Search results for: learning attitude

Authors: Mahdi Bazarganigilani

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Aortic enlargement, also known as an aortic aneurysm, can occur when the walls of the aorta become weak. This disease can become deadly if overlooked and undiagnosed. In this paper, a computer-aided diagnosis (CAD) system was introduced to accurately diagnose aortic enlargement from chest x-ray images. An enhanced convolutional neural network (CNN) was employed and then trained by transfer learning by using three different main areas from the original images. The areas included the left lung, heart, and right lung. The accuracy of the system was then evaluated on 1001 samples by using 4-fold cross-validation. A promising accuracy of 90% was achieved in terms of the F-measure indicator. The results showed using different areas from the original image in the training phase of CNN could increase the accuracy of predictions. This encouraged the author to evaluate this method on a larger dataset and even on different CAD systems for further enhancement of this methodology.

Keywords: computer-aided diagnosis systems, aortic enlargement, chest X-ray, image processing, convolutional neural networks

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Authors: Subodh Chandra Shakya, Badal Shrestha, Suni Thapa, Ashutosh Chauhan, Saugat Adhikari

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To tackle our problem of clothes identification, we used different architectures of Convolutional Neural Networks. Among different architectures, the outcome from Inception ResNet V2 and MobileNet V2 seemed promising. On comparison of the metrices, we observed that the Inception ResNet V2 slightly outperforms MobileNet V2 for this purpose. So this paper of ours proposes the cloth identifier using Inception ResNet V2 and also contains the comparison between the outcome of ResNet V2 and MobileNet V2. The document here contains the results and findings of the research that we performed on the DeepFashion Dataset. To improve the dataset, we used different image preprocessing techniques like image shearing, image rotation, and denoising. The whole experiment was conducted with the intention of testing the efficiency of convolutional neural networks on cloth identification so that we could develop a reliable system that is good enough in identifying the clothes worn by the users. The whole system can be integrated with some kind of recommendation system.

Keywords: inception ResNet, convolutional neural net, deep learning, confusion matrix, data augmentation, data preprocessing

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Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

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Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

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Authors: Behdoukht Mall Amiri, Zohreh Gheydar

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The thrust of the current study was to investigate the relationship among EFL learners' creativity (CR), emotional intelligence (EI), and self-efficacy (SE). To this end, a group of 120 male and female learners, between the ages of 19 and 35 studying BA in English Translation and MA in Teaching English at Islamic Azad University, Central Tehran were selected using convenient sampling and were given three questionnaires: Bar-On’s EQ-I questionnaire by Bar-On (1997), the General Self-Efficacy Scale questionnaire (SGSES) by Sherer et al. (1982), and a questionnaire of creativity (CR) by O'Neil, Abedi, and Spielberger (1992). Analysis of the results through Pearson Moment Correlation Coefficient showed that there was not a significant relationship between students’ CR and EI, and EI and SE. In addition, CR and SE were correlated significantly but negatively. Multiple regressions revealed that CR could significantly predict SE. Regarding the findings of the study, the obtained results may help EFL teachers, teacher trainers, materials developers, and educational policy makers to possess a broader perspective and heightened degree knowledge toward the TEFL practice and to take practical steps toward the attainments of the desired objectives of the profession.

Keywords: creativity, emotional intelligence, self-efficacy, learning

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Authors: Arezou Javadi

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The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

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Authors: Arezou Javadi

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The use of algorithmic models dependent on software calculations and simulation of new government management assays with the help of specialized software had increased the productivity and efficiency of the government management system recently. This has caused the management approach to change from the old bitch & fix model, which has low efficiency and less usefulness, to the capable management model with higher efficiency called the partnership with resident model. By using Govpilot TM software, the relationship between people in a system and the government was examined. The method of two tailed interaction was the outsourcing of a goal in a system, which is formed in the order of goals, qualified executive people, optimal executive model, and finally, summarizing additional activities at the different statistical levels. The results showed that the participation of people in a financial implementation system with a statistical potential of P≥5% caused a significant increase in investment and initial capital in the government system with maximum implement project in a smart government.

Keywords: machine learning, financial income, statistical potential, govpilot

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Authors: Thao Thi Vu, Libby Lee-Hammond, Andrew McConney

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In Vietnam, the Vietnamese language is normally used as the language of instruction. The dominance of this language places children who have a different first language such as Indigenous children at a disadvantage when commencing school. This study explores preschool teachers’ beliefs about second language acquisition in Lai Chau provinces where is typical of highland provinces of Vietnam and the proportion of Indigenous minority groups in high. Data were collected from surveys with both closed-end questions and opened-end questions. The participants in this study were more than 200 public preschool teachers who come from eight different districts in Lai Chau. An analysis of quantitative data survey is presented to indicate several practical implications, such as the connection between teachers’ knowledge background that gained from their pre-service and in-service teacher education programs regarding second language teaching for Indigenous children and their practice. It also explains some factors that influence teachers’ beliefs and perspective about Indigenous children and pedagogies in their classes.

