Search results for: hybrid learning

Authors: Thierry Eude

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The use of videoconferencing platforms adapted to teaching offers students the opportunity to take distance education courses in much the same way as traditional in-class training. The sessions can be recorded and they allow students the option of following the courses synchronously or asynchronously. Three typical profiles can then be distinguished: students who choose to follow the courses synchronously, students who could attend the course in synchronous mode but choose to follow the session off-line, and students who follow the course asynchronously as they cannot attend the course when it is offered because of professional or personal constraints. Our study consists of observing attendance at all distance education courses offered in the synchronous mode by the Computer Science and Software Engineering Department at Laval University during 10 consecutive semesters. The aim is to identify factors that influence students in their choice of attending the distance courses in synchronous mode. It was found that participation tends to be relatively stable over the years for any one semester (fall, winter summer) and is similar from one course to another, although students may be increasingly familiar with the synchronous distance education courses. Average participation is around 28%. There may be deviations, but they concern only a few courses during certain semesters, suggesting that these deviations would only have occurred because of the composition of particular promotions during specific semesters. Furthermore, course schedules have a great influence on the attendance rate. The highest rates are all for courses which are scheduled outside office hours.

Keywords: attendance, distance undergraduate education in computer science, student behavior, synchronous e-learning

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Authors: Tanmay Bisen, Aastha Shayla

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This study introduces an advanced approach to tree canopy detection in urban environments and a regional analysis of Northern and Central Kolkata that delves into the intricate relationship between urban development and environmental conservation. Leveraging high-resolution drone imagery from diverse urban green spaces in Kolkata, we fine-tuned the deep forest model to enhance its precision and accuracy. Our results, characterized by an impressive Intersection over Union (IoU) score of 0.90 and a mean average precision (mAP) of 0.87, underscore the model's robustness in detecting and classifying tree crowns amidst the complexities of aerial imagery. This research not only emphasizes the importance of model customization for specific datasets but also highlights the potential of drone-based remote sensing in urban forestry studies. The study investigates the spatial distribution, density, and environmental impact of trees in Northern and Central Kolkata. The findings underscore the significance of urban green spaces in met-ropolitan cities, emphasizing the need for sustainable urban planning that integrates green infrastructure for ecological balance and human well-being.

Keywords: urban greenery, advanced spatial distribution analysis, drone imagery, deep learning, tree detection

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Authors: Mercy Vivian Sulaiman, Pablo Chavajay

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This study examined parents ways of supporting and facilitating their first-grade children in a book-activity in Nigeria and the United States. Seventy-five parent-child dyads (38 from Nigeria and 37 from the U.S.) were video recorded constructing narratives around a wordless picture book. Analyses focused on identifying parents’ means of facilitating children’s involvement as well as parents and children's reliance on questions and statements during the shared activity. Nigerian parents assumed a sole narrator approach, guiding the narratives and providing most of the information to their children through referential questions and referential and behavioral statements. Unlike the Nigerian parents, US parents engaged in a shared narrator approach, encouraging and building more on their children's contributions, asking more inferential and yes/no questions, and making more inferential and yes/no statements. Nigerian and US children’s extent and types of questions and statements made during their involvement in the activities varied and their contributions resembled those of their parents in their respective cultural groups. These findings highlight significant cultural variations and similarities in book-sharing practices between parents and children, underscoring the role of parental approaches to children's narrative construction and their impact on their learning.

Keywords: book-sharing, cultural differences, parent-child interactions, narrative contributions, Nigeria, united states

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Authors: Jothilakshmy Nagammal

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This research paper deals with the different case studies, where the Form-Based Codes are adopted in general and the different implementation methods in particular are discussed to develop a method for formulating a new planning model. The organizing principle of the Form-Based Codes, the transect is used to zone the city into various context specific transects. An approach is adopted to develop the new planning model, city Specific Planning Model (CSPM), as a tool to achieve sustainability for any city in general. A case study comparison method in terms of the planning tools used, the code process adopted and the various control regulations implemented in thirty two different cities are done. The analysis shows that there are a variety of ways to implement form-based zoning concepts: Specific plans, a parallel or optional form-based code, transect-based code /smart code, required form-based standards or design guidelines. The case studies describe the positive and negative results from based zoning, Where it is implemented. From the different case studies on the method of the FBC, it is understood that the scale for formulating the Form-Based Code varies from parts of the city to the whole city. The regulating plan is prepared with the organizing principle as the transect in most of the cases. The various implementation methods adopted in these case studies for the formulation of Form-Based Codes are special districts like the Transit Oriented Development (TOD), traditional Neighbourhood Development (TND), specific plan and Street based. The implementation methods vary from mandatory, integrated and floating. To attain sustainability the research takes the approach of developing a regulating plan, using the transect as the organizing principle for the entire area of the city in general in formulating the Form-Based Codes for the selected Special Districts in the study area in specific, street based. Planning is most powerful when it is embedded in the broader context of systemic change and improvement. Systemic is best thought of as holistic, contextualized and stake holder-owned, While systematic can be thought of more as linear, generalisable, and typically top-down or expert driven. The systemic approach is a process that is based on the system theory and system design principles, which are too often ill understood by the general population and policy makers. The system theory embraces the importance of a global perspective, multiple components, interdependencies and interconnections in any system. In addition, the recognition that a change in one part of a system necessarily alters the rest of the system is a cornerstone of the system theory. The proposed regulating plan taking the transect as an organizing principle and Form-Based Codes to achieve sustainability of the city has to be a hybrid code, which is to be integrated within the existing system - A Systemic Approach with a Systematic Process. This approach of introducing a few form based zones into a conventional code could be effective in the phased replacement of an existing code. It could also be an effective way of responding to the near-term pressure of physical change in “sensitive” areas of the community. With this approach and method the new Context Specific Planning Model is created towards achieving sustainability is explained in detail this research paper.

