Search results for: content- and task-based learning

Authors: Jinwooung Kim, Jae-Hwan Jung, Seong-Jun Kim, Sung-Ah Kim

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Because the building envelope has a significant impact on the operation and maintenance stage of the building, designing the facade considering the performance can improve the performance of the building and lower the maintenance cost of the building. In general, however, optimizing two or more performance factors confronts the limits of time and computational tools. The optimization phase typically repeats infinitely until a series of processes that generate alternatives and analyze the generated alternatives achieve the desired performance. In particular, as complex geometry or precision increases, computational resources and time are prohibitive to find the required performance, so an optimization methodology is needed to deal with this. Instead of directly analyzing all the alternatives in the optimization process, applying experimental techniques (heuristic method) learned through experimentation and experience can reduce resource waste. This study proposes and verifies a method to optimize the double envelope of a building composed of a perforated panel using machine learning to the design geometry and quantitative performance. The proposed method is to achieve the required performance with fewer resources by supplementing the existing method which cannot calculate the complex shape of the perforated panel.

Keywords: building envelope, machine learning, perforated metal, multi-factor optimization, façade

Procedia PDF Downloads 224

Authors: Nurhayati Br Tarigan, Rizkita Rachmi Esyanti

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Stevia (Stevia rebaudiana Bertoni) has a great potential to be used as a natural sweetener because it contains steviol glycoside, which is approximately 100 - 300 times sweeter than sucrose, yet low calories. Vegetative and generative propagation of S. rebaudiana is inefficient to produce stevia biomass and stevioside. One of alternative for stevia propagation is in vitro shoot culture. This research was conducted to optimize the best medium for shoot growth and to compare the bioconversion efficiency and stevioside production of S. rebaudiana shoot culture cultivated in thin layer culture (TLC), recipient for automated temporary immersion system (TIS RITA®) bioreactor, and bubble column bioreactor. The result showed that 1 ppm of Kinetin produced a healthy shoot and the highest number of leaves compared to BAP. Shoots were then cultivated in TLC, TIS RITA® bioreactor, and bubble column bioreactor. Growth medium efficiency was determined by yield and productivity. TLC produced the highest growth medium efficiency of S. rebaudiana, the yield was 0.471 ± 0.117 gbiomass.gsubstrate-1, and the productivity was 0.599 ± 0.122 gbiomass.Lmedium-1.day-1. While TIS RITA® bioreactor produced the lowest yield and productivity, 0.182 ± 0.024 gbiomass.gsubstrate-1 and 0.041 ± 0.0002 gbiomass.Lmedium-1.day-1 respectively. The yield of bubble column bioreactor was 0.354 ± 0.204 gbiomass.gsubstrate-1 and the productivity was 0,099 ± 0,009 gbiomass.Lmedium-1.day-1. The stevioside content from the highest to the lowest was obtained from stevia shoot which was cultivated on TLC, TIS RITA® bioreactor, and bubble column bioreactor; the content was 93,44 μg/g, 42,57 μg/g, and 23,03 μg/g respectively. All three systems could be used to produce stevia shoot biomass, but optimization on the number of nutrition and oxygen intake was required in each system.

Keywords: bubble column, growth medium efficiency, Stevia rebaudiana, stevioside, TIS RITA®, TLC

Procedia PDF Downloads 267

Authors: Lulu Liao, Huijing Chen, Yinan Zhao, Hongting Ning, Hui Feng

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Urinary tract infection rate is an important index of care quality in nursing homes. The aim of the study is to understand the nursing assistant's current knowledge and attitudes of urinary incontinence and to explore related stakeholders' viewpoint about urinary incontinence training. This explanatory sequential study used Knowledge, Practice, and Attitude Model (KAP) and Adult Learning Theories, as the conceptual framework. The researchers collected data from 509 nursing assistants in sixteen nursing homes in Hunan province in China. The questionnaire survey was to assess the knowledge and attitude of urinary incontinence of nursing assistants. On the basis of quantitative research and combined with focus group, training demands were identified, which nurse managers should adopt to improve nursing assistants’ professional practice ability in urinary incontinence. Most nursing assistants held the poor knowledge (14.0 ± 4.18) but had positive attitudes (35.5 ± 3.19) toward urinary incontinence. There was a significant positive correlation between urinary incontinence knowledge and nursing assistants' year of work and educational level, urinary incontinence attitude, and education level (p < 0.001). Despite a general awareness of the importance of prevention of urinary tract infections, not all nurse managers fully valued the training in urinary incontinence compared with daily care training. And the nursing assistants required simple education resources to equip them with skills to address problem about urinary incontinence. The variety of learning methods also highlighted the need for educational materials, and nursing assistants had shown a strong interest in online learning. Related education material should be developed to meet the learning need of nurse assistants and provide suitable training method for planned quality improvement in urinary incontinence.

