Search results for: online learning environments

Authors: Binger Lu

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It remains unclear whether second language (L2) speakers could use discourse context cues to predict upcoming information as native speakers do during online comprehension. Some researchers propose that L2 learners may have a reduced ability to generate predictions during discourse processing. At the same time, there is evidence that discourse-level cues are weighed more heavily in L2 processing than in L1. Previous studies showed that L1 prediction is sensitive to the global validity of predictive cues. The current study aims to explore whether and to what extent L2 learners can dynamically and strategically adjust their prediction in accord with the global validity of predictive cues in L2 discourse comprehension as native speakers do. In a self-paced reading experiment, Chinese native speakers (N=128), C-E bilinguals (N=128), and English native speakers (N=128) read high-predictable (e.g., Jimmy felt thirsty after running. He wanted to get some water from the refrigerator.) and low-predictable (e.g., Jimmy felt sick this morning. He wanted to get some water from the refrigerator.) discourses in two-sentence frames. The global validity of predictive cues was manipulated by varying the ratio of predictable (e.g., Bill stood at the door. He opened it with the key.) and unpredictable fillers (e.g., Bill stood at the door. He opened it with the card.), such that across conditions, the predictability of the final word of the fillers ranged from 100% to 0%. The dependent variable was reading time on the critical region (the target word and the following word), analyzed with linear mixed-effects models in R. C-E bilinguals showed reliable prediction across all validity conditions (β = -35.6 ms, SE = 7.74, t = -4.601, p< .001), and Chinese native speakers showed significant effect (β = -93.5 ms, SE = 7.82, t = -11.956, p< .001) in two of the four validity conditions (namely, the High-validity and MedLow conditions, where fillers ended with predictable words in 100% and 25% cases respectively), whereas English native speakers didn’t predict at all (β = -2.78 ms, SE = 7.60, t = -.365, p = .715). There was neither main effect (χ^²(3) = .256, p = .968) nor interaction (Predictability: Background: Validity, χ^²(3) = 1.229, p = .746; Predictability: Validity, χ^²(3) = 2.520, p = .472; Background: Validity, χ^²(3) = 1.281, p = .734) of Validity with speaker groups. The results suggest that prediction occurs in L2 discourse processing but to a much less extent in L1, witha significant effect in some conditions of L1 Chinese and anull effect in L1 English processing, consistent with the view that L2 speakers are more sensitive to discourse cues compared with L1 speakers. Additionally, the pattern of L1 and L2 predictive processing was not affected by the global validity of predictive cues. C-E bilinguals’ predictive processing could be partly transferred from their L1, as prior research showed that discourse information played a more significant role in L1 Chinese processing.

Keywords: bilingualism, discourse processing, global validity, prediction, self-paced reading

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Authors: Pataraporn Kheawwan

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Preceptorship represents an important aspect in new nurse orientation. However, there was no formal preceptor training program developed for nurse preceptor in Thailand. The purposes of this study were to develop and evaluate formal preceptor training program for nurse preceptors in King Chulalongkorn Memorial Hospital, Thailand. A research and development study design was utilized in this study. Participants were 37 nurse preceptors. The program contents were delivered by e-learning material, class lecture, group discussion followed by simulation training. Knowledge of the participants was assessed pre and post program. Skill and critical thinking were assessed using Preceptor Skill and Decision Making Evaluation form at the end of program. Statistical significant difference in knowledge regarding preceptor role and coaching strategies between pre and post program were found. All participants had satisfied skill and decision making score after completed the program. Most of participants perceived benefits of preceptor training course. In conclusion, The results of this study reveal that the newly developed preceptorship course is an effective formal training course for nurse preceptors.

Keywords: preceptor, preceptorship, new nurse, clinical education

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Authors: N. Songumpai, W. Sumranwanich, S. Chatmaneerungcharoen

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This research aims to study the understanding of 8 aspects of nature of science (NOS). The research participants were 39 General Science student teachers who were selected by purposive sampling. In 2015 academic year, they enrolled in the course of Science Education Learning Management. Qualitative research was used as research methodology to understand how the student teachers propose on NOS. The research instruments consisted of open-ended questionnaires and semi-structure interviews that were used to assess students’ understanding of NOS. Research data was collected by 8 items- questionnaire and was categorized into students’ understanding of NOS, which consisted of complete understanding (CU), partial understanding (PU), misunderstanding (MU) and no understanding (NU). The findings reveal the majority of students’ misunderstanding of NOS regarding the aspects of theory and law(89.7%), scientific method(61.5%) and empirical evidence(15.4%) respectively. From the interview data, the student teachers present their misconceptions of NOS that indicate about theory and law cannot change; science knowledge is gained through experiment only (step by step); science is the things that are around humans. These results suggest that for effective science teacher education, the composition of design of NOS course needs to be considered. Therefore, teachers’ understanding of NOS is necessary to integrate into professional development program/course for empowering student teachers to begin their careers as strong science teachers in schools.

Keywords: nature of science, student teacher, no understanding, misunderstanding, partial understanding, complete understanding

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Authors: Simiao Ren, En Wei

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Drowning is a significant safety issue worldwide, and a robust computer vision-based alert system can easily prevent such tragedies in swimming pools. However, due to domain shift caused by the visual gap (potentially due to lighting, indoor scene change, pool floor color etc.) between the training swimming pool and the test swimming pool, the robustness of such algorithms has been questionable. The annotation cost for labeling each new swimming pool is too expensive for mass adoption of such a technique. To address this issue, we propose a domain-aware data augmentation pipeline based on Gaussian Poisson Generative Adversarial Network (GP-GAN). Combined with YOLOv8, we demonstrate that such a domain adaptation technique can significantly improve the model performance (from 0.24 mAP to 0.82 mAP) on new test scenes. As the augmentation method only require background imagery from the new domain (no annotation needed), we believe this is a promising, practical route for preventing swimming pool drowning.

