Search results for: word learning

Authors: Sarwat un Nisa

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One of the remarkable gifts that a human being is blessed with is the ability to speak using a combination of sounds. Different combinations of sounds combine to form a word which in turn make a sentence and therefore give birth to a language. A person can either be a monolingual, i.e., can speak one language or bilingual, i.e., can speak more than one language. Whether a person speaks one language or multiple languages or in whatever language a person speaks, the main aim is to communicate, express ideas, feelings or thoughts. Sometimes the choice of a language is deliberate and sometimes it is a habitual act. The language which is used to put our ideas across speaks many things about our cultural, linguistic and ethnic identities. It can never be claimed that bilinguals are better than monolinguals in terms of linguistic skills, bilinguals or multilinguals have more than one language at their disposal. Therefore, how effectively two languages are used by the same person keeps linguists always intrigued. The most prominent and common features found in the speech of bilingual speakers are code switching and code mixing. The aim of the present paper is to explore these features among the adolescent speakers of Kashmir. The reason for studying the linguistics behavior of adolescents is the age when a person is neither an adult nor a child. They want to drift away from the norms and make a new norm for themselves. Therefore, how their linguistics skills are influenced by their age is of great interest because it can set the trend for the future generation. Kashmir is a multilingual society where three languages, i.e., Kashmiri, Urdu, and English are regularly used by the speakers, especially the educated ones. Kashmiri is widely used at home or mostly among adults. Urdu is the official language, and English is used in schools and for most of the written official correspondences. Thus, it is not uncommon to find these three languages coming in contact with each other quite frequently. The language contact results in the code switching and code mixing. In this paper different aspects of code switching and code mixing are discussed. Research Method: The data were collected from the different districts of Kashmir. The informants did not have prior knowledge of the survey. The situation was spontaneous and natural. The topics were introduced by the interviewer to the group of informants which comprised of three participants. They were asked to discuss the topic, most of the times without any intervention of the interviewer. Along with conversations, the informants also filled in written questionnaires comprising sociolinguistic questions. Questionnaires were analysed to get an idea about the sociolinguistic attitude of the informants. Percentage, frequency, and average were used as statistical tools to analyse the data. Conclusions were drawn taking into consideration of interpretations of both speech samples and questionnaires.

Keywords: code mixing, code switching, Kashmir, bilingualism

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Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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Authors: Juliane Toce, Steven Holochwost

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A substantial and growing literature has demonstrated that arts education benefits young children’s socioemotional and cognitive development. Less is known about the capacity of arts-integrated instruction to yield benefits to similar domains, particularly among demographically and socioeconomically diverse groups of young children. However, the small literature on this topic suggests that arts-integrated instruction may foster young children’s socioemotional and cognitive development by presenting opportunities to 1) engage in instructional content in diverse ways, 2) experience and regulate strong emotions, 3) experience growth-oriented feedback, and 4) engage in collaborative work with peers. Start with the Art is a new program of arts-integrated instruction currently being implemented in four schools in a school district that serves students from a diverse range of backgrounds. The program employs a co-teaching model in which teaching artists and classroom teachers engage in collaborative lesson planning and instruction over the course of the academic year and is currently the focus of an impact study featuring a randomized-control design, as well as an implementation study, both of which are funded through an Educational Innovation and Research grant from the United States Department of Education. The paper will present the early results from the Start with the Art implementation study. These results will provide an overview of the extent to which the program was implemented in accordance with design, with a particular emphasis on the degree to which the four opportunities enumerated above (e.g., opportunities to engage in instructional content in diverse ways) were presented to students. There will be a review key factors that may influence the fidelity of implementation, including classroom teachers’ reception of the program and the extent to which extant conditions in the classroom (e.g., the overall level of classroom organization) may have impacted implementation fidelity. With the explicit purpose of creating a program that values and meets the needs of the teachers and students, Start with the Art incorporates the feedback from individuals participating in the intervention. Tracing its trajectory from inception to ongoing development and examining the adaptive changes made in response to teachers' transformative experiences in the post-pandemic classroom, Start with the Art continues to solicit input from experts in integrating artistic content into core curricula within educational settings catering to students from under-represented backgrounds in the arts. Leveraging the input from this rich consortium of experts has allowed for a comprehensive evaluation of the program’s implementation. The early findings derived from the implementation study emphasize the potential of arts-integrated instruction to incorporate restorative practices. Such practices serve as a crucial support system for both students and educators, providing avenues for children to express themselves, heal emotionally, and foster social development, while empowering teachers to create more empathetic, inclusive, and supportive learning environments. This all-encompassing analysis spotlights Start with the Art’s adaptability to any learning environment through the program’s effectiveness, resilience, and its capacity to transform - through art - the classroom experience within the ever-evolving landscape of education.

Keywords: arts-integration, social emotional learning, diverse learners, co-teaching, teaching artists, post-pandemic teaching

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Authors: Abdul Rawuf Hussein, Rusnani Abdul Kadir, Mona Adlina Binti Adanan

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Guidance program has been an essential approach in helping professions from many institutions of learning as well as communities, organizations, and clinical settings. Although the term varies depending on the approaches, objectives, and theories, the core and central element is typically developmental in nature. In this conceptual paper, the researcher will review literature on the concept of group guidance, its impact on students’ and individual’s development, developing a guidance module and proposing a synthesised framework for group guidance program.