Keywords: context based planning model, form based code, transect, systemic approach

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Authors: Grzegorz Raniszewski, Zbigniew Kolacinski, Lukasz Szymanski, Slawomir Wiak, Lukasz Pietrzak, Dariusz Koza

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One of the most promising area for carbon nanotubes (CNTs) application is medicine. One of the most devastating diseases is cancer. Carbon nanotubes may be used as carriers of a slowly released drug. It is possible to use of electromagnetic waves to destroy cancer cells by the carbon nanotubes (CNTs). In our research we focused on thermal ablation by ferromagnetic carbon nanotubes (Fe-CNTs). In the cancer cell hyperthermia functionalized carbon nanotubes are exposed to radio frequency electromagnetic field. Properly functionalized Fe-CNTs join the cancer cells. Heat generated in nanoparticles connected to nanotubes warm up nanotubes and then the target tissue. When the temperature in tumor tissue exceeds 316 K the necrosis of cancer cells may be observed. Several techniques can be used for Fe-CNTs synthesis. In our work, we use high-temperature methods where arc-discharge is applied. Low-temperature systems are microwave plasma with assisted chemical vapor deposition (MPCVD) and hybrid physical-chemical vapor deposition (HPCVD). In the arc discharge system, the plasma reactor works with a pressure of He up to 0,5 atm. The electric arc burns between two graphite rods. Vapors of carbon move from the anode, through a short arc column and forms CNTs which can be collected either from the reactor walls or cathode deposit. This method is suitable for the production of multi-wall and single-wall CNTs. A disadvantage of high-temperature methods is a low purification, short length, random size and multi-directional distribution. In MPCVD system plasma is generated in waveguide connected to the microwave generator. Then containing carbon and ferromagnetic elements plasma flux go to the quartz tube. The additional resistance heating can be applied to increase the reaction effectiveness and efficiency. CNTs nucleation occurs on the quartz tube walls. It is also possible to use substrates to improve carbon nanotubes growth. HPCVD system involves both chemical decomposition of carbon containing gases and vaporization of a solid or liquid source of catalyst. In this system, a tube furnace is applied. A mixture of working and carbon-containing gases go through the quartz tube placed inside the furnace. As a catalyst ferrocene vapors can be used. Fe-CNTs may be collected then either from the quartz tube walls or on the substrates. Low-temperature methods are characterized by higher purity product. Moreover, carbon nanotubes from tested CVD systems were partially filled with the iron. Regardless of the method of Fe-CNTs synthesis the final product always needs to be purified for applications in medicine. The simplest method of purification is an oxidation of the amorphous carbon. Carbon nanotubes dedicated for cancer cell thermal ablation need to be additionally treated by acids for defects amplification on the CNTs surface what facilitates biofunctionalization. Application of ferromagnetic nanotubes for cancer treatment is a promising method of fighting with cancer for the next decade. Acknowledgment: The research work has been financed from the budget of science as a research project No. PBS2/A5/31/2013

Keywords: arc discharge, cancer, carbon nanotubes, CVD, thermal ablation

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Authors: Abdullah Bal, Sevdenur Bal

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This paper purposes a new type of hardware application for training of cellular neural networks (CNN) using optical joint transform correlation (JTC) architecture for image feature extraction. CNNs require much more computation during the training stage compare to test process. Since optoelectronic hardware applications offer possibility of parallel high speed processing capability for 2D data processing applications, CNN training algorithm can be realized using Fourier optics technique. JTC employs lens and CCD cameras with laser beam that realize 2D matrix multiplication and summation in the light speed. Therefore, in the each iteration of training, JTC carries more computation burden inherently and the rest of mathematical computation realized digitally. The bipolar data is encoded by phase and summation of correlation operations is realized using multi-object input joint images. Overlapping properties of JTC are then utilized for summation of two cross-correlations which provide less computation possibility for training stage. Phase-only JTC does not require data rearrangement, electronic pre-calculation and strict system alignment. The proposed system can be incorporated simultaneously with various optical image processing or optical pattern recognition techniques just in the same optical system.