Keywords: computer vision, deep learning, YOLOv8, detection, swimming pool, drowning, domain adaptation, generative adversarial network, GAN, GP-GAN

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Authors: Djelloul Nedjai

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The issue of cultural awareness triggers many controversies, especially in a context where individuals do not share the same cultural backgrounds and characteristics. The Algerian context is no exception. It has been widely documented by the literature that culture remains essential in many domains. In higher education, for instance, culture plays a pivotal role in shaping individuals’ perceptions and attitudes. Henceforth, the current paper attempts to look at the perceptions of the British culture held by students engaged in learning English as a Foreign Language (EFL) at the department of English at Banta 2 University, Algeria. It also inquires into EFL students’ perceptions of British culture. To address the aforementioned research queries, a descriptive study has been carried out wherein a questionnaire of fifteen (15) items has been deployed to collect students’ attitudes and perceptions toward British culture. Results showcase that, indeed, EFL students of the department of English at Banta 2 University hold both positive and negative perceptions towards British culture at different levels. The explanation could relate to the student's lack of acquaintance with and awareness of British culture. Consequently, this paper is an attempt to address the issue of cultural awareness from the perspective of EFL students.

Keywords: British culture, cultural awareness, EFL students’ perceptions, higher education

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Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

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This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

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Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

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The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

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Authors: Armijos-Orellana Ana, González-Calle María, Maldonado-Matute Juan, Guerrero-Maxi Pedro

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Nowadays, the digital economy represents a fundamental element to guarantee economic and social development, whose importance increased significantly with the arrival of the COVID-19 pandemic. However, despite the benefits it offers, it can also be detrimental to those developing countries characterized by a wide digital divide. It is for this reason that the objective of this research was to identify and describe the main characteristics, benefits, and obstacles of the digital economy for Latin American countries. Through a bibliographic review, using the analytical-synthetic method in the period 1995-2021, it was determined that the digital economy could give way to structural changes, reduce inequality, and promote processes of social inclusion, as well as promote the construction and participatory development of organizational structures and institutional capacities in Latin American countries. However, the results showed that the digital economy is still incipient in the region and at least three factors are needed to establish it: joint work between academia, the business sector and the State, greater emphasis on learning and application of digital transformation and the creation of policies that encourage the creation of digital organizations.

Keywords: developing countries, digital divide, digital economy, digital literacy, digital transformation

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Authors: M. A. Rahman, A. T. Ohta, H. V. Trinh, J. Hyvl

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Atmospheric pressure and oxygen (O2) concentration are critical life support parameters for human-occupied aerospace vehicles and habitats. Various medical conditions may require medical O2; for example, the American Medical Association has determined that commercial air travel exposes passengers to altitude-related hypoxia and gas expansion. It may cause some passengers to experience significant symptoms and medical complications during the flight, requiring supplemental medical-grade O2 to maintain adequate tissue oxygenation and prevent hypoxemic complications. Although supplemental medical grade O2 is a successful lifesaver for respiratory and cardiac failure, O2-enriched exhaled air can contain more than 95 % O2, increasing the likelihood of a fire. In an aerospace environment, a localized high concentration O2 bubble forms around a patient being treated for hypoxia, increasing the cabin O2 beyond the safe limit. To address this problem, this work describes a medical O2 delivery system that can reduce the O2 concentration from patient-exhaled O2-rich air to safe levels while maintaining the prescribed O2 administration to the patient. The O2 delivery system is designed to be a part of the medical O2 kit. The system uses cationic multimetallic cobalt complexes to reversibly, selectively, and stoichiometrically chemisorb O2 from the exhaled air. An air-release sub-system monitors the exhaled air, and as soon the O2 percentage falls below 21%, the air is released to the room air. The O2-enriched exhaled air is channeled through a layer of porous, thin-film heaters coated with the cobalt complex. The complex absorbs O2, and when saturated, the complex is heated to 100°C using the thin-film heater. Upon heating, the complex desorbs O2 and is once again ready to absorb or remove the excess O2 from exhaled air. The O2 absorption is a sub-second process, and desorption is a multi-second process. While heating at 0.685 °C/sec, the complex desorbs ~90% O2 in 110 sec. These fast reaction times mean that a simultaneous absorb/desorb process in the O2 delivery system will create a continuous absorption of O2. Moreover, the complex can concentrate O2 by a factor of 160 times that in air and desorb over 90% of the O2 at 100°C. Over 12 cycles of thermogravimetry measurement, less than 0.1% decrease in reversibility in O2 uptake was observed. The 1 kg complex can desorb over 20L of O2, so simultaneous O2 desorption by 0.5 kg of complex and absorption by 0.5 kg of complex can potentially continuously remove 9L/min O2 (~90% desorbed at 100°C) from exhaled air. The complex is synthesized and characterized for reversible O2 absorption and efficacy. The complex changes its color from dark brown to light gray after O2 desorption. In addition to thermogravimetric analysis, the O2 absorption/desorption cycle is characterized using optical imaging, showing stable color changes over ten cycles. The complex was also tested at room temperature in a low O2 environment in its O2 desorbed state, and observed to hold the deoxygenated state under these conditions. The results show the feasibility of using the complex for reversible O2 absorption in the proposed fire safe medical O2 delivery system.

