Search results for: life- long learning

Authors: Zachary Pan

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Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

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Authors: Iman Al Khalidi

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Recently, English has become the language of globalization and technology. In turn, this has resulted in a seemingly bewildering array of influences and trends in the domain of TESOL curriculum. In light of these changes, higher education has to provide a new and more powerful kind of education. It should prepare students to be more engaged citizens, more capable to solve complex problems at work, and well prepared to lead meaningful life. In response to this, universities, colleges, schools, and departments have to work out in light of the requirements and challenges of the global and technological era. Consequently they have to focus on the adoption of contemporary curriculum which goes in line with the pedagogical shifts from teaching –centered approach to learning centered approach. Ideally, there has been noticeable emphasis on the crucial importance of developing and professionalizing teachers in order to engage them in the process of curriculum development and action research. This is a qualitative study that aims at understanding and exploring the process of designing EFL courses by teachers at the tertiary level from the perspectives of the participants in a professional context in TESOL, Department of English, a private college in Oman. It is a case study that stands on the philosophy of the qualitative approach. It employs multi methods for collecting qualitative data: semi-structured interviews with teachers, focus group discussions with students, and document analysis. The collected data have been analyzed qualitatively by adopting Miles and Huberman's Approach using procedures of reduction, coding, displaying and conclusion drawing and verification.

Keywords: course design, components of course design, case study, data analysis

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Authors: Iman Al Khalidi

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Recently, English has become the language of globalization and technology. In turn, this has resulted in a seemingly bewildering array of influences and trends in the domain of TESOL curriculum. In light of these changes, higher education has to provide a new and more powerful kind of education. It should prepare students to be more engaged citizens, more capable to solve complex problems at work, and well prepared to lead a meaningful life. In response to this, universities, colleges, schools, and departments have to work out in light of the requirements and challenges of the global and technological era. Consequently, they have to focus on the adoption of contemporary curriculum which goes in line with the pedagogical shifts from teaching –centered approach to learning centered approach. Ideally, there has been noticeable emphasis on the crucial importance of developing and professionalizing teachers in order to engage them in the process of curriculum development and action research. This is a qualitative study that aims at understanding and exploring the process of designing EFL courses by teachers at the tertiary level from the perspectives of the participants in a professional context in TESOL, Department of English, a private college in Oman. It is a case study that stands on the philosophy of the qualitative approach. It employs multi-methods for collecting qualitative data: semi-structured interviews with teachers, focus group discussions with students, and document analysis. The collected data have been analyzed qualitatively by adopting Miles and Huberman's Approach using procedures of reduction, coding, displaying, and conclusion drawing and verification.

Keywords: course design, components of course design, case study, data analysis

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Authors: Najma Najam, Rukhsana Kausar, Rabia Hussain Kanwal, Saira Batool, Anum Javed

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In Pakistan, elderly population though increasing but it has been neglected by the researchers and policy makers which resulted in compromised quality of life of the ageing population. Two regions, Punjab and Gilgit-Baltistan (GB) were selected for comparison as Lahore and Multan (Punjab) are highly urbanized, large cities whereas Gilgit and Skardu are remote and mountain bounded valleys in GB. This study focuses on psychological and emotional functioning of elderly and a series of measures translated and adapted in Urdu language was used to assess quality of life, psychological and mental well-being, actual and perceived social support, attachment patterns, forgiveness, affects, geriatric depression, and emotional disturbance patterns (depression, anxiety, and stress) in elderly. A gender-equated sample of 201 elderly participants, 93 from GB (60 from Gilgit, 33 from Skardu) and 108 from Punjab (61 from Lahore, 47 from Multan) with over 60 years age was collected from the multiethnic community of Punjab and GB through purposive convenient sampling technique. Findings revealed that elderly from Multan have better psychological and emotional functioning, higher levels of social support, tendency to forgive, better mental wellbeing and quality of life and lower levels of stress, anxiety, depression, negative affect and attachment avoidance and anxiety related to partner as compared to the elderly from Lahore. Furthermore, both elderly male of Gilgit & Skardu have adequate mental well-being including subjective well-being and psychological functioning which showed positive aspects of mental health but elderly female are more attached to their home and neighbourhood which shows their social and environmental mastery. Gilgiti elderly male reported more degree of positive affect such as enthusiasm, active, alertness, excitement and strong whereas among elderly from Skardu shows more negative affect i.e. aversive mood states, irritability, hostility, and general distress. The need of psychosocial therapy and family counseling for the elderly in urban areas has been identified, which can facilitate in reducing or preventing the depressive and stressful tendencies. The findings are expected to have implications for improving quality of life of the elderly, designing interventions, support system and rehabilitation services to help them. However, findings may attract attention of policy makers and researchers as currently this is the most neglected population in Pakistan.

