Search results for: learning from history

Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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Authors: Cristina Costa-Lobo, Sandra Fernandes, Miguel Magalhães, José Dinis-Carvalho, Alfredo Regueiro, Ana Carvalho

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This paper is a report on the findings of the construction and the validation of a questionnaire monetized in a portuguese higher education context with undergraduate students. The Questionnaire for the Evaluation of Entrepreneurship Project Psychopedagogical Practices consists of six scales: Critical appraisal of the project, Developed Learning and Skills, Teamwork, Teacher and Tutor Roles, Evaluation of Student Performance, and Project Effectiveness as a Teaching-Learning Methodology. The proceedings of its construction are analyzed, and the validity and internal consistency analysis are described. Findings indicate good indicators of validity, good fidelity and an interpretable factorial structure.

Keywords: entrepreneurship project, higher education, psychopedagogical practices, teacher and tutor roles

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Authors: Marta Fonseca, Pedro Marvão, Beatriz Oliveira, Bruno Heleno, Pedro Carreiro-Martins, Nuno Neuparth, António Rendas

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Background: Concept maps (CMs) visually represent hierarchical connections among related ideas. They foster logical organization and clarify idea relationships, potentially aiding medical students in critical thinking (to think clearly and rationally about what to do or what to believe). However, there are inconsistent claims about the use of CMs in undergraduate medical education. Our three research questions are: 1) What studies have been published on concept mapping in undergraduate medical education? 2) What was the impact of CMs on students’ critical thinking? 3) How and why have these interventions had an educational impact? Methods: Eight databases were systematically searched (plus a manual and an additional search were conducted). After eliminating duplicate entries, titles, and abstracts, and full-texts were independently screened by two authors. Data extraction and quality assessment of the studies were independently performed by two authors. Qualitative and quantitative data were integrated using mixed-methods. The results were reported using the structured approach to the reporting in healthcare education of evidence synthesis statement and BEME guidance. Results: Thirty-nine studies were included from 26 journals (19 quantitative, 8 qualitative and 12 mixed-methods studies). CMs were considered as a tool to promote critical thinking, both in the perception of students and tutors, as well as in assessing students’ knowledge and/or skills. In addition to their role as facilitators of knowledge integration and critical thinking, CMs were considered both teaching and learning methods. Conclusions: CMs are teaching and learning tools which seem to help medical students develop critical thinking. This is due to the flexibility of the tool as a facilitator of knowledge integration, as a learning and teaching method. The wide range of contexts, purposes, and variations in how CMs and instruments to assess critical thinking are used increase our confidence that the positive effects are consistent.

Keywords: concept map, medical education, undergraduate, critical thinking, meaningful learning

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Authors: Farnaz Nazem

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Iranian architects had creative ways for constructing the buildings in each climate. Some of these architectural elements were made under the ground. Shovadan is one of these underground spaces in hot- humid regions in Dezfoul and Shoushtar city that had special functions and characteristics. In this paper some subjects such as the history of Shovadan, its elements and effective factors in the formation of Shovadan in Dezfool city are discussed.

Keywords: architecture, dezfoul city, Shovadan, south west of Iran

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Authors: Hardisiswo Soedjana, Inne Caroline

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Deep dermal or full thickness burns are inevitably lead to post-burn contractures. These contractures remain to be one of the most concerning late complications of burn injuries. Surgical management includes releasing the contracture followed by resurfacing the defect accompanied by post-operative rehabilitation. Optimal treatment of post-burn contractures depends on the characteristics of the contractures. This study is aimed to describe clinical characteristics, problems, and management of post-burn contractures in adults and children. A retrospective analysis was conducted from medical records of patients suffered from contractures after burn injuries admitted to Hasan Sadikin general hospital between January 2016 and January 2018. A total of 50 patients with post burn contractures were included in the study. There were 17 adults and 33 children. Most patients were male, whose age range within 15-59 years old and 5-9 years old. Educational background was mostly senior high school among adults, while there was only one third of children who have entered school. Etiology of burns was predominantly flame in adults (82.3%); whereas flame and scald were the leading cause of burn injury in children (11%). Based on anatomical regions, hands were the most common affected both in adults (35.2%) and children (48.5%). Contractures were identified in 6-12 months since the initial burns. Most post-burn hand contractures were resurfaced with full-thickness skin graft (FTSG) both in adults and children. There were 11 patients who presented with recurrent contracture after previous history of contracture release. Post-operative rehabilitation was conducted for all patients; however, it is important to highlight that it is still challenging to control splinting and exercise when patients are discharged and especially the compliance in children. In order to improve quality of life in patients with history of deep burn injuries, prevention of contractures should begin right after acute care has been established. Education for the importance of splinting and exercise should be administered as comprehensible as possible for adult patients and parents of pediatric patients.