Keywords: fire risk, medical oxygen, oxygen removal, reversible absorption

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Authors: Madara Apsalone

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Knowledge management and innovation is key to competitive advantage and sustainable business development in advanced economies. Small and medium-sized enterprises (SMEs) have lower capacity and more constrained resources for long-term and high-uncertainty research and development investments. At the same time, SMEs can implement organizational innovation to improve their performance and further foster other types of innovation. The purpose of this study is to analyze, how socio-cultural factors such as shared values, organizational behaviors, work organization and decision making processes can influence knowledge management and help to develop organizational innovation via an empirical study. Surveying 600 SMEs in Latvia, the author explores the contribution of different socio-cultural factors to organizational innovation and the role of knowledge management and organizational learning in this process. A conceptual model, explaining the impact of organizational team, development, result-orientation and structure is created. The study also proposes insights that contribute to theoretical and practical discussions on fostering innovation of small businesses in small economies.

Keywords: knowledge management, organizational innovation, small and medium-sized enterprises, socio-cultural factors

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Authors: Anne Eugenia Wright

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This study examines issues in accessibility to maritime cultural heritage. Using the Pillar Dollar Wreck in Biscayne National Park, Florida, this study presents an approach to public outreach based on the concept of Design for All. Design for All advocates creating products that are accessible and functional for all users, including those with visual, hearing, learning, mobility, or economic impairments. As a part of this study, a small exhibit was created that uses 3D products as a way to bring maritime cultural heritage to the public. It was presented to the public at East Carolina University’s Joyner Library. Additionally, this study presents a methodology for 3D printing scaled photogrammetry models of archaeological sites in full color. This methodology can be used to present a realistic depiction of underwater archaeological sites to those who are incapable of accessing them in the water. Additionally, this methodology can be used to present underwater archaeological sites that are inaccessible to the public due to conditions such as visibility, depth, or protected status. This study presents a practical use for 3D photogrammetry models, as well as an accessibility strategy to expand the outreach potential for maritime archaeology.

Keywords: Underwater Archaeology, 3D Printing, Photogrammetry, Design for All

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Authors: Georgi Y. Georgiev, Matthew Brouillet

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This research applies the power of agent-based modeling to a pivotal question at the intersection of biology, computer science, physics, and complex systems theory about the self-organization processes in open, complex, non-equilibrium thermodynamic systems. Central to this investigation is the principle of Maximum Entropy Production (MEP). This principle suggests that such systems evolve toward states that optimize entropy production, leading to the formation of structured environments. It is hypothesized that guided by the least action principle, open thermodynamic systems identify and follow the shortest paths to transmit energy and matter, resulting in maximal entropy production, internal structure formation, and a decrease in internal entropy. Concurrently, it is predicted that there will be an increase in system information as more information is required to describe the developing structure. To test this, an agent-based model is developed simulating an ant colony's formation of a path between a food source and its nest. Utilizing the Netlogo software for modeling and Python for data analysis and visualization, self-organization is quantified by calculating the decrease in system entropy based on the potential states and distribution of the ants within the simulated environment. External entropy production is also evaluated for information increase and efficiency improvements in the system's action. Simulations demonstrated that the system begins at maximal entropy, which decreases as the ants form paths over time. A range of system behaviors contingent upon the number of ants are observed. Notably, no path formation occurred with fewer than five ants, whereas clear paths were established by 200 ants, and saturation of path formation and entropy state was reached at populations exceeding 1000 ants. This analytical approach identified the inflection point marking the transition from disorder to order and computed the slope at this point. Combined with extrapolation to the final path entropy, these parameters yield important insights into the eventual entropy state of the system and the timeframe for its establishment, enabling the estimation of the self-organization rate. This study provides a novel perspective on the exploration of self-organization in thermodynamic systems, establishing a correlation between internal entropy decrease rate and external entropy production rate. Moreover, it presents a flexible framework for assessing the impact of external factors like changes in world size, path obstacles, and friction. Overall, this research offers a robust, replicable model for studying self-organization processes in any open thermodynamic system. As such, it provides a foundation for further in-depth exploration of the complex behaviors of these systems and contributes to the development of more efficient self-organizing systems across various scientific fields.

Keywords: complexity, self-organization, agent based modelling, efficiency

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Authors: Tawfik Thelaidjia, Salah Chenikher

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Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach

Keywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement

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Authors: Sherine S. Aly, Fahd A. Hemeida, Mohamed A. Elshamy