Keywords: mixed methods, nursing assistants, nursing homes, urinary incontinence

Procedia PDF Downloads 137

Authors: E. Tarantino, G. Disciglio, L. Frabboni, A. Libutti, G. Gatta, A. Gagliaridi, A. Tarantino

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Nowadays, the main goal for modern horticultural production is the increase of quality. In the recent years, the use of organic fertilizers or bio stimulants, that can be applied in agriculture in order to improve the quanti-qualitative crop yields, has encountered an increasing interest. The bio stimulants are gaining importance also for their possible use in organic and sustainable agriculture, avoiding excessive fertilizer applications. Consecutive experimental trials were carried out in Apulia region (southern Italy) on three herbaceous crops (cauliflower, pepper and fennel), grown in pots, under conventional and organic fertilization, with and without bio stimulants application, to verify the effects of several bio stimulants (Siapton®10L, Micotech L and Lysodin Alga-Fert) on quanti-qualitative yield characteristics. At the harvest, the quanti-qualitative yield characteristics of each crop were determined. All experimental data were subjected to analysis of variance (ANOVA) and, when significant effects were detected, the mean values were compared using Tukey’s test. Results showed great differences of yield characteristics between conventional and organic crops, particularly highlighting a higher yield in the conventional one. Variable results were generally observed when bio stimulants were applied. In this contest no effect were noted on quantitative yield, whereas a light positive effect of bio stimulants on qualitative characteristic, related to the higher dry matter content of cauliflower and the higher soluble solid content of pepper, was observed. Moreover, an evident positive effect of bio stimulants was noted in the fennel due to the lower nitrate content. The latter results are according with most of published literature obtained on other herbaceous crops.

Keywords: biostimulants, cauliflower, pepper, fennel

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Authors: M. A. Hashem, I. Jahan

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The experiment was conducted to find out the effect of different levels of Pomegranate (Punica granatum) extract and synthetic antioxidant BHA (Beta Hydroxyl Anisole) on fresh and preserved beef meatballs in order to make functional food. For this purpose, ground beef samples were divided into five treatment groups. They were treated as control group, 0.1% synthetic antioxidant group, 0.1%, 0.2% and 0.3% pomegranate extract group as T1, T2, T3, T4 and T5 respectively. Proximate analysis, sensory tests (color, flavor, tenderness, juiciness, overall acceptability), cooking loss, pH value, free fatty acids (FFA), thiobarbituric acid values (TBARS), peroxide value (POV) and microbiological examination were determined in order to evaluate the effect of pomegranate extract as natural antioxidant and antimicrobial activities compared to BHA (Beta Hydroxyl Anisole) at first day before freezing and for maintaining meatballs qualities on the shelf life of beef meat balls stored for 60 days under frozen condition. Freezing temperature was -20˚C. Days of intervals of experiment were on 0, 15th, 30th and 60th days. Dry matter content of all the treatment groups differ significantly (p<0.05). On the contrary, DM content increased significantly (p<0.05) with the advancement of different days of intervals. CP content of all the treatments were increased significantly (p<0.05) among the different treatment groups. EE and Ash content were decreased significantly (p<0.05) at different treatment levels. FFA values, TBARS, POV were decreased significantly (p<0.05) at different treatment levels. Color, odor, tenderness, juiciness, overall acceptability decreased significantly (p<0.05) at different days of intervals. Raw PH, cooked pH were increased at different treatment levels significantly (p<0.05). The cooking loss (%) at different treatment levels were differ significantly (p<0.05). TVC (logCFU/g), TCC (logCFU/g) and TYMC (logCFU/g) was decreased significantly (p<0.05) at different treatment levels and at different days of intervals comparison to control. Considering CP, tenderness, juiciness, overall acceptability, cooking loss, FFA, POV, TBARS value and microbial analysis it can be concluded that pomegranate extract at 0.1%, 0.2% and 0.3% can be used instead of synthetic antioxidant BHA in beef meatballs. On the basis of sensory evaluation, nutrient quality, physicochemical properties, biochemical analysis and microbial analysis 0.3% Pomegranate extract can be recommended for formulation of value added beef meatball enriched with natural antioxidant.

Keywords: antioxidant, pomegranate, BHA, value added meat products

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Authors: Samuel Marínez González

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In the last decades, the studies about humor have been increasing significantly in all areas. In the field of education and, specially, in the second language teaching, most research has concentrated on the beneficial effects that the introduction of humor in the process of teaching and learning a foreign language, as well as its impact on teachers and students. In the following research, we will try to know the learners’ perspectives about humor and its use in the Spanish as a Foreign Language classes. In order to do this, a different range of students from the Spanish courses at the University of Cape Town will participate in a survey that will reveal their beliefs about the frequency of humor in their daily lives and their Spanish lessons, their reactions to humorous situations, and the main advantages or disadvantages, from their point of view, to the introduction of humor in the teaching of Spanish as a Foreign Language.

Keywords: education, foreign languages, humor, pedagogy, Spanish as a Foreign Language, students’ perceptions

Procedia PDF Downloads 341

Authors: Prateek Rastogi

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Medical teaching in present era concentrates not only on teaching but on effective teaching. For effective teaching a combination of effective carefully designed curriculum, an educated educator, competent learner and fool proof evaluation system is required. Keeping these parameters in mind and study was undertaken at Kasturba Medical College, Mangalore among medical students. In this study, evaluation of Forensic Medicine syllabus along with its teaching and evaluation methodology was done using 20 different parameters. This questionnaire based study was done over a period of two years i.e. 2013 and 2014. Batch of students who just passed the forensic medicine subject was included for study. Carefully designed questionnaire contained questions related to course content, teaching methodology and evaluation system along with provisions to mention merits and demerits of subject. The feedbacks in first round were analyzed and suggestions were implemented before conducting the second round of study. Overall evaluation of course was done as well as it was compared with other subjects of second MBBS. It was noted that Scores improved in 2nd survey thus stressing the importance of course evaluation and student feedback in teaching improvement.

