Search results for: activity learning

Authors: Miguel Pereira, Lígia Pimentel, Manuela Pintado

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Animal blood is a major by-product of slaughterhouses and still represents a cost and environmental problem in some countries. To be eliminated, blood should be stabilised by cooking and afterwards the slaughterhouses must have to pay for its incineration. In order to reduce the elimination costs and valorise the high protein content the aim of this study was the optimization of hydrolysis conditions, in terms of enzyme ratio and time, in order to obtain hydrolysates with biological activity. Two enzymes were tested in this assay: pepsin and proteases from Cynara cardunculus (cardosins). The latter has the advantage to be largely used in the Portuguese Dairy Industry and has a low price. The screening assays were carried out in a range of time between 0 and 10 h and using a ratio of enzyme/reaction volume between 0 and 5%. The assays were performed at the optimal conditions of pH and temperature for each enzyme: 55 °C at pH 5.2 for cardosins and 37 °C at pH 2.0 for pepsin. After reaction, the hydrolysates were evaluated by FPLC (Fast Protein Liquid Chromatography) and tested for their antioxidant activity by ABTS method. FPLC chromatograms showed different profiles when comparing the enzymatic reactions with the control (no enzyme added). The chromatogram exhibited new peaks with lower MW that were not present in control samples, demonstrating the hydrolysis by both enzymes. Regarding to the antioxidant activity, the best results for both enzymes were obtained using a ratio enzyme/reactional volume of 5% during 5 h of hydrolysis. However, the extension of reaction did not affect significantly the antioxidant activity. This has an industrial relevant aspect in what concerns to the process cost. In conclusion, the enzymatic blood hydrolysis can be a better alternative to the current elimination process allowing to the industry the reuse of an ingredient with biological properties and economic value.

Keywords: antioxidant activity, blood, by-products, enzymatic hydrolysis

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Authors: Mthokozisi Simelane

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Background: Malaria remains a life-threatening disease in tropical regions despite the advances in the treatment of this disease, it still remains a significant burden as some parasites have become resistant to the currently available drugs. This has created a necessity for the development of alternative, more efficient antimalarial drugs. Warburgia salutaris is a traditional medicinal plant used in malaria treatment by Zulu traditional healers. Materials and methods: The W. salutaris stem-bark was extracted with dichloromethane and the compound was isolated through column chromatography. The compound was identified and characterized by spectroscopic analysis (1H NMR, 13C NMR, IR and MS) and the structure was also confirmed by x-ray crystallography. The anti-plasmodial activity (in vitro) was studied on NF54 Plasmodium falciparum strain (CQS). Cytotoxicity was measured using the MTT assay on HEK239 and HEPG2 cell lines. Docking of Mukaadial acetate was conducted in AutoDock Vina. Structural modifications were conducted in UCSF Chimera and molecular interactions examined in LigPlot. Results: The compound, Mukaadial Acetate showed appreciable inhibition (IC50 0.44±0.10 µg/ml) of the parasite growth and cytotoxicity activity of 0.124±0.109 and 0.199±0.083 (µg/ml) on HEK293 and HEPG2 cells respectively. Molecular docking revealed that Mukaadial Acetate binds to the purine, pyrophosphate and ribose binding sites of the PfHGXPRT with an optimum binding conformation and forms hydrogen bond, steric and hydrophobic interactions with the residues inhabiting the respective binding sites. Conclusion: It is apparent that W. salutaris contains components (including Mukaadial Acetate) that exhibit antimalarial activity. This study scientifically validates the use of this plant in folk medicine.

Keywords: plasmodium falciparum, molecular docking, antimalarial activity, PfHGXPRT, Warburgia salutaris, mukaadial acetate

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Authors: Sobhy Fathy A. Hashesh

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The study was carried out in the Elementary Classes of Andalus Private Schools, girls section using control and experimental groups formed by Random Assignment Strategy. The study aimed at investigating the effect of Al-Andalus Fused Curriculum (AFC) model of learning and the effect of separate subjects’ approach on the development of students’ conceptual learning and skills acquiring. The society of the study composed of Al-Andalus Private Schools, elementary school students, Girls Section (N=240), while the sample of the study composed of two randomly assigned groups (N=28) with one experimental group and one control group. The study followed the quantitative and qualitative approaches in collecting and analyzing data to investigate the study hypotheses. Results of the study revealed that there were significant statistical differences between students’ conceptual learning and skills acquiring for the favor of the experimental group. The study recommended applying this model on different educational variables and on other age groups to generate more data leading to more educational results for the favor of students’ learning outcomes.

