Search results for: digital learning environment

Authors: Ayse Tarhan, Mustafa Ilkan, Mohammad Karimzadeh

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Science was considered as part of philosophy in ancient Greece. By the nineteenth century, it was understood that philosophy was very inclusive and that social and human sciences such as literature, history, and psychology should be separated and perceived as an autonomous branch of science. The computer was also first seen as a tool of mathematical science. Over time, computer science has grown by encompassing every area in which technology exists, and its growth compelled the division of computer science into different disciplines, just as philosophy had been divided into different branches of science. Now there is almost no branch of science in which computers are not used. One of the newer autonomous disciplines of computer science is digital humanities, and one of the areas of digital humanities is literature. The material of literature is words, and thanks to the software tools created using computer programming languages, data that a literature researcher would need months to complete, can be achieved quickly and objectively. In this article, three different tools that literary researchers can use in their work will be introduced. These studies were created with the computer programming languages Python and R and brought to the world of literature. The purpose of introducing the aforementioned studies is to set an example for the development of special tools or programs on Ottoman language and literature in the future and to support such initiatives. The first example to be introduced is the Stylometry tool developed with the R language. The other is The Metrical Tool, which is used to measure data in poems and was developed with Python. The latest literature analysis tool in this article is Voyant Tools, which is a multifunctional and easy-to-use tool.

Keywords: DH, literature, information technologies, stylometry, the metrical tool, voyant tools

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Authors: T. Sikram, M. Ichinose, R. Sasaki

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In the tropics, indoor thermal environment is usually provided by a cooling mode to maintain comfort all year. Indoor thermal environment performance is sometimes different from the standard or from the first design process because of operation, maintenance, and utilization. The field study of thermal environment in the green building is still limited in this region, while the green building continues to increase. This study aims to clarify thermal performance and subjective perception in the green building by testing the temperature set-points. A Thai green office was investigated twice in October 2018 and in May 2019. Indoor environment variables (temperature, relative humidity, and wind velocity) were collected continuously. The temperature set-point was normally set as 23 °C, and it was changed into 24 °C and 25 °C. The study found that this gap of temperature set-point produced average room temperature from 22.7 to 24.6 °C and average relative humidity from 55% to 62%. Thermal environments slight shifted out of the ASHRAE comfort zone when the set-point was increased. Based on the thermal sensation vote, the feeling-colder vote decreased by 30% and 18% when changing +1 °C and +2 °C, respectively. Predicted mean vote (PMV) shows that most of the calculated median values were negative. The values went close to the optimal neutral value (0) when the set-point was set at 25 °C. The neutral temperature was slightly decreased when changing warmer temperature set-points. Building-related symptom reports were found in this study that the number of votes reduced continuously when the temperature was warmer. The symptoms that occurred by a cooler condition had the number of votes more than ones that occurred by a warmer condition. In sum, for this green office, there is a possibility to adjust a higher temperature set-point to +1 °C (24 °C) in terms of reducing cold sensitivity, discomfort, and symptoms. All results could support the policy of changing a warmer temperature of this office to become “a better green building”.

Keywords: thermal environment, green office, temperature set-point, comfort

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Authors: Mahathir Sarjan, Ramos Radzly, Noor Baiti Jamaluddin, Mohd Hafiz Zakaria, Hisham Suhadi

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Creativity is marked by the ability or power, to produce through imaginative skill and create something anew. The University is one of the great places to improve the talent in imaginative skill. Thus, it is important that for the student have a creativity to adapt the multimedia element in the development of presentation products for learning and teaching the process. The purpose of this study was to identify a creativity of the student in presentation product development. Two hundred seventeen Technical and Vocational Education (TVE) students in Universiti Tun Hussein Onn had chosen as a respondent. This study is to survey the level of creativity which is focused on knowledge, skills, presentation style and character of creative personnel. The level of creativity was measured based on the scale at low, medium and high followed by mean score level. The data collected by questionnaire then analyzed using SPSS version 20.0. The result of the study indicated that the students showed a higher of creativity (mean score in Knowledge = 4.12 and Skills= 4.02). In conjunction with the findings s implications and recommendations were suggested forward like to ensconce the research and improve with a more creativity concept in presentation product of development for learning and teaching the process.

Keywords: creativity, technical, vocational education, presentation products and development for learning and teaching process

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Authors: Suzan Wedyan

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Data mining is one of the main phases in the Knowledge Discovery Database (KDD) which is responsible of finding hidden and useful knowledge from databases. There are many different tasks for data mining including regression, pattern recognition, clustering, classification, and association rule. In recent years a promising data mining approach called associative classification (AC) has been proposed, AC integrates classification and association rule discovery to build classification models (classifiers). This paper surveys and critically compares several AC algorithms with reference of the different procedures are used in each algorithm, such as rule learning, rule sorting, rule pruning, classifier building, and class allocation for test cases.