Keywords: indigenous children, learning Vietnamese, preschool, teachers’ beliefs

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Authors: Sabri Serkan Güllüoğlu

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Analysis can be defined as the process of gathering, recording and researching data related to products and services, in order to learn something. But for marketers, analyses are not only used for learning but also an essential and critical part of the business, because this allows companies to offer products or services which are focused and well targeted. Market analysis also identify market trends, demographics, customer’s buying habits and important information on the competition. Data mining is used instead of traditional research, because it extracts predictive information about customer and sales from large databases. In contrast to traditional research, data mining relies on information that is already available. Simply the goal is to improve the efficiency of supermarkets. In this study, the purpose is to find dependency on products. For instance, which items are bought together, using association rules in data mining. Moreover, this information will be used for improving the profitability of customers such as increasing shopping time and sales of fewer sold items.

Keywords: data mining, association rule mining, market basket analysis, purchasing

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Authors: George Zhou, Yunchan Chen, Candace Chien

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Kidney replacement therapy is the current standard of care for end-stage renal diseases. In-center or home hemodialysis remains an integral component of the therapeutic regimen. Arteriovenous fistulas (AVF) make up the vascular circuit through which blood is filtered and returned. Naturally, AVF patency determines whether adequate clearance and filtration can be achieved and directly influences clinical outcomes. Our aim was to build a deep learning model for automated AVF stenosis screening based on the sound of blood flow through the AVF. A total of 311 patients with AVF were enrolled in this study. Blood flow sounds were collected using a digital stethoscope. For each patient, blood flow sounds were collected at 6 different locations along the patient’s AVF. The 6 locations are artery, anastomosis, distal vein, middle vein, proximal vein, and venous arch. A total of 1866 sounds were collected. The blood flow sounds are labeled as “patent” (normal) or “stenotic” (abnormal). The labels are validated from concurrent ultrasound. Our dataset included 1527 “patent” and 339 “stenotic” sounds. We show that blood flow sounds vary significantly along the AVF. For example, the blood flow sound is loudest at the anastomosis site and softest at the cephalic arch. Contextualizing the sound with location metadata significantly improves classification performance. How to encode and incorporate categorical metadata is an active area of research1. Herein, we study ordinal (i.e., integer) encoding schemes. The numerical representation is concatenated to the flattened feature vector. We train a vision transformer (ViT) on spectrogram image representations of the sound and demonstrate that using scalar multiples of our integer encodings improves classification performance. Models are evaluated using a 10-fold cross-validation procedure. The baseline performance of our ViT without any location metadata achieves an AuROC and AuPRC of 0.68 ± 0.05 and 0.28 ± 0.09, respectively. Using the following encodings of Artery:0; Arch: 1; Proximal: 2; Middle: 3; Distal 4: Anastomosis: 5, the ViT achieves an AuROC and AuPRC of 0.69 ± 0.06 and 0.30 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 10; Proximal: 20; Middle: 30; Distal 40: Anastomosis: 50, the ViT achieves an AuROC and AuPRC of 0.74 ± 0.06 and 0.38 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 100; Proximal: 200; Middle: 300; Distal 400: Anastomosis: 500, the ViT achieves an AuROC and AuPRC of 0.78 ± 0.06 and 0.43 ± 0.11. respectively. Interestingly, we see that using increasing scalar multiples of our integer encoding scheme (i.e., encoding “venous arch” as 1,10,100) results in progressively improved performance. In theory, the integer values do not matter since we are optimizing the same loss function; the model can learn to increase or decrease the weights associated with location encodings and converge on the same solution. However, in the setting of limited data and computation resources, increasing the importance at initialization either leads to faster convergence or helps the model escape a local minimum.

Keywords: arteriovenous fistula, blood flow sounds, metadata encoding, deep learning

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Authors: Keivan Seyyedi, Leila Esmaeilpour, Seyed Jamal Sadeghi

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Investigating the effectiveness of explicit focus on form on the written performance of the EFL learners was the aim of this study. To provide empirical support for this study, sixty male English learners were selected and randomly assigned into two groups of explicit focus on form and meaning focused. Narrative writing was employed for data collection. To measure writing performance, participants were required to narrate a story. They were given 20 minutes to finish the task and were asked to write at least 150 words. The participants’ output was coded then analyzed utilizing Independent t-test for grammatical accuracy and fluency of learners’ performance. Results indicated that learners in explicit focus on form group appear to benefit from error correction and rule explanation as two pedagogical techniques of explicit focus on form with respect to accuracy, but regarding fluency they did not yield any significant differences compared to the participants of meaning-focused group.

