Search results for: online learning activities

Authors: Mohammed Al-Shalabi, Alaa Obeidat

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In any food stores, some items will be expired or destroyed because the demand on these items is infrequent, so we need a system that can help the decision maker to make an offer on such items to improve the demand on the items by putting them with some other frequent item and decrease the price to avoid losses. The system generates hundreds or thousands of patterns (offers) for each low demand item, then it uses the association rules (support, confidence) to find the interesting patterns (the best offer to achieve the lowest losses). In this paper, we propose a data mining method for determining the best offer by merging the data mining techniques with the e-commerce strategy. The task is to build a model to predict the best offer. The goal is to maximize the profits of a store and avoid the loss of products. The idea in this paper is the using of the association rules in marketing with a combination with e-commerce.

Keywords: data mining, association rules, confidence, online stores

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Authors: F. Abdelhamid

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Algeria is a multilingual speech community where individuals constantly mix between codes in spoken discourse. Code is used as a cover term to refer to the existing languages and language varieties which include, among others, the mother tongue of the majority Algerian Arabic, the official language Modern Standard Arabic and the foreign languages French and English. The present study explores whether Algerians mix between these codes in online communication as well. Facebook is the selected platform from which data is collected because it is the preferred social media site for most Algerians and it is the most used one. Adopting the notion of translanguaging, this study attempts explaining how users of Facebook use multilingual messages to communicate meaning. Accordingly, multilingual interactions are not approached from a pejorative perspective but rather as a creative linguistic behavior that multilingual utilize to achieve intended meanings. The study is intended as a contribution to the research on multilingualism online because although an extensive literature has investigated multilingualism in spoken discourse, limited research investigated it in the online one. Its aim is two-fold. First, it aims at ensuring that the selected platform for analysis, namely Facebook, could be a source for multilingual data to enable the qualitative analysis. This is done by measuring frequency rates of multilingual instances. Second, when enough multilingual instances are encountered, it aims at describing and interpreting some selected ones. 120 posts and 16335 comments were collected from two Facebook pages. Analysis revealed that third of the collected data are multilingual messages. Users of Facebook mixed between the four mentioned codes in writing their messages. The most frequent cases are mixing between Algerian Arabic and French and between Algerian Arabic and Modern Standard Arabic. A focused qualitative analysis followed where some examples are interpreted and explained. It seems that Algerians mix between codes when communicating online despite the fact that it is a conscious type of communication. This suggests that such behavior is not a random and corrupted way of communicating but rather an intentional and natural one.

Keywords: Algerian speech community, computer mediated communication, languages in contact, multilingualism, translanguaging

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Authors: Seyed Mehdi Ghezi, Hesam Hasanpoor

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This scientific article explores enhancement methods for ensemble learning with the aim of improving the performance of classifiers in the analysis and classification of brain signals. The research approach in this field consists of two main parts, each with its own strengths and weaknesses. The choice of approach depends on the specific research question and available resources. By combining these approaches and leveraging their respective strengths, researchers can enhance the accuracy and reliability of classification results, consequently advancing our understanding of the brain and its functions. The first approach focuses on utilizing machine learning methods to identify the best features among the vast array of features present in brain signals. The selection of features varies depending on the research objective, and different techniques have been employed for this purpose. For instance, the genetic algorithm has been used in some studies to identify the best features, while optimization methods have been utilized in others to identify the most influential features. Additionally, machine learning techniques have been applied to determine the influential electrodes in classification. Ensemble learning plays a crucial role in identifying the best features that contribute to learning, thereby improving the overall results. The second approach concentrates on designing and implementing methods for selecting the best classifier or utilizing meta-classifiers to enhance the final results in ensemble learning. In a different section of the research, a single classifier is used instead of multiple classifiers, employing different sets of features to improve the results. The article provides an in-depth examination of each technique, highlighting their advantages and limitations. By integrating these techniques, researchers can enhance the performance of classifiers in the analysis and classification of brain signals. This advancement in ensemble learning methodologies contributes to a better understanding of the brain and its functions, ultimately leading to improved accuracy and reliability in brain signal analysis and classification.