Keywords: associative classification, classification, data mining, learning, rule ranking, rule pruning, prediction

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Authors: Piyanut Suchit

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The purposes of this study was to investigate students’ satisfaction learning with the web based instruction on the puppet show. The population of this study includes 53 students in the Program of Library and Information Sciences who registered in the subject of Puppet for Assisting Learning Development in semester 2/2011, Suansunandha Rajabhat University, Bangkok, Thailand. The research instruments consist of web based instruction on the puppet show, and questionnaires for students’ satisfaction. The research statistics includes arithmetic mean, and standard deviation. The results revealed that the students reported very high satisfaction with mean = 4.63, SD = 0.52, on the web based instruction.

Keywords: puppet show, web based instruction, satisfaction, Suansunandha Rajabhat University

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Authors: Chelali Mohammed

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In the context of the application of the competency-based approach in the system educational Algeria, the price of physical education and sport must privilege the acquisition of learning approaches and especially the approach science, which from problem situations, research and develops him information processing and application of knowledge and know-how in new situations in the words of ‘JOHN DEWEY’ ‘learning by practice’. And to achieve these goals and make teaching more EPS motivating, consistent and concrete, it is appropriate to perform a pedagogical approach freed from the constraints and open to creativity and student-centered in the light of the competency approach adopted in the formal curriculum. This approach is not unusual, but we think it is a highly professional nature requires the competence of the teacher.

Keywords: approach competencies, physical, education, teachers

Procedia PDF Downloads 592

Authors: Sînziana Iancu

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In an era marked by rapid urbanization and technological advancement, the concept of smart cities has emerged as a pivotal solution to address the complex challenges faced by urban centres. As cities strive to enhance the quality of life for their residents, the development of smart cities has gained prominence. This study embarks on a comparative analysis of two distinct smart city models, Singapore and Bucharest, to assess their resilience and technological advancements. The significance of this study lies in its potential to provide valuable insights into the strategies, strengths, and areas of improvement in smart city development, ultimately contributing to the advancement of urban planning and sustainability. Methodologies: This comparative study employs a multifaceted approach to comprehensively analyse the smart city development in Singapore and Bucharest: * Comparative Analysis: A systematic comparison of the two cities is conducted, focusing on key smart city indicators, including digital infrastructure, integrated public services, urban planning and sustainability, transportation and mobility, environmental monitoring, safety and security, innovation and economic resilience, and community engagement; * Case Studies: In-depth case studies are conducted to delve into specific smart city projects and initiatives in both cities, providing real-world examples of their successes and challenges; * Data Analysis: Official reports, statistical data, and relevant publications are analysed to gather quantitative insights into various aspects of smart city development. Major Findings: Through a comprehensive analysis of Singapore and Bucharest's smart city development, the study yields the following major findings: * Singapore excels in digital infrastructure, integrated public services, safety, and innovation, showcasing a high level of resilience across these domains; * Bucharest is in the early stages of smart city development, with notable potential for growth in digital infrastructure and community engagement.; * Both cities exhibit a commitment to sustainable urban planning and environmental monitoring, with room for improvement in integrating these aspects into everyday life; * Transportation and mobility solutions are a priority for both cities, with Singapore having a more advanced system, while Bucharest is actively working on improving its transportation infrastructure; * Community engagement, while important, requires further attention in both cities to enhance the inclusivity of smart city initiatives. Conclusion: In conclusion, this study serves as a valuable resource for urban planners, policymakers, and stakeholders in understanding the nuances of smart city development and resilience. While Singapore stands as a beacon of success in various smart city indicators, Bucharest demonstrates potential and a willingness to adapt and grow in this domain. As cities worldwide embark on their smart city journeys, the lessons learned from Singapore and Bucharest provide invaluable insights into the path toward urban sustainability and resilience in the digital age.

Keywords: bucharest, resilience, Singapore, smart city

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Authors: A. Goma Amira, U. E. Mahrous

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Measuring the effect of perinatal lead exposure on learning ability of offspring is considered as a sensitive and selective index for providing an early marker for central nervous system damage produced by this toxic metal. A total of 35 Sprague-Dawley adult rats were used to investigate the effect of lead acetate toxicity on behavioral patterns of adult female rats and learning ability of offspring. Rats were allotted into 4 groups, group one received 1g/l lead acetate (n=10), group two received 1.5g/l lead acetate (n=10), group three received 2g/l lead acetate in drinking water (n=10), and control group did not receive lead acetate (n=5) from 8th day of pregnancy till weaning of pups. The obtained results revealed a dose-dependent increase in the feeding time, drinking frequency, licking frequency, scratching frequency, licking litters, nest building, and retrieving frequencies, while standing time increased significantly in rats treated with 1.5g/l lead acetate than other treated groups and control. On the contrary, lying time decreased gradually in a dose-dependent manner. Moreover, movement activities were higher in rats treated with 1g/l lead acetate than other treated groups and control. Furthermore, time spent in closed arms was significantly lower in rats given 2g/l lead acetate than other treated groups, while they spent significantly much time spent in open arms than other treated groups which could be attributed to occurrence of adaptation. Furthermore, number of entries in open arms was-dose dependent. However, the ratio between open/closed arms revealed a significant decrease in rats treated with 2g/l lead acetate than the control group.

