Search results for: cellular learning automata

Authors: Samantha Rix

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The purpose of this research paper is to investigate the cognitive processing of learners who receive input but produce very little or no output, and who, when they do produce output, exhibit a similar language proficiency as do those learners who produced output more regularly in the language classroom. Previous studies have investigated the benefits of output (with somewhat differing results); therefore, the presentation will begin with an investigation of what may underlie gains in proficiency without output. Consequently, a pilot study was designed and conducted to gain insight into the cognitive processing of low-output language learners looking, for example, at quantity and quality of noticing. This will be carried out within the paradigm of action classroom research, observing and interviewing low-output language learners in an intensive English program at a small Midwest university. The results of the pilot study indicated that autonomy in language learning, specifically utilizing strategies such self-monitoring, self-talk, and thinking 'out-loud', were crucial in the development of language proficiency for academic-level performance. The presentation concludes with an examination of pedagogical implication for classroom use in order to aide students in their language development.

Keywords: cognitive processing, language learners, language proficiency, learning strategies

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Authors: Hamidreza Jabal Ameli, Anahita Movahedi

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Purpose: In radionuclide therapy, radioactive atoms are coupled to monoclonal antibodies (mAbs) for treating cancer tumor while limiting radiation to healthy tissues. We know that tumoral and normal tissues are not equally sensitive to radiation. In fact, biological effects such as cellular repair processes or the presence of less radiosensitive cells such as hypoxic cells should be taken account. For this reason, in this paper, we want to calculate biological effect dose (BED) inside tumoral area and healthy cells around tumors. Methods: In this study, deposited doses of a radionuclide, gold-198, inside cells lattice and surrounding healthy tissues were calculated with Monte Carlo method. The elemental compositions and density of malignant and healthy tissues were obtained from ICRU Report 44. For reaching to real condition of oxygen effects, the necrosis and hypoxia area inside tumors has been assessed. Results: With regard to linear-quadratic expression which was defined in Monte Carlo, results showed that a large amount of BED is deposited in the well-oxygenated part of the hypoxia area compared to necrosis area. Moreover, there is a significant difference between the curves of absorbed dose with BED and without BED.

Keywords: biological dose, monte carlo, hypoxia, radionuclide therapy

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Authors: A. Eiguren-Munitis, N. Berasategi, J. M. Correa

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Changes in family structures, immigration, economic crisis, among others, hinder the connection between different generations. This situation gives rise to a greater lack of social protection of the groups in vulnerable situations, such as the elderly and children. There is a growing need to search for shared spaces where different generations manage to break negative stereotypes and interact with each other. The school environment provides a favourable context in which the approach of different generations can be worked on. The intergenerational experiences that take place within the school context help to introduce the educational ideology for a lifetime. This induces bilateral learning, which encourages citizen participation. For this reason, the general objective of this research is to deepen the impact that intergenerational experiences have on participating students. The research is carried out based on mixed methods. The qualitative and quantitative evaluation included pre-test and post-test questionnaires (n=148) and group interviews (n=43). The results indicate that the intergenerational experiences influence different levels, on the one hand, help to promote school motivation and on the other hand, help to reduce negative stereotypes towards older people thus contributing to greater social cohesion.

Keywords: intergenerational learning, school, stereotypes, social cohesion

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Authors: Muhammad Ramzan

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STEM Education and Critical Thinking Skills are important 21st-century skills. STEM Education is necessary to promote secondary school students’ critical thinking skills. These skills are critical for teachers to respond to students. Pakistan is in the preliminary stages of integrating STEM Education in institutions like other developing countries. Unfortunately, most secondary school students in Pakistan are unaware of STEM Education and teachers are not applying critical thinking skills in classrooms. The study's objectives mainly deal with; to identify the importance of STEM Education in the teaching-learning process; to find out the factors affecting critical thinking skills that can develop interest in students in STEM Education and suggestions on how to improve critical thinking skills in students regarding STEM Education. This study was descriptive. The population of the study was secondary school students. Data was collected from 200 secondary school students through a questionnaire. The research results show that critical thinking skills develop interest in students towards STEM Education.

Keywords: STEM education, teachers, students, critical thinking skills, teaching and learning process

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Authors: Ahmed Abdelrahman, Ahmed Abdelraheem

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There are many essential factors affecting the integration of information and communication technology (ICT) into teaching and learning, including technology infrastructure, institutional support, professional development, and faculty members’ beliefs regarding ICT integration. The present research project investigated the current status of integrating ICT into teaching and learning at Sultan Qaboos University (SQU). A sample of 220 faculty members from six different colleges and four administrators from the Center of Educational Technology (CET) and the Center for Information Systems (CIS) at SQU in Oman were chosen, and quantitative, qualitative design using a semi-structured questionnaire, interviews and checklists were employed. The findings show that SQU had a high availability of ICT infrastructure in terms of hardware, software, and support services, as well as adequate computer labs for educational purposes. However, the results also indicated that, although SQU provided a series of professional development workshops related to using ICT in teaching, few faculty members were interested. Furthermore, the finding indicated that the degree of ICT integration into teaching at SQU was at a medium level.

