Search results for: learning behaviour

Authors: Mohinder Kumar

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Sports are considered as the very prominent social institution in almost every society because it reflects the mores, values, and general culture of a society. Sports activity tend to pave the foundation for learning acceptable values and beliefs and for acquiring desirable character traits such as self-discipline, sportsmanship, and an appreciation for hard work, fairness, self-respect, leadership, followership, justice, perseverance, competition, and goal attainment. The present study focuses on ideal ways of socializing youngsters into sports. Influences of some socializing agents (e.g. family, school, community) are reviewed and suggestions made as to how these socializing agents can be oriented and made effective in carrying out functional processes toward target ends.

Keywords: sports, socializing, family, community, society

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Authors: Matthew Conner, Leah Plocharczyk

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This study examines the role of academic libraries in support of the intellectually disabled (ID) in post-secondary education. With the growing public awareness of the ID, there has been recognition of their need for post-secondary educational opportunities. This was an unforeseen result for a population that has been associated with elementary levels of education, yet the reasons are compelling. After aging out of the school system, the ID need and deserve educational and social support as much as anyone. Moreover, the commitment to diversity in higher education rings hollow if this group is excluded. Yet, challenges remain to integrating the ID into a college curriculum. This presentation focuses on the role of academic libraries. Neglecting this vital resource for the support of the ID is not to be thought of, yet the library’s contribution is not clear. Library collections presume reading ability and libraries already struggle to meet their traditional goals with the resources available. This presentation examines how academic libraries can support post-secondary ID. For context, the presentation first examines the state of post-secondary education for the ID with an analysis of data on the United States compiled by the ThinkCollege! Project. Geographic Information Systems (GIS) and statistical analysis will show regional and methodological trends in post-secondary support of the ID which currently lack any significant involvement by college libraries. Then, the presentation analyzes a case study of a book club at the Florida Atlantic University (FAU) libraries which has run for several years. Issues such as the selection of books, effective pedagogies, and evaluation procedures will be examined. The study has found that the instruction pedagogies used by libraries can be extended through concepts of Universal Learning Design (ULD) to effectively engage the ID. In particular, student-centered, participatory methodologies that accommodate different learning styles have proven to be especially useful. The choice of text is complex and determined not only by reading ability but familiarity of subject and features of the ID’s developmental trajectory. The selection of text is not only a necessity but also promises to give insight into the ID. Assessment remains a complex and unresolved subject, but the voluntary, sustained, and enthusiastic attendance of the ID is an undeniable indicator. The study finds that, through the traditional library vehicle of the book club, academic libraries can support ID students through training in both reading and socialization, two major goals of their post-secondary education.

Keywords: academic libraries, intellectual disability, literacy, post-secondary education

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Authors: J. Ritonja, B. Grcar

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For the synchronous generator simulation and analysis and for the power system stabilizer design and synthesis a mathematical model of synchronous generator is needed. The model has to accurately describe dynamics of oscillations, while at the same time has to be transparent enough for an analysis and sufficiently simplified for design of control system. To study the oscillations of the synchronous generator against to the rest of the power system, the model of the synchronous machine connected to an infinite bus through a transmission line having resistance and inductance is needed. In this paper, the linearized reduced order dynamic model of the synchronous generator connected to the infinite bus is presented and analysed in details. This model accurately describes dynamics of the synchronous generator only in a small vicinity of an equilibrium state. With the digression from the selected equilibrium point the accuracy of this model is decreasing considerably. In this paper, the equations’ descriptions and the parameters’ determinations for the linearized reduced order mathematical model of the synchronous generator are explained and summarized and represent the useful origin for works in the areas of synchronous generators’ dynamic behaviour analysis and synchronous generator’s control systems design and synthesis. The main contribution of this paper represents the detailed analysis of the accuracy of the linearized reduced order dynamic model in the entire synchronous generator’s operating range. Borders of the areas where the linearized reduced order mathematical model represents accurate description of the synchronous generator’s dynamics are determined with the systemic numerical analysis. The thorough eigenvalue analysis of the linearized models in the entire operating range is performed. In the paper, the parameters of the linearized reduced order dynamic model of the laboratory salient poles synchronous generator were determined and used for the analysis. The theoretical conclusions were confirmed with the agreement of experimental and simulation results.

Keywords: eigenvalue analysis, mathematical model, power system stability, synchronous generator

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Authors: Lucy H. Kaiser, Kate Boersen

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Kura Kaupapa Māori (kura) and bilingual schools are primary schools in Aotearoa/New Zealand which operate fully or partially under Māori custom and have curricula developed to include Te Reo Māori and Tikanga Māori (Māori language and cultural practices). These schools were established to support Māori children and their families through reinforcing cultural identity by enabling Māori language and culture to flourish in the field of education. Māori kaupapa (values), Mātauranga Māori (Māori knowledge) and Te Reo are crucial considerations for the development of educational resources developed for kura, bilingual and mainstream schools. The inclusion of hazard risk in education has become an important issue in New Zealand due to the vulnerability of communities to a plethora of different hazards. Māori have an extensive knowledge of their local area and the history of hazards which is often not appropriately recognised within mainstream hazard education resources. Researchers from the Joint Centre for Disaster Research, Massey University and East Coast LAB (Life at the Boundary) in Napier were funded to collaboratively develop a toolkit of tsunami risk reduction activities with schools located in Hawke’s Bay’s tsunami evacuation zones. A Māori-led bicultural approach to developing and running the education activities was taken, focusing on creating culturally and locally relevant materials for students and schools as well as giving students a proactive role in making their communities better prepared for a tsunami event. The community-based participatory research is Māori-centred, framed by qualitative and Kaupapa Maori research methodologies and utilizes a range of data collection methods including interviews, focus groups and surveys. Māori participants, stakeholders and the researchers collaborated through the duration of the project to ensure the programme would align with the wider school curricula and kaupapa values. The education programme applied a tuakana/teina, Māori teaching and learning approach in which high school aged students (tuakana) developed tsunami preparedness activities to run with primary school students (teina). At the end of the education programme, high school students were asked to reflect on their participation, what they had learned and what they had enjoyed during the activities. This paper draws on lessons learned throughout this research project. As an exemplar, retaining a bicultural and bilingual perspective resulted in a more inclusive project as there was variability across the students’ levels of confidence using Te Reo and Māori knowledge and cultural frameworks. Providing a range of different learning and experiential activities including waiata (Māori songs), pūrākau (traditional stories) and games was important to ensure students had the opportunity to participate and contribute using a range of different approaches that were appropriate to their individual learning needs. Inclusion of teachers in facilitation also proved beneficial in assisting classroom behavioral management. Lessons were framed by the tikanga and kawa (protocols) of the school to maintain cultural safety for the researchers and the students. Finally, the tuakana/teina component of the education activities became the crux of the programme, demonstrating a path for Rangatahi to support their whānau and communities through facilitating disaster preparedness, risk reduction and resilience.