Keywords: burn, contracture, education, exercise, splinting

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Authors: Anthony J. Rojas

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In flipped classroom environments, students are tasked with engaging in pre-class learning to maximize the effectiveness of in-class time. This study investigates the use of ‘Quests’, brief formative assessments administered at the start of class, to evaluate student understanding of assigned pre-class materials in an undergraduate chemistry course. Students completed Quests via Microsoft Forms, based on content from instructional videos and worksheets, and these assessments were mandatory, with no opportunity for make-up. This paper examines the correlation between Quest performance and overall course success, finding that students who performed well on the Quests consistently achieved higher final grades in the course. The findings suggest that Quests are effective in both reinforcing student engagement with pre-class content and predicting their broader academic performance. The implications of these results for flipped classroom strategies and student learning outcomes will be discussed.

Keywords: chemistry, flipped classroom, attendance, assessments

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Authors: Lana Burmistrova

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Introduction: The influence of visual impairments on several cognitive processes used in the music learning process is an increasingly important area in special education and cognitive musicology. Many children have several visual impairments due to the refractive errors and irreversible inhibitors. However, based on the compensatory neuroplasticity and functional reorganization, congenitally blind (CB) and early blind (EB) individuals use several areas of the occipital lobe to perceive and process auditory and tactile information. CB individuals have greater memory capacity, memory reliability, and less false memory mechanisms are used while executing several tasks, they have better working memory (WM) and short-term memory (STM). Blind individuals use several strategies while executing tactile and working memory n-back tasks: verbalization strategy (mental recall), tactile strategy (tactile recall) and combined strategies. Methods and design: The aim of the pilot study was to substantiate similar tendencies while executing attention, memory and combined auditory tasks in blind and sighted individuals constructed for this study, and to investigate attention, memory and combined mechanisms used in the music learning process. For this study eight (n=8) blind and eight (n=8) sighted individuals aged 13-20 were chosen. All respondents had more than five years music performance and music learning experience. In the attention task, all respondents had to identify pitch changes in tonal and randomized melodic pairs. The memory task was based on the mismatch negativity (MMN) proportion theory: 80 percent standard (not changed) and 20 percent deviant (changed) stimuli (sequences). Every sequence was named (na-na, ra-ra, za-za) and several items (pencil, spoon, tealight) were assigned for each sequence. Respondents had to recall the sequences, to associate them with the item and to detect possible changes. While executing the combined task, all respondents had to focus attention on the pitch changes and had to detect and describe these during the recall. Results and conclusion: The results support specific features in CB and EB, and similarities between late blind (LB) and sighted individuals. While executing attention and memory tasks, it was possible to observe the tendency in CB and EB by using more precise execution tactics and usage of more advanced periodic memory, while focusing on auditory and tactile stimuli. While executing memory and combined tasks, CB and EB individuals used passive working memory to recall standard sequences, active working memory to recall deviant sequences and combined strategies. Based on the observation results, assessment of blind respondents and recording specifics, following attention and memory correlations were identified: reflective attention and STM, reflective attention and periodic memory, auditory attention and WM, tactile attention and WM, auditory tactile attention and STM. The results and the summary of findings highlight the attention and memory features used in the music learning process in the context of blindness, and the tendency of the several attention and memory types correlated based on the task, strategy and individual features.

Keywords: attention, blindness, memory, music learning, strategy

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Authors: Kate Benedicta Amenador, Dianjian Wang, Bright Nkrumah

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This extensive bibliometric study explores the dynamic influence of artificial intelligence in the field of English as a Foreign Language (EFL) between 2012 and 2024. The study, which examined 4,500 articles from Google Scholar, Modern Language Association Linguistics Abstracts, Web of Science, Scopus, Researchgate, and library genesis databases, indicates that AI integration in EFL is on the rise. This notable increase is ascribed to a variety of transformative events, including increased academic funding for higher education and the COVID-19 epidemic. The results of the study identify leading contributors, prominent authors, publishers and sources, with the United States, China and the United Kingdom emerging as key contributors. The co-occurrence analysis of key terms reveals five clusters highlighting patterns in AI-enhanced language instruction and learning, including evaluation strategies, educational technology, learning motivation, EFL teaching aspects, and learner feedback. The study also discusses the impact of various AIs in enhancing EFL writing skills with software such as Grammarly, Quilbot, and Chatgpt. The current study recognizes limitations in database selection and linguistic constraints. Nevertheless, the results provide useful insights for educators, researchers and policymakers, inspiring and guiding a cross-disciplinary collaboration and creative pedagogical techniques and approaches to teaching and learning in the future.

