Search results for: teaching report writing for innovative learning

Authors: Terence Soule, Tami Al Ghamdi

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To study how the partial knowledge transfer may affect the Genetic Algorithm (GA) performance, we model the Transfer Learning (TL) process using GA as the model solver. The objective of the TL is to transfer the knowledge from one problem to another related problem. This process imitates how humans think in their daily life. In this paper, we proposed to study a case where the knowledge transferred from the S problem has less information than what the T problem needs. We sampled the transferred population using different strategies of TL. The results showed transfer part of the knowledge is helpful and speeds the GA process of finding a solution to the problem.

Keywords: transfer learning, partial transfer, evolutionary computation, genetic algorithm

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Authors: Gurjeet Singh, Harinder Singh

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In this paper, we present "The Language of Science in Higher Education: Related Questions and Discussions". Linguists have written and researched in depth the role of language in science. On this basis, it is clear that language is not just a medium or vehicle for communicating knowledge and ideas. Nor are there mere signs of language knowledge and conversion of ideas into code. In the process of reading and writing, everyone thinks deeply and struggles to understand concepts and make sense. Linguistics play an important role in achieving concepts. In the context of such linguistic diversity, there is no straightforward and simple answer to the question of which language should be the language of advanced science and technology. Many important topics related to this issue are as follows: Involvement in practical or Deep theoretical issues. Languages for the study of science and other subjects. Language issues of science to be considered separate from the development of science, capitalism, colonial history, the worldview of the common man. The democratization of science and technology education in India is possible only by providing maximum reading/resource material in regional languages. The scientific research should be increase to chances of understanding the subject. Multilingual instead or monolingual. As far as deepening the understanding of the subject is concerned, we can shed light on it based on two or three experiences. An attempt was made to make the famous sociological journal Economic and Political Weekly Hindi almost three decades ago. There were many obstacles in this work. The original articles written in Hindi were not found, and the papers and articles of the English Journal were translated into Hindi, and a journal called Sancha was taken out. Equally important is the democratization of knowledge and the deepening of understanding of the subject. However, the question is that if higher education in science is in Hindi or other languages, then it would be a problem to get job. In fact, since independence, English has been dominant in almost every field except literature. There are historical reasons for this, which cannot be reversed. As mentioned above, due to colonial rule, even before independence, English was established as a language of communication, the language of power/status, the language of higher education, the language of administration, and the language of scholarly discourse. After independence, attempts to make Hindi or Hindustani the national language in India were unsuccessful. Given this history and current reality, higher education should be multilingual or at least bilingual. Translation limits should also be increased for those who choose the material for translation. Writing in regional languages on science, making knowledge of various international languages available in Indian languages, etc., is equally important for all to have opportunities to learn English.

Keywords: language, linguistics, literature, culture, ethnography, punjabi, gurmukhi, higher education

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Authors: Komal Fizza

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Irrational and non-judicious use of antibiotics pave the way for an upsurge in antibiotic resistance, diminished effectiveness of different therapeutic regimens and as well as impounding effect on disease management leading to further morbidities. In the backdrop of this the current research is aimed to assess whether antimicrobial prescribing is in accordance with the Infectious Disease Society of America Guidelines in hospitalized patients at Shifa International Hospital, Islamabad, Pakistan. Shifa International Hospital, Islamabad is a 500 bed hospital. With the help of MIS team a form wad developed that gave the information about medical records number, name of the patient, day of start of antibiotic, the day antibiotic is supposed to be stopped and as well as the diagnosis of the patient. A ward pharmacist was employed to generate this report on a daily basis. The therapeutic regiment was reviewed by the pharmacist by monitoring the clinical progress, laboratory report and diagnosis. On the basis of this information, pharmacist made suggestions and forwarded to the hospital doctors responsible for prescribing antibiotics. If desired, changes were made regularly. In the current research our main focus was to implement this action and therefore, started monitoring patients who were on antibiotic regimens for more than 10-15 days. We took this initiative since November, 2013. At the start of the program a maximum 19 patients/day were reported to be on antibiotic regimen for more than 10-15 days. After the implementation of the initiative, the number of patients was decreased to fifteen patients per day in December, further decreased to 7 in the month of January and 9 and 6 in February and March respectively. The average patient census was 350. The current pilot study highlighted the role of pharmacist in initiating antibiotic stewardship programs in hospital settings.

Keywords: stewardship, antibiotics, resistance, clinical process

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Authors: Vania Helena Tonussi Vidal, Ester Eliane Jeunon

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This article aims to analyze the change processes of management related bureaucracy and learning organization model. The theoretical framework was based on Beer and Nohria (2001) model, identified as E and O Theory. Based on this theory the empirical research was conducted in connection with six key dimensions: goal, leadership, focus, process, reward systems and consulting. We used a case study of an educational Institution located in Barbacena, Minas Gerais. This traditional center of technical knowledge for long time adopted the bureaucratic way of management. After many changes in a business model, as the creation of graduate and undergraduate courses they decided to make a deep change in management model that is our research focus. The data were collected through semi-structured interviews with director, managers and courses supervisors. The analysis were processed by the procedures of Collective Subject Discourse (CSD) method, develop by Lefèvre & Lefèvre (2000), Results showed the incremental growing of management model toward a learning organization. Many impacts could be seeing. As negative factors we have: people resistance; poor information about the planning and implementation process; old politics inside the new model and so on. Positive impacts are: new procedures in human resources, mainly related to manager skills and empowerment; structure downsizing, open discussions channel; integrated information system. The process is still under construction and now great stimulus is done to managers and employee commitment in the process.

