Search results for: learning management systems

Authors: Amanda Silva Parra, Dayra Yisel García Ramirez

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In developing countries, agricultural "modernization" has led to a loss of biodiversity and inefficiency of agricultural systems, manifested in increases in Greenhouse Gas Emissions (GHG) and the C footprint, generating the susceptibility of systems agriculture to environmental problems, loss of biodiversity, depletion of natural resources, soil degradation and loss of nutrients, and a decrease in the supply of products that affect food security for peoples and nations. Each year agriculture emits 10 to 12% (5.1 to 6.1 Gt CO2eq per year) of the total estimated GHG emissions (51 Gt CO2 eq per year). The FAO recommends that countries that have not yet done so consider declaring sustainable agriculture as an essential or strategic activity of public interest within the framework of green economies to better face global climate change. The objective of this research was to estimate the balance of GHG in agricultural systems of Cumaral, Meta (Colombia), to contribute to the recovery and sustainable operation of agricultural systems that guarantee food security and face changes generated by the climate in a more intelligent way. To determine the GHG balances, the IPCC methodologies were applied with a Tier 1 and 2 level of use. It was estimated that all the silvopastoral systems evaluated play an important role in this reconversion compared to conventional systems such as improved pastures. and degraded pastures due to their ability to capture C both in soil and in biomass, generating positive GHG balances, guaranteeing greater sustainability of soil and air resources.

Keywords: climate change, carbon capture, environmental sustainability, GHG mitigation, silvopastoral systems

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Authors: Anes Enakoa, Yawei Liang

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Question Answering (QA) system is one of the most important and demanding tasks in the field of Natural Language Processing (NLP). In QA systems, the answer generation task generates a list of candidate answers to the user's question, in which only one answer is correct. Answer selection is one of the main components of the QA, which is concerned with selecting the best answer choice from the candidate answers suggested by the system. However, the selection process can be very challenging especially in Arabic due to its particularities. To address this challenge, an approach is proposed to answer questions with multiple answer choices for Arabic QA systems based on Textual Entailment (TE) recognition. The developed approach employs a Support Vector Machine that considers lexical, semantic and syntactic features in order to recognize the entailment between the generated hypotheses (H) and the text (T). A set of experiments has been conducted for performance evaluation and the overall performance of the proposed method reached an accuracy of 67.5% with C@1 score of 80.46%. The obtained results are promising and demonstrate that the proposed method is effective for TE recognition task.

Keywords: information retrieval, machine learning, natural language processing, question answering, textual entailment

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Authors: Musatafa Abbas Abbood Albadr, Masri Ayob, Sabrina Tiun, Fahad Taha Al-Dhief, Mohammad Kamrul Hasan

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Breast Cancer (BC) is considered one of the most frequent reasons of cancer death in women between 40 to 55 ages. The BC is diagnosed by using digital images of the FNA (Fine Needle Aspirate) for both benign and malignant tumors of the breast mass. Therefore, this work proposes the Online Sequential Extreme Learning Machine (OSELM) algorithm for diagnosing BC by using the tumor features of the breast mass. The current work has used the Wisconsin Diagnosis Breast Cancer (WDBC) dataset, which contains 569 samples (i.e., 357 samples for benign class and 212 samples for malignant class). Further, numerous measurements of assessment were used in order to evaluate the proposed OSELM algorithm, such as specificity, precision, F-measure, accuracy, G-mean, MCC, and recall. According to the outcomes of the experiment, the highest performance of the proposed OSELM was accomplished with 97.66% accuracy, 98.39% recall, 95.31% precision, 97.25% specificity, 96.83% F-measure, 95.00% MCC, and 96.84% G-Mean. The proposed OSELM algorithm demonstrates promising results in diagnosing BC. Besides, the performance of the proposed OSELM algorithm was superior to all its comparatives with respect to the rate of classification.

Keywords: breast cancer, machine learning, online sequential extreme learning machine, artificial intelligence

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Authors: Agih Ukuru Agih

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This work is an appraisal of the application and applicability of computer system to financial management in improving the speed, performance, accuracy, and efficiency of the College of Education, Oju. The computerization of financial management, which is a recent development that has authentic and dedicated balancing of accounting records, would be of enormous benefits to the college. The core objective of this project is to recommend the software that typically matches a computerized institution, making for improved service, reduced fraud, mishandled funds, and financial records in the College of Education, Oju. Considering major globalization impacts in computerized financial management of the college, the study recommends among other things that the College of Education, Oju should endeavor to be positive towards computerized financial management in the institution.