Keywords: psychological, emotional, aging, elderly, quality of life

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Authors: Madad Ali

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In the contemporary landscape of international travel, the infusion of digital technologies has given rise to innovative business models that are reshaping the dynamics of tourism. This research delves into the transformative potential of these novel business models within the realm of digital tourism and their multifaceted impact on local businesses, residents' quality of life, and the overall travel experience. The study focuses on the captivating backdrop of Yunnan Province, China, renowned for its rich cultural heritage and diverse ethnic minorities, to uncover the intricate nuances of this phenomenon. The primary objectives of this research encompass the identification and categorization of emerging business models facilitated by digital technologies, their implications on tourist engagement, and their integration into the operations of local businesses. By employing a mixed-methods approach, blending qualitative techniques like interviews and content analysis with quantitative tools such as surveys and data analysis, the study provides a comprehensive evaluation of these business models' effects on various dimensions of the tourism landscape. The distinctiveness of this research lies in its exclusive focus on Yunnan Province, China. By concentrating on Yunnan Province, the research contributes exceptional insights into the interplay between digital tourism, ethnic diversity, cultural heritage, and sustainable development. The study's outcomes hold significance for both scholarly discourse and the stakeholders involved in shaping the region's tourism strategies.

Keywords: business model, digital tourism, international travel, local businesses, quality of life

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Authors: Pimpisa Rattanadilok Na Phuket

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This research study aims to examine: 1) teaching competency of the native English-speaking teacher (NEST) 2) the English language learning achievement of Thai students, and 3) students’ perceptions toward their NEST. The population considered in this research was a group of 39 undergraduate students of the academic year 2013. The tools consisted of a questionnaire employed to measure the level of competency of NEST, pre-test and post-test used to examine the students’ achievement on English pronunciation, and an interview used to discover how participants perceived their NEST. The data was statistically analysed as percentage, mean, standard deviation and One-sample-t-test. In addition, the data collected by interviews was qualitatively analyzed. The research study found that the level of teaching competency of native speaker teachers of English was mostly low, the English pronunciation achievement of students had increased significantly at the level of 0.5, and the students’ perception toward NEST is combined. The students perceived their NEST as an English expertise, but they felt that NEST had not recognized students' linguistic difficulty and cultural differences.

Keywords: competency, native English-speaking teacher (NET), English teaching, learning achievement

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Authors: Chan Ka Lok Sobel

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The rapid evolution of digital media platforms has given rise to new forms of narrative engagement, particularly through multi-channel storytelling. This research focuses on exploring the teaching pedagogy and effectiveness of multi-channel storytelling for social media, cinema, games, and streaming platforms. The study employs case studies of the popular series "Squid Game" to investigate the diverse pedagogical approaches and strategies used in teaching multi-channel storytelling. Through qualitative research methods, including interviews, surveys, and content analysis, the research assesses the effectiveness of these approaches in terms of student engagement, knowledge acquisition, critical thinking skills, and the development of digital literacy. The findings contribute to understanding best practices for incorporating multi-channel storytelling into educational contexts and enhancing learning outcomes in the digital media landscape.

Keywords: digital literacy, game-based learning, artificial intelligence, animation production, educational technology

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Authors: Moustafa Osman Mohammed

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This paper is mapping air quality model to engineering the industrial system that ultimately utilized in extensive range of energy systems, distribution resources, and end-user technologies. The model is determining long-range transport patterns contribution as area source can either traced from 48 hrs backward trajectory model or remotely described from background measurements data in those days. The trajectory model will be run within stable conditions and quite constant parameters of the atmospheric pressure at the most time of the year. Air parcel trajectory is necessary for estimating the long-range transport of pollutants and other chemical species. It provides a better understanding of airflow patterns. Since a large amount of meteorological data and a great number of calculations are required to drive trajectory, it will be very useful to apply HYPSLIT model to locate areas and boundaries influence air quality at regional location of Windsor. 2–days backward trajectories model at high and low concentration measurements below and upward the benchmark which was areas influence air quality measurement levels. The benchmark level will be considered as 30 (μg/m3) as the moderate level for Ontario region. Thereby, air quality model is incorporating a midpoint concept between biotic and abiotic components to broaden the scope of quantification impact. The later outcomes’ theories of environmental obligation suggest either a recommendation or a decision of what is a legislative should be achieved in mitigation measures of air emission impact ultimately.

Keywords: air quality, management systems, environmental impact assessment, industrial ecology, climate change

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Authors: Selim M. Khan, Aaron A. Goodarzi, Joshua M. Taron, Tryggve Rönnqvist

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Indoor air quality, a prime determinant of health, is strongly influenced by the presence of hazardous radon gas within the built environment. As a health issue, dangerously high indoor radon arose within the 20th century to become the 2nd leading cause of lung cancer. While the 21st century building metrics and human behaviors have captured, contained, and concentrated radon to yet higher and more hazardous levels, the issue is rapidly worsening in Canada. It is established that Canadians in the Prairies are the 2nd highest radon-exposed population in the world, with 1 in 6 residences experiencing 0.2-6.5 millisieverts (mSv) radiation per week, whereas the Canadian Nuclear Safety Commission sets maximum 5-year occupational limits for atomic workplace exposure at only 20 mSv. This situation is also deteriorating over time within newer housing stocks containing higher levels of radon. Deep machine learning (LSTM) algorithms were applied to analyze multiple quantitative and qualitative features, determine the most important contributory factors, and predicted radon levels in the known past (1990-2020) and projected future (2021-2050). The findings showed gradual downwards patterns in Sweden, whereas it would continue to go from high to higher levels in Canada over time. The contributory factors found to be the basement porosity, roof insulation depthness, R-factor, and air dynamics of the indoor environment related to human window opening behaviour. Building codes must consider including these factors to ensure adequate indoor ventilation and healthy living that can prevent lung cancer in non-smokers.

