Search results for: academic learning stress

Authors: S. Asplund, J. Åhlin, S. Åström, B. M. Lindgren

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The aim of this qualitative study was to describe experiences of work-related stress among highly stressed municipal employees in rural northern Sweden. We interviewed 15 employees in the municipal sector in rural northern Sweden using a semi-structured guide and subjected the interviews to qualitative content analysis. Under the main theme of Suffering Though Endless Chaos, we summarized four themes: facing incompatible interests and high demands due to lack of time and resources; feeling powerless, trapped, and ignored due to lack of control; feeling insufficient, insecure, and guilty due to challenging relations and high expectations; and struggling with consequences such as health problems, spillover effects on family life, and difficulty coping. Findings from this study suggest the importance of acknowledging suffering among municipal employees in a stressful work environment. An imbalance between job demands and resources is affecting both the health and family lives of employees and also their ability to work. It seems important to improve the work environment through supportive leadership, job control, and reasonable job demands to prevent stress, reduce suffering, and create a healthy organization.

Keywords: manager, municipal sector, occupational health, qualitative content analysis

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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: Sadia Siddiqa, Z. Khan, M. A. Hossain

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In this article, the effect of thermal radiation on mixed convection boundary layer flow of a viscous fluid along a highly heated vertical flat plate is considered with varying density and volumetric expansion coefficient. The density of the fluid is assumed to vary exponentially with temperature, however; volumetric expansion coefficient depends linearly on temperature. Boundary layer equations are transformed into convenient form by introducing primitive variable formulations. Solutions of transformed system of equations are obtained numerically through implicit finite difference method along with Gaussian elimination technique. Results are discussed in view of various parameters, like thermal radiation parameter, volumetric expansion parameter and density variation parameter on the wall shear stress and heat transfer rate. It is concluded from the present investigation that increase in volumetric expansion parameter decreases wall shear stress and enhances heat transfer rate.

Keywords: thermal radiation, mixed convection, variable density, variable volumetric expansion coefficient

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Authors: Nor Erlissa Abd Aziz, R. M. U. S. Udagedara, S. Sharifi

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Managing and sharing knowledge has been a broadly satisfactory strategy to most of the organisations. Harnessing the power of knowledge supported the organisations to gain a competitive advantage over their competitors. Along with the invention of social media, knowledge sharing process has been more efficient and comfortable. Numerous researches have been conducted to investigate the effect of social media platforms for public and academic use. Furthermore, knowledge sharing, in general, have been subject to considerable n research, but research on sharing knowledge in Higher Education Institutions (HEIs) is rare. Also, it is noted that still there is a gap related to the organisational elements that contribute to the successful knowledge sharing through social media platforms. Thus, this research aims to investigate organisational elements that influence the social media platform based knowledge sharing within the context of Malaysian Higher Education Institutions (HEIs). The research used qualitative research methods to get an in-depth understanding of the subject matter. The conclusions of this study are based on interpreting the results of semi-structured interviews with academic staff from various Malaysian HEIs from the public and private sectors. Documents review will supplement the data from the interviews, and this ensures triangulation of the responses and thus increase the validity of the research. This research contributes to the literature by investigating an in-depth understanding the role of organisational elements about the social media platform based knowledge sharing in nourishing knowledge and spreading it to become better HEIs in utilising their knowledge. The proposed framework which identifies the organisational elements influences of social media platform based knowledge sharing will present as the main contribution of this research.