Keywords: explicit focus on form, rule explanation, accuracy, fluency

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Authors: Ashish Kumar, Kaptan Singh, Amit Saxena

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Today, it is believed that crimes have the greatest impact on a person's ability to progress financially and personally. Identifying places where individuals shouldn't go is crucial for preventing crimes and is one of the key considerations. As society and technologies have advanced significantly, so have crimes and the harm they wreak. When there is a concentration of people in one place and changes happen quickly, it is even harder to prevent. Because of this, many crime prevention strategies have been embraced as a component of the development of smart cities in numerous cities. However, crimes can occur anywhere; all that is required is to identify the pattern of their occurrences, which will help to lower the crime rate. In this paper, an analysis related to crime has been done; information related to crimes is collected from all over India that can be accessed from anywhere. The purpose of this paper is to investigate the relationship between several factors and India's crime rate. The review has covered information related to every state of India and their associated regions of the period going in between 2001- 2014. However various classes of violations have a marginally unique scope over the years.

Keywords: K-nearest neighbor, random forest, decision tree, pre-processing

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Authors: Mohamed Chabi, Mahmoud I. Syam, Sarah Aw

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In Summer 2012, the Foundation Program Unit of Qatar University has started implementing new ways of teaching Math by introducing MML (MyMathLab) as an innovative interactive tool to support standard teaching. In this paper, we focused on the effect of proper use of the Study Plan component of MML on student’s performance. Authors investigated the results of students of pre-calculus course during Fall 2013 in Foundation Program at Qatar University. The results showed that there is a strong correlation between study plan results and final exam results, also a strong relation between homework results and final exam results. In addition, the attendance average affected on the student’s results in general. Multiple regression is determined between passing rate dependent variable and study plan, homework as independent variable.

Keywords: MyMathLab, study plan, assessment, homework, attendance, correlation, regression

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Authors: Fuad M. Alkoot

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We aim at highlighting the benefits of classifier systems especially in supporting educational management decisions. The paper aims at using classifiers in an educational application where an outcome is predicted based on given input parameters that represent various conditions at the institute. We present a classifier system that is designed using a limited training set with data for only one semester. The achieved system is able to reach at previously known outcomes accurately. It is also tested on new input parameters representing variations of input conditions to see its prediction on the possible outcome value. Given the supervised expectation of the outcome for the new input we find the system is able to predict the correct outcome. Experiments were conducted on one semester data from two departments only, Switching and Mathematics. Future work on other departments with larger training sets and wider input variations will show additional benefits of classifier systems in supporting the management decisions at an educational institute.

Keywords: machine learning, pattern recognition, classifier design, educational management, outcome estimation

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Authors: Serge Provost, Yishan Zang

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Copulas are currently utilized in finance, reliability theory, machine learning, signal processing, geodesy, hydrology and biostatistics, among several other fields of scientific investigation. It follows from Sklar's theorem that the joint distribution function of a multidimensional random vector can be expressed in terms of its associated copula and marginals. Since marginal distributions can easily be determined by making use of a variety of techniques, we address the problem of securing the distribution of the copula. This will be done by using several approaches. For example, we will obtain bivariate least-squares approximations of the empirical copulas, modify the kernel density estimation technique and propose a criterion for selecting appropriate bandwidths, differentiate linearized empirical copulas, secure Bernstein polynomial approximations of suitable degrees, and apply a corollary to Sklar's result. Illustrative examples involving actual observations will be presented. The proposed methodologies will as well be applied to a sample generated from a known copula distribution in order to validate their effectiveness.

Keywords: copulas, Bernstein polynomial approximation, least-squares polynomial approximation, kernel density estimation, density approximation

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Authors: Digdem M. Siyez, Bariscan Ozturk, Erol Esen, Ender Siyez, Yelda Kagnici, Bahar Baran