Keywords: CNN training, image processing, joint transform correlation, optoelectronic hardware

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Authors: Madhavi

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All linguistic units are context-dependent. They occur in particular settings, from which they derive much of their import, and are recognized by speakers as distinct entities only through a process of abstraction. Most of the words have several concepts associated with them and convey a number of meanings in different contexts in any language. For instance, there are different uses of the word good as an adjective from English. The adjective good expresses many senses like (1) ‘high quality of someone or something’ (2) ‘efficient’ (3) ‘virtuous’ (4) ‘reliable’ etc. These senses will be analyzed by using cognitive semantics framework. The context has the power to insulate one meaning from all the other meanings in communication. This paper will provide a cognitive semantic analysis. The basic tenet of cognitive semantics is the sense of a word is the way we conceptualize it. Our conceptualization is based on the physical experience we go through. Cognitive semantics tries to capture this conceptualization in terms of some categories like schema, frame, and domain. Cognitive semantics is a subfield of cognitive linguistics. Cognitive linguistics studies the language creation, learning, and usage by the reference to human cognition. The semantic structure is conceptual structure which is related to the concepts which are the elements of reason and constitute the meanings of words and linguistic expressions. Cognitive semantics studies how our mind works for the meaning of any word and how it perceives meaning from the environment through senses and works to map with the knowledge which already exists in our mind through experience. In the present paper, the senses are further classified into some categories.

Keywords: cognitive, contexts, semantics, senses

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Authors: Merry Pearl Rupinta, Rivika Alda

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Inclusive education provides the same opportunity for all students regardless of the difficulties they encounter. Teaching English to learners with special education needs (LSENs) is a significant factor for learners to cope with the academic demands in the regular class. However, these special education (SPED) teachers lack specialized training to teach specific skills in English. Using purposive sampling, this study explored the lived experience of nine SPED teachers handling English to learners with intellectual disabilities from the four divisions of Region 10. An interview schedule, validated by experts, was used in conducting the investigation, where a semi-structured one-on-one interview was employed. The data were analyzed using Smith's (2009) five-step data analysis. The study highlighted themes on challenges in teaching English, coping strategies, adjusted classroom management, and inclusivity. The results suggest that SPED teachers' experience teaching English is a continuous and indefinite loop that continues until the primary goal of mainstreaming LSENs into the regular class is achieved. This study recommends that policymakers and curriculum developers focus their efforts on professional development through a series of training on various strategies and approaches in teaching English that can help SPED teachers provide a more effective and efficient teaching-learning experience.

Keywords: English language teaching, inclusive education, intellectual disability, special education

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Authors: Zhenyu Zhang, Hsi-Hsien Wei

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Highway network systems play a vital role in disaster response for disaster-damaged areas. Damaged bridges in such network systems can impede disaster response by disrupting transportation of rescue teams or humanitarian supplies. Therefore, emergency inspection and repair of bridges to quickly collect damage information of bridges and recover the functionality of highway networks is of paramount importance to disaster response. A widely used measure of a network’s capability to recover from disasters is resilience. To enhance highway network resilience, plenty of studies have developed various repair scheduling methods for the prioritization of bridge-repair tasks. These methods assume that repair activities are performed after the damage to a highway network is fully understood via inspection, although inspecting all bridges in a regional highway network may take days, leading to the significant delay in repairing bridges. In reality, emergency repair activities can be commenced as soon as the damage data of some bridges that are crucial to emergency response are obtained. Given that emergency bridge inspection and repair (EBIR) activities are executed simultaneously in the response phase, the real-time interactions between these activities can occur – the blockage of highways due to repair activities can affect inspection routes which in turn have an impact on emergency repair scheduling by providing real-time information on bridge damages. However, the impact of such interactions on the optimal emergency inspection routes (EIR) and emergency repair schedules (ERS) has not been discussed in prior studies. To overcome the aforementioned deficiencies, this study develops a routing and scheduling model for EBIR while accounting for real-time inspection-repair interactions to maximize highway network resilience. A stochastic, time-dependent integer program is proposed for the complex and real-time interacting EBIR problem given multiple inspection and repair teams at locations as set post-disaster. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. Computational tests are performed using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that the simultaneous implementation of bridge inspection and repair activities can significantly improve the highway network resilience. Moreover, the deployment of inspection and repair teams should match each other, and the network resilience will not be improved once the unilateral increase in inspection teams or repair teams exceeds a certain level. This study contributes to both knowledge and practice. First, the developed mathematical model makes it possible for capturing the impact of real-time inspection-repair interactions on inspection routing and repair scheduling and efficiently deriving optimal EIR and ERS on a large and complex highway network. Moreover, this study contributes to the organizational dimension of highway network resilience by providing optimal strategies for highway bridge management. With the decision support tool, disaster managers are able to identify the most critical bridges for disaster management and make decisions on proper inspection and repair strategies to improve highway network resilience.

Keywords: disaster management, emergency bridge inspection and repair, highway network, resilience, uncertainty

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Authors: Yao-Hong Tsai

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Due to the sensor technology, video surveillance has become the main way for security control in every big city in the world. Surveillance is usually used by governments for intelligence gathering, the prevention of crime, the protection of a process, person, group or object, or the investigation of crime. Many surveillance systems based on computer vision technology have been developed in recent years. Moving target tracking is the most common task for Unmanned Aerial Vehicle (UAV) to find and track objects of interest in mobile aerial surveillance for civilian applications. The paper is focused on vision-based collision avoidance for UAVs by recurrent neural networks. First, images from cameras on UAV were fused based on deep convolutional neural network. Then, a recurrent neural network was constructed to obtain high-level image features for object tracking and extracting low-level image features for noise reducing. The system distributed the calculation of the whole system to local and cloud platform to efficiently perform object detection, tracking and collision avoidance based on multiple UAVs. The experiments on several challenging datasets showed that the proposed algorithm outperforms the state-of-the-art methods.