Keywords: radon, building metrics, deep learning, LSTM prediction model, lung cancer, canada, sweden

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Authors: Nádia Pereira, Paula Ferreira, Sofia Francisco, Sofia Oliveira, Sidclay Souza, Paula Paulino, Ana Margarida Veiga Simão

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Social media has progressed into a platform for hate speech among its users, and thus, there is an increasing need to develop automatic detection classifiers of offense and conflicts to help decrease the prevalence of such incidents. Online communication can be used to intentionally harm someone, which is why such classifiers could be essential in social networks. A possible application of these classifiers is the automatic detection of cyberbullying. Even though identifying the aggressive language used in online interactions could be important to build cyberbullying datasets, there are other criteria that must be considered. Being able to capture the language, which is indicative of the intent to harm others in a specific context of online interaction is fundamental. Offense and hate speech may be the foundation of online conflicts, which have become commonly used in social media and are an emergent research focus in machine learning and natural language processing. This study presents two Portuguese language offense-related datasets which serve as examples for future research and extend the study of the topic. The first is similar to other offense detection related datasets and is entitled Aggressiveness dataset. The second is a novelty because of the use of the history of the interaction between users and is entitled the Conflicts/Attacks dataset. Both datasets were developed in different phases. Firstly, we performed a content analysis of verbal aggression witnessed by adolescents in situations of cyberbullying. Secondly, we computed frequency analyses from the previous phase to gather lexical and linguistic cues used to identify potentially aggressive conflicts and attacks which were posted on Twitter. Thirdly, thorough annotation of real tweets was performed byindependent postgraduate educational psychologists with experience in cyberbullying research. Lastly, we benchmarked these datasets with other machine learning classifiers.

Keywords: aggression, classifiers, cyberbullying, datasets, hate speech, machine learning

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Authors: Tiantian Min, Chuanxiang Cheng, Jin Yue

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The growth and reproduction of microorganisms in food packaging can cause food decay and foodborne diseases, which pose a serious threat to the health of consumers and even cause serious economic losses. Active food packaging containing antibacterial bioactive compounds is a promising strategy for extending the shelf life of products and maintaining the food quality, as well as reducing the food waste. However, most active packaging can only act as slow-release effect for antimicrobials, which causes the release rate of antimicrobials not match the growth rate of microorganisms. Stimuli-responsive active packaging materials based on biopolymeric substrates and bioactive substances that respond to some biological and non-biological trigger factors provide more opportunities for fresh food preservation. The biological stimuli factors such as relative humidity, pH and enzyme existed in the exudate secreted by microorganisms have been expected to design food packaging materials. These stimuli-responsive materials achieved accurate release or delivery of bioactive substances at specific time and appropriate dose. Recently, metal-organic-frameworks (MOFs) nanoparticles become attractive carriers to enhance the efficiency of bioactive compounds or drugs. Cellulose nanofibrils have been widely applied for film substrates due to their biodegradability and biocompatibility. The abundant hydroxyl groups in cellulose can be oxidized to carboxyl groups by TEMPO, making it easier to anchoring MOFs and to be further modification. In this study, a pH and enzyme dual-responsive CAR@ZIF-8/TOCNF/PE film was fabricated by in-situ growth of ZIF-8 nanoparticles onto TEMPO-oxidized cellulose (TOCNF) film and further coated with pectin (PE) for stabilization and controlled release of carvacrol (CAR). The enzyme triggered release of CAR was achieved owing to the degradation of pectin by pectinase secreted by microorganisms. Similarly, the pH-responsive release of CAR was attributed to the unique skeleton degradation of ZIF-8, further accelerating the release of CAR from the topological structure of ZIF-8. The composite film performed excellent crystallinity and adsorb ability confirmed by X-ray diffraction and BET analysis, and the inhibition efficiency against Escherichia coli, Staphylococcus aureus and Aspergillus niger reached more than 99%. The composite film was capable of releasing CAR when exposure to dose-dependent enzyme (0.1, 0.2, and 0.3 mg/mL) and acidic condition (pH = 5). When inoculated 10 μL of Aspergillus niger spore suspension on the equatorial position of mango and raspberries, this composite film acted as packaging pads effectively inhibited the mycelial growth and prolonged the shelf life of mango and raspberries to 7 days. Such MOF-TOCNF based film provided a targeted, controlled and sustained release of bioactive compounds for long-term antibacterial activity and preservation effect, which can also avoid the cross-contamination of fruits.