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In the face of rapid urbanization and the myriad challenges posed by climate change, population growth, and socio-economic disparities, fostering urban resilience has become paramount. This abstract offers a comprehensive overview of the study on "Urban Resilience Challenges," exploring the background, methodologies, major findings, and concluding insights. The paper unveils a spectrum of challenges encompassing environmental stressors and deep-seated socio-economic issues, such as unequal access to resources and opportunities. Emphasizing their interconnected nature, the study underscores the imperative for holistic and integrated approaches to urban resilience, recognizing the intricate web of factors shaping the urban landscape. Urbanization has witnessed an unprecedented surge, transforming cities into dynamic and complex entities. With this growth, however, comes an array of challenges that threaten the sustainability and resilience of urban environments. This study seeks to unravel the multifaceted urban resilience challenges, exploring their origins and implications for contemporary cities. Cities serve as hubs of economic, social, and cultural activities, attracting diverse populations seeking opportunities and a higher quality of life. However, the urban fabric is increasingly strained by climate-related events, infrastructure vulnerabilities, and social inequalities. Understanding the nuances of these challenges is crucial for developing strategies that enhance urban resilience and ensure the longevity of cities as vibrant and adaptive entities. This paper endeavors to discern strategic guidelines for enhancing urban resilience amidst the dynamic challenges posed by rapid urbanization. The study aims to distill actionable insights that can inform strategic approaches. Guiding the formulation of effective strategies to fortify cities against multifaceted pressures. The study employs a multifaceted approach to dissect urban resilience challenges. A qualitative method will be employed, including comprehensive literature reviews and data analysis of urban vulnerabilities that provided valuable insights into the lived experiences of resilience challenges in diverse urban settings. In conclusion, this study underscores the urgency of addressing urban resilience challenges to ensure the sustained vitality of cities worldwide. The interconnected nature of these challenges necessitates a paradigm shift in urban planning and governance. By adopting holistic strategies that integrate environmental, social, and economic considerations, cities can navigate the complexities of the 21st century. The findings provide a roadmap for policymakers, planners, and communities to collaboratively forge resilient urban futures that withstand the challenges of an ever-evolving urban landscape.

Keywords: resilient principles, risk management, sustainable cities, urban resilience

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Authors: Francisco Luis Reyes

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European colonization had a profound impact on Latin America. The influence of the old continent can be perceived in the culture, religion, and language of the region as well as the beliefs and attitudes of the population. Music education is not an exception to this phenomenon. With Europeans controlling cultural life and erecting educational institutions across the continent for several centuries, Western European Art Music (WEAM) has polarized music learning in formal spaces. In contrast, the musics from the indigenous population, the African slaves, and the ones that emerged as a result of the cultural mélanges have largely been excluded from primary and secondary schooling. The purpose of this paper is to suggest the inclusion of indigenous music education in primary and secondary music education. The paper employs a philosophical inquiry in order to achieve this aim. Philosophical inquiry seeks to uncover and examine individuals' unconscious beliefs, principles, values, and assumptions to envision potential possibilities. This involves identifying and describing issues within current music teaching and learning practices. High-quality philosophical research tackles problems that are sufficiently narrow (addressing a specific aspect of a single complex topic), realistic (reflecting the experiences of music education), and significant (addressing a widespread and timely issue). Consequently, this methodological approach fits this topic, as the research addresses the omnipresence of WEAM in Latin American music education, the exclusion of indigenous music, and argues about the transformational impact said artistic expressions can have on practices in the region. The paper initially addresses how WEAM became ubiquitous in the region by recounting historical events, and adressing the issues other types of music face entering higher education. According to Shifres and Rosabal-Coto (2017) Latin America still upholds the musical heritage of their colonial period, and its formal music education institutions promote the European ontology instilled during European expansion. In accordance, the work of Reyes and Lorenzo-Quiles (2024), and Soler, Lorenzo-Quiles, and Hargreaves (2014), demonstrate how music institutions in the region uphold foreign narratives. Their studies show that music programs in Puerto Rico and Colombia instruct students in WEAM as well as require skills in said art form to enter the profession, just like other authors have argued (Cain & Walden, 2019, Walden, 2016). Subsequently, the research explains the issues faced by prospective music educators that do not practice WEAM. Roberts (1991a, 1991b, 1993), Green (2012) have found that music education students that do not adhere to the musical culture of their institution, are less likely to finish their degrees. Hence, practicioners of tradional musics might feel out of place in the environment. The ubiquity of WEAM and the exclusion of traditional musics of the region, provide the primary challenges to the inclusion of indigenous musics in formal spaces in primary and secondary education. The presentation then laids the framework for the inclusion indigenous music, and conclusively offers examples of how the musical expressions from the continent can improove the music education practices of the region. As an ending, the article highlights the benefits of these musics that are lacking in current practices.

Keywords: indigenous music education, postmodern music education, decolonization in music education, music education practice, Latin American music education

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Authors: Ali Babajanzade, Hossein Bozorgian

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Cognitive load plays an important role in learning in general and L2 listening comprehension in particular. This study is an attempt to investigate the effect of metacognitive strategy intervention through dialogic interaction (MSIDI) on L2 listeners’ cognitive load. A mixed-method design with 50 participants of male and female Iranian lower-intermediate learners between 20 to 25 years of age was used. An experimental group (n=25) received weekly interventions based on metacognitive strategy intervention through dialogic interaction for ten sessions. The second group, which was control (n=25), had the same listening samples with the regular procedure without a metacognitive intervention program in each session. The study used three different instruments: a) a modified version of the cognitive load questionnaire, b) digit span tests, and c) focused group interviews to investigate listeners’ level of cognitive load throughout the process. Results testified not only improvements in listening comprehension in MSIDI but a radical shift of cognitive load rate within this group. In other words, listeners experienced a lower level of cognitive load in MSIDI in comparison with their peers in the control group.