Keywords: unmanned aerial vehicle, object tracking, deep learning, collision avoidance

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Authors: Uvais Qidwai, Mohamed Shakir

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This paper presents an initial study related to the use of robotic toys as teaching and therapeutic aid tools for teachers and care-givers as well as parents of children with various levels of autism spectrum disorder (ASD). Some of the most common features related to the behavior of a child with ASD are his/her social isolation, living in their own world, not being physically active, and not willing to learn new things. While the teachers, parents, and all other related care-givers do their best to improve the condition of these kids, it is usually quite an uphill task. However, one remarkable observation that has been reported by several teachers dealing with ASD children is the fact that the same children do get attracted to toys with lights and sounds. Hence, this project targets the development/modifications of such existing toys into appropriate behavior training tools which the care-givers can use as they would desire. Initially, the remote control is in hand of the trainer, but after some time, the child is entrusted with the control of the robotic toy to test for the level of interest. It has been found during the course of this study that children with quite low learning activity got extremely interested in the robot and even advanced to controlling the robot with the Electromyography (EMG). It has been observed that the children did show some hesitation in the beginning 5 minutes of the very first sessions of such interaction but were very comfortable afterwards which has been considered as a very strong indicator of the potential of this technique in teaching and rehabilitation of children with ASD or similar brain disorders.

Keywords: Autism Spectrum Disorder (ASD), robotic toys, IR control, electromyography, LabVIEW based remote control

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Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

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In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: artificial neural network, Taguchi method, real estate valuation model, investors

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Authors: Lukman Omobola Adisa

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Spelling is rule bound in a written discourse. It, however, calls into question, when such convention is grossly contravened in a formal setting revered as citadel of learning, despite availability of computer spell-checker, human knowledge, and lexicon. The foregoing reveals the extent of decadence pervading education sector in Nigeria. It is on this premise that this study reviews the effect of spelling on communicative competence of the University of Ibadan Registry Staff. The theoretical framework basically evaluates diverse scholars’ views on communicative competence and how spelling influences the intended meaning of a word/ sentence as a result of undue infringement on grammatical (spelling) rule. Newsletter, bulletin, memo, and letter are four print materials purposively selected while the methodology adopted is content analysis. Similarly, five categories, though not limited to, through which spelling blunders are committed are considered: effect of spelling (omission, addition, and substitution); sound ( homophone); transposition (heading/body: content) and ambiguity (capitalisation, space, and acronym). Subsequently, the analyses, findings, and recommendations are equally looked into. Summarily, the study x-rays effective role(s) plays by spelling in enhancing communicative competence through appropriate usage of linguistic registers.

Keywords: communicative competence, content analysis, effect of spelling, linguistics registers

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Authors: Amna Khaliq

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This research project centers on Canadian business leaders’ phenomenological online education expansion by navigating the challenges faced by strategic leaders concerning the expansion of online education in the Canadian higher education sector from a business perspective. The study identifies the problems and opportunities of faculty members’ transition from traditional face-to-face to online instruction, particularly in the context of technology-enhanced learning (TEL), and their influence on the growth strategies of Canadian educational institutions. It explores strategic leaders’ approaches and the impact of emerging technologies to assist with developing and executing business strategies to expand online education in Canada. As online education has gained prominence in the country, this research addresses a relevant business problem for educational institutions. The research employs a phenomenological approach in the qualitative research design to conduct this investigation. The study interviews eighteen faculty members engaged in online education in Canada. The interview data is analyzed to answer the three research questions for strategic leaders to expand online education with higher education institutions in Canada. The recommendations include 1) data privacy, infrastructure, security, and technology, 2) support and training for student engagement, 3) accessibility and inclusion, and 4) collaboration among institutions associated with expanding online education.

Keywords: strategic leadership, Canada, education, technology

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Authors: Muhammad Hamza

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This research is based on the effect of self-questioning strategy on reading comprehension of second language learners at medium level. This research is conducted to find out the effects of self-questioning strategy and how self-questioning strategy helps English learners to improve their reading comprehension. In this research study the researcher has analyzed that how much self-questioning is effective in the field of learning second language and how much it helps second language learners to improve their reading comprehension. For this purpose, the researcher has studied different reading strategies, analyzed, collected data from certificate level class at NUML, Peshawar campus and then found out the effects of self-questioning strategy on reading comprehension of ESL learners. The researcher has randomly selected the participants from certificate class. The data was analyzed through pre-test and post-test and then in the final stage the results of both tests were compared. After the pre-test and post-test, the result of both pre-test and post-test indicated that if the learners start to use self-questioning strategy before reading a text, while reading a text and after reading a particular text there’ll be improvement in comprehension level of ESL learners. The present research has addressed the benefits of self-questioning strategy by taking two tests (pre and post-test).After the result of post-test it is revealed that the use of the self-questioning strategy has a significant effect on the readers’ comprehension thus, they can improve their reading comprehension by using self-questioning strategy.