Keywords: information and communication technology, integration, professional development, teaching

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Authors: Jinfeng Zhang, Chun-Sing Lee

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The use of different nanocarriers for delivering hydrophobic pharmaceutical agents to tumor sites has garnered major attention. Despite the merits of these nanocarriers, further studies are needed for improving their drug loading capacities (typically less than 10%) and reducing their potential systemic toxicity. So development of alternative self-carried nanodrug delivery strategies without using any inert carriers is highly desirable. In this study, we developed a self-carried theranostic curcumin (Cur) nanodrug for highly effective cancer therapy in vitro and in vivo with real-time monitoring of drug release. With a biocompatible C18PMH-PEG functionalization, the Cur nanoparticles (NPs) showed excellent dispersibility and outstanding stability in physiological environment, with drug loading capacity higher than 78 wt.%. Both confocal microscopy and flow cytometry confirmed the cellular fluorescent “OFF-ON” activation and real-time monitoring of Cur molecule release, showing its potential for cancer diagnosis. In vitro and in vivo experiments clearly show that therapeutic efficacy of the PEGylated Cur NPs is much better than that of free Cur. This self-carried theranostic strategy with real-time monitoring of drug release may open a new way for simultaneous cancer therapy and diagnosis.

Keywords: drug delivery, in vitro and in vivo cancer therapy, real-time monitoring, self-carried

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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

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

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Authors: Nkechinyere Joy Olawuyi, Babajide Samuel Afolabi, Bola Ibitoye

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This study collected a preprocessed dataset of chest radiographs and formulated a deep neural network model for detecting abnormalities. It also evaluated the performance of the formulated model and implemented a prototype of the formulated model. This was with the view to developing a deep neural network model to automatically classify abnormalities in chest radiographs. In order to achieve the overall purpose of this research, a large set of chest x-ray images were sourced for and collected from the CheXpert dataset, which is an online repository of annotated chest radiographs compiled by the Machine Learning Research Group, Stanford University. The chest radiographs were preprocessed into a format that can be fed into a deep neural network. The preprocessing techniques used were standardization and normalization. The classification problem was formulated as a multi-label binary classification model, which used convolutional neural network architecture to make a decision on whether an abnormality was present or not in the chest radiographs. The classification model was evaluated using specificity, sensitivity, and Area Under Curve (AUC) score as the parameter. A prototype of the classification model was implemented using Keras Open source deep learning framework in Python Programming Language. The AUC ROC curve of the model was able to classify Atelestasis, Support devices, Pleural effusion, Pneumonia, A normal CXR (no finding), Pneumothorax, and Consolidation. However, Lung opacity and Cardiomegaly had a probability of less than 0.5 and thus were classified as absent. Precision, recall, and F1 score values were 0.78; this implies that the number of False Positive and False Negative is the same, revealing some measure of label imbalance in the dataset. The study concluded that the developed model is sufficient to classify abnormalities present in chest radiographs into present or absent.

Keywords: transfer learning, convolutional neural network, radiograph, classification, multi-label

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Authors: Brenda Ravenscroft, Ulemu Luhanga, Bev King

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A comprehensive evaluation of online learning needs to include a blend of educational design, technology use, and online instructional practices that integrate technology appropriately for developing and delivering quality online courses. Research shows that classroom-based evaluation tools do not adequately capture the dynamic relationships between content, pedagogy, and technology in online courses. Furthermore, studies suggest that using classroom evaluations for online courses yields lower than normal scores for instructors, and may affect faculty negatively in terms of administrative decisions. In 2014, the Faculty of Arts and Science at Queen’s University responded to this evidence by seeking an alternative to the university-mandated evaluation tool, which is designed for classroom learning. The Faculty is deeply engaged in e-learning, offering large variety of online courses and programs in the sciences, social sciences, humanities and arts. This paper describes the process by which a new student survey instrument for online courses was developed and piloted, the methods used to analyze the data, and the ways in which the instrument was subsequently adapted based on the results. It concludes with a critical reflection on the challenges of evaluating e-learning. The Student Evaluation of Online Teaching Effectiveness (SEOTE), developed by Arthur W. Bangert in 2004 to assess constructivist-compatible online teaching practices, provided the starting point. Modifications were made in order to allow the instrument to serve the two functions required by the university: student survey results provide the instructor with feedback to enhance their teaching, and also provide the institution with evidence of teaching quality in personnel processes. Changes were therefore made to the SEOTE to distinguish more clearly between evaluation of the instructor’s teaching and evaluation of the course design, since, in the online environment, the instructor is not necessarily the course designer. After the first pilot phase, involving 35 courses, the results were analyzed using Stobart's validity framework as a guide. This process included statistical analyses of the data to test for reliability and validity, student and instructor focus groups to ascertain the tool’s usefulness in terms of the feedback it provided, and an assessment of the utility of the results by the Faculty’s e-learning unit responsible for supporting online course design. A set of recommendations led to further modifications to the survey instrument prior to a second pilot phase involving 19 courses. Following the second pilot, statistical analyses were repeated, and more focus groups were used, this time involving deans and other decision makers to determine the usefulness of the survey results in personnel processes. As a result of this inclusive process and robust analysis, the modified SEOTE instrument is currently being considered for adoption as the standard evaluation tool for all online courses at the university. Audience members at this presentation will be stimulated to consider factors that differentiate effective evaluation of online courses from classroom-based teaching. They will gain insight into strategies for introducing a new evaluation tool in a unionized institutional environment, and methodologies for evaluating the tool itself.