Keywords: artificial intelligence, bibliometrics study, VOSviewer visualization, English as a foreign language

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Authors: Ketevan Epadze

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The paper aims to examine conflicting historical narratives proposed by the Georgian and Abkhazian scholars on the territorial affiliation of Abkhazia in the 1950s, explain how these narratives were connected to the Soviet nationalities policy after WW II and demonstrate the dynamic of the narratives’ battle in the last years of the Soviet system, which was followed by military conflict in the post-Soviet era. Abkhazia –a breakaway region of Georgia- self-declared its independence in 1992. Historical dispute on the territorial rights of Abkhazia emerged long before the military conflict began and was connected to the theory of Abkhazian ethnogenesis written by the Georgian literary scholar Pavle Ingorokva. He argued that medieval Abkhazians were Georgians, while modern Abkhazians are newcomers in Abkhazia. After the de-Stalinization, Abkhazian historians developed historical narrative opposed to Ingorokva’s theory. In the 1980s, Georgian dissidents who strove for Georgia’s independence used Ingorokva’s thesis to oppose Abkhazians desire for self-determination and sovereignty. Abkhazian political actors in their turn employed opposite historical arguments to legitimate their rights over autonomy. Ingorokva’s theory is one of the principal issues, discussed during the Georgian-Abkhazian dialogue; it often confuses Georgians and gives the reasons to Abkhazians for complaining about the Georgian discrimination in the Soviet past. The study is based on the different kind of sources: archival materials of the 1950s (Communist Party Archive of Georgia, Soviet Journal ‘Mnatobi’), the book by Pavle Ingorokva ‘Giorgi Merchule’ (1947-1954) and Zurab Anchabadze’s responsive work to Ingorokva’s book – ‘From the medieval history of Abkhazia’ (1956-1959), political speeches of the Georgian and Abkhazian political actors in the 1980s, secondary sources on the Soviet nationalities policy from the 1950s to the 1990s.

Keywords: Soviet, history, ethnicity, nationalism, politics, post-Soviet, conflict

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Authors: Aaditya U. Jhamb

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Due to the current energy crisis that many countries are battling, energy-efficient buildings are the subject of extensive research in the modern technological era because of growing worries about energy consumption and its effects on the environment. The paper explores 8 factors that help determine energy efficiency for a building: (relative compactness, surface area, wall area, roof area, overall height, orientation, glazing area, and glazing area distribution), with Tsanas and Xifara providing a dataset. The data set employed 768 different residential building models to anticipate heating and cooling loads with a low mean squared error. By optimizing these characteristics, machine learning algorithms may assess and properly forecast a building's heating and cooling loads, lowering energy usage while increasing the quality of people's lives. As a result, the paper studied the magnitude of the correlation between these input factors and the two output variables using various statistical methods of analysis after determining which input variable was most closely associated with the output loads. The most conclusive model was the Decision Tree Regressor, which had a mean squared error of 0.258, whilst the least definitive model was the Isotonic Regressor, which had a mean squared error of 21.68. This paper also investigated the KNN Regressor and the Linear Regression, which had to mean squared errors of 3.349 and 18.141, respectively. In conclusion, the model, given the 8 input variables, was able to predict the heating and cooling loads of a residential building accurately and precisely.

Keywords: energy efficient buildings, heating load, cooling load, machine learning models

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Authors: Gabriela Ilie, Robert D. H. Rutledge

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A review of the literature reveals a need for longitudinal studies to properly understand the quality of life of prostate cancer survivors during their prostate cancer journey in order to identify opportunities for patient support and care during prostate cancer survivorship. In this study, mental health and relationship satisfaction were assessed longitudinally and by treatment modality among a population-based sample of Canadian adult men with a history of prostate cancer diagnosis. A total of 98 men, aged 51 or older with a history of prostate cancer completed an on-line 15-minute survey between May 2017 and February 2018, assessing mental health (Kessler Psychological Distress Scale) and relationship satisfaction (Dyadic Adjustment Scale) at baseline and at three months post-treatment with either active or nonactive prostate cancer treatment. Almost 1 in 6 men in this sample screened positive for mental health issues (17.34%, n=17) irrespective of treatment modality and most (n=11) were not currently on medication for depression, anxiety or both. Mental health outcomes were poorer for men with multimorbidity. For every instance of screening positive for mental health issues, 2.021 (95% CI:1.1 to 3.8) times more comorbidities were recorded. Relationship satisfaction and dyadic cohesion were statistically significantly lower from first assessment to 3 months for men who underwent multiple treatment modalities (surgery and radiation with hormonal therapy). Relationship satisfaction was also lower at 3 months for men who underwent radiation therapy. Almost 1 in 2 men in this sample (74%) indicated they did not attend a prostate cancer support group. Results suggest that treatment for mental health is underutilized in men with prostate cancer. Men who undergo multiple forms of active treatment appear more vulnerable to relationship dissatisfaction and feeling disconnected from their partner. Data points to important opportunities for patient education and care support during survivorship.