Keywords: concept, framework, group guidance, module development

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Authors: Steven W. Carruthers

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The purpose of the present research is to equate two test forms as part of a study to evaluate the educational effectiveness of the ARTé: Mecenas art history learning game. The researcher applied Item Response Theory (IRT) procedures to calculate item, test, and mean-sigma equating parameters. With the sample size n=134, test parameters indicated “good” model fit but low Test Information Functions and more acute than expected equating parameters. Therefore, the researcher applied equipercentile equating and linear equating to raw scores and compared the equated form parameters and effect sizes from each method. Item scaling in IRT enables the researcher to select a subset of well-discriminating items. The mean-sigma step produces a mean-slope adjustment from the anchor items, which was used to scale the score on the new form (Form R) to the reference form (Form Q) scale. In equipercentile equating, scores are adjusted to align the proportion of scores in each quintile segment. Linear equating produces a mean-slope adjustment, which was applied to all core items on the new form. The study followed a quasi-experimental design with purposeful sampling of students enrolled in a college level art history course (n=134) and counterbalancing design to distribute both forms on the pre- and posttests. The Experimental Group (n=82) was asked to play ARTé: Mecenas online and complete Level 4 of the game within a two-week period; 37 participants completed Level 4. Over the same period, the Control Group (n=52) did not play the game. The researcher examined between group differences from post-test scores on test Form Q and Form R by full-factorial Two-Way ANOVA. The raw score analysis indicated a 1.29% direct effect of form, which was statistically non-significant but may be practically significant. The researcher repeated the between group differences analysis with all three equating methods. For the IRT mean-sigma adjusted scores, form had a direct effect of 8.39%. Mean-sigma equating with a small sample may have resulted in inaccurate equating parameters. Equipercentile equating aligned test means and standard deviations, but resultant skewness and kurtosis worsened compared to raw score parameters. Form had a 3.18% direct effect. Linear equating produced the lowest Form effect, approaching 0%. Using linearly equated scores, the researcher conducted an ANCOVA to examine the effect size in terms of prior knowledge. The between group effect size for the Control Group versus Experimental Group participants who completed the game was 14.39% with a 4.77% effect size attributed to pre-test score. Playing and completing the game increased art history knowledge, and individuals with low prior knowledge tended to gain more from pre- to post test. Ultimately, researchers should approach test equating based on their theoretical stance on Classical Test Theory and IRT and the respective  assumptions. Regardless of the approach or method, test equating requires a representative sample of sufficient size. With small sample sizes, the application of a range of equating approaches can expose item and test features for review, inform interpretation, and identify paths for improving instruments for future study.

Keywords: effectiveness, equipercentile equating, IRT, learning games, linear equating, mean-sigma equating

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Authors: Konstantina Georgali

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The present study explores Greek teachers’ understandings of typical language development and of language difficulties. Its core aim was to highlight that teachers need to have a thorough understanding of educational linguistics, that is of how language figures in education. They should also be aware of how language should be taught so as to promote language development for all students while at the same time support the needs of children with language difficulties in an inclusive ethos. The study, thus argued that language can be a dynamic learning mechanism in the minds of all children and a powerful teaching tool in the hands of teachers and provided current research evidence to show that structural and morphological particularities of native languages- in this case, of the Greek language- can be used by teachers to enhance children’s understanding of language and simultaneously improve oral language skills for children with typical language development and for those with language difficulties. The research was based on a Sequential Exploratory Mixed Methods Design deployed in three consecutive and integrative phases. The first phase involved 18 exploratory interviews with teachers. Its findings informed the second phase involving a questionnaire survey with 119 respondents. Contradictory questionnaire results were further investigated in a third phase employing a formal testing procedure with 60 children attending Y1, Y2 and Y3 of primary school (a research group of 30 language impaired children and a comparison group of 30 children with typical language development, both identified by their class teachers). Results showed both strengths and weaknesses in teachers’ awareness of educational linguistics and of language difficulties. They also provided a different perspective of children’s language needs and of language teaching approaches that reflected current advances and conceptualizations of language problems and opened a new window on how best they can be met in an inclusive ethos. However, teachers barely used teaching approaches that could capitalize on the particularities of the Greek language to improve language skills for all students in class. Although they seemed to realize the importance of oral language skills and their knowledge base on language related issues was adequate, their practices indicated that they did not see language as a dynamic teaching and learning mechanism that can promote children’s language development and in tandem, improve academic attainment. Important educational implications arose and clear indications of the generalization of findings beyond the Greek educational context.

Keywords: educational linguistics, inclusive ethos, language difficulties, typical language development

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Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

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Authors: Zeinabsadat Haghshenas

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Bloom’s Taxonomy has been changed during the years. The idea of this writing is about the revision that has happened in both facts and terms. It also contains case studies of using cognitive Bloom’s taxonomy in teaching geometric solids to the secondary school students, affective objectives in a creative workshop for adults and psychomotor objectives in fixing a malfunctioned refrigerator lamp. There is also pointed to the important role of classification objectives in adult education as a way to prevent memory loss.

