Search results for: blended and integrated learning

Authors: Sadeq Al Yaari, Fayza Al Hammadi, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaari, Salah Al Yami

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Background: When we further take Arabic grammatical issues into account in accordance with applied linguistic investigations on Arabic as Second Language (ASL) learners, a fundamental issue arises at this point as to the production of speech in Arabic: Oral grammatical errors committed by ASL learners. Aims: Using manual rating as well as computational analytic methodology to test a corpus of recorded speech by Second Language (ASL) learners of Arabic, this study aims to find the areas of difficulties in learning Arabic grammar. More specifically, it examines how and why ASL learners make grammatical errors in their oral speech. Methods: Tape recordings of four (4) Arabic as Second Language (ASL) learners who ranged in age from 23 to 30 were naturally collected. All participants have completed an intensive Arabic program (two years) and 20 minute-speech was recorded for each participant. Having the collected corpus, the next procedure was to rate them against Arabic standard grammar. The rating includes four processes: Description, analysis and assessment. Conclusions: Outcomes made from the issues addressed in this paper can be summarized in the fact that ASL learners face many grammatical difficulties when studying Arabic word order, tenses and aspects, function words, subject-verb agreement, verb form, active-passive voice, global and local errors, processes-based errors including addition, omission, substitution or a combination of any of them.

Keywords: grammar, error, oral, Arabic, second language, learner, applied linguistics.

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Authors: Maria A. Castillo H., Andres R. Leandro, Jose F. Bienvenido B.

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During the last 20 years, the globalization of economies, population growth, and the increase in the consumption of fresh agricultural products have generated greater demand for ornamentals, flowers, fresh fruits, and vegetables, mainly from tropical areas. This market situation has demanded greater competitiveness and control over production, with more efficient protected agriculture technologies, which provide greater productivity and allow us to guarantee the quality and quantity that is required in a constant and sustainable way. Guatemala, located in the north of Central America, is one of the largest exporters of agricultural products in the region and exports fresh vegetables, flowers, fruits, ornamental plants, and foliage, most of which were grown in greenhouses. Although there are no official agricultural statistics on greenhouse production, several thesis works, and congress reports have presented consistent estimates. A wide range of protection structures and roofing materials are used, from the most basic and simple ones for rain control to highly technical and automated structures connected with remote sensors for monitoring and control of crops. With this breadth of technological models, it is necessary to analyze georeferenced data related to the cultivated area, to the different existing models, and to the covering materials, integrated with altitude, climate, and soil data. The georeferenced registration of the production units, the data collection with digital tools, the use of satellite images, and geographic information systems (GIS) provide reliable tools to elaborate more complete, agile, and dynamic information maps. This study details a methodology proposed for gathering georeferenced data of high protection structures (greenhouses) in Guatemala, structured in four phases: diagnosis of available information, the definition of the geographic frame, selection of satellite images, and integration with an information system geographic (GIS). It especially takes account of the actual lack of complete data in order to obtain a reliable decision-making system; this gap is solved through the proposed methodology. A summary of the results is presented in each phase, and finally, an evaluation with some improvements and tentative recommendations for further research is added. The main contribution of this study is to propose a methodology that allows to reduce the gap of georeferenced data in protected agriculture in this specific area where data is not generally available and to provide data of better quality, traceability, accuracy, and certainty for the strategic agricultural decision öaking, applicable to other crops, production models and similar/neighboring geographic areas.

Keywords: greenhouses, protected agriculture, GIS, Guatemala, satellite image, digital tools, precision agriculture

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Authors: Abdullah Alotaiq, David Wallom, Malcolm McCulloch

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This study presents an archetype-based approach to designing effective strategies for low-carbon transitions in the power sector. To achieve global energy transition goals, a renewable energy transition is critical, and understanding diverse energy landscapes across different countries is essential to design effective renewable energy policies and strategies. Using a clustering approach, this study identifies 12 energy archetypes based on the electricity mix, socio-economic indicators, and renewable energy contribution potential of 187 UN countries. Each archetype is characterized by distinct challenges and opportunities, ranging from high dependence on fossil fuels to low electricity access, low economic growth, and insufficient contribution potential of renewables. Archetype A, for instance, consists of countries with low electricity access, high poverty rates, and limited power infrastructure, while Archetype J comprises developed countries with high electricity demand and installed renewables. The study findings have significant implications for renewable energy policymaking and investment decisions, with policymakers and investors able to use the archetype approach to identify suitable renewable energy policies and measures and assess renewable energy potential and risks. Overall, the archetype approach provides a comprehensive framework for understanding diverse energy landscapes and accelerating decarbonisation of the power sector.

Keywords: fossil fuels, power plants, energy transition, renewable energy, archetypes

Procedia PDF Downloads 38

Authors: Sonja Goegele, Petra Kletzenbauer

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The FH JOANNEUM- a university of applied sciences based in Austria - cooperates in teaching and research with well-known international universities and thus aims to foster so-called strategic partnerships. The exchange of university lecturers and other faculty members is a way to achieve and secure strategic company goals, in which excellent research and teaching play a central role in order to improve both the development of academics and administration. Thanks to mobility not only the university but also the involved people truly benefit in their professional development which can be seen on several levels: increased foreign language proficiency, excellent networking possibilities within the scientific community as well as reinforced didactic competencies in the form of different teaching and learning methodologies. The paper discusses mobility in the light of the university’s strategic paper entitled ‘Hands on 2022’ by presenting results from an empirical research study among faculty members who participate in exchange programmes on a regular basis. In the form of an online questionnaire, mobility was discussed from different angles such as networking, collaborative research, professional training for academics and the overall impact of the exchange within and outside the organization. From the findings, it can be concluded that mobility is an asset for any university. However, keeping in constant dialogue with partner universities requires more than the purpose of the exchange itself. Building rapport and keeping a relationship of trust are challenges that need to be addressed more closely in order to run successful mobility programmes. Best Practice examples should highlight the importance of mobility as a vital initiative to transfer disciplines.