Keywords: prostate cancer survivorship, mental health, quality of life, relationship satisfaction

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Authors: Afsaneh Jasmine Majidi

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Language testing is an important part of language teaching experience and language learning process as it presents assessment strategies for teachers to evaluate the efficiency of teaching and for learners to examine their outcomes. However, language testing is demanding and challenging because it should provide the opportunity for proper and objective decision. In addition to all the efforts test designers put to design valid and reliable tests, there are some other determining factors which are even more complex and complicated. These factors affect the educational system, individuals, and society, and the impact of the tests vary according to the scope of the test. Seemingly, the impact of a simple classroom assessment is not the same as that of high stake tests such as International English Language Testing System (IELTS). As the importance of the test increases, it affects wider domain. Accordingly, the impacts of high stake tests are reflected not only in teaching, learning strategies but also in society. Testing experts use the term ‘washback’ or ‘impact’ to define the different effects of a test on teaching, learning, and community. This paper first looks at the theoretical background of ‘washback’ and ‘impact’ in language testing by reviewing of relevant literature in the field and then investigates washback effects of IELTS test of on Iranian IELTS teachers and students. The study found significant relationship between the washback effect of IELTS test and teaching strategies of Iranian IELTS teachers as well as performance of Iranian IELTS candidates and their community.

Keywords: high stake tests, IELTS, Iranian Candidates, language testing, test impact, washback

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Authors: W. Zekri

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This paper explores Zohra Drif’s memoir, Inside the Battle of Algiers, which narrates her desires as a student to become a revolutionary activist. She exemplified, in her narrative, the different roles, she and her fellows performed as combatants in the Casbah during the Algerian Revolution 1954-1962. This book review aims to evaluate the concept of women’s agency through education and language learning, and its impact on empowering women’s desires. Close-reading method and thematic analysis are used to explore the text. The analysis identified themes that refine the meaning of agency which are social and cultural supports, education, and language proficiency. These themes aim to contribute to the representation in Inside the Battle of Algiers of a woman guerrilla who engaged herself to perform national acts of resistance.

Keywords: agency, education, learning, women

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

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Authors: Todd Zhou, Mikhail Yurochkin

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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

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Authors: M. Isabel Santos, Ana Breda, Ana Margarida Almeida

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Research on academic abilities of individuals with autism spectrum disorder (ASD) underlines the importance of mathematics interventions. Yet the proposal of digital applications for children and youth with ASD continues to attract little attention, namely, regarding the development of mathematical reasoning, being the use of the digital technologies an area of great interest for individuals with this disorder and its use is certainly a facilitative strategy in the development of their mathematical abilities. The use of digital technologies can be an effective way to create innovative learning opportunities to these students and to develop creative, personalized and constructive environments, where they can develop differentiated abilities. The children with ASD often respond well to learning activities involving information presented visually. In this context, we present the digital Learning Environment on Mathematics for Autistic children (LEMA) that was a research project conducive to a PhD in Multimedia in Education and was developed by the Thematic Line Geometrix, located in the Department of Mathematics, in a collaboration effort with DigiMedia Research Center, of the Department of Communication and Art (University of Aveiro, Portugal). LEMA is a digital mathematical learning environment which activities are dynamically adapted to the user’s profile, towards the development of mathematical abilities of children aged 6–12 years diagnosed with ASD. LEMA has already been evaluated with end-users (both students and teacher’s experts) and based on the analysis of the collected data readjustments were made, enabling the continuous improvement of the prototype, namely considering the integration of universal design for learning (UDL) approaches, which are of most importance in ASD, due to its heterogeneity. The learning strategies incorporated in LEMA are: (i) provide options to custom choice of math activities, according to user’s profile; (ii) integrates simple interfaces with few elements, presenting only the features and content needed for the ongoing task; (iii) uses a simple visual and textual language; (iv) uses of different types of feedbacks (auditory, visual, positive/negative reinforcement, hints with helpful instructions including math concept definitions, solved math activities using split and easier tasks and, finally, the use of videos/animations that show a solution to the proposed activity); (v) provides information in multiple representation, such as text, video, audio and image for better content and vocabulary understanding in order to stimulate, motivate and engage users to mathematical learning, also helping users to focus on content; (vi) avoids using elements that distract or interfere with focus and attention; (vii) provides clear instructions and orientation about tasks to ease the user understanding of the content and the content language, in order to stimulate, motivate and engage the user; and (viii) uses buttons, familiarly icons and contrast between font and background. Since these children may experience little sensory tolerance and may have an impaired motor skill, besides the user to have the possibility to interact with LEMA through the mouse (point and click with a single button), the user has the possibility to interact with LEMA through Kinect device (using simple gesture moves).