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Infertility is a reproductive disease identified with the absence of pregnancy after regular unprotected sexual intercourse that has been lasting for 12 months or more. Some of the factors that cause infertility, which has been considered as a social and societal issue since the first days of the humankind, are preventable. These are veneral diseases, age, the frequency of the intercourse and its timing, drug use, bodyweight, environmental and professional conditions. Having actual information about the reproductive health is essential to take protective and preventive measures, and it is accepted as the most effective way to reduce the rate of infertility. However, during the literature review, it has been observed that there are so few studies that focus on the prevention of the infertility. The aim of this study is to develop a psycho-education program to reduce infertility among university students and also to evaluate the program’s effectiveness. It is believed that this program will increase the information level about infertility among the university students, help them to adopt healthy attitudes, develop life skills, create awareness about the risk factors and also contribute to the literature. Throughout the study, first, the contents of sexual/reproductive health programs developed for university students were examined by the researches. Besides, “Views about Reproductive Health Psycho-education Program Survey” was developed and applied to 10221 university students from 21 universities. In accordance with the literature and the university students’ views about reproductive health psycho-education program consisting of 9 sessions each of which lasts for 90 minutes was developed. The pilot program was carried out with 16 volunteer undergraduate students attending to a state university. During the evaluation of the pilot study, at the end of each session “Session Evaluation Form” and at the end of the entire program “Program Evaluation Form” were administered to the participants. Besides, one week after the end of the program, a focus group with half of the group, and individual interviews with the rest were conducted. Based on the evaluations, it was determined that the session duration is enough, the teaching methods meet the expectation, the techniques applied are appropriate and clear, and the materials are adequate. Also, an extra session was added to psycho-education program based on the feedbacks of the participants. In order to evaluate program’s effectiveness, Solomon control group design will be used. According to this design, the research has 2 experiment groups and 2 control groups. The participants who voluntarily participated in the research after the announcement of the psycho-education program were divided into experiment and control groups. In the experiment 1 and control 1 groups, “Personal Information Test”, “Infertility Information Test” and “Infertility Attitude Scale”, “Self Identification Inventory” and “Melbourne Decision Scale” were administered as a preliminary test. Currently, at the present stage, psycho-education still continues. After this 10-week program, the same tests will be administered again as the post-tests. The decision upon which statistical method will be applied in the analysis will be made afterwards according to whether the data meets the presuppositions or not.

Keywords: infertility, prevention, psycho-education, reproductive health

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Authors: Deborah Amas

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Global accreditation standards require Higher Education Institutions to ensure social work students develop self-awareness by reflecting on their personal values and critically evaluating how these influence their thinking for professional practice. The knowledge base indicates there are benefits and vulnerabilities for students when they self-reflect and more needs to be understood about the learning environments that nurture self-awareness. The connection between teaching methods and self-awareness is of interest in this paper which reports findings from an on-line survey with students on BA and MA qualifying social work programs in an English university (n=120). Students were asked about the importance of self-awareness and their experiences of teaching methods for self-reflection. Generally, students thought that self-awareness is of high importance in their education. Students also shared stories that illuminated deeper feelings about the potential risks associated with self-disclosure. The findings indicate that students appreciate safe opportunities for self-reflection, but can be wary of associated assessments or feeling judged. The research supports arguments to qualitatively improve facilitation of self-awareness through the curriculum.

Keywords: reflection, self-awareness, self-reflection, social work education

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Authors: Yi-De Liu

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The aim of this paper is to discuss how the construct of networking and social capital can be used to understand the effect events can have on the cultural sector. Based on case study, this research sought the views of those working in the cultural sector on Liverpool’s year as the European Capital of Culture (ECOC). Methodologically, this study involves literature review to prompt theoretical sensitivity, the collection of primary data via online survey (n= 42) and follow-up telephone interviews (n= 8) to explore the emerging findings in more detail. The findings point to a number of ways in which the ECOC constitutes a boost for networking and its effects on city’s cultural sector, including organisational learning, aspiration and leadership. The contributions of this study are two-fold: (1) Evaluating the long-term effects on network formation in the cultural sector following major event; (2) conceptualising the impact assessment of organisational social capital for future ECOC or similar events.

Keywords: network, social capital, cultural impact, european capital of culture

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Authors: Harriet Bothwell, Lowri Evans, Kevin Jones

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Background: The University of Bristol provides all medical students the opportunity to undertake student selected components (SSCs) at multiple stages of the undergraduate programme. SSCs enable students to explore areas of interest that are not necessarily covered by the curriculum. Students are required to produce a written report and most use SSCs as an opportunity to undertake an audit or small research project. In 2013 Swindon Academy, based at the Great Western Hospital, offered eight students the opportunity of a global health SSC which included a two week trip to rural hospital in Uganda. This SSC has since expanded and in 2017 a total of 20 students had the opportunity to undertake small research projects at two hospitals in rural Uganda. 'Tomorrows Doctors' highlights the importance of understanding healthcare from a 'global perspective' and student feedback from previous SSCs suggests that self-assessed knowledge of global health increases as a result of this SSC. Through the most recent version of this SSC students had the opportunity to undertake projects in a wide range of specialties including paediatrics, palliative care, surgery and medical education. Methods: An anonymous online questionnaire was made available to students following the SSC. There was a response rate of 80% representing 16 out of the 20 students. This questionnaire surveyed students’ satisfaction and experience of the SSC including the level of academic, project and spiritual support provided as well as perceived challenges in completing the project and barriers to healthcare delivery in the low resource setting. This survey had multiple open questions allowing the collection of qualitative data. Further qualitative data was collected from the students’ project report. The suggested format included a reflection and all students completed these. All qualitative data underwent thematic analysis. Results: All respondents rated the overall experience of the SSC as 'good' or 'excellent'. Preliminary data suggest that students’ confidence in their knowledge of global health, diagnosis of tropical diseases and management of tropical diseases improved after completing this SSC. Thematic analysis of students' reflection is ongoing but suggests that students gain far more than improved knowledge of tropical diseases. Students reflect positively on having the opportunity to research in a low resource setting and feel that by completing these projects they will be 'useful' to the hospital. Several students reflect the stark contrast to healthcare delivery in the UK and recognise the 'privilege' of having a healthcare system that is free at the point of access. Some students noted the different approaches that clinicians in Uganda had to train in 'taking ownership' of their own learning. Conclusions: Students completing this SSC report increased knowledge of global health and tropical medicine. However, their reflections reveal much broader learning outcomes and demonstrate considerable insight in multiple topics including conducting research in the low resource setting, training and healthcare inequality.

