Search results for: self-supervised representation learning

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: Q. Ni, J. A. Serna, D. Holland, X. Wang

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The objective of this study is to develop Nuclear Magnetic Resonance (NMR) techniques to enhance bone related research applied on normal and disuse (Biglycan knockout) mice bone in vitro by using both low-field and high-field NMR simultaneously. It is known that the total amplitude of T₂ relaxation envelopes, measured by the Carr-Purcell-Meiboom-Gill NMR spin echo train (CPMG), is a representation of the liquid phase inside the pores. Therefore, the NMR CPMG magnetization amplitude can be transferred to the volume of water after calibration with the NMR signal amplitude of the known volume of the selected water. In this study, the distribution of mobile water, porosity that can be determined by using low-field (20 MHz) CPMG relaxation technique, and the pore size distributions can be determined by a computational inversion relaxation method. It is also known that the total proton intensity of magnetization from the NMR free induction decay (FID) signal is due to the water present inside the pores (mobile water), the water that has undergone hydration with the bone (bound water), and the protons in the collagen and mineral matter (solid-like protons). Therefore, the components of total mobile and bound water within bone that can be determined by low-field NMR free induction decay technique. Furthermore, the bound water in solid phase (mineral and organic constituents), especially, the dominated component of calcium hydroxyapatite (Ca₁₀(OH)₂(PO₄)₆) can be determined by using high-field (400 MHz) magic angle spinning (MAS) NMR. With MAS technique reducing NMR spectral linewidth inhomogeneous broadening and susceptibility broadening of liquid-solid mix, in particular, we can conduct further research into the ¹H and ³¹P elements and environments of bone materials to identify the locations of bound water such as OH- group within minerals and bone architecture. We hypothesize that with low-field and high-field magic angle spinning NMR can provide a more complete interpretation of water distribution, particularly, in bound water, and these data are important to access bone quality and predict the mechanical behavior of bone.

Keywords: bone, mice bone, NMR, water in bone

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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: Cosmas Pandit Pagwiwoko, Ammar Khaled Abdelaziz Abdelsamia

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Flutter as a phenomenon of flow-induced and self-excited vibration has to be recognized considering its harmful effect on the structure especially in a stage of aircraft design. This phenomenon is also important for a wind energy harvester based on the fluttering surface due to its effective operational velocity range. This multi-physics occurrence can be presented by two governing equations in both fluid and structure simultaneously in respecting certain boundary conditions on the surface of the body. In this work, the equations are resolved separately by two distinct solvers, one-time step of each domain. The modelling and simulation of this flow-structure interaction in ANSYS show the effectiveness of this loosely coupled method in representing flutter phenomenon however the process is time-consuming for design purposes. Therefore, another technique using the same weak coupled aero-structure is proposed by using system dynamics approach. In this technique, the aerodynamic forces were calculated using singularity function for a range of frequencies and certain natural mode shapes are transformed into time domain by employing an approximation model of fraction rational function in Laplace variable. The representation of structure in a multi-degree-of-freedom coupled with a transfer function of aerodynamic forces can then be simulated in time domain on a block-diagram platform such as Simulink MATLAB. The dynamic response of flutter at certain velocity can be evaluated with another established flutter calculation in frequency domain k-method. In this method, a parameter of artificial structural damping is inserted in the equation of motion to assure the energy balance of flow and vibrating structure. The simulation in time domain is particularly interested as it enables to apply the structural non-linear factors accurately. Experimental tests on a fluttering airfoil in the wind tunnel are also conducted to validate the method.