Keywords: adult education, affective domain, cognitive domain, memory loss, psychomotor domain

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Authors: Miraji H. Mohamed

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The purpose of this study is to critique ‘radicalisation’ and more particularly ‘youth radicalisation’ by exploring its usage in online newspapers. ‘Radicalisation’ and ‘extremism’ have become the most common terms in terrorism studies since the 9/11 attacks. Regardless of the geographic location, when the word terrorism is used the terms ‘radicalisation’ and ‘extremism’ always follow to attempt to explore the journey of the perpetrators towards violence. These terms have come to represent a discourse of dominantly pejorative traits often used to describe spaces, groups, and processes identified as problematic. Even though ambiguously defined they feature widely in government documents, political statements, news articles, academic research, social media platforms, religious gatherings, and public discussions. Notably, ‘radicalisation’ and ‘extremism’ have been closely conflated with the term youth to form ‘youth radicalisation’ to refer to a discourse of ‘youth at risk’. The three terms largely continue to be used unquestioningly and interchangeably hence the reason why they are placed in single quotation marks to deliberately question their conventional usage. Albeit this comes timely in the Kenyan context where there has been a proliferation of academic and expert research on ‘youth radicalisation’ (used as a neutral label) without considering the political, cultural and socio-historical contexts that inform this label. This study seeks to draw these nuances by employing a genealogical approach that historicises and deconstructs ‘youth radicalisation’; and by applying a Discourse-Historical Approach (DHA) of Critical Discourse Analysis to analyse Kenyan online newspaper - The Daily Nation between 2015 and 2018. By applying the concept of representation to analyse written texts, the study reveals that the use of ‘youth radicalisation’ as a discursive strategy disproportionately affects young people especially those from cultural/ethnic/religious minority groups. Also, the ambiguous use of ‘radicalisation’ and ‘youth radicalisation’ by the media reinforces the discourse of ‘youth at risk’ which has become the major framework underpinning Countering Violent Extremism (CVE) interventions. Similarly, the findings indicate that the uncritical use of ‘youth radicalisation’ has been used to serve political interests; and has become an instrument of policing young people, thus contributing to their cultural shaping. From this, it is evident that the media could thwart rather than assist CVE efforts. By exposing the political nature of the three terms through evidence-based research, this study offers recommendations on how critical reflective reporting by the media could help to make CVE more nuanced.

Keywords: discourse, extremism, radicalisation, terrorism, youth

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Authors: Sylvia Nkiru Ogbuoji

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This paper discussed the consequences of inadequate funding in Nigerian education system. It briefly explained the meaning of education in relation to the context and identified various ways education in Nigeria can be funded. It highlighted some of the consequences of inadequate funding education system to include: Inadequate facilitates for teaching and learning, western brain drain, unemployment, crises of poverty, low staff morale it. Finally, some recommendations were put forward, the government should improve the annual budget allocation to education, in order to achieve educational objective, also government should monitor the utilization of allocated funds to minimize embezzlement.

Keywords: consequences, corruption, education, funding

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Authors: Yolanda Ramirez, Angel Tejada, Agustin Baidez

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In the knowledge-based economy, intangible elements are considered essential in order to achieve competitive advantage in organizations. In this sense, the Balanced Scorecard is a very suitable tool to recognize value and manage intangibles because it translates an organization’s strategic objectives into a set of performance indicators from a financial, as well as customer perspective, internal process and learning and growth perspectives. The aim of this paper is to expose and justify the benefits that the Balanced Scorecard might have for identifying, measuring and managing intellectual capital at universities, by means of reviewing the most important Balanced Scorecard implementations at Spanish public universities.

Keywords: knowledge management, balanced scorecard, universities, Spain

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Authors: Sajjad Ali

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The Quranic pedagogical methods don't imply that the Quran explicitly prescribes teaching methods. Instead, it acknowledges the inherent ways of learning and teaching that align with human nature, offering guidance in this direction. Qur'an briefly describes different angles of acquiring knowledge. Narrative, interrogative, question, analytical, poetic, comparative and critical methods of teaching are briefly described in the Holy Quran. The Muslim Ummah has a firm belief that the Qur'an is a comprehensive book which mentions every dry and wet, but this does not mean that the Qur'an is a manual book. This means that the Qur'an contains symbols and hints about everything. The fact that everything is mentioned in the Qur'an means that the Qur'an only provides guidance, while its interpretation requires contemplation.

Keywords: hadith, knowledge, reality, understanding

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Authors: Danielle L. Iamarino

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This paper explores the embattled territory of academic creative writing—and most focally, the use of critical theory in the teaching and structuring of creative practice. It places creative writing in contemporary social, cultural, and otherwise anthropological contexts, and evaluates conventional creative writing pedagogies based on how well they serve the updated needs of increasingly diverse student congregations. With continued emphasis on student-centered learning, this paper compares theoretical to practical applications of discipline-specific knowledge, examining and critiquing theory in terms of its relevance, accessibility, and whether or not it is both actionable and beneficial in the creative writing classroom.

