Search results for: teaching report writing for innovative learning

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

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

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

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Authors: Deawan Rakin Ahamed Remal, Sinthia Chowdhury, Sharun Akter Khushbu, Sheak Rashed Haider Noori

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Native Speech to text synthesis has its own leverage for the purpose of mankind. The extensive nature of art to speaking different accents is common but the purpose of communication between two different accent types of people is quite difficult. This problem will be motivated by the extraction of the wrong perception of language meaning. Thus, many existing automatic speech recognition has been placed to detect text. Overall study of this paper mentions a review of NSTTR (Native Speech Text to Text Recognition) synthesis compared with Text to Text recognition. Review has exposed many text to text recognition systems that are at a very early stage to comply with the system by native speech recognition. Many discussions started about the progression of chatbots, linguistic theory another is rule based approach. In the Recent years Deep learning is an overwhelming chapter for text to text learning to detect language nature. To the best of our knowledge, In the sub continent a huge number of people speak in Bangla language but they have different accents in different regions therefore study has been elaborate contradictory discussion achievement of existing works and findings of future needs in Bangla language acoustic accent.

Keywords: TTR, NSTTR, text to text recognition, deep learning, natural language processing

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Authors: F. Ruiz-Fuster

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Arnold’s redefinition of human motives can sustain a psychology of education which emphasizes the beauty of knowledge and the exercise of intellectual functions. Thus, education instead of focusing on skills and learning by doing would be centered on ‘the widest reaches of the human spirit’. One way to attain it is by developing children’s inherent interest. Arnold takes into account the fact that the desire to know is the inherent interest which leads students to explore and learn. She also emphasizes the need of exercising human functions as thinking, judging and reasoning. According to Arnold, the influence of psychological theories of motivation in education has derived in considering that all learning and school tasks should derive from children’s needs and impulses. The desire to know and the curiosity have not been considered as basic and active as any instinctive drive or basic need, so there has been an attempt to justify and understand how biological drives guide student’s learning. However, understanding motives and motivation not as a drive, an instinct or an impulse guided by our basic needs, but as a want that leads to action can help to understand, from a psychological perspective, how teachers can motivate students to learn, strengthening their desire and interest to reason and discover the whole new world of knowledge.

Keywords: academic motivation, interests, desire to know, educational psychology, intellectual functions

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Authors: Jacqueline Rose T. Alipo-on, Francesca Isabelle F. Escobar, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar Al Dahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases, which are considered one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis of ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heartbeat types. The dataset used in this work is the synthetic MIT-BIH Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: heartbeat classification, convolutional neural network, electrocardiogram signals, generative adversarial networks, long short-term memory, ResNet-50

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Authors: Tayfun Çay, Yasar İnceyol, Abdurrahman Özbeyaz

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Land reallocation is one of the most important steps in land consolidation projects. Many different models were proposed for land reallocation in the literature such as Fuzzy Logic, block priority based land reallocation and Spatial Decision Support Systems. A model including four parts is considered for automatic block reallocation with genetic algorithm method in land consolidation projects. These stages are preparing data tables for a project land, determining conditions and constraints of land reallocation, designing command steps and logical flow chart of reallocation algorithm and finally writing program codes of Genetic Algorithm respectively. In this study, we designed the first three steps of the considered model comprising four steps.

Keywords: land consolidation, landholding, land reallocation, optimization, genetic algorithm

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Authors: Li Wang

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The explosive of technology advances has opened up many avenues of career options for engineering graduates. Hence, how relevant their learning at university is very much dependent on their actual jobs. Bridging the gap between education and industrial practice is important, but it also becomes evident how both engineering education and industrial training can be leveraged at the same time and balance between what students should grasp at university and what they can be continuously trained at the working environment. Through a case study of developing a commercial product, this paper presents the required level of depth of technical knowledge and skills for some typical engineering jobs (for mechanical/materials engineering). It highlights the necessary collaboration for industry, university, and accreditation bodies to work together to nurture the next generation of engineers.