Keywords: evaluation, online courses, student survey, teaching effectiveness

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Authors: Mohamad Abdullah

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Recent Advancements in technology have stimulated deep change in the language learning classroom. Flipped classroom as a new pedagogical method is at the center of this change. It turns the classroom into a student-centered environment and promotes interactive and autonomous learning. The present study is an attempt to examine the effectiveness of the Flipped Classroom Model (FCM) on students’ motivation level in English speaking performance. This study was carried out with 27 undergraduate female English majors who enrolled in the course of Advanced Communication Skills (ENGL 154) at Buraimi University College (BUC). Data was collected through Motivation in English Speaking Performance Questionnaire (MESPQ) which has been distributed among the participants of this study pre and post the implementation of FCM. SPSS was used for analyzing data. The Paired T-Test which was carried out on the pre-post of (MESPQ) showed a significant difference between them (p < .009) that revealed participants’ tendency to increase their motivation level in English speaking performance after the application of FCM. In addition, respondents of the current study reported positive views about the implementation of FCM.

Keywords: english speaking performance, motivation, flipped classroom model, learner-contentedness

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Authors: Eman Mohamed Abdelwahab, Badreyya Alkhanbooli

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This study focuses on exploring the challenges encountered by English language teachers in same-ability English language classrooms in the United Arab Emirates public schools. This qualitative study uses open-ended questions for data collection from teacher participants. The study sample includes the participation of 60 English language teachers from 8 public schools across 4 emirates/cities in the United Arab Emirates. The study results highlight a number of challenges that are mostly encountered by English language teachers in their classrooms while teaching in same-ability classrooms, including lack of diversity in abilities, class-time limitation, difficulty in engaging all students (especially lower-achieving students), limited opportunities for peer learning and limited linguistic diversity. A set of suggestions is to be provided by participating teachers and researchers to improve the same-ability teaching and learning experience in English language classrooms.

Keywords: English language teaching, same ability grouping, ESL, English language learners

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Authors: Shanxiong Chen, Xu Han, Xiaolong Wang, Hui Ma

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Yi is an ethnic group mainly living in mainland China, with its own spoken and written language systems, after development of thousands of years. Ancient Yi is one of the six ancient languages in the world, which keeps a record of the history of the Yi people and offers documents valuable for research into human civilization. Recognition of the characters in ancient Yi helps to transform the documents into an electronic form, making their storage and spreading convenient. Due to historical and regional limitations, research on recognition of ancient characters is still inadequate. Thus, deep learning technology was applied to the recognition of such characters. Five models were developed on the basis of the four-layer convolutional neural network (CNN). Alpha-Beta divergence was taken as a penalty term to re-encode output neurons of the five models. Two fully connected layers fulfilled the compression of the features. Finally, at the softmax layer, the orthographic features of ancient Yi characters were re-evaluated, their probability distributions were obtained, and characters with features of the highest probability were recognized. Tests conducted show that the method has achieved higher precision compared with the traditional CNN model for handwriting recognition of the ancient Yi.

Keywords: recognition, CNN, Yi character, divergence

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Authors: Sagir M. Yusuf, Chris Baber