Keywords: flutter, flow-induced vibration, flow-structure interaction, non-linear structure

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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: Peter Fornaro, Lothar Schmitt

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The Digital Humanities Lab and the Institute of Art History at the University of Basel are collaborating in the SNSF research project ‘Digital Materiality’. Its goal is to develop and enhance existing methods for the digital reproduction of cultural heritage objects in order to support art historical research. One part of the project focuses on the visualization of a small eye-catching group of early prints that are noteworthy for their subtle reliefs and glossy surfaces. Additionally, this group of objects – known as ‘paste prints’ – is characterized by its fragile state of preservation. Because of the brittle substances that were used for their production, most paste prints are heavily damaged and thus very hard to examine. These specific material properties make a photographic reproduction extremely difficult. To obtain better results we are working with Reflectance Transformation Imaging (RTI), a computational photographic method that is already used in archaeological and cultural heritage research. This technique allows documenting how three-dimensional surfaces respond to changing lighting situations. Our first results show that RTI can capture the material properties of paste prints and their current state of preservation more accurately than conventional photographs, although there are limitations with glossy surfaces because the mathematical models that are included in RTI are kept simple in order to keep the software robust and easy to use. To improve the method, we are currently developing tools for a more detailed analysis and simulation of the reflectance behavior. An enhanced analytical model for the representation and visualization of gloss will increase the significance of digital representations of cultural heritage objects. For collaborative efforts, we are working on a web-based viewer application for RTI images based on WebGL in order to make acquired data accessible to a broader international research community. At the ICDH Conference, we would like to present unpublished results of our work and discuss the implications of our concept for art history, computational photography and heritage science.

Keywords: art history, computational photography, paste prints, reflectance transformation imaging

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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: Maria de Nazaré Moraes Soares, Silvia Maria Dias Pedro Rebouças, José Carlos Lázaro

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The Solidarity Economy (SE) acts in the re-articulation of the economic field to the other spheres of social action. The significant participation of women in SE resulted in the formation of a national network of self-managed enterprises in Brazil: The Solidarity and Feminist Economy Network (SFEN). The objective of the research is to identify factors of gender justice and feminist self-management practices that adhere to the reality of women in SE enterprises. The conceptual apparatus related to feminist studies in this research covers Nancy Fraser approaches on gender justice, and Patricia Yancey Martin approaches on feminist management practices, and authors of postcolonial feminism such as Mohanty and Maria Lugones, who lead the discussion to peripheral contexts, a necessary perspective when observing the women’s movement in SE. The research has a quantitative nature in the phases of data collection and analysis. The data collection was performed through two data sources: the database mapped in Brazil in 2010-2013 by the National Information System in Solidary Economy and 150 questionnaires with women from 16 enterprises in SFEN, in a state of Brazilian northeast. The data were analyzed using the multivariate statistical technique of Factor Analysis. The results show that the factors that define gender justice and feminist self-management practices in SE are interrelated in several levels, proving statistically the intersectional condition of the issue of women. The evidence from the quantitative analysis allowed us to understand the dimensions of gender justice and feminist management practices intersectionality; in this sense, the non-distribution of domestic work interferes in non-representation of women in public spaces, especially in peripheral contexts. The study contributes with important reflections to the studies of this area and can be complemented in the future with a qualitative research that approaches the perspective of women in the context of the SE self-management paradigm.

Keywords: feminist management practices, gender justice, self-management, solidarity economy

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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: 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

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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: Deniz Guven, Wil Ward, Jinming Duan, Li Bai

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Over the past two decades or so, Optical Coherence Tomography (OCT) has been used to diagnose retina and optic nerve diseases. The retinal nerve fibre layer, for example, is a powerful diagnostic marker for detecting and staging glaucoma. With the advances in optical imaging hardware, the adoption of OCT is now commonplace in clinics. More and more OCT images are being generated, and for these OCT images to have clinical applicability, accurate automated OCT image segmentation software is needed. Oct image segmentation is still an active research area, as OCT images are inherently noisy, with the multiplicative speckling noise. Simple edge detection algorithms are unsuitable for detecting retinal layer boundaries in OCT images. Intensity fluctuation, motion artefact, and the presence of blood vessels also decrease further OCT image quality. In this paper, we introduce a new method for segmenting three-dimensional (3D) OCT images. This involves the use of a Kalman filter, which is commonly used in computer vision for object tracking. The Kalman filter is applied to the 3D OCT image volume to track the retinal layer boundaries through the slices within the volume and thus segmenting the 3D image. Specifically, after some pre-processing of the OCT images, points on the retinal layer boundaries in the first image are identified, and curve fitting is applied to them such that the layer boundaries can be represented by the coefficients of the curve equations. These coefficients then form the state space for the Kalman Filter. The filter then produces an optimal estimate of the current state of the system by updating its previous state using the measurements available in the form of a feedback control loop. The results show that the algorithm can be used to segment the retinal layers in OCT images. One of the limitations of the current algorithm is that the curve representation of the retinal layer boundary does not work well when the layer boundary is split into two, e.g., at the optic nerve, the layer boundary split into two. This maybe resolved by using a different approach to representing the boundaries, such as b-splines or level sets. The use of a Kalman filter shows promise to developing accurate and effective 3D OCT segmentation methods.