Keywords: school safety, indigenous, disaster preparedness, children, education, tsunami

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Authors: Gabrielle Robertson, Matthew Downs, Joseph Dagher

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Iron deposition in the brain has been linked with a host of neurological disorders such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. While some treatment options exist, there are no objective measurement tools that allow for the monitoring of iron levels in the brain in vivo. An emerging Magnetic Resonance Imaging (MRI) method has been recently proposed to deduce iron concentration through quantitative measurement of magnetic susceptibility. This is a multi-step process that involves repeated modeling of physical processes via approximate numerical solutions. For example, the last two steps of this Quantitative Susceptibility Mapping (QSM) method involve I) mapping magnetic field into magnetic susceptibility and II) mapping magnetic susceptibility into iron concentration. Process I involves solving an ill-posed inverse problem by using regularization via injection of prior belief. The end result from Process II highly depends on the model used to describe the molecular content of each voxel (type of iron, water fraction, etc.) Due to these factors, the accuracy and repeatability of QSM have been an active area of research in the MRI and medical imaging community. This work aims to estimate iron concentration in the brain via a single step. A synthetic numerical model of the human head was created by automatically and manually segmenting the human head on a high-resolution grid (640x640x640, 0.4mm³) yielding detailed structures such as microvasculature and subcortical regions as well as bone, soft tissue, Cerebral Spinal Fluid, sinuses, arteries, and eyes. Each segmented region was then assigned tissue properties such as relaxation rates, proton density, electromagnetic tissue properties and iron concentration. These tissue property values were randomly selected from a Probability Distribution Function derived from a thorough literature review. In addition to having unique tissue property values, different synthetic head realizations also possess unique structural geometry created by morphing the boundary regions of different areas within normal physical constraints. This model of the human brain is then used to create synthetic MRI measurements. This is repeated thousands of times, for different head shapes, volume, tissue properties and noise realizations. Collectively, this constitutes a training-set that is similar to in vivo data, but larger than datasets available from clinical measurements. This 3D convolutional U-Net neural network architecture was used to train data-driven Deep Learning models to solve for iron concentrations from raw MRI measurements. The performance was then tested on both synthetic data not used in training as well as real in vivo data. Results showed that the model trained on synthetic MRI measurements is able to directly learn iron concentrations in areas of interest more effectively than other existing QSM reconstruction methods. For comparison, models trained on random geometric shapes (as proposed in the Deep QSM method) are less effective than models trained on realistic synthetic head models. Such an accurate method for the quantitative measurement of iron deposits in the brain would be of important value in clinical studies aiming to understand the role of iron in neurological disease.

Keywords: magnetic resonance imaging, MRI, iron deposition, machine learning, quantitative susceptibility mapping

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Authors: M. Mirza Y. Harahap

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This paper explores the interiority of children’s territorialisation in domestic space context by looking at their affective relations with their surroundings. Examining its spatiality, the research focuses on the interactions that developed between the children and the things which exist in their house, specifically those which left traces, indicating the very arena of their territory. As early learners, the children whose mind and body are still in the development stage are hypothetically distinct in the way they territorialise the space. Rule, common sense and other form of common acceptances among the adults might not be relevant with their way on territorialising the space. Unpredictability-ness, inappropriateness, and unimaginableness hypothetically characterise their unique endeavour when territorialising the space. The purpose might even be insignificant, expressing their very development which unrestricted. This indicates how the interiority of children’s territorialisation in a domestic space context actually is. It would also implicate on a new way of seeing territory since territorialisation act has natural purpose: to aim the space and regard them as his/her own. Aiming to disclose the above territorialisation characteristics, this paper addresses a qualitative study which covers a comprehensive analysis as follow: 1) Collecting various territorial traces left from the children activities within their respective houses. Further within this stage, the data is categorised based on the territorial strategy and tactic. This stage would particularly result in the overall map of the children’s territorial interiority which expresses its focuses, range and ways; 2) Examining the interactions occurred between the children and the spatial elements within the house. Stressing on the affective relations, this stage revealed the immaterial aspect of the children’s territorialisation, thus disclosed the unseen spatial aspect of territorialisation; and 3) Synthesising the previous two stages. Correlating the results from the two stages would then help us to understand the children’s unpredictable, inappropriate and unimaginable territorial interiority. This would also help us to justify how the children learn the space through territorialisation act, its importance and its position in interiority conception. The discussed relation between the children and the houses that cover both its physical and imaginary entity as part of their overall dwelling space would also help us to have a better understanding towards specific spatial elements which are significant and undeniably important for children’s spatial learning process. Particularly for this last finding, it would also help us to determine what kind of spatial elements which are necessary to be existed in a house, thus help for design development purpose. Overall, the study in this paper would help us to broaden our mindset regarding the territory, dwelling, interiority and the overall interior architecture conception, promising a chance for further research within interior architecture field.