Keywords: bureaucracy, organizational learning, organizational change, E and O theory

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Authors: Prashant Neupane, Asmi Pandey, Mumna Ehsan, Katie Davies, Richard Lowsby

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Introduction/Background & aims: Safe and effective prescribing in hospitals, directly and indirectly, impacts the health of the patients. Even though digital prescribing in the National Health Service (NHS), UK has been used in lots of tertiary centers along with district general hospitals, a significant number of NHS trusts are still using paper prescribing. We came across lots of irregularities in our daily clinical practice when we are doing paper prescribing. The main aim of the study was to assess how safely and effectively are we prescribing at our hospital where there is no access to digital prescribing. Method/Summary of work: We conducted a prospective audit in the critical care department at Mid Cheshire Hopsitals NHS Foundation Trust in which 20 prescription charts from different patients were randomly selected over a period of 1 month. We assessed 16 multiple categories from each prescription chart and compared them to the standard trust guidelines on prescription. Results/Discussion: We collected data from 20 different prescription charts. 16 categories were evaluated within each prescription chart. The results showed there was an urgent need for improvement in 8 different sections. In 85% of the prescription chart, all the prescribers who prescribed the medications were not identified. Name, GMC number and signature were absent in the required prescriber identification section of the prescription chart. In 70% of prescription charts, either indication or review date of the antimicrobials was absent. Units of medication were not documented correctly in 65% and the allergic status of the patient was absent in 30% of the charts. The start date of medications was missing and alternations of the medications were not done properly in 35%of charts. The patient's name was not recorded in all desired sections of the chart in 50% of cases and cancellations of the medication were not done properly in 45% of the prescription charts. Conclusion(s): From the audit and data analysis, we assessed the areas in which we needed improvement in prescription writing in the Critical care department. However, during the meetings and conversations with the experts from the pharmacy department, we realized this audit is just a representation of the specialized department of the hospital where access to prescribing is limited to a certain number of prescribers. But if we consider bigger departments of the hospital where patient turnover is much more, the results could be much worse. The findings were discussed in the Critical care MDT meeting where suggestions regarding digital/electronic prescribing were discussed. A poster and presentation regarding safe and effective prescribing were done, awareness poster was prepared and attached alongside every bedside in critical care where it is visible to prescribers. We consider this as a temporary measure to improve the quality of prescribing, however, we strongly believe digital prescribing will help to a greater extent to control weak areas which are seen in paper prescribing.

Keywords: safe prescribing, NHS, digital prescribing, prescription chart

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Authors: Paulo Sérgio Ribeiro de Araújo Bogas

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Although several studies have assumed (at least implicitly) that learners' approaches to learning develop into deeper approaches to higher education, there appears to be no clear theoretical basis for this assumption and no empirical evidence. As a scientific contribution to this discussion, a pedagogical intervention of a quasi-experimental nature was developed, with a mixed methodology, evaluating the intervention within a single curricular unit of Marketing, using cases based on real challenges of brands, business simulation, and customer projects. Primary and secondary experiences were incorporated in the intervention: the primary experiences are the experiential activities themselves; the secondary experiences result from the primary experience, such as reflection and discussion in work teams. A diversified learning relationship was encouraged through the various connections between the different members of the learning community. The present study concludes that in the same context, the student's responses can be described as students who reinforce the initial deep approach, students who maintain the initial deep approach level, and others who change from an emphasis on the deep approach to one closer to superficial. This typology did not always confirm studies reported in the literature, namely, whether the initial level of deep processing would influence the superficial and the opposite. The result of this investigation points to the inclusion of pedagogical and didactic activities that integrate different motivations and initial strategies, leading to the possible adoption of deep approaches to learning since it revealed statistically significant differences in the difference in the scores of the deep/superficial approach and the experiential level. In the case of real challenges, the categories of “attribution of meaning and meaning of studied” and the possibility of “contact with an aspirational context” for their future professional stand out. In this category, the dimensions of autonomy that will be required of them were also revealed when comparing the classroom context of real cases and the future professional context and the impact they may have on the world. Regarding the simulated practice, two categories of response stand out: on the one hand, the motivation associated with the possibility of measuring the results of the decisions taken, an awareness of oneself, and, on the other hand, the additional effort that this practice required for some of the students.