Keywords: teaching methodology, system of evaluation, course content, bioinformatics, biomedicine

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Authors: Waleed Afandi

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Artificial intelligence (AI) has rapidly transformed various sectors, including education. This paper explores the integration of AI in education, emphasizing its potential to revolutionize learning processes, enhance teaching methodologies, and personalize education. We examine the historical context of AI in education, current applications, and the potential challenges and ethical considerations associated with its implementation. By reviewing a wide range of literature, this study aims to provide a comprehensive understanding of how AI can be leveraged to improve educational outcomes and the future directions of AI-driven educational innovations. Additionally, the paper discusses the impact of AI on student engagement, teacher support, and administrative efficiency. Case studies highlighting successful AI applications in diverse educational settings are presented, showcasing the practical benefits and real-world implications. The analysis also addresses potential disparities in access to AI technologies and suggests strategies to ensure equitable implementation. Through a balanced examination of the promises and pitfalls of AI in education, this study seeks to inform educators, policymakers, and technologists about the optimal pathways for integrating AI to foster an inclusive, effective, and innovative educational environment.

Keywords: artificial intelligence, education, personalized learning, teaching methodologies, educational outcomes, AI applications, student engagement, teacher support, administrative efficiency, equity in education

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Authors: Wen-Wei Chiang

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In this study, the researcher developed a scale for use in measuring the degree to which high school students experience a state of flow. The researcher then verified its reliability and validity in an actual classroom setting. The ultimate objective was to identify feasible methods by which to promote the experience of a flow state among high school students engaged in the study of science. The nine indices identified in this study to assess the engagement of high school students focus primarily on the study of science-related topics; however, the principles on which they are based are applicable to a wide range of learning situations. Teachers must outline the goals of each lesson clearly and provide unambiguous feedback. They must also look for ways to make the lessons more fun and appealing.

Keywords: flow experience, positive psychology, questionnaire, science learning

Procedia PDF Downloads 119

Authors: Chien-Chun Huang, P. W. Yuan

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Banana is one of the important fruits which constitute a valuable source of energy, vitamins and minerals and an important food component throughout the world. The fruit ripening and maturity standards vary from country to country depending on the expected shelf life of market. During ripening there are changes in appearance, texture and chemical composition of banana. The changes of component of banana during ethylene-induced ripening are categorized as nutritive values and commercial utilization. The objectives of this study were to investigate the changes of chemical composition and physicochemical properties of banana during ethylene-induced ripening. Green bananas were harvested and ripened by ethylene gas at low temperature (15℃) for seven stages. At each stage, banana was sliced and freeze-dried for banana flour preparation. The changes of total starch, resistant starch, chemical compositions, physicochemical properties, activity of amylase, polyphenolic oxidase (PPO) and phenylalanine ammonia lyase (PAL) of banana were analyzed each stage during ripening. The banana starch was isolated and analyzed for gelatinization properties, pasting properties and microscopic appearance each stage of ripening. The results indicated that the highest total starch and resistant starch content of green banana were 76.2% and 34.6%, respectively at the harvest stage. Both total starch and resistant starch content were significantly declined to 25.3% and 8.8%, respectively at the seventh stage. Soluble sugars content of banana increased from 1.21% at harvest stage to 37.72% at seventh stage during ethylene-induced ripening. Swelling power of banana flour decreased with the progress of ripening stage, but solubility increased. These results strongly related with the decreases of starch content of banana flour during ethylene-induced ripening. Both water insoluble and alcohol insoluble solids of banana flour decreased with the progress of ripening stage. Both activity of PPO and PAL increased, but the total free phenolics content decreased, with the increases of ripening stages. As ripening stage extended, the gelatinization enthalpy of banana starch significantly decreased from 15.31 J/g at the harvest stage to 10.55 J/g at the seventh stage. The peak viscosity and setback increased with the progress of ripening stages in the pasting properties of banana starch. The highest final viscosity, 5701 RVU, of banana starch slurry was found at the seventh stage. The scanning electron micrograph of banana starch showed the shapes of banana starch appeared to be round and elongated forms, ranging in 10-50 μm at the harvest stage. As the banana closed to ripe status, some parallel striations were observed on the surface of banana starch granular which could be caused by enzyme reaction during ripening. These results inferred that the highest resistant starch was found in the green banana could be considered as a potential application of healthy foods. The changes of chemical composition and physicochemical properties of banana could be caused by the hydrolysis of enzymes during the ethylene-induced ripening treatment.

Keywords: maturation of banana, appearance, texture, soluble sugars, resistant starch, enzyme activities, physicochemical properties of banana starch

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Authors: Raquel P. F. Guiné, Susana R. Matos, Daniela V. T. A. Costa, Fernando J. Gonçalves

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Because blueberries are worldwide recognized as a good source of beneficial components, their consumption has increased in the past decades, and so have the scientific works about their properties. Hence this work was undertaken to evaluate the effect of some production and conservation factors on the properties of blueberries from cultivar Bluecrop. The physical and chemical analyses were done according to established methodologies and then all data was treated using software SPSS for assessment of the possible differences among the factors investigated and/or the correlations between the variables at study. The results showed that location of production influenced some of the berries properties (caliber, sugars, antioxidant activity, color and texture) and that the age of the bushes was correlated with moisture, sugars and acidity, as well as lightness. On the other hand, altitude of the farm only was correlated to sugar content. With regards to conservation, it influenced only anthocyanins content and DPPH antioxidant activity. Finally, the type of extract and the order of extraction had a pronounced influence on all the phnolic properties evaluated.