Keywords: children, interiority, relation, territory

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Authors: Merrylord Harb-Azar

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Traditionally, PTSD treatment has involved trauma-focused cognitive behaviour therapy (TF CBT) to consolidate traumatic memories. A piloted integrated treatment of TF CBT and eye movement desensitisation reprocessing therapy (EMDR) of eight phases will fasten the rate memory is being consolidated and enhance cognitive functioning in patients with PTSD. Patients spend a considerable amount of time in treatment managing their traumas experienced firsthand, or from aversive details ranging from war, assaults, accidents, abuse, hostage related, riots, or natural disasters. The time spent in treatment or as inpatient affects overall quality of life, relationships, cognitive functioning, and overall sense of identity. EMDR is being offered twice a week in conjunction with the standard prolonged exposure as an inpatient in a private hospital. Prolonged exposure for up to 5 hours per day elicits the affect response required for EMDR sessions in the afternoon to unlock unprocessed memories and facilitate consolidation in the amygdala and hippocampus. Results are indicating faster consolidation of memories, reduction in symptoms in a shorter period of time, reduction in admission time, which is enhancing the quality of life and relationships, and improved cognition. The impact of events scale (IES) results demonstrate a significant reduction in symptoms, trauma symptoms inventory (TSI), and posttraumatic stressor disorder check list (PCL) that demonstrates large effect sizes to date. An integrated treatment approach for PTSD achieves a faster resolution of memories, improves cognition, and reduces the amount of time spent in therapy.

Keywords: EMDR enhances cognitive functioning, faster consolidation of trauma memory, integrated treatment of TF CBT and EMDR, reduction in inpatient admission time

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Authors: Amad Nasseef, Layan Zugail, Joud Musalli, Layan Shaikan

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Technology has become an essential part of our lives. We have also witnessed the significant emergence of artificial intelligence in so many areas. Throughout this research paper, the following will be discussed: an introduction on AI and Socratic application, we also did an overview on the application’s background and other similar applications, as for the methodology, we conducted a survey to collect results on users experience in using the Socratic application. The results of the survey strongly supported the usefulness and interest of users in the Socratic application. Finally, we concluded that Socratic is a meaningful tool for learning purposes due to it being supported by artificial intelligence, which made the application easy to use and familiar to users to deal with through a click of a button.

Keywords: Socratic, artificial intelligence, application, features

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Authors: Kevin Moustapha

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Psychopathy is perceived today as being «the most important concept in the criminal justice system» and as «the most important legal notion of the early 21 th century». The explosion of research related to psychopathy seems to perfectly illustrate this trend. Traditionally, many studies tend to focus on links between insanity defense and psychopathy. That is why our purpose in this article is to analyze psychopathic disorders in the scope of judges sentencing in Canada. Indeed, in every Canadian case related to dangerous offenders, judges must balance between fairness and protection of the individuals rights of the accused and protection of society from dangerous predators who may commit future acts of physical or sexual violence. Increasingly, psychopathic disorders are taking an important part in judge sentencing, especially in Canada. This phenomenon can be illustrated by the high proportion of psychopath offenders incarcerated in North American prisons. Many decisions in Canadians courtrooms seem to point out that psychopathy is often used as a strong argument by the judges to preserve public safety. The fact that psychopathy is often associated with violence, recklessness and recidivism, it could explain why many judges consider psychopathic disorders as an aggravating factor. Generally, the judge reasoning is based on article 753 of Canadian Criminal Code related to dangerous offenders, which is used for individuals who show a pattern of repetitive and persistent aggressive behaviour. However, with cognitive neurosciences, the psychopath’s situation in courtrooms would probably change. Cerebral imaging and news data provided by the neurosciences show that emotional and volitional functions in psychopath’s brains are impaired. Understanding these new issues could enable some judges to recognize psychopathic disorders as a mitigating factor. Two important questions ought to be raised in this article: can exploring psychopaths ‘brains really change the judge sentencing in Canadian courtrooms? If yes, can judges consider psychopathy more as a mitigating factor than an aggravating factor?

Keywords: criminal law, judges sentencing, neurosciences, psychopathy

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Authors: Ameer A. Jebur, William Atherton, Rafid M. Alkhaddar, Edward Loffill

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Superstructures like offshore platforms, tall buildings, transition towers, skyscrapers and bridges are normally designed to resist compression, uplift and lateral forces from wind waves, negative skin friction, ship impact and other applied loads. Better understanding and the precise simulation of the response of batter piles under the action of independent uplift loads is a vital topic and an area of active research in the field of geotechnical engineering. This paper investigates the use of finite element code (FEC) to examine the behaviour of model batter piles penetrated in dense sand, subjected to pull-out pressure by means of numerical modelling. The concept of the Winkler Model (beam on elastic foundation) has been used in which the interaction between the pile embedded depth and adjacent soil in the bearing zone is simulated by nonlinear p-y curves. The analysis was conducted on different pile slenderness ratios (lc⁄d) ranging from 7.5, 15.22 and 30 respectively. In addition, the optimum batter angle for a model steel pile penetrated in dense sand has been chosen to be 20° as this is the best angle for this simulation as demonstrated by other researcher published in literature. In this numerical analysis, the soil response is idealized as elasto-plastic and the model piles are described as elastic materials for the purpose of simulation. The results revealed that the applied loads affect the pullout pile capacity as well as the lateral pile response for dense sand together with varying shear strength parameters linked to the pile critical depth. Furthermore, the pile pull-out capacity increases with increasing the pile aspect ratios.