Keywords: ensemble learning, brain signals, classification, feature selection, machine learning, genetic algorithm, optimization methods, influential features, influential electrodes, meta-classifiers

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Authors: Preecha Phongpeng

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The objectives of this research are to assess the prevalence of travel businesses websites in Thailand, investigate and evaluate the quality of travel business websites in Thailand. The sample size includes 323 websites from the population of 1,458 websites. The study covers 4 types of travel business websites including: 78 general travel agents, 30 online reservation travel agents, 205 hotels, 7 airlines, and 3 car-rental companies with nation-wide operation. The findings indicated that e-tourism in Thailand is at its growth stage, with only 13% of travel businesses having websites, 28% of them providing e-mail and the quality of travel business websites in Thailand was at the average level. Seven common problems were found in websites: lack of travel essential information, insufficient transportation information, lack of navigation tools, lack of link pages to other organizations, lack of safety features, unclear online booking functions, and lack of special features also as well.

Keywords: traveling business, website evaluation, e-commerce, e-tourism

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Authors: Kanyaporn Sommeechai

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Air cadets who aspire to become military pilots upon graduation undergo rigorous training at military academies. As first-year cadets are akin to civilian freshmen, they encounter numerous challenges within the seniority-based military academy system. Imposed routines, such as mandatory morning runs and restrictions on mobile phone usage for two semesters, have the potential to impact their learning process and motivation to study, including second language (L2) acquisition. This study aims to investigate the motivational dynamics and L2 learning transitions experienced by air cadets. To achieve this, a Retrodictive Qualitative Modelling approach will be employed, coupled with the adaptation of the three-barrier structure encompassing institutional factors, situational factors, and dispositional factors. Semi-structured interviews will be conducted to gather rich qualitative data. By analyzing and interpreting the collected data, this research seeks to shed light on the motivational factors that influence air cadets' L2 learning journey. The three-barrier structure will provide a comprehensive framework to identify and understand the institutional, situational, and dispositional factors that may impede or facilitate their motivation and language learning progress. Moreover, the study will explore how these factors interact and shape cadets' motivation and learning experiences. The outcomes of this research will yield fundamental data that can inform strategies and interventions to enhance the motivation and language learning outcomes of air cadets. By better understanding their motivational dynamics and transitions, educators and institutions can create targeted initiatives, tailored pedagogical approaches, and supportive environments that effectively inspire and engage air cadets as L2 learners.

Keywords: second language, education, motivational dynamics, learning transitions

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Authors: Eyibo Ebengeobong Eddie, Halil Zafer Alibaba

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The neglect of classroom acoustics is dominant in most educational facilities, meanwhile, hearing and listening is the learning process in this kind of facilities. A classroom should therefore be an environment that encourages listening, without an obstacles to understanding what is being taught. Although different studies have shown teachers to complain that noise is the everyday factor that causes stress in classroom, the capacity of individuals to understand speech is further affected by Echoes, Reverberation, and room modes. It is therefore necessary for classrooms to have an ideal acoustics to aid the intelligibility of students in the learning process. The influence of these acoustical parameters on learning and teaching in schools needs to be further researched upon to enhance the teaching and learning capacity of both teacher and student. For this reason, there is a strong need to provide and collect data to analyse and define the suitable quality of classrooms needed for a learning environment. Research has shown that acoustical problems are still experienced in both newer and older schools. However, recently, principle of acoustics has been analysed and room acoustics can now be measured with various technologies and sound systems to improve and solve the problem of acoustics in classrooms. These acoustic solutions, materials, construction methods and integration processes would be discussed in this paper.

Keywords: classroom, acoustics, materials, integration, speech intelligibility

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Authors: Hui-Fang Lee, Meng-Chu Liu, Wen-Chi Lu, Hsuan-Jung Hsieh

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The purpose of the study was to examine the effect of health program on the fitness ability of abnormal BMI students of Ching-Yun University of Science and Technology. In order to achieve this purpose, self-regulation theory and dietary education were applied, and the effect of 10-week sports activities and three-day diet records on pre-test and post-test of fitness activities was analyzed. There were 40 original participants. Then, nine people who were with normal BMI, low attendance or unfinished fitness test were eliminated from this research. The valid samples were 31 (77.5%) participants. The fitness activities included sit-bending, one minute sit-up, standing long jump, and three-minute stage boarding. The averages of three-day diet records were compared, and differences of pre-test and post-test of the four fitness activities were analyzed with paired-samples t test. The results showed that there was a significant difference between pre-test and post of male students’ BMI and one minute sit-up. Females’ sit-bending and one minute sit-up had the same effect. Females had high fat intake in three-day diet records. The research showed that the use of self-regulation theory and dietary education, the implementation of sports activities and three-day diet records could significantly enhance the physical fitness indicators or effects. While in the course of sports, we should guide students to think about the gap between self-behavior and ideal behavior, then realize the main reasons and improving methods, and finally go towards the goal and improve the effect of physical fitness.