Keywords: higher education, internationalization, mobility, strategic partnerships

Procedia PDF Downloads 127

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: Hilal Naimi, Amelbahahouda Adamou-Mitiche, Lahcene Mitiche

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The main problem in the area of medical imaging has been image denoising. The most defying for image denoising is to secure data carrying structures like surfaces and edges in order to achieve good visual quality. Different algorithms with different denoising performances have been proposed in previous decades. More recently, models focused on deep learning have shown a great promise to outperform all traditional approaches. However, these techniques are limited to the necessity of large sample size training and high computational costs. This research proposes a denoising approach basing on LDTCWT (Lifting Dual Tree Complex Wavelet Transform) using Hybrid Thresholding with Wiener filter to enhance the quality image. This research describes the LDTCWT as a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). To develop this approach, a hybrid thresholding function is modeled by integrating the Wiener filter into the thresholding function.

Keywords: lifting wavelet transform, image denoising, dual tree complex wavelet transform, wavelet shrinkage, wiener filter

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Authors: Rafat Alwazna

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Translation teaching is a particular activity that includes translators and interpreters training either inside or outside institutionalised settings, such as universities. It can also serve as a means of teaching other fields, such as foreign languages. Translation teaching began in the twentieth century. Teachers of translation hold the responsibilities of educating students, developing their translation competence and training them to be professional translators. The activity of translation teaching involves various tasks, including curriculum design, course delivery, material writing as well as application and implementation. The present paper addresses translation teaching during COVID-19 outbreak, seeking to find out the challenges encountered by translation teachers in online translation teaching and the discoveries/solutions arrived at to resolve them. The paper makes use of a comprehensive questionnaire, containing closed-ended and open-ended questions to elicit both quantitative as well as qualitative data from about sixty translation teachers who have been teaching translation at BA and MA levels during COVID-19 outbreak. The data shows that about 40% of the participants evaluate their online translation teaching experience during COVID-19 outbreak as enjoyable and exhilarating. On the contrary, no participant has evaluated his/her online translation teaching experience as being not good, nor has any participant evaluated his/her online translation teaching experience as being terrible. The data also presents that about 23.33% of the participants evaluate their online translation teaching experience as very good, and the same percentage applies to those who evaluate their online translation teaching experience as good to some extent. Moreover, the data indicates that around 13.33% of the participants evaluate their online translation teaching experience as good. The data also demonstrates that the majority of the participants have encountered obstacles in online translation teaching and have concurrently proposed solutions to resolve them.

Keywords: online translation teaching, electronic learning platform, COVID-19 outbreak, challenges, solutions

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Authors: Rashida Suleiman, Asamoah Jnr. Boakye, Suleiman Ahmed Ibn Ahmed

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In recent years, there has been an enormous success in discoveries of scientific knowledge in medicine coupled with the advancement of technology. Despite all these successes, diagnoses and treatment of diseases have become complex. MYCIN is a groundbreaking illustration of a clinical decision support system (CDSS), which was developed to assist physicians in the diagnosis and treatment of bacterial infections by providing suggestions for antibiotic regimens. MYCIN was one of the earliest expert systems to demonstrate how CDSSs may assist human decision-making in complicated areas. Relevant databases were searched using google scholar, PubMed and general Google search, which were peculiar to clinical decision support systems. The articles were then screened for a comprehensive overview of the functionality, consultative style and statistical usage of MYCIN, a clinical decision support system. Inferences drawn from the articles showed some usage of MYCIN for problem-based learning among clinicians and students in some countries. Furthermore, the data demonstrated that MYCIN had completed clinical testing at Stanford University Hospital following years of research. The system (MYCIN) was shown to be extremely accurate and effective in diagnosing and treating bacterial infections, and it demonstrated how CDSSs might enhance clinical decision-making in difficult circumstances. Despite the challenges MYCIN presents, the benefits of its usage to clinicians, students and software developers are enormous.

Keywords: clinical decision support system, MYCIN, diagnosis, bacterial infections, support systems

Procedia PDF Downloads 119

Authors: Ru-Yin Yang, Chi Wu, Cheng-Yu Tsai, Yin-Tzu Lin, Wen-Te Liu

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Background: Sleep breathing disorder (SDB) is a condition demonstrated by recurrent episodes of the airway obstruction leading to intermittent hypoxia and quality fragmentation during sleep time. However, the procedures for SDB severity examination remain complicated and costly. Objective: The objective of this study is to establish a simplified examination method for SDB by the respiratory impendence pattern sensor combining the signal processing and machine learning model. Methodologies: We records heart rate variability by the electrocardiogram and respiratory pattern by impendence. After the polysomnography (PSG) been done with the diagnosis of SDB by the apnea and hypopnea index (AHI), we calculate the episodes with the absence of flow and arousal index (AI) from device record. Subjects were divided into training and testing groups. Neuron network was used to establish a prediction model to classify the severity of the SDB by the AI, episodes, and body profiles. The performance was evaluated by classification in the testing group compared with PSG. Results: In this study, we enrolled 66 subjects (Male/Female: 37/29; Age:49.9±13.2) with the diagnosis of SDB in a sleep center in Taipei city, Taiwan, from 2015 to 2016. The accuracy from the confusion matrix on the test group by NN is 71.94 %. Conclusion: Based on the models, we established a prediction model for SDB by means of the wearable sensor. With more cases incoming and training, this system may be used to rapidly and automatically screen the risk of SDB in the future.