Keywords: leverage, collaboration, career, industry, engineering education

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Authors: Wendi Dunham, Kimberly Floyd

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The constructivist approach to learning is a theoretical orientation that posits that individuals create their own understanding and knowledge of the world through their experiences and interactions. This approach emphasizes that learning is an active process and that individuals are not passive recipients when constructing their understanding of their world. When used concurrently with trauma-informed practices, a constructivist approach can inform the development of a framework for students and teachers that supports their social, emotional, and mental health in addition to enabling academic success. This framework can be applied to teachers and students. When applied to teachers, it can be used to achieve purposeful coping mechanisms through restorative justice and dispositional mindfulness. When applied to students, the framework can implement proactive, student-based practices such as Response to Intervention (RtI) and the 4 Rs to connect resiliency and intervention to academic learning. Using a constructivist, trauma-informed framework can provide students with a greater sense of control and agency over their trauma experiences and impart confidence in achieving school success.

Keywords: trauma, trauma informed practices in education, constructivist theory framework, school responses to trauma, trauma informed supports for teachers, trauma informed strategies for students, restorative justice, mindfulness, response to intervention, the 4 R's, resiliency

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Authors: Jan-Peter Mund, Christian Kind

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In view of the ongoing climate change and global warming, fires along railways in Germany are occurring more frequently, with sometimes massive consequences for railway operations and affected railroad infrastructure. In the absence of systematic studies within the infrastructure network of German Rail, little is known about the causes of such embankment fires. Since a further increase in these hazards is to be expected in the near future, there is a need for a sound knowledge of triggers and drivers for embankment fires as well as methodical knowledge of prediction tools. Two predictable future trends speak for the increasing relevance of the topic: through the intensification of the use of rail for passenger and freight transport (e.g..: doubling of annual passenger numbers by 2030, compared to 2019), there will be more rail traffic and also more maintenance and construction work on the railways. This research project approach uses satellite data to identify historical embankment fires along rail network infrastructure. The team links data from these fires with infrastructure and weather data and trains a machine-learning model with the aim of predicting fire hazards on sections of the track. Companies reflect on the results and use them on a pilot basis in precautionary measures.

Keywords: embankment fires, railway maintenance, machine learning, remote sensing, VIIRS data

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Authors: Georg Ebner

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The National Defence Academy, an element of the Austrian Ministry of Defence, is undergoing a transition process leading the Academy towards a new target structure that is currently being developed. In so doing, in addition to a subject-oriented approach, also an employee-oriented process was introduced. This process was initiated by the Ministry of Defence and should lead the National Defence Academy into a new constellation. During this process, the National Defence Academy worked in very special adapted World Café sessions. The “change manager” dealed with very different issues. They took the data feedback from the sessions and prepared with the feedback and information from the guidance the next session. So they got various information and a very different picture around the academy. It was very helpful to involve most of the employees of the academy during this process and to take their knowledge and wisdom. The process himself started with very different feelings and ended with great consent. A very interesting part of this process was also that the commander and his deputy worked together during all of this sessions and they answered all questions from the employees in time. The adapted World Café phases were necessary to deal with the information of the staff and to implement these absolutely needful data into this process. In cooperation with the responsible Headquarters, the first items resulting from the World Café phases could already be fed back to the employees and be implemented. The staff-oriented process is currently supported via a point of contact, through which the staff can contribute ideas as well, but also by the active information policy on the part of the Headquarters. The described change process makes innovative innovations possible. So far, in the event of change processes staff members have been entrusted only with the concrete implementation plan and tied into the process when the respective workplaces were to be re-staffed. The procedure described here can be seen as food-for-thought for further change processes. The findings of this process are that a staff oriented process can lead an organisation into a new era of thinking and working. This process has shown, that a lot of innovative ideas can also take place in a ministry. This process can be a background for a lot of change management processes in ministries and governmental and non-governmental organisations.

Keywords: both directions approach, change management, knowledge database, transformation process, World Cafe

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Traditional optimization methods like evolutionary algorithms are widely used in production processes to find an optimal or near-optimal solution of control parameters based on the simulated environment space of a process. These algorithms are computationally intensive and therefore do not provide the opportunity for real-time optimization. This paper utilizes the Deep Reinforcement Learning (DRL) framework to find an optimal or near-optimal solution for control parameters. A model based on maximum a posteriori policy optimization (Hybrid-MPO) that can handle both numerical and categorical parameters is used as a benchmark for comparison. A comparative study shows that DRL can find optimal solutions of similar quality as compared to evolutionary algorithms while requiring significantly less time making them preferable for real-time optimization. The results are confirmed in a large-scale validation study on datasets from production and other fields. A trained XGBoost model is used as a surrogate for process simulation. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, evolutionary algorithms, production process optimization, real-time optimization, hybrid-MPO