Keywords: Antioxidant activity, blueberry, conservation, geographical origin, phenolic compounds, statistical analysis

Procedia PDF Downloads 476

Authors: Josue Javier Martinez Flores, Jaime Alvarez Quintana

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A thermal rectifier consists of a device which can load a different heat flow which depends on the direction of that flow. That device is a thermal diode. It is well known that heat transfer in solids basically depends on the electrical, magnetic and crystalline nature of materials via electrons, magnons and phonons as thermal energy carriers respectively. In the present research, we have synthesized polycrystalline Ni-Cu alloys and identified the Curie temperatures; and we have observed that by way of secondary phase transitions, it is possible manipulate the heat conduction in solid state thermal diodes via transition temperature. In this sense, we have succeeded in developing solid state thermal diodes with a control gate through the Curie temperature via the activation and deactivation of magnons in Ni-Cu ferromagnetic alloys at room temperature. Results show thermal diodes with thermal rectification factors up to 1.5. Besides, the performance of the electrical rectifiers can be controlled by way of alloy Cu content; hence, lower Cu content alloys present enhanced thermal rectifications factors than higher ones.

Keywords: thermal rectification, Curie temperature, ferromagnetic alloys, magnons

Procedia PDF Downloads 247

Authors: Thrivikraman Aswathi, S. Advaith

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As there can be cases where the use of real data is somehow limited, such as when it is hard to get access to a large volume of real data, we need to go for synthetic data generation. This produces high-quality synthetic data while maintaining the statistical properties of a specific dataset. In the present work, a generative adversarial network (GAN) is trained to produce multivariate time series (MTS) data since the MTS is now being gathered more often in various real-world systems. Furthermore, the GAN-generated MTS data is fed into a transformer-based deep learning architecture that carries out the data categorization into predefined classes. Further, the model is evaluated across various distinct domains by generating corresponding MTS data.

Keywords: GAN, transformer, classification, multivariate time series

Procedia PDF Downloads 130

Authors: Siham Boulaknadel

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Every culture has its share of a rich history of storytelling in oral, visual, and textual form. The Amazigh language, as many languages, has its own which has entertained and informed across centuries and cultures, and its instructional potential continues to serve teachers. According to many researchers, listening to stories draws attention to the sounds of language and helps children develop sensitivity to the way language works. Stories including repetitive phrases, unique words, and enticing description encourage students to join in actively to repeat, chant, sing, or even retell the story. This kind of practice is important to language learners’ oral language development, which is believed to correlate completely with student’s academic success. Today, with the advent of multimedia, digital storytelling for instance can be a practical and powerful learning tool. It has the potential in transforming traditional learning into a world of unlimited imaginary environment. This paper reports on a research project on development of multimedia Storytelling Website using traditional Amazigh oral narratives called “tell me a story”. It is a didactic tool created for the learning of good moral values in an interactive multimedia environment combining on-screen text, graphics and audio in an enticing environment and enabling the positive values of stories to be projected. This Website developed in this study is based on various pedagogical approaches and learning theories deemed suitable for children age 8 to 9 year-old. The design and development of Website was based on a well-researched conceptual framework enabling users to: (1) re-play and share the stories in schools or at home, and (2) access the Website anytime and anywhere. Furthermore, the system stores the students work and activities over the system, allowing parents or teachers to monitor students’ works, and provide online feedback. The Website contains following main feature modules: Storytelling incorporates a variety of media such as audio, text and graphics in presenting the stories. It introduces the children to various kinds of traditional Amazigh oral narratives. The focus of this module is to project the positive values and images of stories using digital storytelling technique. Besides development good moral sense in children using projected positive images and moral values, it also allows children to practice their comprehending and listening skills. Reading module is developed based on multimedia material approach which offers the potential for addressing the challenges of reading instruction. This module is able to stimulate children and develop reading practice indirectly due to the tutoring strategies of scaffolding, self-explanation and hyperlinks offered in this module. Word Enhancement assists the children in understanding the story and appreciating the good moral values more efficiently. The difficult words or vocabularies are attached to present the explanation, which makes the children understand the vocabulary better. In conclusion, we believe that the interactive multimedia storytelling reveals an interesting and exciting tool for learning Amazigh. We plan to address some learning issues, in particularly the uses of activities to test and evaluate the children on their overall understanding of story and words presented in the learning modules.

Keywords: Amazigh language, e-learning, storytelling, language teaching

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Authors: A. D. Tayal

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The energy industry is undergoing significant disruption. This research outlines that, whilst challenging; this disruption is also an emerging opportunity for electricity utilities. One such opportunity is leveraging the developments in data analytics and machine learning. As the uptake of renewable energy technologies and complimentary control systems increases, electricity grids will likely transform towards dense microgrids with high penetration of renewable generation sources, rich in network and customer data, and linked through intelligent, wireless communications. Data digitisation and analytics have already impacted numerous industries, and its influence on the energy sector is growing, as computational capabilities increase to manage big data, and as machines develop algorithms to solve the energy challenges of the future. The objective of this paper is to address how far the uptake of renewable technologies can go given the constraints of existing grid infrastructure and provides a qualitative assessment of how higher levels of renewable energy penetration can be facilitated by incorporating even broader technological advances in the fields of data analytics and machine learning. Western Australia is used as a contextualised case study, given its abundance and diverse renewable resources (solar, wind, biomass, and wave) and isolated networks, making a high penetration of renewables a feasible target for policy makers over coming decades.