Keywords: autism spectrum disorder, digital technologies, inclusion, mathematical abilities, mathematical learning activities

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Authors: Vesile Evrim, Aliyu Awwal

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Today as in the other domains, there are an enormous number of political transcripts available in the Web which is waiting to be mined and used for various purposes such as statistics and recommendations. Therefore, automatically determining the political orientation on these transcripts becomes crucial. The methodologies used by machine learning algorithms to do the automatic classification are based on different features such as Linguistic. Considering the ideology differences between Liberals and Conservatives, in this paper, the effect of Personality Traits on political orientation classification is studied. This is done by considering the correlation between LIWC features and the BIG Five Personality Traits. Several experiments are conducted on Convote U.S. Congressional-Speech dataset with seven benchmark classification algorithms. The different methodologies are applied on selecting different feature sets that constituted by 8 to 64 varying number of features. While Neuroticism is obtained to be the most differentiating personality trait on classification of political polarity, when its top 10 representative features are combined with several classification algorithms, it outperformed the results presented in previous research.

Keywords: politics, personality traits, LIWC, machine learning

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Authors: Dasom Kim, William Xiu Shun Wong, Yoonjin Hyun, Donghoon Lee, Minji Paek, Sungho Byun, Namgyu Kim

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There have been many researches on document classification for classifying voluminous documents automatically. Through document classification, we can assign a specific category to each unlabeled document on the basis of various machine learning algorithms. However, providing labeled documents manually requires considerable time and effort. To overcome the limitations, the semi-supervised learning which uses unlabeled document as well as labeled documents has been invented. However, traditional document classifiers, regardless of supervised or semi-supervised ones, cannot sufficiently explain the reason or the process of the classification. Thus, in this paper, we proposed a methodology to visualize major topics and class components of each document. We believe that our methodology for visualizing topics and classes of each document can enhance the reliability and explanatory power of document classifiers.

Keywords: data mining, document classifier, text mining, topic modeling

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Authors: Chirine Dannaoui, Maya Antoun

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This paper explores the intricate dynamics of play-based early childhood education (ECE) and the impact of professional development on teachers implementing play-based pedagogy, particularly in the context of vulnerable Syrian refugee children in Lebanon. By utilizing qualitative methodologies, including classroom observations and in-depth interviews with five early childhood educators and a field manager, this study delves into the challenges and transformations experienced by teachers in adopting play-based learning strategies. The research unveils the critical role of continuous and context-specific professional development in empowering teachers to implement play-based pedagogies effectively. When appropriately supported, it emphasizes how such educational approaches significantly enhance children's cognitive, social, and emotional development in crisis-affected environments. Key findings indicate that despite diverse educational backgrounds, teachers show considerable growth in their pedagogical skills through targeted professional development. This growth is vital for fostering a learning environment where vulnerable children can thrive, particularly in humanitarian settings. The paper also addresses educators' challenges, including adapting to play-based methodologies, resource limitations, and balancing curricular requirements with the need for holistic child development. This study contributes to the discourse on early childhood education in crisis contexts, emphasizing the need for sustainable, well-structured professional development programs. It underscores the potential of play-based learning to bridge educational gaps and contribute to the healing process of children facing calamity. The study highlights significant implications for policymakers, educators, schools, and not-for-profit organizations engaged in early childhood education in humanitarian contexts, stressing the importance of investing in teacher capacity and curriculum reform to enhance the quality of education for children in general and vulnerable ones in particular.

Keywords: play-based learning, professional development, vulnerable children, early childhood education

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Authors: Kwangmin Joo

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Automatic detection of lumbar vertebrae and classification method is proposed for evaluating the degree of disc narrowing. Prior to classification, deep learning based segmentation is applied to detect individual lumbar vertebra. M-net is applied to segment five lumbar vertebrae and fine-tuning segmentation is employed to improve the accuracy of segmentation. Using the features extracted from previous step, clustering technique, k-means clustering, is applied to estimate the degree of disc space narrowing under four grade scoring system. As preliminary study, techniques proposed in this research could help building an automatic scoring system to diagnose the severity of disc narrowing from X-ray images.

Keywords: Disc space narrowing, Degenerative disc disorders, Deep learning based segmentation, Clustering technique

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Authors: Pantelis Sklias, Panagiota Chatzimichailidou

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This study intents to clarify the nexus of adult education and economic development within the methodological framework of political economy within EU. The main logic behind this study is that economies with a higher level of adult education have higher levels of economic development. Despite the assumption that policy making in adult education will clearly be facilitated by any ‘proofs’ of efficiency, mainly monetary, this study acknowledges the limitations following the use of the narrow economic approaches embedded in the neoclassical framework and proposes that the methodological framework of political economy is the most relevant to explore the correlation between adult education and economic development. Focusing only on neoclassical economics to explore the financial impact of adult education, it will marginalize the consideration of its history, producing a short of historical amnesia, besides the social harm, namely the devaluation of its socio-cultural influences. On the other side the political economy perspective offers a wider perception of adult education’s profits from a quantitative and a qualitative perspective too. The understanding of adult education engages questions of political economy because it is identified mainly as means of transformation, either personal or societal, serving humanistic values, besides its accepted monetary attributes. The political economy elevates questions regarding how the three institutional arrangements -the state, the market, and the civil society, are engaged in promoting adult education and therefore how adult education could reinforce economic development. Here the economic substance is still considered but it is placed into a wider social spectrum, where politics, economy, and history interact with one another. This study restricts itself in EU and explores the role of the three institutional arrangements both in the formulation of policy planning, and in the mental transformational process of the individual learners, which opens the path to a deeper understanding of the interaction between the individual and the social action, and therefore between adult education and economic development. This study also elevates the idea that economic development can have a positive impact on the unification of Europe, which encompasses economic, political, and cultural components.