Keywords: creative writing, literary theory, content, pedagogy, workshop, teaching

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Authors: Joanna Estkowska

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The Sensory Integration Method is aimed primarily at children with learning disabilities. It can also be used as a complementary method in treatment of children with cerebral palsy, autistic, mentally handicapped, blind and deaf. Autism is holistic development disorder that manifests itself in the specific functioning of a child. The most characteristic are: disorders in communication, difficulties in social relations, rigid patterns of behavior and impairment in sensory processing. In addition to these disorders may occur abnormal intellectual development, attention deficit disorders, perceptual disorders and others. This study was focused on the application sensory integration techniques in science education of autistic students. The lack of proper sensory integration causes problems with complicated processes such as motor coordination, movement planning, visual or auditory perception, speech, writing, reading or counting. Good functioning and cooperation of proprioceptive, tactile and vestibular sense affect the child’s mastery of skills that require coordination of both sides of the body and synchronization of the cerebral hemispheres. These include, for example, all sports activities, precise manual skills such writing, as well as, reading and counting skills. All this takes place in stages. Achieving skills from the first stage determines the development of fitness from the next level. Any deficit in the scope of the first three stages can affect the development of new skills. This ultimately reflects on the achievements at school and in further professional and personal life. After careful analysis symptoms from the emotional and social spheres appear to be secondary to deficits of sensory integration. During our research, the students gained knowledge and skills in the classroom of experience by learning biology, chemistry and physics with application sensory integration techniques. Sensory integration therapy aims to teach the child an adequate response to stimuli coming to him from both the outside world and the body. Thanks to properly selected exercises, a child can improve perception and interpretation skills, motor skills, coordination of movements, attention and concentration or self-awareness, as well as social and emotional functioning.

Keywords: autism spectrum disorder, science education, sensory integration, special educational needs

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Authors: Sultan Çağırıcı, Arsida Bajrami, Beyza Aslan, Hacı Ali Erdoğan, Nejla Sözer Topçular, Dilek Bozkurt, Vildan Yayla

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Objective: Corticobasal syndrome (CBS) is phenotypically characterized by asymmetric rigidity, apraxia, alien-limb phenomenon, cortical sensory loss, dystonia and myoclonus. The underlying pathologies consists of corticobasal degeneration (CBD), progressive supra nuclear palsy, Alzheimer's, Creutzfeldt-Jakob and frontotemporal degeneration. CBD is a degenerative disease with clinical symptoms related to the prominent involvement of cerebral cortex and basal ganglia. CBD is a pathological diagnosis and antemortem clinical diagnosis may change many times. In this paper, we described the clinical features and discussed a cases diagnosed with symmetric CBS because of its rarity. Case: Seventy-five-year-old woman presented with a three years history of difficulty in speaking and reading. Involuntary hand jerks and slowness of movement also had began in the last six months. In the neurological examination the patient was alert but not fully oriented. The speech was non-fluent, word finding difficulties were present. Bilateral limited upgaze, bradimimia, bilateral positive cogwheel' rigidity but prominent in the right side, postural tremor and negative myoclonus during action on the left side were detected. Receptive language was normal but expressive language and repetition were impaired. Acalculia, alexia, agraphia and apraxia were also present. CSF findings were unremarkable except for elevated protein level (75 mg/dL). MRI revealed bilateral symmetric cortical atrophy prominent in the frontoparietal region. PET showed hypometabolism in the left caudate nucleus. Conclusion: The increase of data related to neurodegenerative disorders associated with dementia, movement disorders and other findings results in an expanded range of diagnosis and transitions between clinical diagnosis. When considered the age of onset, clinical symptoms, imaging findings and prognosis of this patient, clinical diagnosis was CBS and pathologic diagnosis as probable CBD. Imaging of CBD usually consist of typical asymmetry between hemispheres. Still few cases with clinical appearance of CBD may show symmetrical cortical cerebral atrophy. It is presented this case who was diagnosed with CBD although we found symmetrical cortical cerebral atrophy in MRI.

Keywords: symmetric cortical atrophy, corticobasal degeneration, corticobasal syndrome

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Authors: Angelis P. Barlampas

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The purpose of this study is to inform the reader, about the various applications of artificial intelligence (AI), in cardiac imaging. AI grows fast and its role is crucial in medical specialties, which use large amounts of digital data, that are very difficult or even impossible to be managed by human beings and especially doctors.Artificial intelligence (AI) refers to the ability of computers to mimic human cognitive function, performing tasks such as learning, problem-solving, and autonomous decision making based on digital data. Whereas AI describes the concept of using computers to mimic human cognitive tasks, machine learning (ML) describes the category of algorithms that enable most current applications described as AI. Some of the current applications of AI in cardiac imaging are the follows: Ultrasound: Automated segmentation of cardiac chambers across five common views and consequently quantify chamber volumes/mass, ascertain ejection fraction and determine longitudinal strain through speckle tracking. Determine the severity of mitral regurgitation (accuracy > 99% for every degree of severity). Identify myocardial infarction. Distinguish between Athlete’s heart and hypertrophic cardiomyopathy, as well as restrictive cardiomyopathy and constrictive pericarditis. Predict all-cause mortality. CT Reduce radiation doses. Calculate the calcium score. Diagnose coronary artery disease (CAD). Predict all-cause 5-year mortality. Predict major cardiovascular events in patients with suspected CAD. MRI Segment of cardiac structures and infarct tissue. Calculate cardiac mass and function parameters. Distinguish between patients with myocardial infarction and control subjects. It could potentially reduce costs since it would preclude the need for gadolinium-enhanced CMR. Predict 4-year survival in patients with pulmonary hypertension. Nuclear Imaging Classify normal and abnormal myocardium in CAD. Detect locations with abnormal myocardium. Predict cardiac death. ML was comparable to or better than two experienced readers in predicting the need for revascularization. AI emerge as a helpful tool in cardiac imaging and for the doctors who can not manage the overall increasing demand, in examinations such as ultrasound, computed tomography, MRI, or nuclear imaging studies.