Keywords: strategy, self-questioning, comprehension, intermediate level ESL learner

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Authors: Dolapo Adeyemo

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Technology can be designed specifically for geriatrics and persons with disabilities or ICT accessibility solutions. Both solutions stand to benefit from advances in Artificial intelligence, which are computer systems that perform tasks that require human intelligence. Tasks such as decision making, visual perception, speech recognition, and even language translation are useful in both situation and will provide significant benefits to people with temporarily or permanent disabilities. This research’s goal is to review innovations focused on the use of artificial intelligence that bridges the accessibility gap in technology from a user-centered perspective. A mixed method approach that utilized a comprehensive review of academic literature on the subject combined with semi structure interviews of users, developers, and technology product owners. The internet of things and artificial intelligence technology is creating new opportunities in the assistive technology space and proving accessibility to existing technology. Device now more adaptable to the needs of the user by learning the behavior of users as they interact with the internet. Accessibility to devices have witnessed significant enhancements that continue to benefit people with disabilities. Examples of other advances identified are prosthetic limbs like robotic arms supported by artificial intelligence, route planning software for the visually impaired, and decision support tools for people with disabilities and even clinicians that provide care.

Keywords: ICT, IOT, accessibility solutions, universal design

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Authors: T. L. Granzyk, S. Scarborough, J. DeCosmo

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The use of health-related or medical narratives has gained increasing anecdotal and research-based support as a successful device for changing health behavior and outcomes. These narratives, in the form of oral storytelling, short films, and educational documentaries, for example, are most effective when including empathetic characters that transport viewers into the story and command both their attention and emotional response. This case study outlines how and why one large health system created a short narrative film for their internal Sepsis Awareness campaign, which told the dramatic story of a patient recovering from a missed sepsis diagnosis, leaving her a quad-amputee. Results include positive global anecdotal response to the film from healthcare professionals and patients, as well as use of the film to support legislation, ultimately passed in favor of the formation of Sepsis Awareness Workgroups in Maryland. Authors conclude that narrative films can be used successfully to initiate healthcare legislation and to increase internal and external awareness of health-related areas in need of greater improvement and support. As such, healthcare leaders and stakeholders would benefit from learning how to intentionally create, cultivate, and curate narratives from within their own health systems that elicit an empathetic response.

Keywords: healthcare policy, healthcare narratives, sepsis awareness, short films

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Authors: M. Nikafrooz, J. Darsareh

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Due to the COVID-19 pandemic, its impacts on education all over the world and the problems arising from the use of traditional methods in education, it was necessary to apply alternative solutions to achieve educational goals. In this regard, electronic content production through screen recording and giving educational services in virtual classes became popular among many teachers. But the production of screen recorded videos involves special technical and educational considerations so that educators could be able to produce valuable and well-made videos by taking those considerations into account. The purpose of this study was to extract and find the technical and educational considerations of producing screen recorded videos to provide a useful and comprehensive guideline for e-content producers to enable them to produce high-quality educational videos. This study is fundamental research and data collection has been done using the Delphi method. In this research, an attempt has been made to provide the necessary criteria and considerations regarding the design and production of screen recorded videos by studying the literatures, identifying and analyzing learners' and teachers' needs and expectations, reviewing the previously produced videos. The results of these studies led to the finding and extracting 129 indicators in the form of 6 criteria. Such considerations are expected to reduce production and editing time, increase the technical and educational quality, and finally facilitating and enhancing the processes of teaching and learning.

Keywords: e-content, screen recorded videos, screen recording software, technical and pedagogical considerations

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Authors: Laila Alkhayat

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In this study, the researcher explored the positive and negative effects of children watching YouTube on changing social values from the perspective of parents in Kuwait. This study also explored whether any correlation exists between changed values from watching YouTube and the following variables: relationship with a child, social situation, school level, gender, and age. The researcher collected data from 286 questionnaires distributed randomly to parents in Kuwait. The results of the study show that parents face many disadvantages when dealing with children watching YouTube, such as children spending too much time in front of screens, inability to organize bedtime, and children’s social isolation. However, the researcher found some positives come from watching YouTube, such as learning new information, enabling children to search for new information, and introducing children to the culture of their society and other cultures around them. Moreover, this study found that boys are more likely to have negative viewing habits than girls. Given the results, this study shows that the biggest impact on social values from children watching YouTube is that they are preoccupied with watching YouTube and they waste time, which makes them feel disturbed, and this affects the value of time management and delays children’s sleeping times. This study concludes that watching YouTube simultaneously has negative and positive effects on changing social values, but it plays a negative role in changing social values of children from the parents’ perspective.