Keywords: lead toxicity, rats, learning ability, behavior

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Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

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Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

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Authors: Mostafa Fanaei, Shahram R. Sistani, Athare Nazri-Panjaki

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Introduction: Critical thinking skills are increasingly recognized as vital for academic success, particularly in higher education. This study examines the influence of critical thinking on learning achievement among undergraduate and master's students enrolled in foreign language programs. By investigating this correlation, educators can gain valuable insights into optimizing teaching methodologies and enhancing academic outcomes. Methods: This cross-sectional study involved 150 students from the Shahid Bahonar University of Kerman, recruited via random sampling. Participants completed the Critical Thinking Questionnaire (CThQ), assessing dimensions such as analysis, evaluation, creation, remembering, understanding, and application. Academic performance was measured using the students' GPA (0-20). Results: The participants' mean age was 21.46 ± 5.2 years, with 62.15% being female. The mean scores for critical thinking subscales were as follows: Analyzing (13.2 ± 3.5), Evaluating (12.8 ± 3.4), Creating (18.6 ± 4.8), Remembering (9.4 ± 2.1), Understanding (12.9 ± 3.3), and Applying (12.5 ± 3.2). The overall critical thinking score was 79.4 ± 18.1, and the average GPA was 15.7 ± 2.4. Significant positive correlations were found between GPA and several critical thinking subscales: Analyzing (r = 0.45, p = 0.013), Creating (r = 0.52, p < 0.001), Remembering (r = 0.29, p = 0.021), Understanding (r = 0.41, p = 0.002), and the overall CThQ score (r = 0.54, p = 0.043). Conclusion: The study demonstrates a significant positive relationship between critical thinking skills and learning achievement in foreign language programs. Enhancing critical thinking skills through educational interventions could potentially improve academic performance. Further research is recommended to explore the underlying mechanisms and long-term impacts of critical thinking on academic success.

Keywords: critical thinking, learning achievement, higher education, foreign language programs, student success

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Authors: Javier López

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This Paper presents the evaluation model designed for the virtual education branch of The “Universidad Manuela Beltrán, Bogotá-Colombia”. This was the result of a research, developed as a case study, which had three stages: Document review, observation, and a perception survey for teachers. In the present model, the evaluation is a cross-cutting issue to the educational process. Therefore, it consists in a group of actions and guidelines which lead to analyze the student’s learning process from the admission, during the academic training, and to the graduation. This model contributes to the evaluation components which might interest other educational institutions or might offer methodological guidance to consolidate an own model

Keywords: model, evaluation, virtual education, learning process

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Authors: Mohamad Reza Asariha

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The development and extension of modern communication innovations at an extraordinary speed has caused crucial changes in all financial, social, social and political areas of the world. The improvement of toady and cable innovations, in expansion to expanding the generation and dissemination needs of worldwide programs; the financial defense made it more appealing. The alter of the administration of mechanical economy to data economy and benefit economy in created nations brought approximately uncommon advancements within the standards of world exchange and as a result, it caused the extension of media organizations in outside measurements, and the advancement of financial speculations in many Asian nations, beside the worldwide demand for the utilization of media merchandise, made new markets, and the media both within the household scene of the nations and within the universal field. Universal and financial are of great significance and have and viable and compelling nearness within the condition of picking up, keeping up and expanding financial control and riches within the world. Moreover, mechanical progresses and mechanical joining are critical components in media auxiliary alter. This auxiliary alter took put beneath the impact of digitalization. That’s, the method that broke the boundaries between electronic media administrations. Until presently, the direction of mass media was totally subordinate on certain styles of data transmission that were for the most part utilized. Digitization made it conceivable for any content to be effortlessly transmitted through distinctive electronic transmission styles, and this media merging has had clear impacts on media approaches and the way mass media are controlled.

Keywords: media, digital era, digital ages, media convergence

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Authors: Babatunde Kasim Oladele

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One of the major objectives of the Nigeria national policy on education is the provision of equal educational opportunities to all citizens at different levels of education. With regards to higher education, an aspect of the policy encourages distance learning to be organized and delivered by tertiary institutions in Nigeria. This study therefore, determines how much of the Government resources are committed, how the resources are utilized and what alternative sources of funding are available for this system of education. This study investigated the trends in recurrent costs between 2004/2005 and 2013/2014 at University of Ibadan Distance Learning Centre (DLC). A descriptive survey research design was employed for the study. Questionnaire was the research instrument used for the collection of data. The population of the study was 280 current distance learning education students, 70 academic staff and 50 administrative staff. Only 354 questionnaires were correctly filled and returned. Data collected were analyzed and coded using the frequencies, ratio, average and percentages were used to answer all the research questions. The study revealed that staff salaries and allowances of academic and non-academic staff represent the most important variable that influences the cost of education. About 55% of resources were allocated to this sector alone. The study also indicates that costs rise every year with increase in enrolment representing a situation of diseconomies of scale. This study recommends that Universities who operates distance learning program should strive to explore other internally generated revenue option to boost their revenue. University of Ibadan, being the premier university in Nigeria, should be given foreign aid and home support, both financially and materially, to enable the institute to run a formidable distance education program that would measure up in planning and implementation with those of developed nation.

