Search results for: structure learning

Authors: Hsiao-Wen Hsu

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It is generally believed that the teacher’s use of motivational strategies can enhance student motivation, especially in a place like Taiwan where teacher usually dominates student EFL learning. However, only little empirical studies support this claim. This study examined the connection between teachers’ use of motivational teaching practice and observed student motivated behavior in rural junior high schools in Taiwan. The use of motivational strategies by 12 teachers in five recognized rural junior high schools was investigated observed using a classroom observation instrument, the Motivation Orientation of Language Teaching. Meanwhile, post-lesson teacher evaluations accomplished by both the researcher and the teacher were functioning as part of the measure of teacher motivational practice. The data collected through observation scheme follows the real-time coding principle to examine observable teacher motivational practice and learner motivated behaviors. The results support the previous research findings that teachers’ use of motivational strategies is associated with the student motivated behaviors as well as the students’ level of motivation regarding English learning.

Keywords: English learning, motivational strategies, student motivation, teacher motivational practices

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Authors: Jagannath P. Tegar

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The new National Education Policy (NEP) 2020 of Govt. of India has envisaged a major overhaul of the education system of India, in particular, the revamping of the Curriculum of Higher Education. In this process, the faculty members of the Indian universities and institutions have a challenging role in developing the curriculum, which is a shift from the traditional (content-based) curriculum to a student-centric- outcome-based Curriculum (SC-OBC) to be implemented in all of the Universities and institutions. The efforts and initiatives on the design and implementation of SC-OBC are remarkable in the engineering and technical education landscape of the country, but it is still in its early stages and many more steps are needed for the successful adaptation in every level of Higher Education. The premier institute of Govt. of India (NITTTR, Bhopal) has trained and developed the capacity and capability among the teachers of Polytechnics on the design and development of Student Centric - Outcome Based Curriculum and also providing academic consultancy for reforming curriculum in line of NEP- 2020 envisions for the states such as Chhattisgarh, Bihar and Maharashtra to make them responsibly ready for such a new shift in Higher Education. This research-based paper is on three main aspects: 1) the level of acceptance and preparedness of teachers /faculty towards NEP-2020 and student-centred outcome-based learning. 2) the extent of implementing NEP-2020 and student-centered outcome-based learning at Indian institutions/ universities and 3) the challenges of implementing NEP-2020 and student-centered outcome-based learning outcome-based education in the Indian context. The paper content will inspire curriculum designers and developers to prepare SC-OBC that meets the specific needs of industry and society at large, which is intended in the NEP-2020 of Govt. of India

Keywords: outcome based curriculum, student centric learning, national education policy -2020, implementation of nep-2020. outcome based learning, higher education curriculum

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Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

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The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. While it is recognized that SOC predictors vary significantly when derived from remote sensing data and environmental variables, identifying the specific parameters most suitable for accurately estimating SOC in diverse agricultural areas remains a challenge. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors' impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

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Authors: Tomas Premoli, Sareh Rowlands

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In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.

Keywords: Alzheimer’s disease, convolutional neural networks, deep learning, medical imaging, MRI

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Authors: L. N. P. Wedikandage, Mohamed Razmi Zahir

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Technology is a global imperative because of its contributions to human existence and because it has improved global socioeconomic relations. As a result, the mobile phone has become the most important mode of communication today. Smartphones, Internet-enabled devices with built-in computer software and applications, are one of the most significant inventions of the twenty-first century. Technology is advantageous to many people, especially those involved in education. It is an important learning tool for today's schoolchildren. It enables students to access online learning platforms and course resources and interact digitally. Senior secondary students, in particular, have some of the most expensive and sophisticated mobile phones, tablets, and iPads capable of connecting to the internet and various social media platforms, other websites, and so on. At present, the use of mobile phones' potential for effective teaching and learning is growing. This is due to the benefits of mobile learning, including the ability to share knowledge without any limits in space or Time and the capacity to facilitate the development of critical thinking, participatory learning, problem-solving, and the development of lifelong communication skills. However, it is yet unclear how mobile devices may affect education and how they may affect opportunities for learning. As a result, the purpose of this research was to ascertain the relationship between mobile phone usage and the academic Performance of secondary-level students at an international school in Sri Lanka. The study's sample consisted of 523 secondary-level students from an international school, ranging from Form 1 to Upper 6. For the study, a survey research design and questionnaires were used. Google Forms was used to create the students' survey. There were three hypotheses tested to find out the relationship between mobile phone usage and academic preference. The findings show that there is a positive relationship between mobile phone usage and academic performance among secondary school students (the number of students obtaining simple passes is significantly higher when mobile phones are being used for more than 7 hours), no relationship between mobile phone usage and academic performance among secondary school students of different parents' occupations, and a relationship between the frequency of mobile phone usage and academic performance among secondary school students.