Keywords: self-regulation theory, dietary education, three-day diet records, physical fitness

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Authors: J. Thiele

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Teachers working at vocational Colleges are often confronted with the problem, that many students graduated from different schools and therefore each had a different education. Especially in mathematics many students lack fundamentals or had different priorities at their previous schools. Furthermore, these vocational Colleges have to provide Graduations for many different working-fields, with different core themes. The Colleges are interested in measuring the different Education levels of their students and providing assistance for those who need to catch up. The Project mathe-meistern was initiated to remedy this problem at vocational Colleges. For this purpose, online-tests were developed. The aim of these tests is to evaluate basic mathematical abilities of the students. The tests are online Multiple-Choice-Tests with a total of 65 Items. They are accessed online with a unique Transaction-Number (TAN) for each participant. The content is divided in several Categories (Arithmetic, Algebra, Fractions, Geometry, etc.). After each test, the student gets a personalized summary depicting their strengths and weaknesses in mathematical Basics. Teachers can visit a special website to examine the results of their classes or single students. In total 5830 students did participate so far. For standardization and optimization purposes the tests are being evaluated, using the classic and probabilistic Test-Theory regarding Objectivity, Reliability and Validity, annually since 2015. This Paper is about the Optimization process considering the Rasch-scaling and Standardization of the tests. Additionally, current results using standardized tests will be discussed. To achieve this Competence levels and Types of errors of students attending vocational Colleges in Nordrheinwestfalen, Germany, were determined, using descriptive Data and Distractorevaluations.

Keywords: diagnostical tests in mathematics, distractor devaluation, test-optimization, test-theory

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Authors: Sacha Joseph-Mathews, Leili Javadpour

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In the tourism industry, hoteliers spend millions annually on marketing and positioning efforts for their respective hotels, all in an effort to create a specific image in the minds of the consumer. Yet despite extensive efforts to seduce potential hotel guests with sophisticated advertising messages generated by hotel entities, consumers continue to mistrust corporate branding, preferring instead to place their trust in the reviews of their consumer peers. In today’s complex and cluttered marketplace, online reviews can serve as a mediator for consumers who do not have actual knowledge and experiences with the brand, but are in the process of deciding whether or not to engage in a consumption exercise. Traditionally, consumers have used online reviews as a source of comfort and confirmation of a product/service’s positioning. But today, very few customers make any purchase decisions without first researching existing user reviews, making reviews more of a necessity, rather than a luxury in the purchase decision process. The influence of user generated content (UGC) is amplified in the tourism industry; as more than a third of potential hotel guests will not book a room without first reading a review. As corporate branding becomes less relevant and online reviews become more important, how much of the consumer’s stay expectations are being dictated by existing UGC? Moreover, as hotel guest experience a hotel through the lens of an existing review, how much of their stay and in turn their review, would have been influenced by those reviews that they read? Ultimately, there is the potential for UGC to dictate what potential guests will be most critical about, and or most focused on during their stay. If UGC is a stronger influencer in the purchase decision process than corporate branding, doesn’t it have the potential to dictate, the entire stay experience by influencing the expectations of the guest prior to them arriving on the property? For example, if a hotel is an eco-destination and they focus their branding on their website around sustainability and the retreat nature of the hotel. Yet, guest reviews constantly discuss how dissatisfactory the service and food was with no mention of nature or sustainability, will future reviews then focus primarily on the food? Using text analysis software to examine over 25,000 online reviews, we explore the extent to which new reviews are influenced by wording used in previous reviews for a hotel property, versus content generated by corporate positioning. Additionally, we investigate how distinct hotel related UGC is across different types of tourism destinations. Our findings suggest that UGC can have a greater impact on future reviews, than corporate branding and there is more cohesiveness across UGC of different types of hotel properties than anticipated. A model of User Generated Content Influence is presented and the managerial impact of the power of online reviews to trump corporate branding and shape future user experiences is discussed.