Keywords: computer system, balancing, accounting records, computerized financial management

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Authors: Rachid Ed-Dali, Khalid Elasri

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Mass media seem to provide a rich content for language acquisition. Exposure to television, the Internet, the mobile phone and other technological gadgets and devices helps enrich the student’s lexicon positively as well as negatively. The difficulties encountered by students while learning and acquiring second languages in addition to their eagerness to comprehend the content of a particular program prompt them to diversify their methods so as to achieve their targets. The present study highlights the significance of certain media channels and their involvement in language acquisition with the employment of the Natural Approach to further grasp whether students, especially secondary and high school students, learn and acquire errors through watching subtitled television programs. The chief objective is investigating the deductive and inductive relevance of certain programs beside the involvement of peripheral learning while acquiring mistakes.

Keywords: errors, mistakes, Natural Approach, peripheral learning, solecism

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Authors: Mei-Chun Chang

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Due to digital transformation and social media development in recent years, various real-time interactive digital tools have been developed to meet the design demands for virtual reality avatars, which also promote digital content learners' active participation in the creation process. As a result, new social media design tools have the characteristics of intuitive operation with a simplified interface for fast production, from which works can be simply created. This study carried out observations, records, questionnaire surveys, and interviews on the creation and learning of visual avatars made by students of the National Taiwan University of Science and Technology (NTUST) with the VRoid Studio 3D modeling tool so as to explore their learning effectiveness on the design of visual avatars. According to the results of this study, the VRoid Studio 3D character modeling tool has a positive impact on the learners and helps to improve their learning effectiveness. Students with low academic achievements said that they could complete the conceived modeling with their own thinking by using the design tool, which increased their sense of accomplishment. Conclusions are drawn according to the results, and relevant future suggestions are put forward.

Keywords: virtual avatar, character design, social media, vroid studio, creation, digital learning

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Authors: Sarah Lister, Pauline Palmer

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Research findings presented within this paper form part of a larger scale collaboration between academics at Manchester Metropolitan University and a technology company. The overarching aims of this project focus on developing a series of game-based resources to promote the teaching of aspects of mathematics through a second language (L2) in primary schools. This study explores the potential of game-based learning (GBL) as a dynamic way to engage and motivate learners, making learning fun and purposeful. The research examines the capacity of GBL resources to provide a meaningful and purposeful context for CLIL. GBL is a powerful learning environment and acts as an effective vehicle to promote the learning of mathematics through an L2. The fun element of GBL can minimise stress and anxiety associated with mathematics and L2 learning that can create barriers. GBL provides one of the few safe domains where it is acceptable for learners to fail. Games can provide a life-enhancing experience for learners, revolutionizing the routinized ways of learning through fusing learning and play. This study argues that playing games requires learners to think creatively to solve mathematical problems, using the L2 in order to progress, which can be associated with the development of higher-order thinking skills and independent learning. GBL requires learners to engage appropriate cognitive processes with increased speed of processing, sensitivity to environmental inputs, or flexibility in allocating cognitive and perceptual resources. At surface level, GBL resources provide opportunities for learners to learn to do things. Games that fuse subject content and appropriate learning objectives have the potential to make learning academic subjects more learner-centered, promote learner autonomy, easier, more enjoyable, more stimulating and engaging and therefore, more effective. Data includes observations of the children playing the games and follow up group interviews. Given that learning as a cognitive event cannot be directly observed or measured. A Cognitive Discourse Functions (CDF) construct was used to frame the research, to map the development of learners’ conceptual understanding in an L2 context and as a framework to observe the discursive interactions that occur learner to learner and between learner and teacher. Cognitively, the children were required to engage with mathematical content, concepts and language to make decisions quickly, to engage with the gameplay to reason, solve and overcome problems and learn through experimentation. The visual elements of the games supported the learning of new concepts. Children recognised the value of the games to consolidate their mathematical thinking and develop their understanding of new ideas. The games afforded them time to think and reflect. The teachers affirmed that the games provided meaningful opportunities for the learners to practise the language. The findings of this research support the view that using the game-based resources supported children’s grasp of mathematical ideas and their confidence and ability to use the L2. Engaging with the content and language through the games led to deeper learning.