Keywords: slenderness ratio, soil-pile interaction, winkler model (beam on elastic foundation), pull-out capacity

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Authors: Luisa Mesquita Oliveira Ribeiro, Alexei Manso Correa Machado

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Handwritten signature is a unique form for recognizing an individual, used to discern documents, carry out investigations in the criminal, legal, banking areas and other applications. Signature verification is based on large amounts of biometric data, as they are simple and easy to acquire, among other characteristics. Given this scenario, signature forgery is a worldwide recurring problem and fast and precise techniques are needed to prevent crimes of this nature from occurring. This article carried out a study on the efficiency of the Capsule Network in analyzing and recognizing signatures. The chosen architecture achieved an accuracy of 98.11% and 80.15% for the CEDAR and GPDS databases, respectively.

Keywords: biometrics, deep learning, handwriting, signature forgery

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Authors: Estelle Ardanouy, Helene Delage, Pascal Zesiger

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Morphological awareness contributes to the acquisition of reading and spelling in typical learners as well as in children with learning disorders. Indeed, the acquisition of phoneme-grapheme correspondences is not sufficient to master spelling, especially in inconsistent orthographic systems such as English or French. Several meta-analyses show the benefit of explicit training in derivational morphology on reading and spelling in old children (who have already learned the main grapheme-phoneme correspondences), but highlight the lack of studies with younger children, particularly in French. In this study, we chose to focus on the efficiency of an intensive training in derivational morphology on spelling skills in French-speaking four-graders (9-10 years of age). The training consisted of 1) learning how to divide words into morphemes (ex: para/pente in French, paraglider in English), as well as 2) working on the meaning of affixes in relation to existing words (ex: para/pente: to protect against – para - the slope -pente). One group of pupils (N = 37, M age = 9.5) received this experimental group training in morphology while an alternative training group (N = 34, M age = 9.6) received a visuo-semantic training based on visual cues to memorize the spelling difficulties of complex words (such as the doubling of “r” in “verre” in French -or "glass" in English-which are represented by the drawing of two glasses). Both trainings lasted a total of 15 hours at a rate of four 45 minutes sessions per week, resulting in five weeks of training in the school setting. Our preliminary results show a significant improvement in the experimental group in the spelling of affixes on the trained (p < 0.001) and untrained word lists (p <0.001), but also in the root of words on the trained (p <0.001) and untrained word lists group (p <0.001). The training effect is also present on both trained and untrained morphologically composed words. By contrast, the alternative training group shows no progress on these previous measures (p >0.15). Further analyses testing the effects of both trainings on other measures such as morphological awareness and reading of morphologically compose words are in progress. These first results support the effectiveness of explicitly teaching derivational morphology to improve spelling in school-aged children. The study is currently extended to a group of children with developmental dyslexia because these children are known for their severe and persistent spelling difficulties.

Keywords: developmental dyslexia, derivational morphology, reading, school-aged children, spelling, training

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Authors: Carolina S. Correia, Thalita V. Thomé, Andersen Boniolo, Dhayana I. Veiga

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Evidence-based practices (EBP) in education is a set of principles and practices used to raise educational policy, it involves the integration of professional expertise in education with the best empirical evidence in making decisions about how to deliver instruction. The purpose of this presentation is to describe and characterize studies about EBP in education in elementary classroom setting. Data here presented is part of an ongoing systematic review research. Articles were searched and selected from four academic databases: ProQuest, Scielo, Science Direct and Capes. The search terms were evidence-based practices or program effectiveness, and education or teaching or teaching practices or teaching methods. Articles were included according to the following criteria: The studies were explicitly described as evidence-based or discussed the most effective practices in education, they discussed teaching practices in classroom context in elementary school level. Document excerpts were extracted and recorded in Excel, organized by reference, descriptors, abstract, purpose, setting, participants, type of teaching practice, study design and main results. The total amount of articles selected were 1.185, 569 articles from Proquest Research Library; 216 from CAPES; 251 from ScienceDirect and 149 from Scielo Library. The potentially relevant references were 178, from which duplicates were removed. The final number of articles analyzed was 140. From 140 articles, are 47 theoretical studies and 93 empirical articles. The following research design methods were identified: longitudinal intervention study, cluster-randomized trial, meta-analysis and pretest-posttest studies. From 140 articles, 103 studies were about regular school teaching and 37 were on special education teaching practices. In several studies, used as teaching method: active learning, content acquisition podcast (CAP), precision teaching (PT), mediated reading practice, speech therapist programs and peer-assisted learning strategies (PALS). The countries of origin of the studies were United States of America, United Kingdom, Panama, Sweden, Scotland, South Korea, Argentina, Chile, New Zealand and Brunei. The present study in is an ongoing project, so some representative findings will be discussed, providing further acknowledgment on the best teaching practices in elementary classroom setting.

Keywords: best practices, children, evidence-based education, elementary school, teaching methods

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Authors: Rinda Kurnia

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Despite the differences and additional needs in the learning process, every individual has the right to receive educational services in order to enhance her/his abilities and potentials. This notion underlies the principle of inclusive education system, something many countries in the world are striving for since the UNESCO Salamanca Statement in 1994. This paper will consider different views that many theorists have published of the term inclusive, the issues, challenges, and dilemmas encountered during the practice, as well as some possible ways forward. It is being described, criticized and analyzed using the standpoint of a shadow teacher in an inclusive secondary school in Jakarta, Indonesia.