Keywords: mobile phone, academic performance, secondary level, international schools

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Authors: Pouya Vakili

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Since computers were first introduced into educational facilities, foreign language educators have been faced with the problem of integrating high-tech multimedia techniques into a traditional text-based curriculum. As studies of language teaching have pointed out, ‘Language teaching tends in practice to be eclectic…. There are not only exceptionally many paths and educational means for arriving at a given educational goal, but there are also many types of educational materials which can be used to achieve that goal’. For language educators who are trying to incorporate technology into their curricula, the choices seem endless. Yet the quantity, as well as the limitations, of available computer programs does not guarantee that these programs can be successfully integrated into a curriculum.

Keywords: curriculum, language teaching, learning, multimedia, technology

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Authors: Richard Renou, Laurent Soulard

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Lasers are widely used in glass material processing, from waveguide fabrication to channel drilling. The gradual damage of glass optics under UV lasers is also an important issue to be addressed. Glass materials (including metallic glasses) can undergo a permanent densification under laser-induced shock loading. Despite increased interest on interactions between laser and glass materials, little is known about the structural mechanisms involved under shock loading. For example, the densification process in silica glasses occurs between 8 GPa and 30 GPa. Above 30 GPa, the glass material returns to the original density after relaxation. Investigating these unusual mechanisms in silica glass will provide an overall better understanding in glass behaviour. Non-Equilibrium Molecular Dynamics simulations (NEMD) were carried out in order to gain insight on the silica glass microscopic structure under shock loading. The shock was generated by the use of a piston impacting the glass material at high velocity (from 100m/s up to 2km/s). Periodic boundary conditions were used in the directions perpendicular to the shock propagation to model an infinite system. One-dimensional shock propagations were therefore studied. Simulations were performed with the STAMP code developed by the CEA. A very specific structure is observed in a silica glass. Oxygen atoms around Silicon atoms are organized in tetrahedrons. Those tetrahedrons are linked and tend to form rings inside the structure. A significant amount of empty cavities is also observed in glass materials. In order to understand how a shock loading is impacting the overall structure, the tetrahedrons, the rings and the cavities were thoroughly analysed. An elastic behaviour was observed when the shock pressure is below 8 GPa. This is consistent with the Hugoniot Elastic Limit (HEL) of 8.8 GPa estimated experimentally for silica glasses. Behind the shock front, the ring structure and the cavity distribution are impacted. The ring volume is smaller, and most cavities disappear with increasing shock pressure. However, the tetrahedral structure is not affected. The elasticity of the glass structure is therefore related to a ring shrinking and a cavity closing. Above the HEL, the shock pressure is high enough to impact the tetrahedral structure. An increasing number of hexahedrons and octahedrons are formed with the pressure. The large rings break to form smaller ones. The cavities are however not impacted as most cavities are already closed under an elastic shock. After the material relaxation, a significant amount of hexahedrons and octahedrons is still observed, and most of the cavities remain closed. The overall ring distribution after relaxation is similar to the equilibrium distribution. The densification process is therefore related to two structural mechanisms: a change in the coordination of silicon atoms and a cavity closing. To sum up, non-equilibrium molecular dynamics were carried out to investigate silica behaviour under shock loading. Analysing the structure lead to interesting conclusions upon the elastic and the densification mechanisms in glass materials. This work will be completed with a detailed study of the mechanism occurring above 30 GPa, where no sign of densification is observed after the material relaxation.

Keywords: densification, molecular dynamics simulations, shock loading, silica glass

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Authors: I. Zahraoui, J. Terhzaz, A. Errkik, El. H. Abdelmounim, A. Tajmouati, L. Abdellaoui, N. Ababssi, M. Latrach

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This paper presents a novel design of a microstrip fractal antenna based on the use of Sierpinski triangle shape, it’s designed and simulated by using FR4 substrate in the operating frequency bands (GPS, WiMAX), the design is a fractal antenna with a modified ground structure. The proposed antenna is simulated and validated by using CST Microwave Studio Software, the simulated results presents good performances in term of radiation pattern and matching input impedance.