Keywords: active food packaging, controlled release, fruit preservation, in-situ growth, stimuli-responsive

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Authors: Saeed Saffar-Heidari

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This article aims to study the recent Iranian national uprising of “Women, Life, Freedom” as a site of memory which renders the political possibility of imagining the post-Islamic futures in Iran. “Women, Life, Freedom” movement in Iran has been arguably the most pervasive social movement since the Islamic Revolution (1979) as it has posed serious issues and conflicts for the present Islamic state in Iran. The core argument of this article, however, is oriented toward the critical role of collective memory as a means of political transition and revolutionary mobilization. “Women, Life, Freedom” movement, among other things, has revitalized the popular binary opposition of pre-1979 and post-1979 Iran through which the Ancien Régime or the pre-1979 era is likely to be interpreted, read, and remembered in terms of present post-1979 cultural and political demands. As remembering involves everyday participation in shaping and reshaping the past through new codes, criteria, and values, it is argued that the presentist refashioning and remembering of the pre-1979 monarchical era has been one of the major facilitatory forces for the on-going revolutionary mobilization in Iran. The construction of the pre-1979 memory and the return of the dynastic specter has played a significant role in revolutionary mobilization as it has provided the protesters with the possible perspectives of post-Islamic regime in Iran. Additionally, the question of compulsory “Hijab” (veiling) as the prime mover of "Women, Life, Freedom” movement in Iran has strongly contributed to the everyday comparative discourse of pre/post 1979 memory. According to this presentist remembering of pre-1979, the Pahlavi dynasty would be conceived as a symbol of modernization, westernization, secularization, and non-compulsory Hijab. While the memory of the pre-revolutionary Iran is genuinely an imaginative as well as a constructed entity that finally culminates in the public condemnation of the very Islamic revolution (1979), it serves the enrichment of the Iranian political imagination as it paves the ways for the revolutionary mobilization and then the overthrowing of the Islamic regime in Iran. This article makes a case for the ways that the public narrative and discourse around the Islamic regime (especially the Islamic Hijab) led to the refashioning of the memory of pre-1979 era and inspired he revolutionary mobilization in Iran.

Keywords: post-islamic, utopias, memory, revolutionary, mobilization, Iran

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Authors: Mojtaba Mahmoodian, Joshua Phelan, Mehdi Shahparvari

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With a large percentage of countries’ total infrastructure expenditure attributed to water network maintenance, it is essential to optimise maintenance strategies to rehabilitate or replace underground pipes before failure occurs. The aim of this paper is to provide water utility managers with a maintenance management approach for underground water pipes, subject to external loading and material corrosion, to give the lowest life cycle cost over a predetermined time period. This reliability-based maintenance management methodology details the optimal years for intervention, the ideal number of maintenance activities to perform before replacement and specifies feasible renewal options and intervention prioritisation to minimise the life cycle cost. The study was then extended to include feasible renewal methods by determining the structural condition index and potential for soil loss, then obtaining the failure impact rating to assist in prioritising pipe replacement. A case study on optimisation of maintenance plans for the Melbourne water pipe network is considered in this paper to evaluate the practicality of the proposed methodology. The results confirm that the suggested methodology can provide water utility managers with a reliable systematic approach to determining optimum maintenance plans for pipe networks.

Keywords: water pipe networks, maintenance management, reliability analysis, optimum maintenance plan

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Authors: Parth Shah

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The author examines the recent trend where business organizations are significantly reducing their developmental cycle times to stay competitive in today’s global marketspace. The author proposes a rapid systems engineering framework to address late design changes and allow for flexibility (i.e. to react to unexpected or late changes and its impacts) during the product development cycle using a Systems Engineering approach. A System Engineering approach is crucial in today’s product development to deliver complex products into the marketplace. Design changes can occur due to shortened timelines and also based on initial consumer feedback once a product or service is in the marketplace. The ability to react to change and address customer expectations in a responsive and cost-efficient manner is crucial for any organization to succeed. Past literature, research, and methods such as concurrent development, simultaneous engineering, knowledge management, component sharing, rapid product integration, tailored systems engineering processes, and studies on reducing product development cycles all suggest a research gap exist in specifically addressing late design changes due to the shortening of life cycle environments in increasingly competitive markets. The author’s research suggests that 1) product development cycles time scales are now measured in months instead of years, 2) more and more products have interdepended systems and environments that are fast-paced and resource critical, 3) product obsolesce is higher and more organizations are releasing products and services frequently, and 4) increasingly competitive markets are leading to customization based on consumer feedback. The author will quantify effectiveness with respect to success factors such as time-to-market, return-of-investment, life cycle time and flexibility in late design changes by complexity of product or service, number of late changes and ability to react and reduce late design changes.

Keywords: product development, rapid systems engineering, scalability, systems engineering, systems integration, systems life cycle

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Authors: Muzaffar Hussain

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Requests strategies are considered as a part of the speech acts, which are frequently used in everyday communication. Each language provides speech acts to the speakers; therefore, the selection of appropriate form seems more culture-specific rather than language. The present paper investigates the gender-based difference in the use of request strategies by native speakers of Urdu/Punjabi male and female who are learning English as a second language. The data for the present study were collected from 68 graduate students, who are learning English as an L2 in Pakistan. They were given an online close-ended questionnaire, based on Discourse Completion Test (DCT). After analyzing the data, it was found that the L1 male Urdu/Punjabi speakers were inclined to use more direct request strategies while the female Urdu/Punjabi speakers used indirect request strategies. This paper also found that in some situations female participants used more direct strategies than male participants. The present study concludes that the use of request strategies is influenced by culture, social status, and power distribution in a society.