Keywords: global health, medical education, student feedback, undergraduate

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Authors: Elaine Crable, Amit Sen

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Short-term study abroad programs have become a mainstay of MBA programs. The benefits of international business experiences, along with its exposure to global cultures, are well documented. However, developing a rewarding study, abroad program at the graduate level can be challenging for Faculty, especially when devising such a program for a group of part-time MBA students who come with a wide range of experiences and demographic characteristics. Each student has individual expectations for the study abroad experience. This study provides suggestions and considerations for Faculty that are planning to design a short-term study abroad program, especially for part-time MBA students. Insights are based on a recent experience leading a group of twenty-one students on a ten-day program to Morocco. The trip was designed and facilitated by two faculty members and a local Moroccan facilitator. This experience led to a number of insights and recommendations. First, the choice of location is critical. The choice of Morocco was very deliberate, owing to its multi-faceted cultural landscape and international business interest. It is an Islamic State with close ties to Europe both culturally and geographically and Morocco is a multi-lingual country with some combination of three languages spoken by most – English, Arabic, and French. Second, collaboration with a local ‘academic’ partner allowed the level of instruction to be both rigorous and significantly more engaging. Third, allowing students to participate in the planning of the trip enabled the trip participants to collaborate, negotiate, and share their own experiences and strengths. The pre-trip engagement was structured by creating four sub-groups, each responsible for an assigned city. Each student sub-group had to provide a historical background of the assigned city, plan the itinerary including sites to visit, cuisine to experience, industries to explore, markets to visit, plus provide a budget for that city’s expenses. The pre-planning segment of the course was critical for the success of the program as students were able to contribute to the design of the program through collaboration and negotiation with their peers. Fourth, each student sub-group was assigned industry to study within Morocco. The student sub-group prepared a presentation and a group paper with their analysis of the chosen industries. The pre-planning activities created strong bonds among the trip participants, which was evident when faced with on-ground challenges, especially when it was necessary to quickly evacuate due to a surprise USA COVID evacuation notice. The entire group supported each other when quickly making their way back to the United States. Unfortunately, the trip was cut short by two days due to this emergency exit, but the feedback regarding the program was very positive all around. While the program design put pressure on the Faculty leads regarding planning and coordination upfront, the outcome in terms of student engagement, student learning, collaboration and negotiation were all favorable and worth the effort. Finally, an added value, the cost of the program for the student was significantly lower compared to running a program with a professional provider.

Keywords: business education, experiential learning, international education, study abroad

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Authors: Roberta Martino, Viviana Ventre

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Empirical evidence has, over time, confirmed that the behavior of individuals is inconsistent with the descriptions provided by the Discounted Utility Model, an essential reference for calculating the utility of intertemporal prospects. The model assumes that individuals calculate the utility of intertemporal prospectuses by adding up the values of all outcomes obtained by multiplying the cardinal utility of the outcome by the discount function estimated at the time the outcome is received. The trend of the discount function is crucial for the preferences of the decision maker because it represents the perception of the future, and its trend causes temporally consistent or temporally inconsistent preferences. In particular, because different formulations of the discount function lead to various conclusions in predicting choice, the descriptive ability of models with a hyperbolic trend is greater than linear or exponential models. Suboptimal choices from any time point of view are the consequence of this mechanism, the psychological factors of which are encapsulated in the discount rate trend. In addition, analyzing the decision-making process from a psychological perspective, there is an equivalence between the selection of dominated prospects and a degree of impatience that decreases over time. The first part of the paper describes and investigates the anomalies of the discounted utility model by relating the cognitive distortions of the decision-maker to the emotional factors that are generated during the evaluation and selection of alternatives. Specifically, by studying the degree to which impatience decreases, it’s possible to quantify how the psychological and emotional mechanisms of the decision-maker result in a lack of decision persistence. In addition, this description presents inconsistency as the consequence of an inconsistent attitude towards time-delayed choices. The second part of the paper presents an experimental phase in which we show the relationship between inconsistency and impatience in different contexts. Analysis of the degree to which impatience decreases confirms the influence of the decision maker's emotional impulses for each anomaly in the utility model discussed in the first part of the paper. This work provides an application in the field of personalized behavioral finance. Indeed, the numerous behavioral diversities, evident even in the degrees of decrease in impatience in the experimental phase, support the idea that optimal strategies may not satisfy individuals in the same way. With the aim of homogenizing the categories of investors and to provide a personalized approach to advice, the results proven in the experimental phase are used in a complementary way with the information in the field of behavioral finance to implement the Analytical Hierarchy Process model in intertemporal choices, useful for strategic personalization. In the construction of the Analytic Hierarchy Process, the degree of decrease in impatience is understood as reflecting irrationality in decision-making and is therefore used for the construction of weights between anomalies and behavioral traits.

