Search results for: motivation techniques

Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

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This article offers a approach to the automatic discovery of semantic concepts and links in the domain of Oil Exploration and Production (E&P). Machine learning methods combined with textual pre-processing techniques were used to detect local patterns in texts and, thus, generate new concepts and new semantic links. Even using more specific vocabularies within the oil domain, our approach has achieved satisfactory results, suggesting that the proposal can be applied in other domains and languages, requiring only minor adjustments.

Keywords: semantic links, data mining, linked data, SKOS

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Authors: Akhila Vasudev, Himanshu Kaushik, Tadikonda Venkata Bharat

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A large number of mine tailings are produced every year as part of the extraction process of phosphates, gold, copper, and other materials. Mine tailings are high in water content and have very slow dewatering behavior. The efficient design of tailings dam and economical disposal of these slurries requires the knowledge of tailings consolidation behavior. The large-strain consolidation theory closely predicts the self-weight consolidation of these slurries as the theory considers the conservation of mass and momentum conservation and considers the hydraulic conductivity as a function of void ratio. Classical laboratory techniques, such as settling column test, seepage consolidation test, etc., are expensive and time-consuming for the estimation of hydraulic conductivity variation with void ratio. Inverse estimation of the constitutive relationships from the measured settlement versus time curves is explored. In this work, inverse analysis based on metaheuristics techniques will be explored for predicting the hydraulic conductivity parameters for mine tailings from the base excess pore water pressure dissipation curve and the initial conditions of the mine tailings. The proposed inverse model uses particle swarm optimization (PSO) algorithm, which is based on the social behavior of animals searching for food sources. The finite-difference numerical solution of the forward analytical model is integrated with the PSO algorithm to solve the inverse problem. The method is tested on synthetic data of base excess pore pressure dissipation curves generated using the finite difference method. The effectiveness of the method is verified using base excess pore pressure dissipation curve obtained from a settling column experiment and further ensured through comparison with available predicted hydraulic conductivity parameters.

Keywords: base excess pore pressure, hydraulic conductivity, large strain consolidation, mine tailings

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Authors: Paolo Lenzuni

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Cost-effectiveness of noise abatement treatments at the workplace has not yet received adequate consideration. Furthermore, most of the published work is focused on productivity, despite the poor correlation of this quantity with noise levels. There is currently no tool to estimate the social benefit associated to a specific noise abatement treatment, and no comparison among different options is accordingly possible. In this paper, we present an algorithm which has been developed to predict the cost-effectiveness of any planned noise control treatment in a workplace. This algorithm is based the estimates of hearing threshold shifts included in ISO 1999, and on compensations that workers are entitled to once their work-related hearing impairments have been certified. The benefits of a noise abatement treatment are estimated by means of the lower compensation costs which are paid to the impaired workers. Although such benefits have no real meaning in strictly monetary terms, they allow a reliable comparison between different treatments, since actual social costs can be assumed to be proportional to compensation costs. The existing European legislation on occupational exposure to noise it mandates that the noise exposure level be reduced below the upper action limit (85 dBA). There is accordingly little or no motivation for employers to sustain the extra costs required to lower the noise exposure below the lower action limit (80 dBA). In order to make this goal more appealing for employers, the algorithm proposed in this work also includes an ad-hoc element that promotes actions which bring the noise exposure down below 80 dBA. The algorithm has a twofold potential: 1) it can be used as a quality index to promote cost-effective practices; 2) it can be added to the existing criteria used by workers’ compensation authorities to evaluate the cost-effectiveness of technical actions, and support dedicated employers.

Keywords: cost-effectiveness, noise, occupational exposure, treatment

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Authors: Mohamed Ben Rabha

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In this paper, we report on the effect of porous silicon (PS) treatment on the surface passivation of monocrystalline silicon (c-Si). PS film with a thickness of 80 nm was deposited by stain etching. It was demonstrated that PS coating is a very interesting solution for surface passivation. The level of surface passivation is determined by techniques based on photoconductance and FTIR. As a results, the effective minority carrier lifetime increase from 2 µs to 7 µs at ∆n=1015 cm-3 and the reflectivity reduce from 28 % to about 7 % after PS coating.

Keywords: porous silicon, effective minority carrier lifetime, reflectivity

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Authors: Tanimola Kazeem Abiodun

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In Nigeria, both formal education and distance learning opportunities are used in teacher training. Practical courses aim to improve the skills of teacher candidates in a school environment. Teacher candidates attend kindergarten classes under the supervision of a teacher. In this context, the guiding skills of teachers gain importance in terms of shaping candidates’ perceptions about teaching profession. In this study, the teachers’ perceptions related to the guiding skills within the practical courses were determined. Also, the perceptions and applications related to guiding skills were compared. A Likert scale questionnaire and an open-ended question were used to determine perceptions and applications. 120 questionnaires were taken into consideration and analyses of data were performed by using percentage distribution and QSR Nvivo 8 program. In this study, statements related to teachers’ perceptions about the guiding skills were asked and it is determined that almost all the teachers agreed about the importance of these statements. On the other hand, how these guidance skills are applied by teachers is also queried with an open-ended question. Finally, thoughts and applications related to guidance skills were compared to each other. Based on this comparison, it is seen that there are some differences between the thoughts and applications especially related with time management, planning, feedbacks, curriculum, workload, rules and guidance. It can be said that some guidance skills cannot be controlled only by teachers. For example, candidates’ motivation, attention, population and educational environment are also determinative factors for effective guidance. In summary, it is necessary to have prior conditions for teachers to apply these idealized guidance skills for training more successful candidates to pre-school education era. At this point, organization of practical courses by the faculties gains importance and in this context it is crucial for faculties to revise their applications based on more detailed researches.