Keywords: artificial intelligence, cardiac imaging, ultrasound, MRI, CT, nuclear medicine

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Authors: Mei Xuan Tan, Gim-Yang Maggie Pee, Mei Chee Tan

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Academic performance, in the form of scoring high grades in enrolled subjects, is not the only significant trait in achieving success. Engineering graduates with experience in working on hands-on projects in a team setting are highly sought after in industry upon graduation. Such projects are typically real world problems that require the integration and application of knowledge and skills from several disciplines. In a traditional university setting, subjects are taught in a silo manner with no cross participation from other departments or disciplines. This may lead to knowledge compartmentalization and students are unable to understand and connect the relevance and applicability of the subject. University instructors thus see this integration across disciplines as a challenging task as they aim to better prepare students in understanding and solving problems for work or future studies. To improve students’ academic performance and to cultivate various skills such as critical thinking, there has been a gradual uptake in the use of an active learning approach in introductory science and engineering courses, where lecturing is traditionally the main mode of instruction. This study aims to discuss the implementation and experience of a hands-on, interdisciplinary project that involves all the four core subjects taught during the term at the Singapore University of Technology Design (SUTD). At SUTD, an interdisciplinary design activity, named 2D, is integrated into the curriculum to help students reinforce the concepts learnt. A student enrolled in SUTD experiences his or her first 2D in Term 1. This activity. which spans over one week in Week 10 of Term 1, highlights the application of chemistry, physics, mathematics, humanities, arts and social sciences (HASS) in designing an engineering product solution. The activity theme for Term 1 2D revolved around “work and play”. Students, in teams of 4 or 5, used a scaled-down model of a chemical launcher to launch a projectile across the room. It involved the use of a small chemical combustion reaction between ethanol (a highly volatile fuel) and oxygen. This reaction generated a sudden and large increase in gas pressure built up in a closed chamber, resulting in rapid gas expansion and ejection of the projectile out of the launcher. Students discussed and explored the meaning of play in their lives in HASS class while the engineering aspects of a combustion system to launch an object using underlying principles of energy conversion and projectile motion were revisited during the chemistry and physics classes, respectively. Numerical solutions on the distance travelled by the projectile launched by the chemical launcher, taking into account drag forces, was developed during the mathematics classes. At the end of the activity, students developed skills in report writing, data collection and analysis. Specific to this 2D activity, students gained an understanding and appreciation on the application and interdisciplinary nature of science, engineering and HASS. More importantly, students were exposed to design and problem solving, where human interaction and discussion are important yet challenging in a team setting.

Keywords: active learning, collaborative learning, first year undergraduate, interdisciplinary, STEAM

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Authors: Rizky Dwi A, Mikha Herlina Pi

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Physics lessons for high school students, especially in Indonesia is less desirable because many people believe that physics is very difficult, especially the development of increasingly sophisticated era make online gaming more attractive many people especially school children with a variety of increasingly sophisticated gadgets. Therefore, if those two things combined to attract students in physics, the physics-based educational game android can motivate students' interest and understanding of the physics because while playing, they can also learn physics.

Keywords: education, game physics, interest, student's motivation

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Authors: Zahid Ullah, Atlas Khan

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The rapid growth of data in diverse domains has created an urgent need for effective utilization of mathematical and statistical sciences in data analytics. This abstract explores the journey from theory to practice, emphasizing the importance of harnessing mathematical and statistical innovations to unlock the full potential of data analytics. Drawing on a comprehensive review of existing literature and research, this study investigates the fundamental theories and principles underpinning mathematical and statistical sciences in the context of data analytics. It delves into key mathematical concepts such as optimization, probability theory, statistical modeling, and machine learning algorithms, highlighting their significance in analyzing and extracting insights from complex datasets. Moreover, this abstract sheds light on the practical applications of mathematical and statistical sciences in real-world data analytics scenarios. Through case studies and examples, it showcases how mathematical and statistical innovations are being applied to tackle challenges in various fields such as finance, healthcare, marketing, and social sciences. These applications demonstrate the transformative power of mathematical and statistical sciences in data-driven decision-making. The abstract also emphasizes the importance of interdisciplinary collaboration, as it recognizes the synergy between mathematical and statistical sciences and other domains such as computer science, information technology, and domain-specific knowledge. Collaborative efforts enable the development of innovative methodologies and tools that bridge the gap between theory and practice, ultimately enhancing the effectiveness of data analytics. Furthermore, ethical considerations surrounding data analytics, including privacy, bias, and fairness, are addressed within the abstract. It underscores the need for responsible and transparent practices in data analytics, and highlights the role of mathematical and statistical sciences in ensuring ethical data handling and analysis. In conclusion, this abstract highlights the journey from theory to practice in harnessing mathematical and statistical sciences in data analytics. It showcases the practical applications of these sciences, the importance of interdisciplinary collaboration, and the need for ethical considerations. By bridging the gap between theory and practice, mathematical and statistical sciences contribute to unlocking the full potential of data analytics, empowering organizations and decision-makers with valuable insights for informed decision-making.