Keywords: AFC, STEAM, lego education, Al-Andalus fused curriculum, mechatronics

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Authors: Zhuoran Shan, Li Wan, Xianchun Zhang

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With an increasing trend of regionalization and polycentricity in Chinese contemporary big cities, “sub-region life circle” turns to be an effective method on rational organization of urban function and spatial structure. By the method of questionnaire, network big data, route inversion on internet map, GIS spatial analysis and logistic regression, this article makes research on characteristic and formation mechanism of “sub-region life circle” based on human high-probability daily activity in Chinese big cities. Firstly, it shows that “sub-region life circle” has been a new general spatial sphere of residents' high-probability daily activity and mobility in China. Unlike the former analysis of the whole metropolitan or the micro community, “sub-region life circle” has its own characteristic on geographical sphere, functional element, spatial morphology and land distribution. Secondly, according to the analysis result with Binary Logistic Regression Model, the research also shows that seven factors including land-use mixed degree and bus station density impact the formation of “sub-region life circle” most, and then analyzes the index critical value of each factor. Finally, to establish a smarter “sub-region life circle”, this paper indicates that several strategies including jobs-housing fit, service cohesion and space reconstruction are the keys for its spatial organization optimization. This study expands the further understanding of cities' inner sub-region spatial structure based on human daily activity, and contributes to the theory of “life circle” in urban's meso-scale.

Keywords: sub-region life circle, characteristic, formation mechanism, human activity, spatial structure

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Authors: Yi-Hsiang Pan, Chen-Hui Huang, Ching-Hsiang Chen, Wei-Ting Hsu

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The purposes of the study were to explore the students' learning effect of physical education curriculum between merging Teaching Personal and Social Responsibility (TPSR) with sport education model and TPSR with traditional teaching model, which these learning effects included sport self-efficacy, sport enthusiastic, group cohesion, responsibility and game performance. The participants include 3 high school physical education teachers and 6 physical education classes, 133 participants with experience group 75 students and control group 58 students, and each teacher taught an experimental group and a control group for 16 weeks. The research methods used questionnaire investigation, interview, focus group meeting. The research instruments included personal and social responsibility questionnaire, sport enthusiastic scale, group cohesion scale, sport self-efficacy scale and game performance assessment instrument. Multivariate Analysis of covariance and Repeated measure ANOVA were used to test difference of students' learning effects between merging TPSR with sport education model and TPSR with traditional teaching model. The findings of research were: 1) The sport education model with TPSR could improve students' learning effects, including sport self-efficacy, game performance, sport enthusiastic, group cohesion and responsibility. 2) The traditional teaching model with TPSR could improve students' learning effect, including sport self-efficacy, responsibility and game performance. 3) the sport education model with TPSR could improve more learning effects than traditional teaching model with TPSR, including sport self-efficacy, sport enthusiastic,responsibility and game performance. 4) Based on qualitative data about learning experience of teachers and students, sport education model with TPSR significant improve learning motivation, group interaction and game sense. The conclusions indicated sport education model with TPSR could improve more learning effects in physical education curriculum. On other hand, the curricular projects of hybrid TPSR-Sport Education model and TPSR-Traditional Teaching model are both good curricular projects of moral character education, which may be applied in school physical education.

Keywords: character education, sport season, game performance, sport competence

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Authors: Shweta Sinha, Mukesh Doble, Manju S. L.

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Pyrazole scaffold is an important group of compound in heterocyclic chemistry and is found to possess numerous uses in chemistry. Pyrazole derivatives are also known to possess important biological activities including antitumor, antimicrobial, antiviral, antifungal, anticancer and anti-inflammatory. Inflammation is associated with pain, allergy and asthma. Leukotrienes are mediators of various inflammatory and allergic disorders. 5-Lipoxygenase (5-LOX) is an important enzyme involved in the biosynthesis of leukotrienes and metabolism of arachidonic acid (AA) and thus targeted for anti-inflammation. In vitro inhibitory activity of pyrazol-3-yl thiazole 4-carboxylic acid derivatives is tested against enzyme 5-LOX. Most of these compounds exhibit good inhibitory activity against this enzyme. Binding mode study of these compounds is determined by computational tool. Further experiments are being done to understand the mechanism of action of these compounds in inhibiting this enzyme. To conclude, these compounds appear to be a promising target in drug design against 5-LOX.

Keywords: inflammation, inhibition, 5-lipoxygenase, pyrazole

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Authors: Daniel A. Walzer

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As the options for course delivery and development expand, plenty of misconceptions still exist concerning e-learning and online course delivery. Classroom instructors often discuss pedagogy, methodologies, and best practices regarding teaching from a singular, traditional in-class perspective. As more professors integrate online, blended, and hybrid courses into their dossier, a clearly defined rubric for gauging online course delivery is essential. The transition from a traditional learning structure towards an updated distance-based format requires careful planning, evaluation, and revision. This paper examines how new media stimulates reflective practice and guided inquiry to improve pedagogy, engage interdisciplinary collaboration, and supply rich qualitative data for future research projects in media arts disciplines.