Keywords: user generated content, UGC, corporate branding, online reviews, hotels and tourism

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Authors: Kai Qian, Lixin Tao

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Mobile devices such as smartphones are getting more and more popular in our daily lives. The security vulnerability and threat attacks become a very emerging and important research and education topic in computing security discipline. There is a need to have an innovative mobile security hands-on laboratory to provide students with real world relevant mobile threat analysis and protection experience. This paper presents an authentic teaching and learning mobile security approach with smartphone devices which covers most important mobile threats in most aspects of mobile security. Each lab focuses on one type of mobile threats, such as mobile messaging threat, and conveys the threat analysis and protection in multiple ways, including lectures and tutorials, multimedia or app-based demonstration for threats analysis, and mobile app development for threat protections. This authentic learning approach is affordable and easily-adoptable which immerse students in a real world relevant learning environment with real devices. This approach can also be applied to many other mobile related courses such as mobile Java programming, database, network, and any security relevant courses so that can learn concepts and principles better with the hands-on authentic learning experience.

Keywords: mobile computing, Android, network, security, labware

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Authors: Mehrab Karimian

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The present research aimed to investigate the problems of teaching and learning English in middle schools in Esfahan, Iran. These problems are associated with the learner, teacher, textbook, syllabus, and language policy. The instrument used was a self-constructed likert scale questionnaire. All the variables had a hand in the problems among which textbook, syllabus and language policy had the most effect. Twenty five problems were distinguished among which some are as follows: students do not consider pair work important; most of the time, most teachers do not speak in English in the classroom; the textbook does not include CDs or cassettes, does not consists of all the English Skills; the syllabus does not include one or two projects for students apart from the midterm or final test, Language Policy being not completely familiar with the steps of EFL teaching, does not selecting the most qualified and proficient teachers in EFL teaching. It can be concluded that the language policy should take a practical step in reducing the problems by changing the textbooks and providing more teaching aids for the teachers.

Keywords: teaching and learning english, problems of teaching and learning english, middle school, Iran

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Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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Authors: Janet Jeanne B. Comia, Camille R. Del Rosario, Ma. Janzen A. Dizon, Jacob Russell A. Gooh, Patricia Ann S. Muli

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The researchers conducted the study in Sablayan, Occidental Mindoro.There is a substantial lack of research regarding this place as a destination for tourism as well as its potentials. The researchers aspired to determine how the locals perceive the tourism development in the province in terms of activities, attractions, as well as tourist influx. The main instrument used in the study is the interview method to get more in-depth information regarding the subject. The results showed that attractions and activities greatly increased. There has been a very evident ascent in the number of tourists, foreign and local, visiting the place leading to an increase in tourist influx. Results also presented that tourist congestion is moderate and manageable. It has been observed as well that the town lacked tourism-related merchandise available for tourist consumption and the same can be said for the accommodation and lodging facilities in the destination.

Keywords: tourism development, tourism activities, tourist attractions, tourist influx

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Authors: Priyadarshini Kiran, Gulshan Kumar

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: Social media are becoming the most important tools for interaction among learners, pedagogues and parents where everybody can share, exchange, comment, discuss and create information and knowledge in a collaborative way. The present case study attempts to highlight the role of social media (WhatsApp) in nurturing learning habits in toddlers with the help of parents in primary education. The Case study is based on primary data collected from a primary school situated in a small town in the northern state of Uttar Pradesh, India. In research methodology, survey and structured interviews have been used as a tool collected from parents and pedagogues. The findings Suggest: - To nurture learning habits in toddlers, parents and pedagogues use social media site (WhatsApp) in real-time and that too is convenient and handy; - Skill enhancement on the part of Pedagogues as a result of employing innovative teaching-learning techniques; - Social media sites serve as a social connectivity tool to ward off negativity and monotony on the part of parents and pedagogues in the wake of COVID- 19

Keywords: innovative teaching-learning techniques, pedagogues, social media, nurture, toddlers

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Authors: Aanuoluwapo Olusola Adesanya, Adesina Joseph

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This paper examined the class-size and instructional materials as correlates of pupils learning and academic achievement in primary school. The population of the study comprised 198 primary school pupils in three selected schools in Ogun State, Nigeria. Data were collected through questionnaire and were analysed with the use of multiple regression and ANOVA to analysed the correlation between class-size, instructional materials (independent variables) and learning achievement (dependent variable). The findings revealed that schools having an average class-size of 30 and below with use of instructional materials obtained better results than schools having more than 30 and above. The main score were higher in the school in schools having 30 and below than schools with 30 and above. It was therefore recommended that government, stakeholders and NGOs should provide more classrooms and supply of adequate instructional materials in all primary schools in the state to cater for small class-size.