Keywords: inclusive education, inclusive education challenges, inclusive education dilemmas, inclusive education future plans, inclusive education issues

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Authors: Victor Birikorang Danquah

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Ghana's primary energy supply is heavily reliant on petroleum, biomass, and hydropower. Currently, Ghana gets its energy from hydropower (Akosombo and Bui), thermal power plants powered by crude oil, natural gas, and diesel, solar power, and imports from La Cote d'Ivoire. Until the early 2000s, large hydroelectric dams dominated Ghana's electricity generation. Due to unreliable weather patterns, Ghana increased its reliance on thermal power. However, thermal power contributes the highest percentage in terms of electricity generation in Ghana and is predominantly supplied by Independent Power Producers (IPPs). Ghana's electricity industry operates the corporate utility model as its business model. This model is typically' vertically integrated,' with a single corporation selling the majority of power generated by its generation assets to its retail business, which then sells the electricity to retail market consumers. The corporate utility model has a straightforward value proposition that is based on increasing the number of energy units sold. The unit volume business model drives the entire energy value chain to increase throughput, locking system users into unsustainable practices. This report uses the qualitative research approach to explore the electricity industry in Ghana. There is a need for increasing renewable energy, such as wind and solar, in electricity generation. The research recommends two critical business models for the penetration of renewable energy in Ghana's power sector. The first model is the peer-to-peer electricity trading model, which relies on a software platform to connect consumers and generators in order for them to trade energy directly with one another. The second model is about encouraging local energy generation, incentivizing optimal time-of-use behaviour, and allowing any financial gains to be shared among the community members.

Keywords: business model innovation, electricity generation, renewable energy, solar energy, sustainability, wind energy

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Authors: Yi Meng, Yun Gao

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Having spent significant periods studying and working in North America and Europe, we, as two Chinese art educators, have been profoundly shaped by both Eastern and Western cultures. Consequently, our ambition is to enrich students' learning experiences by delving into and merging both cultural perspectives for innovative, creative expressions. This exposition draws on our action research study on students' visual literacy practices in a visual literacy course at a prominent Chinese university. The central premise was to explore innovative art forms by cross-utilizing various aspects of diverse cultures. By examining distinct cultural elements, we encouraged students to break away from familiar approaches and forge new paths in their creative endeavors. In implementing our curriculum, we utilized a multimodal pedagogy that deviated from the predominant print-based presentations typically employed in our classroom settings. This pedagogical approach effectively encouraged students to critically analyze the artifact, imbue it with their understanding and perspectives, and then produce an original piece. This approach also motivated students to leverage the semiotic potential of various communicative modes to address diverse cultural issues through their multimodal designs. To demonstrate the potential for cultural amalgamation, we utilized the artwork of Hong Kong-based artist Tik Ka. His works epitomize the fusion of Chinese traditions with Western pop culture, which served as a visual and conceptual reference point for students. Seeing how these distinct cultural elements could coexist and enrich each other in Tik Ka's work was inspiring and motivating for the students. Taken together, these pedagogical strategies helped create a dialogical space where students could actively experience, analyze, and negotiate complex modes of expression. This environment fostered active learning, encouraging students to apply their knowledge, question their assumptions, and reconsider their perspectives. Overall, such a unique approach to visual literacy education has the potential to reshape students' understanding of both cultures. By encouraging them to critically engage with their multimodal designs, we promoted an in-depth, nuanced appreciation of these diverse cultural heritages. The students no longer just interpreted and replicated images—they actively contributed to a dynamic and ongoing conversation between cultures.

Keywords: multimodal pedagogy, creative expressions, visual literacy education, multimodal designs

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Authors: N. R. Prasannakumar, M. N. Maruthi

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The whitefly, Bemisia tabaci (Gennadius) (Hemiptera; Aleyrodidae) is a highly polyphagous pest reported to infest over 600 plant hosts globally. About 42 genetic groups/cryptic species of B. tabaci exist in the world on different hosts. The species have variable behaviour with respect to feeding, development and transmission of viral diseases. Feeding on diverse host plants affect both whitefly development and the population of the endosymbionts harboured by the insects. Due to changes in the level of endosymbionts, the virus transmission efficiency by the vector also gets affected. We investigated these interactions on five host plants – egg plant, tomato, beans, okra and cotton - using a single whitefly species Asia 1 infected with three different bacteria Portiera, Wolbachia and Arsenophonus. The Asia 1 transmits the Tomato leaf curl Bangalore virus (ToLCBV) effectively and thus was used in the interaction studies. We found a significant impact of hosts on whitefly growth and development; eggplant was most favourable host, while okra and tomato were least favourable. Among the endosymbiotic bacteria, the titre of Wolbachia was significantly affected by feeding of B. tabaci on different host plants whereas Arsenophonus and Portiera were unaffected. When whitefly fed on ToLCBV-infected tomato plants, the Arsenophonus population was significantly increased, indicating its previously confirmed role in ToLCBV transmission. Further, screening of total proteins of B. tabaci Asia 1 genetic group interacting with ToLCBV coat protein was carried out using Y2H system. Some of the proteins found to be interacting with ToLCBV CP were HSPs 70kDa, GroEL, nucleoproteins, vitellogenins, apolipophorins, lachesins, enolase. The reported protein thus would be the potential targets for novel whitefly control strategies such as RNAi or novel insecticide target sites for sustainable whitefly management after confirmation of genuine proteins.

Keywords: cDNA, whitefly, ToLCBV, endosymbionts, Y2H

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Authors: Francesca Radice

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Domestic and sexual violence provokes, on average in Australia, one female death per week due to intimate violence behaviours. 83% of couples meet online, and intercepting domestic and sexual violence at this level would be beneficial. It has been observed that violent or coercive behaviour has been apparent from initial conversations on dating apps like Tinder. Child pornography, stalking, and coercive control are some criminal offences from dating apps, including women murdered after finding partners through Tinder. Police databases and predictive policing are novel approaches taken to prevent crime before harm is done. This research will investigate how police databases can be used in a privacy-preserving way to characterise users in terms of their potential for violent crime. Using the COPS database of NSW Police, we will explore how the past criminal record can be interpreted to yield a category of potential danger for each dating app user. It is up to the judgement of each subscriber on what degree of the potential danger they are prepared to enter into. Sentiment analysis is an area where research into natural language processing has made great progress over the last decade. This research will investigate how sentiment analysis can be used to interpret interchanges between dating app users to detect manipulative or coercive sentiments. These can be used to alert law enforcement if continued for a defined number of communications. One of the potential problems of this approach is the potential prejudice a categorisation can cause. Another drawback is the possibility of misinterpreting communications and involving law enforcement without reason. The approach will be thoroughly tested with cross-checks by human readers who verify both the level of danger predicted by the interpretation of the criminal record and the sentiment detected from personal messages. Even if only a few violent crimes can be prevented, the approach will have a tangible value for real people.