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In this paper, we describe how to achieve knowledge understanding and prediction (Situation Awareness (SA)) for multiple-agents conducting searching activity using Bayesian inferential reasoning and learning. Bayesian Belief Network was used to monitor agents' knowledge about their environment, and cases are recorded for the network training using expectation-maximisation or gradient descent algorithm. The well trained network will be used for decision making and environmental situation prediction. Forest fire searching by multiple UAVs was the use case. UAVs are tasked to explore a forest and find a fire for urgent actions by the fire wardens. The paper focused on two problems: (i) effective agents’ path planning strategy and (ii) knowledge understanding and prediction (SA). The path planning problem by inspiring animal mode of foraging using Lévy distribution augmented with Bayesian reasoning was fully described in this paper. Results proof that the Lévy flight strategy performs better than the previous fixed-pattern (e.g., parallel sweeps) approaches in terms of energy and time utilisation. We also introduced a waypoint assessment strategy called k-previous waypoints assessment. It improves the performance of the ordinary levy flight by saving agent’s resources and mission time through redundant search avoidance. The agents (UAVs) are to report their mission knowledge at the central server for interpretation and prediction purposes. Bayesian reasoning and learning were used for the SA and results proof effectiveness in different environments scenario in terms of prediction and effective knowledge representation. The prediction accuracy was measured using learning error rate, logarithm loss, and Brier score and the result proves that little agents mission that can be used for prediction within the same or different environment. Finally, we described a situation-based knowledge visualization and prediction technique for heterogeneous multi-UAV mission. While this paper proves linkage of Bayesian reasoning and learning with SA and effective searching strategy, future works is focusing on simplifying the architecture.

Keywords: Levy flight, distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Farzaneh Sarbandi Farahani

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Drought and decrease in the level of lakes in recent years due to global warming and excessive use of water resources feeding lakes are of great importance, and this research has provided a structure to investigate this issue. First, the information required for simulating lake drought is provided with strong references and necessary assumptions. Entity-Component-System (ECS) structure has been used for simulation, which can consider assumptions flexibly in simulation. Three major users (i.e., Industry, agriculture, and Domestic users) consume water from groundwater and surface water (i.e., streams, rivers and lakes). Lake Mead has been considered for simulation, and the information necessary to investigate its drought has also been provided. The results are presented in the form of a scenario-based design and optimal strategy selection. For optimal strategy selection, a deep reinforcement algorithm is developed to select the best set of strategies among all possible projects. These results can provide a better view of how to plan to prevent lake drought.

Keywords: drought simulation, Mead lake, entity component system programming, deep reinforcement learning

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Authors: Fakieh Alrabai

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This paper presents an experimental study designed to explore some of the learner’s individual and interpersonal factors (e.g. persistence, interest, regulation, satisfaction, appreciation, etc.) that Saudi learners experience when learning English as a Foreign Language and how learners’ perceptions of these factors influence various aspects of their motivation to learn English language. As part of the study, a 27-item structured survey was administered to a randomly selected sample of 105 Saudi learners from public schools and universities. Data collected through the survey were subjected to some basic statistical analyses, such as "mean" and "standard deviation". Based on the results from the analysis, a number of generalizations and conclusions are made in relation to how these inherent factors affect Saudi learners’ motivation to learn English as a foreign language. In addition, some recommendations are offered to Saudi academics on how to effectively make use of such factors, which may enable Saudi teachers and learners of English as a foreign language to achieve better learning outcomes in an area widely associated by Saudis with lack of success.

Keywords: persistence, interest, appreciation, satisfaction, SL/FL motivation

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Authors: Sanat K. Dash, Rama S. Verma, Sarit K. Das

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A logarithmic microfluidic shear device was designed and fabricated for cellular mechanotransduction studies. The device contains four cell culture chambers in which flow was modulated to achieve a logarithmic increment. Resistance values were optimized to make the device compact. The network of resistances was developed according to a unique combination of series and parallel resistances as found via optimization. Simulation results done in Ansys 16.1 matched the analytical calculations and showed the shear stress distribution at different inlet flow rates. Fabrication of the device was carried out using conventional photolithography and PDMS soft lithography. Flow profile was validated taking DI water as working fluid and measuring the volume collected at all four outlets. Volumes collected at the outlets were in accordance with the simulation results at inlet flow rates ranging from 1 ml/min to 0.1 ml/min. The device can exert fluid shear stresses ranging four orders of magnitude on the culture chamber walls which will cover shear stress values from interstitial flow to blood flow. This will allow studying cell behavior in the long physiological range of shear stress in a single run reducing number of experiments.

Keywords: microfluidics, mechanotransduction, fluid shear stress, physiological shear