Keywords: dual-band antenna, fractal antenna, GPS band, modified ground structure, sierpinski triangle, WiMAX band

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Authors: Jean Marie Tshimula, Atsushi Togashi

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We develop a data-science approach for providing an interactive visualization and predictive models to find insights into the projects' historical data in order for stakeholders understand some unseen opportunities in the African market that might escape them behind the online project portfolio of the African Development Bank. This machine learning-based web application identifies the market trend of the fastest growing economies across the continent as well skyrocketing sectors which have a significant impact on the future of business in Africa. Owing to this, the approach is tailored to predict where the investment needs are the most required. Moreover, we create a corpus that includes the descriptions of over more than 1,200 projects that approximately cover 14 sectors designed for some of 53 African countries. Then, we sift out this large amount of semi-structured data for extracting tiny details susceptible to contain some directions to follow. In the light of the foregoing, we have applied the combination of Latent Dirichlet Allocation and Random Forests at the level of the analysis module of our methodology to highlight the most relevant topics that investors may focus on for investing in Africa.

Keywords: machine learning, topic modeling, natural language processing, big data

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Authors: Heungsu Lee, Youngseok Kim, Jonghwa Yi, Chul Park

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A landing pier is subjected to safety assessment by visual inspection and design data, but it is difficult to check the damage in real-time. In this study, real - time damage detection and safety evaluation methods were studied. As a result of structural analysis of the arbitrary landing pier structure, the inflection point of deformation and moment occurred at 10%, 50%, and 90% of pile length. The critical value of Fiber Bragg Grating (FBG) sensor was set according to the safety factor, and the FBG sensor application method for real - time safety evaluation was derived.

Keywords: FBG sensor, harbor structure, maintenance, safety evaluation system

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Authors: Joan Esper Kuhnly, Jess Holden, Lynn Shelley, Nicole Kuhnly

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Empathy serves as a foundational nursing principle inherent in the nurse’s ability to form those relationships from which to care for patients. Evidence supports, including empathy in nursing and healthcare education, but there is limited data on what methods are effective to do so. Building evidence supports experiential and interactive learning methods to be effective for students to gain insight and perspective from a personalized experience. The purpose of this project is to evaluate learning activities designed to promote the attainment of empathic behaviors across 5 levels of the nursing curriculum. Quantitative analysis will be conducted on data from pre and post-learning activities using the Toronto Empathy Questionnaire. The main hypothesis, that simulation learning activities will increase empathy, will be examined using a repeated measures Analysis of Variance (ANOVA) on Pre and Post Toronto Empathy Questionnaire scores for three simulation activities (Stroke, Poverty, Dementia). Pearson product-moment correlations will be conducted to examine the relationships between continuous demographic variables, such as age, credits earned, and years practicing, with the dependent variable of interest, Post Test Toronto Empathy Scores. Krippendorff’s method of content analysis will be conducted to identify the quantitative incidence of empathic responses. The researchers will use Colaizzi’s descriptive phenomenological method to describe the students’ simulation experience and understand its impact on caring and empathy behaviors employing bracketing to maintain objectivity. The results will be presented, answering multiple research questions. The discussion will be relevant to results and educational pedagogy in the nursing curriculum as they relate to the attainment of empathic behaviors.