Keywords: YouTube, children, social value, social media effects

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Authors: Pierobon Enrico, Missiaggia Marta, Castelluzzo Michele, Tommasino Francesco, Ricci Leonardo, Scifoni Emanuele, Vincezo Monaco, Boscardin Maurizio, La Tessa Chiara

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Clinical outcomes collected over the past three decades have suggested that ion therapy has the potential to be a treatment modality superior to conventional radiation for several types of cancer, including recurrences, as well as for other diseases. Although the results have been encouraging, numerous treatment uncertainties remain a major obstacle to the full exploitation of particle radiotherapy. To overcome therapy uncertainties optimizing treatment outcome, the best possible radiation quality description is of paramount importance linking radiation physical dose to biological effects. Microdosimetry was developed as a tool to improve the description of radiation quality. By recording the energy deposition at the micrometric scale (the typical size of a cell nucleus), this approach takes into account the non-deterministic nature of atomic and nuclear processes and creates a direct link between the dose deposited by radiation and the biological effect induced. Microdosimeters measure the spectrum of lineal energy y, defined as the energy deposition in the detector divided by most probable track length travelled by radiation. The latter is provided by the so-called “Mean Chord Length” (MCL) approximation, and it is related to the detector geometry. To improve the characterization of the radiation field quality, we define a new quantity replacing the MCL with the actual particle track length inside the microdosimeter. In order to measure this new quantity, we propose a two-stage detector consisting of a commercial Tissue Equivalent Proportional Counter (TEPC) and 4 layers of Low Gain Avalanche Detectors (LGADs) strips. The TEPC detector records the energy deposition in a region equivalent to 2 um of tissue, while the LGADs are very suitable for particle tracking because of the thickness thinnable down to tens of micrometers and fast response to ionizing radiation. The concept of HDM has been investigated and validated with Monte Carlo simulations. Currently, a dedicated readout is under development. This two stages detector will require two different systems to join complementary information for each event: energy deposition in the TEPC and respective track length recorded by LGADs tracker. This challenge is being addressed by implementing SoC (System on Chip) technology, relying on Field Programmable Gated Arrays (FPGAs) based on the Zynq architecture. TEPC readout consists of three different signal amplification legs and is carried out thanks to 3 ADCs mounted on a FPGA board. LGADs activated strip signal is processed thanks to dedicated chips, and finally, the activated strip is stored relying again on FPGA-based solutions. In this work, we will provide a detailed description of HDM geometry and the SoC solutions that we are implementing for the readout.

Keywords: particle tracking, ion therapy, low gain avalanche diode, tissue equivalent proportional counter, microdosimetry

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Authors: Y. Kamarulzaman, A. Madun, F. D. Yusop, N. Abdullah, N. K. Hoong

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In 2011, the Malaysian Government has initiated a nationwide project called 1BestariNet which will adopt the using of technology in teaching and learning, resulting in the construction of telecommunication towers inside the public schools’ premise. Using qualitative approach, this study investigated public perception of risks associated with the project, particularly the telecommunication towers. Data collection involved observation and in-depth interviews with 22 individuals consist of a segment of public that was anxious about the risks of radio frequency electromagnetic field (RFEMF) which include two employees of telecommunication companies (telcos) and five employees of Government agencies. Observation of the location of the towers at 10 public schools, a public forum, and media reports provide valuable information in our analysis. The study finds that the main concern is related to the health risks. This study also shows that it is not easy for the Government to manage public perception mainly because it involves public trust. We find that risk perception is related with public trust, as well as the perceived benefits and level of knowledge. Efficient communication and continuous engagement with the local communities help to build and maintain public trust, reduce public fear and anxiety, hence mitigating the risk perception among the public.

Keywords: risk perception, risk communication, trust, telecommunication tower, radio frequency electromagnetic field (RFEMF)

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Authors: E. Cascarosa-Salillas, J. Pozuelo-Muñoz, C. Rodríguez-Casals, A. de Echave

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This study focuses on improving the understanding of the capillarity phenomenon among Primary and Secondary Education students. Despite being a common concept in daily life and covered in various subjects, students’ comprehension remains limited. This work explores inquiry-based teaching methods to build a conceptual foundation of capillarity by examining the forces involved. The study adopts an inquiry-based teaching approach supported by research emphasizing the importance of modeling in science education. Scientific modeling aids students in applying knowledge across varied contexts and developing systemic thinking, allowing them to construct scientific models applicable to everyday situations. This methodology fosters the development of scientific competencies such as observation, hypothesis formulation, and communication. The research was structured as a case study with activities designed for Spanish Primary and Secondary Education students aged 9 to 13. The process included curriculum analysis, the design of an activity sequence, and its implementation in classrooms. Implementation began with questions that students needed to resolve using available materials, encouraging observation, experimentation, and the re-contextualization of activities to everyday phenomena where capillarity is observed. Data collection tools included audio and video recordings of the sessions, which were transcribed and analyzed alongside the students' written work. Students' drawings on capillarity were also collected and categorized. Qualitative analyses of the activities showed that, through inquiry, students managed to construct various models of capillarity, reflecting an improved understanding of the phenomenon. Initial activities allowed students to express prior ideas and formulate hypotheses, which were then refined and expanded in subsequent sessions. The generalization and use of graphical representations of their ideas on capillarity, analyzed alongside their written work, enabled the categorization of capillarity models: Intuitive Model: A visual and straightforward representation without explanations of how or why it occurs. Simple symbolic elements, such as arrows to indicate water rising, are used without detailed or causal understanding. It reflects an initial, immediate perception of the phenomenon, interpreted as something that happens "on its own" without delving into the microscopic level. Explanatory Intuitive Model: Students begin to incorporate causal explanations, though still limited and without complete scientific accuracy. They represent the role of materials and use basic terms such as ‘absorption’ or ‘attraction’ to describe the rise of water. This model shows a more complex understanding where the phenomenon is not only observed but also partially explained in terms of interaction, though without microscopic detail. School Scientific Model: This model reflects a more advanced and detailed understanding. Students represent the phenomenon using specific scientific concepts like ‘surface tension,’ cohesion,’ and ‘adhesion,’ including structured explanations connecting microscopic and macroscopic levels. At this level, students model the phenomenon as a coherent system, demonstrating how various forces or properties interact in the capillarity process, with representations on a microscopic level. The study demonstrated that the capillarity phenomenon can be effectively approached in class through the experimental observation of everyday phenomena, explained through guided inquiry learning. The methodology facilitated students’ construction of capillarity models and served to analyze an interaction phenomenon of different forces occurring at the microscopic level.