Keywords: data, innovation, renewable, solar

Procedia PDF Downloads 365

Authors: Aragorn Joaquin Pineda Dela Cruz

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Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

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Authors: Yasser Y. Lenis, Amy Jo Montgomery, Diego F. Carrillo-Gonzalez

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Introduction: The use of didactic instruments in different learning environments plays a pivotal role in enhancing the level of knowledge in veterinary science students. The direct instruction of basic animal reproduction concepts in students enrolled in veterinary medicine programs allows them to elucidate the biological and molecular mechanisms that perpetuate the animal species in an ecosystem. Therefore, universities must implement didactic strategies that facilitate the teaching and learning processes for students and, in turn, enrich learning environments. Objective: to evaluate the effect of the use of a didactic textbook on the level of theoretical knowledge in embryo-maternal recognition for veterinary medicine students. Methods: the participants (n=24) were divided into two experimental groups: control (Ctrl) and treatment (Treat). Both groups received 4 hours of theoretical training regarding the basic concepts in bovine embryo-maternal recognition. However, the Treat group was also exposed to a guided lecture and the activity play-to-learn from a cow reproduction didactic textbook. A pre-test and a post-test were applied to assess the prior and subsequent knowledge in the participants. Descriptive statistics were applied to identify the success rates for each of the tests. Afterwards, a repeated measures model was applied where the effect of the intervention was considered. Results: no significant difference (p>0,05) was observed in the number of right answers for groups Ctrl (54,2%±12,7) and Treat (40,8%±16,8) in the pre-test. There was no difference (p>0,05) compering the number of right answers in Ctrl pre-test (54,2%±12,7) and post-test (60,8±18,8). However, the Treat group showed a significant (p>0,05) difference in the number of right answers when comparing pre-test (40,8%±16,8) and post-test (71,7%±14,7). Finally, after the theoretical training and the didactic activity in the Treat group, an increase of 10.9% (p<0,05) in the number of right answers was found when compared with the Ctrl group. Conclusion: the use of didactic tools that include guided lectures and activities like play-to-learn from a didactic textbook enhances the level of knowledge in an animal reproduction course for veterinary medicine students.

Keywords: animal reproduction, pedagogic, level of knowledge, learning environment

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Authors: Jayanth C., Anirudh Sai Yetikuri, Kavitha S. N.

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This paper explores the development and application of computer vision and machine learning techniques for real-time pose detection, facial recognition, and number plate extraction. Utilizing MediaPipe for pose estimation, the research presents methods for detecting hand raises and ducking postures through real-time video analysis. Complementarily, facial recognition is employed to compare and verify individual identities using the face recognition library. Additionally, the paper demonstrates a robust approach for extracting and storing vehicle number plates from images, integrating Optical Character Recognition (OCR) with a database management system. The study highlights the effectiveness and versatility of these technologies in practical scenarios, including security and surveillance applications. The findings underscore the potential of combining computer vision techniques to address diverse challenges and enhance automated systems for both individual and vehicular identification. This research contributes to the fields of computer vision and machine learning by providing scalable solutions and demonstrating their applicability in real-world contexts.

Keywords: computer vision, pose detection, facial recognition, number plate extraction, machine learning, real-time analysis, OCR, database management

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Authors: Ellina Zipman

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This research investigates the place of music education in aged care facilities through the implementation of a program of regular piano lessons for residents. Using a qualitative case study methodology, the research explores aged care residents’ experiences in learning to play the piano. Since the aged care homes are unlikely places for formal learning and since older adults, especially in residential care, are not considered likely candidates for learning, this research opens the door for innovative and transformative thinking about where and to whom educational programs can be delivered. By addressing the educational needs of residents in aged care facilities, this research fills the gap in the literature. The research took place in Australia in two of Melbourne’s residential aged care facilities, engaging two residents (a nonagenarian female and an octogenarian male) to participate in 12-months weekly individual piano lessons. The data was collected through video recording of lessons, observations, interviews, emails, and a reflective journal. Data analysis was done using Nvivo and hard copy analysis with identifications of themes. The case studies revealed that passion for music was a major driver in participants’ motivation to engage in a long-term piano lessons program. This participation led to experiences of positive emotions, positive attitude, successes and challenges, the exercise of control, maintaining and building new relationships, improved self-confidence through autonomy and independent skills development, and discovering new identities through finding a new purpose and new roles in life. Speaking through participants’ voices, this research project demonstrates the importance of music education for older adults and hopes to influence transformation in the residential aged care sector.