Keywords: curriculum, empathy, nursing, simulation

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Authors: John Zanetich

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Designing an educational activity that encourages inquiry and collaboration is key to engaging students in meaningful learning. Educational Information and Communications Technology (EICT) plays an important role in facilitating cooperative and collaborative learning in the classroom. The EICT also facilitates students’ learning and development of the critical thinking skills needed to solve real world problems. Projects and activities based on constructivism encourage students to embrace complexity as well as find relevance and joy in their learning. It also enhances the students’ capacity for creative and responsible real-world problem solving. Classroom activities based on constructivism offer students an opportunity to develop the higher–order-thinking skills of defining problems and identifying solutions. Participating in a classroom project is an activity for both acquiring experiential knowledge and applying new knowledge to practical situations. It also provides an opportunity for students to integrate new knowledge into a skill set using reflection. Classroom projects can be developed around a variety of learning objects including social media, knowledge management and learning communities. The construction of meaning through project-based learning is an approach that encourages interaction and problem-solving activities. Projects require active participation, collaboration and interaction to reach the agreed upon outcomes. Projects also serve to externalize the invisible cognitive and social processes taking place in the activity itself and in the student experience. This paper describes a classroom project designed to elicit interactions by helping students to unfreeze existing knowledge, to create new learning experiences, and then refreeze the new knowledge. Since constructivists believe that students construct their own meaning through active engagement and participation as well as interactions with others. knowledge management can be used to guide the exchange of both tacit and explicit knowledge in interpersonal interactions between students and guide the construction of meaning. This paper uses an action research approach to the development of a classroom project and describes the use of technology, social media and the active use of tacit knowledge in the college classroom. In this project, a closed group Facebook page becomes the virtual classroom where interaction is captured and measured using engagement analytics. In the virtual learning community, the principles of knowledge management are used to identify the process and components of the infrastructure of the learning process. The project identifies class member interests and measures student engagement in a learning community by analyzing regular posting on the Facebook page. These posts are used to foster and encourage interactions, reflect a student’s interest and serve as reaction points from which viewers of the post convert the explicit information in the post to implicit knowledge. The data was collected over an academic year and was provided, in part, by the Google analytic reports on Facebook and self-reports of posts by members. The results support the use of active tacit knowledge activities, knowledge management and social media to enhance the student learning experience and help create the knowledge that will be used by students to construct meaning.

Keywords: constructivism, knowledge management, tacit knowledge, social media

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Authors: W. S. Barber, S. L. King

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This paper reports on a pilot project to develop a collaborative partnership between a community college in rural northern Ontario, Canada, and an urban university in the greater Toronto area in Oshawa, Canada. Partner institutions will collaborate to address learning needs of university applicants whose goals are to attain an undergraduate university BA in Educational Studies and Digital Technology degree, but who may not live in a geographical location that would facilitate this pathways process. The UOIT BA degree is attained through a 2+2 program, where students with a 2 year college diploma or equivalent can attain a four year undergraduate degree. The goals reported on the project are as: 1. Our aim is to expand the BA program to include an additional stream which includes serious educational games, simulations and virtual environments, 2. Develop fully (using both synchronous and asynchronous technologies) online learning modules for use by university applicants who otherwise are not geographically located close to a physical university site, 3. Assess the digital competencies of all students, including members of local, distance and Indigenous communities using a validated tool developed and tested by UOIT across numerous populations. This tool, the General Technical Competency Use and Scale (GTCU) will provide the collaborating institutions with data that will allow for analyzing how well students are prepared to succeed in fully online learning communities. Philosophically, the UOIT BA program is based on a fully online learning communities model (FOLC) that can be accessed from anywhere in the world through digital learning environments via audio video conferencing tools such as Adobe Connect. It also follows models of adult learning and mobile learning, and makes a university degree accessible to the increasing demographic of adult learners who may use mobile devices to learn anywhere anytime. The program is based on key principles of Problem Based Learning, allowing students to build their own understandings through the co-design of the learning environment in collaboration with the instructors and their peers. In this way, this degree allows students to personalize and individualize the learning based on their own culture, background and professional/personal experiences. Using modified flipped classroom strategies, students are able to interrogate video modules on their own time in preparation for one hour discussions occurring in video conferencing sessions. As a consequence of the program flexibility, students may continue to work full or part time. All of the partner institutions will co-develop four new modules, administer the GTCU and share data, while creating a new stream of the UOIT BA degree. This will increase accessibility for students to bridge from community colleges to university through a fully digital environment. We aim to work collaboratively with Indigenous elders, community members and distance education instructors to increase opportunities for more students to attain a university education.

