Search results for: activity learning

Authors: Subramaniam Chandran, A. Geetha

Abstract:

This paper addresses three issues: how to prepare the instructional design for imparting English language skill from inter-disciplinary self-learning material; how the disadvantaged students are benefited from such kind of language skill imparted through m-learning; and how do m-learners perform better than the other learners. This paper examines these issues through an experimental study conducted among the distance learners enrolled in a preparatory program for bachelor’s degree. This program is designed for the disadvantaged learners especially for the school drop-outs to qualify to pursue graduate program through distant education. It also explains how mobile learning helps them to enhance their capacity in learning despite their rural background and other disadvantages. In India, nearly half of the students enrolled in schools do not complete their study. The pursuance of higher education is very low when compared with developed countries. This study finds a significant increase in their learning capacity and mobile learning seems to be a viable alternative where the conventional system could not reach the disadvantaged learners. Improving the English language skill is one of the reasons for such kind of performance. Exercises framed from the relevant self-learning material for enhancing English language skill not only improves language skill but also widens the subject-knowledge. This paper explains these issues out of the study conducted among the disadvantaged learners.

Keywords: English language skill, disadvantaged learners, distance education, m-learning

Procedia PDF Downloads 406

Authors: Liza Meutia Sari, Gus Permana Subita, Elza Ibrahim Auerkari

Abstract:

Background: Many herbs have been discovered to be potential sources of anticancer drugs. Biji Pinang or areca nut (Areca catechu Linn.) has a high content of phenolics and flavonoids, and which is related to antioxidant activity. However, data on its effects on oral squamous cell carcinoma is not available. Objectives: Identification of the cytotoxicity and apoptosis activity in HSC-2 and HSC-3. Methods: The areca nut was extracted by ethanol 96%, MTS assay and apoptosis activity with flow cytometry. Results: The extract of areca nut showed higher toxicity on HSC-3 cell compared to HSC-2. The IC₅₀ of HSC-3 was 164.06 μg/ml vs. 629.50 μg/ml in HSC-2. There was an increase in late apoptosis percentage after 24 and 48 hours in HSC-2. There was a significant increase in early apoptosis percentage after 24 hours and late in 48 hours in HSC-3. Conclusion: The antioxidant activity of the extract of areca nut might be associated with the selective cytotoxicity on HSC-2 and HSC-3. Apoptosis is the major cell death mechanism involved. The areca nut may play an important role in anticancer herb medicine.

Keywords: areca nut, cytotoxicity, apoptosis, oral carcinoma

Procedia PDF Downloads 211

Authors: Panagiotis Kosmas, Panayiotis Zaphiris

Abstract:

Embodied Cognition (EC) as a learning paradigm is based on the idea of an inseparable link between body, mind, and environment. In recent years, the advent of theoretical learning approaches around EC theory has resulted in a number of empirical studies exploring the implementation of the theory in education. This systematic literature overview identifies the mainstream of EC research and emphasizes on the implementation of the theory across learning environments. Based on a corpus of 43 manuscripts, published between 2013 and 2017, it sets out to describe the range of topics covered under the umbrella of EC and provides a holistic view of the field. The aim of the present review is to investigate the main issues in EC research related to the various learning contexts. Particularly, the study addresses the research methods and technologies that are utilized, and it also explores the integration of body into the learning context. An important finding from the overview is the potential of the theory in different educational environments and disciplines. However, there is a lack of an explicit pedagogical framework from an educational perspective for a successful implementation in various learning contexts.

Keywords: embodied cognition, embodied learning, education, technology, schools

Procedia PDF Downloads 127

Authors: Seyed-Ali Sadegh-Zadeh, Kaveh Kavianpour, Hamed Atashbar, Elham Heidari, Saeed Shiry Ghidary, Amir M. Hajiyavand

Abstract:

Evaluation metrics play a critical role in assessing the performance of machine learning models. In this review paper, we provide a comprehensive overview of performance measurement approaches for machine learning models. For each category, we discuss the most widely used metrics, including their mathematical formulations and interpretation. Additionally, we provide a comparative analysis of performance measurement approaches for metric combinations. Our review paper aims to provide researchers and practitioners with a better understanding of performance measurement approaches and to aid in the selection of appropriate evaluation metrics for their specific applications.