Keywords: teacher training, guiding skills, education, practical courses

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Authors: Gaurav Kumar Sinha

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In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

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Authors: Sharifa Alduraibi, Abir El Sadik, Ahmed Elzainy, Alaa Alduraibi, Ahmed Alsolai

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Introduction: Problem-based learning (PBL) is an active student-centered educational modality, influenced by the students' interest that required continuous motivation to improve their engagement. The new era of professional information technology facilitated the utilization of educational multimedia, such as videos, soundtracks, and photographs promoting students' learning. The aim of the present study was to introduce multimedia-enriched PBL scenarios for the first time in college of medicine, Qassim University, as an incentive for better students' engagement. In addition, students' performance and satisfaction were evaluated. Methodology: Two multimedia-enhanced PBL scenarios were implemented to the third years' students in the urinary system block. Radiological images, plain CT scan, and X-ray of the abdomen and renal nuclear scan correlated with their pathological gross photographs were added to the scenarios. One week before the first sessions, pre-recorded orientation videos for PBL tutors were submitted to clarify the multimedia incorporated in the scenarios. Other two traditional PBL scenarios devoid of multimedia demonstrating the pathological and radiological findings were designed. Results and Discussion: Comparison between the formative assessments' results by the end of the two PBL modalities was done. It revealed significant increase in students' engagement, critical thinking and practical reasoning skills during the multimedia-enhanced sessions. Students' perception survey showed great satisfaction with the new strategy. Conclusion: It could be concluded from the current work that multimedia created technology-based teaching strategy inspiring the student for self-directed thinking and promoting students' overall achievement.

Keywords: multimedia, pathology and radiology images, problem-based learning, videos

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Authors: Abdou Elhendy

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Numerous study have shown the efficacy of the percutaneous intervention (PCI) and coronary stenting in improving left ventricular function and relieving exertional angina. Furthermore, PCI remains the main line of therapy in acute myocardial infarction. Improvement of procedural techniques and new devices have resulted in an increased number of PCI in those with difficult and extensive lesions, multivessel disease as well as total occlusion. Immediate and late outcome may be compromised by acute thrombosis or the development of fibro-intimal hyperplasia. In addition, progression of coronary artery disease proximal or distal to the stent as well as in non-stented arteries is not uncommon. As a result, complications can occur, such as acute myocardial infarction, worsened heart failure or recurrence of angina. In a stent, restenosis can occur without symptoms or with atypical complaints rendering the clinical diagnosis difficult. Routine invasive angiography is not appropriate as a follow up tool due to associated risk and cost and the limited functional assessment. Exercise and pharmacologic stress testing are increasingly used to evaluate the myocardial function, perfusion and adequacy of revascularization. Information obtained by these techniques provide important clues regarding presence and severity of compromise in myocardial blood flow. Stress echocardiography can be performed in conjunction with exercise or dobutamine infusion. The diagnostic accuracy has been moderate, but the results provide excellent prognostic stratification. Adding myocardial contrast agents can improve imaging quality and allows assessment of both function and perfusion. Stress radionuclide myocardial perfusion imaging is an alternative to evaluate these patients. The extent and severity of wall motion and perfusion abnormalities observed during exercise or pharmacologic stress are predictors of survival and risk of cardiac events. According to current guidelines, stress echocardiography and radionuclide imaging are considered to have appropriate indication among patients after PCI who have cardiac symptoms and those who underwent incomplete revascularization. Stress testing is not recommended in asymptomatic patients, particularly early after revascularization, Coronary CT angiography is increasingly used and provides high sensitive for the diagnosis of coronary artery stenosis. Average sensitivity and specificity for the diagnosis of in stent stenosis in pooled data are 79% and 81%, respectively. Limitations include blooming artifacts and low feasibility in patients with small stents or thick struts. Anatomical and functional cardiac imaging modalities are corner stone for the assessment of patients after PCI and provide salient diagnostic and prognostic information. Current imaging techniques cans serve as gate keeper for coronary angiography, thus limiting the risk of invasive procedures to those who are likely to benefit from subsequent revascularization. The determination of which modality to apply requires careful identification of merits and limitation of each technique as well as the unique characteristic of each individual patient.

Keywords: coronary artery disease, stress testing, cardiac imaging, restenosis

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Authors: Wang Qiaowei, Gao Yujiang

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With the economic growth and rapid urbanization after the reform and openness, some of China's fast-growing cities have demolished former dwellings and built modern residential quarters. The blind, incomplete reference to western modern cities and the one-off construction lacking feedback mechanism have intensified such phenomenon, causing the citizen gradually expanded their living scale with the popularization of car traffic, and the peer-to-peer lifestyle gradually settled. The construction of large-scale commercial centers has caused obstacles to small business around the residential areas, leading to space for residents' interaction has been compressed. At the same time, the advocated Central Business District (CBD) model even leads to the unsatisfactory reconstruction of many historical blocks such as the Hangzhou Southern Song Dynasty Imperial Street. However, the popularity of historical spaces such as Wuzhen and Hongcun also indicates the collective memory and needs of the street space for Chinese residents. The evolution of Shanghai TianZiFang also proves the importance of the motivation of space participants in space construction in the context of the “top-down” construction model in China. In fact, there are frequent occurrences of “reconstruction”, which may redefine the space, in various residential areas. If these activities can be selectively controlled and encouraged, it will be beneficial to activate the public space as well as the residents’ intercourse, so that the traditional Chinese street space can be reconstructed in the context of modern cities.