Keywords: adult education, economic development, EU, political economy, unification of Europe

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Authors: Ghazala Hcini, Imen Jdey, Hela Ltifi

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Malaria disease should be considered and handled as a potential restorative catastrophe. One of the most challenging tasks in the field of microscopy image processing is due to differences in test design and vulnerability of cell classifications. In this article, we focused on applying deep learning to classify patients by identifying images of infected and uninfected cells. We performed multiple forms, counting a classification approach using the Hue, Saturation, Value (HSV) color space. HSV is used since of its superior ability to speak to image brightness; at long last, for classification, a convolutional neural network (CNN) architecture is created. Clusters of focus were used to deliver the classification. The highlights got to be forbidden, and a few more clamor sorts are included in the information. The suggested method has a precision of 99.79%, a recall value of 99.55%, and provides 99.96% accuracy.

Keywords: deep learning, convolutional neural network, image classification, color transformation, HSV color, malaria diagnosis, malaria cells images

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Authors: Bruce Wrightsman

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Construction and design are inexorably linked. Traditional building methodologies, including those using wood, comprise a series of material layers differentiated and separated from each other. This results in the separation of two agencies of building envelope (skin) separate from the structure. However, from a material performance position reliant on additional materials, this is not an efficient strategy for the building. The merits of traditional platform framing are well known. However, its enormous effectiveness within wood-framed construction has seldom led to serious questioning and challenges in defining what it means to build. There are several downsides of using this method, which is less widely discussed. The first and perhaps biggest downside is waste. Second, its reliance on wood assemblies forming walls, floors and roofs conventionally nailed together through simple plate surfaces is structurally inefficient. It requires additional material through plates, blocking, nailers, etc., for stability that only adds to the material waste. In contrast, when we look back at the history of wood construction in airplane and boat manufacturing industries, we will see a significant transformation in the relationship of structure with skin. The history of boat construction transformed from indigenous wood practices of birch bark canoes to copper sheathing over wood to improve performance in the late 18th century and the evolution of merged assemblies that drives the industry today. In 1911, Swiss engineer Emile Ruchonnet designed the first wood monocoque structure for an airplane called the Cigare. The wing and tail assemblies consisted of thin, lightweight, and often fabric skin stretched tightly over a wood frame. This stressed skin has evolved into semi-monocoque construction, in which the skin merges with structural fins that take additional forces. It provides even greater strength with less material. The monocoque, which translates to ‘mono or single shell,’ is a structural system that supports loads and transfers them through an external enclosure system. They have largely existed outside the domain of architecture. However, this uniting of divergent systems has been demonstrated to be lighter, utilizing less material than traditional wood building practices. This paper will examine the role monocoque systems have played in the history of wood construction through lineage of boat and airplane building industries and its design potential for wood building systems in architecture through a case-study examination of a unique wood construction approach. The innovative approach uses a wood monocoque system comprised of interlocking small wood members to create thin shell assemblies for the walls, roof and floor, increasing structural efficiency and wasting less than 2% of the wood. The goal of the analysis is to expand the work of practice and the academy in order to foster deeper, more honest discourse regarding the limitations and impact of traditional wood framing.

Keywords: wood building systems, material histories, monocoque systems, construction waste

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Authors: Ayyaz Hussain, Tariq Sadad

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Breast cancer (BC) is one of the widespread ailments among females globally. The early prognosis of BC can decrease the mortality rate. Exact findings of benign tumors can avoid unnecessary biopsies and further treatments of patients under investigation. However, due to variations in images, it is a tough job to isolate cancerous cases from normal and benign ones. The machine learning technique is widely employed in the classification of BC pattern and prognosis. In this research, a deep convolution neural network (DCNN) called AlexNet architecture is employed to get more discriminative features from breast tissues. To achieve higher accuracy, K-nearest neighbor (KNN) classifiers are employed as a substitute for the softmax layer in deep learning. The proposed model is tested on a widely used breast image database called MIAS dataset for experimental purposes and achieved 99% accuracy.