Keywords: evaluation metrics, performance measurement, supervised learning, unsupervised learning, reinforcement learning, model robustness and stability, comparative analysis

Procedia PDF Downloads 45

Authors: Frederik Calsius, Mirela Popa, Alexia Briassouli

Abstract:

In the field of machine learning, it is common practice to use benchmark datasets to prove the working of a method. The domain of action recognition in videos often uses datasets like Kinet-ics, Something-Something, UCF-101 and HMDB-51 to report results. Considering the properties of the datasets, there are no datasets that focus solely on very short clips (2 to 3 seconds), and on highly-similar fine-grained actions within one specific domain. This paper researches how current state-of-the-art action recognition methods perform on a dataset that consists of highly similar, fine-grained actions. To do so, a dataset of skateboarding tricks was created. The performed analysis highlights both benefits and limitations of state-of-the-art methods, while proposing future research directions in the activity recognition domain. The conducted research shows that the best results are obtained by fusing RGB data with OpenPose data for the Temporal Shift Module.

Keywords: activity recognition, fused deep representations, fine-grained dataset, temporal modeling

Procedia PDF Downloads 211

Authors: Derek Brandon G. Yu, Clyde Vincent O. Pilapil, Christine F. Peña

Abstract:

College students of Cebu province have been indoors since March 2020, and a challenge encountered is the sudden shift from face to face to online learning and with the lack of empirical data on online learning on Higher Education Institutions (HEIs) in the Philippines. Sentiments on face to face and online learning will be collected from University of San Carlos (USC), School of Arts and Sciences (SAS) students regarding Mathematics in the Modern World (MMW), a General Education (GE) course. Natural Language Processing with machine learning algorithms will be used to classify the sentiments of the students. Results of the research study are the themes identified through topic modelling and the overall sentiments of the students in USC SAS

Keywords: natural language processing, online learning, sentiment analysis, topic modelling

Procedia PDF Downloads 223

Authors: Akrpoum Souad, Lalaoui Korrichi

Abstract:

Vicia faba L.,Vaccinium macrocarpon, Punica granatum, Lavandula officinalis, Artemisia absinthium, Linum capitatum and Camellia sinensis were frequently used in our alimentation. In this study, we have tested the antimicrobial activity of their ethanolic and methanolic extracts on some pathogen bacteria, then their ability to in vivo inhibit the growth of Strepcoccus pneumonia. The phytochemical screening has given the composition of the most active extracts. According to the obtained results, the ethanolic extract of Lavendula. officinalis and A absinthium has shown an inhibition of all the tested strains of becteria3. The ethanolic extract of L. officinalis has given the highest activity against S. pneumoniae, followed by the methanolic extract of C. sinensis 1, 2 and P. granatum. The phytochemical screening showed that the most active extracts contained mainly naturels compounds.

Keywords: plants, extracts, antimicrobial activity, streptococcus pneumoniae, phytochemical screening

Procedia PDF Downloads 502

Authors: PB Venkataraman

Abstract:

Most of the real-life problems are ill-structured. They do not have a single solution but many competing solutions. The solution paths are non-linear and ambiguous, and the problem definition itself is many times a challenge. Students of professional education learn to solve such problems through internships. The current pandemic situation has constrained on-site internship opportunities; thus the students have no option but to pursue this learning online. This research assessed the learning gain of four undergraduate students in engineering as they undertook an online internship in an organisation over a period of eight weeks. A clinical interview at the end of the internship provided the primary data to assess the team’s problem-solving skills using a tested rubric. In addition to this, change in their learning attitudes were assessed through a pre-post study using a repurposed CLASS instrument for Electrical Engineering. Analysis of CLASS data indicated a shift in the sophistication of their learning attitude. A learning engagement survey adopting a 6-point Likert scale showed active participation and motivation in learning. We hope this new research will stimulate educators to exploit online internships even beyond the time of pandemic as more and more business operations are transforming into virtual.