Keywords: CLIL, gaming, language, mathematics

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Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: Mona Hoyng

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In times of digitalization nowadays, the use of games became a crucial new way for digital game-based learning (DGBL) in higher education. In this regard, the development of a gameful experience (GE) among students is decisive when examining DGBL as the GE is a necessary precondition determining the effectiveness of games. In this regard, the purpose of this study is to provide deeper insights into the GE and to empirically investigate whether and how these meaningful learning experiences within games, i.e., GE, among students are created. Based on the theory of experience and flow theory, a double-mediation model was developed considering instructional support, group engagement, and flow as determinants of students’ GE. Based on data of 337 students taking part in a business simulation game at two different universities in Germany, regression-based statistical mediation analysis revealed that instructional support promoted students’ GE. This relationship was further sequentially double mediated by group engagement and flow. Consequently, in the context of DGBL, meaningful learning experiences within games in terms of GE are created and promoted through appropriate instructional support, as well as high levels of group engagement and flow among students.

Keywords: gameful experience, instructional support, group engagement, flow, education, learning

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Authors: Peter Ecke

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This research presents insights from a questionnaire study and autobiographic narrative analyses about the language and cultural backgrounds, challenges, interests, and needs, as well as perceptions about bilingualism and language learning of undergraduate students at a Public University in the southwestern United States. Participants were 650 students, enrolled in college-level general education courses, entitled “Becoming multilingual: Learning and maintaining two or more languages” between 2020 and 2024. Data were collected via pre- and post-course questionnaires administered online through the Qualtrix XM platform and complemented with analyses of excerpts from autobiographical narratives that students produced as part of the course assignments. Findings, for example, show that course participants have diverse linguistic backgrounds. The five most frequently reported L1s were English (about 50% of course participants), Spanish, Arabic, Mandarin, and Korean (in that order). The five most frequently reported L2s were English, Spanish, French, ASL, Japanese, German, and Mandarin (in that order). Participants also reported on their L2, L3, L4, and L5 if applicable. Most participants (over 60%) rated themselves bilingual or multilingual whereas 40% considered themselves to be monolingual or foreign language learners. Only about half of the participants reported feeling very or somewhat comfortable with their language skills, but these reports changed somewhat from the pre- to the post-course survey. About half of participants were mostly interested in learning how to effectively learn a foreign language. The other half of participants reported being most curious about learning about themselves as bi/multilinguals, (re)learning a language used in childhood, learning how to bring up a child as a bi/multilingual or learning about people who speak multiple languages (distributed about evenly). Participants’ comments about advantages and disadvantages of being bilingual remained relatively stable but their agreement with common myths about bilingualism and language learning changed from the pre- to the post-course survey. Students’ reflections in the autobiographical narratives and comments in (institutionally administered) anonymous course evaluations provided additional data on students’ concerns about their current language skills and uses as well as their perceptions about learning outcomes and the usefulness of the general education course for their current and future lives. It is hoped that the presented findings and discussion will spark interest among colleagues in offering similar courses as a resource for college students (and possibly other audiences), including those from migrant, indigenous, multilingual, and multicultural communities to contribute to a more harmonious bilingualism and well-being of college students who are or inspire to become bi-or multilingual.

Keywords: autobiographic narratives, general education university course, harmonious bilingualism and well-being, multilingualism, questionnaire study

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Authors: N. Hammid, F. Bouarab-Dahmani, T. Berkane

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Since its appearance, the MOOC (massive open online course) is gaining more and more intention of the educational communities over the world. Apart from the current MOOCs design and purposes, the creators of MOOC focused on the importance of the connection and knowledge exchange between individuals in learning. In this paper, we present a conceptual model for massive open online blended courses where teachers over the world can collaborate and exchange their experience to get a common efficient content designed as a MOOC opened to their students to live a better learning experience. This model is based on disciplines’ concepts capitalization and the detection of the obstacles met by their students when faced with problem situations (exercises, projects, case studies, etc.). This detection is possible by analyzing the frequently of semantic errors committed by the students. The participation of teachers in the design of the course and the attendance by their students can guarantee an efficient and extensive participation (an important number of participants) in the course, the learners’ motivation and the evaluation issues, in the way that the teachers designing the course assess their students. Thus, the teachers review, together with their knowledge, offer a better assessment and efficient connections to their students.