Keywords: breast cancer, DCNN, KNN, mammography

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Authors: Nadia H. Mohammed, Anmar Al-Taie, Fadia H. Al-Sultany

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Although breast cancer prevalence continues to increase, mortality has been decreasing as a result of early detection and improvement in adjuvant systemic therapy. Nevertheless, this disease required further efforts to understand and identify the associated potential risk factors that could play a role in the prevalence of this malignancy among Iraqi women. The objective of this study was to assess the perception of certain predictive risk factors on the prevalence of breast cancer types among a sample of Iraqi women diagnosed with breast cancer. This was a retrospective observational study carried out at National Cancer Research Center in College of Medicine, Baghdad University from November 2017 to January 2018. Data of 100 patients with breast cancer whose biopsies examined in the National Cancer Research Center were included in this study. Data were collected to structure a detailed assessment regarding the patients’ demographic, medical and cancer records. The majority of study participants (94%) suffered from ductal breast cancer with mean age 49.57 years. Among those women, 48.9% were obese with body mass index (BMI) 35 kg/m². 68.1% of them had positive family history of breast cancer and 66% had low parity. 40.4% had stage II ductal breast cancer followed by 25.5% with stage III. It was found that 59.6% and 68.1% had positive oestrogen receptor sensitivity and positive human epidermal growth factor (HER2/neu) receptor sensitivity respectively. In regard to the impact of prediction of certain variables on the incidence of ductal breast cancer, positive family history of breast cancer (P < 0.0001), low parity (P< 0.0001), stage I and II breast cancer (P = 0.02) and positive HER2/neu status (P < 0.0001) were significant predictive factors among the study participants. The results from this study provide relevant evidence for a significant positive and potential association between certain risk factors and the prevalence of breast cancer among Iraqi women.

Keywords: Ductal Breast Cancer, Hormone Sensitivity, Iraq, Risk Factors

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Authors: Fiona Jensen, Barb Goodwin, Nancy Kleiman, Rhonda Usunier

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Background: Clinical simulation is now a common component in many health profession curricula in preparation for clinical practice. In the Rady Faculty of Health Sciences (RFHS) college leads in simulation and interprofessional (IP) education, planned an eight hour simulated hospital day shift, where seventy students from six health professions across two campuses, learned with each other in a safe, realistic environment. Learning about interprofessional collaboration, an expected competency for many health professions upon graduation, was a primary focus of the simulation event. Method: Faculty representatives from the Colleges of Nursing, Medicine, Pharmacy and Rehabilitation Sciences (Physical Therapy, Occupation Therapy, Respiratory Therapy) and Pharmacy worked together to plan the IP event in a simulation facility in the College of Nursing. Each college provided a faculty mentor to guide the same profession students. Students were placed in interprofessional teams consisting of a nurse, physician, pharmacist, and then sharing respiratory, occupational, and physical therapists across the team depending on the needs of the patients. Eight patient scenarios were role played by health profession students, who had been provided with their patient’s story shortly before the event. Each team was guided by a facilitator. Results and Outcomes: On the morning of the event, all students gathered in a large group to meet mentors and facilitators and have a brief overview of the six competencies for effective collaboration and the session objectives. The students assuming their same profession roles were provided with their patient’s chart at the beginning of the shift, met with their team, and then completed professional specific assessments. Shortly into the shift, IP team rounds began, facilitated by the team facilitator. During the shift, each patient role-played a spontaneous health incident, which required collaboration between the IP team members for assessment and management. The afternoon concluded with team rounds, a collaborative management plan, and a facilitated de-brief. Conclusions: During the de-brief sessions, students responded to set questions related to the session learning objectives and expressed many positive learning moments. We believe that we have a sustainable simulation IP collaborative learning opportunity, which can be embedded into curricula, and has the capacity to grow to include more health profession faculties and students. Opportunities are being explored in the RFHS at the administrative level, to offer this event more frequently in the academic year to reach more students. In addition, a formally structured event evaluation tool would provide important feedback and inform the qualitative feedback to event organizers and the colleges about the significance of the simulation event to student learning.

Keywords: simulation, collaboration, teams, interprofessional

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Authors: Nina Dzamashvili Fogelström

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This paper examines concepts of Game-Based Learning and Gamification. Conducted literature survey found an increased interest in the academia in these concepts, limited evidence of a positive effect on student motivation and academic performance, but also certain scepticism for adding games to traditional educational activities. A small-scale empirical study presented in this paper aims to evaluate student experience and usefulness of GameBased Learning and Gamification for a better understanding of the threshold concepts in software engineering project courses. The participants of the study were 22 second year students from bachelor’s program in software engineering at Blekinge Institute of Technology. As a part of the course instruction, the students were introduced to a digital game specifically designed to simulate agile software project. The game mechanics were designed as to allow manipulation of the agile concept of team velocity. After the application of the game, the students were surveyed to measure the degree of a perceived increase in understanding of the studied threshold concept. The students were also asked whether they would like to have games included in their education. The results show that majority of the students found the game helpful in increasing their understanding of the threshold concept. Most of the students have indicated that they would like to see games included in their education. These results are encouraging. Since the study was of small scale and based on convenience sampling, more studies in the area are recommended.