Keywords: analytic hierarchy process, behavioral finance, financial anomalies, impatience, time inconsistency

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Authors: Nasir Mustafa

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One of the prerequisites required for an efficient diagnosis in a medical practice is to have a strong command of both functional and clinical anatomy. In this study, we introduce a new collaborative approach to the effective teaching of the knee and hip joints. In the present teaching model, anatomists, orthopedists and physical therapists present the anatomy of the hip and knee joints in small groups. Courses for the hip and knee joints were scheduled during the early stages of the medical curriculum. Students of nursing and physical therapy were grouped together to sensitize to the importance of a collaborative effort. The study results clearly demonstrate that nursing students and physical therapy students appreciated this teaching approach. The collaborative approach further proved to be a suitable method to teach both functional and clinical anatomy of the hip and knee joints. Aside from this training, a collaborative approach between medical students and physical therapy students was also successful for a healthcare organization.

Keywords: hip and knee joint anatomy, collaborative, Anatomy teaching, Nursing students, Physiotherapy students

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Authors: Chidiebere Samuel Ijeoma

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The impact and importance of technology in all domains of existence cannot be overemphasized. It is like a double-edged sword which can be both constructive and destructive. The paper, therefore, tends to evaluate the impact of technology so far in the teaching and learning of French language in Nigeria. According to the study, the traditional methods of teaching French as a Foreign Language and recognized as our cultural methods of knowledge transfer are being fast replaced by digitalization in teaching. This, the research tends to portray and suggest the best way forward. In the Nigerian Primary Education System, the use of some local and cultural Instructional materials (teaching aids) is now almost history which the paper frowns at. Consequently, the study has these questions to ask?; Where are the chalks and blackboards? Where are the ‘Handworks’ (local brooms) submitted by school children as part of their Continuous Assessment? Finally, the research is in no way against the application of technology in the Nigerian French Language Teaching System but tries to draw a curtain between Technological methods of teaching French as a Foreign Language and the Original Nigerian System of teaching the language before the arrival of technology.

Keywords: French language teaching, future, impact, importance of technology

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Authors: Abdullah Abu-Tineh, Hissa Sadiq, Fatma Al-Mutawah, Youmen Chabaan

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The current study examined the experiences of educators in Qatar with the licensure process currently implemented at government schools. Using a survey study design, a total of 1,669 participants expressed their perceptions on the strengths and weaknesses of the licensure system, the professional standards, and the professional portfolio. Findings included participants’ beliefs on the importance of the licensure system in improving their performance, the necessity of using the professional standards as tools for professional growth and development, the importance of refining the professional portfolio for authenticity and reliability, and the inclusion of multiple sources of evidence, such as classroom observations, interviews, student learning outcomes, and surveys. Documenting teachers’ and school leaders’ voices was fundamental in finding ways to successfully drive future developments of the licensure system. The findings may also provide implications for other countries interested in developing or refining their own appraisal systems.

Keywords: licensure system, educator voice, professional standards, professional portfolio

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Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

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This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: landslide, limit analysis, artificial neural network, soil properties

Procedia PDF Downloads 187

Authors: Alexander Suuk Laar, Emmanuel Bekyieriya, Sylvester Isang, Benjamin Baguune