Keywords: knowledge sharing, social media, knowledge and knowledge management

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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: Diane Ghanem, Arjun Gupta, Rohan Vijayan, Ali Uneri, Babar Shafiq

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Introduction: Ankle sprains and fractures often result in syndesmosis injuries. Unstable syndesmotic injuries result from relative motion between the distal ends of the tibia and fibula, anatomic juncture which should otherwise be rigid, and warrant operative management. Clinical and radiological evaluations of intraoperative syndesmosis stability remain a challenging task as traditional 2D fluoroscopy is limited to a uniplanar translational displacement. The purpose of this pilot cadaveric study is to compare the 2D fluoroscopy and 3D cone beam computed tomography (CBCT) stress-induced syndesmosis displacements. Methods: Three fresh-frozen lower legs underwent 2D fluoroscopy and 3D CIOS CBCT to measure syndesmosis position before dissection. Syndesmotic injury was simulated by resecting the (1) anterior inferior tibiofibular ligament (AITFL), the (2) posterior inferior tibiofibular ligament (PITFL) and the inferior transverse ligament (ITL) simultaneously, followed by the (3) interosseous membrane (IOM). Manual external rotation and Cotton stress test were performed after each of the three resections and 2D and 3D images were acquired. Relevant 2D and 3D parameters included the tibiofibular overlap (TFO), tibiofibular clear space (TCS), relative rotation of the fibula, and anterior-posterior (AP) and medial-lateral (ML) translations of the fibula relative to the tibia. Parameters were measured by two independent observers. Inter-rater reliability was assessed by intraclass correlation coefficient (ICC) to determine measurement precision. Results: Significant mismatches were found in the trends between the 2D and 3D measurements when assessing for TFO, TCS and AP translation across the different resection states. Using 3D CBCT, TFO was inversely proportional to the number of resected ligaments while TCS was directly proportional to the latter across all cadavers and ‘resection + stress’ states. Using 2D fluoroscopy, this trend was not respected under the Cotton stress test. 3D AP translation did not show a reliable trend whereas 2D AP translation of the fibula was positive under the Cotton stress test and negative under the external rotation. 3D relative rotation of the fibula, assessed using the Tang et al. ratio method and Beisemann et al. angular method, suggested slight overall internal rotation with complete resection of the ligaments, with a change < 2mm - threshold which corresponds to the commonly used buffer to account for physiologic laxity as per clinical judgment of the surgeon. Excellent agreement (>0.90) was found between the two independent observers for each of the parameters in both 2D and 3D (overall ICC 0.9968, 95% CI 0.995 - 0.999). Conclusions: The 3D CIOS CBCT appears to reliably depict the trend in TFO and TCS. This might be due to the additional detection of relevant rotational malpositions of the fibula in comparison to the standard 2D fluoroscopy which is limited to a single plane translation. A better understanding of 3D imaging may help surgeons identify the precise measurements planes needed to achieve better syndesmosis repair.

Keywords: 2D fluoroscopy, 3D computed tomography, image processing, syndesmosis injury

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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: Nimrod Bantigue

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The Department of Education is continuously providing safe teaching-learning facilities and hazard-free environments to the learners. To achieve this goal, teachers’ awareness of DepEd’s DRRM programs and activities is extremely important; thus, this descriptive correlational quantitative study was conceptualized. This research answered four questions on the profile and level of awareness of the 153 teacher respondents of Oriental Mindoro National High School for the academic year 2018-2019. Stratified proportional sampling was employed, and both descriptive and inferential statistics were utilized to treat data. The findings revealed that the majority of the teachers at OMNHS are female and are in the age bracket of 20-40. Most are married and pursue graduate studies. They have moderate awareness of the Department of Education’s DRRM programs and activities in terms of assessment of risks activities, planning activities, implementation activities during disaster and evaluation and monitoring activities with 3.32, 3.12, 3.40 and 3.31 as computed means, respectively. Further, the result showed a significant relationship between the profile of the respondents such as age, civil status and educational attainment and the level of awareness. On the contrary, sex does not have a significant relationship with the level of awareness. The Support School DRRM program with Utilization Guide on School DRRM Manual was proposed to increase, improve and strengthen the weakest areas of awareness rated in each DRRM activity, such as assessment of risks, planning, and implementation during disasters and monitoring and evaluation.