Keywords: open education, distance education, University of Ibadan, Nigeria, cost of education

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Authors: Lijuan Zhou, Mengqi Wu, Changyong Niu

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Attributed graph clustering can utilize the graph topology and node attributes to uncover hidden community structures and patterns in complex networks, aiding in the understanding and analysis of complex systems. Utilizing contrastive learning for attributed graph clustering can effectively exploit meaningful implicit relationships between data. However, existing attributed graph clustering methods based on contrastive learning suffer from the following drawbacks: 1) Complex data augmentation increases computational cost, and inappropriate data augmentation may lead to semantic drift. 2) The selection of positive and negative samples neglects the intrinsic cluster structure learned from graph topology and node attributes. Therefore, this paper proposes a method called self-supervised Attributed Graph Clustering with Dual Contrastive Loss constraints (AGC-DCL). Firstly, Siamese Multilayer Perceptron (MLP) encoders are employed to generate two views separately to avoid complex data augmentation. Secondly, the neighborhood contrastive loss is introduced to constrain node representation using local topological structure while effectively embedding attribute information through attribute reconstruction. Additionally, clustering-oriented contrastive loss is applied to fully utilize clustering information in global semantics for discriminative node representations, regarding the cluster centers from two views as negative samples to fully leverage effective clustering information from different views. Comparative clustering results with existing attributed graph clustering algorithms on six datasets demonstrate the superiority of the proposed method.

Keywords: attributed graph clustering, contrastive learning, clustering-oriented, self-supervised learning

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Authors: Sharifa Alduraibi, Abir El Sadik, Ahmed Elzainy, Alaa Alduraibi, Ahmed Alsolai

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Introduction: Problem-based learning (PBL) is an active student-centered educational modality, influenced by the students' interest that required continuous motivation to improve their engagement. The new era of professional information technology facilitated the utilization of educational multimedia, such as videos, soundtracks, and photographs promoting students' learning. The aim of the present study was to introduce multimedia-enriched PBL scenarios for the first time in college of medicine, Qassim University, as an incentive for better students' engagement. In addition, students' performance and satisfaction were evaluated. Methodology: Two multimedia-enhanced PBL scenarios were implemented to the third years' students in the urinary system block. Radiological images, plain CT scan, and X-ray of the abdomen and renal nuclear scan correlated with their pathological gross photographs were added to the scenarios. One week before the first sessions, pre-recorded orientation videos for PBL tutors were submitted to clarify the multimedia incorporated in the scenarios. Other two traditional PBL scenarios devoid of multimedia demonstrating the pathological and radiological findings were designed. Results and Discussion: Comparison between the formative assessments' results by the end of the two PBL modalities was done. It revealed significant increase in students' engagement, critical thinking and practical reasoning skills during the multimedia-enhanced sessions. Students' perception survey showed great satisfaction with the new strategy. Conclusion: It could be concluded from the current work that multimedia created technology-based teaching strategy inspiring the student for self-directed thinking and promoting students' overall achievement.

Keywords: multimedia, pathology and radiology images, problem-based learning, videos

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Authors: K. Sivasubramanin, S. Mahimairaja, S. Pavithrapriya

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Heavy metal pollution originating from industrial wastes is becoming a serious problem in many urban environments. These heavy metals, if not properly managed, could enter into the food chain and cause a serious health hazards in animals and humans. Industrial wastes, sewage sludge, and automobile emissions also contribute to heavy metal like Pb pollution in the urban environment. However, information is scarce on the heavy metal pollution in Coimbatore urban environment. Therefore, the current study was carried out to examine the extent of lead pollution in Coimbatore urban environment the maximum Pb concentration in Coimbatore urban environment was found in ukkadam, whose concentration in soils 352 mg kg-1. In many places, the Pb concentration was found exceeded the permissible limit of 100 mg kg-1. In laboratory, closed incubation experiment showed that the concentration of different species of Pb viz., water soluble Pb(H2O-Pb), exchangeable Pb(KNO3-Pb), organic-Pb(NaOH-Pb), and organic plus metal (Fe & Al) oxides bound-Pb(Na2 EDTA-Pb) was found significantly increased during the 15 days incubation, mainly due to biotransformation processes. Both the moisture content of soil and ambient temperature exerted a profound influence on the transformation of Pb. The results of a batch experiment has shown that the sorption data was adequately described by the Freundlich equation as indicated by the high correlation coefficients (R2= 0.64) than the Langmuir equation (R2 = 0.33). A maximum of 86 mg of Pb was found adsorbed per kilogram of soil. Consistently, a soil column experiment result had shown that only a small amount of Pb( < 1.0 µg g-1 soil) alone was found leached from the soil. This might be due to greater potential of the soil towards Pb adsorption.