Keywords: rapid urbanization, traditional street space, space re-construction, bottom-up design

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Authors: M. Chen, H. Lee, D. M. Weary

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China is the world’s largest egg producer, with more than 90% of production occurring in conventional cages. Cage-free housing systems offer the potential for improving hen welfare, but the growth of this system requires consumer demand, making it is important to understand consumers’ willingness to engage with cage-free eggs. Previous survey research indicates that the majority of Chinese consumers have a basic understanding of cage-free eggs and that some are willing to pay a price premium for these eggs. The aim of this research is to understand consumer behaviour, experience, and motivations when purchasing cage-free eggs in China. Purposive sampling will be used to select 20 participants from each of 2 groups: 1) consumers of cage-free eggs and 2) sales representatives who promote these eggs directly to consumers in supermarkets. This 4-month study will use methods of virtual ethnography to interact with participants repeatedly. Consumers will be asked to share their egg shopping, cooking, and eating experiences, and sales representatives will be asked to share their experiences promoting the eggs to consumers. Data collection will involve audio-recorded interviews, informal conversations (casual texts and calls), participant observation (video calling during shopping, cooking, and eating), and informant diaries (written reflections, photos, videos). All data (field notes, transcripts, diaries, photos, and videos) will be analyzed using Thematic Analysis. We expect that these will result in a nuanced understanding of consumer purchasing behaviour and motivation and will thus help identify strategies to promote higher animal welfare and cage-free egg products in China.

Keywords: animal welfare, cage-free eggs, China, consumer behaviour, ethnography

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Authors: Tholokuhle T. Ntshakala, Seraphin D. Eyono Obono

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Nations are still finding it quite difficult to win mega sport competitions despite the major contribution of sport to society in terms of social and economic development, personal health, and in education. Even though the world of sports has been transformed into a huge global economy, it is important to note that the first step of sport is usually its introduction to children at school through physical education or PE. In other words, nations who do not win mega sport competitions also suffer from a weak and neglected PE system. This problem of the neglect of PE systems is the main motivation of this research aimed at examining the factors affecting the perceived awareness of physical education teachers on the ICT's that are adoptable for the teaching and learning of physical education. Two types of research objectives will materialize this aim: relevant theories will be identified in relation to the analysis of the perceived ICT awareness of PE teachers and subsequent models will be compiled and designed from existing literature; the empirical testing of such theories and models will also be achieved through the survey of PE teachers from the Camperdown magisterial district of the KwaZulu-Natal province of South Africa. The main hypothesis at the heart of this study is the relationship between the demographics of PE teachers, their behavior both as individuals and as social entities, and their perceived awareness of the ICTs that are adoptable for PE, as postulated by existing literature; except that this study categorizes human behavior under performance expectancy, computer attitude, and social influence. This hypothesis was partially confirmed by the survey conducted by this research in the sense that performance expectancy and teachers’ age, gender, computer usage, and class size were found to be the only factors affecting their awareness of ICT's for physical education.

Keywords: human behavior, ICT Awareness, physical education, teachers

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Authors: Suraj Mehrotra

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The stock market is a volatile, bustling marketplace that is a cornerstone of economics. It defines whether companies are successful or in spiral. A thorough understanding of it is important - many companies have whole divisions dedicated to analysis of both their stock and of rivaling companies. Linking the world of finance and artificial intelligence (AI), especially the stock market, has been a relatively recent development. Predicting how stocks will do considering all external factors and previous data has always been a human task. With the help of AI, however, machine learning models can help us make more complete predictions in financial trends. Taking a look at the stock market specifically, predicting the open, closing, high, and low prices for the next day is very hard to do. Machine learning makes this task a lot easier. A model that builds upon itself that takes in external factors as weights can predict trends far into the future. When used effectively, new doors can be opened up in the business and finance world, and companies can make better and more complete decisions. This paper explores the various techniques used in the prediction of stock prices, from traditional statistical methods to deep learning and neural networks based approaches, among other methods. It provides a detailed analysis of the techniques and also explores the challenges in predictive analysis. For the accuracy of the testing set, taking a look at four different models - linear regression, neural network, decision tree, and naïve Bayes - on the different stocks, Apple, Google, Tesla, Amazon, United Healthcare, Exxon Mobil, J.P. Morgan & Chase, and Johnson & Johnson, the naïve Bayes model and linear regression models worked best. For the testing set, the naïve Bayes model had the highest accuracy along with the linear regression model, followed by the neural network model and then the decision tree model. The training set had similar results except for the fact that the decision tree model was perfect with complete accuracy in its predictions, which makes sense. This means that the decision tree model likely overfitted the training set when used for the testing set.