Keywords: gender variation, request strategies, face-threatening, second language pragmatics, language competence

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Authors: Kamaludeen Samaila, Khashyaullah Abdulfattah, Fahimi Ahmad Bin Amir

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The study was conducted to examine the relationship between selected factors (performance expectancy, effort expectancy, social influence and facilitating condition) and students’ intention to use the learning management system (LMS), as well as investigating the factors predicting students’ intention to use the LMS. The study was specifically conducted at the Faculty of Educational Study of University Putra Malaysia. Questionnaires were distributed to 277 respondents using a random sampling technique. SPSS Version 22 was employed in analyzing the data; the findings of this study indicated that performance expectancy (r = .69, p < .01), effort expectancy (r=.60, p < .01), social influence (r = .61, p < .01), and facilitating condition (r=.42, p < .01), were significantly related to students’ intention to use the LMS. In addition, the result also revealed that performance expectancy (β = .436, p < .05), social influence (β=.232, p < .05), and effort expectancy (β = .193, p < .05) were strong predictors of students’ intention to use the LMS. The analysis further indicated that (R2) is 0.054 which means that 54% of variation in the dependent variable is explained by the entire predictor variables entered into the regression model. Understanding the factors that affect students’ intention to use the LMS could help the lecturers, LMS managers and university management to develop the policies that may attract students to use the LMS.

Keywords: LMS, postgraduate students, PutraBlas, students’ intention, UPM, UTAUT model

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Authors: Joshua van Staden, Dane Brown, Karen Bradshaw

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Gun violence is a significant problem in modern-day society. Early detection of carried handguns through closed-circuit television (CCTV) can aid in preventing potential gun violence. However, CCTV operators have a limited attention span. Machine learning approaches to automating the detection of dangerous gun carriers provide a way to aid CCTV operators in identifying these individuals. This study provides insight into the relationship between human key points extracted using human pose estimation (HPE) and their intention to fire a weapon. We examine the feature importance of each keypoint and their correlations. We use principal component analysis (PCA) to reduce the feature space and optimize detection. Finally, we run a set of classifiers to determine what form of classifier performs well on this data. We find that hips, shoulders, and knees tend to be crucial aspects of the human pose when making these predictions. Furthermore, the horizontal position plays a larger role than the vertical position. Of the 66 key points, nine principal components could be used to make nonlinear classifications with 86% accuracy. Furthermore, linear classifications could be done with 85% accuracy, showing that there is a degree of linearity in the data.

Keywords: feature engineering, human pose, machine learning, security

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Authors: Pia Berner Hansson, Robert Murison Anders Lund, Hammar Åsa

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Major Depressive Disorder (MDD) is often associated with high levels of stress and disturbances in the Hypothalamic Pituitary Adrenal (HPA) system, yielding high levels of cortisol, in addition to cognitive dysfunction. Previous studies in this patient group have shown a relationship between cortisol profile and cognitive functioning in the acute phase of MDD and that the patients had significantly less suppression after dexamethasone administration. However, few studies have investigated this relationship over time and in phases of symptom reduction. The aim of the present study was to examine the relationships between cortisol levels after the Dexamethasone Suppression Test (DST) and cognitive function in a long term perspective in MDD patients. Patients meeting the DSM-IV criteria for a MDD were included in the study and tested in symptom reduction. A control group was included. Cortisol was measured in saliva collected with Salivette sampling devices. Saliva samples were collected 4 times during a 24 hours period over two consecutive days: at awakening, after 45 minutes, after 7 hours and at 11 pm. Dexamethasone (1.0 mg) was given on Day 1 at 11 pm. The neuropsychological test battery consisted of standardized tests measuring memory and Executive Functioning (EF). Cortisol levels did not differ significantly between patients and controls on Day 1 or Day 2. Both groups showed significant suppression after Dexamethasone. There were no correlations between cortisol levels or suppression after Dexamethasone and cognitive measures. The results indicate that the HPA-axis functioning normalizes in phases of symptom reduction in MDD patients and that there no relation between cortisol profile and cognitive functioning in memory or EF.

Keywords: depression, MDD, cortisol, suppression, cognitive functioning

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Authors: John E Coumbe-Lilley

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This IRB-approved study explored athletes' emotional recovery experiences following a severe sports injury keeping them out of their sport for six months or longer. A realistic thematic analytical approach was used to interpret the findings of 44 semi-structured interviews of athletes who competed at high school, college, and professional levels of competition. Thematic analysis validated by a self-rating scale demonstrated athletes cross a series of emotional thresholds during their injury rehabilitation process. Results showed athletes crossed two to six emotional thresholds before positive emotion and coping were consistently experienced following their injury. Athletes reported being unequipped to cope with negative emotional intensity, the longevity of recovery, and enduring depression during long-term rehabilitation. Positive emotional recovery was expected no sooner than nine months and up to 2.5 years following a sports injury. In addition, 100% of athletes received no psychological skills training (PST) for coping and recovery, and 93% of athletes indicated passive psychological coping strategies in the first month following injury, which extended their time to recover. Athletes recommended immediate, realistic, and evidence-based strategies benefitting the emotional recovery of severely injured athletes emotional recovery to improve athletes' emotional well-being during long-term rehabilitation and enhance their return to sport. Future experimental research might compare the post-PST program that emerged from this study to determine its efficacy in improving the recovery of severely injured athletes.