Keywords: optical coherence tomography, image segmentation, Kalman filter, object tracking

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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

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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: Lee Artz

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Based on content analyses of major US media, immediately following the George Floyd killing in May 2020, some mayors and local, state, and national officials offered favorable representations of protests against police violence. As the protest movement grew to historic proportions with 26 million joining actions in large cities and small towns, dominant representations of racism by elected officials and leading media shifted—replacing both the voices and demands of protestors with representations by elected officials. Major media quoted Black mayors and Congressional representatives who emphasized concerns about looting and the disruption of public safety. Media coverage privileged elected officials who criticized movement demands for defunding police and deplored isolated instances of property damaged by protestors. Subsequently, public opinion polls saw an increase in concern for law and order tropes and a decrease in support for protests against police violence. Black Lives Matter and local organizations had no coordinated response and no effective means of communication to counter dominant representations voiced by politicians and globally disseminated by major media. Politician and media-instigated public opinion shifts indicate that social movements need their own means of communication and collective decision-making--both of which were largely missing from Black Lives Matter leaders, leading to disaffection and a political split by more than 20 local affiliates. By itself, social media by myriad individuals and groups had limited purchase as a means for social movement communication and organization. Lacking a collaborative, coordinated strategy, organization, and independent media, the loose network of Black Lives Matter groups was unable to offer more accurate, democratic, and favorable representations of protests and their demands for more justice and equality. The fight for equality was diverted by the fight for representation.

Keywords: black lives matter, public opinion, racism, representations, social movements

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Authors: Nuray Okcum, Jenny Sharples

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While the scrutinization towards marginalized groups throughout the globe has been existent for decades, prejudice towards Muslims in Western countries has been increasing dramatically. The vicious attacks across the globe by perpetrators who identify with Islam as well as popular political discourse by politicians in Western countries claiming and portraying Muslims as being dangerous, oppressed, or lacking the ability to assimilate into the community, adds to the exclusion and lack of belonging Muslims living in Western countries experience. The early stages of adulthood which have recently been conceptualized as emerging adulthood is a critical and socially ambiguous transition. For a young Muslim emerging into adulthood in a Western country, a variety of different challenges and demands that can exceed their coping abilities can arise. While in search for their identity and in a bid to structure themselves with their past childhood experiences together with their newly forming values, the emerging adult may attempt to direct or change the way in which they are viewed by others. This can be done to gain approval from others and to feel a sense of belonging. A change in the emerging adult’s interpersonal interactions and relationships, the way in which they view themselves and others, their sense of belonging, and their identity, also occurs during this developmental stage. To explore the manner in which Muslims emerging into adulthood carve their identity, their experiences, and representation of their Muslim identity, social identification, and their sense of belonging in Australia, an interpretative phenomenological methodology was utilized. This allowed participants to offer their own subjective experiences. A total of eight emerging adults took part in the study whilst four adults who work with emerging adults took part. Adult participants who work with emerging adults took part in the study to bring forth their insight and experiences. Common experiences were organized into themes. Themes included identifying as a Muslim, social identification, and belonging. Identification included visual identification and name, discrimination and resilience. Findings clearly indicated that Muslims emerging into adulthood in Australia do face various hurdles while they try to retain and represent their religious identity. Despite the unique challenges that they face, they still feel a sense of belonging and identity as being Australian.