Keywords: lead pollution, adsorption, transformation, heavy metal pollution

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Authors: I. Ling Tsai, Shu Fen Wu, Chen-Fuh Lam, Chia Yu Chen, Shu Jiuan Chen, Yen Lin Liu

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Purpose: Following the conduction of the National Health Insurance (NHI) system in Taiwan since 1995, the demand for anesthesia services continues to increase in the operating rooms and other medical units. It has been well recognized that increased work stress not only affects the clinical performance of the medical staff, long-term work load may also result in occupational burnout. Our study aimed to determine the influence of working environment, work stress and job satisfaction on the occupational burnout in nurse anesthetists. The ultimate goal of this research project is to develop a strategy in establishing a friendly, less stressful workplace for the nurse anesthetists to enhance their job satisfaction, thereby reducing occupational burnout and increasing the career life for nurse anesthetists. Methods: This was a cross-sectional, descriptive study performed in a metropolitan teaching hospital in southern Taiwan between May 2017 to July 2017. A structured self-administered questionnaire, modified from the Practice Environment Scale of the Nursing Work Index (PES-NWI), Occupational Stress Indicator 2 (OSI-2) and Maslach Burnout Inventory (MBI) manual was collected from the nurse anesthetists. The relationships between two numeric datasets were analyzed by the Pearson correlation test (SPSS 20.0). Results: A total of 66 completed questionnaires were collected from 75 nurses (response rate 88%). The average scores for the working environment, job satisfaction, and work stress were 69.6%, 61.5%, and 63.9%, respectively. The three perspectives used to assess the occupational burnout, namely emotional exhaustion, depersonalization and sense of personal accomplishment were 26.3, 13.0 and 24.5, suggesting the presence of moderate to high degrees of burnout in our nurse anesthetists. The presence of occupational burnout was closely correlated with the unsatisfactory working environment (r=-0.385, P=0.001) and reduced job satisfaction (r=-0.430, P=0.000). Junior nurse anesthetists (<1-year clinical experience) reported having higher satisfaction in working environment than the seniors (5 to 10-year clinical experience) (P=0.02). Although the average scores for work stress, job satisfaction, and occupational burnout were lower in junior nurses, the differences were not statistically different. The linear regression model, the working environment was the independent factor that predicted occupational burnout in nurse anesthetists up to 19.8%. Conclusions: High occupational burnout is more likely to develop in senior nurse anesthetists who experienced the dissatisfied working environment, work stress and lower job satisfaction. In addition to the regulation of clinical duties, the increased workload in the supervision of the junior nurse anesthetists may result in emotional stress and burnout in senior nurse anesthetists. Therefore, appropriate adjustment of clinical and teaching loading in the senior nurse anesthetists could be helpful to improve the occupational burnout and enhance the retention rate.

Keywords: nurse anesthetists, working environment, work stress, job satisfaction, occupational burnout

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Kerstin Grunden, Ann Svensson, Berit Forsman, Christina Karlsson, Ayman Obeid

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The research question of the article is to explore whether the dialogue meetings method could be relevant for reflective learning among researchers and practitioners when welfare technology should be implemented in municipalities, or not. A testbed was planned to be implemented in a retirement home in a Swedish municipality, and the practitioners worked with a pre-study of that testbed. In the article, the dialogue between the researchers and the practitioners in the dialogue meetings is described and analyzed. The potential of dialogue meetings as an arena for learning and reflection among researchers and practitioners is discussed. The research methodology approach is participatory action research with mixed methods (dialogue meetings, focus groups, participant observations). The main findings from the dialogue meetings were that the researchers learned more about the use of traditional research methods, and the practitioners learned more about how they could improve their use of the methods to facilitate change processes in their organization. These findings have the potential both for the researchers and the practitioners to result in more relevant use of research methods in change processes in organizations. It is concluded that dialogue meetings could be relevant for reflective learning among researchers and practitioners when welfare technology should be implemented in a health care organization.

Keywords: dialogue meetings, implementation, reflection, test bed, welfare technology, participatory action research

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Authors: Dini Riandini

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The research is aimed to find out the causes and effect of Andrea’s lifestyle changes and the other factors that contribute to Andrea’s lifestyle changes which influence Andrea’s behavior and personality in The Devil Wears Prada novel. The method of this research is descriptive qualitative method. Theory of Anderson (1999) about social psychology is used to figure out Andrea’s lifestyle changes. Lifestyle changes are influenced by social and environment in which people live. Andrea changes her lifestyle from simple to luxurious because of society and environment in which she lives. Social interaction creates humans’ lifestyles which influence their personality and behavior.