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Authors: A. Marais

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A challenging aspect of teaching cello to novice adult learners is finding adequate lesson material and applying relevant teaching methodologies. It could play a crucial role in adult learners' decision to commence or stop taking music lessons. This study contributes to the theory and practises of continuing education. This study is important to lifelong learning, especially with the focus on adult teaching and learning and the difficulties concerning these themes. The research problem identified for this study is we are not aware of adults' life stories; thus, cello lesson material is not always relevant for adult's specific needs for motivation and goals for starting cello lessons. In my experience, an adult does not necessarily want to play children songs when they learn a new instrument. They want material and lessons fitted to adult learners. Adults also learn differently from younger beginners. Adults ask questions such as how and why, while children more readily accept what is being taught. This research creates awareness of adults' musical needs and learning methods. If every adult shares their own story for commencing and continuing with cello lessons, material should be created, revised, or adapted for more individually appropriate lessons. A number of studies show that adults taking music lessons experience a decrease in feelings of loneliness and isolation. It gives adults a sense of wellbeing and can help improve immune systems. The purpose of this research study will be to discover the life stories of adult amateur cellists. At this stage in the research, the life stories of amateur cellists can generally be defined as personal reflections of their motivations for and experiences of commencing and continuing with individual lessons. The findings of this study will contribute to the development of cello lesson material for adult beginners based on their stories. This research could also encourage adults to commence with music lessons and could, in that way, contribute to their quality of life. Music learners become aware of deep spiritual, emotional, and social values incorporated or experienced through musical learning. This will be a qualitative study with a narrative approach making use of oral history. The chosen method will encapsulate the stories of amateur individual adults starting and continuing with cello lessons. The narrative method entails experiences as expressed in lived and told stories of individuals. Oral history is used as part of the narrative method and entails gathering of personal reflections of events and their cause and effects from an individual or several individuals. These findings from this study will contribute to adult amateur cellists' motivations to continue with music lessons and inspire others to commence. The inspiring life stories of the amateur cellists would provide insight into finding and creating new cello lesson material and enhance existing teaching methodologies for adult amateur cellists.

Keywords: adult, amateur, cello, education, learning, music, stories

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Authors: Pantaleon Lutta, Mohamed Sedky, Mohamed Hassan

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The inability of organizations to put in place management control measures for Internet of Things (IoT) complexities persists to be a risk concern. Policy makers have been left to scamper in finding measures to combat these security and privacy concerns. IoT forensics is a cumbersome process as there is no standardization of the IoT products, no or limited historical data are stored on the devices. This paper highlights why IoT forensics is a unique adventure and brought out the legal challenges encountered in the investigation process. A quadrant model is presented to study the conflicting aspects in IoT forensics. The model analyses the effectiveness of forensic investigation process versus the admissibility of the evidence integrity; taking into account the user privacy and the providers’ compliance with the laws and regulations. Our analysis concludes that a semi-automated forensic process using machine learning, could eliminate the human factor from the profiling and surveillance processes, and hence resolves the issues of data protection (privacy and confidentiality).

Keywords: cloud forensics, data protection Laws, GDPR, IoT forensics, machine Learning

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Authors: Cina Mosito, Toyin Mary Adewumi, Charlene Nissen

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One of the goals of inclusive education is to provide learners with suitable learning environments and prospects to best attain their potential. This study sought to determine the experiences of studying inclusive education on pre-service teachers’ teaching within the South African education context. A purposeful sample comprising 6 pre-service teachers was selected from a university of technology located in the Western Cape South Africa. Data were collected using open-ended questionnaires, which were exploratory in nature and analyzed thematically. The findings supported significant proportions of experiences as self-reported by pre-service teachers. The pre-service teachers’ experiences of studying inclusive education included inclusive education as an “eye-opener” to the fact that learners experiencing various barriers to learning can be accommodated in the regular classrooms, exposure to some aspects of inclusive education, such as diversity, learners’ rights, and curriculum differentiation. It was also revealed that studying inclusive education made pre-service teachers love and enjoy teaching more. The study shows that awareness of inclusive education has influenced pre-service teachers in South African schools.

Keywords: experience, inclusive education, pre-service teacher, South Africa

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Authors: Anne Marie Morrin

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This paper will focus on the design, delivery and assessment of a transdisciplinary STEAM (Science, Technology, Engineering, Arts, and Mathematics) education initiative in a college of education in Ireland. The project explores a transdisciplinary approach to supporting STEAM education where the concepts, methodologies and assessments employed derive from visual art sessions within initial teacher education. The research will demonstrate that the STEAM Education approach is effective when visual art concepts and methods are placed at the core of the teaching and learning experience. Within this study, emphasis is placed on authentic collaboration and transdisciplinary pedagogical approaches with the STEAM subjects. The partners included a combination of teaching expertise in STEM and Visual Arts education, artists, in-service and pre-service teachers and children. The inclusion of all stakeholders mentioned moves towards a more authentic approach where transdisciplinary practice is at the core of the teaching and learning. Qualitative data was collected using a combination of questionnaires (focused and open-ended questions) and focus groups. In addition, the data was collected through video diaries where students reflected on their visual journals and transdisciplinary practice, which gave rich insight into participants' experiences and opinions on their learning. It was found that an effective program of STEAM education integration was informed by co-teaching (continuous professional development), which involved a commitment to adaptable and flexible approaches to teaching, learning, and assessment, as well as the importance of continuous reflection-in-action by all participants. The delivery of a transdisciplinary model of STEAM education was devised to reconceptualizatise how individual subject areas can develop essential skills and tackle critical issues (such as self-care and climate change) through data visualisation and technology. The success of the project can be attributed to the collaboration, which was inclusive, flexible and a willingness between various stakeholders to be involved in the design and implementation of the project from conception to completion. The case study approach taken is particularistic (focusing on the STEAM-ED project), descriptive (providing in-depth descriptions from varied and multiple perspectives), and heuristic (interpreting the participants’ experiences and what meaning they attributed to their experiences).