Keywords: capillarity, inquiry-based learning, scientific modeling, primary and secondary education, conceptual understanding, Drawing analysis.

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Authors: Jiaqi Dong, Qing-Hua Qin, Yi Xiao

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Some of the most fundamental challenges of elastic metamaterials (EMMs) optimization can be attributed to the high consumption of computational power resulted from finite element analysis (FEA) simulations that render the optimization process inefficient. Furthermore, due to the inherent mesh dependence of FEA, minuscule geometry features, which often emerge during the later stages of optimization, induce very fine elements, resulting in enormously high time consumption, particularly when repetitive solutions are needed for computing the objective function. In this study, a surrogate modelling algorithm is developed to reduce computational time in structural optimization of EMMs. The surrogate model is constructed based on a multilayer feedforward artificial neural network (ANN) architecture, trained with prepopulated eigenfrequency data prepopulated from FEA simulation and optimized through regime selection with genetic algorithm (GA) to improve its accuracy in predicting the location and width of the primary elastic band gap. With the optimized ANN surrogate at the core, a Nelder-Mead (NM) algorithm is established and its performance inspected in comparison to the FEA solution. The ANNNM model shows remarkable accuracy in predicting the band gap width and a reduction of time consumption by 47%.

Keywords: artificial neural network, machine learning, mechanical metamaterials, Nelder-Mead optimization

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Authors: Jurica Hižak

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Getting to know the agents, i.e., identifying the free riders in a population, can be considered one of the main challenges in establishing cooperation. An ordinary memory-one agent such as Tit-for-tat may learn “who is who” in the population through direct interactions. Past experiences serve them as a landmark to know with whom to cooperate and against whom to retaliate in the next encounter. However, this kind of learning is risky and expensive. A cheaper and less painful way to detect free riders may be achieved by gossiping. For this reason, as part of this research, a special type of Tit-for-tat agent was designed – a “Gossip-Tit-for-tat” agent that can share data with other agents of its kind. The performances of both strategies, ordinary Tit-for-tat and Gossip-Tit-for-tat, against Always-defect have been compared in the finite-game framework of the Iterated Prisoner’s Dilemma via the Moran process. Agents were able to move in a random-walk fashion, and they were programmed to play Prisoner’s Dilemma each time they met. Moreover, at each step, one randomly selected individual was eliminated, and one individual was reproduced in accordance with the Moran process of selection. In this way, the size of the population always remained the same. Agents were selected for reproduction via the roulette wheel rule, i.e., proportionally to the relative fitness of the strategy. The absorption probability was calculated after the population had been absorbed completely by cooperators, which means that all the states have been occupied and all of the transition probabilities have been determined. It was shown that gossip increases absorption probabilities and therefore enhances the evolution of cooperation in the population.

Keywords: cooperation, gossip, indirect reciprocity, Moran process, prisoner’s dilemma, tit-for-tat

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Authors: Elvin Karaaslan Klose

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In the field of Visual Culture, Art Education students are given the opportunity to discuss topics of interest that are closer to their own social life and media consumption habits. In contrast to the established corpus of literature and sources about Art History, educators are challenged to find topics and examples from Popular Culture and Contemporary Art that provide familiarity, depth and inspiration for students’ future practice, both as educators as well as artists. In order to establish a welcoming and fruitful discussion environment at the beginning of an introductory Visual Culture Education course with fourth year Art Education students, the class watched and subsequently discussed the movie “Vantage Point”. Using the descriptive method and content analysis; video recordings, discussion transcripts and learning diaries were summarized to highlight students’ critical points of view towards commonly experienced but rarely reflected on topics of Popular and Visual Culture. As an introduction into more theory-based forms of discussion, watching and intensely discussing a movie has proven useful by proving a combination of a familiar media type with an unfamiliar educational context. Resulting areas of interest have served as a starting point for later research, discussion and artistic production in the scope of an introductory Visual Culture Education course.