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Introduction: In Ghana, despite the implementation of strategies and initiatives to ensure universal access to reproductive health and family planning (FP) services for the past two decades, interventions have not adequately addressed the access and utilization needs of women of reproductive age, especially in rural Ghana. To improve access and use of reproductive and maternal health services in Ghana, a free maternal care exemption policy under the universal health coverage of the National Health Insurance Scheme was implemented in 2005. Despite the importance of FP, this service was left out of the benefit package of the policy. Low or no use of FP services is often associated with poor health among women. However, to date, there has been limited research on perspectives of women for not making FP services as part of the benefit package of the free maternal health services. This qualitative study explored perceptions of women on the comprehensiveness of the free maternal health benefit package and the effects on utilisation of services in the rural Upper West region of Ghana to improve services. Methods: This exploratory qualitative study used focus group discussions with pregnant and lactating women in three rural districts in the Upper West region of Ghana. Six focus groups were held with both pregnant women and lactating mothers at the time of the interview. Three focus group discussions were organised with the same category of women in each district. We used a purposive sampling procedure to select the participants from the districts. The interviews with the written consent of the participants lasted between 60 minutes and 120 minutes. Interviews were audio-recorded and transcribed verbatim. Data were analysed using Braun and Clarke thematic framework guidelines. Results: This research presents an in-depth account of women's perceptions on the effects associated with the uptake of FP services and its exclusion from the benefit package of the free maternal health policy. Our study found that participants did not support the exclusion of FP services in the benefit package. Participants mentioned factors hampering their access to and use of FP and contraceptive services to include the cost of services, distance and cost of transport to health facilities, lack of knowledge about FP services, socio-cultural norms and negative attitude of healthcare professionals. Participants are of the view that making FP services part of the benefit package could have addressed the cost aspect of services which act as the main barrier to improve the use of services by poor rural women. Conclusion: Women of reproductive age face cost barriers that limit their access to and use of FP and contraception services in the rural Upper West region of Ghana and need health policymakers to revise the free maternal health package to include FP services. It is essential for policymakers to begin considering revising the free maternal health policy benefit package to include FP services to help address the cost barrier for rural poor women to use services.

Keywords: benefit package, free maternal policy, women, Ghana, rural Upper West Region, Universal Health Coverage.

Procedia PDF Downloads 213

Authors: Bernard Nnamdi Emenyeonu

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The study of communication as a fully-fledged discipline in institutions of higher education in the Sultanate of Oman is relatively young. Its evolution is associated with Oman's Renaissance beginning from 1970, which ushered in an era of modernization in which education, industrialization, expansion, and liberalization of the mass media, provision of infrastructure, and promotion of multilateral commercial ventures were considered among the top priorities of national development plans. Communication studies were pioneered by the sole government university, Sultan Qaboos University, in the 1990s, but so far, the program is taught in Arabic only. In recognition of the need to produce professionals suitably equipped to fit into the expanding media establishments in the Sultanate as well as the widening global market, the government decided to establish programs in which communication would be taught in English language. Under the supervision of the Ministry of Higher Education, six Colleges of Applied Sciences were established in Oman in 2007. These colleges offer a 4-year Bachelor degree program in communication studies that comprises six areas of specialization: Advertising, Digital Media, International Communication, Journalism, Media Management and Public Relations. Over the years, a trend has emerged where students tend to flock to particular specializations such as Public Relations and Digital Media, while others, such as Advertising and Journalism, continue to draw the least number of students. In some instances, some specializations have had to be frozen due to the dire lack of interest among new students. It has also been observed that female students are more likely to be more biased in choice of specializations. It was therefore the task of this paper to establish, through a survey and focus group interviews, the factors that influence choice of communication studies as well as particular specializations, among Omani Communication Studies undergraduates. Results of the study show that prior to entering into the communication studies program, the majority of students had no idea of what the field entailed. Whatever information they had about communication studies was sourced from friends and relatives rather than more reliable sources such as career fairs or guidance counselors. For the most part, the choice of communication studies as a major was also influenced by factors such as family, friends and prospects for jobs. Another significant finding is the strong association between gender and choice of specializations within the program, with females flocking to digital media while males tended to prefer public relations. Reasons for specialization preferences dwelt strongly on expectations of a good GPA and the promise of a good salary after graduation. Regardless of gender, most students identified careers in news reporting, public relations and advertising as unsuitable for females. Teaching and program presentation were identified as the most suitable for females. Based on these and other results, the paper not only examined the social and cultural factors that are likely to have influenced the respondent's attitude to communication studies, but also discussed the implication for curriculum development and career development in a developing society such as Oman.

Keywords: career choice, communication specialization, media education, Oman

Procedia PDF Downloads 220

Authors: Yuanjin Liu

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Retirement withdrawal strategies are very important to minimize the probability of ruin in retirement. The ruin probability is modeled as a function of initial withdrawal age, gender, asset allocation, inflation rate, and initial withdrawal rate. The ruin probability is obtained based on the 2019 period life table for the Social Security, IRS Required Minimum Distribution (RMD) Worksheets, US historical bond and equity returns, and inflation rates using simulation. Several popular machine learning algorithms of the generalized additive model, random forest, support vector machine, extreme gradient boosting, and artificial neural network are built. The model validation and selection are based on the test errors using hyperparameter tuning and train-test split. The optimal model is recommended for retirees to monitor the ruin probability. The optimal withdrawal strategy can be obtained based on the optimal predictive model.