Keywords: machine learning, testing set, artificial intelligence, stock analysis

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Authors: Nilgün Katrancı, Pınar Göv

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The privatization of public services has intensified and extended the delivery of healthcare services at hospitals, which leads to an increase in health and safety risks for healthcare professionals. More efficient and effective delivery of healthcare services can be realized through the provision of occupational safety of healthcare professionals. However, healthcare professionals are exposed to more dangers, accidents, and diseases because of such reasons as present working conditions, hospital infections, lack of ergonomic design, medication, wastes, excessive work load, negligent attitudes of workers, violence, psychological risks, etc. Unsafe working conditions cause fear, injury and wearing impacts in healthcare professionals in many countries. Thus, it is emphasized that the protection of the health of healthcare professionals is important to have educated, healthy workers and adequate workforce. Occupational health and safety measures applied in health facilities are aimed at protecting workers and providing the safety of services and facilities. All activities to be undertaken at hospitals with regard to occupational safety in accordance with these goals will help to reduce costs and provide continuous services. At the same time, a safe working environment will increase worker satisfaction and motivation, sense of institutional belonging and indirectly patient safety and satisfaction. In addition, the control and correction of occupational safety activities are also as important as the implementation. Occupational health and safety practices in the facilities will also lead to positive developments for national economy and society. This study emphasizes that approaching occupational safety practices for healthcare professionals in a sensitive manner is important for enabling healthcare professionals to do more productive works in terms of physical, social and psychological aspects, maintaining the continuity of healthcare services and social and economic contributions.

Keywords: health facilities, healthcare professional, occupational health, occupational safety

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Authors: Lawrence Williams

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As the mechanism which converts domains to internet protocol (IP) addresses, Domain Name System (DNS) is an essential part of internet usage. It was not designed securely and can be subject to attacks. DNS attacks have become more frequent and sophisticated and the need for detecting and preventing them becomes more important for the modern network. DNS tunnelling attacks are one type of attack that are primarily used for distributed denial-of-service (DDoS) attacks and data exfiltration. Discussion of different techniques to detect and prevent DNS tunneling attacks is done. The methods, models, experiments, and data for each technique are discussed. A proposal about feasibility is made. Future research on these topics is proposed.

Keywords: DNS, tunneling, exfiltration, botnet

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Authors: M. O. Olayiwola

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Numerical solutions of the generalized Burger-Fisher are obtained using a Modified Variational Iteration Method (MVIM) with minimal computational efforts. The computed results with this technique have been compared with other results. The present method is seen to be a very reliable alternative method to some existing techniques for such nonlinear problems.

Keywords: burger-fisher, modified variational iteration method, lagrange multiplier, Taylor’s series, partial differential equation

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Authors: Mumtaz Ali Baloch

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This article aims at to review the policies and gaps including the socioeconomic and institutional factors that affected the enrollment of disabled children and caused drop-outs. It provides insights to scrutinize the gaps in policies, socioeconomic, and institutional factors with the specific concern in enrollment and drop out of disabled children in Pakistan, and Balochistan in particular. The findings of this study revealed that the old-age centralized policies and a number of socio-economic and institutional factors seemed to have significantly affected the enrollment and quality education in the case of physically disabled children. There were only a few schools functional in entire Balochistan. For example, an entire province (Balochistan) there are only two schools for disabled children, established in Quetta city. In the other 31 districts, an estimated population of 300,000 people of each district there were no schools for the disabled children. The findings of this study revealed that there is a great distinction between the policy and practice in the case of physically disabled children in Quetta, Balochistan. Consequently, such children seemed to have been out of schools. Dropout after the class eighth grade is almost 100%, as there are no high schools available for physically/disabled children, in Balochistan. The concerned organizations and authorities need to develop and ratify specific policies, provide required) facilities to the schools including sufficient budget, streamline the academic planning, and an effective monitoring and evaluation system. Only awareness and motivation could not help in improving the enrollment rate and decreasing the dropout in the case of physically disabled children. There is an urgent need to provide the required facilities to the schools. Almost all students needed assistive equipment, effective physical therapy as well as regular medical facilities. Such measures can improve the enrolment and rehabilitation of children.

Keywords: education policy, practices, physically disabled children, challenges, Balochistan, Pakistan

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Authors: Gulce Kanturer Yasar, Hayriye Esbah Tuncay

