perceptions and opinions of students -as one the main participants-. Student opinions and recommendations are important in terms of providing information about the fulfillment of expectation. This will help to improve the applications and contribute to the more efficient implementations. In this context, ideas and perceptions of the students related to the virtual classrooms, in general, were determined in this study. Advantages and disadvantages of virtual classrooms expected contributions to the educational system and expected characteristics of virtual classrooms have examined in this study. Students of an online distance education graduate program in which all the courses offered by virtual classrooms have asked for their opinions. Online Distance Education Graduate Program has totally 19 students. The questionnaire that consists of open-ended and multiple choice questions sent to these 19 students and finally 12 of them answered the questionnaire. Analysis of the data presented as frequencies and percentages for each item. SPSS for multiple-choice questions and Nvivo for open-ended questions were used for analyses. According to the results obtained by the analysis, participants stated that they did not get any training on virtual classes before the courses; but they emphasize that newly enrolled students should be educated about the virtual classrooms. In addition, all participants mentioned that virtual classroom contribute their personal development and they want to improve their skills by gaining more experience. The participants, who mainly emphasize the advantages of virtual classrooms, express that the dissemination of virtual classrooms will contribute to the Turkish Education System. Within the advantages of virtual classrooms, ‘recordable and repeatable lessons’ and ‘eliminating the access and transportation costs’ are most common advantages according to the participants. On the other hand, they mentioned ‘technological features and keyboard usage skills affect the attendance’ is the most common disadvantage. Participants' most obvious problem during virtual lectures is ‘lack of technical support’. Finally ‘easy to use’, ‘support possibilities’, ‘communication level’ and ‘flexibility’ come to the forefront in the scope of expected features of virtual classrooms. Last of all, students' opinions about the virtual classrooms seems to be generally positive. Designing and managing virtual classrooms according to the prioritized features will increase the students’ satisfaction and will contribute to improve applications that are more effective.

Keywords: distance education, virtual classrooms, higher education, e-learning

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Authors: Diego Santibañez Oyarce, Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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The advent of high-throughput sequencing technologies has revolutionized genomics, generating vast amounts of genetic data that challenge traditional bioinformatics methods. Machine learning addresses these challenges by leveraging computational power to identify patterns and extract information from large datasets. However, biological sequence data, being symbolic and non-numeric, must be converted into numerical formats for machine learning algorithms to process effectively. So far, some encoding methods, such as one-hot encoding or k-mers, have been explored. This work proposes additional approaches for encoding DNA sequences in order to compare them with existing techniques and determine if they can provide improvements or if current methods offer superior results. Data from the 16S rRNA gene, a universal marker, was used to analyze eight bacterial groups that are significant in the pulmonary environment and have clinical implications. The bacterial genes included in this analysis are Prevotella, Abiotrophia, Acidovorax, Streptococcus, Neisseria, Veillonella, Mycobacterium, and Megasphaera. These data were downloaded from the NCBI database in Genbank file format, followed by a syntactic analysis to selectively extract relevant information from each file. For data encoding, a sequence normalization process was carried out as the first step. From approximately 22,000 initial data points, a subset was generated for testing purposes. Specifically, 55 sequences from each bacterial group met the length criteria, resulting in an initial sample of approximately 440 sequences. The sequences were encoded using different methods, including one-hot encoding, k-mers, Fourier transform, and Wavelet transform. Various machine learning algorithms, such as support vector machines, random forests, and neural networks, were trained to evaluate these encoding methods. The performance of these models was assessed using multiple metrics, including the confusion matrix, ROC curve, and F1 Score, providing a comprehensive evaluation of their classification capabilities. The results show that accuracies between encoding methods vary by up to approximately 15%, with the Fourier transform obtaining the best results for the evaluated machine learning algorithms. These findings, supported by the detailed analysis using the confusion matrix, ROC curve, and F1 Score, provide valuable insights into the effectiveness of different encoding methods and machine learning algorithms for genomic data analysis, potentially improving the accuracy and efficiency of bacterial classification and related genomic studies.

Keywords: DNA encoding, machine learning, Fourier transform, Fourier transformation

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Authors: Nora Arbaoui, Rachid Tadili

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The substantial increase of areas cultivated under glasshouses compels the use of other natural heating and cooling procedures to make a profit as well as avoid both exorbitant fuel consumption and CO₂ emissions. This experimental study is designed to examine the functioning of a solar heating system that will increase positive consequences in terms of both quantity and quality while successfully enhancing greenhouse microclimate during wintertime. Those configurations have been tested in a miniaturized greenhouse simply after having optimized the operating parameters. These were noteworthy results when compared to an unheated witness greenhouse.

Keywords: solar system, agricultural greenhouse, heating, cooling, storage, drying

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Authors: Maryam Zarra-Nezhad, Ali Moazami-Goodarzi, Joona Muotka, Nina Sajaniemi

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This study examines the extent to which the impact of a universal intervention program, i.e., POMPedaSens, on children’s early social-emotional learning (SEL) is different depending on early childhood education (ECE) teaches stress at work. The POMPedaSens program aims to promote children’s (5–6-year-olds) SEL by supporting ECE teachers’ engagement and emotional availability. The intervention effectiveness has been monitored using an 8-month randomized controlled trial design with an intervention (IG; 26 teachers and 195 children) and a waiting control group (CG; 36 teachers and 198 children) that provided the data before and after the program implementation. The ECE teachers in the IG are trained to implement the intervention program in their early childhood education and care groups. Latent change score analysis suggests that the program increases children’s prosocial behavior in the IG when teachers show a low level of stress. No significant results were found for the IG regarding a change in antisocial behavior. However, when teachers showed a high level of stress, an increase in prosocial behavior and a decrease in antisocial behavior were only found for children in the CG. The results suggest a promising application of the POMPedaSens program for promoting prosocial behavior in early childhood when teachers have low stress. The intervention will likely need a longer time to display the moderating effect of ECE teachers’ well-being on children’s antisocial behavior change.

Keywords: early childhood, social-emotional learning, universal intervention program, professional development, teachers' stress

Procedia PDF Downloads 89

Authors: Qiaohui Zhong, Yiqi Kuang, Wanxun Cai, Libin Huang

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As a community public facility, the popularity and perfection of old clothes recycling products directly affect people's impression of the whole city, which is related to the happiness index of residents' lives and is of great significance to the construction of eco-civilized cities and the realization of sustainable urban development. At present, China's waste clothing is characterized by large production and a high utilization rate, but the current rate of old clothes recycling is low, and the ‘one-size-fits-all’ recycling model makes people's motivation for old clothes recycling low, and old clothes recycling is in a dilemma. Based on the two online and offline recycling modes of old clothes recycling in Chinese communities, this paper conducts an in-depth survey on the public, operators, and regulators from the aspects of activity scene analysis, crowd attributes analysis, and community space analysis summarizes the difficulties of old clothes recycling for the public - nowhere to recycle, inconvenient to recycle and unwilling to recycle, and analyzes the factors that lead to these difficulties, and gives a solution with foreign experience to solve these problems. It also analyzes the factors that lead to these difficulties and gives targeted suggestions in combination with foreign experience, exploring and proposing a set of appropriate modern old-clothes recycling modes.

Keywords: community, old clothes recycling, recycling mode, sustainable urban development

Procedia PDF Downloads 46