Keywords: sentiment analysis, data mining, predictive policing, virtual manipulation

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Authors: Elcin Timur Cakmak, Ayse Oguzlar

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This study presents the results of the tweets sent by Twitter users on social media about the Russia-Ukraine war by bigram and trigram methods. On February 24, 2022, Russian President Vladimir Putin declared a military operation against Ukraine, and all eyes were turned to this war. Many people living in Russia and Ukraine reacted to this war and protested and also expressed their deep concern about this war as they felt the safety of their families and their futures were at stake. Most people, especially those living in Russia and Ukraine, express their views on the war in different ways. The most popular way to do this is through social media. Many people prefer to convey their feelings using Twitter, one of the most frequently used social media tools. Since the beginning of the war, it is seen that there have been thousands of tweets about the war from many countries of the world on Twitter. These tweets accumulated in data sources are extracted using various codes for analysis through Twitter API and analysed by Python programming language. The aim of the study is to find the word sequences in these tweets by the n-gram method, which is known for its widespread use in computational linguistics and natural language processing. The tweet language used in the study is English. The data set consists of the data obtained from Twitter between February 24, 2022, and April 24, 2022. The tweets obtained from Twitter using the #ukraine, #russia, #war, #putin, #zelensky hashtags together were captured as raw data, and the remaining tweets were included in the analysis stage after they were cleaned through the preprocessing stage. In the data analysis part, the sentiments are found to present what people send as a message about the war on Twitter. Regarding this, negative messages make up the majority of all the tweets as a ratio of %63,6. Furthermore, the most frequently used bigram and trigram word groups are found. Regarding the results, the most frequently used word groups are “he, is”, “I, do”, “I, am” for bigrams. Also, the most frequently used word groups are “I, do, not”, “I, am, not”, “I, can, not” for trigrams. In the machine learning phase, the accuracy of classifications is measured by Classification and Regression Trees (CART) and Naïve Bayes (NB) algorithms. The algorithms are used separately for bigrams and trigrams. We gained the highest accuracy and F-measure values by the NB algorithm and the highest precision and recall values by the CART algorithm for bigrams. On the other hand, the highest values for accuracy, precision, and F-measure values are achieved by the CART algorithm, and the highest value for the recall is gained by NB for trigrams.

Keywords: classification algorithms, machine learning, sentiment analysis, Twitter

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Authors: A. Alzeyadi, E. Loffill, R. Alkhaddar

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Continuous upflow filters can combine the nutrient (nitrogen and phosphate) and suspended solid removal in one unit process. The contaminant removal could be achieved chemically or biologically; in both processes the filter removal efficiency depends on the interaction between the packed filter media and the influent. In this paper a residence time distribution (RTD) study was carried out to understand and compare the transfer behaviour of contaminants through a selected filter media packed in a laboratory-scale continuous up flow filter; the selected filter media are limestone and white dolomite. The experimental work was conducted by injecting a tracer (red drain dye tracer –RDD) into the filtration system and then measuring the tracer concentration at the outflow as a function of time; the tracer injection was applied at hydraulic loading rates (HLRs) (3.8 to 15.2 m h-1). The results were analysed according to the cumulative distribution function F(t) to estimate the residence time of the tracer molecules inside the filter media. The mean residence time (MRT) and variance σ2 are two moments of RTD that were calculated to compare the RTD characteristics of limestone with white dolomite. The results showed that the exit-age distribution of the tracer looks better at HLRs (3.8 to 7.6 m h-1) and (3.8 m h-1) for limestone and white dolomite respectively. At these HLRs the cumulative distribution function F(t) revealed that the residence time of the tracer inside the limestone was longer than in the white dolomite; whereas all the tracer took 8 minutes to leave the white dolomite at 3.8 m h-1. On the other hand, the same amount of the tracer took 10 minutes to leave the limestone at the same HLR. In conclusion, the determination of the optimal level of hydraulic loading rate, which achieved the better influent distribution over the filtration system, helps to identify the applicability of the material as filter media. Further work will be applied to examine the efficiency of the limestone and white dolomite for phosphate removal by pumping a phosphate solution into the filter at HLRs (3.8 to 7.6 m h-1).

Keywords: filter media, hydraulic loading rate, residence time distribution, tracer

Procedia PDF Downloads 267

Authors: L. Hoade, O. O. Onafowokan, K. Anderson, G. E. Bartlett, E. D. Fern, M. R. Norton, R. G. Middleton

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Aims: Femoroacetabular impingement (FAI) was first recognised as a potential driver for hip pain at the turn of the last millennium. While there is an increasing trend towards surgical management of FAI by arthroscopic means, open surgical hip dislocation and debridement (SHD) remains the Gold Standard of care in terms of reported outcome measures. (1) Long-term functional and survivorship outcomes of SHD as a treatment for FAI are yet to be sufficiently reported in the literature. This study sets out to help address this imbalance. Methods: We undertook a retrospective review of our institutional database for all patients who underwent SHD for FAI between January 2003 and December 2008. A total of 223 patients (241 hips) were identified and underwent a ten year review with a standardised radiograph and patient-reported outcome measures questionnaire. The primary outcome measure of interest was survivorship, defined as progression to total hip arthroplasty (THA). Negative predictive factors were analysed. Secondary outcome measures of interest were survivorship to further (non-arthroplasty) surgery, functional outcomes as reflected by patient reported outcome measure scores (PROMS) scores, and whether a learning curve could be identified. Results: The final cohort consisted of 131 females and 110 males, with a mean age of 34 years. There was an overall native hip joint survival rate of 85.4% at ten years. Those who underwent a THA were significantly older at initial surgery, had radiographic evidence of preoperative osteoarthritis and pre- and post-operative acetabular undercoverage. In those whom had not progressed to THA, the average Non-arthritic Hip Score and Oxford Hip Score at ten year follow-up were 72.3% and 36/48, respectively, and 84% still deemed their surgery worthwhile. A learning curve was found to exist that was predicated on case selection rather than surgical technique. Conclusion: This is only the second study to evaluate the long-term outcomes (beyond ten years) of SHD for FAI and the first outside the originating centre. Our results suggest that, with correct patient selection, this remains an operation with worthwhile outcomes at ten years. How the results of open surgery compared to those of arthroscopy remains to be answered. While these results precede the advent of collison software modelling tools, this data helps set a benchmark for future comparison of other techniques effectiveness at the ten year mark.