Keywords: collaboration, transdisciplinary, STEAM, visual arts education

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Authors: Jingwen Ou

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Writing for academic purposes in a second or foreign language is one of the most important and the most demanding skills to be mastered by non-native speakers. Traditionally, the EAP writing instruction at the tertiary level encompasses the teaching of academic genre knowledge, more specifically, the disciplinary writing conventions, the rhetorical functions, and specific linguistic features. However, one of the main sources of challenges in English academic writing for L2 students at the tertiary level can still be found in proficiency in academic discourse, especially vocabulary, academic register, and organization. Data-Driven Learning (DDL) is defined as “a pedagogical approach featuring direct learner engagement with corpus data”. In the past two decades, the rising popularity of the application of the data-driven learning (DDL) approach in the field of EAP writing teaching has been noticed. Such a combination has not only transformed traditional pedagogy aided by published DDL guidebooks in classroom use but also triggered global research on corpus use in EAP classrooms. This study endeavors to delineate a systematic review of research in the intersection of DDL and EAP writing instruction by conducting a systematic literature review on both indirect and direct DDL practice in EAP writing instructional settings in China. Furthermore, the review provides a synthesis of significant discoveries emanating from prior research investigations concerning Chinese university students’ perception of Data-Driven Learning (DDL) and the subsequent impact on their academic writing performance following corpus-based training. Research papers were selected from Scopus-indexed journals and core journals from two main Chinese academic databases (CNKI and Wanfang) published in both English and Chinese over the last ten years based on keyword searches. Results indicated an insufficiency of empirical DDL research despite a noticeable upward trend in corpus research on discourse analysis and indirect corpus applications for material design by language teachers. Research on the direct use of corpora and corpus tools in DDL, particularly in combination with genre-based EAP teaching, remains a relatively small fraction of the whole body of research in Chinese higher education settings. Such scarcity is highly related to the prevailing absence of systematic training in English academic writing registers within most Chinese universities' EAP syllabi due to the Chinese English Medium Instruction policy, where only English major students are mandated to submit English dissertations. Findings also revealed that Chinese learners still held mixed attitudes towards corpus tools influenced by learner differences, limited access to language corpora, and insufficient pre-training on corpus theoretical concepts, despite their improvements in final academic writing performance.

Keywords: corpus linguistics, data-driven learning, EAP, tertiary education in China

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Authors: Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu

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Causal inference from observational data is receiving wide applications in many fields. However, unidentifiable situations, where causal effects cannot be uniquely computed from observational data, pose critical barriers to applying causal inference to complicated real applications. In this paper, we develop a bounding method for estimating the average causal effect (ACE) under unidentifiable situations due to hidden confounders. We propose to parameterize the unknown exogenous random variables and structural equations of a causal model using neural networks and implicit generative models. Then, with an adversarial learning framework, we search the parameter space to explicitly traverse causal models that agree with the given observational distribution and find those that minimize or maximize the ACE to obtain its lower and upper bounds. The proposed method does not make any assumption about the data generating process and the type of the variables. Experiments using both synthetic and real-world datasets show the effectiveness of the method.

Keywords: average causal effect, hidden confounding, bound estimation, generative adversarial learning

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Authors: Sina Saadati

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Multiprocessors Systems-On-Chips (MPSOCs) are used widely on modern computers to execute sophisticated software and applications. These systems include different processors for distinct aims. Most of the proposed task schedulers attempt to improve energy consumption. In some schedulers, the processor's temperature is considered to increase the system's reliability and performance. In this research, we have proposed a new method for thermal-aware task scheduling which is based on an artificial neural network (ANN). This method enables us to consider a variety of factors in the scheduling process. Some factors like ambient temperature, season (which is important for some embedded systems), speed of the processor, computing type of tasks and have a complex relationship with the final temperature of the system. This Issue can be solved using a machine learning algorithm. Another point is that our solution makes the system intelligent So that It can be adaptive. We have also shown that the computational complexity of the proposed method is cheap. As a consequence, It is also suitable for battery-powered systems.