Keywords: class-size, instructional materials, learning, academic achievement

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Authors: Onesimus Bulus Shiaki

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The study investigated the effect of cooperative learning strategy on mathematics achievement and retention among senior secondary school students of different abilities in Taraba State Nigeria. Cooperative learning strategy could hopefully contribute to students’ achievement which will spur the teachers to develop strategies for better learning. The quasi-experimental of pretest, posttest and control group design was adopted in this study. A sample of one hundred and sixty-four (164) Senior Secondary Two (SS2) students were selected from a population of twelve thousand, eight hundred and seventy-three (12,873) SS2 Students in Taraba State. Two schools with equivalent mean scores in the pre-test were randomly assigned to experimental and control groups. The experimental group students were stratified according to ability levels of low, medium and high. The experimental group was guided by the research assistants using the cooperative learning instructional package. After six weeks post-test was administered to the two groups while the retention test was administered two weeks after the post-test. The researcher developed a 50-item Mathematics Achievement Test (MAT) which was validated by experts obtaining the reliability coefficient of 0.87. Mean scores and standard deviations were used to answer the research questions while the Analysis of Co-variance (ANCOVA) was used to test the hypotheses. Major findings from the statistical analysis showed that cooperative learning strategy has a significant effect on the mean achievement of students as well as retention among students of high, medium and low ability in mathematics. However, cooperative learning strategy has no effect on the interaction of ability level and retention. Based on the results obtained, it was therefore recommended that the adoption of the use of cooperative learning strategy in the teaching and learning of mathematics in senior secondary schools be initiated, maintained and sustained for the benefit of senior secondary school students in Taraba State. Periodic Government sponsored in-service training in form of long vacation training programme, workshops, conferences and seminars on the nature, scope, and use of cooperative learning strategy should be organized for senior secondary school mathematics teachers in Taraba state.

Keywords: ability level, cooperative learning, mathematics achievement, retention

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Authors: Phusit Phukamchanoad

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The research studies the behaviors based on sufficiency economy philosophy at individual and community levels as well as the satisfaction of the urban community leaders by collecting data with purposive sampling technique. For in-depth interviews with 26 urban community leaders, the result shows that the urban community leaders have good knowledge and understanding about sufficiency economy philosophy. Especially in terms of money spending, they must consider the need for living and be economical. The activities in the community or society should not take advantage of the others as well as colleagues. At present, most of the urban community leaders live in a sufficient way. They often spend time with public service, but many families are dealing with debt. Many communities have some political conflict and high family allowances because of living in the urban communities with rapid social and economic changes. However, there are many communities that leaders have applied their wisdom in development for their people by gathering and grouping the professionals to form activities such as making chili sauce, textile organization, making artificial flowers worshipping the sanctity. The most prominent group is the foot massage business in Wat Pracha Rabue Tham. This professional group is supported continuously by the government. One of the factors in terms of satisfaction used for evaluating community leaders is the customary administration in brotherly, interdependent way rather than using the absolute power or controlling power, but using the roles of leader to perform the activities with their people intently, determinedly and having a public mind for people.