Keywords: femoroacetabular impingement, hip pain, surgical hip dislocation, hip debridement

Procedia PDF Downloads 77

Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

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The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

Procedia PDF Downloads 106

Authors: S. Curtin, A. Trace

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Introduction: As patients can often be ambivalent about or resistant to any change in their smoking behavior the traditional ‘5 A’ model may be limited as it assumes that patients are ready and motivated to change. However, there is a stage model that is helpful to give guidance for dental students: the Transtheoretical Model (TTM). This model allows students to understand the tasks and goals for the pre-contemplation stage. The TTM was introduced in early stages as a core component of a smoking cessation programme that was integrated into a Behavioral Science programme as applied to dentistry. The aim of the present study is to evaluate and illustrate the students’ current level of knowledge from the questions the students generated in order to engage patients in the tasks and goals of the pre-contemplation stage. Method: N=47 responses of fifth-year undergraduate dental students. These responses were the data set for this study and related to their knowledge base of appropriate questions for a dentist to ask at the pre-contemplation stage of change. A deductive -descriptive analysis was conducted on the data. The goals and tasks of the pre-contemplation stage of the TTM provided a template for this deductive analysis. Results: 51% of students generated relevant, open, exploratory questions for the pre-contemplation stage, whilst 100% of students generated closed questions. With regard to those questions appropriate for the pre-contemplation stage, 19% were open and exploratory, while 66% were closed questions. A deductive analysis of the open exploratory questions revealed that 53% of the questions addressed increased concern about the current pattern of behavior, 38% of the questions concerned increased awareness of a need for change and only 8% of the questions dealt with the envisioning of the possibility of change. Conclusion: All students formulated relevant questions for the pre-contemplation stage, and half of the students generated the open, exploratory questions that increased patients’ awareness of the need to change. More training is required to facilitate a shift in the formulation from closed to open questioning, especially given that, traditionally, smoking cessation was modeled on the ‘5 As’, and that the general training for dentists supports an advisory and directive approach.

Keywords: behaviour change, pre-contemplation stage, trans-theoretical model, undergraduate dentistry students

Procedia PDF Downloads 400

Authors: Umit Cali

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The integration of intermittent energy sources like wind farms into the electricity grid has become an important challenge for the utilization and control of electric power systems, because of the fluctuating behaviour of wind power generation. Wind power predictions improve the economic and technical integration of large amounts of wind energy into the existing electricity grid. Trading, balancing, grid operation, controllability and safety issues increase the importance of predicting power output from wind power operators. Therefore, wind power forecasting systems have to be integrated into the monitoring and control systems of the transmission system operator (TSO) and wind farm operators/traders. The wind forecasts are relatively precise for the time period of only a few hours, and, therefore, relevant with regard to Spot and Intraday markets. In this work predictive data mining techniques are applied to identify a statistical and neural network model or set of models that can be used to predict wind power output of large onshore and offshore wind farms. These advanced data analytic methods helps us to amalgamate the information in very large meteorological, oceanographic and SCADA data sets into useful information and manageable systems. Accurate wind power forecasts are beneficial for wind plant operators, utility operators, and utility customers. An accurate forecast allows grid operators to schedule economically efficient generation to meet the demand of electrical customers. This study is also dedicated to an in-depth consideration of issues such as the comparison of day ahead and the short-term wind power forecasting results, determination of the accuracy of the wind power prediction and the evaluation of the energy economic and technical benefits of wind power forecasting.

Keywords: renewable energy sources, wind power, forecasting, data mining, big data, artificial intelligence, energy economics, power trading, power grids

Procedia PDF Downloads 507

Authors: Q. Giraud, J. Gonçalvès, B. Paris

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Remediation of dense non-aqueous phase liquids (DNAPLs) represents a challenging issue because of their persistent behaviour in the environment. This pilot-scale study investigates, by means of in situ experiments and numerical modelling, the feasibility of the pulsed pumping process of a large amount of a DNAPL in an alluvial aquifer. The main compound of the DNAPL is hexachlorobutadiene, an emerging organic pollutant. A low-permeability keyed enclosure was built at the location of the DNAPL source zone in order to isolate a finite undisturbed volume of soil, and a 3-month pulsed pumping process was applied inside the enclosure to exclusively extract the DNAPL. The water/DNAPL interface elevation at both the pumping and observation wells and the cumulated pumped volume of DNAPL were also recorded. A total volume of about 20m³ of purely DNAPL was recovered since no water was extracted during the process. The three-dimensional and multiphase flow simulator TMVOC was used, and a conceptual model was elaborated and generated with the pre/post-processing tool mView. Numerical model consisted of 10 layers of variable thickness and 5060 grid cells. Numerical simulations reproduce the pulsed pumping process and show an excellent match between simulated, and field data of DNAPL cumulated pumped volume and a reasonable agreement between modelled and observed data for the evolution of the water/DNAPL interface elevations at the two wells. This study offers a new perspective in remediation since DNAPL pumping system optimisation may be performed where a large amount of DNAPL is encountered.