Keywords: ill-structured problems, learning attitudes, internship, assessment, student engagement

Procedia PDF Downloads 191

Authors: Siti Helmyati, Euis Nurdiyawati, Joko Susilo, Endri Yuliati, Siti Fadhilatun Nashriyah, Kurnia Widyastuti

Abstract:

Background: Iron fortification is one of the most effective and sustainable strategies to overcome anemia. It contradictively, has negative effect on gut microbiota balance. Pathogenic bacteria required iron for their growth. The iron source have greatly affect iron absorption in the intestine. Probiotic can inhibit the growth of pathogen. Lactobacillus plantarum Dad 13, Indonesian local isolate provides many benefits for health while fructo-oligosaccharides (FOS) provides selective substrates for probiotics’ growth. Objective: To determine the effect of iron fortification (NaFeEDTA and FeSO4) on antibacterial activity of synbiotic fermented milk. Methods: The antibacterial activity test was performed using the disc diffusion method. Paper discs were soaked in three kinds of synbiotic fermented milk, which are: 1) fortified with NaFeEDTA, 2) FeSO4 and 3) control. Escherichia coli was inoculated on nutrient agar medium. The ability of inhibition was shown by the formation of clear zone around the paper disc and measured in diameter (mm). Results: Synbiotic fermented milk fortified with iron (either NaFeEDTA or FeSO4) had antibacterial activity against Escherichia coli with diameter of clear zone were 6.53 mm and 12.3 mm, respectively (p<0.05). Compared to control (10.73 mm), synbiotic fermented milk fortified with FeSO4 had similar antibacterial activity (p>0.05). Conclusions: In vitro, synbiotic fermented milk fortified with NaFeEDTA and FeSO4 had different antibacterial activity against Escherichia coli. Iron fortification compound affected the antibacterial activity of synbiotic fermented milk.

Keywords: lactobacillus plantarum Dad 13, FOS, NaFeEDTA, FeSO4, antibacterial activity

Procedia PDF Downloads 534

Authors: Christodoulou Christos, Politis Anastasios

Abstract:

A large majority of users favoured to wireless LAN connection since it was so simple to use. A wireless network can be the target of numerous attacks. Class hijacking is a well-known attack that is fairly simple to execute and has significant repercussions on users. The statistical flow analysis based on machine learning (ML) techniques is a promising categorization methodology. In a given dataset, which in the context of this paper is a collection of components representing frames belonging to various flows, machine learning (ML) can offer a technique for identifying and characterizing structural patterns. It is possible to classify individual packets using these patterns. It is possible to identify fraudulent conduct, such as class hijacking, and take necessary action as a result. In this study, we explore a way to use machine learning approaches to thwart this attack.

Keywords: wireless lan, quality of service, machine learning, class hijacking, EDCA remapping

Procedia PDF Downloads 40

Authors: Pieter Conradie, M. Marina Moller

Abstract:

Web 2.0 Internet-based technologies have intruded all aspects of human life. Presently, this phenomenon is especially evident in the educational context, with increased disruptive Web 2.0 technology infusions dramatically changing educational practice. The most prominent of these Web 2.0 intrusions can be identified as Massive Open Online Courses (Coursera, EdX), video and photo sharing sites (Youtube, Flickr, Instagram), and Web 2.0 online tools utilize to create Personal Learning Environments (PLEs) (Symbaloo (aggregator), Delicious (social bookmarking), PBWorks (collaboration), Google+ (social networks), Wordspress (blogs), Wikispaces (wiki)). These Web 2.0 technologies have supported the realignment from a teacher-based pedagogy (didactic presentation) to a learner-based pedagogy (problem-based learning, project-based learning, blended learning), allowing greater learner autonomy. No longer is the educator the source of knowledge. Instead the educator has become the facilitator and mediator of the learner, involved in developing learner competencies to support life-long learning (continuous learning) in the 21st century. In this study, the self-regulated learning skills of thirty first-year university learners were explored by utilizing the Online Self-regulated Learning Questionnaire. Implementing an action research method, an intervention was affected towards improving the self-regulation skill set of the participants. Statistical significant results were obtained with increased self-regulated learning proficiency, positively impacting learner performance. Goal setting, time management, environment structuring, help seeking, task (learning) strategies and self-evaluation skills were confirmed as determinants of improved learner success.

Keywords: andragogy, online self-regulated learning questionnaire, self-regulated learning, web 2.0

Procedia PDF Downloads 399

Authors: Sergio Andres Rojas, Julian Benavides Franco, Juan Tomas Sayago

Abstract:

An increasing amount of research demonstrates how market mood affects financial markets, but their primary goal is to demonstrate how Trump's tweets impacted US interest rate volatility. Following that lead, this work evaluates the effect that Trump's tweets had during his presidency on local and international stock markets, considering not just volatility but the direction of the movement. Three indexes for Trump's tweets were created relating his activity with movements in the S&P500 using natural language analysis and machine learning algorithms. The indexes consider Trump's tweet activity and the positive or negative market sentiment they might inspire. The first explores the relationship between tweets generating negative movements in the S&P500; the second explores positive movements, while the third explores the difference between up and down movements. A pseudo-investment strategy using the indexes produced statistically significant above-average abnormal returns. The findings also showed that the pseudo strategy generated a higher return in the local market if applied to intraday data. However, only a negative market sentiment caused this effect on daily data. These results suggest that the market reacted primarily to a negative idea reflected in the negative index. In the international market, it is not possible to identify a pervasive effect. A rolling window regression model was also performed. The result shows that the impact on the local and international markets is heterogeneous, time-changing, and differentiated for the market sentiment. However, the negative sentiment was more prone to have a significant correlation most of the time.

Keywords: market sentiment, Twitter market sentiment, machine learning, natural dialect analysis

Procedia PDF Downloads 53

Authors: Heny Hartono, Cecilia Titiek Murniati

Abstract:

The pandemic has given teachers and students no other choice but having full online learning. In such an emergency situation as the time of the covid-19 pandemic, the application of LMS (Learner Management System) in higher education is the most reasonable solution for students and teachers. In fact, the online learning requires all elements of a higher education systems, including the human resources, infrastructure, and supporting systems such as the application, server, and stable internet connection. The readiness of the higher education institution in preparing the online system may secure those who are involved in the online learning process. It may also result in students’ self-efficacy in online learning. This research aimed to investigate how students perceive their self-efficacy in online English learning, especially in speaking classes which is considered as a productive language skill. This research collects qualitative data with narrative inquiry involving 25 students of speaking classes as the respondents. The results of this study show that students perceive their self-efficacy in speaking online classes as not very high.

Keywords: self-efficacy, online learning, speaking class, college students, e-learning

Procedia PDF Downloads 86

Authors: Nadjib Melkemi, Salah Belaidi

Abstract:

Quantitative Structure-Activity Relationship (QSAR) studies have been performed on nineteen molecules of 1,2-dithiole-3-thione analogues. The compounds used are the potent inducers of enzymes involved in the maintenance of reduced glutathione pools as well as phase-2 enzymes important to electrophile detoxication. A multiple linear regression (MLR) procedure was used to design the relationships between molecular descriptor and detoxication properties of the 1,2-dithiole-3-thione derivatives. The predictivity of the model was estimated by cross-validation with the leave-one-out method. Our results suggest a QSAR model based of the following descriptors: qS2, qC3, qC5, qS6, DM, Pol, log P, MV, SAG, HE and EHOMO for the specific activity of quinone reductase; qS1, qS2, qC3, qC4, qC5, qS6, DM, Pol, logP, MV, SAG, HE and EHOMO for the production of growth hormone. To confirm the predictive power of the models, an external set of molecules was used. High correlation between experimental and predicted activity values was observed, indicating the validation and the good quality of the derived QSAR models.

Keywords: QSAR, quinone reductase activity, production of growth hormone, MLR

Procedia PDF Downloads 328

Authors: Jianhua Wang, Ying Zhou, Xi Zhang

Abstract:

To establish the influential mechanism of learning engagement on interpreter’s performance, the present study submitted a questionnaire to a sample of 927 English major students with 804 valid ones and used the structural equation model as the basis for empirical analysis and statistical inference on the sample data. In order to explore the mechanism for interpreting learning engagement on student interpreters’ performance, a path model of interpreting processes with three variables of ‘input-environment-output’ was constructed. The results showed that the effect of each ‘environment’ variable on interpreting ability was different from and greater than the ‘input’ variable, and learning engagement was the greatest influencing factor. At the same time, peer interaction on interpreting performance has significant influence. Results suggest that it is crucial to provide effective guidance for optimizing learning engagement and interpreting teaching research by both improving the environmental support and building the platform of peer interaction, beginning with learning engagement.

Keywords: learning engagement, interpreting performance, interpreter training, English major students

Procedia PDF Downloads 185

Authors: M. Ouassaf, S. Belaidi

Abstract:

Aromatase is an estrogen biosynthetic enzyme belonging to the cytochrome P450 family, which catalyzes the limiting step in the conversion of androgens to estrogens. As it is relevant for the promotion of tumor cell growth. A set of thirty 1,2,3-triazole derivatives was used in the quantitative structure activity relationship (QSAR) study using regression multiple linear (MLR), We divided the data into two training and testing groups. The results showed a good predictive ability of the MLR model, the models were statistically robust internally (R² = 0.982) and the predictability of the model was tested by several parameters. including external criteria (R²pred = 0.851, CCC = 0.946). The knowledge gained in this study should provide relevant information that contributes to the origins of aromatase inhibitory activity and, therefore, facilitates our ongoing quest for aromatase inhibitors with robust properties.