Keywords: lifestyle, lifestyle changes, personality, behaviour

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Authors: Stephen Grant Atkins

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Radical use of project-based learning (PBL) in a small New Zealand business school provides an opportunity to longitudinally examine its effects over a decade of pre-Covid data. Prior to this business school’s implementation of PBL, starting in 2012, the business pedagogy literature presented just one example of PBL replacing an entire core-set of courses. In that instance, a British business school merged four of its ‘degree Year 3’ accounting courses into one PBL semester. As radical as that would have seemed, to students aged 20-to-22, the PBL experiment conducted in a New Zealand business school was notably more extreme: 41 nationally-approved Learning Outcomes (L.O.s), these deriving from 8 separate core courses, were aggregated into one grand set of L.O.s, and then treated as a ‘full-year’/‘full-time’ single course. The 8 courses in question were all components of this business school’s compulsory ‘degree Year 1’ curriculum. Thus, the students involved were notably younger (…ages 17-to-19…), and no ‘part-time’ enrolments were allowed. Of interest are this PBL experiment’s effects on subsequent performance outcomes in ‘degree Years 2 & 3’ (….which continued to operate in their traditional ways). Of special interest is the quality of ‘group project’ outcomes. This is because traditionally, ‘degree Year 1’ course assessments are only minimally based on group work. This PBL experiment altered that practice radically, such that PBL ‘degree Year 1’ alumni entered their remaining two years of business coursework with far more ‘project group’ experience. Timeline-wise, thus of interest here, firstly, is ‘degree Year 2’ performance outcomes data from years 2010-2012 + 2016-2018, and likewise ‘degree Year 3’ data for years 2011-2013 + 2017-2019. Those years provide a pre-&-post comparative baseline for performance outcomes in students never exposed to this school’s radical PBL experiment. That baseline is then compared to PBL alumni outcomes (2013-2016….including’Student Evaluation of Course Quality’ outcomes…) to clarify ‘radical PBL’ effects.

Keywords: project-based learning, longitudinal mixed-methods, students criticism, effects-on-learning

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Authors: Ahmed S. Attia

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This paper includes a study of modern sustainable architectural techniques and elements that are originally found in vernacular and traditional architecture, particularly in the Arab region. Courtyards, Wind Catchers, and Mashrabiya, for example, are elements that have been developed in contemporary architecture using modern technology to create sustainable architecture designs. An analytical study of the topic will deal with some examples of the Islamic House in Fatimid Cairo city in Egypt, analyzing its elements and their relationship to the environment, in addition to the examples in southern Egypt (Nubba) of sustainable architecture systems, and traditional houses in Sana'a city, Yemen, using earth resources of mud bricks and other construction materials. In conclusion, a comparative study between traditional and contemporary techniques will be conducted to confirm that it is possible to achieve sustainable architecture through the use of low-technology in buildings in Arab regions.

Keywords: Islamic context, cultural environment, natural environment, Islamic house, low-technology, mud brick, vernacular and traditional architecture

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Authors: Shraddha Jain Sharma, Ratnalata Gupta

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Predicting stock movements in the financial market is both difficult and rewarding. Analysts and academics are increasingly using advanced approaches such as machine learning techniques to anticipate stock price patterns, thanks to the expanding capacity of computing and the recent advent of graphics processing units and tensor processing units. Stock market prediction is a type of time series prediction that is incredibly difficult to do since stock prices are influenced by a variety of financial, socioeconomic, and political factors. Furthermore, even minor mistakes in stock market price forecasts can result in significant losses for companies that employ the findings of stock market price prediction for financial analysis and investment. Soft computing techniques are increasingly being employed for stock market prediction due to their better accuracy than traditional statistical methodologies. The proposed research looks at the need for soft computing techniques in stock market prediction, the numerous soft computing approaches that are important to the field, past work in the area with their prominent features, and the significant problems or issue domain that the area involves. For constructing a predictive model, the major focus is on neural networks and fuzzy logic. The stock market is extremely unpredictable, and it is unquestionably tough to correctly predict based on certain characteristics. This study provides a complete overview of the numerous strategies investigated for high accuracy prediction, with a focus on the most important characteristics.

Keywords: stock market prediction, artificial intelligence, artificial neural networks, fuzzy logic, accuracy, deep learning, machine learning, stock price, trading volume

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Authors: Bolanle Deborah Motilewa, E. K. Rowland Worlu, Gbenga Mayowa Agboola, Ayodele Maxwell Olokundun

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Several studies have proposed a one-size fit all approach to Corporate Social Responsibility (CSR) practices, such that CSR as it applies to developed countries is adapted to developing countries, ignoring the differing institutional environments (such as the regulative, economic, social and political environments), which affects the profitability and practices of businesses operating in them. CSR as it applies to filling institutional gaps in developing countries, was categorized into four themes: environmental protection, product and service innovation, social innovation and local cluster development. Based on the four themes, the study employed a qualitative research approach through the use of interviews and review of available publications to study the influence of institutional environments on CSR practices engaged in by three renewable energy firms operating in Nigeria. Over the course of three 60-minutes sessions with the top management and selected workers of the firms, four propositions were made: regulatory environment influences environmental protection practice of Nigerian renewable firms, economic environment influences product and service innovation practice of Nigerian renewable energy firms, the social environment impacts on social innovation in Nigerian renewable energy firms, and political environment affects local cluster development practice of Nigerian renewable energy firms. It was also observed that beyond institutional environments, the international exposure of an organization’s managers reflected in their approach to CSR. This finding on the influence of international exposure on CSR practices creates an area for further study. Insights from this paper are set to help policy makers in developing countries, CSR managers, and future researchers.