Keywords: experiential learning, higher education, mixed methods, reflective learning, marketing

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Authors: Vineesh Amin, Ananya Agrawal

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In a prolonged period of uncertainty and disruptions in the pre-said normal order, non-cognitive skills, especially entrepreneurial mindsets, have become a pillar that can reform the educational models to inform the economy. Dreamverse Learning Lab’s IVR-based storytelling program -Call-a-Kahaani- is an evolving experiment with an aim to kindle entrepreneurial mindsets in the remotest locations of India in an accessible and engaging manner. At the heart of this experiment is the belief that at every phase in our life’s story, we have a choice which brings us closer to achieving our true potential. This interactive program is thus designed using real-time storytelling principles to empower learners, ages 24 and below, to make choices and take decisions as they become more self-aware, practice grit, try new things through stories, guided activities, and interactions, simply over a phone call. This research paper highlights the framework behind an ongoing scalable, data-oriented, low-tech program to kindle entrepreneurial mindsets in media dark zones supported by iterative design and prototyping to reach 13700+ unique learners who made 59000+ calls for 183900+min listening duration to listen to content pieces of around 3 to 4 min, with the last monitored (March 2022) record of 34% serious listenership, within one and a half years of its inception. The paper provides an in-depth account of the technical development, content creation, learning, and assessment frameworks, as well as mobilization models which have been leveraged to build this end-to-end system.

Keywords: non-cognitive skills, entrepreneurial mindsets, speech interface, remote learning, storytelling

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Authors: Danica Maljkovic, Igor Balen, Bojana Dalbelo Basic

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Following the regulation of EU Directive on Energy Efficiency, specifically Article 9, individual metering in district heating systems has to be introduced by the end of 2016. These directions have been implemented in member state’s legal framework, Croatia is one of these states. The directive allows installation of both heat metering devices and heat cost allocators. Mainly due to bad communication and PR, the general public false image was created that the heat cost allocators are devices that save energy. Although this notion is wrong, the aim of this work is to develop a model that would precisely express the influence of installation heat cost allocators on potential energy savings in each unit within multifamily buildings. At the same time, in recent years, a science of machine learning has gain larger application in various fields, as it is proven to give good results in cases where large amounts of data are to be processed with an aim to recognize a pattern and correlation of each of the relevant parameter as well as in the cases where the problem is too complex for a human intelligence to solve. A special method of machine learning, decision tree method, has proven an accuracy of over 92% in prediction general building consumption. In this paper, a machine learning algorithms will be used to isolate the sole impact of installation of heat cost allocators on a single building in multifamily houses connected to district heating systems. Special emphasises will be given regression analysis, logistic regression, support vector machines, decision trees and random forest method.

Keywords: district heating, heat cost allocator, energy efficiency, machine learning, decision tree model, regression analysis, logistic regression, support vector machines, decision trees and random forest method

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Authors: Patcharapa Thaweekul, Paskorn Sritipsukho

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Background: During the training period of the 6-year medical curriculum, medical students seem to have many risk behaviors of developing obesity. This study aims to demonstrate the prevalence and risk behavior of obesity and related metabolic disorders among the final-year medical students of Thammasat University as well as the change in nutritional status during studying program. Methods: 123 participants were asked to complete the self-report questionnaires. Weight, height, waist circumference and blood pressure were obtained. Blood samples were drawn for total cholesterol, high-density lipoprotein, low-density lipoprotein, triglycerides and plasma glucose. Body weight and height of the medical students in the first year were obtained from the medical report at the entry. Results: The prevalence of overweight and obesity at the entry to medical school was 22.0% and increased to 30.1% in the final year. Two obese students (5.4%) was diagnosed as metabolic syndrome. During 6-year curriculum, the BMI gained in male medical students were more significant as compared to female students (1.76±1.74 and 0.43±1.82 kg/m2, respectively; p <.001). The current BMI is significantly correlated with the BMI at entry. Serum LDL-C in the overweight/obese students was significantly higher as compared to the normal weight and underweight group. Sleep deprivation was a significantly frequent behavior in the overweight/obese students. Conclusion: Medical students, as having high-risk behaviors, should be assessed for the nutritional status and metabolic parameters. Medical schools should promote the healthy behaviors to increase the healthy eating and exercise habits and reduced the risk behaviors among them.

Keywords: medical students, metabolic syndrome, obesity, risk behaviors

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Authors: Teresa M. Odipo

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Inclusive physical education and an inclusive educational approach in German schools have received much attention in recent years due to the UN Convention on the rights of persons with disabilities proposals, which came into force in Germany in 2009. The aim of inclusive PE is to include children with disabilities and able bodied children, based on the idea, that all children should attend school together. While PE mostly took place in a heterogeneous environment, introducing children with all kinds of disabilities posed more challenges to the teachers, when children with disabilities were included. Therefore it is important that the educational approach should include pre-service teachers’ (PST) self-efficacy for and their attitudes towards inclusive practices. The PSTs’ self-efficacy for inclusive practices is one of the strongest predictors of the success of the inclusion reforms introduced in 2009, in order to improve PSTs’ ability to handle these very new challenges. PE stands out because the very nature of sport involves the body which means that all children, especially those with special needs should be treated in an appropriate manner. Up till now, it has been mostly English-speaking countries that have been assessed for inclusive practices in PE. Due to the lack of research in Germany, there is a strong need to question PSTs’ prepared-ness. This paper presents results from the 2016 survey conducted on around 100 PSTs by the German University of Sports in Cologne and opens up new directions within PSTs’ education, concerning their attitudes and self-efficacy towards inclusive PE. These new aspects will be included in the construction of new learning and teaching tools to improve pre-service teachers’ education for inclusive Physical Education.