Keywords: task scheduling, MOSOC, artificial neural network, machine learning, architecture of computers, artificial intelligence

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Authors: Maimuna Akram, Khadija Zia, Sohaib Naseer

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Pedagogical objectives and the nature of the course content may lead instructors to take varied approaches to selecting a student for the cold call, specifically in a studio setup where students work on different projects independently and show progress work time to time at scheduled critiques. Cold-calling often proves to be an effective tool in eliciting a response without enforcing judgment onto the recipients. While there is a mixed range of behavior exhibited by students who are cold-called, a classification of responses from anxiety-provoking to inspiring may be elicited; there is a need for a greater understanding of utilizing the exchanges in bringing about fruitful and engaging outcomes of studio discussions. This study aims to unravel the dimensions of utilizing the cold-call approach in a didactic exchange within studio pedagogy. A questionnaire survey was conducted in an undergraduate class at Arts and Design School. The impact of cold calling on students’ participation was determined through various parameters, including course choice, participation frequency, students’ comfortability, and teaching methodology. After analyzing the surveys, specific classroom teachers were interviewed to provide a qualitative perspective of the faculty. It was concluded that cold-calling increases students’ participation frequency and also increases preparation for class. Around 67% of students responded that teaching methods play an important role in learning activities and students’ participation during class discussions. 84% of participants agreed that cold calling is an effective way of learning. According to research, cold-calling can be done in large numbers without making students uncomfortable. As a result, the findings of this study support the use of this instructional method to encourage more students to participate in class discussions.

Keywords: active learning, class discussion, class participation, cold calling, pedagogical methods, student engagement

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Authors: Candela Contero Urgal

Abstract:

Using realia to teach English for Specific Purposes (ESP) is a must, as it is thought to be designed to meet the students’ real needs in their professional life. Teachers are then expected to offer authentic materials and set students in authentic contexts where their learning outcomes can be highly meaningful. One way of engaging students is using social networks as a way to bridge the gap between their everyday life and their ESP learning outcomes. It is in ESP, particularly in Business English teaching, that our study focuses, as the ongoing process of digitalization is leading firms to use social media to communicate with potential clients. The present paper is aimed at carrying out a case study in which different digital tools are employed as a way to offer a collection of formats businesses are currently using so as to internationalize and advertise their products and services. A secondary objective of our study will then be to progress on the development of multidisciplinary competencies students are to acquire during their degree. A two-phased study will be presented. The first phase will cover the analysis of course tasks accomplished by undergraduate students at the University of Cadiz (Spain) in their third year of the Degree in Business Management and Administration by comparing the results obtained during the years 2019 to 2021. The second part of our study will present a survey conducted to these students in 2021 and 2022 so as to verify their interest in learning new ways to digitalize as well as internationalize their future businesses. Findings will confirm students’ interest in working with updated realia in their Business English lessons, as a consequence of their strong belief in the necessity to have authentic contexts and didactic resources. Despite the limitations social media can have as a means to teach business English, students will still find it highly beneficial since it will foster their familiarisation with the digital tools they will need to use when they get to the labour market.

Keywords: English for specific purposes, business English, internationalization of higher education, foreign language teaching

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Authors: G. M. Vlasceanu, H. Iovu, E. Vasile, M. Ionita

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Herein, the synthesis and characterization of chitosan-gelatin highly porous scaffold reinforced with graphene oxide, and hydroxyapatite (HAp), crosslinked with genipin was targeted. In tissue engineering, chitosan and gelatin are two of the most robust biopolymers with wide applicability due to intrinsic biocompatibility, biodegradability, low antigenicity properties, affordability, and ease of processing. HAp, per its exceptional activity in tuning cell-matrix interactions, is acknowledged for its capability of sustaining cellular proliferation by promoting bone-like native micro-media for cell adjustment. Genipin is regarded as a top class cross-linker, while graphene oxide (GO) is viewed as one of the most performant and versatile fillers. The composites with natural bone HAp/biopolymer ratio were obtained by cascading sonochemical treatments, followed by uncomplicated casting methods and by freeze-drying. Their structure was characterized by Fourier Transform Infrared Spectroscopy and X-ray Diffraction, while overall morphology was investigated by Scanning Electron Microscopy (SEM) and micro-Computer Tomography (µ-CT). Ensuing that, in vitro enzyme degradation was performed to detect the most promising compositions for the development of in vivo assays. Suitable GO dispersion was ascertained within the biopolymer mix as nanolayers specific signals lack in both FTIR and XRD spectra, and the specific spectral features of the polymers persisted with GO load enhancement. Overall, correlations between the GO induced material structuration, crystallinity variations, and chemical interaction of the compounds can be correlated with the physical features and bioactivity of each composite formulation. Moreover, the HAp distribution within follows an auspicious density gradient tuned for hybrid osseous/cartilage matter architectures, which were mirrored in the mice model tests. Hence, the synthesis route of a natural polymer blend/hydroxyapatite-graphene oxide composite material is anticipated to emerge as influential formulation in bone tissue engineering. Acknowledgement: This work was supported by the project 'Work-based learning systems using entrepreneurship grants for doctoral and post-doctoral students' (Sisteme de invatare bazate pe munca prin burse antreprenor pentru doctoranzi si postdoctoranzi) - SIMBA, SMIS code 124705 and by a grant of the National Authority for Scientific Research and Innovation, Operational Program Competitiveness Axis 1 - Section E, Program co-financed from European Regional Development Fund 'Investments for your future' under the project number 154/25.11.2016, P_37_221/2015. The nano-CT experiments were possible due to European Regional Development Fund through Competitiveness Operational Program 2014-2020, Priority axis 1, ID P_36_611, MySMIS code 107066, INOVABIOMED.