Keywords: sleep breathing disorder, apnea and hypopnea index, body parameters, neuron network

Procedia PDF Downloads 127

Authors: Bamikole J. Adeyemi, Prashant Jadhawar, Lateef Akanji

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Liquid-liquid interfacial flow is an important process that has applications across many spheres. One such applications are residual oil mobilization, where crude oil and low salinity water are emulsified due to lowered interfacial tension under the condition of low shear rates. The amphiphilic components (asphaltenes and resins) in crude oil are considered to assemble at the interface between the two immiscible liquids. To justify emulsification, drag and snap-off suppression as the main effects of low salinity water, mobilization of residual oil is visualized as thickening and slip of the wetting phase at the brine/crude oil interface which results in the squeezing and drag of the non-wetting phase to the pressure sinks. Meanwhile, defining the boundary conditions for such a system can be very challenging since the interfacial dynamics do not only depend on interfacial tension but also the flow rate. Hence, understanding the flow boundary condition at the brine/crude oil interface is an important step towards defining the influence of low salinity water composition on residual oil mobilization. This work presents a numerical evaluation of three slip boundary conditions that may apply at liquid-liquid interfaces. A mathematical model was developed to describe the evolution of a viscoelastic interfacial thin liquid film. The base model is developed by the asymptotic expansion of the full Navier-Stokes equations for fluid motion due to gradients of surface tension. This model was upscaled to describe the dynamics of the film surface deformation. Subsequently, Jeffrey’s model was integrated into the formulations to account for viscoelastic stress within a long wave approximation of the Navier-Stokes equations. To study the fluid response to a prescribed disturbance, a linear stability analysis (LSA) was performed. The dispersion relation and the corresponding characteristic equation for the growth rate were obtained. Three slip (slip, 1; locking, -1; and no-slip, 0) boundary conditions were examined using the resulted characteristic equation. Also, the dynamics of the evolved interfacial thin liquid film were numerically evaluated by considering the influence of the boundary conditions. The linear stability analysis shows that the boundary conditions of such systems are greatly impacted by the presence of amphiphilic molecules when three different values of interfacial tension were tested. The results for slip and locking conditions are consistent with the fundamental solution representation of the diffusion equation where there is film decay. The interfacial films at both boundary conditions respond to exposure time in a similar manner with increasing growth rate which resulted in the formation of more droplets with time. Contrarily, no-slip boundary condition yielded an unbounded growth and it is not affected by interfacial tension.

Keywords: boundary conditions, liquid-liquid interfaces, low salinity water, residual oil mobilization

Procedia PDF Downloads 119

Authors: N. Nor Azman, M. F. Kamarudin, S. I. Ong, N. Maaulot

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PERMATApintar^® National Gifted Center is, to the author’s best of knowledge, the first center in Malaysia that provides a platform for Malaysian talented students with high ability in thinking. This center has built a teaching and learning biology curriculum that suits the ability of these gifted students. The level of PERMATApintar^® biology curriculum is basically higher than the national biology curriculum. Here, the foundation students are exposed to the PERMATApintar^® biology curriculum at the age of as early as 11 years old. This center practices a 4-time-a-year examination system to monitor the academic performances of the students. Generally, most of the time, male students show no or low interest towards biology subject compared to female students. This study is to investigate the association of students’ gender and their academic performances in biology examination. A total of 39 students’ scores in twelve sets of biology examinations in 3 years have been collected and analyzed by using the statistical analysis. Based on the analysis, there are no significant differences between male and female students against the biology academic performances with a significant level of p = 0.05. This indicates that gender is not associated with the scores of biology examinations among the students. Another result showed that the average score for male studenta was higher than the female students. Future research can be done by comparing the biology academic achievement in Malaysian National Examination (Sijil Pelajaran Malaysia, SPM) between the Foundation 3 students (Grade 9) and Level 2 students (Grade 11) with similar PERMATApintar^® biology curriculum.