Keywords: performance and activities, sufficiency economy, urban communities leader, Dusit district

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Authors: Mashaal Hooda

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The rationale for conducting this action research was to increase students' Academic Achievement (AA) contexts of studying/researching by employing the Goal Setting intervention (GS). The purposive sample consisted of 10 female undergraduate students at a university in Dubai. The intervention was introduced through workshop classes conducted online. The pre-intervention consisted of discussions concentrating on participants' research contexts amidst a pandemic. The GS moderators were implemented in the class, followed by scaffolding and mentoring interactions and self-reflective accounts of students' actions and feelings of using the intervention to better plan and structure their dissertation tasks. The research incorporated a Mixed Methods Methodology (MMM). Quantitative data collection took place through surveys, while qualitative data were collected using semi-structured interviews. Triangulation of the emergent themes showed a positive increase in students achievable GS, self-regulatory study skills, feedback-seeking behaviours, research organisation and synthesis, self-reflection and Academic Resilient (AR) attitudes amalgamate to enhance students' AA outcomes. Though, students' intrinsic motivational levels to study and research observed minor changes only. Nonetheless, the pebble in the shoe was removed as students AA contexts improved in undertaking better actionable steps for their research. Therefore, the GS intervention enabled students to set, balance, and achieve academic goals while catering to their academic anxieties, mental health concerns, and adaptability to the e-learning platforms amidst the COVID-19 pandemic. Despite the wide-scale changes the pandemic brought to the teaching and learning communities, the GS intervention served as a targeted intervention to help students maintain their achievement contexts in a goal-oriented way.

Keywords: academic achievement, acadeic resilience, COVID-19, goal setting

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Authors: Maria Isabel Garcia-Planas, Maria Victoria Garcia-Camba

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The use of brain stem auditory evoked potential (BAEP) is a common way to study the auditory function of people, a way to learn the functionality of a part of the brain neuronal groups that intervene in the learning process by studying the behaviour of wave VI. The latest advances in neuroscience have revealed the existence of different brain activity in the learning process that can be highlighted through the use of innocuous, low-cost, and easy-access techniques such as, among others, the BAEP that can help us to detect early possible neurodevelopmental difficulties for their subsequent assessment and cure. To date and to the authors' best knowledge, only the latency data obtained, observing the first to V waves and mainly in the left ear, were taken into account. This work shows that it is essential to take into account both ears; with these latest data, it has been possible had diagnosed more precise some cases than with the previous data had been diagnosed as 'normal' despite showing signs of some alteration that motivated the new consultation to the specialist.

Keywords: ear, neurodevelopment, auditory evoked potentials, intervals of normality, learning disabilities

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Authors: S. R. M. Krishna, R. Santosh Kumar, V. Kamakshi Prasad

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Machine learning techniques are applied for the analysis of the impact of mental illness on the burden of disease. It is calculated using the disability-adjusted life year (DALY). DALYs for a disease is the sum of years of life lost due to premature mortality (YLLs) + No of years of healthy life lost due to disability (YLDs). The critical analysis is done based on the Data sources, machine learning techniques and feature extraction method. The reviewing is done based on major databases. The extracted data is examined using statistical analysis and machine learning techniques were applied. The prediction of the impact of mental illness on the population using machine learning techniques is an alternative approach to the old traditional strategies, which are time-consuming and may not be reliable. The approach makes it necessary for a comprehensive adoption, innovative algorithms, and an understanding of the limitations and challenges. The obtained prediction is a way of understanding the underlying impact of mental illness on the health of the people and it enables us to get a healthy life expectancy. The growing impact of mental illness and the challenges associated with the detection and treatment of mental disorders make it necessary for us to understand the complete effect of it on the majority of the population.

Keywords: ML, DAL, YLD, YLL

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Authors: Anjum Afrooze

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The curriculum at General Sciences department in Prince Sultan University includes ‘Physical science’ for Computer Science, Information Technology and Business courses. Students are apathetic towards Physical Science and question, as to, ‘How this course is related to their majors?’ English is not a native language for the students and also for many instructors. More than sixty percent of the students come from institutions where English is not the medium of instruction, which makes student learning and academic achievement challenging. After observing the less enthusiastic student cohort for two consecutive semesters, the instructor was keen to find effective strategies to enhance learning and further encourage deep learning by engaging students in different tasks to empower them with necessary skills and motivate them. This study is participatory action research, in which instructor designs effective tasks to engage students in their learning. The study is conducted through two semesters with a total of 200 students. The effectiveness of this approach is studied using questionnaire at the end of each semester and teacher observation. Major outcomes of this study were overall improvement in students attitude towards science learning, enhancement of multiple skills like note taking, problem solving, language proficiency and also fortifying confidence. This process transformed instructor into engaging and reflecting practitioner. Also, these strategies were implemented by other instructors teaching the course and proved effective in opening a path to changes in related areas of the course curriculum. However, refinement in the strategies could be done based on student evaluation and instructors observation.