Keywords: attitudes, inclusive physical education, pre-service teachers, self-efficacy

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Authors: Mehrnaz Mostafavi

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The assessment and categorization of incidental lung nodules present a considerable challenge in healthcare, often necessitating resource-intensive multiple computed tomography (CT) scans for growth confirmation. This research addresses this issue by introducing a distinct computational approach leveraging radiomics and deep-learning methods. However, understanding local services is essential before implementing these advancements. With diverse tracking methods in place, there is a need for efficient and accurate identification approaches, especially in the context of managing lung nodules alongside pre-existing cancer scenarios. This study explores the integration of text-based algorithms in medical data curation, indicating their efficacy in conjunction with machine learning and deep-learning models for identifying lung nodules. Combining medical images with text data has demonstrated superior data retrieval compared to using each modality independently. While deep learning and text analysis show potential in detecting previously missed nodules, challenges persist, such as increased false positives. The presented research introduces a Structured-Query-Language (SQL) algorithm designed for identifying pulmonary nodules in a tertiary cancer center, externally validated at another hospital. Leveraging natural language processing (NLP) and machine learning, the algorithm categorizes lung nodule reports based on sentence features, aiming to facilitate research and assess clinical pathways. The hypothesis posits that the algorithm can accurately identify lung nodule CT scans and predict concerning nodule features using machine-learning classifiers. Through a retrospective observational study spanning a decade, CT scan reports were collected, and an algorithm was developed to extract and classify data. Results underscore the complexity of lung nodule cohorts in cancer centers, emphasizing the importance of careful evaluation before assuming a metastatic origin. The SQL and NLP algorithms demonstrated high accuracy in identifying lung nodule sentences, indicating potential for local service evaluation and research dataset creation. Machine-learning models exhibited strong accuracy in predicting concerning changes in lung nodule scan reports. While limitations include variability in disease group attribution, the potential for correlation rather than causality in clinical findings, and the need for further external validation, the algorithm's accuracy and potential to support clinical decision-making and healthcare automation represent a significant stride in lung nodule management and research.

Keywords: lung cancer diagnosis, structured-query-language (SQL), natural language processing (NLP), machine learning, CT scans

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Authors: Uwaruile Austin Obuh

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This research work focuses on the use of computers in improving the academic performance of students in mathematics in Benin City, Edo State. To guide this study, two research questions were raised, and two corresponding hypotheses were formulated. A total of one hundred and twenty (120) respondents were randomly selected from four schools in the city (60 boys and 60 girls). The instrument employed for the collation of data for the study was the multiple-choice test items on geometry (MCTIOG), drawn from past senior school certificate examinations (SSCE) questions. The instrument was validated by an expert in mathematics and measurement and evaluation. The data obtained from the pre and post-test were analysed using the mean, standard deviation, and T-test. The study revealed a non-significant difference between the experimental and control group in the pre-test, and the two groups were found to be the same before treatment began. The study also revealed that the experimental group performed better than the control group. One can, therefore, conclude that the use of computers for mathematics instruction has improved the performance of students in Geometry. Therefore, the hypothesis was rejected. The study finally revealed that there was no significant difference between the boys and girls taught mathematics using a computer. Therefore, the hypothesis which states there will be no significant difference in the performance of boys and girls taught mathematics using the computer was not rejected. Consequent upon the findings of this study, a number of recommendations were postulated that would enhance the performance of teachers in the use of computer-aided instruction.

Keywords: computer, teaching, learning, mathematics

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Cristina Maria Mendoza Sanchez, Maria Angeles Navarro Perán