Keywords: aromatase inhibitors, QSAR, MLR, 1, 2, 3-triazole

Procedia PDF Downloads 100

Authors: Cheeze Janito, Crisly Dawang

Abstract:

It is important to determine the personality traits that exist in the workplace and the contribution of these personality traits in the staff’s daily work routines; a sedentary lifestyle is harmful to one’s health. This study reports the personality traits of the University of Southern Mindanao, Kabacan, Philippines, non-teaching staff, the physical activity involvement of the non-teaching staff, and the big five personality traits that shape the relationship of university non-teaching staff in engaging physical activities. A quantitative method approach, which comprised a three-part questionnaire, was used to collect the data. The fifty non-teaching staff complete the survey. The results revealed that among the big five personality traits, the university non-teaching staff scored higher in agreeableness as revealed, that there was a commonality among the respondents’ traits of consideration to the feelings of the co-workers in observance to not being rude and vividly display of respect to co-workers and workplace and scored least in the personality trait of neuroticism. The study also reported that the university non-teaching staff's main physical activity was house chores as a prime physical exercise in which respondents reported a physical activity frequency of once to twice a week; thus, this study reported that the respondents are less engaged in doing physical activities. Further, the relationship of personality traits and the physical activity of the non-teaching staff gained a p-value of .596 that indicates there is no significant relationship between the two variables, the personality trait and physical activities. This study recommends the tight promotion of staff in engaging in physical activity of at least one hundred fifty minutes of moderate-intensity activity each week. Added to this, the use of different platforms containing physical exercise literacy and the benefits of physical exercise for the holistic development of the university community.

Keywords: university staff, physical fitness, personality traits, physical activity

Procedia PDF Downloads 174

Authors: Vincenzo Capalbo, Gianpaolo Ghiani, Emanuele Manni

Abstract:

Global e-commerce sales have reached unprecedented levels in the past few years. As this trend is only predicted to go up as we continue into the ’20s, new challenges will be faced by companies when planning and controlling e-commerce logistics. In this paper, we survey the related literature on Optimization and Machine Learning as well as on combined methodologies. We also identify the distinctive features of next-generation planning algorithms - namely scalability, model-and-run features and learning capabilities - that will be fundamental to cope with the scale and complexity of logistics in the next decade.

Keywords: e-commerce, hardware acceleration, logistics, machine learning, mixed integer programming, optimization

Procedia PDF Downloads 220

Authors: Farhad Azadi, Mohammad Mahdi Mohammadi, Mohsen Vahedi, Zahra Mahdiin

Abstract:

Context: The aging population is growing all over the world and maintaining physical activity is essential for healthy aging. However, fear of falling is a major obstacle to physical activity among the elderly. The aim of this study is to investigate and compare the relationship between fear of falling and physical activity in Iranian urban and rural elderly. Research Aim: The main aim of this cross-sectional analytical study is to investigate and compare the relationship between fear of falling and physical activity in Iranian rural and urban elderly. Methodology: The study used simple non-probability sampling to select 350 participants aged 60 years and older from rural and urban areas of Konarak, Sistan and Baluchistan provinces in Iran. The Persian versions of the Falls Efficacy Scale - International, Rapid Physical Activity Assessment, Activities of Daily Living, and Instrumental Activities of Daily Living questionnaires were used to assess fear of falling and physical activity. The data were analyzed using Pearson correlation tests. Findings: The study found a statistically significant negative correlation between fear of falling and physical activity, as measured by ADL, IADL, and RAPA1(aerobic ), in all elderly and rural and urban elderly (p<0.001). Fear of falling was higher in rural areas, while physical activity levels measured by ADL and RAPA1 were higher in urban areas. No significant difference was found between the two groups in IADL and RAPA2 (strength and flexibility) scores. Theoretical Importance: This study highlights the importance of considering the fear of falling as a significant obstacle to proper physical activity, especially among the elderly living in rural areas. Furthermore, the study provides insight into the difference between rural and urban elderly people in terms of fear of falling and physical activity. Data Collection and Analysis Procedures: Data was collected through questionnaires and analyzed using Pearson correlation tests. Questions Addressed: The study attempted to answer the following questions: Is there a relationship between fear of falling and physical activity in Iranian urban and rural elderly people? Is there a difference in fear of falling and physical activity between rural and urban elderly? Conclusion: Fear of falling is a major obstacle to physical activity among the elderly, especially in rural areas. The study found a significant negative correlation between fear of falling and physical activity in all elderly and rural and urban elderly. In addition, urban and rural elderly have differences in aerobic activity levels, but they do not differ in terms of flexibility and strength. Therefore, proper interventions are required to ensure that the elderly can maintain physical activity, especially in rural and deprived areas.