Keywords: sports, injury, rehabilitation, psychological skills training, coping

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Authors: Elham A. Alsadoon, Hamadah B. Alsadoon

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Educators try to design learning environments that are preferred by their students. With the wide-spread adoption of cell phones surpassing any other technology, educators should not fail to invest in the power of such technology. This study aimed to explore the current use of cell phones in education among Saudi students in Saudi universities and how students perceive such use. Data was collected from 237 students at King Saud University. Descriptive analysis was used to analyze the data. A T-test for independent groups was used to examine whether there was a significant difference between males and females in their perception of using cell phones in education. Findings suggested that students have a positive attitude toward the use of cell phones in education. The most accepted use was for sending notification to students, which has already been experienced through the Twasel system provided by King Saud University. This electronic system allows instructors to easily send any SMS or email to their students. The use of cell phone applications came in the second rank of using cell phones in education. Students have already experienced the benefits of having these applications handy wherever they go. On the other hand, they did not perceive using cell phones for assessment as practical educational usage. No gender difference was detected in terms of students’ perceptions toward using cell phones in education.

Keywords: cell phone, mobile learning, educational sciences, education

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Authors: Khairani Binti Supyan, Fatimah Khalid, Mas Rina Mustaffa, Azreen Bin Azman, Amirul Azuani Romle

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Perennial plant classification plays a significant role in various agricultural and environmental applications, assisting in plant identification, disease detection, and biodiversity monitoring. Nevertheless, attaining high accuracy in perennial plant image classification remains challenging due to the complex variations in plant appearance, the diverse range of environmental conditions under which images are captured, and the inherent variability in image quality stemming from various factors such as lighting conditions, camera settings, and focus. This paper proposes an adaptation approach to optimize perennial plant image classification by fine-tuning the pre-trained DNNs model. This paper explores the efficacy of fine-tuning prevalent architectures, namely VGG16, ResNet50, and InceptionV3, leveraging transfer learning to tailor the models to the specific characteristics of perennial plant datasets. A subset of the MYLPHerbs dataset consisted of 6 perennial plant species of 13481 images under various environmental conditions that were used in the experiments. Different strategies for fine-tuning, including adjusting learning rates, training set sizes, data augmentation, and architectural modifications, were investigated. The experimental outcomes underscore the effectiveness of fine-tuning deep neural networks for perennial plant image classification, with ResNet50 showcasing the highest accuracy of 99.78%. Despite ResNet50's superior performance, both VGG16 and InceptionV3 achieved commendable accuracy of 99.67% and 99.37%, respectively. The overall outcomes reaffirm the robustness of the fine-tuning approach across different deep neural network architectures, offering insights into strategies for optimizing model performance in the domain of perennial plant image classification.

Keywords: perennial plants, image classification, deep neural networks, fine-tuning, transfer learning, VGG16, ResNet50, InceptionV3

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Authors: Maurice Ntahobari, Levin Kuhlmann, Mario Boley, Zhinoos Razavi Hesabi

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For machine learning based epileptic seizure prediction, it is important for the model to be implemented in small implantable or wearable devices that can be used to monitor epilepsy patients; however, current state-of-the-art methods are complex and computationally intensive. We use Shapley Additive Explanation (SHAP) to find relevant intracranial electroencephalogram (iEEG) features and improve the computational efficiency of a state-of-the-art seizure prediction method based on the extra trees classifier while maintaining prediction performance. Results for a small contest dataset and a much larger dataset with continuous recordings of up to 3 years per patient from 15 patients yield better than chance prediction performance (p < 0.004). Moreover, while the performance of the SHAP-based model is comparable to that of the benchmark, the overall training and prediction time of the model has been reduced by a factor of 1.83. It can also be noted that the feature called zero crossing value is the best EEG feature for seizure prediction. These results suggest state-of-the-art seizure prediction performance can be achieved using efficient methods based on optimal feature selection.

Keywords: machine learning, seizure prediction, extra tree classifier, SHAP, epilepsy

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Authors: Renate Verkaik, Mieke Rijken, Hennie Boeije

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Elderly who are living alone and who are having one or more impairments are vulnerable for a loss of wellbeing and institutionalization. Physical exercise and social activities together with peers have the potential to make them more resilient. The Dutch program ‘More Resilience, Longer at Home’ initiated by FNO funded 126 local projects to stimulate vulnerable older citizens to participate in exercise and social activities, and as such to improve wellbeing and independent living. The program evaluation addressed the following questions: (1) what are the effects of the program on older (65+) participants exercise behavior, social activities and what is the relationship with wellbeing?, (2) which factors contribute to successful implementation of the projects and their outcomes? A mixed method approach was used. Effects on participants were assessed with a short survey, containing questions on exercise, social engagement, daily functioning, loneliness and life satisfaction. Results of the participants were compared with those of a reference group from the Dutch national population. Perceived influencing factors were investigated with a questionnaire for project leaders. This questionnaire was based on site visits and interviews with project leaders, volunteers and participating elderly. Preliminary results show that social engagement of the participating elderly rises significantly (p ≤ .05) as do their exercise levels and daily functioning. They experience less social loneliness, but not less emotional loneliness. Additionally, there is a positive association between daily functioning and life satisfaction and between exercise and life satisfaction. Perceived influencing factors that contribute to successful implementation of the projects can be categorized in 4 types: (1) characteristics of the activities; (2) profiles of the involved staff (professionals and volunteers), (3) characteristics of the organization, (4) the social political environment. Conclusions are that local projects have been successful in stimulating older citizens to participate in exercise and social activities. Multiple factors need to be addressed to ensure sustainability and scaling-up of the good practices.