Keywords: adult music education, quality of life, passion, positive ageing, wellbeing

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Authors: Chamika Chiran Perera, Dananjaya Perera, Chirath Dasanayake, Banuka Athuraliya

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Male infertility is a major problem in the world, and it is a neglected and sensitive health issue in Sri Lanka. It can be determined by analyzing human semen samples. Sperm motility is one of many factors that can evaluate male’s fertility potential. In Sri Lanka, this analysis is performed manually. Manual methods are time consuming and depend on the person, but they are reliable and it can depend on the expert. Machine learning and deep learning technologies are currently being investigated to automate the spermatozoa motility analysis, and these methods are unreliable. These automatic methods tend to produce false positive results and false detection. Current automatic methods support different techniques, and some of them are very expensive. Due to the geographical variance in spermatozoa characteristics, current automatic methods are not reliable for motility analysis in Sri Lanka. The suggested system, DeepMotile, is to explore a method to analyze motility of human spermatozoa automatically and present it to the andrology laboratories to overcome current issues. DeepMotile is a novel deep learning method for analyzing spermatozoa motility parameters in the Sri Lankan population. To implement the current approach, Sri Lanka patient data were collected anonymously as a dataset, and glass slides were used as a low-cost technique to analyze semen samples. Current problem was identified as microscopic object detection and tackling the problem. YOLOv5 was customized and used as the object detector, and it achieved 94 % mAP (mean average precision), 86% Precision, and 90% Recall with the gathered dataset. StrongSORT was used as the object tracker, and it was validated with andrology experts due to the unavailability of annotated ground truth data. Furthermore, this research has identified many potential ways for further investigation, and andrology experts can use this system to analyze motility parameters with realistic accuracy.

Keywords: computer vision, deep learning, convolutional neural networks, multi-target tracking, microscopic object detection and tracking, male infertility detection, motility analysis of human spermatozoa

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Authors: Kayla Marie Sarte

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This study sought to describe mother tongue-based classes in the light of classroom interactional discourse using the Sinclair and Coulthard model. It specifically identified the exchanges, grouped into Teaching and Boundary types; moves, coded as Opening, Answering and Feedback; and the occurrence of the 13 acts (Bid, Cue, Nominate, Reply, React, Acknowledge, Clue, Accept, Evaluate, Loop, Comment, Starter, Conclusion, Aside and Silent Stress) in the classroom, and determined what these reveal about the teaching and learning processes in the MTB classroom. Being a qualitative study, using the Single Collective Case Within-Site (embedded) design, varied data collection procedures such as non-participant observations, audio-recordings and transcription of MTB classes, and semi-structured interviews were utilized. The results revealed the presence of all the codes in the model (except for the silent stress) which also implied that the Hiligaynon mother tongue-based class was eclectic, cultural and communicative, and had a healthy, analytical and focused environment which aligned with the aims of MTB-MLE, and affirmed the purported benefits of mother tongue teaching. Through the study, gaps in the mother tongue teaching and learning were also identified which involved the difficulty of children in memorizing Hiligaynon terms expressed in English in their homes and in the communities.

Keywords: discourse analysis, language teaching and learning, mother tongue-based education, multilingualism

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Authors: Chua Si Wen Alicia, Marcus Goh Tian Xi, Eunice Gan Ghee Wu, Helen Bound, Lee Liang Ying, Albert Lee

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In a world full of rapid changes, people often need a set of skills to help them navigate an ever-changing workscape. These skills, often known as “future-oriented skills,” include learning to learn, critical thinking, understanding multiple perspectives, and knowledge creation. Future-oriented skills are typically assumed to be domain-general, applicable to multiple domains, and can be cultivated through a learning approach called Dialogical Inquiry. Dialogical Inquiry is known for its benefits of making sense of multiple perspectives, encouraging critical thinking, and developing learner’s capability to learn. However, it currently exists as a quantitative tool, which makes it hard to track and compare learning processes over time. With these concerns, the present research aimed to develop and validate a quantitative tool for the Map of Dialogical Inquiry, focusing Imagining aspect of learning. The Imagining aspect four dimensions: 1) speculative/ look for alternatives, 2) risk taking/ break rules, 3) create/ design, and 4) vision/ imagine. To do so, an exploratory literature review was conducted to better understand the dimensions of Imagining. This included deep-diving into the history of the creation of the Map of Dialogical Inquiry and a review on how “Imagining” has been conceptually defined in the field of social psychology, education, and beyond. Then, we synthesised and validated scales. These scales measured the dimension of Imagination and related concepts like creativity, divergent thinking regulatory focus, and instrumental risk. Thereafter, items were adapted from the aforementioned procured scales to form items that would contribute to the preliminary version of the Imagining Scale. For scale validation, 250 participants were recruited. A Confirmatory Factor Analysis (CFA) sought to establish dimensionality of the Imagining Scale with an iterative procedure in item removal. Reliability and validity of the scale’s dimensions were sought through measurements of Cronbach’s alpha, convergent validity, and discriminant validity. While CFA found that the distinction of Imagining’s four dimensions could not be validated, the scale was able to establish high reliability with a Cronbach alpha of .96. In addition, the convergent validity of the Imagining scale was established. A lack of strong discriminant validity may point to overlaps with other components of the Dialogical Map as a measure of learning. Thus, a holistic approach to forming the tool – encompassing all eight different components may be preferable.