Keywords: academic performances, biology, gender differences, gifted students,

Procedia PDF Downloads 227

Authors: R. Tariq, R. Lee

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Background: Heywood, Middleton & Rochdale Urgent Community Care Team (UCCT)1 is a great example of using a multidisciplinary team to cope with demand. The service reduces unnecessary admissions to hospitals and ensures that patients can leave the hospital quicker by making care more readily available within the community and patient’s homes. The team comprises nurses, community practitioners, and allied health professions, including physiotherapy, occupational therapy, pharmacy, and GPs. The main challenge for a team with a range of experiences and skill sets is to maintain consistency of care, which technology can help address. Allied healthcare professionals (HCPs) are often used in expanded roles with duties mainly involving patient consultations and decision making to ease pressure on doctors. The Clinical Reasoning Platform (CRP) Dem Dx is used to support new as well as experienced professionals in the decision making process. By guiding HCPs through diagnosing patients from an expansive directory of differential diagnoses, patients can receive quality care in the community. Actions on the platform are determined using NICE guidelines along with local guidance influencing the assessment and management of a patient. Objective: To compare the clinical assessment, decisions, and actions taken by the UCCT multidisciplinary team in the community and Dem Dx, using retrospective clinical cases. Methodology: Dem Dx was used to analyse 192 anonymised cases provided by the HMR UCCT. The team’s performance was compared with Dem Dx regarding the quality of the documentation of the clinical assessment and the next steps on the patient’s journey, including the initial management, actions, and any onward referrals made. The cases were audited by two medical doctors. Results: The study found that the actions outlined by the Dem Dx platform were appropriate in almost 87% of cases. When in a direct comparison between DemDX and the actions taken by the clinical team, it was found that the platform was suitable 83% (p<0.001) of the time and could lead to a potential improvement of 66% in the assessment and management of cases. Dem Dx also served to highlight the importance of comprehensive and high quality clinical documentation. The quality of documentation of cases by UCCT can be improved to provide a detailed account of the assessment and management process. By providing step-by-step guidance and documentation at every stage, Dem Dx may ensure that legal accountability has been fulfilled. Conclusion: With the ever expanding workforce in the NHS, technology has become a key component in driving healthcare outcomes. To improve healthcare provision and clinical reasoning, a decision support platform can be integrated into HCPs’ clinical practice. Potential assistance with clinical assessments, the most appropriate next step and actions in a patient’s care, and improvements in the documentation was highlighted by this retrospective study. A further study has been planned to ascertain the effectiveness of improving outcomes using the clinical reasoning platform within the clinical setting by clinicians.

Keywords: allied health professional, assessment, clinical reasoning, clinical records, clinical decision-making, ocumentation

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Authors: Sonia David, Uma Warrier

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Background: Film therapy is the use of commercial or non-commercial films to enhance healing for therapeutic purposes. Objectives: The mixed-method study aims to evaluate the effect of film-based counseling on body image dissatisfaction among adolescents to precisely ascertain the cause of the alteration in body image dissatisfaction due to the said intervention. Method: The one group pre-test post-test research design study using inferential statistics and thematic analysis is based on a pre-test post-test design conducted on 44 school-going adolescents between 13 and 17. The Body Shape Questionnaire (BSQ- 34) was used as a pre-test and post-test measure. The film-based counseling intervention model was used through individual counseling sessions. The analysis involved paired sample t-test used to examine the data quantitatively, and thematic analysis was used to evaluate qualitative data. Findings: The results indicated that there is a significant difference between the pre-test and post-test means. Since t(44)= 9.042 is significant at a 99% confidence level, it is ascertained that film-based counseling intervention reduces body image dissatisfaction. The five distinct themes from the thematic analysis are “acceptance, awareness, empowered to change, empathy, and reflective.” Novelty: The paper originally contributes to the repertoire of research on film therapy as a successful counseling intervention for addressing the challenges of body image dissatisfaction. This study also opens avenues for considering alteration of teaching pedagogy to include video-based learning in various subjects.

Keywords: body image dissatisfaction, adolescents, film-based counselling, film therapy, acceptance and commitment therapy

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Authors: Anisa Suraya Ab Razak, Izza Hayat

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Introduction: The diagnosis and management of severe hyponatremia in neuropsychiatric patients present a significant challenge to physicians. Several factors contribute, including diagnostic shadowing and attributing abnormal behavior to intellectual disability or psychiatric conditions. Hyponatraemia is the commonest electrolyte abnormality in the inpatient population, ranging from mild/asymptomatic, moderate to severe levels with life-threatening symptoms such as seizures, coma and death. There are several documented fatal case reports in the literature of severe hyponatremia secondary to psychogenic polydipsia, often diagnosed only in autopsy. This paper presents a case study of acute severe hyponatremia in a neuropsychiatric patient with early diagnosis and admission to intensive care. Case study: A 21-year old Caucasian male with known epilepsy and learning disability was admitted from residential living with generalized tonic-clonic self-terminating seizures after refusing medications for several weeks. Evidence of superficial head injury was detected on physical examination. His laboratory data demonstrated mild hyponatremia (125 mmol/L). Computed tomography imaging of his brain demonstrated no acute bleed or space-occupying lesion. He exhibited abnormal behavior - restlessness, drinking water from bathroom taps, inability to engage, paranoia, and hypersexuality. No collateral history was available to establish his baseline behavior. He was loaded with intravenous sodium valproate and leveritircaetam. Three hours later, he developed vomiting and a generalized tonic-clonic seizure lasting forty seconds. He remained drowsy for several hours and regained minimal recovery of consciousness. A repeat set of blood tests demonstrated profound hyponatremia (117 mmol/L). Outcomes: He was referred to intensive care for peripheral intravenous infusion of 2.7% sodium chloride solution with two-hourly laboratory monitoring of sodium concentration. Laboratory monitoring identified dangerously rapid correction of serum sodium concentration, and hypertonic saline was switched to a 5% dextrose solution to reduce the risk of acute large-volume fluid shifts from the cerebral intracellular compartment to the extracellular compartment. He underwent urethral catheterization and produced 8 liters of urine over 24 hours. Serum sodium concentration remained stable after 24 hours of correction fluids. His GCS recovered to baseline after 48 hours with improvement in behavior -he engaged with healthcare professionals, understood the importance of taking medications, admitted to illicit drug use and drinking massive amounts of water. He was transferred from high-dependency care to ward level and was initiated on multiple trials of anti-epileptics before achieving seizure-free days two weeks after resolution of acute hyponatremia. Conclusion: Psychogenic polydipsia is often found in young patients with intellectual disability or psychiatric disorders. Patients drink large volumes of water daily ranging from ten to forty liters, resulting in acute severe hyponatremia with mortality rates as high as 20%. Poor outcomes are due to challenges faced by physicians in making an early diagnosis and treating acute hyponatremia safely. A low index of suspicion of water intoxication is required in this population, including patients with known epilepsy. Monitoring urine output proved to be clinically effective in aiding diagnosis. Early referral and admission to intensive care should be considered for safe correction of sodium concentration while minimizing risk of fatal complications e.g. central pontine myelinolysis.