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Introduction: Nursing as a profession, from its initial formation and after its development in practice, has been built and identified mainly from its technical competence and professionalization within the positivist approach of the XIX century that provides a conception of the disease built on the basis of to the biomedical paradigm, where the care provided is more focused on the physiological processes and the disease than on the suffering person understood as a whole. The main issue that is in need of study here is a review of the nursing profession's history to get to know how the nursing profession was before the XIX century. It is unclear if there were organizations or people with knowledge about looking after others or if many people survived by chance. The holistic care, in which the appearance of the disease directly affects all its dimensions: physical, emotional, cognitive, social and spiritual. It is not a concept from the 21st century. It is common practice, most probably since established life in this world, with the final purpose of covering all these perspectives through quality care. Objective: In this paper, we describe and analyze the history of education in nursing learning in terms of reviewing and analysing theoretical foundations of clinical teaching and learning in nursing, with the final purpose of determining and describing the development of the nursing profession along the history. Method: We have done a descriptive systematic review study, doing a systematically searched of manuscripts and articles in the following health science databases: Pubmed, Scopus, Web of Science, Temperamentvm and CINAHL. The selection of articles has been made according to PRISMA criteria, doing a critical reading of the full text using the CASPe method. A compliment to this, we have read a range of historical and contemporary sources to support the review, such as manuals of Florence Nightingale and John of God as primary manuscripts to establish the origin of modern nursing and her professionalization. We have considered and applied ethical considerations of data processing. Results: After applying inclusion and exclusion criteria in our search, in Pubmed, Scopus, Web of Science, Temperamentvm and CINAHL, we have obtained 51 research articles. We have analyzed them in such a way that we have distinguished them by year of publication and the type of study. With the articles obtained, we can see the importance of our background as a profession before modern times in public health and as a review of our past to face challenges in the near future. Discussion: The important influence of key figures other than Nightingale has been overlooked and it emerges that nursing management and development of the professional body has a longer and more complex history than is generally accepted. Conclusions: There is a paucity of studies on the subject of the review to be able to extract very precise evidence and recommendations about nursing before modern times. But even so, as more representative data, an increase in research about nursing history has been observed. In light of the aspects analyzed, the need for new research in the history of nursing emerges from this perspective; in order to germinate studies of the historical construction of care before the XIX century and theories created then. We can assure that pieces of knowledge and ways of care were taught before the XIX century, but they were not called theories, as these concepts were created in modern times.

Keywords: nursing history, nursing theory, Saint John of God, Florence Nightingale, learning, nursing education

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Kevin R. Wilson, Roger Mantie

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Community arts-based learning and participatory education are pedagogical techniques that serve to be advantageous for students, curriculum development, and local communities. Using an interpretive approach to examine the significance of this arts-informed research in relation to the eight ‘design imperatives’ proposed as the new model for measuring quality in scholarship for Arizona State University as ‘A New American University’, the purpose of this study was to investigate personal, social, and cultural benefits resulting from student engagement in interdisciplinary community-based projects. Students from a graduate level music education class at the ASU Tempe campus (n=7) teamed with students from an undergraduate level community development class at the ASU Downtown Phoenix campus (n=14) to plan, facilitate, and evaluate seven community-based projects in several locations around the Phoenix-metro area. Data was collected using photo evidence, student reports, and evaluative measures designed by the students. The effectiveness of each project was measured in terms of their ability to meet the eight design imperatives to: 1) leverage place; 2) transform society; 3) value entrepreneurship; 4) conduct use-inspired research; 5) enable student success; 6) fuse intellectual disciplines; 7) be socially embedded; and 8) engage globally. Results indicated that this community arts-based project sufficiently captured the essence of each of these eight imperatives. Implications for how the nature of this interdisciplinary initiative allowed for the eight imperatives to manifest are provided, and project success is expounded upon in relation to utility of each imperative. Discussion is also given for how this type of service learning project formatted within the ‘New American University’ model for measuring quality in academia can be a beneficial pedagogical tool in higher education.

Keywords: community arts-based learning, participatory education, pedagogy, service learning

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Authors: May Ling González-Ruiz, Ana Cristina Solís-Solís

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Everyday more people can thrive towards the dream of pursuing a university diploma. This can be more attainable for some than for others who may face different types of limitations. Even though not all limitations come from within the individual but most of the times they come from without it may include the environment, the support of the person’s family, the school – its infrastructure, administrative procedures, and attitudes. This is a qualitative type of research that is developed through a case study. It is based on the experiences of two students who are visually impaired and who have attended a public university in Costa Rica. We enquire about the experiences of these two students in the English as a Foreign Language courses at the university scenario. An in-depth analysis of their lived experiences is presented. Their values, attitudes, and expectations serve as the guiding elements for this research. Findings are presented in light of the Social Justice Approach to inclusive education. Some of the most salient aspects found have to do with the attitudes the students used to face challenges; others point at those elements that may have hindered the learning experience of the persons observed and to those that encouraged them to continue their journey and successfully achieve a diploma.

Keywords: inclusion, case study, visually impaired student, learning experience, social justice approach

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Authors: Florence A. Undiyaundeye, Aniashie Akpanke

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Early identification of developmental disorders in infants and toddlers is critical for the well being of children. It is also an integral function of the primary care medical provider and the early care given in the home or crèche. This paper is focused at providing information on special need infants and toddlers and strategies to support them in developmental concern to cope with the challenges in and out of the classroom and to interact with their peers without stigmatization and inferiority complex. The target children are from birth through three years of age. There is a strong recommendation for developmental surveillance to be incorporated at every well child preventive care program in training and practical stage of formal school settings. The paper posits that any concerns raised during surveillance should be promptly addressed with standardized developmental screening by appropriate health service providers. In addition screening tests should be administered regularly at age 9+, 19+ and 30 months of these infants. The paper also establishes that the early identification of these developmental challenges of the infants and toddlers should lead to further developmental and medical evaluation, diagnosis and treatment, including early developmental school intervention, control and teaching and learning integration and inclusion for proper career build up. Children diagnosed with developmental disorders should be identified as children with special needs so that management is initiated and its underlying etiology may also drive a range of treatment of the child, to parents. Conselling and school integration as applicable to the child’s specific need and care for sustenance in societal functioning.