Keywords: agile development, gamification, game based learning, digital games, software engineering, threshold concepts

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Authors: Paula Escudeiro, Nuno Escudeiro, Márcia Campos, Francisca Escudeiro

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In today's world, technical and scientific knowledge plays a vital role in education, research, and employment. Deaf students face unique challenges in educational settings, particularly when it comes to understanding technical and scientific terminology. The reliance on written and spoken languages can create barriers for deaf individuals who primarily communicate using sign language. This lack of accessibility can hinder their learning experience and compromise equity in education. To address this issue, the TechWhiz project has been developed as a comprehensive glossary of scientific and technical concepts explained in sign language. By providing deaf students with access to education in their first language, TechWhiz aims to enhance their learning achievements and promote inclusivity while also fostering equity in education for all students.

Keywords: deaf students, technical and scientific knowledge, automatic sign language, inclusive education

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Authors: Ece Kaya

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Urban waterfront re-development is a well-established phenomenon internationally since 1960s. In cities throughout the world, old industrial waterfront land is being redeveloped into luxury housing, offices, tourist attractions, cultural amenities and shopping centres. These developments are intended to attract high-income residents, tourists and investors to the city. As urban waterfronts are iconic places for the cities and catalyst for further development. They are often referred as flagship project. In Sydney, the re-development of industrial waterfront has been exposed since 1980s with Darling Harbour Project. Darling Harbour waterfront used to be the main arrival and landing place for commercial and industrial shipping until 1970s. Its urban development has continued since the establishment of the city. It was developed as a major industrial and goods-handling precinct in 1812. This use was continued by the mid-1970s. After becoming a redundant industrial waterfront, the area was ripe for re-development in 1984. Darling Harbour is now one of the world’s fascinating waterfront leisure and entertainment destinations and its transformation has been considered as a success story. It is a contradictory statement for this paper. Data collection was carried out using an extensive archival document analysis. The data was obtained from Australian Institute of Architects, City of Sydney Council Archive, Parramatta Heritage Office, Historic Houses Trust, National Trust, and University of Sydney libraries, State Archive, State Library and Sydney Harbour Foreshore Authority Archives. Public documents, primarily newspaper articles and design plans, were analysed to identify possible differences in motives and to determine the process of implementation of the waterfront redevelopments. It was also important to obtain historical photographs and descriptions to understand how the waterfront had been altered. Sites maps in different time periods have been identified to understand what kind of changes happened on the urban landscape and how the developments affected areas. Newspaper articles and editorials have been examined in order to discover what aspects of the projects reflected the history and heritage. The thematic analysis of the archival data helped determine Darling Harbour is a historically important place as it had represented a focal point for Sydney's industrial growth and the cradle of industrial development in European Australia. It has been found that the development area was designated in order to be transformed to a place for tourist, education, recreational, entertainment, cultural and commercial activities and as a result little evidence remained of its industrial past. This paper aims to discuss the industrial significance of Darling Harbour and to explain the changes on its industrial landscape. What is absent now is the layer of its history that creates the layers of meaning to the place so its historic industrial identity is effectively lost.

Keywords: historical significance, industrial heritage, industrial waterfront, re-development

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Authors: Paras Agarwal

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Background: Initially believed to be rare, metastases to the eye are the most common ocular malignancy. The choroid’s high perfusion rate not only makes it the most susceptible ocular site for tumour seeding, but also promotes its growth. The cancers most frequently responsible for choroidal metastases originate from the breast and lung, although a significant proportion have unidentified primaries at the time of presentation. Case Presentation: This case report describes a 34 year old female presenting to the ophthalmology department with a one month history of painless distorted vision. On fundus examination, she was noted to have bilateral choroidal lesionsand subsequently underwent a comprehensive diagnostic work-up. The patient was diagnosed with metastatic pulmonary adenocarcinoma, despite lacking conventional risk factors. As she was found to have a mutation in EGFR, the patient was commenced on tyrosine-kinase inhibition with afatinib. The choroidal lesions regressed with a significant improvement in visual acuity and a dramatic anatomical reduction of the choroidal masses. Conclusions: Our case demonstrates the importance of considering metastases as a differential diagnosis for choroidal lesions. Appropriate and thorough history-taking, examination and investigations may be required in order to deduce the underlying cause. Our case is unusual in view of the choroidal lesion being the primary manifestation of metastatic lung cancer in a young patient with no known risk factors. Early recognition of choroidal metastases is important as it is often the first sign of tumour dissemination and will prompt earlier treatment with systemic medications such as chemotherapy, immunotherapy, targeted therapy or hormonal therapy. Our case report also demonstrates the efficacy of afatinib for the treatment of choroidal metastases, with morphological and functional improvements observed with regard to the choroidal metastatic tumour.

Keywords: choroidal neoplasm, choroidal naevus, pulmonary adenocarcinoma, metastases, lung cancer

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