Keywords: aged, fear of falling, physical activity, urban population, rural population

Procedia PDF Downloads 58

Authors: Chinaza Uleanya, Martin Duma, Bongani Gamede

Abstract:

The study investigated learning challenges experienced by students in universities situated in developing sub-Saharan African countries using selected universities in South Africa and Nigeria. Questionnaires were administered to 2,335 randomly selected students from selected universities in South Africa and Nigeria. The outcome of the study shows that six common learning challenges are visible in developing sub-Sahara African universities. The causes of these learning challenges cut across the failure in responsibilities of the various stakeholders in the field of education and the effects are monumental both to the students and society. This paper suggests recommendations to university administrators, education policy makers and implementers on the need to take education more seriously, to review and implement appropriate policies, and to ensure provision of quality education through the supply of adequate amenities and other motivating factors.

Keywords: learning, challenges, learning challenges, access with success, participatory access

Procedia PDF Downloads 279

Authors: Eyasu Gemech, Kassa Michael, Mulugeta Atnafu

Abstract:

A non-equivalent group's quasi-experiment research was conducted at Wolkite University to investigate MATLAB supported learning and students' conceptual understanding in learning Applied Mathematics II using four different comparative instructional approaches: MATLAB supported traditional lecture method, MATLAB supported collaborative method, only collaborative method, and only traditional lecture method. Four intact classes of mechanical engineering groups 1 and 2, garment engineering and textile engineering students were randomly selected out of eight departments. The first three departments were considered as treatment groups and the fourth one 'Textile engineering' was assigned as a comparison group. The departments had 30, 29, 35 and 32 students respectively. The results of the study show that there is a significant mean difference in students' conceptual understanding between groups of students learning through MATLAB supported collaborative method and the other learning approaches. Students who were learned through MATLAB technology-supported learning in combination with collaborative method were found to understand concepts of functions of two variables better than students learning through the other methods of learning. These, hence, are informative of the potential approaches universities would follow for a better students’ understanding of concepts.

Keywords: MATLAB supported collaborative method, MATLAB supported learning, collaborative method, conceptual understanding, functions of two variables

Procedia PDF Downloads 257

Authors: Haitham Taha

Abstract:

The cognitive flexibility of 27 asthmatic children with learning difficulties was tested by using the Wisconsin card sorting test (WCST) and compared to the performances of 30 non-asthmatic children who have persistence learning difficulties also. The results revealed that the asthmatic group had poor performance through all the WCST psychometric parameters and especially the preservative errors one. The results were discussed in light of the postulation that poor executive functions and specifically poor cognitive flexibility are in the basis of the learning difficulties of asthmatic children with learning difficulties. Neurophysiologic framework was suggested for explaining the etiology of poor executive functions and cognitive flexibility among children with moderate into severe asthma.

Keywords: asthma, learning disabilities, executive functions, cognitive flexibility, WCST

Procedia PDF Downloads 483

Authors: Nassim Belkacem, Amina Azzam, Dalila Haouchine, Kahina Bennacer, Samira Soufit

Abstract:

Objective: To evaluate the antioxidant activity of the methanolic extract along with the antimicrobial activity of the essential oil of the aerial parts of Rosmarinus officinalis L. collected in the region of Bejaia (northern center of Algeria). Materials and methods: The polyphenols and flavonoids contents of the methanolic extract were measured. The antioxidant activity was evaluated using two methods: the ABTS method and DPPH assay. The antimicrobial activity was studied by the agar diffusion method against five bacterial strains (Three Gram positive strains and two Gram negative strains) and one fungus. Results: The total polyphenol and flavonoid content was about 43.8 mg gallic acid equivalent per gram (GA Eq/g) and 7.04 mg quercetin equivalent per gram (Q Eq/g), respectively. In the ABTS assay, the rosemary extract has shown an inhibition of 98.02% at the concentration of 500ug/ml with a half maximal inhibitory concentration value (IC50) of 194.92ug/ml. The results of DPPH assay have shown that the rosemary extract has an inhibition of 94.67 % with an IC50 value of 17.87ug/ml, which is lower than that of Butylhydroxyanisol (BHA) about 6.03ug/ml and ascorbic acid about 1.24μg/ml. The yield in essential oil of rosemary obtained by hydrodistillation was 1.42%. Based on the determination of the diameter of inhibition, different antimicrobial activity of the essential oil was revealed against the six tested microbes. Escherichia coli from the University Hospital (UH), Streptococcus aureus (UH) and Pseudomonas aeruginosa ATCC have a minimum inhibitory concentration value (MIC) of 62.5µl/ml. However, Bacillus sp (UH) and Staphylococcus aureus ATCC have an MIC value of 125μl/ml. The inhibition zone against Candida sp was about 24 mm. The aromatograms showed that the essential oil of rosemary exercises an antifungal activity more important than the antibacterial one.

Keywords: Rosmarinus officinalis L., maceration, essential oil, antioxidant, antimicrobial activity

Procedia PDF Downloads 501

Authors: Linda Chularojmontri, Seewaboon Sireeratawong, Suvara Wattanapitayakul

Abstract:

Terminalia arjuna Roxb. (family Combretaceae) is commonly known as ‘Sa maw thet’ in Thai. The fruit is used in traditional medicine as natural mild laxatives, carminative and expectorant. Aim of the study: This research aims to study the anti-inflammatory, analgesic and antipyretic activities of Terminalia arjuna extract by using animal models in comparison to the reference drugs. Materials and Methods: The anti-inflammatory study was conducted by two experimental animal models namely ethyl phenylpropionate (EPP)-induced ear edema and carrageenan-induced paw edema. The study of analgesic activity used two methods of pain induction including acetic acid and heat-induced pain. In addition, the antipyretic activity study was performed by induced hyperthermia with yeast. Results: The results showed that the oral administration of Terminalia arjuna extract possessed acute anti-inflammatory effect in carrageenan-induced paw edema. Terminalia arjuna extract showed the analgesic activity in acetic acid-induced writhing response and heat-induced pain. This indicates its peripheral effect by inhibiting the biosynthesis and/or release of some pain mediators and some mechanism through Central nervous system. Moreover, Terminalia arjuna extract at the dose of 1000 and 1500 mg/kg body weight showed the antipyretic activity, which might be because of the inhibition of prostaglandins. Conclusion: The findings of this study indicated that the Terminalia arjuna extract possesses the anti-inflammatory, analgesic and antipyretic activities in animals.

Keywords: analgesic activity, anti-inflammatory activity, antipyretic activity, Terminalia arjuna extract

Procedia PDF Downloads 252

Authors: Dante J. Dorantes-González, Aldrin Balsa-Yepes

Abstract:

Existing learning techniques such as problem-based learning, project-based learning, or case study learning are learning techniques that focus mainly on technical details, but give no specific guidelines on learner’s experience and emotional learning aspects such as arousal salience and valence, being emotional states important factors affecting engagement and retention. Some approaches involving emotion in educational settings, such as social and emotional learning, lack neuroscientific rigorousness and use of specific neurobiological mechanisms. On the other hand, neurobiology approaches lack educational applicability. And educational approaches mainly focus on cognitive aspects and disregard conditioning learning. First, authors start explaining the reasons why it is hard to learn thoughtfully, then they use the method of neurobiological mapping to track the main limbic system functions, such as the reward circuit, and its relations with perception, memories, motivations, sympathetic and parasympathetic reactions, and sensations, as well as the brain cortex. The authors conclude explaining the major finding: The mechanisms of nonconscious learning and the triggers that guarantee long-term memory potentiation. Afterward, the educational framework for practical application and the instructors’ guidelines are established. An implementation example in engineering education is given, namely, the study of tuned-mass dampers for earthquake oscillations attenuation in skyscrapers. This work represents an original learning technique based on nonconscious learning mechanisms to enhance long-term memories that complement existing cognitive learning methods.

Keywords: emotion, emotion-enhanced memory, learning technique, STEM

Procedia PDF Downloads 77

Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

Abstract:

Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

Procedia PDF Downloads 153

Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias

Abstract:

Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.