Keywords: massive open online course, MOOC, online learning, e-learning

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Authors: Maria L. Ulloa, Ruth M. Crawford, Stephanie Kelly, Joey Domdom

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In recent decades health and social service delivery have become more collaborative and interdisciplinary. Emerging trends suggest the need for an integrative and interprofessional approach to meet the challenges faced by professionals navigating the complexities of health and social service practice environments. Terms such as multidisciplinary practice, interprofessional collaboration, interprofessional education and transprofessional practice have become the common language used across a range of social services and health providers in western democratic systems. In Aotearoa New Zealand, one example of an interprofessional collaborative approach to curriculum design and delivery in health and social service is the development of an innovative Masters of Professional Practice programme. This qualification is the result of a strategic partnership between two tertiary institutions – Whitireia New Zealand (NZ) and the Wellington Institute of Technology (Weltec) in Wellington. The Master of Professional Practice programme was designed and delivered from the perspective of a collaborative, interprofessional and relational approach. Teachers and students in the programme come from a diverse range of cultural, professional and personal backgrounds and are engaged in courses using a blended learning approach that incorporates the values and pedagogies of interprofessional education. Students are actively engaged in professional practice while undertaking the programme. This presentation describes the themes of exploratory qualitative formative observations of engagement in class and online, student assessments, student research projects, as well as qualitative interviews with the programme teaching staff. These formative findings reveal the development of critical practice skills around the common themes of the programme: research and evidence based practice, education, leadership, working with diversity and advancing critical reflection of professional identities and interprofessional practice. This presentation will provide evidence of enhanced learning experiences in higher education and learning in multi-disciplinary contexts.

Keywords: diversity, exploratory research, interprofessional education, professional identity

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Authors: Shirekha Layangani, Suneth Dharmaparakrama

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When the manufacturing industry is concerned the Environment Management System (EMS) is a common term. Currently most organizations have obtained the environmental standard certification, ISO 14001. In the Sri Lankan context even though the organizations adopt Environmental Management, a very limited number of companies tend to calculate their Carbon Footprints. This research discusses the demotivating factors of manufacturing organizations in Sri Lanka to integrate calculation of carbon footprint into their supply chains. Further it also identifies the benefits that manufacturing organizations can gain by implementing calculation of carbon footprint. The manufacturing companies listed under “ISO 14001” certification were considered in this study in order to investigate the problems mentioned above. 100% enumeration was used when the surveys were carried out. In order to gather essential data two surveys were designed to be done among manufacturing organizations that are currently engaged in calculating their carbon footprint and the organizations that have not. The survey among the first set of manufacturing organizations revealed the benefits the organizations were able to gain by implementing calculation of carbon footprint. The latter set organizations revealed the demotivating factors that have influenced not to integrate calculation of carbon footprint into their supply chains. This paper has summarized the results obtained by the surveys and segregated depending on the market share of the manufacturing organizations. Further it has indicated the benefits that can be obtained by implementing carbon footprint calculation, depending on the market share of the manufacturing entity. Finally the research gives suggestions to manufacturing organizations on applicability of adopting carbon footprint calculation depending on the benefits that can be obtained.

Keywords: carbon footprint, environmental management systems (EMS), benefits of carbon footprint, ISO14001

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Authors: Tracy B.E. Omorogiuwa

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Understanding the role of social work in improving societal well-being cannot be separated from the place of field education, which is an integral aspect of social work education. Field learning provides students with knowledge and opportunities to experience solving issues in the field and giving them a clue of the practice situation. Despite being a crucial component in social work curriculum, field education occupies a large space in learning outcome, given the issues and challenges pertaining to its purpose and significance in the society. The drive of this paper is to provide insight on the specific ways in which field education has been conceived, realized and valued in the society. Emphasis is on the significance of field instruction; the link with classroom learning; and the structure of field experience in social work education. Given documented analysis and experience, this study intends to contribute to the development of social work curriculum, by analyzing the pattern, issues and challenges fronting the social work field education in the University of Benin, Nigeria.