Keywords: awareness, management, monitoring, risk reduction

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Authors: Imed Mezghani, Yousra Ben Salah, Mohamed Chaieb

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Tricholaena teneriffae L. is a xerophytic perennial herb that belongs to the Poaceae family likely to be used for ecological restoration programs. It's a dominant and economically important species widely distributed in the Bou-Hedma National Park, Tunisia. Reintroduction and expansion of T. teneriffae depend solely on sexual reproduction. This makes the understanding of its germination requirements vital for conservation and management. To provide basic information for its conservation and reintroduction, we studied the influence of environmental factors on seed germination patterns. The germination responses of seeds were determined over a wide range of constant temperatures (15–35°C), polyethylene glycol solutions of different osmotic potentials (0 to −2 MPa) and salt solution (0 to 150 mM of NaCl). Results indicated that the optimum temperature germination was attained at 25°C which corresponds to temperatures prevailing during mid spring season in the Mediterranean area. Seeds germinated in Polyethylene Glycol solutions exhibited significantly lower germination than control especially when water potential fell below -0.6 MPa. Germination percentage and rate decreased with an increase NaCl concentration. Seeds germination was substantially delayed and reduced with an increase in NaCl to levels above 50 mM. T. teneriffae is moderately salt tolerant at germination stage.

Keywords: germination, temperature, Tricholaena teneriffae L., salt stress, water stress, rehabilitation

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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: I. A. Libata

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The present study was carried out to determine the attitudes of Secondary School Students towards Biology in Birnin Kebbi metropolis. The population of the study is 2680 SS 2 Secondary School Students in Birnin Kebbi metropolis. Proportionate random sampling was used in selecting the samples. Oppinnionnaire was the only instrument used in the study. The instrument was subjected to test-retest reliability. The reliability index of the instrument was 0.69. Overall scores of the Students were analyzed and a mean score was determined, the mean score of students was 85. There were no significant differences between the attitudes of male and female students. The results also revealed that there was significant difference between the attitude of science and art students. The results also revealed that there was significant difference between the attitude of public and private school students. The study also reveals that majority of students in Birnin Kebbi Metropolis have positive attitudes towards biology. Based on the findings of this study, the researcher recommended that teachers should motivate students, which they can do through their teaching styles and by showing them the relevance of the learning topics to their everyday lives. Government and the school management should create the learning environment that helps motivate students not only to come to classes but also want to learn and enjoy learning Biology.

Keywords: attitudes, students, Birnin-Kebbi, metropolis

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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: Ghada Ben Brahim, Aicha El Rabia, Mohamed Hedi Inoubli

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Climate change has exacerbated disparities in the distribution of water resources in Tunisia, resulting in significant degradation in quantity and quality over the past five decades. The Mio-Plio-Quaternary aquifer, the primary water source in the Zarzis region, is subject to climatic, geographical, and geological challenges, as well as human stress. The region is experiencing uneven distribution and growing threats from groundwater salinity and saltwater intrusion. Addressing this challenge is critical for the arid region’s socioeconomic development, and effective water resource management is required to combat climate change and reduce water deficits. This study uses a multidisciplinary approach to determine the groundwater potential of this aquifer, involving geophysics and hydrogeology data analysis. We used advanced techniques such as 3D Euler deconvolution and power spectrum analysis to generate detailed anomaly maps and estimate the depths of density sources, identifying significant Bouguer anomalies trending E-W, NW-SE, and NE-SW. Various techniques, such as wavelength filtering, upward continuation, and horizontal and vertical derivatives, were used to improve the gravity data, resulting in consistent results for anomaly shapes and amplitudes. The Euler deconvolution method revealed two prominent surface faults, trending NE-SW and NW-SE, that have a significant impact on the distribution of sedimentary facies and water quality within the Mio-Plio-Quaternary aquifer. Additionally, depth maxima greater than 1400 m to the North indicate the presence of a Cretaceous paleo-fault. Geoelectrical models and resistivity pseudo-sections were used to interpret the distribution of electrical facies in the Mio-Plio-Quaternary aquifer, highlighting lateral variation and depositional environment type. AI optimises the analysis and interpretation of exploration data, which is important to long-term management and water security. Machine learning algorithms and deep learning models analyse large datasets to provide precise interpretations of subsurface conditions, such as aquifer salinisation. However, AI has limitations, such as the requirement for large datasets, the risk of overfitting, and integration issues with traditional geological methods.