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Authors: Jiaxin Shi, Kaifeng Hao, Qingfan An, Zeng Peng

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Due to a lack of data sources and data processing techniques, it has always been difficult to quantify public space quality, which includes urban construction quality and how it is perceived by people, especially in large urban areas. This study proposes a quantitative research method based on the consideration of emotional health and physical health of the built environment. It highlights the low quality of public areas in Tianjin, China, where there are many negative elements. Deep learning technology is then used to measure how effectively people perceive urban areas. First, this work suggests a deep learning model that might simulate how people can perceive the quality of urban construction. Second, we perform semantic segmentation on street images to identify visual elements influencing scene perception. Finally, this study correlated the scene perception score with the proportion of visual elements to determine the surrounding environmental elements that influence scene perception. Using a small-scale labeled Tianjin street view data set based on transfer learning, this study trains five negative spatial discriminant models in order to explore the negative space distribution and quality improvement of urban streets. Then it uses all Tianjin street-level imagery to make predictions and calculate the proportion of negative space. Visualizing the spatial distribution of negative space along the Tianjin Inner Ring Road reveals that the negative elements are mainly found close to the five key districts. The map of Tianjin was combined with the experimental data to perform the visual analysis. Based on the emotional assessment, the distribution of negative materials, and the direction of street guidelines, we suggest guidance content and design strategy points of the negative phenomena in Tianjin street space in the two dimensions of perception and substance. This work demonstrates the utilization of deep learning techniques to understand how people appreciate high-quality urban construction, and it complements both theory and practice in urban planning. It illustrates the connection between human perception and the actual physical public space environment, allowing researchers to make urban interventions.

Keywords: human perception, public space quality, deep learning, negative elements, street images

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Authors: Preethi Sudarshanie Dassanayake, R. A. Sudath Weerasiri

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Objective: The objective of this study were to find out highest expectation and perception,highest gap between perception and expectation of service quality, and to find out such gaps between perception and expectation with regard to service quality dimensions were whether statistically significant. Methodology: This study carried out at the Out Patient Department (OPD) of the Veterinary Teaching Hospital (VTH), University of Peradeniya. Modified version of SERVQUAL with 22-pairs of items regarding expectation and perception of service quality in dimensions of tangible, reliability, responsiveness, assurance and empathy were included in Part 1 and the Part 2 of the questionnaire consisted of questions regarding socio-demographic factors. Sample size was 200 and sampling procedure was Systematic Random Sampling. Customers above 18 years of age, able to read, write and understand Sinhala or English language, visits more than twice in last six months and who willing to respond were selected. Findings: The analysis revealed customers expectations of service higher than the perceived for all 22- items of the SERVQUAL. This high expectation suggests that there is sufficient room for further improvement of service quality in all five dimensions. Originality/Value of the Paper: This study gave a new insight for poorly researched area of veterinary health service quality in Sri Lankan context. It provides hospital administrators and policy makers to develop strategies for further improvement of service quality according to customers' view.

Keywords: expectation, perception, service quality, SERVQUAL, veterinary health care

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Authors: Peter R. Reuter

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Health professionals play important roles in helping patients use Complementary and Alternative Medicine (CAM) practices safely and accurately. Consequently, it is important for future health professionals to learn about CAM practices during their time in undergraduate and graduate programs. To satisfy this need for education, teaching CAM in nursing and medical schools and other health professions programs is becoming more prevalent. Our study was the first to look specifically at the knowledge of, and attitude toward CAM of undergraduate health professions students at a university in the U.S. Students were invited to participate in one of two anonymous online surveys depending on whether they were pre-health professions students or graduating health professions seniors. Of the 763 responses analyzed, 71.7% were from pre-health professions students, and 28.3% came from graduating seniors. The overall attitude of participants toward and interest in learning about CAM practices was generally fairly positive with graduating seniors being more positive than pre-health professions students. Yoga, meditation, massage therapy, aromatherapy, and chiropractic care were the practices most respondents had personal experience with. Massage therapy, yoga, chiropractic care, meditation, music therapy, and diet-based therapy received the highest ratings from respondents. Three-quarters of respondents planned on including aspects of holistic medicine in their future career as a health professional. The top five practices named were yoga, meditation, massage therapy, diet-based therapy, and music therapy. The study confirms the need to educate health professions students about CAM practices to give them the background information they need to select or recommend the best practices for their patients' needs.