Keywords: care, special need, support, infants and toddlers, management and developmental disorders

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Authors: Saeed Eskandari, Seyed Rasoul Mehdikhani

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Radiation sources have been used in many industries, such as gamma sources in medical imaging. These waves have destructive effects on humans and the environment. It is very important to detect and find the source of these waves because these sources cannot be seen by the eye. A portable robot has been designed and built with the purpose of revealing radiation sources that are able to scan the place from 5 to 20 meters away and shows the location of the sources according to the intensity of the waves on a two-dimensional digital image. The operation of the robot is done by measuring the pixels separately. By increasing the image measurement resolution, we will have a more accurate scan of the environment, and more points will be detected. But this causes a lot of time to be spent on scanning. In this paper, to overcome this challenge, we designed a method that can optimize this time. In this method, a small number of important points of the environment are measured. Hence the remaining pixels are predicted and estimated by regression algorithms in machine learning. The research method is based on comparing the actual values of all pixels. These steps have been repeated with several other radiation sources. The obtained results of the study show that the values estimated by the regression method are very close to the real values.

Keywords: regression, machine learning, scan radiation, robot

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Authors: Ahmad Saleem

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Ethereum is the second largest crypto currency in blockchain ecosystem. Along with standard transactions, it supports smart contracts and NFT’s. Current research trends are focused on analyzing the overall structure of the network its growth and behavior. Ethereum addresses are anonymous and can be created on fly. The nature of Ethereum network and addresses make it hard to predict their behavior. The activity period of an ethereum address is not much analyzed. Using machine learning we can make early prediction about the disposability of the address. In this paper we analyzed the lifetime of the addresses. We also identified and predicted the disposable addresses using machine learning models and compared the results.

Keywords: blockchain, Ethereum, cryptocurrency, prediction

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Authors: Ling-Lang Huang, Yih-Jer Wu

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Empathy is crucial for a patient-physician relationship and medical professionalism. Internet activity, gaming, or even addiction, have been more and more common among medical students. However, there’s been no report showing whether internet behavior has a substantial impact on empathy in medical students to our best knowledge. All year-2 medical students taking the optional course 'Narrative, Comprehension, and Communication' were enrolled. Internet behaviors are divided into two groups, 'internet users without online gaming (IU)' and 'internet users with online gaming (IG)', each group was further divided into 3 groups according to their average online retention time each day (< 2, 2 - 6, > 6 hours). Empathy was evaluated by the scores of the reports and humanities reflection after watching indicated movies, and by self-measured empathy questionnaire. All students taking the year-2 optional course 'Narrative, Comprehension, and Communication' were enrolled. As compared with students in the IU group, those in the IG group had significantly lower scores for the reports (81.3 ± 3.7 vs. 86.4 ± 5.1, P = 0.014). If further dividing the students into 5 groups (IU < 2, IU 2-6, IG < 2, IG 2 - 6, and IG > 6 hours), the scores were significantly and negatively correlated to online gaming with longer hours (r = -0.556, P = 0.006). However, there was no significant difference between IU and IG groups (33.0 ± 5.4 vs. 34.8 ± 3.2, P = n.s.), in terms of scores in the self-measured empathy questionnaire, neither was there any significant trend of scores along with longer online hours across the 5 groups (r = -0.164, P = n.s.). To date, there has been no evidence showing whether different internet behaviors (with or without online gaming) have distinct impacts on empathy. Although all of the medical students had a similarly good self-perception for empathy, our data suggested that online gaming did have a negative impact on their actual expression of empathy. Our observation has brought up an important issue for pondering: May IT- or gaming-assisted medical learning actually harm students’ empathy? In conclusion, this data suggests that long hours of online gaming harms expression of empathy, though all medics think themselves a person of high empathy.

Keywords: empathy. Internet, medical students, online gaming

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Authors: Hasan Al Banna, Nazmus Sakib, Anjan Roy

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From the perspective of the underdeveloped countries such as Bangladesh, health issue can readily be pointed out as the most demanding but the least promoted concern due to lack of initiatives from both government and NGOs. Furthermore an worldwide scenario is that most death and suffering from various pathogenic and non-pathogenic diseases occur due to delay diagnosis, and this happen for the lacking of regular health check-up facility or tradition. In this epistle, an innovative proposal on social business can be introduced to ensure the one-stop medical facility to the door-step of the rural society and create jobs for the educated rural youths to serve their own people. To illustrate the policy, this newly proposed organization will work as a health club which will offer a life-time membership to villagers within a very affordable fee of 250 BDT (2.63 Euro) per month. In this package the members will get the facility of tri-monthly full health check-up by specialist doctors, a health record book and computerized health database for each member and anytime medical consultancy for the members only. We will also organize free medical campaign and workshops on nutrition, sanitation, adulteration, pregnancy-care, child-health etc with the assistance of different sponsors. Among other services that will be provided on payment include emergency ambulance facility in low rents, quality diagnostic lab and 24-hour dispensary facility. Likewise, this policy will involve local educated people by recruiting them after providing intensive courses on nursing and other medical instrumental skills. Henceforth, the engagement of local youth will make the program more acceptable to the rural community. In the later part of this paper, a survey report on Daragram union of Manikganj district, Bangladesh, having population above 25000, will be presented to delineate the scenario how this policy can repay the initial capital expense of BDT 7 million (around 73381 Euro) within 5 years and how I can realistically earn handsome revenue from the first month of business. To recapitulate, this policy is very promising to enlighten the underprivileged community by providing health assurance, and alleviating unemployment besides the investor’s financial profit.