Keywords: action research, inquiry, new media, reflection

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Authors: T. E. Tshikalange, B. C. Mophuting

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Traditional medicine often consists of complex ingredients prepared from a mixture of plant species. These herbal mixtures are used in the treatment of various ailments such as sexually transmitted diseases including HIV. The present study was carried out to determine the biological activities of the herbal mixture used traditionally in the treatment of sexually transmitted diseases. This herbal mixture consists of four plant species from families Asteraceae, Bignoniaceae, Fabaceae, and Myrtaceae. Five crude extracts (hexane, dichloromethane, methanol, water and boiled) of the herbal mixture were investigated for anti-gonococcal, anti-inflammatory, and reverse transcriptase activities. The anti-inflammatory activity of the plant extracts was determined by measuring the extract inhibitory effect on the pro-inflammatory enzyme lipoxygenase. The extracts were also tested for anti-HIV activity against recombinant HIV-1 enzyme using non-radioactive HIV-RT colorimetric assay. The boiled extract exhibited good anti-inflammatory activity with an IC₅₀ of 87 µg/ml compared to that of the positive control quercetin (IC₅₀= 92 µg/ml). All the other extracts showed little or no activity. Hexane extract was the only extract that showed reverse transcriptase extract inhibitory effect with an IC₅₀ of 74 µg/ml. Anti-gonococcal and cytotoxicity investigations are underway. The preliminary results support the use of herbal mixture by traditional healers.

Keywords: sexually transmitted diseases, lipoxygenase, anti-inflammatory, herbal mixture

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Authors: Ruchika Malhotra, Megha Khanna

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The development of change prediction models can help the software practitioners in planning testing and inspection resources at early phases of software development. However, a major challenge faced during the training process of any classification model is the imbalanced nature of the software quality data. A data with very few minority outcome categories leads to inefficient learning process and a classification model developed from the imbalanced data generally does not predict these minority categories correctly. Thus, for a given dataset, a minority of classes may be change prone whereas a majority of classes may be non-change prone. This study explores various alternatives for adeptly handling the imbalanced software quality data using different sampling methods and effective MetaCost learners. The study also analyzes and justifies the use of different performance metrics while dealing with the imbalanced data. In order to empirically validate different alternatives, the study uses change data from three application packages of open-source Android data set and evaluates the performance of six different machine learning techniques. The results of the study indicate extensive improvement in the performance of the classification models when using resampling method and robust performance measures.

Keywords: change proneness, empirical validation, imbalanced learning, machine learning techniques, object-oriented metrics

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Authors: Karthik Mittal

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This study performs an unsupervised machine learning analysis to find clusters of related SNPs which highlight biological pathways that are important for the biological mechanisms of breast cancer. Studying genetic variations in isolation is illogical because these genetic variations are known to modulate protein production and function; the downstream effects of these modifications on biological outcomes are highly interconnected. After extracting the SNPs and their effect on different types of breast cancer using the MRBase library, two unsupervised machine learning clustering algorithms were implemented on the genetic variants: a k-means clustering algorithm and a hierarchical clustering algorithm; furthermore, principal component analysis was executed to visually represent the data. These algorithms specifically used the SNP’s beta value on the three different types of breast cancer tested in this project (estrogen-receptor positive breast cancer, estrogen-receptor negative breast cancer, and breast cancer in general) to perform this clustering. Two significant genetic pathways validated the clustering produced by this project: the MAPK signaling pathway and the connection between the BRCA2 gene and the ESR1 gene. This study provides the first proof of concept showing the importance of unsupervised machine learning in interpreting GWAS summary statistics.

Keywords: breast cancer, computational biology, unsupervised machine learning, k-means, PCA

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Authors: Thilivhali Emmanuel Tshikalange, Phiwokuhle Mamba

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Ten medicinal plants used traditionally in the treatment of sexually transmitted diseases (STDs) and urinary tract infections (UTIs) were selected from an ethnobotanical database developed in Mpumalanga. The plants were investigated for their antimicrobial activity against five bacterial strains (Escherichia coli, Klebsiella oxytoca, Klebsiella pneumoniae, Neisseria gonorrhoeae and Staphylococcus aureus) and one fungal strain (Candida albicans). Eight of the plants inhibited the growth of all microorganisms at a concentration range of 0.4 mg/ml to 12.5 mg/ml. Acacia karroo showed the most promising antimicrobial activity, with a minimum inhibitory concentration (MIC) of 0.4 mg/ml on Staphylococcus aureus and 0.8 mg/ml on Neisseria gonorrhoeae. All ten plants were further investigated for their antioxidant activities using the DPPH scavenging method. Acacia karroo and Rhoicissus tridentata subsp. cuneifolia showed good antioxidant activity with IC50 values of 0.83 mg/ml and 0.06 mg/ml, respectively. The toxicity of plants was determined using the XTT reduction method against Vero cells. None of the ten plants showed toxicity on the cells. The obtained results confirmed that Acacia karroo and possibly Rhoicissus tridentata subsp. cuneifolia have the potential of being used as antimicrobial agents in the treatment of STDs and UTIs. These results support and validate traditional use of medicinal plants studied.