Keywords: CAM education, health professions, health professions students, pre-health professions students

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Authors: Maho Komura

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The purpose of this study was to determine from a questionnaire survey of teachers the status of implementation of individualized support for the pupils with suspected developmental disabilities in regular elementary school classes in Japan. In inclusive education, the goal is for all pupils to learn in the same place as much as possible by receiving the individualized support they need. However, in the Japanese school culture, strong "homogeneity" sometimes surfaces, and it is pointed out that it is difficult to provide individualized support from the viewpoint of formal equality. Therefore, we decided to conduct this study in order to examine whether there is a difference in the frequency of implementation depending on the content of individualized support and to consider the direction of future individualized support. The subjects of the survey were 196 public elementary school teachers who had been in charge of regular classes within the past five years. In the survey, individualized support was defined as individualized consideration including rational consideration, and did not include support for the entire class or all pupils enrolled in the class (e.g., reducing the amount of homework for pupils who have trouble learning, changing classroom rules, etc.). (e.g., reducing the amount of homework for pupils with learning difficulties, allowing pupils with behavioral concerns to use the library or infirmary when they are unstable). The respondents were asked to choose one answer from four options, ranging from "very much" to "not at all," regarding the degree to which they implemented the nine individual support items that were set up with reference to previous studies. As a result, it became clear that the majority of teachers had pupils with developmental disabilities or pupils who require consideration in terms of learning and behavior, and that the majority of teachers had experience in providing individualized support to these pupils. Investigating the content of the individualized support that had been implemented, it became clear that the frequency with which it was implemented varied depending on the individualized support. Individualized support that allowed pupils to perform the same learning tasks was implemented more frequently, but individualized support that allowed different learning tasks or use of places other than the classroom was implemented less frequently. It was suggested that flexible support methods tailored to each pupil may not have been considered.

Keywords: inclusive education, ndividualized support, regular class, elementary school

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Authors: Ethan James

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Over one billion people worldwide suffer from some level of vision loss or blindness as a result of progressive retinal diseases. Many patients, particularly in developing areas, are incorrectly diagnosed or undiagnosed whatsoever due to unconventional diagnostic tools and screening methods. Artificial intelligence (AI) based on deep learning (DL) convolutional neural networks (CNN) have recently gained a high interest in ophthalmology for its computer-imaging diagnosis, disease prognosis, and risk assessment. Optical coherence tomography (OCT) is a popular imaging technique used to capture high-resolution cross-sections of retinas. In ophthalmology, DL has been applied to fundus photographs, optical coherence tomography, and visual fields, achieving robust classification performance in the detection of various retinal diseases including macular degeneration, diabetic retinopathy, and retinitis pigmentosa. However, there is no complete diagnostic model to analyze these retinal images that provide a diagnostic accuracy above 90%. Thus, the purpose of this project was to develop an AI model that utilizes machine learning techniques to automatically diagnose specific retinal diseases from OCT scans. The algorithm consists of neural network architecture that was trained from a dataset of over 20,000 real-world OCT images to train the robust model to utilize residual neural networks with cyclic pooling. This DL model can ultimately aid ophthalmologists in diagnosing patients with these retinal diseases more quickly and more accurately, therefore facilitating earlier treatment, which results in improved post-treatment outcomes.