Keywords: mio-plio-quaternary aquifer, Southeastern Tunisia, geophysical methods, hydrogeological analysis, artificial intelligence

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Authors: Alshutwi Sitah

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Many countries around the world are struggling to maintain an adequate number of nurses. Inadequate nursing staffing could compromise the quality of patient care. Among many factors that contribute to registered nurses (RN) turnover, the influence of work–family conflict (WFC) has gained little attention. WFC was found to be significantly associated with increased turnover intention (TI) among employees. Furthermore, WFC has been linked to a number of negative consequences, including lower job satisfaction and organizational commitment, sleep insufficiency, insomnia symptoms, obesity, cardiovascular diseases, sleep insufficiency, and high cholesterol. In an effort to find strategies to manage the consequences of WFC, many behavioral, psychological, and career scholars have focused on the role of supervisor support. Family Supportive Supervisor Behaviors (FSSB) has been found to be a promising approach contributing to the reduction of TI in employees’ experiencing WFC. Despite the importance of work–family issues and the influence of FSSB, limited studies have been conducted among the nursing population and none were found that included a sample from Saudi Arabia. Therefore, the main Purpose of this study was to evaluate the influence of FSSB on the relationship among WFC, Stress, and TI in Saudi Arabian registered nurses. Method: A cross-sectional study. Sample: Convenience sampling; 113 Saudi female nurse. Result: Fifty percent of nurses intended to leave their workplace, 68 % of nurses reported having a conflict between work and family, and 44% reported having a high level of stress. A significant positive correlation was found between WFC and TI (r= .43, P < 0.01). A negative correlation was found between FSSB and TI (r= -.53, P < 0.01). Both WFC and stress were associated with TI; however, these associations were buffered (weaken), when nurses had higher FSSB. Conclusion: The FSSB could be seen as a tool to help married, female nurses to demonstrate their professional role without compromising their family responsibilities. Nurses’ turnover is a complex issue that may require multiple prevention strategies; however, enhancing FSSB could be a key resource for maintaining a positive workplace environment and reducing TI.

Keywords: turnover intention, work-family conflict, supervisor support, nursing retention

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Authors: Rohan Roberts

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The purpose of this project was to collaborate with a group of high-functioning, more-able students (aged 15-18) to promote STEM Education and a love for science by bringing a cosmic perspective into the classroom and high school environment. This was done using 21st century science of learning, a focus on the latest research on Neuroeducation, and modern pedagogical methods based on Howard Gardner's theory of Multiple Intelligences, Bill Lucas’ theory of New Smarts, and Sir Ken Robinson’s recommendations on encouraging creativity. The result was an increased sense of passion, excitement, and wonder about science in general, and about the marvels of space and the universe in particular. In addition to numerous unique and innovative science-based initiatives, clubs, workshops, and science trips, this project also saw a marked rise in student-teacher collaboration in science learning and in student engagement with the general public through the press, social media, and community-based initiatives. This paper also outlines the practical impact that bringing a cosmic perspective into the classroom has had on the lives, interests, and future career prospects of the students involved in this endeavour.