Keywords: cognitive load theory, human mental functioning, metacognitive theory, listening comprehension, sociocultural theory

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Authors: Natasha Gabriella, Josef-Peter Schöggl, Alfred Posch

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Being a mature industry, pulp and paper industry (PPI) possess strength points coming from its existing infrastructure, technology know-how, and abundant availability of biomass. However, the declining trend of the wood-based products sales sends a clear signal to the industry to transform its business model in order to increase its profitability. With the emerging global attention on bio-based economy and circular economy, coupled with the low price of fossil feedstock, the PPI starts to integrate biorefinery as a value-added business model to keep the industry’s competitiveness. Nonetheless, biorefinery as an innovation exposes the PPI with some barriers, of which the uncertainty of the promising product becomes one of the major hurdles. This study aims to assess factors that affect the diffusion and development of forest biorefinery in the PPI, including drivers, barriers, advantages, disadvantages, as well as the most promising bio-based products of forest biorefinery. The study examines the identified factors according to the layer of business environment, being the macro-environment, industry, and strategic group level. Besides, an overview of future state of the identified factors is elaborated as to map necessary improvements for implementing forest biorefinery. A two-phase Delphi method is used to collect the empirical data for the study, comprising of an online-based survey and interviews. Delphi method is an effective communication tools to elicit ideas from a group of experts to further reach a consensus of forecasting future trends. Collaborating a total of 50 experts in the panel, the study reveals that influential factors are found in every layers of business of the PPI. The politic dimension is apparent to have a significant influence for tackling the economy barrier while reinforcing the environmental and social benefits in the macro-environment. In the industry level, the biomass availability appears to be a strength point of the PPI while the knowledge gap on technology and market seem to be barriers. Consequently, cooperation with academia and the chemical industry has to be improved. Human resources issue is indicated as one important premise behind the preceding barrier, along with the indication of the PPI’s resistance towards biorefinery implementation as an innovation. Further, cellulose-based products are acknowledged for near-term product development whereas lignin-based products are emphasized to gain importance in the long-term future.

Keywords: forest biorefinery, pulp and paper, bio-based product, Delphi method

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Authors: Zheng Zhihao

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Recently, Knowledge Graph Framework Network (KGCN) has developed powerful capabilities in knowledge representation and reasoning tasks. However, traditional KGCN often uses a fixed weight mechanism when aggregating information, failing to make full use of rich structural information, resulting in a certain expression ability of node representation, and easily causing over-smoothing problems. In order to solve these challenges, the paper proposes an new graph neural network model called KGCN-STAR (Knowledge Graph Convolutional Network with Structural Adaptive Receptive Fields). This model dynamically adjusts the perception of each node by introducing a structural adaptive receptive field. wild range, and a subgraph aggregator is designed to capture local structural information more effectively. Experimental results show that KGCN-STAR shows significant performance improvement on multiple knowledge graph data sets, especially showing considerable capabilities in the task of representation learning of complex structures.

Keywords: knowledge graph, graph neural networks, structural adaptive receptive fields, information aggregation

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Authors: Yosra Mefteh Rekik, Younes Boujelbene

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We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

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Authors: Z. Sun

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Health communication is essential in promoting healthy lifestyles, managing disease conditions, and eventually reducing health disparities. The key elements of successful health communication always include the development of communication strategies to engage people in thinking about their health, inform them about healthy choices, persuade them to adopt safe and healthy behaviours, and eventually achieve public health objectives. The use of 'Narrative' is recognised as a kind of health communication strategy to enhance personal and public health due to its potential persuasive effect in motivating and supporting individuals change their beliefs and behaviours by inviting them into a narrative world, breaking down their cognitive and emotional resistance and enhance their acceptance of the ideas portrayed in narratives. Meanwhile, the popularity of social media has provided a novel means of communication for both healthcare stakeholders, and a special group of active social media users (influencers) have started playing a pivotal role in providing health ‘solutions’. Such individuals are often referred to as ‘influencers’ because of their central position in the online communication system and the persuasive effect their actions may have on audiences. They may have established a positive rapport with their audience, earned trust and credibility in a specific area, and thus, their audience considers the information they delivered to be authentic and influential. To our best knowledge, to date, there is no published research that examines the effect of diabetes narratives presented by social media influencers and their impacts on health-related outcomes. The primary aim of this study is to investigate the diabetes narratives presented by social media influencers in the UK because of the new dimension they bring to health communication and the potential impact they may have on audiences' health outcomes. This study is situated within the interpretivist and narrative paradigms. A mixed methodology combining both quantitative and qualitative approaches has been adopted. Qualitative data has been derived to provide a better understanding of influencers’ personal experiences and how they construct meanings and make sense of their world, while quantitative data has been accumulated to identify key social media influencers in the UK and measure the impact of diabetes narratives on audiences. Twitter has been chosen as the social media platform to initially identify key influencers. Two groups of participants are the top 10 key social media influencers in the UK and 100 audiences of each influencer, which means a total of 1000 audiences have been invited. This paper is going to discuss, first of all, the background of the research under the context of health communication; Secondly, the necessity and contribution of this research; then, the major research questions being explored; and finally, the methods to be used.

Keywords: diabetes, health communication, narratives, social media influencers

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Authors: Sobhy Fathy A. Hashesh

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The study was carried out in the High School Classes of Andalus Private Schools, boys section, using control and experimental groups that were randomly assigned. The study investigated the effect of Al-Andalus Improvement Model (AIM) on the development of students’ skills acquiring. The society of the study composed of Al-Andalus Private Schools, high school students, boys Section (N=700), while the sample of the study composed of four randomly assigned groups two groups of teachers (N=16) and two groups of students (N=42) with one experimental group and one control group for teachers and their students respectively. The study followed the quantitative and qualitative approaches in collecting and analyzing data to investigate the study hypotheses. Results of the study revealed that there were significant statistical differences in teachers’ performances and students' skills acquiring for the favor of the experimental groups and there was a strong correlation between the teachers performances and the students skills acquiring. The study recommended the implementation of the AIM model for the sake of teachers performances and students’ learning outcomes.