Keywords: artificial intelligence, deep learning, imaging, medical devices, ophthalmic devices, ophthalmology, retina

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Authors: Priscilla Akua Agyapong

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Background: In a country of nearly 34 million people, Ghana suffers from rapidly growing pediatric CHD cases and not enough pediatric specialists to attend to the burgeoning needs of these children. Most of the cases are either missed or diagnosed late, resulting in increased mortality. According to the National Cardiothoracic Centre, 1 in every 100,000 births in Ghana has CHD; however, there is limited data on the clinical presentation and its management, one of the many reasons I decided to do this case study coupled with the loss my 2 month old niece to multiple Ventricular Septal Defect 3 years ago due late diagnoses. Method: A retrospective cohort study was performed at the child health clinic of one of Ghana’s public tertiary Institutions using data from their electronic health record (EHR) from February 2021 to April 2022. All suspected or provisionally diagnosed cases were included in the analysis. Results: Records of over 3000 children were reviewed with an approximate male to female ratio of 1:1.53 cases diagnosed during the period of study, most of whom were less than 5 years of age. 25 cases had complete clinical records, with acyanotic septal defects being the most diagnosed. 62.5% of the cases were ventricular septal defects, followed by Patent Ductus Arteriosus (23%) and Atrial Septal Defects (4.5%). Tetralogy of Fallot was the most predominant and complex cyanotic CHD with 10%. Conclusion: The indeterminate coronary anatomy of infants makes it difficult to use only echocardiography and other conventional clinical methods in screening for CHDs. There are rising modernizations and new innovative ways that can be employed in Ghana for early detection, hence preventing the delay of a potential surgical repair. It is, therefore, imperative to create the needed awareness about these “SILENT CRISES” and help save the Ghanaian child’s life.

Keywords: congenital heart defect(CHD), ventricular septal defect(VSD), atrial septal defect(ASD), patent ductus arteriosus(PDA)

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Authors: Iman Al Khalidi

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Recently, English has become the language of globalization and technology. In turn, this has resulted in a seemingly bewildering array of influences and trends in the domain of TESOL curriculum. In light of these changes, higher education has to provide a new and more powerful kind of education. It should prepare students to be more engaged citizens, more capable to solve complex problems at work, and well prepared to lead meaningful life. In response to this, universities, colleges, schools, and departments have to work out in light of the requirements and challenges of the global and technological era. Consequently they have to focus on the adoption of contemporary curriculum which goes in line with the pedagogical shifts from teaching –centered approach to learning centered approach. Ideally, there has been noticeable emphasis on the crucial importance of developing and professionalizing teachers in order to engage them in the process of curriculum development and action research. This is a qualitative study that aims at understanding and exploring the process of designing EFL courses by teachers at the tertiary level from the perspectives of the participants in a professional context in TESOL, Department of English, a private college in Oman. It is a case study that stands on the philosophy of the qualitative approach. It employs multi methods for collecting qualitative data: semi-structured interviews with teachers, focus group discussions with students, and document analysis. The collected data have been analyzed qualitatively by adopting Miles and Huberman's Approach using procedures of reduction, coding, displaying and conclusion drawing and verification.

Keywords: course design, components of course design, case study, data analysis

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Authors: Iman Al Khalidi

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Recently, English has become the language of globalization and technology. In turn, this has resulted in a seemingly bewildering array of influences and trends in the domain of TESOL curriculum. In light of these changes, higher education has to provide a new and more powerful kind of education. It should prepare students to be more engaged citizens, more capable to solve complex problems at work, and well prepared to lead a meaningful life. In response to this, universities, colleges, schools, and departments have to work out in light of the requirements and challenges of the global and technological era. Consequently, they have to focus on the adoption of contemporary curriculum which goes in line with the pedagogical shifts from teaching –centered approach to learning centered approach. Ideally, there has been noticeable emphasis on the crucial importance of developing and professionalizing teachers in order to engage them in the process of curriculum development and action research. This is a qualitative study that aims at understanding and exploring the process of designing EFL courses by teachers at the tertiary level from the perspectives of the participants in a professional context in TESOL, Department of English, a private college in Oman. It is a case study that stands on the philosophy of the qualitative approach. It employs multi-methods for collecting qualitative data: semi-structured interviews with teachers, focus group discussions with students, and document analysis. The collected data have been analyzed qualitatively by adopting Miles and Huberman's Approach using procedures of reduction, coding, displaying, and conclusion drawing and verification.