Keywords: epilepsy, psychogenic polydipsia, seizure, severe hyponatremia

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Authors: Catherine Sunter, Marius Nygaard, Lars Hamran, Børre Skodvin, Ute Groba

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Globally, the construction and operation of buildings contribute up to 30% of annual green house gas emissions. In addition, the building sector is responsible for approximately a third of global waste. In this context, the utilization of renewable resources in buildings, especially materials that store carbon, will play a significant role in the growing city. These are two reasons for introducing wood as a building material with a growing relevance. A third is the potential economic value in countries with a forest industry that is not currently used to capacity. In 2013, a four-year interdisciplinary research project titled “Wood Be Better” was created, with the principle goal to produce and publicise knowledge that would facilitate increased use of wood in buildings in urban areas. The research team consisted of architects, engineers, wood technologists and mycologists, both from research institutions and industrial organisations. Five structured work packages were included in the initial research proposal. Work package 2 was titled “Design-based research” and proposed using architecture master courses as laboratories for systematic architectural exploration. The aim was twofold: to provide students with an interdisciplinary team of experts from consultancies and producers, as well as teachers and researchers, that could offer the latest information on wood technologies; whilst at the same time having the studio course test the effects of the use of wood on the functional, technical and tectonic quality within different architectural projects on an urban scale, providing results that could be fed back into the research material. The aim of this article is to examine the successes and failures of this pedagogical approach in an architecture school, as well as the opportunities for greater integration between academic research projects, industry experts and studio courses in the future. This will be done through a set of qualitative interviews with researchers, teaching staff and students of the studio courses held each semester since spring 2013. These will investigate the value of the various experts of the course; the different themes of each course; the response to the urban scale, architectural form and construction detail; the effect of working with the goals of a research project; and the value of the studio projects to the research. In addition, six sample projects will be presented as case studies. These will show how the projects related to the research and could be collected and further analysed, innovative solutions that were developed during the course, different architectural expressions that were enabled by timber, and how projects were used as an interdisciplinary testing ground for integrated architectural and engineering solutions between the participating institutions. The conclusion will reflect on the original intentions of the studio courses, the opportunities and challenges faced by students, researchers and teachers, the educational implications, and on the transparent and inclusive discourse between the architectural researcher, the architecture student and the interdisciplinary experts.

Keywords: architecture, interdisciplinary, research, studio, students, wood

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Authors: Amruta D. S. Pathare, Indira Hinduja, Kusum Zaveri

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Implantation failure (IF) even after the good-quality embryo transfer (ET) in the physiologically normal endometrium is the main obstacle in in vitro fertilization (IVF). Various microarray studies have been performed worldwide to elucidate the genes requisite for endometrial receptivity. These studies have included the population based on different phases of menstrual cycle during natural cycle and stimulated cycle in normal fertile women. Additionally, the literature is also available in recurrent implantation failure patients versus oocyte donors in natural cycle. However, for the first time, we aim to study the genomics of endometrial receptivity in IF patients under controlled ovarian stimulation (COS) during which ET is generally practised in IVF. Endometrial gene expression profiling in IF patients (n=10) and oocyte donors (n=8) were compared during window of implantation under COS by whole genome microarray (using Illumina platform). Enrichment analysis of microarray data was performed to determine dys-regulated biological functions and pathways using Database for Annotation, Visualization and Integrated Discovery, v6.8 (DAVID). The enrichment mapping was performed with the help of Cytoscape software. Microarray results were validated by real-time PCR. Localization of genes related to immune response (Progestagen-Associated Endometrial Protein (PAEP), Leukaemia Inhibitory Factor (LIF), Interleukin-6 Signal Transducer (IL6ST) was detected by immunohistochemistry. The study revealed 418 genes downregulated and 519 genes upregulated in IF patients compared to healthy fertile controls. The gene ontology, pathway analysis and enrichment mapping revealed significant downregulation in activation and regulation of immune and inflammation response in IF patients under COS. The lower expression of Progestagen Associated Endometrial Protein (PAEP), Leukemia Inhibitory Factor (LIF) and Interleukin 6 Signal Transducer (IL6ST) in cases compared to controls by real time and immunohistochemistry suggests the functional importance of these genes. The study was proved useful to uncover the probable reason of implantation failure being imbalance of immune and inflammatory regulation in our group of subjects. Based on the present study findings, a panel of significant dysregulated genes related to immune and inflammatory pathways needs to be further substantiated in larger cohort in natural as well as stimulated cycle. Upon which these genes could be screened in IF patients during window of implantation (WOI) before going for embryo transfer or any other immunological treatment. This would help to estimate the regulation of specific immune response during WOI in a patient. The appropriate treatment of either activation of immune response or suppression of immune response can be then attempted in IF patients to enhance the receptivity of endometrium.