Keywords: Muslim, Islam, emerging adulthood, Australia

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Authors: Adriana Haulica

Abstract:

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

Procedia PDF Downloads 58

Authors: Nathaniel A. Hoston

Abstract:

Teacher coaching is necessary for improving student behaviors. While coaching technologies (e.g., bug-in-ear coaching, video-coaching) can assist the coaching process, little is known about the usability of those tools. This study assessed the usability and perceived efficacy of the Behavior Coaching Organizer (BCO) using usability testing methods (i.e., concurrent think-aloud, retrospective probing) in a simulated learning environment. Participants found that the BCO is moderately usable while perceiving the tool as highly effective for addressing concerning student behaviors. Additionally, participants noted a general need for continued coaching support. The results indicate a need for further usability testing with education research.

Keywords: behavioral interventions, Behavior Coaching Organizer, coaching technologies, usability methods

Procedia PDF Downloads 114

Authors: R. Pargas, M. Reba

Abstract:

Since 2006, the School of Computing and the Department of Mathematical Sciences have collaborated on several industry and NSF grants to develop new uses of technology in teaching and learning. Clemson University’s Creative Inquiry Program allowed computer science and mathematics students to earn credit each semester for participating in seminars which introduced them to new areas for independent research. We will discuss how the development of three interactive instructional apps for Calculus resulted not only in a useful product, but also in unique educational benefits for both the computer science students and the mathematics students, graduate and undergraduate, involved in the development process.

Keywords: calculus, apps, programming, mathematics

Procedia PDF Downloads 393

Authors: Supratman Ahman Maedi

Abstract:

The construction of knowledge is the goal of learning. The purpose of this research is to know how the role of Piaget theory in allegation via analogy reasoning. This study uses Think out loads when troubleshooting. To explore conjecturing via analogical reasoning is given the question of open analogy. The result: conjecture via analogical reasoning has been done by students in the construction of knowledge, in conjecture there are differences in thinking flow depending on the basic knowledge of the students, in the construction of knowledge occurs assimilation and accommodation problems, strategies and relationships.

Keywords: analogical reasoning, conjecturing, knowledge construction, Piaget's theory

Procedia PDF Downloads 312

Authors: Audrey Romero-Pelaez, Juan Carlos Morocho-Yunga

Abstract:

The increasing amount of open educational resources (OER) published on the web for consumption in teaching and learning environments also generates a growing need to ensure the quality of these resources. The low level of OER discovery is one of the most significant drawbacks when faced with its reuse, and as a consequence, high-quality educational resources can go unnoticed. Metadata enables the discovery of resources on the web. The purpose of this study is to lay the foundations for open educational resources to achieve their first quality star within the Quality4OER Framework. In this study, we evaluate the quality of OER metadata and establish the main guidelines on metadata quality in this context.

Keywords: open educational resources, OER quality, quality metadata

Procedia PDF Downloads 225

Authors: Allen A. Espinosa, Arlyne C. Marasigan, Janir T. Datukan

Abstract:

The study explored how students visualize the states and classifications of matter using scientific models. It also identified misconceptions of students in using scientific models. In general, high percentage of students was able to use scientific models correctly and only a little misconception was identified. From the result of the study, a teaching framework was formulated wherein scientific models should be employed in classroom instruction to visualize abstract concepts in chemistry and for better conceptual understanding.

Keywords: visual conception, scientific models, mental models, states of matter, classification of matter

Procedia PDF Downloads 387

Authors: Laurence Craven

Abstract:

Academic writing is one of the most important class a freshman will take, as it provides the skill needed to formulate an academic essay in any discipline. Written assignments are the most common form of assessment in higher education and thus it is of paramount importance for students to master the skill of academic writing. This presentation aims to give practitioners multiple ways to enhance their academic writing classes using the Blackboard environment, with a view to improving student performance. The presentation will include ways to improve assessment and give corrective feedback. It will also provide ideas on how to increase variety in teaching lessons, assigning homework and on organizing materials.

Keywords: academic writing, assessment, e-learning, technology

Procedia PDF Downloads 336