Keywords: visual culture, critical pedagogy, media literacy, art education

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.

Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation

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Authors: S. Sharan Sundar, Nithish B. Moudhgalya, Nidhi Bhandari, Vineeth Vijayaraghavan

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Automatic Short Answer Grading is one of the prime applications of artificial intelligence in education. Several approaches involving the utilization of selective handcrafted features, graphical matching techniques, concept identification and mapping, complex deep frameworks, sentence embeddings, etc. have been explored over the years. However, keeping in mind the real-world application of the task, these solutions present a slight overhead in terms of computations and resources in achieving high performances. In this work, a simple and effective solution making use of elemental features based on statistical, linguistic properties, and word-based similarity measures in conjunction with tree-based classifiers and regressors is proposed. The results for classification tasks show improvements ranging from 1%-30%, while the regression task shows a stark improvement of 35%. The authors attribute these improvements to the addition of multiple similarity scores to provide ensemble of scoring criteria to the models. The authors also believe the work could reinstate that classical natural language processing techniques and simple machine learning models can be used to achieve high results for short answer grading.

Keywords: artificial intelligence, intelligent systems, natural language processing, text mining

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Authors: Li-Ju Chen, Hsiang-Lin Chan, Hsin-Yi Kathy Cheng, Hui-Ju Chen

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Stereotype behavior is one of the maladaptive syndromes of the individuals with autism. Most of the previous researches focused on the stereotype behavior with stimulating type, while less on the stereotype behavior about cognition (This research names it cognitive stereotype behavior; CSB). This research explored CSB and the rationality to explain CSB with imprinting phenomenon. After excluding the samples without CSB described, the data that came from 271 individuals with autism were recruited and analyzed with quantitative and qualitative analyses. This research discovers that : (1) Most of the individuals with autism originally came out CSB at 3 years old and more than a half of them appeared before 4 years old; The average age which firstly came out CSB was 6.10 years old, the average time insisting or ossifying CSB was 31.71 minutes each time and the average longest time which they last was 358.35 minutes (5.97 hours). (2) CSB demonstrates various aspects, this research classified them into 4 fields with 26 categories. They were categorized into sudden CSB or habitual CSB by imprinting performance. (3) Most of the autism commented that their CSBs were not necessary but they could not control them well. One-third of them appeared CSB suddenly and the first occurrence accompanied a strong emotional or behavioral response. (4) Whether respondent is the person with autism himself/herself or not was the critical element: on the awareness of the severity degree, disturbance degree, and the emotional /behavioral intensity at the first-time CSB happened. This study concludes imprinting could reasonably explain the phenomenon CSB forms. There are implications leading the individuals with autism and their family to develop coping strategies to promote individuals with autism having a better learning accomplishment and life quality in their future.

Keywords: autism, cognitive stereotype behavior, constructivism, imprinting, stereotype

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Authors: C. Fernanda da S. Sampaio, M. Gabriela Sadith Perez Paredes, V. Antonio de O. Martins

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Today the transport sector is undergoing a revolution, with the rise of Advanced Driver Assistance Systems (ADAS), industry and society itself will undergo a major transformation. However, the technological development of these applications is a challenge that requires new techniques and great machine learning and artificial intelligence. The study proposes to develop a vehicular perception system called Veibra, which consists of two front cameras for day/night viewing and an embedded device capable of working with Yolov2 image processing algorithms with low computational cost. The strategic version for the market is to assist the driver on the road with the detection of day/night objects, such as road signs, pedestrians, and animals that will be viewed through the screen of the phone or tablet through an application. The system has the ability to perform real-time driver detection and recognition to identify muscle movements and pupils to determine if the driver is tired or inattentive, analyzing the student's characteristic change and following the subtle movements of the whole face and issuing alerts through beta waves to ensure the concentration and attention of the driver. The system will also be able to perform tracking and monitoring through GSM (Global System for Mobile Communications) technology and the cameras installed in the vehicle.

Keywords: advanced driver assistance systems, tracking, traffic signal detection, vehicle perception system

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Authors: J. Jebunnesa, Y. Budd, T. Mason

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COVID-19 changed the pedagogical expectations of early childhood education as many teachers across Australia had to quickly adapt to new teaching practices such as remote teaching. An important factor in the successful implementation of any new teaching and learning approach is teacher preparation, however, due to the pandemic, the transformation to remote teaching was immediate. A timely question to be asked is how early childhood teachers managed the transition from face-to-face teaching to remote teaching and what was learned through this time. This study explores the experiences of early childhood educators in Australia during COVID-19 lockdowns. Data were collected from an online survey conducted through the official Facebook forum of “Early Childhood Education and Care Australia,” and a constructivist grounded theory methodology was used to analyse the data. Initial research results suggest changing expectations of teachers’ roles and responsibilities during the lockdown, with a significant category related to transitioning teacher identities emerging. The concept of transitioning represents the shift from the role of early childhood educator to educational innovator, essential worker, social worker, and health officer. The findings illustrate the complexity of early childhood educators’ roles during the pandemic.

Keywords: changing role of teachers, constructivist grounded theory, lessons learned, teaching during COVID-19

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