Keywords: course design, components of course design, case study, data analysis

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Authors: Tong He, Long Chen, Irag Mantegh, Wen-Fang Xie

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This paper proposes an image-based obstacle avoidance and tracking target identification strategy in GPS-degraded or GPS-denied environment for an Unmanned Aerial Vehicle (UAV). The traditional force algorithm for obstacle avoidance could produce local minima area, in which UAV cannot get away obstacle effectively. In order to eliminate it, an artificial potential approach based on harmonic potential is proposed to guide the UAV to avoid the obstacle by using the vision system. And image-based visual servoing scheme (IBVS) has been adopted to implement the proposed obstacle avoidance approach. In IBVS, the pixel accuracy is a key factor to realize the obstacle avoidance. In this paper, the deep reinforcement learning framework has been applied by reducing pixel errors through constant interaction between the environment and the agent. In addition, the combination of OpenTLD and Tensorflow based on neural network is used to identify the type of tracking target. Numerical simulation in Matlab and ROS GAZEBO show the satisfactory result in target identification and obstacle avoidance.

Keywords: image-based visual servoing, obstacle avoidance, tracking target identification, deep reinforcement learning, artificial potential approach, neural network

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Authors: Heru Al Amin

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Sarcoidosis is a granulomatous inflammatory disorder of unclear etiology that can affect multiple different organ systems. Isolated cardiac sarcoidosis is a very rare condition that causes lethal arrhythmia and heart failure. A definite diagnosis of cardiac sarcoidosis remains challenging. The use of multimodality imaging plays a pivotal role in the diagnosis of this entity. Case summary: In this report, we discuss a case of a 50-year-old woman who presented with recurrent palpitation, dizziness, vertigo and presyncope. Electrocardiogram revealed variable heart blocks, including first-degree AV block, second-degree AV block, high-degree AV block, complete AV block, trifascicular block and sometimes supraventricular arrhythmia. Twenty-four hours of Holter monitoring show atrial bigeminy, first-degree AV block and trifascicular block. Transthoracic echocardiography showed Thinning of basal anteroseptal and inferred septum with LV dilatation with reduction of Global Longitudinal Strain. A dual-chamber pacemaker was implanted. CT Coronary angiogram showed no coronary artery disease. Cardiac magnetic resonance revealed basal anteroseptal and inferior septum thinning with focal edema with LGE suggestive of sarcoidosis. Computed tomography of the chest showed no lymphadenopathy or pulmonary infiltration. 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) of the whole body showed. We started steroids and followed up with the patient. Conclusion: This case serves to highlight the challenges in identifying and managing isolated CS in a young patient with recurrent syncope with variable heart block. Early, even late initiation of steroids can improve arrhythmia as well as left ventricular function.

Keywords: cardiac sarcoidosis, conduction abnormality, syncope, cardiac MRI

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Authors: Loulwah Bokhari, Jori Nazer, Hala Sultan

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Nowadays, artificial intelligence (AI) is used as a foundation for many activities in modern computing applications at home, in vehicles, and in businesses. Many modern machines are built to carry out a specific activity or purpose. This is where the Amazon Alexa application comes in, as it is used as a virtual assistant. The purpose of this paper is to explore the use of Amazon Alexa among people and how it has improved and made simple daily tasks easier for many people. We gave our participants several questions regarding Amazon Alexa and if they had recently used or heard of it, as well as the different tasks it provides and whether it successfully satisfied their needs. Overall, we found that participants who have recently used Alexa have found it to be helpful in their daily tasks.

Keywords: artificial intelligence, Echo system, machine learning, feature for feature match

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Authors: Atitallah Sofien, Bouyahia Olfa, Krifi Farah, Missaoui Nada, Ben Rabeh Rania, Yahyaoui Salem, Mazigh Sonia, Boukthir Samir

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Introduction: Cutis marmorata telangiectatica congenita (CMTC) is a rare cutaneous vascular malformation. It most often appears at birth or during the first days of life. Its origin is still unknown. It associates a livedo with telangiectasias of diffuse or segmental topography. In rare cases, it can be associated with neurological disorders such as macrocephaly and, less frequently, with epilepsy. Methodology: We report a case of an infant with Macrocephaly- Cutis marmorata telangiectatica congenita syndrome associated with epilepsy. Results: This is the case of a one month and 15 days old female infant from a non-consanguineous marriage, admitted for a status epilepticus in the context of apyrexia. Infectious and metabolic causes had been eliminated. Physical examination had shown non-infiltrated and reticular livedoid erythematous patches affecting the left upper limb and atrophic on the back of the left hand. Cerebral magnetic resonance imaging (MRI) showed thin layers of bifrontal, temporal, and left parietal hygromas associated with the widening of the bifrontal subarachnoid spaces. The electroencephalogram showed a well-organized sleep tracing with a single right occipital paroxysmal abnormality. Antiepileptic treatment has been administered with good clinical evolution and regression of the skin lesion and a control electroencephalogram without abnormality. Conclusion: This observation illustrates an association of CMTC with both macrocephaly and epilepsy. This pathology, which is relatively benign and has a good prognosis, generally does not require treatment. However, a detailed examination must be carried out, and a follow-up plan must be put in place for each patient presenting with CMTC, given the risk of association with other abnormalities, which can be potentially serious.