Keywords: antimicrobial, antioxidant, Neisseria gonorrhoeae, sexually transmitted diseases

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Authors: Anam Gopi

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The undesired torque and flux ripple may occur in conventional direct torque control (DTC) induction motor drive. DTC can improve the system performance at low speeds by continuously tuning the regulator by adjusting the Kp, Ki values. In this Teaching Learning Based Optimization (TLBO) is proposed to adjust the parameters (Kp, Ki) of the speed controller in order to minimize torque ripple, flux ripple, and stator current distortion. The TLBO based PI controller has resulted is maintaining a constant speed of the motor irrespective of the load torque fluctuations.

Keywords: teaching learning based optimization, direct torque control, PI controller

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Authors: Gauravi Agarkar, Mahendra Rai

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Endophytic fungi from medicinal plants are important source of numerous pharmacologically important compounds. In the present investigation, the endophytic fungi were isolated from three medicinal plants; Andrographis paniculata, Rauwolfia serpentina and Tridax procumbens. Endophytic Colletotrichum sp. were identified on the basis of cultural and morphological characteristics as well as internal transcribed spacer (ITS) sequence analysis. Antibacterial and antifungal activity of the ethyl acetate and methanol extract of endophytic Colletotrichum sp. was evaluated against seven different human pathogenic bacteria and six Candida sp. The extracts were effective and showed significant activity against all the test pathogens. In case of yeast Candida, the combined effect of extracts and standard antibiotic was enhanced greatly showing synergistic activity. Further, the extracts were assayed for Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal/Fungicidal Concentration (MBC/MFC) where, MIC values were in the range of 100-250 μg/ml. These results suggest that the endophytic Colletotrichum sp. isolated from the medicinal plants are capable of producing promising antimicrobial metabolites.

Keywords: antimicrobial, colletotrichum, endophytic fungi, medicinal plants

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Authors: Pinar Ercan, Sedef N. El

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The goals of this study were to determine the total anthocyanin and procyanidin contents and their in vitro bioaccessibilities of apple, red grape and cinnamon by a static in vitro digestion method reported by the COST FA1005 Action INFOGEST, as well as in vitro inhibitory effects of these food samples on starch and lipid digestive enzymes. While the highest total anthocyanin content was found in red grape (164.76 ± 2.51 mg/100 g), the highest procyanidin content was found in cinnamon (6432.54±177.31 mg/100 g) among the selected food samples (p<0.05). The anthocyanin bioaccessibilities were found as 10.23±1 %, 8.23±0.64 %, and 8.73±0.70 % in apple, red grape, and cinnamon, respectively. The procyanidin bioaccessibilities of apple, red grape, and cinnamon were found as 17.57±0.71 %, 14.08±0.74 % and 18.75±1.49 %, respectively. The analyzed apple, red grape and cinnamon showed the inhibitory activity against α-glucosidase (IC50 544.27±21.94, 445.63±15.67, 1592±17.58 μg/mL, respectively), α-amylase (IC50 38.41±7.26, 56.12±3.60, 3.54±0.86 μg/mL, respectively), and lipase (IC50 52.65±2.05, 581.70±54.14, 49.63±2.72 μg/mL, respectively). Red grape sample showed the highest inhibitory activity against α-glucosidase, cinnamon showed the highest inhibitory activity against α-amylase and lipase according to IC50 (concentration of inhibitor required to produce a 50% inhibition of the initial rate of reaction) and Catechin equivalent inhibition capacity (CEIC50) values. This study reported that apple, grape and cinnamon samples can inhibit the activity of digestive enzymes in vitro. The consumption of these samples would be used in conjunction with a low-calorie diet for body weight management.

Keywords: anthocyanin, α-amylase, α-glucosidase, lipase, procyanidin

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Authors: Agis Andriani

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To create an effective teaching condition, the teacher requests the students as the instruction to guide the them interactively in the learning activities in the classroom. This study involves 160 Indonesian students who study English in the university, as participants in the discourse completion test, and ten of them are interviewed. The result shows that when the students response the teacher’s request, it realizes assertives, directives, commisives, expressives, and declaratives. These indicate that the students are active, motivated, and responsive in the learning process, although in the certain condition these responses are to prevent their faces from the shyness of their silence in interaction. Therefore, it needs the teacher’s creativity to give the conducive atmosphere in order to support the students’ participation in learning English.

Keywords: discourse completion test, effective teaching, request, teacher’s creativity

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Authors: Ágoston Nagy

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This paper introduces a method of using unsupervised machine learning to visualize the feature space of a dataset in 2D, in order to find most characteristic segments in the set. After dimension reduction, users can select clusters by manual drawing. Selected clusters are recorded into a data model that is used for later predictions, based on realtime data. Predictions are made with supervised learning, using Gesture Recognition Toolkit. The paper introduces two example applications: a semantic audio organizer for analyzing incoming sounds, and a gesture database organizer where gestural data (recorded by a Leap motion) is visualized for further manipulation.