Keywords: biopolymer blend, ectopic osteoinduction, graphene oxide composite, hydroxyapatite

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Authors: Cheng-Cao Sun, Shu-Jun Li, Cuili Yang, Yongyong Xi, Liang Wang, Feng Zhang, De-Jia Li

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Hsa-miRNA-326 (miR-326) has recently been discovered having anticancer efficacy in different organs. However, the role of miR-326 on non-small cell lung cancer (NSCLC) is still ambiguous. In this study, we investigated the role of miR-326 on the development of NSCLC. The results indicated that miR-326 was significantly down-regulated in primary tumor tissues and very low levels were found in NSCLC cell lines. Ectopic expression of miR-326 in NSCLC cell lines significantly suppressed cell growth as evidenced by cell viability assay, colony formation assay and BrdU staining, through inhibition of cyclin D1, cyclin D2, CDK4, and up-regulation of p57(Kip2) and p21(Waf1/Cip1). In addition, miR-326 induced apoptosis, as indicated by concomitantly with up-regulation of key apoptosis protein cleaved caspase-3, and down-regulation of anti-apoptosis protein Bcl2. Moreover, miR-326 inhibited cellular migration and invasiveness through inhibition of matrix metalloproteinases (MMP)-7 and MMP-9. Further, oncogene CCND1 was revealed to be a putative target of miR-326, which was inversely correlated with miR-326 expression in NSCLC. Taken together, our results demonstrated that miR-326 played a pivotal role on NSCLC through inhibiting cell proliferation, migration, invasion, and promoting apoptosis by targeting oncogenic CCND1.

Keywords: hsa-miRNA-326 (miR-326), cyclin D1, non-small cell lung cancer (NSCLC), proliferation, apoptosis

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Authors: Alex Elentukh

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The paper is based on data collected from final exams administered during five years of teaching the graduate course in software engineering. The visualization instrument with four distinct personas has been used to improve the effectiveness of each class. The study offers a plethora of clues toward students' behavioral preferences. Diversity among students (professional background, physical proximity) is too significant to assume a single face of a learner. This is particularly true for a body of online graduate students in computer science. Conclusions of the study (each learner is unique, and each class is unique) are extrapolated to demystify the notion of an 'average software engineer.' An immediate direction for an educator is to ensure a course applies to a wide audience of very different individuals. On the other hand, a student should be clear about his/her abilities and preferences - to follow the most effective learning path.

Keywords: K.3.2 computer and information science education, learner profiling, adaptive learning, software engineering

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Authors: Chris Procter

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There is a significant debate on the role of University education in developing or teaching employability skills. Should higher education attempt to do this? Is it the best place? Is it able to do so? Different views abound, but the question is wrongly posed – one of the reasons that previous employability initiatives foundered (e.g., in the UK). Our role is less to teach than to guide, less to develop and more to help articulate: “the mind is not a vessel to be filled, but a fire to be lit” (Plutarch). This paper then addresses how this can be achieved taking into account criticism of employability initiatives as well as relevant learning theory. It discusses the experience of a large module which involved students being assessed on all stages of application for a live job description together with reflection on their professional development. The assessment itself adopted a Patchwork Text approach as a vehicle for learning. Students were guided to evaluate their strengths and areas to be developed, articulate their competencies, and reflect upon their development, moving on to new Thresholds of Employability. The paper uses the student voices to express the progress they made. It concludes that employability can and should be an effective part of the higher education curriculum when designed to encourage students to confidently articulate their competencies and take charge of their own professional development.

Keywords: competencies, employability, patchwork assessment, threshold concepts

Procedia PDF Downloads 190

Authors: Mohammad Haghighi, Amineh Akhondi, Leila Jahangard, Mohammad Ahmadpanah, Masoud Ansari

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Background: According to the recent estimation, approximately 4%-12% percent of Iranians have difficulty in learning to read and spell possibly as a result of developmental dyslexia. The study was planned to investigate spelling error patterns among Persian children with developmental dyslexia and compare that with the errors exhibited by control groups Participants: 90 students participated in this study. 30 students from Grade level five, diagnosed as dyslexics by professionals, 30 normal 5th Grade readers and 30 younger normal readers. There were 15 boys and 15 girls in each of the groups. Qualitative and quantitative methods for analysis of errors were used. Results and conclusion: results of this study indicate similar spelling error profiles among dyslexics and the reading level matched groups, and these profiles were different from age-matched group. However, performances of dyslexic group and reading level matched group were different and inconsistent in some cases.

Keywords: spelling, error types, developmental dyslexia, Persian, writing system, learning disabilities, processing

Procedia PDF Downloads 408