Keywords: elderly living alone in the community, exercise and social activities, resilience, quality of life

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Authors: Bae Yu been, Choi Sung won, Lee Ju yeon, Yang Dan Bi

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The purpose of this study is to develop a self-help therapy program for bipolar disorder (BD). Psychosocial treatment is adjunct to pharmacotherapy for BD, however, it is limited and they demand high costs. Therefore, the objective of the study is to overcome these limitations by developing the self-treatment for BD. The study was examined the efficacy of the self-treatment program for BD. A randomized controlled trial compared the self-help therapy (ST) intervention with a treatment as usual (TAU) group. ST group has conducted the program for 8 weeks (16 sessions). Mood chart, Quality of Life in Bipolar Disorder Questionnaire, Attitudes toward seeking professional help Scale, BIS, CERQ, YMRS, MADRS were used by pre, post, and follow up. The efficacy of the self-help therapy was analyzed by using mixed ANOVAs. There were significant differences in the rate of occurrence of mania or depression between the two groups. ST group reported stable moods on mood chart, and reductions in mood symptoms and improvements in quality of life and treatment adherence. This study was confirmed applicable to BD to the self-help therapy for patients with BD conducted first in Korea.

Keywords: self help therapy, bipolar disorder, self help, self therapy

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Authors: Magdalena Suárez-Ortega, M. Fe. Sánchez-García

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This paper focuses on the analysis of the motivations that lead people to undertake and consolidate their business. It is addressed from the framework of planned behavior theory, which recognizes the importance of the social environment and cultural values, both in the decision to undertake business and in business consolidation. Similarly, it is also based on theories of career development, which emphasize the importance of career management competencies and their connections to other vital aspects of people, including their roles within their families and other personal activities. This connects directly with the impact of entrepreneurship on the career and the professional-personal project of each individual. This study is part of the project titled Career Design and Talent Management (Ministry of Economy and Competitiveness of Spain, State Plan 2013-2016 Excellence Ref. EDU2013-45704-P). The aim of the study is to identify and describe entrepreneurial competencies and motivational profiles in a sample of 248 Spanish entrepreneurs, considering the consolidated profile and the profile in transition (n = 248).In order to obtain the information, the Questionnaire of Motivation and conditioners of the entrepreneurial career (MCEC) has been applied. This consists of 67 items and includes four scales (E1-Conflicts in conciliation, E2-Satisfaction in the career path, E3-Motivations to undertake, E4-Guidance Needs). Cluster analysis (mixed method, combining k-means clustering with a hierarchical method) was carried out, characterizing the groups profiles according to the categorical variables (chi square, p = 0.05), and the quantitative variables (ANOVA). The results have allowed us to characterize three motivational profiles relevant to the motivation, the degree of conciliation between personal and professional life, and the degree of conflict in conciliation, levels of career satisfaction and orientation needs (in the entrepreneurial project and life-career). The first profile is formed by extrinsically motivated entrepreneurs, professionally satisfied and without conflict of vital roles. The second profile acts with intrinsic motivation and also associated with family models, and although it shows satisfaction with their professional career, it finds a high conflict in their family and professional life. The third is composed of entrepreneurs with high extrinsic motivation, professional dissatisfaction and at the same time, feel the conflict in their professional life by the effect of personal roles. Ultimately, the analysis has allowed us to line the kinds of entrepreneurs to different levels of motivation, satisfaction, needs and articulation in professional and personal life, showing characterizations associated with the use of time for leisure, and the care of the family. Associations related to gender, age, activity sector, environment (rural, urban, virtual), and the use of time for domestic tasks are not identified. The model obtained and its implications for the design of training actions and orientation to entrepreneurs is also discussed.

Keywords: motivation, entrepreneurial career, guidance needs, life-work balance, job satisfaction, assessment

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Authors: Guru Prakash, Revanth Dugalam

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A road’s condition often deteriorates due to harsh loading such as overload due to trucks, and severe environmental conditions such as heavy rain, snow load, and cyclic loading. In absence of proper maintenance planning, this results in potholes, wide cracks, bumps, and increased roughness of roads. In this paper, a data-driven model will be developed to detect these damages using vibration and image signals. The key idea of the proposed methodology is that the road anomaly manifests in these signals, which can be detected by training a machine learning algorithm. The use of various machine learning techniques such as the support vector machine and Radom Forest method will be investigated. The proposed model will first be trained and tested with artificially simulated data, and the model architecture will be finalized by comparing the accuracies of various models. Once a model is fixed, the field study will be performed, and data will be collected. The field data will be used to validate the proposed model and to predict the future road’s health condition. The proposed will help to automate the road condition monitoring process, repair cost estimation, and maintenance planning process.