Keywords: cosmic perspective, gifted and talented, neuro-education, STEM education

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Authors: J. R. Büttler, T. Pham

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Basic understanding of interfacial mechanisms is of importance for the development of polymer composites. For this purpose, we need techniques to analyze the quality of interphases, their chemical and physical interactions and their strength and fracture resistance. In order to investigate the interfacial phenomena in detail, advanced characterization techniques are favorable. Dynamic mechanical thermal analysis (DMTA) using a rheological system is a sensitive tool. T-peel tests were performed with this system, to investigate the temperature-dependent peel behavior of woven textile composites. A model system was made of polyamide (PA) woven fabric laminated with films of polypropylene (PP) or PP modified by grafting with maleic anhydride (PP-g-MAH). Firstly, control measurements were performed with solely PP matrixes. Polymer melt investigations, as well as the extensional stress, extensional viscosity and extensional relaxation modulus at -10°C, 100 °C and 170 °C, demonstrate similar viscoelastic behavior for films made of PP-g-MAH and its non-modified PP-control. Frequency sweeps have shown that PP-g-MAH has a zero phase viscosity of around 1600 Pa·s and PP-control has a similar zero phase viscosity of 1345 Pa·s. Also, the gelation points are similar at 2.42*104 Pa (118 rad/s) and 2.81*104 Pa (161 rad/s) for PP-control and PP-g-MAH, respectively. Secondly, the textile composite was analyzed. The extensional stress of PA66 fabric laminated with either PP-control or PP-g-MAH at -10 °C, 25 °C and 170 °C for strain rates of 0.001 – 1 s^-1 was investigated. The laminates containing the modified PP need more stress for T-peeling. However, the strengthening effect due to the modification decreases by increasing temperature and at 170 °C, just above the melting temperature of the matrix, the difference disappears. Independent of the matrix used in the textile composite, there is a decrease of extensional stress by increasing temperature. It appears that the more viscous is the matrix, the weaker the laminar adhesion. Possibly, the measurement is influenced by the fact that the laminate becomes stiffer at lower temperatures. Adhesive lap-shear testing at room temperature supports the findings obtained with the T-peel test. Additional analysis of the textile composite at the microscopic level ensures that the fibers are well embedded in the matrix. Atomic force microscopy (AFM) imaging of a cross section of the composite shows no gaps between the fibers and matrix. Measurements of the water contact angle show that the MAH grafted PP is more polar than the virgin-PP, and that suggests a more favorable chemical interaction of PP-g-MAH with PA, compared to the non-modified PP. In fact, this study indicates that T-peel testing by DMTA is a technique to achieve more insights into polymeric textile composites.

Keywords: dynamic mechanical thermal analysis, interphase, polyamide, polypropylene, textile composite

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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: Hussain Darraj

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Background: Healthcare workers, especially nurses, are subjected to a great risk of psychological stress, mostly moral distress. Therefore, it is crucial to address moral distress in nurses. Objectives: The aim of this study is to study the extent of moral distress among hospital nurses in Jazan. Methods: This study used a cross-sectional study design, which included 419 nurses from Jazan hospitals. A questionnaire was used to measure moral distress and its related factors. Results: The average total score for moral distress among the study participants is 134.14, with a standard deviation of 53.94. Moreover, the current study findings indicate that those over the age of 35 years who work as nurse managers, working in critical departments, have the intention to leave a position, have received ethical training or workshops, have provided care for COVID-19 cases, or work in a department with staff shortages are associated with the experience of higher-level moral stress. Conclusion: Nurses are recommended to be provided with ongoing education and resources in order to reduce moral distress and create a positive work atmosphere for nurses. Moreover, the current study sheds light on the importance of organizational support to provide enough resources and staffing in order to reduce moral distress among nurses. Further research is needed to focus on other health professionals and moral distress. Moreover, future studies are also required to explore the strategies to reduce moral distress levels among nurses.