Keywords: corporate social responsibility, renewable energy firms, institutional environment, social entrepreneurship

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Authors: Jimmy K. C. Lam, Carrie Wong

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One of the key goals on Learning and Teaching as documented in the University strategic plan 2012/13 – 2017/18 is to encourage active learning, the use of innovative teaching approaches and technology, and promoting the adoption of flexible and varied teaching delivery methods. This research reported the recent visited to Prof Eric Mazur at Harvard University on Peer Instruction: Collaborative learning in large class and innovative use of technology to enable new mode of learning. Peer Instruction is a research-based, interactive teaching method developed by Prof. Eric Mazur at Harvard University in the 1990s. It has been adopted across the disciplines, institutional type and throughout the world. One problem with conventional teaching lies in the presentation of the material. Frequently, it comes straight out of textbook/notes, giving students little incentive to attend class. This traditional presentation is always delivered as monologue in front of passive audience. Only exceptional lecturers are capable of holding students’ attention for an entire lecture period. Consequently, lectures simply reinforce students’ feelings that the most important step in mastering the material is memorizing a zoo of unrelated examples. In order to address these misconceptions about learning, Prof Mazur’s Team developed “Peer Instruction”, a method which involves students in their own learning during lectures and focuses their attention on underling concepts. Lectures are interspersed with conceptual questions called Concept Tests, designed to expose common difficulties in understanding the material. The students are given one or two minutes to think about the question and formulate their own answers; they then spend two or three minutes discussing their answers in a group of three or four, attempting to reach consensus on the correct answer. This process forces the students to think through the arguments being developed, and enable them to assess their understanding concepts before they leave the classroom. The findings from Peer Instruction and innovative use of technology on teaching at Harvard University were applied to the first year Textiles and Fashion students in Hong Kong. Survey conducted from 100 students showed that over 80% students enjoyed the flexibility of peer instruction and 70% of them enjoyed the instant feedback from the Clicker system (Student Response System used at Harvard University). Further work will continue to explore the possibility of peer instruction to art and fashion students.

Keywords: peer instruction, education, technology, fashion

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Authors: Abdullah M. Alzahrani, Abdel Halim Boussabaine

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There is an international consensus on the climate change in the entire world and this is as a result of the combination of the natural factors, such as volcanoes and hurricanes with increased of human activity on the earth, such as industrial renaissance. Where this solidarity increases emissions of greenhouse gases GHGs that considered as the main driver of climate change scenarios and related emerging risks and impacts on buildings. These climatic risks including damages, disruption and disquiet are set to increase and it is considered as the main challenges and difficulties facing built environment due to major implications on assets sector. Consequently, the threat from climate change patterns has a significant impact on a variety of complex human decisions, which affect all aspects of living. Understanding the relationship between buildings and such risks arising from climate change scenarios on buildings are the key in insuring the optimal timing and design of policies and systems, which affect all aspects of the built environment. This paper will uncovering this correlation between emerging climate change risks and the building assets. In addition, how these emerging risks can be classified in practical way in terms of their impact type on buildings. Hence, this mapping will assist professionals and interested parties in the building sector to cope with such risks in several systematic ways including development and designing of mitigation and adaptation strategies and processes of design, specification, construction, and operation; all these leads to successful management of assets.

Keywords: climate change, climate change risks, built environment, building sector, impacts

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Authors: B. Salehi, D. Andrews, I. Chaer, A. Gillich, A. Chalk, D. Bush

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With the rapid increase of energy consumption in buildings in recent years, especially with the rise in population and growing economies, the importance of energy savings in buildings becomes more critical. One of the key factors in ensuring energy consumption is controlled and kept at a minimum is to utilise building energy modelling at the very early stages of the design. So, building modelling and simulation is a growing discipline. During the design phase of construction, modelling software can be used to estimate a building’s projected energy consumption, as well as building performance. The growth in the use of building modelling software packages opens the door for improvements in the design and also in the modelling itself by introducing novel methods such as building information modelling-based software packages which promote conventional building energy modelling into the digital building design process. To understand the most effective implementation tools, research projects undertaken should include elements of real-world experiments and not just rely on theoretical and simulated approaches. Upon review of the related studies undertaken, it’s evident that they are mostly based on modelling and simulation, which can be due to various reasons such as the more expensive and time-consuming nature of real-time data-based studies. Taking in to account the recent rise of building energy software modelling packages and the increasing number of studies utilising these methods in their projects and research, the accuracy and reliability of these modelling software packages has become even more crucial and critical. This Energy Performance Gap refers to the discrepancy between the predicted energy savings and the realised actual savings, especially after buildings implement energy-efficient technologies. There are many different software packages available which are either free or have commercial versions. In this study, IES VE (Integrated Environmental Solutions Virtual Environment) is used as it is a common Building Energy Modeling and Simulation software in the UK. This paper describes a study that compares real time results with those in a virtual model to illustrate this gap. The subject of the study is a north west facing north-west (345°) facing, naturally ventilated, conservatory within a domestic building in London is monitored during summer to capture real-time data. Then these results are compared to the virtual results of IES VE, which is a commonly used building energy modelling and simulation software in the UK. In this project, the effect of the wrong position of blinds on overheating is studied as well as providing new evidence of Performance Gap. Furthermore, the challenges of drawing the input of solar shading products in IES VE will be considered.