Keywords: SVM, data-driven, road health monitoring, pot-hole

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Authors: Lisa Graham, Kathleen Grant

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South Africa is a multicultural country with eleven official languages, yet most of the formal education at institutions of higher education in the country is in English. It is well known that many students, irrespective of their home language, struggle to grasp difficult scientific concepts and the same is true for students enrolled in the Extended Curriculum Programme at the Cape Peninsula University of Technology (CPUT), studying biomedical sciences. Today we are fortunate in that there is a plethora of resources available to students to research and better understand subject matter online. For example, the students often use YouTube videos to supplement the formal education provided in our course. Unfortunately, most of this material is presented in English. The rationale behind this project lies in that it is well documented that students think and grasp concepts easier in their home language and addresses the fact that the lingua franca of instruction in the field of biomedical science is English. A project aimed at addressing the lack of available resources in most of the South African languages is planned, where students studying Bachelor of Health Science in Medical Laboratory Science will collaborate with those studying Film and Video Technology to create educational videos, explaining scientific concepts in their home languages. These videos will then be published on our own YouTube channel, thereby making them accessible to fellow students, future students and anybody with interest in the subject. Research will be conducted to determine the benefit of the project as well as the published videos to the student community. It is suspected that the students engaged in making the videos will benefit in such a way as to gain further understanding of their course content, a broader appreciation of the discipline, an enhanced sense of civic responsibility, as well as greater respect for the different languages and cultures in our classes. Indeed, an increase in student engagement has been shown to play a central role in student success, and it is well noted that deeper learning and more innovative solutions take place in collaborative groups. We aim to make a meaningful contribution towards the production and repository of knowledge in multilingual teaching and learning for the benefit of the diverse student population and staff. This would strengthen language development, multilingualism, and multiculturalism at CPUT and empower and promote African languages as languages of science and education at CPUT, in other institutions of higher learning, and in South Africa as a whole.

Keywords: educational videos, multiculturalism, multilingualism, student engagement

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Authors: Flavia Schuler Gomes, Cristina Brito Dias, Emily Schuler

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One of the emerging themes in modern society is migration. What in the past was a route mostly traveled by men, is currently carried out by women and even children. In this sense, the objective of this research was to understand the experiences and repercussions of the migration in the life of young Brazilians who went to Switzerland. The specific objectives were: to know the causes and consequences of migration; how was the adaptation in the country in emotional and educational terms; as how the interviewees feel the impact of living with two cultures simultaneously. The research had a qualitative methodology. The participants were eight young men and women, between the ages of 18 and 25, who migrated to Switzerland as a child. The instrument used was interview technique of life history. The collected data were analyzed through the thematic content analysis. The results indicate that the young people migrated to accompany their mothers; in terms of nationality, two participants feel completely Swiss, and six believe they share Swiss and Brazilian aspects. None of the participants followed an academic career, having secondary education.

Keywords: adaptation, children, culture, migration

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Authors: Chanoknart Mayusoh

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The research about Formal Thai National Costume in the reign of King Bhumibol Adulyadej is an applied research that aimed to study the accurate knowledge concerning to Thai national costume in the reign of King Rama IX, also to study origin of all costumes in the reign of King Rama IX and to study the style, material used, and using accasion. This research methodology which are collect quanlitative data through observation, document, and photograph from key informant of costume in the reign of King Rama IX and from another who related to this field. The formal Thai national costume of the reign of King Bhumibol Adulyadej originated from the visit of His Majesty the King to Europe and America in 1960. Since Thailand had no traditional national costume; Her Majesty the Queen initiated the idea to create formal Thai national costumes. In 1964, Her Majesty the Queen selected 8 styles of formal Thai national costume. Later, Her Majesty the Queen confered another 3 formal Thai national costume for men. There are 8 styles of formal Thai national costume for women: Thai Ruean Ton, Thai Chit Lada, Thai Amarin, Thai Borom Phiman, Thai Siwalia, Thai Chakkri, Thai Dusit, and Thai Chakkraphat. There are 3 styles of formal Thai national costume for men: short-sleeve shirt, long-sleeve shirt, and long-sleeve shirt with breechcloth. The costume is widely used in formal ceremony such as greeting ceremony for official foreign visitors, wedding ceremony, or other auspicious ceremonies. Now a day, they are always used as a bridal gown as well. The formal Thai national costume is valuable art that shows Thai identity and, should be preserved for the next generation.

Keywords: formal Thai national costume for women, formal Thai national costume for men, His Majesty King Bhumibol Adulyadej the Great King Rama IX, Her Majesty Queen Sirikit Queen

Procedia PDF Downloads 251

Authors: Ismail Becenen

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Air pollution, a consequence of urbanization brought about by modern life, is as global as it is local and regional. Because of the adverse effects of air pollution on human health, air quality is given importance all over the world. According to the decision of the World Health Organization, clean air is the basic necessity for human health and well-being. It poses a very high risk especially for heart diseases and stroke cases. In this study, the positive effects of natural gas usage on air pollution in cities are explained by using literature scans and air pollution measurement values. Natural gas is cleaner than other types of fuel. It contains less sulfur and organic sulfur compounds. When natural gas burns, it does not leave ashes, it does not cause problems in the rubbish mountains. It's a clean fuel, it easily burns and shines. It is a burning gas that is easy and efficient. In addition, there is not a toxic effect for people in case of inhalation. As a result, the use of natural gas needs to be widespread to reduce air pollution around the world in order to provide a healthier life for people and the environment.

Keywords: natural gas, air pollution, sulfur dioxide, particulate matter, energy

Procedia PDF Downloads 192