Keywords: gesture recognition, machine learning, real-time interaction, visualization

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Authors: Tesfaye Mengistu

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This thesis aims to investigate the effectiveness of Reinforcement Learning (RL) for Autonomous Energy Management solutions. The study explores the potential of Model Free RL approaches, such as Monte Carlo RL and Q-learning, to improve energy management by autonomously adjusting energy management strategies to maximize efficiency. The research investigates the implementation of RL algorithms for optimizing energy consumption in a single-agent environment. The focus is on developing a framework for the implementation of RL algorithms, highlighting the importance of RL for enabling autonomous systems to adapt quickly to changing conditions and make decisions based on previous experiences. Moreover, the paper proposes RL as a novel energy management solution to address nations' CO2 emission goals. Reinforcement learning algorithms are well-suited to solving problems with sequential decision-making patterns and can provide accurate and immediate outputs to ease the planning and decision-making process. This research provides insights into the challenges and opportunities of using RL for energy management solutions and recommends further studies to explore its full potential. In conclusion, this study provides valuable insights into how RL can be used to improve the efficiency of energy management systems and supports the use of RL as a promising approach for developing autonomous energy management solutions in residential buildings.

Keywords: artificial intelligence, reinforcement learning, monte carlo, energy management, CO2 emission

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Authors: Naila Safdar, Faria Riasat, Azra Yasmin

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Lychee is an emerging fruit crop in Pakistan. Two famous cultivars of lychee, Gola and Surakhi, were collected from Khanpur Orchard, Pakistan and their whole fruit (including peel, pulp and seed) was investigated for pomological features and therapeutic activities. Both cultivars differ in shape and size with Gola having large size (3.27cm length, 2.36cm width) and more flesh to seed ratio (8.65g). FTIR spectroscopy and phytochemical tests confirmed presence of different bioactive compounds like phenol, flavonoids, quinones, anthraquinones, tannins, glycosides, and alkaloids, in both lychee fruits. Atomic absorption spectroscopy indicated an increased amount of potassium, magnesium, sodium, iron, and calcium in Gola and Surakhi fruits. Small amount of trace metals, zinc and copper, were also detected in lychee fruit, while heavy metals lead, mercury, and nickel were absent. These two lychee cultivars were also screened for antitumor activity by Potato disc assay with maximum antitumor activity shown by aqueous extract of Surakhi seed (77%) followed by aqueous extract of Gola pulp (74%). Antimicrobial activity of fruit parts was checked by agar well diffusion method against six bacterial strains Enterococcus faecium, Enterococcus faecalis, Staphylococcus aureus, Bacillus subtilis, Bacillus sp. MB083, and Bacillus sp. MB141. Highest antimicrobial activity was shown by methanolic extract of Gola pulp (27mm ± 0.70) and seed (19.5mm ± 0.712) against Enterococcus faecalis. DPPH scavenging assay revealed highest antioxidant activity by aqueous extract of Gola peel (98.10%) followed by n-hexane extract of Surakhi peel (97.73%). Results obtained by reducing power assay also corroborated with the results of DPPH scavenging activity.

Keywords: antimicrobial evaluation, antitumor assay, gola, phytoconstituents, reactive oxygen species, Surakhi

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Authors: Akram Hashemi

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This study provided an empirical evidence for learners of elementary level of language proficiency to investigate the potential role of contextualization in vocabulary learning. Prior to the main study, pilot study was performed to determine the reliability and validity of the researcher-made pretest and posttest. After manifesting the homogeneity of the participants, the participants (n = 90) were randomly assigned into three equal groups, i.e., two experimental groups and a control group. They were pretested by a vocabulary test, in order to test participants' pre-knowledge of vocabulary. Then, vocabulary instruction was provided through three methods of visual instruction, the use of context and the use of conventional techniques. At the end of the study, all participants took the same posttest in order to assess their vocabulary gain. The results of independent sample t-test indicated that there is a significant difference between learning vocabulary visually and learning vocabulary contextually. The results of paired sample t-test showed that different teaching strategies have significantly different impacts on learners’ vocabulary gains. Also, the contextual strategy was significantly more effective than visual strategy in improving students’ performance in vocabulary test.

Keywords: vocabulary instruction, explicit instruction, implicit instruction, strategy

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Authors: Murad Almadani, Khalil Abu-Hantash, Xinyu Wang, Herbert Jelinek, Kinda Khalaf

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Gait analysis is used by healthcare professionals as a tool to gain a better understanding of the movement impairment and track progress. In most circumstances, monitoring patients in their real-life environments with low-cost equipment such as cameras and wearable sensors is more important. Inertial sensors, on the other hand, cannot provide enough information on angular dynamics. This research offers a method for tracking 2D joint coordinates using cutting-edge vision algorithms and a single RGB camera. We provide an end-to-end comprehensive deep learning pipeline for marker-less gait parameter estimation, which, to our knowledge, has never been done before. To make our pipeline function in real-time for real-world applications, we leverage the AlphaPose human posture prediction model and a deep learning transformer. We tested our approach on the well-known GPJATK dataset, which produces promising results.