Keywords: data analytics, mathematical sciences, optimization, machine learning, interdisciplinary collaboration, practical applications

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Authors: S. Jamshidi, E. Feizi Ashtiani, M. Ardestani, A. Feizi Ashtiani

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Waste load allocation (WLA) strategies usually intend to find economical policies for water resource management. Water quality trading (WQT) is an approach that uses discharge permit market to reduce total environmental protection costs. This primarily requires assigning discharge limits known as total maximum daily loads (TMDLs). These are determined by monitoring organizations with respect to the receiving water quality and remediation capabilities. The purpose of this study is to compare two approaches of TMDL assignment for WQT policy in small catchment area of Haraz River, in north of Iran. At first, TMDLs are assigned uniformly for the whole point sources to keep the concentrations of BOD and dissolved oxygen (DO) at the standard level at checkpoint (terminus point). This was simply simulated and controlled by Qual2kw software. In the second scenario, TMDLs are assigned using multi objective particle swarm optimization (MOPSO) method in which the environmental violation at river basin and total treatment costs are minimized simultaneously. In both scenarios, the equity index and the WLA based on trading discharge permits (TDP) are calculated. The comparative results showed that using economically optimized TMDLs (2nd scenario) has slightly more cost savings rather than uniform TMDL approach (1st scenario). The former annually costs about 1 M$ while the latter is 1.15 M$. WQT can decrease these annual costs to 0.9 and 1.1 M$, respectively. In other word, these approaches may save 35 and 45% economically in comparison with command and control policy. It means that using multi objective decision support systems (DSS) may find more economical WLA, however its outcome is not necessarily significant in comparison with uniform TMDLs. This may be due to the similar impact factors of dischargers in small catchments. Conversely, using uniform TMDLs for WQT brings more equity that makes stakeholders not feel that much envious of difference between TMDL and WQT allocation. In addition, for this case, determination of TMDLs uniformly would be much easier for monitoring. Consequently, uniform TMDL for TDP market is recommended as a sustainable approach. However, economical TMDLs can be used for larger watersheds.

Keywords: waste load allocation (WLA), water quality trading (WQT), total maximum daily loads (TMDLs), Haraz River, multi objective particle swarm optimization (MOPSO), equity

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Authors: Jaehyung An, Sungjoo Lee

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Patent documents constitute an up-to-date and reliable source of knowledge for reflecting technological advance, so patent analysis has been widely used for identification of technological trends and formulation of technology strategies. But, identifying technological information from patent data entails some limitations such as, high cost, complexity, and inconsistency because it rely on the expert’ knowledge. To overcome these limitations, researchers have applied to a quantitative analysis based on the keyword technique. By using this method, you can include a technological implication, particularly patent documents, or extract a keyword that indicates the important contents. However, it only uses the simple-counting method by keyword frequency, so it cannot take into account the sematic relationship with the keywords and sematic information such as, how the technologies are used in their technology area and how the technologies affect the other technologies. To automatically analyze unstructured technological information in patents to extract the semantic information, it should be transformed into an abstracted form that includes the technological key concepts. Specific sentence structure ‘SAO’ (subject, action, object) is newly emerged by representing ‘key concepts’ and can be extracted by NLP (Natural language processor). An SAO structure can be organized in a problem-solution format if the action-object (AO) states that the problem and subject (S) form the solution. In this paper, we propose the new methodology that can extract the SAO structure through technical elements extracting rules. Although sentence structures in the patents text have a unique format, prior studies have depended on general NLP (Natural language processor) applied to the common documents such as newspaper, research paper, and twitter mentions, so it cannot take into account the specific sentence structure types of the patent documents. To overcome this limitation, we identified a unique form of the patent sentences and defined the SAO structures in the patents text data. There are four types of technical elements that consist of technology adoption purpose, application area, tool for technology, and technical components. These four types of sentence structures from patents have their own specific word structure by location or sequence of the part of speech at each sentence. Finally, we developed algorithms for extracting SAOs and this result offer insight for the technology innovation process by providing different perspectives of technology.