Keywords: moral distress, Jazan, nurses, hospital

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Authors: Colleen Cleveland, W. Adam Baldowski

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In the dynamic realm of online education, the integration of games and entertainment has emerged as a powerful strategy to captivate learners, drive active participation, and cultivate meaningful learning experiences. This abstract presents an overview of the upcoming conference, "Game On," dedicated to exploring the transformative impact of gamification, interactive simulations, and multimedia content in the digital learning landscape. Introduction: The conference aims to blur the traditional boundaries between education and entertainment, inspiring learners of diverse ages and backgrounds to actively engage in their online learning journeys. By leveraging the captivating elements of games and entertainment, educators can enhance motivation, retention, and deep understanding among virtual classroom participants. Conference Highlights: Commencing with an exploration of theoretical foundations drawing from educational psychology, instructional design, and the latest pedagogical research, participants will gain valuable insights into the ways gamified elements elevate the quality of online education. Attendees can expect interactive sessions, workshops, and case studies showcasing best practices and innovative strategies, including game-based assessments and virtual reality simulations. Inclusivity and Diversity: The conference places a strong emphasis on inclusivity, accessibility, and diversity in the integration of games and entertainment for educational purposes. Discussions will revolve around accommodating diverse learning styles, overcoming potential challenges, and ensuring equitable access to engaging educational content for all learners. Educational Transformation: Educators, instructional designers, and e-learning professionals attending "Game On" will acquire practical techniques to elevate the quality of their online courses. The conference promises a stimulating and informative exploration of blending education with entertainment, unlocking the untapped potential of games and entertainment in online education. Conclusion: "Game On" invites participants to embark on a journey that transforms online education by harnessing the power of entertainment. This event promises to be a cornerstone in the evolution of virtual learning, offering valuable insights for those seeking to create a more engaging and effective online educational experience. Join us as we explore new horizons, pushing the boundaries of online education through the fusion of games and entertainment.

Keywords: online education, games, entertainment, psychology, therapy, pop culture

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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: Zelalem Markos Borko

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The quality of life of people with blindness is significantly influenced by the level of resilience they possess. A qualitative approach of the descriptive phenomenological design was employed to address basic study objectives. The researcher purposely selected three blind graduate students from Sidist Kilo Campus and conducted a semi-structured interview to gather data. Data were analyzed by using thematic coding techniques. The present study found that personal characteristics such as commitment, living hope, motivation, positive self-esteem, self-confidence, and communication have shaped resiliency for successful university students with visual disabilities. The finding showed that the school environment is the place in which blind students had developed/experienced social, psychological, and economical competency and hope for their academic and entire life success. Furthermore, the finding showed that blind students had experienced individual, family, school, and community-related risks in the success track. Therefore, governmental and non-governmental organizations should provide training for students with visual impairments that focus on the individual traits that shape resilience for academic success, such as commitment, living hope, motivation, positive self-esteem, self-confidence, and communication and also community-oriented training should be to break the social stigma and discriminations for the individuals with the visual impairment.

Keywords: blind students, risk and protective factors, lived experience, success

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Authors: K. I. M. Guerra, L. A. P. Silva, J. C. Leal

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This study aims to understand with more amplitude and clarity the behavior of a porous medium where a pressure wave travels, translated into relative displacements inside the material, using mathematical tools derived from topology and symplectic geometry. The paper starts with a given partial differential equation based on the continuity and conservation theorems to describe the traveling wave through the porous body. A solution for this equation is proposed after all boundary, and initial conditions are fixed, and it’s accepted that the solution lies in a manifold U of purely spatial dimensions and that is embedded in the Real n-dimensional manifold, with spatial and kinetic dimensions. It’s shown that the U manifold of lower dimensions than IRna, where it is embedded, inherits properties of the vector spaces existing inside the topology it lies on. Then, a second manifold (U*), embedded in another space called IRnb of stress dimensions, is proposed and there’s a non-degenerative function that maps it into the U manifold. This relation is proved as a transformation in between two corresponding admissible solutions of the differential equation in distinct dimensions and properties, leading to a more visual and intuitive understanding of the whole dynamic process of a stress wave through a porous medium and also highlighting the dimensional invariance of Terzaghi’s theory for any coordinate system.