Keywords: group activity, language proficiency, reasoning skills, science learning

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Authors: O. R. Raimi, A. Lateef

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Inoculum developments of A. niger were used for inoculation of medium for submerged fermentation and solid state fermentation. The filtrate obtained were used as sources of the extra-cellular enzymes. The FTase activities and the course of pH in submerged fermentation ranged from 7.53-24.42µ/ml and 4.4-4.8 respectively. The maximum FTase activity was obtained at 48 hours fermentation. In solid state fermentation, FTase activities ranged from 2.41-27.77µ/ml. Using ripe plantain peel and kola nut pod respectively. Both substrates supported the growth of the fungus, producing profuse growth during fermentation. In the control experiment (using kolanut pod) that lack supplementation, appreciable FTase activity of 16.92µ/ml was obtained. The optimum temperature range was 600C. it was also active at broad pH range of 1-9 with optimum obtain at pH of 5.0. FTase was stable within the range of investigated pH showing more than 60% activities. FTase can be used in the production of fructooligosaccharide, a functional food.

Keywords: Aspergillus niger, solid state fermentation, kola nut pods, Fructosyltransferase (FTase)

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Authors: Rashika Sharma

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The campuses at tertiary institutes can act as a social environment for peer to peer connections. However, socialization is not the only aspect that campuses provide. The campus can act as a learning environment that has often been termed as the campus curriculum. Many tertiary institutes have taken steps to make their campus a ‘green campus’ whereby initiatives have been taken to reduce their impact on the environment. However, as visible as these initiatives are, it is debatable whether these have any effect on students’ and their understanding of sustainable campus operations. Therefore, research was conducted to evaluate the effectiveness of sustainable campus operations in raising students’ awareness of sustainability. Students at two vocational institutes participated in this interpretive research with data collected through surveys and focus groups. The findings indicated that majority of vocational education students remained oblivious of sustainability initiatives on campuses.

Keywords: campus learning, education for sustainability, social learning, vocational education

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Authors: Hala Shaari, Nuredin Ahmed

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Teaching computer programming is recognized to be difficult and a real challenge. The biggest problem faced by novice programmers is their lack of understanding of basic programming concepts. A visualized learning tool was developed and used by volunteered first-year students for two semesters. The purposes of this paper are firstly, to emphasize factors which directly affect the performance of our students negatively. Secondly, to examine whether the proposed tool would improve their performance and learning progression. The results of adopting this tool were conducted using a pre-survey and post-survey questionnaire. As a result, students who used the learning tool showed better performance in their programming subject.

Keywords: factors, novice, programming, visualization

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Authors: Cahit Perkgöz

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Artificial intelligence has brought new approaches to solving problems in almost every research field in recent years. One of these topics is shape design and optimization, which has the possibility of applications in many fields, such as nanotechnology and electronics. A properly constructed cost function can eliminate the need for labeled data required in deep learning and create desired shapes. In this work, the network parameters are optimized differentially, which differs from traditional approaches. The methods are tested for physics-related structures and successful results are obtained. This work is supported by Eskişehir Technical University scientific research project (Project No: 20ADP090)

Keywords: deep learning, shape design, optimization, artificial intelligence

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Authors: Gokhan Zengin, Cengiz Sarikurkcu, Abdurrahman Aktumsek, Ramazan Ceylan

Abstract:

The present study was designated to characterize the essential oil from S. galatica (SGEOs) and evaluate its antioxidant and enzyme inhibitory activities. Antioxidant capacity were tested different methods including free radical scavenging (DPPH, ABTS and NO), reducing power (FRAP and CUPRAC), metal chelating and phosphomolybdenum. Inhibitory activities were analyzed on acetylcholiesterase, butrylcholinesterase, α-amylase and α-glucosidase. SGEOs were chemically analyzed and identified by gas chromatography (GC) and gas chromatography/mass spectrophotometry (GC/MS). 23 components, representing 98.1% of SGEOs were identified. Monoterpene hydrocarbons (74.1%), especially α- (23.0%) and β-pinene (32.2%), were the main constituents in SGEOs. The main sesquiterpene hydrocarbons were β-caryophyllene (16.9%), Germacrene-D (1.2%) and Caryophyllene oxide (1.2%), respectively. Generally, SGEOs has shown moderate free radical, reducing power, metal chelating and enzyme inhibitory activities. These activities related to chemical profile in SGEOs. Our findings supported that the possible utility of SGEOs is a source of natural agents for food, cosmetics or pharmaceutical industries.