Keywords: NLP, patent analysis, SAO, semantic-analysis

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Authors: Denise Levy, Anna Lucia C. H. Villavicencio

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Food irradiation is a processing and preservation technique to eliminate insects and parasites and reduce disease-causing microorganisms. Moreover, the process helps to inhibit sprouting and delay ripening, extending fresh fruits and vegetables shelf-life. Nevertheless, most Brazilian consumers seem to misunderstand the difference between irradiated food and radioactive food and the general public has major concerns about the negative health effects and environmental contamination. Society´s judgment and decision making are directly linked to perceived benefits and risks. The web-based project entitled ‘Scientific information about food irradiation: Internet as a tool to approach science and society’ was created by the Nuclear and Energetic Research Institute (IPEN), in order to offer an interdisciplinary approach to science education, integrating economic, ethical, social and political aspects of food irradiation. This project takes into account that, misinformation and unfounded preconceived ideas impact heavily on the acceptance of irradiated food and purchase intention by the Brazilian consumer. Taking advantage of the potential value of the Internet to enhance communication and education among general public, a research study was carried out regarding the possibilities and trends of Information and Communication Technologies among the Brazilian population. The content includes concepts, definitions and Frequently Asked Questions (FAQ) about processes, safety, advantages, limitations and the possibilities of food irradiation, including health issues, as well as its impacts on the environment. The project counts on eight self-instructional interactive web courses, situating scientific content in relevant social contexts in order to encourage self-learning and further reflections. Communication is a must to improve public understanding of science. The use of information technology for quality scientific divulgation shall contribute greatly to provide information throughout the country, spreading information to as many people as possible, minimizing geographic distances and stimulating communication and development.

Keywords: food irradiation, multimedia learning tools, nuclear science, society and education

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Authors: Hamad Aljassmi, Sangwon Han

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Various solutions for preventing construction defects have been suggested. However, a construction company may have difficulties adopting all these suggestions due to financial and practical constraints. Based on this recognition, this paper aims to identify the most significant defect causes and formulate their defect generation mechanism in order to help a construction company to set priorities of its defect prevention strategies. For this goal, we conducted a questionnaire survey of 106 industry professionals and identified five most significant causes including: (1) organizational culture, (2) time pressure and constraints, (3) workplace quality system, (4) financial constraints upon operational expenses and (5) inadequate employee training or learning opportunities.

Keywords: defect, quality, failure, risk

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Authors: Elena Ginghina

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There are two major categories of language acquisition: first and second language acquisition, which distinguish themselves in their learning process and in their ultimate attainment. However, in the case of a bilingual child, one of the languages he grows up with receives gradually the features of a second language. This phenomenon characterizes the successive first language acquisition, when the initial state of the child is already marked by another language. Nevertheless, the dominance of the languages can change throughout the life, if the exposure to language and the quality of the input are better in 2L1. Related to the exposure to language and the quality of the input, there are cases even at the simultaneous bilingualism, where the two languages although learned from birth one, differ from one another at some point. This paper aims to see, what makes a 2L1 to become a second language and under what circumstances can a L2 learner reach a native or a near native speaker level.

Keywords: bilingualism, first language acquisition, native speakers of German, second language acquisition

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Authors: Nilki Upathissa, Torin Wirasinghe

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This solution addresses the challenges faced by traditional bookstores and the limitations of digital media, striking a balance between the tactile experience of printed books and the convenience of modern technology. The book exchange system offers a sustainable alternative, empowering users to access a diverse range of books while promoting community engagement. The user-friendly interfaces incorporated into the book exchange system ensure a seamless and enjoyable experience for users. Intuitive features for book management, search, and messaging facilitate effortless exchanges and interactions between users. By streamlining the process, the system encourages readers to explore new books aligned with their interests, enhancing the overall reading experience. Central to the system's success is the hybrid recommendation engine, which leverages advanced technologies such as Long Short-Term Memory (LSTM) models. By analyzing user input, the engine accurately predicts genre preferences, enabling personalized book recommendations. The hybrid approach integrates multiple technologies, including user interfaces, machine learning models, and recommendation algorithms, to ensure the accuracy and diversity of the recommendations. The evaluation of the book exchange system with the hybrid recommendation engine demonstrated exceptional performance across key metrics. The high accuracy score of 0.97 highlights the system's ability to provide relevant recommendations, enhancing users' chances of discovering books that resonate with their interests. The commendable precision, recall, and F1score scores further validate the system's efficacy in offering appropriate book suggestions. Additionally, the curve classifications substantiate the system's effectiveness in distinguishing positive and negative recommendations. This metric provides confidence in the system's ability to navigate the vast landscape of book choices and deliver recommendations that align with users' preferences. Furthermore, the implementation of this book exchange system with a hybrid recommendation engine has the potential to revolutionize the way readers interact with printed books. By facilitating book exchanges and providing personalized recommendations, the system encourages a sense of community and exploration within the reading community. Moreover, the emphasis on sustainability aligns with the growing global consciousness towards eco-friendly practices. With its robust technical approach and promising evaluation results, this solution paves the way for a more inclusive, accessible, and enjoyable reading experience for book lovers worldwide. In conclusion, the developed book exchange system with a hybrid recommendation engine represents a progressive solution to the challenges faced by traditional bookstores and the limitations of digital media. By promoting sustainability, widening access to printed books, and fostering engagement with reading, this system addresses the evolving needs of book enthusiasts. The integration of user-friendly interfaces, advanced machine learning models, and recommendation algorithms ensure accurate and diverse book recommendations, enriching the reading experience for users.