Keywords: aboriginal, college, competencies, digital, universities

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Authors: Hyoshin Kim

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Most post-secondary educational institutions have offered a wide variety of professional development programs and resources in order to advance the quality of education. Such programs are designed to support faculty members by focusing on topics such as course design, behavioral learning objectives, class discussion, and evaluation methods. These are based on good intentions and might help both new and experienced educators. However, the fundamental flaw is that these ‘effective methods’ are assumed to work regardless of what we teach and whom we teach. This paper is focused on intercultural intelligence and its application to education. It presents a comprehensive literature review on context and cultural diversity in terms of beliefs, values and worldviews. What has worked well with a group of homogeneous local students may not work well with more diverse and international students. It is because students hold different notions of what is means to learn or know something. It is necessary for educators to move away from certain sets of generic teaching skills, which are based on a limited, particular view of teaching and learning. The main objective of the research is to expand our teaching strategies by incorporating what students bring to the course. There have been a growing number of resources and texts on teaching international students. Unfortunately, they tend to be based on the deficiency model, which treats diversity not as strengths, but as problems to be solved. This view is evidenced by the heavy emphasis on assimilationist approaches. For example, cultural difference is negatively evaluated, either implicitly or explicitly. Therefore the pressure is on culturally diverse students. The following questions reflect the underlying assumption of deficiencies: - How can we make them learn better? - How can we bring them into the mainstream academic culture?; and - How can they adapt to Western educational systems? Even though these questions may be well-intended, there seems to be something fundamentally wrong as the assumption of cultural superiority is embedded in this kind of thinking. This paper examines how educators can incorporate intercultural intelligence into the course design by utilizing a variety of tools such as pre-course activities, peer learning and reflective learning journals. The main goal is to explore ways to engage diverse learners in all aspects of learning. This can be achieved by activities designed to understand their prior knowledge, life experiences, and relevant cultural identities. It is crucial to link course material to students’ diverse interests thereby enhancing the relevance of course content and making learning more inclusive. Internationalization of higher education can be successful only when cultural differences are respected and celebrated as essential and positive aspects of teaching and learning.

Keywords: intercultural competence, intercultural intelligence, teaching and learning, post-secondary education

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Authors: Anoush Saadatmehr

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Design and build of large clear span structures have always been demanding in the construction industry targeting industrial and commercial buildings around the world. The function of these spectacular structures encompasses distinguished types of building such as aircraft and airship hangars, warehouses, bulk storage buildings, sports and recreation facilities. From an engineering point of view, there are various types of steel structure systems that are often adopted in large-span buildings like conventional trusses, space frames and cable-supported roofs. However, this paper intends to investigate and review an innovative light, economic and quickly erected large span steel structure renowned as “Stressed-Arch,” which has several advantages over the other common types of structures. This patented system integrates the use of cold-formed hollow section steel material with high-strength pre-stressing strands and concrete grout to establish an arch shape truss frame anywhere there is a requirement to construct a cost-effective column-free space for spans within the range of 60m to 180m. In this study and firstly, the main structural properties of the stressed-arch system and its components are discussed technically. These features include nonlinear behavior of truss chords during stress-erection, the effect of erection method on member’s compressive strength, the rigidity of pre-stressed trusses to overcome strict deflection criteria for cases with roof suspended cranes or specialized front doors and more importantly, the prominent lightness of steel structure. Then, the effects of utilizing pre-stressing strands to safeguard a smooth process of installation of main steel members and roof components and cladding are investigated. In conclusion, it is shown that the Stressed-Arch system not only provides an optimized light steel structure up to 30% lighter than its conventional competitors but also streamlines the process of building erection and minimizes the construction time while preventing the risks of working at height.

Keywords: large span structure, pre-stressed steel truss, stressed-arch building, stress-erection, steel structure

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Authors: Lakshmi Shenoy

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In today’s era of Globalization, arises the need that students and professionals relocate temporarily or permanently to another country in order to pursue their respective academic and career goals. This involves not only learning the local language of the country but also integrating oneself into the native culture. This paper explains the method of understanding a nation’s culture through the study of its language. The method uses language not as a series of rules that connect words together but as a social practice in which one can actively participate. It emphasizes on how culture provides an environment in which languages can flourish and how culture dictates the interpretation of the language especially in case of German. This paper introduces language and culture as inseparable entities, as two sides of the same coin.

Keywords: language and culture, sociolinguistics, Ronald Wardhaugh, German

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Authors: Xu Jiaqiao

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Text sentiment analysis is an important branch of natural language processing. This technology is widely used in public opinion analysis and web surfing recommendations. At present, the mainstream sentiment analysis methods include three parts: sentiment analysis based on a sentiment dictionary, based on traditional machine learning, and based on deep learning. This paper mainly analyzes and compares the advantages and disadvantages of the SVM method of traditional machine learning and the Long Short-term Memory (LSTM) method of deep learning in the field of Chinese sentiment analysis, using Chinese comments on Sina Microblog as the data set. Firstly, this paper classifies and adds labels to the original comment dataset obtained by the web crawler, and then uses Jieba word segmentation to classify the original dataset and remove stop words. After that, this paper extracts text feature vectors and builds document word vectors to facilitate the training of the model. Finally, SVM and LSTM models are trained respectively. After accuracy calculation, it can be obtained that the accuracy of the LSTM model is 85.80%, while the accuracy of SVM is 91.07%. But at the same time, LSTM operation only needs 2.57 seconds, SVM model needs 6.06 seconds. Therefore, this paper concludes that: compared with the SVM model, the LSTM model is worse in accuracy but faster in processing speed.