Keywords: challenges, curriculum, field education, social work education

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Authors: Lloyd A. Taylor

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An increase in the prevalence of Attention Deficit-Hyperactivity Disorder (ADHD) highlights the need to consider factors that may be exacerbating symptom presentation. Traditional diagnostic criteria provide a little framework for healthcare providers to consider as they attempt to diagnose and treat children with behavioral problems. In fact, aside from exclusion criteria, limited alternative considerations are available, and approaches fail to consider the impact of outside factors that could increase or decrease the likelihood of appropriate diagnosis and success of interventions. This paper will consider specific systems-based factors that influence behavior and intervention successes that, when not considered, could account for the upsurge of diagnoses. These include understanding (1) challenges in the healthcare system, (2) the influence and impact of educators and the educational system, (3) technology use, and (4) patient and parental attitudes about the diagnosis of ADHD. These factors must be considered both individually and as a whole when considering both the increase in diagnoses and the subsequent increases in prescriptions for psychostimulant medication. A theoretical model based on a risk management approach will be presented. Finally, data will be presented that demonstrates pediatric provider satisfaction with this approach to diagnoses and treatment of ADHD as it relates to practice trends.

Keywords: ADHD, diagnostic criteria, risk management model, pediatricians

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Authors: Daniele Traversaro

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Problem: Senior citizens have been facing a challenging reality as a result of strict public health measures designed to protect people from the COVID-19 outbreak. These include the risk of social isolation due to the inability of the elderly to integrate with technology. Never before have information and communication technology (ICT) skills become essential for their everyday life. Although third-age ICT education and lifelong learning are widely supported by universities and governments, there is a lack of literature on which teaching strategy/methodology to adopt in an entirely online ICT course aimed at third-age learners. This contribution aims to present an application of the Think-Pair-Share (TPS) learning method in an ICT third-age virtual classroom with an intergenerational approach to conducting online group labs and review activities. This collaborative strategy can help increase student engagement, promote active learning and online social interaction. Research Question: Is collaborative learning applicable and effective, in terms of student engagement and learning outcomes, for an entirely online third-age ICT introductory course? Methods: In the TPS strategy, a problem is posed by the teacher, students have time to think about it individually, and then they work in pairs (or small groups) to solve the problem and share their ideas with the entire class. We performed four experiments in the ICT course of the University of the Third Age of Genova (University of Genova, Italy) on the Microsoft Teams platform. The study cohort consisted of 26 students over the age of 45. Data were collected through online questionnaires. Two have been proposed, one at the end of the first activity and another at the end of the course. They consisted of five and three close-ended questions, respectively. The answers were on a Likert scale (from 1 to 4) except two questions (which asked the number of correct answers given individually and in groups) and the field for free comments/suggestions. Results: Results show that groups perform better than individual students (with scores greater than one order of magnitude) and that most students found it helpful to work in groups and interact with their peers. Insights: From these early results, it appears that TPS is applicable to an online third-age ICT classroom and useful for promoting discussion and active learning. Despite this, our experimentation has a number of limitations. First of all, the results highlight the need for more data to be able to perform a statistical analysis in order to determine the effectiveness of this methodology in terms of student engagement and learning outcomes as a future direction.

Keywords: collaborative learning, information technology education, lifelong learning, older adult education, think-pair-share

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Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

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Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.

Keywords: basketball, deep learning, feature extraction, single-camera, tracking

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Authors: Nurul Nadhirah Anuar, Muhammad Fauzi Abdul Ghani

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Scheduled waste management is very important in environmental and health aspects. Despite it is very important, the research study on schedule waste management is very little in the highway industry even though there is a rapid growth of highway operation in the Asian region. It should be noted that there are many unnoticeable wastes in highway industry that should be managed properly. This paper aims to define the scheduled waste, to provide a conceptual framework of the scheduled waste management in highway industry, to highlight the effect of improper management of scheduled waste and to encourage future researchers to identify and share the present practice of scheduled management in their country. The understanding on effective management of scheduled waste will help the operators of highway industry, the academicians, future researchers, and encourage a friendly environment around the world. The study on scheduled waste management in highway industry is very crucial as compared to factories in which the factories are located on specified areas whereas, highway transverse and run along kilometers crossing the various type of environment, residential and schools. Using Environmental Quality (Scheduled Waste) Regulations, 2005 as a guide, this conceptual paper highlight several scheduled wastes produced by highway industry in Malaysia and provide a conceptual framework of scheduled waste management that focused on the highway industry. Understanding on schedule waste management is vital in order to preserve the environment. Besides that, the waste substances are hazardous to human being. Many diseases have been associated with the improper management of scheduled waste such as cancer, throat irritation and respiration problem.