Keywords: cutis marmorata telangiectatica congenita, macrocephaly, epilepsy, children

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Authors: Corlia van der Walt, Michele K. Havenga

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The study considers corporate governance regulation and practice in South African higher education institutions and makes recommendations for the improvement of current governance practices in this sector. The development of corporate governance principles and practices in South Africa, culminating in the King IV Report on Corporate Governance which was launched in November 2016, is discussed. King IV enjoys international recognition as a progressive corporate governance instrument. It was necessitated by the fundamental changes in business and society nationally and globally, as well as by the significant changes to South African company law introduced by new legislation. Corporate governance and the corporate form are narrowly associated, but there is general recognition that the principles of ethical and effective leadership are not restricted to corporations. Thus King IV was drafted with the express aim that it should apply to all organisations, regardless of their form of incorporation, and the report includes specific sector supplements in support of this aspiration. The South African higher education sector has of late been under intense scrutiny, and a few universities have been placed under administration because of poor governance practices. Universities have also been severely impacted by the consequences of what is generally known as ‘#FeesmustFall’, a student led protest movement initially aimed against the increase of fees at public universities, but which rapidly expanded to also include other concerns. It was clearly necessary to revisit corporate governance policy and practice in the sector. The review of the current higher education governance regime in light of the King IV recommendations, lessons from company law regarding the entrenchment and enforcement of corporate governance principles, and a comparison of higher education governance practices in selected other jurisdictions led to recommendations for the improvement of governance practices in South African higher education. It is further suggested that a sector supplement for higher education institutions may provide additional clarity. Some of the recommendations may be of comparative value for international higher education governance.

Keywords: committees, corporate governance, ethical leadership, higher education institutions, integrated reporting, King IV, sector supplements, sustainability

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Authors: Robert Caulk

Abstract:

A generalized framework for adaptive machine learning deployments in algorithmic trading is introduced, tested, and released as open-source code. The presented software aims to test the hypothesis that recent data contains enough information to form a probabilistically favorable short-term price prediction. Further, the framework contains various adaptive machine learning techniques that are geared toward generating profit during strong trends and minimizing losses during trend changes. Results demonstrate that this adaptive machine learning approach is capable of capturing trends and generating profit. The presentation also discusses the importance of defining the parameter space associated with the dynamic training data-set and using the parameter space to identify and remove outliers from prediction data points. Meanwhile, the generalized architecture enables common users to exploit the powerful machinery while focusing on high-level feature engineering and model testing. The presentation also highlights common strengths and weaknesses associated with the presented technique and presents a broad range of well-tested starting points for feature set construction, target setting, and statistical methods for enforcing risk management and maintaining probabilistically favorable entry and exit points. The presentation also describes the end-to-end data processing tools associated with FreqAI, including automatic data fetching, data aggregation, feature engineering, safe and robust data pre-processing, outlier detection, custom machine learning and statistical tools, data post-processing, and adaptive training backtest emulation, and deployment of adaptive training in live environments. Finally, the generalized user interface is also discussed in the presentation. Feature engineering is simplified so that users can seed their feature sets with common indicator libraries (e.g. TA-lib, pandas-ta). The user also feeds data expansion parameters to fill out a large feature set for the model, which can contain as many as 10,000+ features. The presentation describes the various object-oriented programming techniques employed to make FreqAI agnostic to third-party libraries and external data sources. In other words, the back-end is constructed in such a way that users can leverage a broad range of common regression libraries (Catboost, LightGBM, Sklearn, etc) as well as common Neural Network libraries (TensorFlow, PyTorch) without worrying about the logistical complexities associated with data handling and API interactions. The presentation finishes by drawing conclusions about the most important parameters associated with a live deployment of the adaptive learning framework and provides the road map for future development in FreqAI.