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Cultivated food production systems have coexisted harmoniously with nature for thousands of years through ancient techniques. Based on this experience, experimentation, and discovery, these culturally embedded methods have evolved to sustain food production, restore ecosystems, and harmoniously adapt to nature. In this era, as we seek solutions to food security challenges, enhancing and repairing our food production systems is crucial, making them more resilient to future disasters without harming the ecosystem. Instead of unsustainable conventional systems with ongoing destructive effects, we must investigate innovative and restorative production systems that integrate ancient wisdom and technology. Whether we consider agricultural fields, pastures, forests, coastal wetland ecosystems, or lagoons, it is crucial to harness the potential of these natural resources in addressing future global challenges, fostering both socio-economic resilience and ecological sustainability through strategic organization for food production. When thoughtfully designed and managed, marine-based food production has the potential to function as a living infrastructure system that addresses social and environmental challenges despite its known adverse impacts on the environment and local economies. These areas are also stages of daily life, vibrant hubs where local culture is produced and shared, contributing to the distinctive rural character of coastal settlements and exhibiting numerous spatial expressions of public nature. When we consider the history of humanity, indigenous communities have engaged in these sustainable production practices that provide goods for food, trade, culture, and the environment for many ages. Ecosystem restoration and socio-economic resilience can be achieved by combining production techniques based on ecological knowledge developed by indigenous societies with modern technologies. Coastal lagoons are highly productive coastal features that provide various natural services and societal values. They are especially vulnerable to severe physical, ecological, and social impacts of changing, challenging global conditions because of their placement within the coastal landscape. Coastal lagoons are crucial in sustaining fisheries productivity, providing storm protection, supporting tourism, and offering other natural services that hold significant value for society. Although there is considerable literature on the physical and ecological dimensions of lagoons, much less literature focuses on their economic and social values. This study will discuss the possibilities of coastal lagoons to achieve both ecologically sustainable and socio-economically resilient while maintaining their productivity by combining local techniques and modern technologies. The case study will present Turkey’s traditional aquaculture method, "Dalyans," predominantly operated by small-scale farmers in coastal lagoons. Due to human, ecological, and economic factors, dalyans are losing their landscape characteristics and efficiency. These 1000-year-old ancient techniques, rooted in centuries of traditional and agroecological knowledge, are under threat of tourism, urbanization, and unsustainable agricultural practices. Thus, Dalyans have diminished from 29 to approximately 4-5 active Dalyans. To deal with the adverse socio-economic and ecological consequences on Turkey's coastal areas, conserving Dalyans by protecting their indigenous practices while incorporating contemporary methods is essential. This study seeks to generate scenarios that envision the potential ways protection and development can manifest within case study areas.

Keywords: coastal foodscape, lagoon aquaculture, regenerative food systems, watershed food networks

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Authors: Ebtisam Alqahtani

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The purpose of this study is to investigate academic staff perspectives on using Augmented Reality in teaching practice to support students learning remotely during the COVID pandemic. the study adopted the DTPB theoretical model to guide the identification of key potential factors that could motivate academic staff to use or not use AR in teaching practices. A mixing method design was adopted for a better understanding of the study problem. A survey was completed by 851 academic staff, and this was followed by interviews with 20 academic staff. Statistical analyses were used to assess the survey data, and thematic analysis was used to assess the interview data. The study finding indicates that 75% of academic staff were aware of AR as a pedagogical tool, and they agreed on the potential benefits of AR in teaching and learning practices. However, 36% of academic staff use it in teaching and learning practice, and most of them agree with most of the potential barriers to adopting AR in educational environments. In addition, the study results indicate that 91% of them are planning to use it in the future. The most important factors that motivated them to use it in the future are the COVID pandemic factor, hedonic motivation factor, and academic staff attitude factor. The perceptions of academic staff differed according to the universities they attended, the faculties they worked in, and their gender. This study offers further empirical support for the DTPB model, as well as recommendations to help higher education implement technology in its educational environment based on the findings of the study. It is unprecedented the study the necessity of the use of AR technologies in the time of Covid-19. Therefore, the contribution is both theoretical and practice

Keywords: higher education, academic staff, AR technology as pedological tools, teaching and learning practice, benefits of AR, barriers of adopting AR, and motivating factors to adopt AR

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Authors: Yuan-Jye Tseng, Ching-Yen Chen

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In the design cycle, a main design task is to determine the external shape of the product. The external shape of a product is one of the key factors that can affect the customers’ preferences linking to the motivation to buy the product, especially in the case of a consumer electronic product such as a mobile phone. The relationship between the external shape and the customer preferences needs to be studied to enhance the customer’s purchase desire and action. In this research, a design for customer preferences model is developed for investigating the relationships between the external shape and the customer preferences of a product. In the first stage, the names of the geometric features are collected and evaluated from the data of the specified internet web pages using the developed text miner. The key geometric features can be determined if the number of occurrence on the web pages is relatively high. For each key geometric feature, the numerical values are explored using the text miner to collect the internet data from the web pages. In the second stage, a cluster analysis model is developed to evaluate the numerical values of the key geometric features to divide the external shapes into several groups. Several design suggestion cases can be proposed, for example, large model, mid-size model, and mini model, for designing a mobile phone. A customer preference index is developed by evaluating the numerical data of each of the key geometric features of the design suggestion cases. The design suggestion case with the top ranking of the customer preference index can be selected as the final design of the product. In this paper, an example product of a notebook computer is illustrated. It shows that the external shape of a product can be used to drive customer preferences. The presented design for customer preferences model is useful for determining a suitable external shape of the product to increase customer preferences.

Keywords: cluster analysis, customer preferences, design evaluation, design for customer preferences, product design

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Authors: Yuxuan Tang

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Cognitive diagnostic assessment has received much attention in second language education, and assessment for it can provide pedagogically useful feedback for language learners. However, there is a lack of research on how students interpret and use cognitive diagnostic feedback. Thus the present study aims to adopt a mixed-method approach mainly to explore the relationship between the goal-orientation and students' response to cognitive diagnostic feedback. Almost 200 Chinese undergraduates from two universities in Xi'an, China, will be invited to do a cognitive diagnostic reading test, and each student will receive specialized cognitive diagnostic feedback, comprising of students' reading attributes mastery level generated by applying a well-selected cognitive diagnostic model, students' perceived reading ability assessed by a self-assessing questionnaire and students’ level position in the whole class. And a goal-orientation questionnaire and a self-generated questionnaire on the perception of feedback will be given to students the moment they receive feedback. In addition, interviews of students will be conducted on their future plans to see whether they have awareness of carrying out studying plans. The study aims to find a new perspective towards how students use and interpret cognitive diagnostic feedback in terms of their different goal-orientation (self-based, task-based, and other-based goals) by applying the newest goal orientation model, which is an important construct of motivation in psychology, seldom researched under language learning area. And the study is expected to provide evidence on how diagnostic feedback promotes students' learning under the educational belief of assessment for learning. Practically speaking, according to the personalized diagnostic feedback, students can take remedial self-learning more purposefully, and teachers can target students' weaknesses to adjust teaching methods and carry out tailored teaching.