Keywords: Asia region, environment, highway industry, scheduled waste

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Authors: Dorit Alt, Nirit Raichel

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

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

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Authors: Jie Zhang, Qianyu Guo, Tieyi Zhang, Zhiyong Feng, Xiaohong Li

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With the widespread popularity of mobile devices and the development of artificial intelligence (AI), deep learning (DL) has been extensively applied in Android apps. Compared with traditional Android apps (traditional apps), deep learning based Android apps (DL-based apps) need to use more third-party application programming interfaces (APIs) to complete complex DL inference tasks. However, existing methods (e.g., FlowDroid) for detecting sensitive information leakage in Android apps cannot be directly used to detect DL-based apps as they are difficult to detect third-party APIs. To solve this problem, we design DLtrace; a new static information flow analysis tool that can effectively recognize third-party APIs. With our proposed trace and detection algorithms, DLtrace can also efficiently detect privacy leaks caused by sensitive APIs in DL-based apps. Moreover, using DLtrace, we summarize the non-sequential characteristics of DL inference tasks in DL-based apps and the specific functionalities provided by DL models for such apps. We propose two formal definitions to deal with the common polymorphism and anonymous inner-class problems in the Android static analyzer. We conducted an empirical assessment with DLtrace on 208 popular DL-based apps in the wild and found that 26.0% of the apps suffered from sensitive information leakage. Furthermore, DLtrace has a more robust performance than FlowDroid in detecting and identifying third-party APIs. The experimental results demonstrate that DLtrace expands FlowDroid in understanding DL-based apps and detecting security issues therein.

Keywords: mobile computing, deep learning apps, sensitive information, static analysis

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Authors: Esraa Alhadad

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Recently, there has been considerable debate surrounding the definition, conservation, and management of heritage. Over the past few years, there has been a growing call for the inclusion of local communities in heritage management. However, the perspectives on involvement, especially concerning key stakeholders like community members, often diverge significantly. While the theoretical foundation for community involvement is reasonably established, the application of this approach in heritage management has been sluggish. Achieving a balance to fulfill the diverse goals of stakeholders in any involvement project proves challenging in practice. Consequently, there is a dearth of empirical studies exploring the practical implications of effective tools in heritage management, and limited indication exists to persuade current authorities, such as governmental organizations, to share their influence with local community members. This research project delves into community involvement within heritage management as a potent means of constructing a robust management framework. Its objective is to assess both the extent and caliber of involvement within the management of heritage sites overall, utilizing a cultural mapping-centered methodology. The findings of this study underscore the significance of engaging the local community in both heritage management and planning endeavors. Ultimately, this investigation furnishes crucial empirical evidence and extrapolates valuable theoretical and practical insights that advance understanding of cultural mapping in pivotal areas, including the catalysts for involvement and collaborative decision-making processes.

Keywords: community involvement, heritage management, cultural mapping, stakeholder mangement

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Authors: Moustafa Osman Mohamed

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This paper will explore the influence of energy sector in Arab Republic of Egypt which has shared its responsibilities of many environmental challenges as the second largest economy in the Middle East (after Iran). Air and water pollution, desertification, inadequate disposal of solid waste and damage to coral reefs are serious problems that influence environmental management in Egypt. The intensive reliance of high population density and strong industrial growth are wearing Egypt's resources, and the rapidly-growing population has forced Egypt to breakdown agricultural land to residential and relevant use of commercial ingestion. The depletion effects of natural resources impose the government to apply innovation techniques in emission control and focus on sustainability. The cogeneration will be presented to control thermal losses and increase efficiency of energy power system.