Keywords: create job for the rural people, handsome financial profit, quality health services, underprivileged areas of underdeveloped countries

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Authors: Naor Cohen

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In recent years, business schools made teaching ethical leadership a higher priority. Greater attention to moral and ethical concepts and reasoning processes may prove beneficial to future business leaders. But with a shift in focus, there is a need for a shift in pedagogy. This paper explores an imaginative literature-based pedagogy in the teaching of ethical leadership. An imaginative literature-based pedagogy uses works of fiction to help students build moral analysis and moral judgment capabilities through a rigorous assessment of the moral soundness of actions, motivations, rationales, and consequences portrayed in works of fiction. Business students enrolled in 4 leadership senior-level courses were assigned the White Tiger: A Novel by Aravind Adiga as their main course reading. Students' engagement was measured as a three-factor construct exploring cognitive engagement, behavioural engagement and emotional engagement. In addition, students' final papers were analyzed using thematic content analysis. This paper will present the results of this analysis and argue that incorporating fiction into the leadership curriculum allows students to explore the dire consequences of avoiding countervailing interests, engaging in dishonesty and engaging in moral puffery-based leadership.

Keywords: ethical leadership, empathetic imagination, business education, pedagogy, fiction

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Authors: Saba Ebrahimi, Saeed Ahmadian, Hedie Ashrafi

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Selecting appropriate patients for surgery is one of the main issues in thoracic surgery (TS). Both short-term and long-term risks and benefits of surgery must be considered in the patient selection criteria. There are some limitations in the existing datasets of TS patients because of missing values of attributes and imbalanced distribution of survival classes. In this study, a novel ensemble architecture of deep learning networks is proposed based on stacking different linear and non-linear layers to deal with imbalance datasets. The categorical and numerical features are split using different layers with ability to shrink the unnecessary features. Then, after extracting the insight from the raw features, a novel biased-kernel layer is applied to reinforce the gradient of the minority class and cause the network to be trained better comparing the current methods. Finally, the performance and advantages of our proposed model over the existing models are examined for predicting patient survival after thoracic surgery using a real-life clinical data for lung cancer patients.

Keywords: deep learning, ensemble models, imbalanced classification, lung cancer, TS patient selection

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Authors: Ava Dodd, Jonathan Adams

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The purpose of this study is to explore the characteristics of developing a machine learning application using synthetic data. The study is structured to develop the application for the purpose of deploying the computer vision model. The findings discuss the realities of attempting to develop a computer vision model for practical purpose, and detail the processes, tools, and techniques that were used to meet accuracy requirements. The research reveals that synthetic data represents another variable that can be adjusted to improve the performance of a computer vision model. Further, a suite of tools and tuning recommendations are provided.

Keywords: computer vision, machine learning, synthetic data, YOLOv4

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Authors: Inezia Aurelia, Soebowo Musa

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Many firms still fail to develop organizational agility. There are more than 40% of organizations think that they are low/not agile in facing market change. Organizational culture plays an important role in developing the organizations to be adaptive in order to manage the VUCA effectively. This study examines the relationships of organizational culture towards participative leadership, employee satisfaction, employee work motivation, organizational learning, and absorptive capacity in developing organizational agility in managing the VUCA environment. 263 employees located from international chemical-based company offices across the globe who have worked for more than three years were the respondents in this study. This study showed that organizational clan culture promotes the development of participative leadership, which it has an empowering effect on people in the organization resulting in employee satisfaction. The study also confirms the role of organizational culture in creating organizational behavior within the organization that fosters organizational learning, absorptive capacity, and organizational agility, while the study also found that the relationship between participative leadership and employee work motivation is not significant.

Keywords: absorptive capacity, employee satisfaction, employee work motivation, organizational agility, organizational culture, organizational learning, participative leadership

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Authors: Mohit Kumar, Beklashwar Salona, Shiv Murti, Mukesh Singh