Keywords: AIM, improvement model, Classera, Al-Andalus Improvement Model.

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Authors: Farshad Zeinali, Sajedeh Norouzi, Nader Mokari, Eduard Jorswieck

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The capacity of fifth-generation (5G) vehicle-to-everything (V2X) networks poses significant challenges. To ad- dress this challenge, this paper utilizes New Radio (NR) and New Radio Unlicensed (NR-U) networks to develop a heterogeneous vehicular network (HetNet). We propose a new framework, named joint BS assignment and resource allocation (JBSRA) for mobile V2X users and also consider coexistence schemes based on flexible duty cycle (DC) mechanism for unlicensed bands. Our objective is to maximize the average throughput of vehicles while guaranteeing the WiFi users' throughput. In simulations based on deep reinforcement learning (DRL) algorithms such as deep deterministic policy gradient (DDPG) and deep Q network (DQN), our proposed framework outperforms existing solutions that rely on fixed DC or schemes without consideration of unlicensed bands.

Keywords: vehicle-to-everything (V2X), resource allocation, BS assignment, new radio (NR), new radio unlicensed (NR-U), coexistence NR-U and WiFi, deep deterministic policy gradient (DDPG), deep Q-network (DQN), joint BS assignment and resource allocation (JBSRA), duty cycle mechanism

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Authors: Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev

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The neural network quantization is highly desired procedure to perform before running neural networks on mobile devices. Quantization without fine-tuning leads to accuracy drop of the model, whereas commonly used training with quantization is done on the full set of the labeled data and therefore is both time- and resource-consuming. Real life applications require simplification and acceleration of quantization procedure that will maintain accuracy of full-precision neural network, especially for modern mobile neural network architectures like Mobilenet-v1, MobileNet-v2 and MNAS. Here we present a method to significantly optimize training with quantization procedure by introducing the trained scale factors for discretization thresholds that are separate for each filter. Using the proposed technique, we quantize the modern mobile architectures of neural networks with the set of train data of only ∼ 10% of the total ImageNet 2012 sample. Such reduction of train dataset size and small number of trainable parameters allow to fine-tune the network for several hours while maintaining the high accuracy of quantized model (accuracy drop was less than 0.5%). Ready-for-use models and code are available in the GitHub repository.

Keywords: distillation, machine learning, neural networks, quantization

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Authors: Huey-Fang Sun, Wei-Kai Weng, Mei-Kuang Chao, Hui-Shan Hsu, Tsai-Yin Shih

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Psycho-social stress is important for mental illness and the presence of emotional and behavioral symptoms to an identifiable event is the central feature of adjustment disorders. However, whether patients with adjustment disorders have been raised in family with poor family functions and social supports and have higher stress perception than their peer group when they both experienced a similar stressful environment remains unknown. The specific aims of the study are to investigate the correlation among the family function, social supports and the level of stress perception and to test the hypothesis that military patients with adjustment disorders would have lower family function, lower social supports and higher stress perception than their healthy colleagues recruited in the same cohort for military services given their common exposure to similar stressful environments. Methods: The study was conducted in four hospitals of northern part of Taiwan from July 1, 2015 to June 30, 2017 and a matched case-control study design was used. The inclusion criteria for potential patient participants were psychiatric inpatients that serviced in military during the study period and met the diagnosis of adjustment disorders. Patients who had been admitted to psychiatric ward before or had illiteracy problem were excluded. A healthy military control sample matched by the same military service unit, gender, and recruited cohort was invited to participate the study as well. Totally 74 participants (37 patients and 37 controls) completed the consent forms and filled out the research questionnaires. Questionnaires used in the study included Perceived Stress Scale (PSS) as a measure of stress perception; Family APGAR as a measure of family function, and Multidimensional Scale of Perceived Social Support (MSPSS) as a measure of social supports. Pearson correlation analysis and t-test were applied for statistical analysis. Results: The analysis results showed that PSS level significantly negatively correlated with three social support subscales (family subscale, r= -.37, P < .05; friend subscale, r= -.38, P < .05; significant other subscale, r= -.39, P < .05). A negative correlation between PSS level and Family APGAR only reached a borderline significant level (P= .06). The t-test results for PSS scores, Family APGAR levels, and three subscale scores of MSPSS between patient and control participants were all significantly different (P < .001, P < .05, P < .05, P < .05, P < .05, respectively) and the patient participants had higher stress perception scores, lower social supports and lower family function scores than the healthy control participants. Conclusions: Our study suggested that family function and social supports were negatively correlated with patients’ subjective stress perception. Military patients with adjustment disorders tended to have higher stress perception and lower family function and social supports than those military peers who remained healthy and still provided services in their military units.