Keywords: cogeneration, environmental management, power electricity, energy indicators

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Authors: Hao Li, Guy Y. Cornejo Maceda, Yiqing Li, Jianguo Tan, Marek Morzynski, Bernd R. Noack

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We propose an automated analysis of the flow control behaviour from an ensemble of control laws and associated time-resolved flow snapshots. The input may be the rich database of machine learning control (MLC) optimizing a feedback law for a cost function in the plant. The proposed methodology provides (1) insights into the control landscape, which maps control laws to performance, including extrema and ridge-lines, (2) a catalogue of representative flow states and their contribution to cost function for investigated control laws and (3) visualization of the dynamics. Key enablers are classification and feature extraction methods of machine learning. The analysis is successfully applied to the stabilization of a mixing layer with sensor-based feedback driving an upstream actuator. The fluctuation energy is reduced by 26%. The control replaces unforced Kelvin-Helmholtz vortices with subsequent vortex pairing by higher-frequency Kelvin-Helmholtz structures of lower energy. These efforts target a human interpretable, fully automated analysis of MLC identifying qualitatively different actuation regimes, distilling corresponding coherent structures, and developing a digital twin of the plant.

Keywords: machine learning control, mixing layer, feedback control, model-free control

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Authors: Pi-Lan Yang

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It is controversial which type of gloss condition (i.e., gloss language or gloss position) is more effective in second or foreign language (L2) vocabulary learning. The present study compared the performance on learning ten English words in the conditions of L2 English reading with no glosses and with glosses of Chinese equivalents/translations and L2 English definitions at the side of a page and at an attached sheet for low-intermediate Chinese-speaking learners of English, who were technology university students in Taiwan. It is found first that the performances on the immediate posttest and the delayed posttest were overall better in the gloss condition than those in the no-gloss condition. Next, it is found that the glosses of Chinese translations were more effective and sustainable than those of L2 English definitions. Finally, the effects of L2 English glosses at the side of a page were observed to be less sustainable than those at an attached sheet. In addition, an opinion questionnaire used also showed a preference for the glosses of Chinese translations in L2 English reading. These results would be discussed in terms of automated lexical access, sentence processing mechanisms, and the trade-off nature of storage and processing functions in working memory system, proposed by the capacity theory of language comprehension.

Keywords: glosses of Chinese equivalents/translations, glosses of L2 English definitions, L2 vocabulary learning, L2 English reading

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Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

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The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

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Authors: Aya Salama

Abstract:

Digital Twin is an emerging research topic that attracted researchers in the last decade. It is used in many fields, such as smart manufacturing and smart healthcare because it saves time and money. It is usually related to other technologies such as Data Mining, Artificial Intelligence, and Machine Learning. However, Human digital twin (HDT), in specific, is still a novel idea that still needs to prove its feasibility. HDT expands the idea of Digital Twin to human beings, which are living beings and different from the inanimate physical entities. The goal of this research was to create a Human digital twin that is responsible for real-time human replies automation by simulating human behavior. For this reason, clustering, supervised classification, topic extraction, and sentiment analysis were studied in this paper. The feasibility of the HDT for personal replies generation on social messaging applications was proved in this work. The overall accuracy of the proposed approach in this paper was 63% which is a very promising result that can open the way for researchers to expand the idea of HDT. This was achieved by using Random Forest for clustering the question data base and matching new questions. K-nearest neighbor was also applied for sentiment analysis.

Keywords: human digital twin, sentiment analysis, topic extraction, supervised machine learning, unsupervised machine learning, classification, clustering

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Authors: Shamshuddin K., Nagaraj Vannal, Diwakar Kulkarni

Abstract:

This paper presents details of teaching and learning pedagogical techniques attempted for the undergraduate engineering program to improve the concentration span of students in a classroom. The details of activities such as valid statement, quiz competition, classroom paper, group work and product marketing to make the students remain active for the entire class duration and to improve presentation skills are presented. These activities shown tremendous improvement in student’s performance in academics, also in asking questions, concept understanding and interaction with the course instructor. With these pedagogical activities we are able to achieve Program outcome elements and ABET Program outcomes such as d, i, g and h which are difficult to achieve through the conventional teaching methods.