Keywords: endometrial receptivity, immune and inflammatory response, gene expression microarray, window of implantation

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Authors: Jamunarani Appalasamy, Tha Kyi Kyi, Quek Kia Fatt, Joyce Pauline Joseph, Anuar Zaini M. Zain

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Background: The Health Belief Theory had always been associated with chronic disease management. Various health behaviour concepts and perception branching from this Health Belief Theory had involved with medication understanding, use, and self-efficacy which directly link to medication adherence. In a previous quantitative and qualitative study, stroke patients in Malaysia were found to be strongly believing information obtained by various sources such as the internet and social communication. This action leads to lower perception of their stroke preventative medication benefit which in long-term creates non-adherence. Hence, this study intends to pilot an intervention which uses audio-visual concept incorporated with mHealth service to enhance learning and self-reflection among stroke patients to manage their disease. Methods/Design: Twenty patients will be allocated to a proposed intervention whereas another twenty patients are allocated to the usual treatment. The intervention involves a series of developed audio-visual videos sent via mobile phone which later await for responses and feedback from the receiver (patient) via SMS or recorded calls. The primary outcome would be the medication understanding, use and self-efficacy measured over two months pre and post intervention. Secondary outcome is measured from changes of blood parameters and other self-reported questionnaires. Discussion: This study shall also assess uptake/attrition, feasibility, and acceptability of this intervention. Trial Registration: NMRR-15-851-24737 (IIR)

Keywords: health belief, medication understanding, medication use, self-efficacy

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Authors: Celine Bonnaud, Isabelle Billard, Nicolas Papaiconomou, Eric Chainet

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Thanks to their high magnetization and low mass, permanent magnets (NdFeB and SmCo) have quickly became essential for new energies (wind turbines, electrical vehicles…). They contain large quantities of neodymium, samarium and dysprosium, that have been recently classified as critical elements and that therefore need to be recycled. Electrochemical processes including electrodissolution followed by electrodeposition are an elegant and environmentally friendly solution for the recycling of such lanthanides contained in permanent magnets. However, electrochemistry of the lanthanides is a real challenge as their standard potentials are highly negative (around -2.5V vs ENH). Consequently, non-aqueous solvents are required. Ionic liquids (IL) are novel electrolytes exhibiting physico-chemical properties that fulfill many requirements of the sustainable chemistry principles, such as extremely low volatility and non-flammability. Furthermore, their chemical and electrochemical properties (solvation of metallic ions, large electrochemical windows, etc.) render them very attractive media to implement alternative and sustainable processes in view of integrated processes. All experiments that will be presented were carried out using butyl-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide. Linear sweep, cyclic voltammetry and potentiostatic electrochemical techniques were used. The reliability of electrochemical experiments, performed without glove box, for the classic three electrodes cell used in this study has been assessed. Deposits were obtained by chronoamperometry and were characterized by scanning electron microscopy and energy-dispersive X-ray spectroscopy. The IL cathodic behavior under different constraints (argon, nitrogen, oxygen atmosphere or water content) and using several electrode materials (Pt, Au, GC) shows that with argon gas flow and gold as a working electrode, the cathodic potential can reach the maximum value of -3V vs Fc+/Fc; thus allowing a possible reduction of lanthanides. On a gold working electrode, the reduction potential of samarium and neodymium was found to be -1.8V vs Fc+/Fc while that of dysprosium was -2.1V vs Fc+/Fc. The individual deposits obtained were found to be porous and presented some significant amounts of C, N, F, S and O atoms. Selective deposition of neodymium in presence of dysprosium was also studied and will be discussed. Next, metallic Sm, Nd and Dy electrodes were used in replacement of Au, which induced changes in the reduction potential values and the deposit structures of lanthanides. The individual corrosion potentials were also measured in order to determine the parameters influencing the electrodissolution of these metals. Finally, a full recycling process was investigated. Electrodissolution of a real permanent magnet sample was monitored kinetically. Then, the sequential electrodeposition of all lanthanides contained in the IL was investigated. Yields, quality of the deposits and consumption of chemicals will be discussed in depth, in view of the industrial feasibility of this process for real permanent magnets recycling.

Keywords: electrodeposition, electrodissolution, ionic liquids, lanthanides, rcycling

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Authors: Zhu Weimin, Allegorico Carmine, Ruggiero Gionata

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During decades of Baker Hughes (BH) iCenter experience, it is demonstrated that in addition to conventional insights on equipment steady operation conditions, insights on transient conditions can add significant and exclusive value for anomaly detection, downtime saving, and predictive maintenance. Our work shows examples from the BH iCenter experience to introduce the advantages and features of using transient condition analytics: (i) Operation under critical engine conditions: e.g., high level or high change rate of temperature, pressure, flow, vibration, etc., that would not be reachable in normal operation, (ii) Management of dedicated sub-systems or components, many of which are often bottlenecks for reliability and maintenance, (iii) Indirect detection of anomalies in the absence of instrumentation, (iv) Repetitive sequences: if data is properly processed, the engineering features of transients provide not only anomaly detection but also problem characterization and prognostic indicators for predictive maintenance, (v) Engine variables accounting for fatigue analysis. iCenter has been developing and deploying a series of analytics based on transient conditions. They are contributing to exclusive value adding in the following areas: (i) Reliability improvement, (ii) Startup reliability improvement, (iii) Predictive maintenance, (iv) Repair/overhaul cost down. Illustrative examples for each of the above areas are presented in our study, focusing on challenges and adopted techniques ranging from purely statistical approaches to the implementation of machine learning algorithms. The obtained results demonstrate how the value is obtained using transient condition analytics in the BH iCenter experience.