Keywords: sentiment analysis, support vector machine, long short-term memory, Chinese microblog comments

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Authors: Yuet Wah Echo Yeung

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Practice learning is an important component of social work education. Practice educators are charged with the responsibility to support and enable learning while students are on placement. They also play a key role in teaching students to integrate theory and practice, as well as assessing their performance. Current literature highlights the structural factors that make it difficult for practice educators to create a positive learning environment for students. Practice educators find it difficult to give sufficient attention to their students because of the lack of workload relief, the increasing emphasis on managerialism and bureaucratisation, and a range of competing organisational and professional demands. This paper reports the challenges practice educators face and how they manage these challenges in this context. Semi-structured face-to-face interviews were conducted with thirteen practice educators who support students in statutory and voluntary social care settings in the Northwest of England. Interviews were conducted between April and July 2017 and each interview lasted about 40 minutes. All interviews were recorded and transcribed. All practice educators are experienced social work practitioners with practice experience ranging from 6 to 42 years. On average they have acted as practice educators for 13 years and all together have supported 386 students. Our findings reveal that apart from the structural factors that impact how practice educators perform their roles, they also faced other challenges when supporting students on placement. They include difficulty in engaging resistant students, complexity in managing power dynamics in the context of practice learning, and managing the dilemmas of fostering a positive relationship with students whilst giving critical feedback. Suggestions to enhance the practice educators’ role include support from organisations and social work teams; effective communication with university tutors, and a forum for practice educators to share good practice and discuss placement issues.

Keywords: social work education, placement challenges, practice educator, practice learning

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Authors: Nicoleta Simona Vedeanu, Rares Stiufiuc, Dana Alina Magdas

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A detailed knowledge of the teeth structure is mandatory to understand and explain the defects and the dental pathology, but especially to take a correct decision regarding dental prophylaxis and treatment. The present work is an alternative study to the traditional investigation methods used in dentistry, a study based on the use of modern, sensitive physical methods to investigate human enamel and dentin. For the present study, several teeth collected from patients of different ages were used for structural and dietary investigation. The samples were investigated by Raman spectroscopy for the molecular structure analysis of dentin and enamel, atomic force microscopy (AFM) to view the dental topography at the micrometric size and mass spectrometry for isotopic ratios as a fingerprint of patients’ personal diet. The obtained Raman spectra and their interpretation are in good correlation with the literature and may give medical information by comparing affected dental structures with healthy ones. AFM technique gave us the possibility to study in details the dentin and enamel surface to collect information about dental hardness or dental structural changes. δ¹³C values obtained for the studied samples can be classified in C4 category specific to young people and children diet (sweets, cereals, juices, pastry). The methods used in this attempt furnished important information about dentin and enamel structure and dietary habits and each of the three proposed methods can be extended at a larger level in the study of the teeth structure.

Keywords: AFM, dentine, enamel, Raman spectroscopy

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Authors: Gebreegziabher Hailu Gebrecherkos

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This study examines the effectiveness of GeoGebra in developing the conceptual understanding of transformation geometry among Grade 11 students. Utilizing a quasi-experimental design, the research compares the learning outcomes of students who engaged with GeoGebra against those who received traditional instruction. Pre- and post-tests were administered to assess students' grasp of key transformation concepts, including translations, rotations, reflections, and dilations. Additionally, qualitative data were gathered through student interviews and classroom observations to explore their experiences and perceptions of using GeoGebra. Results indicate that students utilizing GeoGebra showed significantly greater improvement in their understanding of transformation geometry concepts. The interactive features of GeoGebra facilitated visualization and exploration, leading to enhanced engagement and deeper conceptual insights. The findings underscore the potential of GeoGebra as a powerful educational tool that not only fosters mathematical understanding but also accommodates diverse learning styles in the classroom. This study contributes valuable insights for educators seeking to improve the teaching and learning of transformation geometry in secondary education.