Keywords: poremechanics, soil dynamics, symplectic geometry, wave propagation

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Authors: Shaan Khosla, Jon Krohn

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In a recruiting context, machine learning models are valuable for recommendations: to predict the best candidates for a vacancy, to match the best vacancies for a candidate, and compile a set of similar candidates for any given candidate. While useful to create these models, validating their accuracy in a recommendation context is difficult due to a sparsity of data. In this report, we use network graph data to generate useful representations for candidates and vacancies. We use candidates and vacancies as network nodes and designate a bi-directional link between them based on the candidate interviewing for the vacancy. After using node2vec, the embeddings are used to construct a validation dataset with a ranked order, which will help validate new recommender systems.

Keywords: AI, machine learning, NLP, recruiting

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Authors: Alireza Jalilifar, Nadia Mayahi

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An oral defense is the examination of a doctoral program in which the candidates display their academic capacity through sharing and disseminating the findings of their study and defending their position. In this challenging criticism-generating context, the examiners evaluate the PhD dissertation critically so as to confirm its scholarly merit or lack of it. To identify the examiners’ expectations of the viva, this study used a conversation analytic approach for analyzing the data. The research is inductive in that it seeks to develop theory that is grounded in the data. The data comprised transcripts of the question and answer section of two applied linguistics doctoral defense sessions from two accredited Iranian state universities in 2019, both of which are among the top Iranian universities on the list of Times Higher Education World University Rankings. In spite of the similar shortcomings and deficiencies, for instance, in terms of innovation, development, sampling, and treatment, raised by the examiners, one of these defenses passed with distinction while the other was referred for re-submission. It seems that the outcome of a viva, in an EFL context, not only depends on adherence to the rules and regulations of doctoral research but is also influenced to a certain extent by the strictness of the examiners and the candidates’ language proficiency and effective negotiation and communication skills in this confrontational communicative event. The findings of this study provide evidence for the issues determining the success or failure of PhD candidates in displaying their claims of scholarship during their defense sessions. This study has implications for both applied linguistics doctoral students and academics in EFL contexts who try to prove and authenticate the doctorateness of a dissertation.

Keywords: academic discourse, conversation analysis, doctoral defense, doctorateness, EFL

Procedia PDF Downloads 156

Authors: Muhammad Shahzad Hussain

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Two major problems are facing generally by conventional poultry farming that is disease outbreaks and poor performance, which results due to improper management. To enhance the growth performance and efficiency of feed and reduce disease outbreaks, antibiotic growth promoters (AGPs) which are antibiotics at sub-therapeutic levels, are extensively used in the poultry industry. European Union has banned the use of antibiotics due to their presence in poultry products, development of antibiotic-resistant pathogens, and disturbance of normal gut microbial ecology. These residues cause serious health concerns and produce antibiotic resistance in pathogenic microbes in human beings. These issues strengthen the need for the withdrawal of AGPs from poultry feed. Nowadays, global warming is a major issue, and it is more critical in tropical areas like Pakistan, where heat stress is already a major problem. Heat stress leads to poor production performance, high mortality, immuno-suppression, and concomitant diseases outbreak. The poultry feed industry in Pakistan, like other countries of the world, has been facing shortages and high prices of local as well as imported feed ingredients. Prebiotics are potential replacer for AGP as prebiotics has properties to enhance the production potential and reduce the growth of harmful bacteria as well as stimulate the growth/activity of beneficial bacteria. The most commonly used prebiotics in poultry includes mannan oligosaccharide (MOS). MOS is an essential component of the yeast cell wall (YCW) (Saccharomyces cerevisiae); therefore, the YCW wall possesses prebiotic properties. The use of distillery yeast wall (YCW) has the potential to replace conventional AGPs and to reduce mortality due to heat stress as well as to bind toxins in the feed. The dietary addition of YCW has not only positive effects on production performance in poultry during normal conditions but during stressful conditions. A total of 168-day-old broilers were divided into 6 groups, each of which has 28 birds with 4 replicates (n=7).Yeast cell wall (YCW) supplementation @ 0%, 1%, 1.5%, 2%, 2.5%, 3% from day 0 to 35. Heat stress was exposed from day 21 to 35 at 30±1.1ᵒC with relative humidity 65±5%. Zootechnical parameters like body weight, FCR, Organ development, and histomorphometric parameters were studied. A significant weight gain was observed at group C supplemented @ 1.5% YCW during the fifth week. Significant organ weight gain of Gizzard, spleen, small intestine, and cecum was observed at group C supplemented @ 1.5% YCW. According to morphometric indices Duodenum, Jejunum, and Ileum has significant villus height, while Jejunum and Ileum have also significant villus surface area in the group supplemented with 1.5% YCW. IEL count was only decreased in 1.5% YCW-fed group in jejunum and ileum, not in duodenum, that was less in 2% YCW-supplemented group. Dietary yeast cell wall of saccharomyces cerevisiae partially reduced the effects of high ambient temperature in terms of better growth and modified gut histology and components of mucosal immune response to better withstand heat stress in broilers.