Keywords: learning, education, imagining, pedagogy, dialogical teaching

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Authors: Zoi Konsoula

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Antioxidant-rich extracts were prepared from pomegranate peels, seeds and juice using methanol and ethanol and their antioxidant activity was evaluated by the 1,1-diphenyl-2-picrylhydrazine (DPPH) radical scavenging and Ferric Reducing Antioxidant Power (FRAP) method. Both analytical methods indicated a higher antioxidant activity in extracts prepared from peels, which was comparable to that of butylated hydroxytoluene (BHT). Furthermore, the antioxidant activity was correlated to the phenolic and flavonoid content of the various extracts. The antioxidant effectiveness of the extracts was also assessed using corn oil as the oxidation substrate. More specifically, preheated corn oil samples stabilized with extracts at a concentration of 250 ppm, 500 ppm or 1,000 ppm were subjected to accelerated aging (100 oC, 10 days) and the extent of oxidative alteration was followed by the measurement of the peroxide, conjugated dienes and trienes, as well as p-aniside value. BHT at its legal limit (200 ppm) served as standard besides the control sample. Results from the different parameters were in agreement with each other suggesting that pomegranate extracts can stabilize corn oil effectively under accelerated conditions, at all concentrations tested. However, the magnitude of oil stabilization depended strongly on the amount of extract added and this was positively correlated with their phenolic content. Pomegranate peel extracts, which exhibited the highest not only phenolic and flavonoid content but also antioxidant activity, were more potent in inhibiting oxidative deterioration. Both methanolic and ethanolic peel extracts at a concentration of 500 ppm exerted a stabilizing effect comparable to that of BHT, while at a concentration of 1000 ppm they exhibited higher stabilization efficiency in comparison to BHT. Finally, heating oil samples resulted in a time dependent decrease in their antioxidant capacity. Samples containing peel extracts appeared to retain their antioxidant capacity for a longer period, indicating that these extracts contained active compounds that offered superior antioxidant protection to corn oil.

Keywords: antioxidant activity, corn oil, oxidative deterioration, pomegranate

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Authors: Olufunke O. Ezekiel, Adenike O. Ogunshe, Omotola F. Olagunju, Arinola O. Falola

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Studies were conducted on fermentation of tamarind seed for production of food condiment. Fermentation followed the conventional traditional method of fermented locust bean (iru) production and was carried out over a period of three days (72 hours). Samples were withdrawn and analysed for proximate composition, pH, titratable acidity, tannin content, phytic acid content and trypsin inhibitor activity using standard methods. Effects of fermentation on proximate composition, anti-nutritional factors and sensory properties of the seed were evaluated. All data were analysed using ANOVA and means separated using Duncan multiple range test. Microbiological analysis to identify and characterize the microflora responsible for the fermentation of the seed was also carried out. Fermentation had significant effect on the proximate composition on the fermented seeds. As fermentation progressed, there was significant reduction in the anti-nutrient contents. Organisms isolated from the fermenting tamarind seeds were identified as non-pathogenic and common with fermented legumes.

Keywords: condiment, fermentation, legume, tamarind seed

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Authors: Shrabani Ghosh

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Automatic offensive language detection in social media has become a stirring task in today's NLP. Manual Offensive language detection is tedious and laborious work where automatic methods based on machine learning are only alternatives. Previous works have done sentiment analysis over social media in different ways such as supervised, semi-supervised, and unsupervised manner. Domain adaptation in a semi-supervised way has also been explored in NLP, where the source domain and the target domain are different. In domain adaptation, the source domain usually has a large amount of labeled data, while only a limited amount of labeled data is available in the target domain. Pretrained transformers like BERT, RoBERTa models are fine-tuned to perform text classification in an unsupervised manner to perform further pre-train masked language modeling (MLM) tasks. In previous work, hate speech detection has been explored in Gab.ai, which is a free speech platform described as a platform of extremist in varying degrees in online social media. In domain adaptation process, Twitter data is used as the source domain, and Gab data is used as the target domain. The performance of domain adaptation also depends on the cross-domain similarity. Different distance measure methods such as L2 distance, cosine distance, Maximum Mean Discrepancy (MMD), Fisher Linear Discriminant (FLD), and CORAL have been used to estimate domain similarity. Certainly, in-domain distances are small, and between-domain distances are expected to be large. The previous work finding shows that pretrain masked language model (MLM) fine-tuned with a mixture of posts of source and target domain gives higher accuracy. However, in-domain performance of the hate classifier on Twitter data accuracy is 71.78%, and out-of-domain performance of the hate classifier on Gab data goes down to 56.53%. Recently self-supervised learning got a lot of attention as it is more applicable when labeled data are scarce. Few works have already been explored to apply self-supervised learning on NLP tasks such as sentiment classification. Self-supervised language representation model ALBERTA focuses on modeling inter-sentence coherence and helps downstream tasks with multi-sentence inputs. Self-supervised attention learning approach shows better performance as it exploits extracted context word in the training process. In this work, a self-supervised attention mechanism has been proposed to detect hate speech on Gab.ai. This framework initially classifies the Gab dataset in an attention-based self-supervised manner. On the next step, a semi-supervised classifier trained on the combination of labeled data from the first step and unlabeled data. The performance of the proposed framework will be compared with the results described earlier and also with optimized outcomes obtained from different optimization techniques.