Keywords: calculus, conceptual understanding, GeoGebra, transformation geometry

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Authors: Pyung Soo Kim, Eung Hyuk Lee, Mun Suck Jang

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In the current paper, a residual generation filter with finite memory structure is proposed for fault detection. The proposed finite memory residual generation filter provides the residual by real-time filtering of fault vector using only the most recent finite observations and inputs on the window. It is shown that the residual given by the proposed residual generation filter provides the exact fault for noise-free systems. Finally, to illustrate the capability of the proposed residual generation filter, numerical examples are performed for the discretized DC motor system having the multiple sensor faults.

Keywords: residual generation filter, finite memory structure, kalman filter, fast detection

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Authors: Ayomide Oyedele

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In the dynamic landscape of cybersecurity, "Strategic Cyber Sentinel" emerges as a revolutionary framework, transcending traditional approaches. This paper pioneers a holistic strategy, weaving together threat intelligence, machine learning, and adaptive defenses. Through meticulous real-world simulations, we demonstrate the unprecedented resilience of our framework against evolving cyber threats. "Strategic Cyber Sentinel" redefines proactive threat mitigation, offering a robust defense architecture poised for the challenges of tomorrow.

Keywords: cybersecurity, resilience, threat intelligence, machine learning, adaptive defenses

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: cost prediction, machine learning, project management, random forest, neural networks

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Authors: Olga Guseynova

Abstract:

Being an individual activity, the memorizing process is affected to a greater degree by the individual variables; therefore, one of the decisive factors influencing the memorization is students’ individual characteristics. Based on an extensive literature study in the domains of piano education, psychology, and neuroscience, this comprehensive research was designed in order to develop three memorizing strategies that are reflective of individual students’ learning modalities (visual, kinesthetic and auditory) applied to the piano education. The design of the study required an interdisciplinary approach which incorporated the outcome of neuropsychological and pedagogic experiments. The objectives were to determine the interaction between the process of perception and the process of memorizing music; to systematize the methods of memorizing piano sheet music in accordance with the specifics of perception types; to develop Piano Memorization Inventory (PMI) and the Three Memorizing Strategies (TMS). The following research methods were applied: a method of interdisciplinary analysis and synthesis, a method of non-participant observation. As a result of literature analysis, the following conclusions were made: the majority of piano teachers and piano students participated in the surveys, had not used and usually had not known any memorizing strategy regarding learning styles. As a result, they had used drilling as the main strategy of memorizing. The Piano Memorization Inventory and Three Memorizing Strategies developed by the author of the research were based on the observation and findings of the previous researches and considered the experience of pedagogical and neuropsychological studies.

Keywords: interdisciplinary approach, memorizing strategies, perceptual learning styles, piano memorization inventory

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Authors: Yoshio Kurosawa, Takao Yamaguchi

Abstract:

High frequency automotive interior noise above 500 Hz considerably affects automotive passenger comfort. To reduce this noise, sound insulation material is often laminated on body panels or interior trim panels. For a more effective noise reduction, the sound reduction properties of this laminated structure need to be estimated. We have developed a new calculate tool that can roughly calculate the sound absorption and insulation properties of laminate structure and handy for designers. In this report, the outline of this tool and an analysis example applied to floor mat are introduced.

Keywords: automobile, acoustics, porous material, transfer matrix method

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Authors: Ziba Omidi, Min-Ki Kim

Abstract:

This research presents the design, fabrication and application of a flavor sensor for an integrated electronic tongue and electronic nose that can allow rapid characterization of multi-component mixtures in a solution. The odor gas and liquid are separated using hydrophobic porous membrane in micro fluidic channel. The sensor uses an array composed of microbeads in micromachined cavities localized on silicon wafer. Sensing occurs via colorimetric and fluorescence changes to receptors and indicator molecules that are attached to termination sites on the polymeric microbeads. As a result, the sensor array system enables simultaneous and near-real-time analyses using small samples and reagent volumes with the capacity to incorporate significant redundancies. One of the key parts of the system is a passive pump driven only by capillary force. The hydrophilic surface of the fluidic structure draws the sample into the sensor array without any moving mechanical parts. Since there is no moving mechanical component in the structure, the size of the fluidic structure can be compact and the fabrication becomes simple when compared to the device including active microfluidic components. These factors should make the proposed system inexpensive to mass-produce, portable and compatible with biomedical applications.