Keywords: recommendation systems, hybrid recommendation systems, machine learning, data science, long short-term memory, recurrent neural network

Procedia PDF Downloads 75

Authors: Frank Fan

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PharmD (Doctor of Pharmacy) education has confronted an increasing challenge — curricular overload, a phenomenon resulting from the expansion of curricular requirements, as PharmD education strives to produce graduates who are practice-ready. The aftermath of the global pandemic has amplified the need for healthcare professionals, leading to a growing trend of assigning more responsibilities to them to address the global healthcare shortage. For instance, the pharmacist’s role has expanded to include not only compounding and distributing medication but also providing clinical services, including minor ailments management, patient counselling and vaccination. Consequently, PharmD programs have responded by continually expanding their curricula adding more requirements. While these changes aim to enhance the education and training of future professionals, they have also led to unintended consequences, including curricular overload, student burnout, and a potential decrease in program quality. To address the issue and ensure program quality, there is a growing need for evidence-based curriculum reforms. My research seeks to integrate Cognitive Load Theory, emerging machine learning algorithms within artificial intelligence (AI), and statistical approaches to develop a quantitative framework for optimizing curriculum design within the PharmD program at the University of Toronto, the largest PharmD program within Canada, to provide quantification and measurement of issues that currently are only discussed in terms of anecdote rather than data. This research will serve as a guide for curriculum planners, administrators, and educators, aiding in the comprehension of how the pharmacy degree program compares to others within and beyond the field of pharmacy. It will also shed light on opportunities to reduce the curricular load while maintaining its quality and rigor. Given that pharmacists constitute the third-largest healthcare workforce, their education shares similarities and challenges with other health education programs. Therefore, my evidence-based, data-driven curriculum analysis framework holds significant potential for training programs in other healthcare professions, including medicine, nursing, and physiotherapy.

Keywords: curriculum, curriculum analysis, health professions education, reflective writing, machine learning

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Authors: Hashem A. Alsamadani

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Identifying the level of job satisfaction has many positive benefits for both the worker and employer. The purpose of the study was to examine the overall level of job satisfaction among English as a Foreign Language (EFL) instructors. During the past years, multiple methods were utilized to collect data to determine the level of job satisfaction among teachers. This study was conducted using survey research method. A questionnaire was coded and analyzed using the SPSS. The findings revealed that the overall level of job satisfaction among EFL instructors is high. The study recommended improving conditions of instructors working at public universities so as to gain a high level of job satisfaction and improve outcomes of the teaching-learning process.

Keywords: job satisfaction, EFL teachers, Saudi Arabia, instruction

Procedia PDF Downloads 393

Authors: Ashwaq Alsulami, Jianhua Shao

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Various organisations often need to understand discussions on social media, such as what trending topics are and characteristics of the people engaged in the discussion. A number of approaches have been proposed to extract attributes that would characterise a discussion group. However, these approaches are largely based on supervised learning, and as such they require a large amount of labelled data. We propose an approach in this paper that does not require labelled data, but rely on lexical sources to detect meaningful attributes for online discussion groups. Our findings show an acceptable level of accuracy in detecting attributes for Twitter discussion groups.

Keywords: attributed community, attribute detection, community, social network

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Authors: Angelis P. Barlampas

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Objective: The confusion of terms is a common practice in many situations of the everyday life. But, in some circumstances, such as in medicine, the precise meaning of a word curries a critical role for the health of the patient. Fahr disease and Fahr syndrome are often falsely used interchangeably, but they are two different conditions with different physical histories of different etiology and different medical management. A case of the seldom Fahr disease is presented, and a comparison with the more common Fahr syndrome follows. Materials and method: A 72 years old patient came to the emergency department, complaining of some kind of non specific medal disturbances, like anxiety, difficulty of concentrating, and tremor. The problems had a long course, but he had the impression of getting worse lately, so he decided to check them. Past history and laboratory tests were unremarkable. Then, a computed tomography examination was ordered. Results: The CT exam showed bilateral, hyperattenuating areas of heavy, dense calcium type deposits in basal ganglia, striatum, pallidum, thalami, the dentate nucleus, and the cerebral white matter of frontal, parietal and iniac lobes, as well as small areas of the pons. Taking into account the absence of any known preexisting illness and the fact that the emergency laboratory tests were without findings, a hypothesis of the rare Fahr disease was supposed. The suspicion was confirmed with further, more specific tests, which showed the lack of any other conditions which could probably share the same radiological image. Differentiating between Fahr disease and Fahr syndrome. Fahr disease: Primarily autosomal dominant Symmetrical and bilateral intracranial calcifications The patient is healthy until the middle age Absence of biochemical abnormalities. Family history consistent with autosomal dominant Fahr syndrome :Earlier between 30 to 40 years old. Symmetrical and bilateral intracranial calcifications Endocrinopathies: Idiopathic hypoparathyroidism, secondary hypoparathyroidism, hyperparathyroidism, pseudohypoparathyroidism ,pseudopseudohypoparathyroidism, e.t.c The disease appears at any age There are abnormal laboratory or imaging findings. Conclusion: Fahr disease and Fahr syndrome are not the same illness, although this is not well known to the inexperienced doctors. As clinical radiologists, we have to inform our colleagues that a radiological image, along with the patient's history, probably implies a rare condition and not something more usual and prompt the investigation to the right route. In our case, a genetic test could be done earlier and reveal the problem, and thus avoiding unnecessary and specific tests which cost in time and are uncomfortable to the patient.

Keywords: fahr disease, fahr syndrome, CT, brain calcifications

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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