Keywords: attention learning, language model, offensive language detection, self-supervised learning

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Authors: Isabel Medina, Mario Duran

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Although Problem-based learning provides students with multiple opportunities for rigorous instructional experiences in which students are challenged to address problems in the community; there are still gaps in connecting community leaders to the PBL process. At a south Texas high school, community participation serves as an integral component of the PBL process. Problem-based learning (PBL) has recently gained momentum due to the increase in global communities that value collaboration and critical thinking. As an instructional approach, PBL engages high school students in meaningful learning experiences. Furthermore, PBL focuses on providing students with a connection to real-world situations that require effective peer collaboration. For PBL leaders, providing students with a meaningful process is as important as the final PBL outcome. To achieve this goal, STEM high school strategically created a space for community involvement to be woven within the PBL fabric. This study examines the impact community members had on PBL students attending a STEM high school in South Texas. At STEM High School, community members represent a support system that works through the PBL process to ensure students receive real-life mentoring from business and industry leaders situated in the community. A phenomenological study using a semi-structured approach was used to collect data about students’ perception of community involvement within the PBL process for one South Texas high school. In our proposed presentation, we will discuss how community involvement in the PBL process academically impacted the educational experience of high school students at STEM high school. We address the instructional concerns PBL critics have with the lack of direct instruction, by providing a representation of how STEM high school utilizes community members to assist in impacting the academic experience of students.

Keywords: phenomenological, STEM education, student engagement, community involvement

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Authors: Natalia Efremova, Sergey Tarasenko

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We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.

Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment

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Authors: Michael Johnson, Vincenzo Oliveri

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This work considers an interdisciplinary Problem-Based Learning (PBL) project developed by lecturers from the Aeronautical and Electronic and Computer Engineering departments at the University of Limerick. This “CANSAT” project utilises the CanSat can-sized satellite platform in order to allow students from aeronautical and electronic engineering to engage in a mixed format (online/face-to-face), interdisciplinary PBL assignment using a real-world platform and application. The project introduces students to the design, development, and construction of the CanSat system over the course of a single semester, enabling student(s) to apply their aeronautical and technical skills/capabilities to the realisation of a working CanSat system. In this case study, the CanSat kits are used to pivot the real-world, discipline-relevant PBL goal of designing, building, and testing the CanSat system with payload(s) from a traditional module-based setting to an online PBL setting. Feedback, impressions, benefits, and challenges identified through the semester are presented. Students found the project to be interesting and rewarding, with the interdisciplinary nature of the project appealing to them. Challenges and difficulties encountered are also addressed, with solutions developed between the students and facilitators to overcoming these discussed.

Keywords: problem-based learning, interdisciplinary, engineering, CanSATs

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Authors: Loren Clarke, Katie Reed

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The integration of artificial intelligence (AI) in high school education assessment offers transformative potential, providing more personalized, timely, and accurate evaluations of student performance. However, the successful adoption of AI-driven assessment systems requires robust change management strategies to navigate the complexities and resistance that often accompany such technological shifts. This presentation explores effective methods for implementing AI in high school assessment, emphasizing the need for strategic planning and stakeholder engagement. Focusing on a case study of a Victorian high school, it will examine the practical steps taken to integrate AI into teaching and learning. This school has developed innovative processes to support academic integrity and foster authentic cogeneration with AI, ensuring that the technology is used ethically and effectively. By creating comprehensive professional development programs for teachers and maintaining transparent communication with students and parents, the school has successfully aligned AI technologies with their existing curricula and assessment frameworks. The session will highlight how AI has enhanced both formative and summative assessments, providing real-time feedback that supports differentiated instruction and fosters a more personalized learning experience. Participants will learn about best practices for managing the integration of AI in high school settings while maintaining a focus on equity and student-centered learning. This presentation aims to equip high school educators with the insights and tools needed to effectively manage the integration of AI in assessment, ultimately improving educational outcomes and preparing students for future success. Methodologies: The research is a case study of a Victorian high school to examine AI integration in assessments, focusing on practical implementation steps, ethical practices, and change management strategies to enhance personalized learning and assessment. Outcomes: This research explores AI integration in high school assessments, focusing on personalized evaluations, ethical use, and change management. A Victorian school case study highlights best practices to enhance assessments and improve student outcomes. Main Contributions: This research contributes by outlining effective AI integration in assessments, showcasing a Victorian school's implementation, and providing best practices for ethical use, change management, and enhancing personalized learning outcomes.

Keywords: artificial intelligence, assessment, curriculum design, teaching and learning, ai in education

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Authors: Georges Bou Ghantous

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This literature review examines the transformative impact of Artificial Intelligence (AI) on higher education, highlighting both the potential benefits and challenges associated with its adoption. The review reveals that AI significantly enhances personalized learning by tailoring educational experiences to individual student needs, thereby boosting engagement and learning outcomes. Automated grading systems streamline assessment processes, allowing educators to focus on improving instructional quality and student interaction. AI's data-driven insights provide valuable analytics, helping educators identify trends in at-risk students and refine teaching strategies. Moreover, AI promotes enhanced instructional innovation through the adoption of advanced teaching methods and technologies, enriching the educational environment. Administrative efficiency is also improved as AI automates routine tasks, freeing up time for educators to engage in research and curriculum development. However, the review also addresses the challenges that accompany AI integration, such as data privacy concerns, algorithmic bias, dependency on technology, reduced human interaction, and ethical dilemmas. This balanced exploration underscores the need for careful consideration of both the advantages and potential hurdles in the implementation of AI in higher education.

Keywords: administrative efficiency, data-driven insights, data privacy, ethical dilemmas, higher education, personalized learning

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