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We report here a case of five-months old male baby, born as second child of non-consanguineous parents with no considerable history of genetic abnormality which was referred to our cytogenetic laboratory for chromosomal analysis. Physical dysmorphic facial features including mongoloid face, cleft palate, simian crease, and developmental delay were observed. We present this case with unique balanced autosomal translocation of t(3;10)(p21;p13). The risk of phenotypic abnormalities based on de novo balanced translocation was estimated to be 7%. The association of balanced chromosomal rearrangement with Down syndrome features such as multiple congenital anomalies, facial dysmorphism and congenital heart anomalies are very rare in a 5-months old male child. Trisomy-21 is not uncommon in chromosomal abnormality with the birth defect and balanced translocations are frequently observed in patients with secondary infertility or recurrent spontaneous abortion (RSA). Two ml heparinized peripheral blood cells cultured in RPMI-1640 for 72 hours supplemented with 20% fetal bovine serum, phytohemagglutinin (PHA), and antibiotics were used for chromosomal analysis. A total 30 metaphases images were captured using Olympus-BX51 microscope and analyzed using Bio-view karyotyping software through GTG-banding (G bands by trypsin and Giemsa) according to International System for Human Cytogenetic Nomenclature 2016. The results showed balanced translocation between short arm of chromosome # 3 and short arm of chromosome # 10. The karyotype of the child was found to be 46,XY,t(3;10)(p21; p13). Chromosomal abnormalities are one of the major causes of birth defect in new born babies. Also, balanced translocations are frequently observed in patients with secondary infertility or recurrent spontaneous abortion. The index case presented with dysmorphic facial features and had a balanced translocation 46,XY,t(3;10)(p21;p13). This translocation with break points at (p21; p13) has not been reported in the literature in a child with facial dysmorphism. To the best of our knowledge, this is the first report of novel balanced translocation t(3;10) with break points in a child with dysmorphic features. We found balanced chromosomal translocation instead of any trisomy or unbalanced aberrations along with some phenotypic abnormalities. Therefore, we suggest that such novel balanced translocation with abnormal phenotype should be reported in order to enable the pathologist, pediatrician, and gynecologist to have a better insight into the intricacies of chromosomal abnormalities and their associated phenotypic features. We hypothesized that dysmorphic features as seen in this case may be the result of change in the pattern of genes located at the breakpoint area in balanced translocations or may be due to deletion or mutation of genes located on the p-arm of chromosome # 3 and p-arm of chromosome # 10.

Keywords: balanced translocation, karyotyping, phenotypic abnormalities, facial dimorphisms

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Authors: Hirokatsu Kawashima

Abstract:

In an attempt to elucidate relationships between listening to music and pronunciation learning, a classroom-based investigation was conducted with Japanese EFL learners (n=45). The subjects were instructed to listen to English songs they liked on YouTube, especially paying attention to phonologically similar vowel and consonant minimal pair words (e.g., live and leave). This kind of activity, which included taking notes, was regularly carried out in the classroom, and the same kind of task was given to the subjects as homework in order to reinforce the in-class activity. The duration of these activities was eight weeks, after which the program was evaluated on a 9-point scale (1: the lowest and 9: the highest) by learners’ self-evaluation. The main questions for this evaluation included 1) how good the learners had been at pronouncing vowel and consonant minimal pair words originally, 2) how often they had listened to songs good for pronouncing vowel and consonant minimal pair words, 3) how frequently they had moved their mouths to vowel and consonant minimal pair words of English songs, and 4) how much they thought the program would support and enhance their pronunciation learning of phonologically similar vowel and consonant minimal pair words. It has been found, for example, A) that the evaluation of this program is by no means low (Mean: 6.51 and SD: 1.23), suggesting that listening to music may support and enhance pronunciation learning, and B) that listening to consonant minimal pair words in English songs and moving the mouth to them are more related to the program’s evaluation (r =.69, p=.00 and r =.55, p=.00, respectively) than listening to vowel minimal pair words in English songs and moving the mouth to them (r =.45, p=.00 and r =.39, p=.01, respectively).

Keywords: minimal pair, music, pronunciation, song

Procedia PDF Downloads 304

Authors: Nicolas Koslover, Tamara Levene

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Aims: Tonsilitis is one of the most common presentations to the A+E department. We aimed to assess whether patients presenting with tonsilitis are being managed in-line with current guidance. We then set out to educate A+E staff about tonsilitis management and then assessed for improvement in management. Methods: All patients presenting to A+E in one fortnight with a documented diagnosis of tonsilitis were included. We reviewed the notes to assess the choice of treatment in each case and whether a clinical score (CENTOR or FEVERPain score) was used to guide choice of treatment (in accordance with NICE guideline [NG84]). We designed and delivered an educational intervention for A+E staff covering tonsilitis guidelines. The audit was repeated two weeks later. Results: Over the study period, 49 patients were included; only 35% (n=17) had either a clinical score documented or had all components of a score recorded. In total, 39% (n=19) were treated with antibiotics. Of these, 63% (n=12) should not have been prescribed an antibiotic and 37% (n=7) were prescribed an inappropriate antibiotic. At re-audit, (n=50 cases), 58% (n=29) had a clinical score documented and 28% (n=14) were treated with antibiotics. Of these, 29% (n=4) should not have been prescribed antibiotics and 21% (n=3) were prescribed an inappropriate antibiotic. Thus, after this teaching session, there was a significant improvement in antibiotic prescribing practices (63% vs. 29%, p=0.026). Conclusions: A+E assessment and management of tonsilitis frequently deviated from guidelines, but a single teaching session vastly improved clinical scoring and antibiotic prescribing practices.

Keywords: tonsilitis, education, emergency medicine, ENT

Procedia PDF Downloads 148