Keywords: ruin probability, retirement withdrawal strategies, predictive models, optimal model

Procedia PDF Downloads 61

Authors: M. Testa, L. Peotta, S. Giusiano, B. Lazzolino, U. Manera, A. Canosa, M. Grassano, F. Palumbo, A. Bombaci, S. Cabras, F. Di Pede, L. Solero, E. Matteoni, C. Moglia, A. Calvo, A. Chio

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Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease of adulthood, which primarily affects the central nervous system and is characterized by progressive bilateral degeneration of motor neurons. The degeneration processes in ALS extend far beyond the neurons of the motor system, and affects cognition, behaviour and language. To outline the prevalence of language deficits in an ALS cohort and explore their profile along with demographic and neuropsychological data. A full neuropsychological battery and language assessment was administered to 56 ALS patients. Neuropsychological assessment included tests of executive functioning, verbal fluency, social cognition and memory. Language was assessed using tests for verbal comprehension, production and pragmatics. Patients were cognitively classified following the Revised Consensus Criteria and divided in three groups showing different levels of language deficits: group 1 - no language deficit; group 2 - one language deficit; group 3 - two or more language deficits. Chi-square for independence and non-parametric measures to compare groups were applied. Nearly half of ALS-CN patients (48%) reported one language test under the clinical cut-off, and only 13% of patents classified as ALS-CI showed no language deficits, while the rest 87% of ALS-CI reported two or more language deficits. ALS-BI and ALS-CBI cases all reported two or more language deficits. Deficits in production and in comprehension appeared more frequent in ALS-CI patients (p=0.011, p=0.003 respectively), with a higher percentage of comprehension deficits (83%). Nearly all ALS-CI reported at least one deficit in pragmatic abilities (96%) and all ALS-BI and ALS-CBI patients showed pragmatic deficits. Males showed higher percentage of pragmatic deficits (97%, p=0.007). No significant differences in language deficits have been found between bulbar and spinal onset. Months from onset and level of impairment at testing (ALS-FRS total score) were not significantly different between levels and type of language impairment. Age and education were significantly higher for cases showing no deficits in comprehension and pragmatics and in the group showing no language deficits. Comparing performances at neuropsychological tests among the three levels of language deficits, no significant differences in neuropsychological performances were found between group 1 and 2; compared to group 1, group 3 appeared to decay specifically on executive testing, verbal/visuospatial learning, and social cognition. Compared to group 2, group 3 showed worse performances specifically in tests of working memory and attention. Language deficits have found to be spread in our sample, encompassing verbal comprehension, production and pragmatics. Our study reveals that also cognitive intact patients (ALS-CN) showed at least one language deficit in 48% of cases. Pragmatic domain is the most compromised (84% of the total sample), present in nearly all ALS-CI (96%), likely due to the influence of executive impairment. Lower age and higher education seem to preserve comprehension, pragmatics and presence of language deficits. Finally, executive functions, verbal/visuospatial learning and social cognition differentiate the group with no language deficits from the group with a clinical language impairment (group 3), while attention and working memory differentiate the group with one language deficit from the clinical impaired group.

Keywords: amyotrophic lateral sclerosis, language assessment, neuropsychological assessment, language deficit

Procedia PDF Downloads 139

Authors: Sobhani U. Pilapitiya, Tharanga Peiris

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Software Engineering curriculums generally consist of industry-based practices such as project-based learning (PBL) which mainly focuses on efficient and innovative product development. These approaches can be tailored and used in project-based modules in software engineering curriculums. However, there are very limited attempts in the area especially related to the Sri Lankan context. This paper describes a tailored pedagogical approach and its results of using design sprint which can be used for project-based modules in SE curriculums. A controlled group of second-year software engineering students was selected for the study. The study results indicate that 100% of students agreed that the Design Sprint approach is effective in group-based projects and 83% of students stated that it minimized the re-work compared to traditional project approaches. The tailored process was effective, easy to implement and produced desired results at the end of the session while providing students an enjoyable experience.

Keywords: design sprint, PBL, software engineering, curriculum

Procedia PDF Downloads 185

Authors: Li Kewen, Su Zhaoxin, Wang Xingmou, Zhu Jian Bing

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Conventional reservoir prediction methods ar not sufficient to explore the implicit relation between seismic attributes, and thus data utilization is low. In order to improve the predictive classification accuracy of reservoir lithology, this paper proposes a deep learning lithology prediction method based on ResNet (Residual Neural Network) and SENet (Squeeze-and-Excitation Neural Network). The neural network model is built and trained by using seismic attribute data and lithology data of Shengli oilfield, and the nonlinear mapping relationship between seismic attribute and lithology marker is established. The experimental results show that this method can significantly improve the classification effect of reservoir lithology, and the classification accuracy is close to 70%. This study can effectively predict the lithology of undrilled area and provide support for exploration and development.

Keywords: convolutional neural network, lithology, prediction of reservoir, seismic attributes

Procedia PDF Downloads 162