Keywords: assessment for learning, cognitive diagnostic assessment, goal-orientation, personalized feedback

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Authors: Caterina Calicchio, Talia Sbardella

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The ability to move through geographical and symbolic spaces is key for building new nodes and social relationships. Especially in the framework of language learning, accepting and valuing diversity can help to create a constructive atmosphere of cooperation, innovation, and creativity. Thus, it is important to outline the stages of forming a learning community, focusing on the characteristics that can favor its development. It is known that elements like curiosity and motivation are significant for individual language learning; hence, the study attempts to investigate how factors like openness to diversity and cultural immersion could improve Italian learning and teaching. This paper aims to indicate the factors that could be significant for the development of a Learning Community by presenting a case study on a course on Italian as a second language for beginners: first, the theoretical matrices underlying social learning will be outlined. Secondly, a quantitative study will be described based on an adaptation of the openness to diversity and some insights psychometric scale questionnaire developed at the Umbra Institute. The questionnaire was delivered to 52 American college students with open-ended and closed-ended questions. Students were asked to specify their level of agreement to a set of statements on a six-point Likert scale ranging from (1) Strongly disagree to (6) Strongly agree. The data has been analyzed with a quantitative and qualitative method and has been represented in a pie chart and in a histogram. Moreover, mean and frequency have been calculated. The research findings demonstrate that openness to diversity and challenge enhances cross-cutting skills such as intercultural and communicative competence: through cultural immersion and the facility of speaking with locals, the participants have been able to develop their own Italian L2 language community. The goal is to share with the scientific community some insights to trace possible future lines of research.

Keywords: Italian as second language, language learning, learning community, openness to diversity

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Addin Osman, Anwar Ali Yahya, Mohammed Basit Kamal

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Datasets or collections are becoming important assets by themselves and now they can be accepted as a primary intellectual output of a research. The quality and usage of the datasets depend mainly on the context under which they have been collected, processed, analyzed, validated, and interpreted. This paper aims to present a collection of program educational objectives mapped to student’s outcomes collected from self-study reports prepared by 32 engineering programs accredited by ABET. The manual mapping (classification) of this data is a notoriously tedious, time consuming process. In addition, it requires experts in the area, which are mostly not available. It has been shown the operational settings under which the collection has been produced. The collection has been cleansed, preprocessed, some features have been selected and preliminary exploratory data analysis has been performed so as to illustrate the properties and usefulness of the collection. At the end, the collection has been benchmarked using nine of the most widely used supervised multiclass classification techniques (Binary Relevance, Label Powerset, Classifier Chains, Pruned Sets, Random k-label sets, Ensemble of Classifier Chains, Ensemble of Pruned Sets, Multi-Label k-Nearest Neighbors and Back-Propagation Multi-Label Learning). The techniques have been compared to each other using five well-known measurements (Accuracy, Hamming Loss, Micro-F, Macro-F, and Macro-F). The Ensemble of Classifier Chains and Ensemble of Pruned Sets have achieved encouraging performance compared to other experimented multi-label classification methods. The Classifier Chains method has shown the worst performance. To recap, the benchmark has achieved promising results by utilizing preliminary exploratory data analysis performed on the collection, proposing new trends for research and providing a baseline for future studies.

Keywords: ABET, accreditation, benchmark collection, machine learning, program educational objectives, student outcomes, supervised multi-class classification, text mining

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Authors: Tamara Matevosyan

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In this globalized world, intercultural communication is becoming essential for understanding communication among people, for developing understanding of cultures, to appreciate the opportunities and challenges that each culture presents to people. Moreover, it plays an important role in developing an ideal personification to understand different behaviors in different cultures. Native speakers assimilate sociolinguistic knowledge in natural conditions, while it is a great problem for language learners, and in this context feature films reveal cultural peculiarities and involve students in real communication. As we know nowadays the key role of language learning is the development of intercultural competence as communicating with someone from a different cultural background can be exciting and scary, frustrating and enlightening. Intercultural competence is important in FL learning classroom and here feature films can perform as essential tools to develop this competence and overcome the intercultural gap that foreign students face. Current proposal attempts to reveal the correlation of the given culture and language through feature films. To ensure qualified, well-organized and practical classes on Intercultural Communication for language learners a number of methods connected with movie watching have been implemented. All the pre-watching, while watching and post-watching methods and techniques are aimed at developing students’ communicative competence. The application of such activities as Climax, Role-play, Interactive Language, Daily Life helps to reveal and overcome mistakes of cultural and pragmatic character. All the above-mentioned activities are directed at the assimilation of the language vocabulary with special reference to the given culture. The study dwells into the essence of culture as one of the core concepts of intercultural communication. Sometimes culture is not a priority in the process of language learning which leads to further misunderstandings in real life communication. The application of various methods and techniques with feature films aims at developing students’ cultural competence, their understanding of norms and values of individual cultures. Thus, feature film activities will enable learners to enlarge their knowledge of the particular culture and develop a fundamental insight into intercultural communication.