Keywords: adjustment disorders, family function, social support, stress perception

Procedia PDF Downloads 192

Authors: Jia-Chao Wang

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A model of the universe without invoking space expansion is proposed to explain the observed redshift-distance relation and the cosmic microwave background radiation (CMB). The main hypothesized feature of the model is that photons traveling in space interact with the CMB photon gas. This interaction causes the photons to gradually lose energy through dissipation and, therefore, experience redshift. The interaction also causes some of the photons to be scattered off their track toward an observer and, therefore, results in beam intensity attenuation. As observed, the CMB exists everywhere in space and its photon density is relatively high (about 410 per cm³). The small average energy of the CMB photons (about 6.3×10⁻⁴ eV) can reduce the energies of traveling photons gradually and will not alter their momenta drastically as in, for example, Compton scattering, to totally blur the images of distant objects. An object moving through a thermalized photon gas, such as the CMB, experiences a drag. The cause is that the object sees a blue shifted photon gas along the direction of motion and a redshifted one in the opposite direction. An example of this effect can be the observed CMB dipole: The earth travels at about 368 km/s (600 km/s) relative to the CMB. In the all-sky map from the COBE satellite, radiation in the Earth's direction of motion appears 0.35 mK hotter than the average temperature, 2.725 K, while radiation on the opposite side of the sky is 0.35 mK colder. The pressure of a thermalized photon gas is given by Pγ = Eγ/3 = αT⁴/3, where Eγ is the energy density of the photon gas and α is the Stefan-Boltzmann constant. The observed CMB dipole, therefore, implies a pressure difference between the two sides of the earth and results in a CMB drag on the earth. By plugging in suitable estimates of quantities involved, such as the cross section of the earth and the temperatures on the two sides, this drag can be estimated to be tiny. But for a photon traveling at the speed of light, 300,000 km/s, the drag can be significant. In the present model, for the dissipation part, it is assumed that a photon traveling from a distant object toward an observer has an effective interaction cross section pushing against the pressure of the CMB photon gas. For the attenuation part, the coefficient of the typical attenuation equation is used as a parameter. The values of these two parameters are determined by fitting the 748 µ vs. z data points compiled from 643 supernova and 105 γ-ray burst observations with z values up to 8.1. The fit is as good as that obtained from the lambda cold dark matter (ΛCDM) model using online cosmological calculators and Planck 2015 results. The model can be used to interpret Hubble's constant, Olbers' paradox, the origin and blackbody nature of the CMB radiation, the broadening of supernova light curves, and the size of the observable universe.

Keywords: CMB as the lowest energy state, model of the universe, origin of CMB in a static universe, photon-CMB photon gas interaction

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Authors: Maaly Jarrah

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There is no doubt that reflective practice has become a stable component in continuous professional development (CPD) courses around the world for the purpose of promoting teacher development, meaningful learning, and deliberate teacher personal and professional growth. However, while there is much research on the benefits of integrating reflective practice in teacher CPD courses, not enough research explores EFL teachers’ experiences with engagement in reflective practice in the CPD from their own perspectives. This research employed a case study approach to explore the experience of 7 EFL teachers with engaging in reflective practice in a CPD course that took place in Kuwait.The participating EFL teachers engaged in collaborative dialogue reflections and completed reflection journal entries as part of the course. Data was collected through semi-structured interviews and analyzed thematically. Findings indicate that the participating teachers’ positive experience with reflective practice is associated with their engagement in collaborative dialogue reflections, while challenges and negative feelings are associated with writing their reflection journal entries. Accordingly, the study offers recommendations for CPD courses to help improve EFL teachers’ experiences with engagement in reflective practice.

Keywords: Collaborative dialogue reflections, continuous professional development, EFL teachers, reflection journals, teacher reflective practice

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Authors: Atilola O. Abidemi-Iromini, Oluayo A. Bello-Olusoji, Immanuel A. Adebayo

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Ecological studies were carried out in Asejire Reservoir (AR) and Lagos Lagoon (LL), Southwest Nigeria from January 2012 to December 2013 to determine the health status of Chrysichthys nigrodigitatus (CN) and Oreochromis niloticus (ON). The fish species samples were collected every month, these were separated into sexes, and growth pattern {length, (cm); weight (g), Isometric index, condition factor} were measured. Heavy metals (lead (Pb), iron (Fe), zinc (Zn), copper (Cu), and chromium (Cr) in ppm concentrations were also determined while bacteria occurrence(s), (load and prevalence) on fish skins, gills and intestine in the two ecological zones were determined. The fish ratio collected is in range with normal aquatic (1: 1+) male: female ratio. Growth assessment determined revealed no significant difference in length and weight in O. niloticus between locations, but a significant difference in weight occurred in C. nigrodigitatus between locations, with a higher weight (196.06 ±0.16 g) from Lagos Lagoon. Highest condition factor (5.25) was recorded in Asejire Reservoir O. niloticus, (ARON); and lowest condition factor (1.64) was observed in Asejire Reservoir C. nigrodigitatus (ARCN); as this indicated a negative allometric value which is normal in Bagridae species because it increases more in Length to weight gain than for the Cichlidae growth status. Normal growth rate (K > 1) occurred between sexes, with the male species having higher K - factors than female species within locations, between locations, between species, and within species, except for female C. nigrodigitatus having higher condition factor (K = 1.75) than male C. nigrodigitatus (K = 1.54) in Asejire Reservoir. The highest isometric value (3.05) was recorded in Asejire Reservoir O. niloticus and lowest in Lagos Lagoon C. nigrodigitatus. Male O. niloticus from Asejire Reservoir had highest isometric value, and O. niloticus species had higher condition factor which ranged between isometric (b ≤ 3) and positive allometric (b > 3), hence, denoted robustness of fish to grow more in weight than in length; while C. nigrodigitatus fish has negative allometric (b < 3) indicating fish add more length than in weight on growth. The status of condition factors and isometric values obtained is species-specific, and environmental influence, food availability or reproduction factor may as well be contributing factors. The concentrations of heavy metals in fish flesh revealed that Zn (6.52 ±0.82) had the highest, while Cr (0.01±0.00) was ranked lowest; for O. niloticus in Asejire Reservoir. In Lagos Lagoon, heavy metals concentration level revealed that O. niloticus flesh had highest in Zn (4.71±0.25) and lowest in Pb (0.01±0.00). Lagos Lagoon C. nigrodigitatus heavy metal concentration level revealed Zn (9.56±0.96) had highest, while Cr (0.06±0.01) had lowest; and Asejire Reservoir C. nigrodigitatus heavy metal level revealed that Zn (8.26 ±0.74) had highest, and Cr (0.08±0.00) had lowest. In all, Zinc (Zn) was top-ranked in level among species.