Keywords: healthcare, fall detection, transformer, transfer learning

Procedia PDF Downloads 112

Authors: Chen-Ya Juan

Abstract:

In recent years, the increasing number of children with special needs has brought a lot of attention by many scholars and experts in education, which enforced the preschool teachers face the harsh challenge in the classroom. To protect the right of equal education for all children, enhance the quality of children learning, and take care of the needs of children with special needs, the special education paraprofessional becomes one of the future employment trends for students of the department of the early childhood care and education. Problem-based learning is a problem-oriented instruction, which is different from traditional instruction. The instructor first designed an ambiguous problem direction, following the basic knowledge of early intervention, students had to find clues to solve the problem defined by themselves. In the class, the total instruction included 20 hours, two hours per week. The primary purpose of this paper is to investigate the relationship of student academic scores, self-awareness, learning motivation, learning attitudes, and early intervention knowledge. A total of 105 college students participated in this study and 97 questionnaires were effective. The effective response rate was 90%. The student participants included 95 females and two males. The average age of the participants was 19 years old. The questionnaires included 125 questions divided into four major dimensions: (1) Self-awareness, (2) learning motivation, (3) learning attitudes, and (4) early intervention knowledge. The results indicated (1) the scores of self-awareness were 58%; the scores of the learning motivations was 64.9%; the scores of the learning attitudes was 55.3%. (2) After the instruction, the early intervention knowledge has been increased to 64.2% from 38.4%. (3) Student’s academic performance has positive relationship with self-awareness (p < 0.05; R = 0.506), learning motivation (p < 0.05; R = 0.487), learning attitudes (p < 0.05; R = 0.527). The results implied that although students had gained early intervention knowledge by using PBL instruction, students had medium scores on self-awareness and learning attitudes, medium high in learning motivations.

Keywords: college students, children with special needs, problem-based learning, learning motivation

Procedia PDF Downloads 143

Authors: Hamza Zidoum

Abstract:

This paper investigates the impact of human genetic variation on the function of human proteins using machine-learning algorithms. Single-Nucleotide Polymorphism represents the most common form of human genome variation. We focus on the single amino-acid polymorphism located in the coding region as they can affect the protein function leading to pathologic phenotypic change. We use several supervised Machine Learning methods to identify structural properties correlated with increased risk of the missense mutation being damaging. SVM associated with Principal Component Analysis give the best performance.

Keywords: single-nucleotide polymorphism, machine learning, feature selection, SVM

Procedia PDF Downloads 360

Authors: Dorit Alt, Nirit Raichel

Abstract:

Educational practice is continually subjected to renewal needs, due mainly to the growing proportion of information communication technology, globalization of education, and the pursuit of quality. These types of renewal needs require developing updated instructional and assessment practices that put a premium on adaptability to the emerging requirements of present society. However, university instruction is criticized for not coping with these new challenges while continuing to exemplify the traditional instruction. In order to overcome this critical inadequacy between current educational goals and instructional methods, the LLAF consortium (including 16 members from 8 countries) is collaborating to create a curricular reform for lifelong learning (LLL) in teachers' education, health care and other applied fields. This project aims to achieve its objectives by developing, and piloting models for training students in LLL and promoting meaningful learning activities that could integrate knowledge with the personal transferable skills. LLAF has created a practical guide for teachers containing updated pedagogical strategies and assessment tools based on the constructivist approach for learning. This presentation will be limited to teachers' education only and to the contribution of a pre-pilot research aimed at providing a scale designed to measure constructivist activities in higher education learning environments. A mix-method approach was implemented in two phases to construct the scale: The first phase included a qualitative content analysis involving both deductive and inductive category applications of students' observations. The results foregrounded eight categories: knowledge construction, authenticity, multiple perspectives, prior knowledge, in-depth learning, teacher- student interaction, social interaction and cooperative dialogue. The students' descriptions of their classes were formulated as 36 items. The second phase employed structural equation modeling (SEM). The scale was submitted to 597 undergraduate students. The goodness of fit of the data to the structural model yielded sufficient fit results. This research elaborates the body of literature by adding a category of in-depth learning which emerged from the content analysis. Moreover, the theoretical category of social activity has been extended to include two distinctive factors: cooperative dialogue and social interaction. Implications of these findings for the LLAF project are discussed.

Keywords: constructivist learning, higher education, mix-methodology, lifelong learning

Procedia PDF Downloads 317