Keywords: sideritis galatica, antioxidant, monoterpenes, cholinesterase, anti-diabetic

Procedia PDF Downloads 442

Authors: Mohammad Rostami, Mohammad Reza Forghani, Elahe Neshat, Fatemeh Yaghoobi

Abstract:

An Ad Hoc network consists of wireless mobile equipment which connects to each other without any infrastructure, using connection equipment. The best way to form a hierarchical structure is clustering. Various methods of clustering can form more stable clusters according to nodes' mobility. In this research we propose an algorithm, which allocates some weight to nodes based on factors, i.e. link stability and power reduction rate. According to the allocated weight in the previous phase, the cellular learning automaton picks out in the second phase nodes which are candidates for being cluster head. In the third phase, learning automaton selects cluster head nodes, member nodes and forms the cluster. Thus, this automaton does the learning from the setting and can form optimized clusters in terms of power consumption and link stability. To simulate the proposed algorithm we have used omnet++4.2.2. Simulation results indicate that newly formed clusters have a longer lifetime than previous algorithms and decrease strongly network overload by reducing update rate.

Keywords: mobile Ad Hoc networks, clustering, learning automaton, cellular automaton, battery power

Procedia PDF Downloads 413

Authors: Ahmad. A. Kardan, Amir Narimani, Foozhan Ataiefard

Abstract:

Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC forums by applying social network analysis and association rule mining techniques. Initial results indicate that the proposed recommender system performs comparatively well with regard to limited available data from users' previous posts in the forum.

Keywords: association rule mining, hybrid recommender system, massive open online courses, MOOCs, social network analysis

Procedia PDF Downloads 296

Authors: Shu-Hsien Liao, Yao-Hsuan Yang

Abstract:

Social media is a virtual community and online platform that people use to create, share, and exchange opinions/experiences. Internet celebrities are people who become famous on the Internet, increasing their popularity through their social networking or video websites. Social commerce (s-ecommerce) is the combination of social relations and commercial transaction activities. The combination of social media and Internet celebrities is an emerging model for the development of s-ecommerce. With recent advances in system sciences, recommendation systems are gradually moving to develop intentional and behavioral recommendations. This background leads to the research issues regarding digital and social media in enterprises. Thus, this study implements data mining analytics, including clustering analysis and association rules, to investigate Taiwanese users (n=2,102) to investigate social media and Internet celebrities’ preferences to find knowledge profiles/patterns/rules for s-ecommerce intentional and behavioral recommendations.

Keywords: social media, internet celebrity, social commerce (s-ecommerce), data mining analytics, intentional and behavioral recommendations

Procedia PDF Downloads 33

Authors: Nubwimana Rachel, Mugabowindekwe Maurice

Abstract:

Trees play a crucial role in maintaining biodiversity and providing various ecological services. Traditional methods of counting trees are time-consuming, and there is a need for more efficient techniques. However, deep learning makes it feasible to identify the multi-scale elements hidden in aerial imagery. This research focuses on the application of deep learning techniques for tree detection and counting in both forest and non-forest areas through the exploration of the deep learning application for automated tree detection and counting using satellite imagery. The objective is to identify the most effective model for automated tree counting. We used different deep learning models such as YOLOV7, SSD, and UNET, along with Generative Adversarial Networks to generate synthetic samples for training and other augmentation techniques, including Random Resized Crop, AutoAugment, and Linear Contrast Enhancement. These models were trained and fine-tuned using satellite imagery to identify and count trees. The performance of the models was assessed through multiple trials; after training and fine-tuning the models, UNET demonstrated the best performance with a validation loss of 0.1211, validation accuracy of 0.9509, and validation precision of 0.9799. This research showcases the success of deep learning in accurate tree counting through remote sensing, particularly with the UNET model. It represents a significant contribution to the field by offering an efficient and precise alternative to conventional tree-counting methods.

Keywords: remote sensing, deep learning, tree counting, image segmentation, object detection, visualization

Procedia PDF Downloads 80