Keywords: dense non-aqueous phase liquid (DNAPL), hexachlorobutadiene, in situ pulsed pumping, multiphase flow, numerical modelling, porous media

Procedia PDF Downloads 170

Authors: Harrys Purnama, Wardatul Jannah, Rizkia Nita Hawari

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In the development of the times, there are many materials used to plan a building structure. Steel became one of the most widely used materials in building construction that works as the main structure. Steel Castellated Beam is a type of innovation in the use of steel in building construction. Steel Castellated Beam is a beam that used for long span construction (more than 10 meters). The Castellated Beam is two steel profiles that unified into one to get the appropriate profile height (more than 10 meters). The profile is perforated to minimize the profile's weight, increase the rate, save costs, and have architectural value. The perforations shape in the Castellated Beam can be circular, elliptical, hexagonal, and rectangular. The Castellated beam has a height (h) almost 50% higher than the initial profile thus increasing the axial bending value and the moment of inertia (Iₓ). In this analysis, there are 3 specimens were used with 12.1 meters span of Castellated Beam as the sample with varied perforation, such us round, hexagon, and octagon. Castellated Beam testing system is done with computer-based applications that named Staad Pro V8i. It is to provide a central load in the middle of the steel beam span. It aims to determine the effect of perforation on bending behavior on the steel Castellated Beam by applying some form of perforations on the steel Castellated Beam with test specimen WF 200.100.5.5.8. From the analysis, results found the behavior of steel Castellated Beam when receiving such central load. From the results of the analysis will be obtained the amount of load, shear, strain, and Δ (deflection). The result of analysis by using Staad Pro V8i shows that with the different form of perforations on the profile of Castellated steel, then we get the different tendency of inertia moment. From the analysis, results obtained the moment of the greatest inertia can increase the stiffness of Castellated steel. By increasing the stiffness of the steel Castellated Beam the deflection will be smaller, so it can withstand the moment and a large strength. The results of the analysis show that the most effective and efficient perforations are the steel beam with a hexagon perforation shape.

Keywords: Castellated Beam, the moment of inertia, stress, deflection, bending test

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Authors: Laraba Bala Mohammed

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Education is a very vital tool in enhancement of the general development of individuals in the society who would participate effectively in national development processes, including people with special need, educating children with special needs is one of the greatest challenges of this millennium, this is because professionals in the field of special education are operating in an exciting and rapidly changing phenomenon. Inclusive education in Nigeria is not a new development in the teaching and learning process, but the most important aspect is the utilization and effective integration of people with special needs in the society. This paper focuses on the need of parents, government, professionals in the field of special education and stakeholders to work together for the full implementation of inclusive education in Nigeria.

Keywords: inclusive education, national policy, education, special needs

Procedia PDF Downloads 497

Authors: Jiongbin Liu, William Yeoh, Shang Gao, Xiaoliang Meng, Yuhan Zhu

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The metaverse concept has sparked significant interest in both academic and industrial spheres. As educational institutions increasingly adopt this technology, understanding its implementation becomes crucial. In response, we conducted a comprehensive case study at a large university, systematically analyzing the nine stages of metaverse development initiatives. Our study unveiled critical insights into the planning, assessment, and execution processes, offering invaluable guidance for stakeholders. The findings highlight both the opportunities for enhanced learning experiences and the challenges related to technological integration and social interaction in higher education.

Keywords: metaverse, metaverse development framework, higher education, case study

Procedia PDF Downloads 17

Authors: Allen A. Espinosa, Larkins A. Trinidad

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The present study investigated collegiate students’ problem solving strategies and misconceptions in solving stoichiometric problems and later on formulate a teaching framework from the result of the study. The study found out that the most prominent strategies among students are the mole method and the proportionality method, which are both algorithmic by nature. Misconception was also noted as some students rely on Avogadro’s number in converting between moles. It is suggested therefore that the teaching of stoichiometry should not be confined to demonstration. Students should be involved in the process of thinking of ways to solve the problem.

Keywords: stoichiometry, Svogadro’s number, mole method, proportionality method

Procedia PDF Downloads 374

Authors: Shantanu Arya, Sachin Sakhuja, Gunjan Mehta, Sanjay Munjal

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Stuttering may be defined as a speech disorder affecting the fluency domain of speech and characterized by covert features like word substitution, omittance and circumlocution and overt features like prolongation of sound, syllables and blocks etc. Many etiologies have been postulated to explain stuttering based on various experiments and research. Moreover, Breathlessness has also been reported by many individuals with stuttering for which breathing exercises are generally advised. However, no studies reporting objective evaluation of the pulmonary capacity and further objective assessment of the efficacy of breathing exercises have been conducted. Pulmonary Function Test which evaluates parameters like Forced Vital Capacity, Peak Expiratory Flow Rate, Forced expiratory flow Rate can be used to study the pulmonary behavior of individuals with stuttering. The study aimed: a) To identify speech motor & physiologic behaviours associated with stuttering by administering PFT. b) To recognize possible reasons for an association between speech motor behaviour & stuttering severity. In this regard, PFT tests were administered on individuals who reported signs and symptoms of stuttering and showed abnormal scores on Stuttering Severity Index. Parameters like Forced Vital Capacity, Forced Expiratory Volume, Peak Expiratory Flow Rate (L/min), Forced Expiratory Flow Rate (L/min) were evaluated and correlated with scores of Stuttering Severity Index. Results showed significant decrease in the parameters (lower than normal scores) in individuals with established stuttering. Strong correlation was also found between degree of stuttering and the degree of decrease in the pulmonary volumes. Thus, it is evident that fluent speech requires strong support of lung pressure and requisite volumes. Further research in demonstrating the efficacy of abdominal breathing exercises in this regard is needed.

Keywords: forced expiratory flow rate, forced expiratory volume, forced vital capacity, peak expiratory flow rate, stuttering

Procedia PDF Downloads 257