Keywords: climax, intercultural competence, interactive language, role-play

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Authors: N. Khanyile, P. Dlamini, M. Masenya

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Background: Most of the population in Africa is still dependent on indigenous medicinal knowledge for treating and managing ailments. Indigenous traditional knowledge owners/practitioners who own this knowledge are consulted by communities, but their knowledge is not known how they get it. The question of how knowledge is acquired and preserved remains one of the biggest challenges in traditional healing and treatment with herbal medicines. It is regrettable that despite the importance and recognition of indigenous medicinal knowledge globally, the details of acquirement, storing and transmission, and preservation techniques are not known. Hence this study intends to unveil the process of acquirement and transmission, and preservation techniques of indigenous medical knowledge by its owners. Objectives: This study aims to assess the process of acquiring and preservation of traditional medicinal knowledge by traditional medicinal knowledge owners/practitioners in uMhlathuze Municipality, in the province of KwaZulu-Natal, South Africa. The study was guided by four research objectives which were to: identify the types of traditional medicinal knowledge owners who possess this knowledge, establish the approach used by indigenous medicinal knowledge owners/healers for acquiring medicinal knowledge, identify the process of preservation of medicinal knowledge by indigenous medicinal knowledge owners/healers, and determine the challenges encountered in transferring the knowledge. Method: The study adopted a qualitative research approach, and a snowball sampling technique was used to identify the study population. Data was collected through semi-structured interviews with indigenous medicinal knowledge owners. Results: The findings suggested that uMhlathuze municipality had different types of indigenous medicinal knowledge owners who possess valuable knowledge. These are diviners (Izangoma), faith healers (Abathandazi), and herbalists (Izinyanga). The study demonstrated that indigenous medicinal knowledge is acquired in many different ways, including visions, dreams, and vigorous training. The study also revealed the acquired knowledge is preserved or shared with specially chosen children and trainees. Conclusion: The study concluded that this knowledge is gotten through vigorous training, which requires the learner to be attentive and eager to learn. It was recommended that a study of this nature be conducted but at a broader level to enhance an informed conclusion and recommendations.

Keywords: preserving, indigenous medicinal knowledge, indigenous knowledge, indigenous medicinal knowledge owners/practitioners, acquiring

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Authors: Yanjie Zhu, André Jesus, Irwanda Laory

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Structural Health Monitoring (SHM), involving data acquisition, data interpretation and decision-making system aim to continuously monitor the structural performance of civil infrastructures under various in-service circumstances. The main value and purpose of SHM is identifying damages through data interpretation system. Research on SHM has been expanded in the last decades and a large volume of data is recorded every day owing to the dramatic development in sensor techniques and certain progress in signal processing techniques. However, efficient and reliable data interpretation for damage detection under environmental variations is still a big challenge. Structural damages might be masked because variations in measured data can be the result of environmental variations. This research reports a novel method based on single-channel Blind Signal Separation (BSS), which extracts environmental effects from measured data directly without any prior knowledge of the structure loading and environmental conditions. Despite the successful application in audio processing and bio-medical research fields, BSS has never been used to detect damage under varying environmental conditions. This proposed method optimizes and combines Ensemble Empirical Mode Decomposition (EEMD), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) together to separate structural responses due to different loading conditions respectively from a single channel input signal. The ICA is applying on dimension-reduced output of EEMD. Numerical simulation of a truss bridge, inspired from New Joban Line Arakawa Railway Bridge, is used to validate this method. All results demonstrate that the single-channel BSS-based method can recover temperature effects from mixed structural response recorded by a single sensor with a convincing accuracy. This will be the foundation of further research on direct damage detection under varying environment.

Keywords: damage detection, ensemble empirical mode decomposition (EEMD), environmental variations, independent component analysis (ICA), principal component analysis (PCA), structural health monitoring (SHM)

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Authors: Ahlem Bouziri, Chiraz Latiri, Eric Gaussier

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The steady growth in the size of textual document collections is a key progress-driver for modern information retrieval techniques whose effectiveness and efficiency are constantly challenged. Given a user query, the number of retrieved documents can be overwhelmingly large, hampering their efficient exploitation by the user. In addition, retaining only relevant documents in a query answer is of paramount importance for an effective meeting of the user needs. In this situation, the query expansion technique offers an interesting solution for obtaining a complete answer while preserving the quality of retained documents. This mainly relies on an accurate choice of the added terms to an initial query. Interestingly enough, query expansion takes advantage of large text volumes by extracting statistical information about index terms co-occurrences and using it to make user queries better fit the real information needs. In this respect, a promising track consists in the application of data mining methods to extract dependencies between terms, namely a generic basis of association rules between terms. The key feature of our approach is a better trade off between the size of the mining result and the conveyed knowledge. Thus, face to the huge number of derived association rules and in order to select the optimal combination of query terms from the generic basis, we propose to model the problem as a classification problem and solve it using a supervised learning algorithm such as SVM or k-means. For this purpose, we first generate a training set using a genetic algorithm based approach that explores the association rules space in order to find an optimal set of expansion terms, improving the MAP of the search results. The experiments were performed on SDA 95 collection, a data collection for information retrieval. It was found that the results were better in both terms of MAP and NDCG. The main observation is that the hybridization of text mining techniques and query expansion in an intelligent way allows us to incorporate the good features of all of them. As this is a preliminary attempt in this direction, there is a large scope for enhancing the proposed method.