Keywords: gait analysis, human pose estimation, deep learning, real time gait estimation, AlphaPose, transformer

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Authors: Malathi Balakrishnan, Cheng Lee Ooi, Chander Vengadasalam

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The purpose of this study is to explore a case study of trainee teachers’ learning experience on innovating traditional games during the traditional game carnival. It explores issues arising from multiple case studies of trainee teachers learning experiences in innovating traditional games. A qualitative methodology was adopted through observations, semi-structured interviews and reflective journals’ content analysis of trainee teachers’ learning experiences creating and implementing innovative traditional games. Twelve groups of 36 trainee teachers who registered for Sports and Physical Education Management Course were the participants for this research during the traditional game carnival. Semi structured interviews were administrated after the trainee teachers learning experiences in creating innovative traditional games. Reflective journals were collected after carnival day and the content analyzed. Inductive data analysis was used to evaluate various data sources. All the collected data were then evaluated through the Nvivo data analysis process. Inductive reasoning was interpreted based on the Self Determination Theory (SDT). The findings showed that the trainee teachers had positive game participation experiences, game knowledge about traditional games and positive motivation to innovate the game. The data also revealed the influence of themes like cultural significance and creativity. It can be concluded from the findings that the organized game carnival, as a requirement of course work by the Institute of Teacher Training Malaysia, was able to enhance teacher trainers’ innovative thinking skills. The SDT, as a multidimensional approach to motivation, was utilized. Therefore, teacher trainers may have more learning experiences using the SDT.

Keywords: learning experiences, innovation, traditional games, trainee teachers

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Authors: Edicio M. Faller

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The use of technology in the delivery of teaching and learning is vital nowadays especially in education. Computer Assisted Learning Module (CALM) software is the use of computer in the delivery of instruction with a tailored fit program intended for a specific lesson or a set of topics. The CALM software developed in this study is intended to supplement the traditional teaching methods in technical-vocational (TECH-VOC) instruction specifically the Consumer Electronics Servicing course. There are three specific objectives of this study. First is to create a learning enhancement and review materials on the selected lessons. Second, is to computerize the end-of-chapter quizzes. Third, is to generate a computerized mock exam and summative assessment. In order to obtain the objectives of the study the researcher adopted the Agile Model where the development of the study undergoes iterative and incremental process of the Software Development Life Cycle. The study conducted an acceptance testing using a survey questionnaire to evaluate the CALM software. The results showed that CALM software was generally interpreted as very satisfactory. To further improve the CALM software it is recommended that the program be updated, enhanced and lastly, be converted from stand-alone to a client/server architecture.

Keywords: computer assisted learning module, software development life cycle, computerized mock exam, consumer electronics servicing

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Authors: Shayan Mohajer Hamidi

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Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

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Authors: Ira Slabodar

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Autonomous learning in English as a Foreign Language (EFL) refers to the use of target language, learner collaboration and students’ responsibility for their learning. Teachers play a vital role of mediators and facilitators in self-regulated method. Thus, their perception of self-guided practices dictates their implementation of this approach. While research has predominantly focused on inadequate administration of autonomous learning in school mostly due to lack of appropriate teacher training, this study examined whether novice teachers who were exposed to extensive autonomous practices were likely to implement this method in their teaching. Twelve novice teachers were interviewed to examine their perception of learner autonomy and their administration of this method. It was found that three-thirds of the respondents experienced a gap between familiarity with autonomous learning and a favorable attitude to this approach and their deficient integration of self-directed learning. Although learner-related and institution-oriented factors played a role in this gap, it was mostly caused by the respondents’ not being genuinely autonomous. This may be due to indirect exposure rather than explicit introduction of the learner autonomy approach. The insights of this research may assist curriculum designers and heads of teacher training programs to rethink course composition to guarantee the transfer of methodologies into EFL classes.

Keywords: learner autonomy, teacher training, english as a foreign language (efl), genuinely autonomous teachers, explicit instruction, self-determination theory

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Authors: Liliana Villavicencio, Yohn Garcia, Pallavi Singh, Luis Fernando Cruz, Wilfrido Moreno