Keywords: optical sensor, semiconductor manufacturing, smell sensor, taste sensor

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Authors: Prakash Singh, Piet Maphodisa Kgohlo

Abstract:

Knowledge-worker productivity is one of the biggest leadership challenges facing all organizations in the twenty-first century. It cannot be denied that knowledge-worker productivity affects all organizations. The work and the workforce are both undergoing greater changes currently than at any time, since the beginning of the industrial revolution two centuries ago. Employees welcome collegial teaming (CT) as an innovative way to develop their work-integrated learning competencies. Human resource development policies must evoke the symbiotic relationship between CT and work-integrated learning, seeing that employees need to be endowed with the competence to move from one skill to another, as each one becomes obsolete, and to simultaneously develop their cognitive and emotional intelligence. The outcome of this relationship must culminate in the development of highly productive knowledge-workers. While this study focuses on teachers, the conceptual framework and the findings of this research can be beneficial for any organization, public or private sector, business or non-business. Therefore, in this quantitative study, the benefits of CT are considered in developing human resources to sustain knowledge-worker productivity. The ANOVA p-values reveal that the majority of teachers agree that CT can empower them to overcome the challenges of managing curriculum change. CT can equip them with continuous and sustained learning, growth and improvement, necessary for knowledge-worker productivity. This study, therefore, confirms that CT benefits all workers, immaterial of their age, gender or experience. Hence, this exploratory research provides a new perspective of CT in addressing knowledge-worker productivity when organizational change alters the vision of the organization.

Keywords: collegial teaming, human resource development, knowledge-worker productivity, work-integrated learning

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Authors: Mitchell Gohnert, Ryan Bradley

Abstract:

This paper reviews some fundamental concepts of structural optimization, which are based on the type of materials used in construction and the shape of the structure. The first step in structural optimization is to break down all internal forces in a structure into fundamental stresses, which are tensions and compressions. Knowing the stress patterns directs our selection of structural shapes and the most appropriate type of construction material. In our selection of materials, it is essential to understand all construction materials have flaws, or micro-cracks, which reduce the capacity of the material, especially when subjected to tensions. Because of material defects, many construction materials perform significantly better when subjected to compressive forces. Structures are also more efficient if bending moments are eliminated. Bending stresses produce high peak stresses at each face of the member, and therefore, substantially more material is required to resist bending. The shape of the structure also has a profound effect on stress levels. Stress may be reduced dramatically by simply changing the shape. Catenary, triangular and linear shapes are the fundamental structural forms to achieve optimal stress flow. If the natural flow of stress matches the shape of the structures, the most optimal shape is determined.

Keywords: arches, economy of stresses, material strength, optimization, shells

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Authors: M. Helen

Abstract:

Chemical graph serves as a convenient model for any real or abstract chemical system. Dendrimers are novel three dimensional hyper branched globular nanopolymeric architectures. Drug delivery scientists are especially enthusiastic about possible utility of dendrimers as drug delivery tool. Dendrimers like poly L lysine (PLL), poly-propylene imine (PPI) and poly-amidoamine (PAMAM), etc., are used as gene carrier in drug delivery system because of their chemical characteristics. These characteristics of chemical compounds are analysed using topological indices (invariants under graph isomorphism) such as Wiener index, Zagreb index, etc., Prof. V. R. Kulli motivated by the application of Zagreb indices in finding the total π energy and derived Gourava indices which is an improved version over Zagreb indices. In this paper, we study the structure of PLL-Dendrimer that has the following applications: reduction in toxicity, colon delivery, and topical delivery. Also, we determine first and second Gourava indices, first and second hyper Gourava indices, product and sum connectivity Gourava indices for PLL-Dendrimer. Gourava Indices have found applications in Quantitative Structure-Property Relationship (QSPR)/ Quantitative Structure-Activity Relationship (QSAR) studies.

Keywords: connectivity Gourava indices, dendrimer, Gourava indices, hyper GouravaG indices

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Authors: Nuttha Kirdsinsap, Watchaneeporn Setthasakko

Abstract:

This paper aims to gain opinions and perspectives of Certified Public Accountants (CPA) in Thailand regarding the driven force of Integrated Reporting. It employs in-depth interviews with CPA from different big 4 audits firms in Thailand, including PWC, Ernst and Young, Deloitte, and KPMG. It is found that the driven force of Integrated Reporting made CPA in Thailand awaken to the big change that is coming in the future, and it is said to be another big learning and integrating period between certified public accountants and other professionals (for example, engineers, environmentalists and lawyers), which, certified public accountants in Thailand will have to push themselves so hard to catch up.

Keywords: integrated reporting, learning, knowledge, certified public accountants, Thailand

Procedia PDF Downloads 268