Keywords: analytics, diagnostics, monitoring, turbomachinery

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Authors: Anastasios Papathanasiou, George Liontos, Athanasios Katsouras, Vasiliki Liagkou, Euripides Glavas

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Email remains a crucial communication tool due to its efficiency, accessibility and cost-effectiveness, enabling rapid information exchange across global networks. However, the global adoption of email has also made it a prime target for cyber threats, including phishing, malware and Business Email Compromise (BEC) attacks, which exploit its integral role in personal and professional realms in order to perform fraud and data breaches. To combat these threats, this research advocates for a multi-layered defense strategy incorporating advanced technological tools such as anti-spam and anti-malware software, machine learning algorithms and authentication protocols. Moreover, we developed an artificial intelligence model specifically designed to analyze email headers and assess their security status. This AI-driven model examines various components of email headers, such as "From" addresses, ‘Received’ paths and the integrity of SPF, DKIM and DMARC records. Upon analysis, it generates comprehensive reports that indicate whether an email is likely to be malicious or benign. This capability empowers users to identify potentially dangerous emails promptly, enhancing their ability to avoid phishing attacks, malware infections and other cyber threats.

Keywords: email security, artificial intelligence, header analysis, threat detection, phishing, DMARC, DKIM, SPF, ai model

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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Authors: Jianhong Xiang, Rui Sun, Linyu Wang

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In recent years, due to the continuous improvement of deep learning theory, Convolutional Neural Network (CNN) has played a great superior performance in the research of Hyperspectral Image (HSI) classification. Since HSI has rich spatial-spectral information, only utilizing a single dimensional or single size convolutional kernel will limit the detailed feature information received by CNN, which limits the classification accuracy of HSI. In this paper, we design a multi-scale CNN with MLP based on residual and attention modules (INRAM-3DCNN) for the HSI classification task. We propose to use multiple 3D convolutional kernels to extract the packet feature information and fully learn the spatial-spectral features of HSI while designing residual 3D convolutional branches to avoid the decline of classification accuracy due to network degradation. Secondly, we also design the 2D Inception module with a joint channel attention mechanism to quickly extract key spatial feature information at different scales of HSI and reduce the complexity of the 3D model. Due to the high parallel processing capability and nonlinear global action of the Multilayer Perceptron (MLP), we use it in combination with the previous CNN structure for the final classification process. The experimental results on two HSI datasets show that the proposed INRAM-3DCNN method has superior classification performance and can perform the classification task excellently.

Keywords: INRAM-3DCNN, residual, channel attention, hyperspectral image classification

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

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Authors: Nina Leila Mussa

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Background: The devastating effects of the war on Syria’s educational infrastructure has been widely reported, with millions of children denied access. However, among those who resettled in Lebanon, the impact of receiving educational assistance on their abilities to pass the English entrance exam is not well described. The aim of this study was to identify predictors of success among Syrian refugees receiving English language courses in a Lebanese university. Methods: The database of Syrian refugee girls matriculated in English courses at the American University of Beirut (AUB) was reviewed. The study period was 7/2018-09/2020. Variables compared included: family size and income, welfare status, parents’ education, English proficiency, access to the internet, and need for external help with homework. Results: For the study period, there were 28 girls enrolled. The average family size was 6 (range 4-9), with eight having completed primary, 14 secondary education, and 6 graduated high school. Eighteen were single-income families. After 12 weeks of English courses, 16 passed the Test of English as Foreign Language (TOEFL) from the first attempt, and 12 failed. Out of the 12, 8 received external help, and 6 passed on the second attempt, which brings the total number of successful passing to 22. Conclusion: Despite the tragedy of war, girls receiving assistance in learning English in Lebanon are able to pass the basic language test. Investment in enhancing those educational experiences will be determinantal in achieving widespread progress among those at-risk children.

Keywords: refugee girls, TOEFL, education, success

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Authors: Sujeet Kumar

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Education has greater importance particularly in terms of increasing human capital and economic competitiveness. It plays a crucial role in terms of cognitive and skill development. Its plays a vital role in process of socialization, fostering social justice, and enhancing social cohesion. Policy related to education has been always a priority for developed countries, which is later adopted by developing countries also. The government of India has also brought change in education polices in line with recognizing change at national and supranational level. However, quality education is still not become an open door for every child in India and several reports are produced year to year about level of school education in India. This paper is concerned with schooling in India. Particularly, it focuses on two government and two private schools in Bihar, but reference has made to schools in Delhi especially around slum communities. The paper presents brief historical context and an overview of current school systems in India. Later, it focuses on analysis of current development in policy in reference with field observation, which is anchored around choice, diversity, market – orientation and gap between different groups of pupils. There is greater degree of difference observed at private and government school levels in terms of quality of teachers, method of teaching and overall environment of learning. The paper concludes that the recent policy development in education particularly Sarva Siksha Abhiyaan (SAA) and Right to Education Act (2009) has required renovating new approach to bridge the gap through broader consultation at grassroots and participatory approach with different stakeholders.

Keywords: education, public policy, participatory approach

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Authors: Rana Alaa El-Deen Ahmed, M. Elemam Shehab, Shereen Morsy, Nermeen Mekawie

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With the growing popularity and acceptance of e-commerce platforms, users face an ever increasing burden in actually choosing the right product from the large number of online offers. Thus, techniques for personalization and shopping guides are needed by users. For a pleasant and successful shopping experience, users need to know easily which products to buy with high confidence. Since selling a wide variety of products has become easier due to the popularity of online stores, online retailers are able to sell more products than a physical store. The disadvantage is that the customers might not find products they need. In this research the customer will be able to find the products he is searching for, because recommender systems are used in some ecommerce web sites. Recommender system learns from the information about customers and products and provides appropriate personalized recommendations to customers to find the needed product. In this paper eleven classification algorithms are comparatively tested to find the best classifier fit for consumer online shopping attitudes and behavior in the experimented dataset. The WEKA knowledge analysis tool, which is an open source data mining workbench software used in comparing conventional classifiers to get the best classifier was used in this research. In this research by using the data mining tool (WEKA) with the experimented classifiers the results show that decision table and filtered classifier gives the highest accuracy and the lowest accuracy classification via clustering and simple cart.