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Psychophysiological adaptive automation is a concept that combines human physiological data and computer algorithms to create personalized interfaces and experiences for users. This approach aims to enhance human learning by adapting to individual needs and preferences and optimizing the interaction between humans and machines. According to neurosciences, the working memory demand during the student learning process is modified when the student is learning a new subject or topic, managing and/or fulfilling a specific task goal. A sudden increase in working memory demand modifies the level of students’ attention, engagement, and cognitive load. The proposed psychophysiological adaptive automation system will adapt the task requirements to optimize cognitive load, the process output variable, by monitoring the student's brain activity. Cognitive load changes according to the student’s previous knowledge, the type of task, the difficulty level of the task, and the overall psychophysiological state of the student. Scaling the measured cognitive load as low, medium, or high; the system will assign a task difficulty level to the next task according to the ratio between the previous-task difficulty level and student stress. For instance, if a student becomes stressed or overwhelmed during a particular task, the system detects this through signal measurements such as brain waves, heart rate variability, or any other psychophysiological variables analyzed to adjust the task difficulty level. The control of engagement and stress are considered internal variables for the hypermedia system which selects between three different types of instructional material. This work assesses the feasibility of a fuzzy controller to track a student's physiological responses and adjust the learning content and pace accordingly. Using an industrial automation approach, the proposed fuzzy logic controller is based on linguistic rules that complement the instrumentation of the system to monitor and control the delivery of instructional material to the students. From the test results, it can be proved that the implemented fuzzy controller can satisfactorily regulate the delivery of academic content based on the working memory demand without compromising students’ health. This work has a potential application in the instructional design of virtual reality environments for training and education.

Keywords: fuzzy logic controller, hypermedia control system, personalized education, psychophysiological adaptive automation

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Authors: Mihail Calalb

Abstract:

The aim of this research is to identify ways for achieving sustainable conceptual understanding within science lessons. For this purpose, a set of teaching and learning strategies, parts of the theory of visible teaching and learning (VTL), is studied. As a result, a new didactic approach named "learning by being" is proposed and its correlation with educational paradigms existing nowadays in science teaching domain is analysed. In the context of VTL the author describes the main strategies of "learning by being" such as guided self-scaffolding, structuring of information, and recurrent use of previous knowledge or help seeking. Due to the synergy effect of these learning strategies applied simultaneously in class, the impact factor of learning by being on cognitive achievement of students is up to 93 % (the benchmark level is equal to 40% when an experienced teacher applies permanently the same conventional strategy during two academic years). The key idea in "learning by being" is the assumption by the student of cognitive goals. From this perspective, the article discusses the role of student’s personal learning effort within several teaching strategies employed in VTL. The research results emphasize that three mandatory student – related moments are present in each constructivist teaching approach: a) students’ personal learning effort, b) student – teacher mutual feedback and c) metacognition. Thus, a successful educational strategy will target to achieve an involvement degree of students into the class process as high as possible in order to make them not only know the learning objectives but also to assume them. In this way, we come to the ownership of cognitive goals or students’ deep intrinsic motivation. A series of approaches are inherent to the students’ ownership of cognitive goals: independent research (with an impact factor on cognitive achievement equal to 83% according to the results of VTL); knowledge of success criteria (impact factor – 113%); ability to reveal similarities and patterns (impact factor – 132%). Although it is generally accepted that the school is a public service, nonetheless it does not belong to entertainment industry and in most of cases the education declared as student – centered actually hides the central role of the teacher. Even if there is a proliferation of constructivist concepts, mainly at the level of science education research, we have to underline that conventional or frontal teaching, would never disappear. Research results show that no modern method can replace an experienced teacher with strong pedagogical content knowledge. Such a teacher will inspire and motivate his/her students to love and learn physics. The teacher is precisely the condensation point for an efficient didactic strategy – be it constructivist or conventional. In this way, we could speak about "hybridized teaching" where both the student and the teacher have their share of responsibility. In conclusion, the core of "learning by being" approach is guided learning effort that corresponds to the notion of teacher–student harmonic oscillator, when both things – guidance from teacher and student’s effort – are equally important.

Keywords: conceptual understanding, learning by being, ownership of cognitive goals, science learning

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Authors: Justine Jun

Abstract:

This study aims to reveal migrant women English instructors' workplace learning experiences in Canadian post-secondary institutions in Ontario. Although many scholars have conducted research studies on internationally educated teachers and their professional and employment challenges, few studies have recorded migrant women English language instructors’ professional learning and support experiences in post-secondary English language programs in Canada. This study employs a qualitative research paradigm. Mezirow’s Transformative Learning Theory is an essential lens for the researcher to explain, analyze, and interpret the research data. It is a collaborative research project. The researcher and participants cooperatively create photographic or other artwork data responding to the research questions. Photovoice and arts-informed data collection methodology are the main methods. Research participants engage in the study as co-researchers and inquire about their own workplace learning experiences, actively utilizing their critical self-reflective and dialogic skills. Co-researchers individually select the forms of artwork they prefer to engage with to represent their transformative workplace learning experiences about the Canadian workplace cultures that they underwent while working with colleagues and administrators in the workplace. Once the co-researchers generate their cultural artifacts as research data, they collaboratively interpret their artworks with the researcher and other volunteer co-researchers. Co-researchers jointly investigate the themes emerging from the artworks. They also interpret the meanings of their own and others’ workplace learning experiences embedded in the artworks through interactive one-on-one or group interviews. The following are the research questions that the migrant women English instructor participants examine and answer: (1) What have they learned about their workplace culture and how do they explain their learning experiences?; (2) How transformative have their learning experiences been at work?; (3) How have their colleagues and administrators influenced their transformative learning?; (4) What kind of support have they received? What supports have been valuable to them and what changes would they like to see?; (5) What have their learning experiences transformed?; (6) What has this arts-informed research process transformed? The study findings implicate English language instructor support currently practiced in post-secondary English language programs in Ontario, Canada, especially for migrant women English instructors. This research is a doctoral empirical study in progress. This research has the urgency to address the research problem that few studies have investigated migrant English instructors’ professional learning and support issues in the workplace, precisely that of English instructors working with adult learners in Canada. While appropriate social and professional support for migrant English instructors is required throughout the country, the present workplace realities in Ontario's English language programs need to be heard soon. For that purpose, the conceptualization of this study is crucial. It makes the investigation of under-represented instructors’ under-researched social phenomena, workplace learning and support, viable and rigorous. This paper demonstrates the robust theorization of English instructors’ workplace experiences using Mezirow’s Transformative Learning Theory in the English language teacher education field.