Keywords: supervised leaning, classification, query expansion, association rules

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Authors: O. Nthoi-Molefe, V. Makwinja

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In the North West district of Botswana, Heritage tourism has the potential to offer tremendous economic and social opportunities for local communities in terms of supporting Tourism product development and entrepreneurship. This paper Identifies that Cultural Heritage Entrepreneur brings to the market goods and services, organizes and runs cultural heritage in a commercial or non-profit manner depending on characteristics of cultural resources identified. Data was collected through a series of focus group discussions that included sixteen village community members within the region. Data collected was transcribed and then further analyzed thematically to bring forward results to be analysed. Using Tsodilo Hills World Heritage Site as a case study, the researchers acknowledged that Cultural Heritage Entrepreneurs in that area should use a creative approach in order toidentify suitable solutions for financing different tourism activities starting with sponsored events, grant funds, donations, including the benefits of financial opportunities brough be foreign visitors and domestic tourists alike. The researchers also identified a need for specialized training for the identified entrepreneurs in order to maintain quality services of tourism products and sites (interpretation), information for tourists, visitation services, diversification, and upgrading of the heritage experience. The research reveals that the identified Cultural Heritage Entrepreneurs prefer economic motivation, exploitation over the cultural value of their resources, further calling for recommendations of the research that emphasize on the need for detailed training on how to valorize their cultural resources for the growth of Tourism in the area.

Keywords: education, community development, entrepreneurship, cultural tourism

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Authors: Recep Gundogan, Turgay Dindaroglu, Hikmet Gunal, Mustafa Ulukavak, Ron Bingner

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A majority of total soil losses in agricultural areas could be attributed to ephemeral gullies caused by heavy rains in conventionally tilled fields; however, ephemeral gully erosion is often ignored in conventional soil erosion assessments. Ephemeral gullies are often easily filled from normal soil tillage operations, which makes capturing the existing ephemeral gullies in croplands difficult. This study was carried out to determine topographic features, including slope and aspect composite topographic index (CTI) and initiation points of gully channels, using images obtained from unmanned aerial vehicle (UAV) images. The study area was located in Topcu stream watershed in the eastern Mediterranean Region, where intense rainfall events occur over very short time periods. The slope varied between 0.7 and 99.5%, and the average slope was 24.7%. The UAV (multi-propeller hexacopter) was used as the carrier platform, and images were obtained with the RGB camera mounted on the UAV. The digital terrain models (DTM) of Topçu stream micro catchment produced using UAV images and manual field Global Positioning System (GPS) measurements were compared to assess the accuracy of UAV based measurements. Eighty-one gully channels were detected in the study area. The mean slope and CTI values in the micro-catchment obtained from DTMs generated using UAV images were 19.2% and 3.64, respectively, and both slope and CTI values were lower than those obtained using GPS measurements. The total length and volume of the gully channels were 868.2 m and 5.52 m³, respectively. Topographic characteristics and information on ephemeral gully channels (location of initial point, volume, and length) were estimated with high accuracy using the UAV images. The results reveal that UAV-based measuring techniques can be used in lieu of existing GPS and total station techniques by using images obtained with high-resolution UAVs.

Keywords: aspect, compound topographic index, digital terrain model, initial gully point, slope, unmanned aerial vehicle

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Authors: Akudo Ejelonu, Sarah Willig, J. Anthony Sauder, Heather Murphy, Frances Shofer

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Background: The high prevalence of diarrheal diseases in the village of Tzununá, Guatemala is linked to lack of sanitation facilities and handwashing practices. Diarrheal diseases are preventable and improved access to latrines, hygiene education and clean water may improve sanitation by reducing the spread of disease. Objective: Between May 2015-January 2017, the University of Pennsylvania Chapter of Engineers Without Border (PennEWB) and local partners designed an intervention to reduce diarrheal disease by building pour flush latrines in 50 individual households and providing education on the importance of handwashing practice. Design/Methods: Through convenient sampling, we surveyed 45 households to evaluate the community’s knowledge of diarrheal disease, handwashing practices, and maintenance of the latrines. Results: 92% of the study participants experienced decrease of new cases of diarrheal disease after receiving a latrine. Only 11% washed their hands after defecating in the latrine. There was gap in understanding the health outcome of latrine sanitation and handwashing education. The respondents did not connect the reduction of diarrheal disease with latrine use and maintenance. Instead, they associated their motivation for latrine use with aesthetics, proximity to their home, ease and comfort, and reduction of shame. We recommend that PennEWB adopt UNICEF or WHO education on hand washing practice. Conclusion: Social interaction and social pressure drove the household use of latrines. The latrines are being valued and cleaned. The education that the residents received did not target norms and behaviors. Latrines could be used to create a new social norm that supports behavioral change.

Keywords: diarrheal disease, latrine, open defecation, water, sanitation and hygiene

Procedia PDF Downloads 139