Keywords: activities, pedagogy, interactive learning, valid statement, quiz competition, classroom papers, group work, product marketing

Procedia PDF Downloads 629

Authors: María-Dolores Olvera-Lobo, Bryan John Robinson, Juncal Gutierrez-Artacho

Abstract:

Graduates are equipped with a wide range of generic competencies which complement solid curricular competencies and facilitate their access to the labour market in diverse fields and careers. However, some generic competencies such as instrumental, personal and systemic competencies related to teamwork and interpersonal communication skills, decision-making and organization skills are seldom taught explicitly and even less often assessed. In this context, translator training has embraced a broad range of competencies specified in the undergraduate program currently taught at universities and opens up the learning experience to cover areas often ignored due to the difficulties inherent in both teaching and assessment. In practice, translator training combines two well-established approaches to teaching/learning: project-based learning and genuinely cooperative – or merely collaborative – learning. Our professional approach to translator training is a model focused on and adapted to the teleworking context of professional translation and presented through the medium of blended e-learning. Teamwork-related competencies are extremely relevant, and they require explicit and implicit teaching so that graduates can be confident about their capacity to make their way in professional contexts. In order to highlight the importance of teamwork and intra-team relationships beyond the classroom, we aim to raise awareness of teamwork processes so as to empower translation students in managing their interaction and ensure that they gain valuable pre-professional experience. With these objectives, at the University of Granada (Spain) we have developed a range of classroom activities and assessment tools. The results of their application are summarized in this study.

Keywords: blended learning, collaborative teamwork, cross-curricular competencies, higher education, intra-team relationships, students’ perceptions, translator training

Procedia PDF Downloads 149

Authors: Eunice H. Li

Abstract:

This e-Poster presents how the ‘digital backpack’ was introduced to primary school children in Ivory Coast. The idea of a ‘digital backpack’ was initiated by Mr. Thierry N’Doufou in 2012, who later designed and presented to the rest of the world in September 2014. The motivation behind the backpack was to relieve children of the heavy-weight they carry in their school backpacks. Another motivation was to promote Ivory Coast as a country where all children are brought into the digital era. Thierry N’Doufou regards education as the means by which his nation and the entire African Continent can be developed as a prosperous territory. The ‘digital backpack’ contains the entire curriculum for each class and favours a constructivist approach to learning. The children’s notes and exercises are also included in the pack. Additionally, teachers and parents are able to monitor remotely children’s activities while they are working with the ‘backpack’. Teachers are also able to issue homework, assess student’s progress and manage the student’s coursework. This means that teachers should always think the most appropriate pedagogies that can be used to help children to learn. Furthermore, teachers, parents and fellow students are able to have conversations and discussions by using web portals. It is also possible to access more apps if children would like to have additional learning activities. From the presentation in the e-Poster, it seems reasonable to conclude that the ‘digital backpack’ has potential to reach other-level of education. In this way, all will be able to benefit from this new invention.

Keywords: pedagogy, curriculum, constructivism, social constructivism, distance learning environment, ubiquitous learning environment

Procedia PDF Downloads 642

Authors: Shatha Ahmad Alharthi

Abstract:

Prior research suggests that reduced social interaction can negatively affect well-being and impair mental health (e.g., depression and anxiety), resulting in lower academic performance. The COVID-19 pandemic has significantly limited social interaction among Saudi Arabian school children since the government closed schools and implemented lockdown restrictions to reduce the spread of the disease. These restrictions have resulted in prolonged remote learning for middle school students with unknown consequences for perceived academic performance, mental health, and well-being. This research project explores how middle school Saudi students’ current remote learning practices affect their mental health (e.g., depression and anxiety) and well-being during the lockdown. Furthermore, the study will examine the association between social interaction, mental health, and well-being pertaining to students’ perceptions of their academic achievement. Research findings could lead to a better understanding of the role of lockdown on depression, anxiety, well-being and perceived academic performance. Research findings may also inform policy-makers or practitioners (e.g., teachers and school leaders) about the importance of facilitating increased social interactions in remote learning situations and help to identify important factors to consider when seeking to re-integrate students into a face-to-face classroom setting. Potential implications for future educational research include exploring remote learning interventions targeted at bolstering students’ mental health and academic achievement during periods of remote learning.

Keywords: depression, anxiety, academic performance, social interaction

Procedia PDF Downloads 100