Keywords: English teacher education, professional learning, transformative learning theory, workplace learning

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Authors: Amal Khalifa, Nicolas Vana Santos

Abstract:

Steganography has been known for centuries as an efficient approach for covert communication. Due to its popularity and ease of access, image steganography has attracted researchers to find secure techniques for hiding information within an innocent looking cover image. In this research, we propose a novel deep-learning approach to digital image steganography. The proposed method, DeepWaveletFusion, uses convolutional neural networks (CNN) to hide a secret image into a cover image of the same size. Two CNNs are trained back-to-back to merge the Discrete Wavelet Transform (DWT) of both colored images and eventually be able to blindly extract the hidden image. Based on two different image similarity metrics, a weighted gain function is used to guide the learning process and maximize the quality of the retrieved secret image and yet maintaining acceptable imperceptibility. Experimental results verified the high recoverability of DeepWaveletFusion which outperformed similar deep-learning-based methods.

Keywords: deep learning, steganography, image, discrete wavelet transform, fusion

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Authors: R. Yuvakkumar, S. I. Hong

Abstract:

Visible light driven monoclinic α-Bi2O3 photocatalyst was synthesized employing green synthesis method using rambutan peel wastes. 10 ml rambutan extract was added to 50 ml of 0.1M Bi(NO3)3 under stirring at about 80°C for 2 hours. The centrifuged and dried product was calcinated in a muffle furnace at 450°C to get pure α-Bi2O3. The characterized product photocatalytic activity was evaluated employing methyl orange (MeO) as model pollutant with 10 mg l-1 concentration at pH 7. The obtained product optical absorption edges located at 484 nm clearly revealed the photocatalyst excitation by visible light irradiation. The obtained yellow color photocatalyst accord with its strong absorption spectrum revealed the visible light absorption due to the band gap transition. The band gap energy of α-Bi2O3 was estimated to be 2.81 eV indicating the absorption of α-Bi2O3 in visible light region. The photocatalytic results of MeO degradation revealed that green synthesized Bi2O3 can effectively degrade 92% MeO within 240 min under visible light (>400 nm), which is slightly increased to that of chemically synthesized Bi2O3 (90%).

Keywords: green synthesis, bismuth oxide, photocatalytic activity, nano

Procedia PDF Downloads 198

Authors: Hye Kyung Kim, Myung-Gyou Kim, Kang-Hyun Leem

Abstract:

It has been reported that deer antler extract has bone-strengthening activity and effectively used in bone diseases therapy. However, little is known about the cellular and molecular mechanism of this effect. The upper section, mid section, and base of the antler has been known to exhibit different biological properties. Present study investigated the effects of these three parts of deer antler extracts on bone formation and resorption. The effects of deer antler extracts (DH) on bone formation were determined by cell proliferation, alkaline phosphatase (ALP) activity, collagen synthesis, and mineralization in human osteoblastic MG-63 cells. The effect on bone resorption was determined by osteoclastogenesis from bone marrow-derived precursor cells driven by RANKL. Ethanol extracts of DH (50 ~ 100 µg/ml) dose-dependently increased cell proliferation, and upper part increased the cell proliferation by 118.4% while mid and base parts increased proliferation by 107.8% and 102.3%, respectively. ALP activity was significantly increased by upper part of the DH treatment. After enhancement of ALP activity, significant augmentation of collagen synthesis and calcification assessed by Sirus red and Alzarin red staining, respectively, was observed in upper part of the DH treatment. The effect of DH on bone resorption was not observed in all three parts of the DH. These results could provide a mechanistic explanation for the bone-strengthening effects of DH.

Keywords: alkaline phosphatase, collagen synthesis, deer antler, osteoblastic MG-63 cells

Procedia PDF Downloads 299