Keywords: antibiotics, AGPs, broilers, MOS, prebiotics, YCW

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Authors: Hirokatsu Kawashima

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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 319

Authors: Honey Bryant, Elvina Chu

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Stroke is the leading cause of disability in adults in Canada and directly related to depression, anxiety, and sleep disorders; with an estimated annual cost of $50 billion in health care. Strokes not only impact the individual but society as a whole. Current stroke rehabilitation does not include Music Therapy, although it has success in clinical research in the use of stroke rehabilitation. This study examines the use of neurologic music therapy (NMT) in conjunction with stroke rehabilitation to improve sleep quality, reduce stress levels, and promote neurogenesis. Existing research on NMT in stroke is limited, which means any conclusive information gathered during this study will be significant. My novel hypotheses are a.) stroke patients will become less depressed and less anxious with improved sleep following NMT. b.) NMT will reduce stress levels and promote neurogenesis in stroke patients admitted for rehabilitation. c.) Beneficial effects of NMT will be sustained at least short-term following treatment. Participants were recruited from the in-patient stroke rehabilitation program at Providence Care Hospital in Kingston, Ontario, Canada. All participants-maintained stroke rehabilitation treatment as normal. The study was spilt into two groups, the first being Passive Music Listening (PML) and the second Neurologic Music Therapy (NMT). Each group underwent 10 sessions of intensive music therapy lasting 45 minutes for 10 consecutive days, excluding weekends. Psychiatric Assessments, Epworth Sleepiness Scale (ESS), Hospital Anxiety & Depression Rating Scale (HADS), and Music Engagement Questionnaire (MusEQ), were completed, followed by a general feedback interview. Physiological markers of stress were measured through blood pressure measurements and heart rate variability. Serum collections reviewed neurogenesis via Brain-derived neurotrophic factor (BDNF) and stress markers of cortisol levels. As this study is still on-going, a formal analysis of data has not been fully completed, although trends are following our hypotheses. A decrease in sleepiness and anxiety is seen upon the first cohort of PML. Feedback interviews have indicated most participants subjectively felt more relaxed and thought PML was useful in their recovery. If the hypothesis is supported, larger external funding which will allow for greater investigation of the use of NMT in stroke rehabilitation. As we know, NMT is not covered under Ontario Health Insurance Plan (OHIP), so there is limited scientific data surrounding its uses as a clinical tool. This research will provide detailed findings of the treatment of neuropsychiatric aspects of stroke. Concurrently, a passive music listening study is being designed to further review the use of PML in rehabilitation as well.

Keywords: music therapy, psychotherapy, neurologic music therapy, passive music listening, neuropsychiatry, counselling, behavioural, stroke, stroke rehabilitation, rehabilitation, neuroscience

Procedia PDF Downloads 113