Keywords: building energy modelling and simulation, integrated environmental solutions virtual environment, IES VE, performance gap, real time data, solar shading products

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Authors: Marina Karaseva

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The beginning of our century became a new digital epoch in the educational situation. Last decade the newest stage of this process had been initialized by the touch-screen mobile devices with program applications for them. The touch possibilities for learning fundamentals of music are of especially importance for music majors. The phenomenon of touching, firstly, makes it realistic to play on the screen as on music instrument, secondly, helps students to learn music theory while listening in its sound elements by music ear. Nowadays we can detect several levels of such mobile applications: from the basic ones devoting to the elementary music training such as intervals and chords recognition, to the more advanced applications which deal with music perception of non-major and minor modes, ethnic timbres, and complicated rhythms. The main purpose of the proposed paper is to disclose the main tendencies in this process and to demonstrate the most innovative features of music theory applications on the base of iOS and Android systems as the most common used. Methodological recommendations how to use these digital material musicologically will be done for the professional music education of different levels. These recommendations are based on more than ten year ‘iTheory’ teaching experience of the author. In this paper, we try to logically classify all types of ‘iTheory’mobile applications into several groups, according to their methodological goals. General concepts given below will be demonstrated in concrete examples. The most numerous group of programs is formed with simulators for studying notes with audio-visual links. There are link-pair types as follows: sound — musical notation which may be used as flashcards for studying words and letters, sound — key, sound — string (basically, guitar’s). The second large group of programs is programs-tests containing a game component. As a rule, their basis is made with exercises on ear identification and reconstruction by voice: sounds and intervals on their sounding — harmonical and melodical, music modes, rhythmic patterns, chords, selected instrumental timbres. Some programs are aimed at an establishment of acoustical communications between concepts of the musical theory and their musical embodiments. There are also programs focused on progress of operative musical memory (with repeating of sounding phrases and their transposing in a new pitch), as well as on perfect pitch training In addition a number of programs improvisation skills have been developed. An absolute pitch-system of solmisation is a common base for mobile programs. However, it is possible to find also the programs focused on the relative pitch system of solfegе. In App Store and Google Play Market online store there are also many free programs-simulators of musical instruments — piano, guitars, celesta, violin, organ. These programs may be effective for individual and group exercises in ear training or composition classes. Great variety and good sound quality of these programs give now a unique opportunity to musicians to master their music abilities in a shorter time. That is why such teaching material may be a way to effective study of music theory.

Keywords: ear training, innovation in music education, music theory, mobile devices

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Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

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In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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Authors: Zhiyong Zheng, Xu Li, Liang Huang, Zhengliang Sun, Jianhua Xu

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Yaw angle plays a significant role in many vehicle safety applications, such as collision avoidance and lane-keeping system. Although the estimation of the yaw angle has been extensively studied in existing literature, it is still the main challenge to simultaneously achieve a reliable and cost-effective solution in complex urban environments. This paper proposes a multi-stage learning framework to estimate the yaw angle with a monocular camera, which can deal with the challenge in a more reliable manner. In the first stage, an efficient road detection network is designed to extract the road region, providing a highly reliable reference for the estimation. In the second stage, a variational auto-encoder (VAE) is proposed to learn the distribution patterns of road regions, which is particularly suitable for modeling the changing patterns of yaw angle under different driving maneuvers, and it can inherently enhance the generalization ability. In the last stage, a gated recurrent unit (GRU) network is used to capture the temporal correlations of the learned patterns, which is capable to further improve the estimation accuracy due to the fact that the changes of deflection angle are relatively easier to recognize among continuous frames. Afterward, the yaw angle can be obtained by combining the estimated deflection angle and the road direction stored in a roadway map. Through effective multi-stage learning, the proposed framework presents high reliability while it maintains better accuracy. Road-test experiments with different driving maneuvers were performed in complex urban environments, and the results validate the effectiveness of the proposed framework.

Keywords: gated recurrent unit, multi-stage learning, reliable estimation, variational auto-encoder, yaw angle

Procedia PDF Downloads 123