Keywords: Oreochromis niloticus, growth status, Chrysichthys nigrodigitatus, environments, heavy metals

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Authors: Yi-Ping Lo, Shi-Yao Wei, Chih-Chun Ma

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Since Google launched Google Glass in 2012, numbers of commercial wearable devices were released, such as smart belt, smart band, smart shoes, smart clothes ... etc. However, most of these devices perform as sensors to show the readings of measurements and few of them provide the interactive feedback to the user. Furthermore, these devices are single task devices which are not able to communicate with each other. In this paper a new health promotion system, Ubiquitous Life People Informatics Engine (U-Life PIE), will be presented. This engine consists of People Informatics Engine (PIE) and the interactive user interface. PIE collects all the data from the compatible devices, analyzes this data comprehensively and communicates between devices via various application programming interfaces. All the data and informations are stored on the PIE unit, therefore, the user is able to view the instant and historical data on their mobile devices any time. It also provides the real-time hands-free feedback and instructions through the user interface visually, acoustically and tactilely. These feedback and instructions suggest the user to adjust their posture or habits in order to avoid the physical injuries and prevent illness.

Keywords: machine learning, wearable devices, user interface, user experience, internet of things

Procedia PDF Downloads 291

Authors: Asma Ashoul

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Nowadays, smartphones are playing a major role in our lives, by communicating with family, friends or using them to learn different things in life. Using smartphones to learn and teach today is something common to see in places like schools or colleges. Therefore, thinking about developing an app that teaches Arabic language may help some categories in society to learn a second language. For example, kids under the age of five or older would learn fast by using smartphones. The problem is based on the Arabic language, which is most like to be not used anymore. The developer assumed to develop an app that would help the younger generation on their learning the Arabic language. A research was completed about user interface design to help the developer choose appropriate layouts and designs. Developing the artefact contained different stages. First, analyzing the requirements with the client, which is needed to be developed. Secondly, designing the user interface design based on the literature review. Thirdly, developing and testing the application after it is completed contacting all the tools that have been used. Lastly, evaluation and future recommendation, which contained the overall view about the application followed by the client’s feedback. Gathering the requirements after having client meetings based on the interface design. The project was done following an agile development methodology. Therefore, this methodology helped the developer to manage to finish the work on time.

Keywords: developer, application, interface design, layout, Agile, client

Procedia PDF Downloads 114

Authors: Bintou Jobe

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Background: The research is focused on the concept of equality, diversity, and inclusion (EDI) and the need to achieve equity by treating individuals according to their circumstances and needs. The research is rooted in the UK Equality Act 2010, which emphasizes the importance of equal opportunities for all individuals regardless of their background and social life. However, inequality persists in society, particularly for those from minority backgrounds who face discrimination. Research Aim: The aim of this research is to promote equality, diversity, and inclusion by encouraging the regeneration of minds and the eradication of stereotypes. The focus is on promoting good Equality, Diversity and Inclusion practices in various settings, including schools, colleges, universities, and workplaces, to create environments where every individual feels a sense of belonging. Methodology: The research utilises a literature review approach to gather information on promoting inclusivity, diversity, and inclusion. Findings: The research highlights the significance of promoting equality, diversity, and inclusion practices to ensure that individuals receive the respect and dignity they deserve. It emphasises the importance of treating individuals based on their unique circumstances and needs rather than relying on stereotypes. The research also emphasises the benefits of diversity and inclusion in enhancing innovation, creativity, and productivity. The theoretical importance of this research is to raise awareness about the importance of regenerating minds, challenging stereotypes, and promoting equality, diversity, and inclusion. The emphasis is on treating individuals based on their circumstances and needs rather than relying on generalizations. Diversity and inclusion are beneficial in different settings, as highlighted by the research. By raising awareness about the importance of mind regeneration, eradicating stereotypes, and promoting equality, diversity, and inclusion, this research makes a significant contribution to the subject area. It emphasizes the necessity of treating individuals based on their unique circumstances instead of relying on generalizations. However, the methodology could be strengthened by incorporating primary research to complement the literature review approach. Data Collection and Analysis Procedures: The research utilised a literature review approach to gather relevant information on promoting inclusivity, diversity, and inclusion. NVivo software application was used to analysed and synthesize the findings to identify themes and support the research aim and objectives. Question Addressed: This research addresses the question of how to promote inclusivity, diversity, and inclusion and reduce the prevalence of stereotypes and prejudice. It explores the need to treat individuals based on their unique circumstances and needs rather than relying on generic assumptions. Encourage individuals to adopt a more inclusive approach. Provide managers with responsibility and training that helps them understand the importance of their roles in shaping the workplace culture. Have an equality, diversity, and inclusion manager from a majority background at the senior level who can speak up for underrepresented groups and flag any issues that need addressing. Conclusion: The research emphasizes the importance of promoting equality, diversity, and inclusion practices to create a fairer society. It highlights the need to challenge stereotypes, treat individuals according to their circumstances and needs, and promote a culture of respect and dignity.

Keywords: equality, fairer society, inclusion, diversity

Procedia PDF Downloads 47