Keywords: classification, data mining, machine learning, online shopping, WEKA

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Authors: M. Shopska, D. Paneva, G. Kadinov, Z. Cherkezova-Zheleva, I. Mitov

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The iron containing materials are used as catalysts in different processes. The chemical methods of their synthesis use toxic and expensive chemicals; sophisticated devices; energy consumption processes that raise their cost. Besides, dangerous waste products are formed. At present time such syntheses are out of date and wasteless technologies are indispensable. The bioinspired technologies are consistent with the ecological requirements. Different microorganisms participate in the biomineralization of the iron and some phytochemicals are involved, too. The methods for biogenic production of iron containing materials are clean, simple, nontoxic, realized at ambient temperature and pressure, cheaper. The biogenic iron materials embrace different iron compounds. Due to their origin these substances are nanosized, amorphous or poorly crystalline, porous and have number of useful properties like SPM, high magnetism, low toxicity, biocompatibility, absorption of microwaves, high surface area/volume ratio, active sites on the surface with unusual coordination that distinguish them from the bulk materials. The biogenic iron materials are applied in the heterogeneous catalysis in different roles - precursor, active component, support, immobilizer. The application of biogenic iron oxide materials gives rise to increased catalytic activity in comparison with those of abiotic origin. In our study we investigated the catalytic behavior of biomasses obtained by cultivation of Leptothrix bacteria in three nutrition media – Adler, Fedorov, and Lieske. The biomass composition was studied by Moessbauer spectroscopy and transmission IRS. Catalytic experiments on CO oxidation were carried out using in situ DRIFTS. Our results showed that: i) the used biomasses contain α-FeOOH, γ-FeOOH, γ-Fe2O3 in different ratios; ii) the biomass formed in Adler medium contains γ-FeOOH as main phase. The CO conversion was about 50% as evaluated by decreased integrated band intensity in the gas mixture spectra during the reaction. The main phase in the spent sample is γ-Fe2O3; iii) the biomass formed in Lieske medium contains α-FeOOH. The CO conversion was about 20%. The main phase in the spent sample is α-Fe2O3; iv) the biomass formed in Fedorov medium contains γ-Fe2O3 as main phase. CO conversion in the test reaction was about 19%. The results showed that the catalytic activity up to 200°C resulted predominantly from α-FeOOH and γ-FeOOH. The catalytic activity at temperatures higher than 200°C was due to the formation of γ-Fe2O3. The oxyhydroxides, which are the principal compounds in the biomass, have low catalytic activity in the used reaction; the maghemite has relatively good catalytic activity; the hematite has activity commensurate with that of the oxyhydroxides. Moreover it can be affirmed that catalytic activity is inherent in maghemite, which is obtained by transformation of the biogenic lepidocrocite, i.e. it has biogenic precursor.

Keywords: nanosized biogenic iron compounds, catalytic behavior in reaction of CO oxidation, in situ DRIFTS, Moessbauer spectroscopy

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Authors: Virender Singh, Mathew Rees, Simon Hampton, Sivaram Annadurai

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Plant identification is a challenging task that aims to identify the family, genus, and species according to plant morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users narrow down the possibilities. However, numerous morphological similarities between and within species render correct classification difficult. In this paper, we tested custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88,000 provided by the Royal Horticultural Society (RHS) and a smaller dataset of 16,000 images from the PlantClef 2015 dataset for classifying plants at genus and species levels, respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420 and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. For classifying plants at the species level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success. In conclusion, these results could help end users, professionals and the general public alike in identifying plants quicker and with improved accuracy.

Keywords: plant identification, CNN, image processing, vision transformer, classification

Procedia PDF Downloads 78

Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifying the RBCs as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-alaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively.

Keywords: K-nearest neighbors algorithm, radial basis function neural network, red blood cells, support vector machine

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Authors: Hanadi Khadawardi

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The current study contributes to research on foreign/second language (L2) academic reading by presenting a significant case study, which seeks to investigate specific groups of international (Arab) postgraduate students’ L2 academic reading practices in the UK educational context. In particular, the study scrutinises postgraduate students’ L2 paper-based and digital-based academic reading strategies, and their use of digital aids while engaged in L2 academic reading. To this end, the study investigates Arab readers’ attitudes toward digital L2 academic reading. The study aims to compare between paper and digital L2 academic reading strategies that the students employ and which reading formats they prefer. This study tracks Masters-level students and examines the way in which their reading strategies and attitudes change throughout their Masters programme in the UK educational context. The academic reading strategies and attitudes of five students from four different disciplines (Health Science, Psychology, Management, and Education) are investigated at two points during their one-year Masters programmes. In addition, the study investigates the same phenomenon with 15 Saudi PhD students drawn from seven different disciplines (Computer Science, Engineering, Psychology, Management, Marketing, Health Science, and Applied Linguistics) at one period of their study in the same context. The study uses think-aloud protocol, field notes, stimulated recall, and semi-structured interviews to collect data. The data is analysed qualitatively. The results of the study will explain the process of learning in terms of reading L2 paper and digital academic texts in the L2 context.

Keywords: EFL: English as a foreign language, ESL: English as a second language, L: Language

Procedia PDF Downloads 364