Keywords: machine learning, market trend detection, open-source, adaptive learning, parameter space exploration

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Danuvasin Charoen

Abstract:

The study investigates the business process and business model of GRABTAXI. The paper also discusses how the company implemented strategies to gain competitive advantages. The data is derived from the analysis of secondary data and the in-depth interviews among staffs, taxi drivers, and key customers. The findings indicated that the company’s competitive advantages come from being the first mover, emphasising on the ease of use and tangible benefits of application, and using network effect strategy.

Keywords: taxi, mobile application, innovative business model, Thailand

Procedia PDF Downloads 288

Authors: Popoola Sulaimon Akorede, Muinat A. Agbabiaka-Mustapha

Abstract:

The Quranic / piazza school where the rudiments of Islam are being imparted from the teaching of Arabic/ Quranic alphabets which later metamorphosized to higher fundamental principles of Islam is the major determinant of the existence of Islam in any part of south western Nigeria. In other words, one can successfully say that where there is a few or non-existence of such schools in that part of the country, the practice of the religion of Islam would be either very low or not existing at all. However, it has been discovered in the modern worlds that several challenges are militating against the development of these schools and among these challenges are poor admission policy, inadequate facilities such as learning environment and instructional materials, curriculum inadequacy and the management and the administration of the schools which failed to change in order to meet the modern contemporary Educational challenges. The focus of this paper therefore is to improve the conditions of these basic Islamic schools through the introduction of quality assurance and integrating accreditation Exercise to improve their status in order to enhance economic empowerment and to further their educational career in the future so that they will be able to compete favourably among the graduates of conventional universities. The scope of this study is limited to only seven (7) states of yorubaland and with only three (3) proprietors/ schools from each state which are Lagos, Oyo, Ogun, Osun, Ekiti, Ondo and parts of Kwara State. The study revealed that quality assurance as well as accreditation exercise are lacking in all the local Arabic/Quranic schools. Suggestions are proffered towards correcting the anomalies in these schools so that they can meet the modern Educational standard.

Keywords: accreditation, quality assurance, Quranic schools, South-western Nigeria

Procedia PDF Downloads 364

Authors: Felipa M. Rico

Abstract:

Linguistic oral competence plays a vital role in attaining effective communication. Since the English language is considered as universally used language and has a high demand skill needed in the work-place, mastery is the expected output from learners. To achieve this, learners should be given integrated differentiated tasks which help them develop and strengthen the expected skills. This study aimed to develop speaking instructional supplementary material to enhance the English linguistic competence of Grade 9 students in areas of pronunciation, intonation and stress, voice projection, diction and fluency. A descriptive analysis was utilized to analyze the speaking level of performance of the students in order to employ appropriate strategies. There were two sets of respondents: 178 Grade 9 students selected through a stratified sampling and chosen at random. The other set comprised English teachers who evaluated the usefulness of the devised teaching materials. A teacher conducted a speaking test and activities were employed to analyze the speaking needs of students. Observation and recordings were also used to evaluate the students’ performance. The findings revealed that the English pronunciation of the students was slightly unclear at times, but generally fair. There were lapses but generally they rated moderate in intonation and stress, because of other language interference. In terms of voice projection, students have erratic high volume pitch. For diction, the students’ ability to produce comprehensible language is limited, and as to fluency, the choice of vocabulary and use of structure were severely limited. Based on the students’ speaking needs analyses, the supplementary material devised was based on Nunan’s IM model, incorporating context of daily life and global work settings, considering the principle that language is best learned in the actual meaningful situation. To widen the mastery of skill, a rich learning environment, filled with a variety instructional material tends to foster faster acquisition of the requisite skills for sustained learning and development. The role of IM is to encourage information to stick in the learners’ mind, as what is seen is understood more than what is heard. Teachers say they found the IM “very useful.” This implied that English teachers could adopt the materials to improve the speaking skills of students. Further, teachers should provide varied opportunities for students to get involved in real life situations where they could take turns in asking and answering questions and share information related to the activities. This would minimize anxiety among students in the use of the English language.

Keywords: diction, fluency, intonation, instructional materials, linguistic competence

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Authors: Martha E. Aguiar-Barrera, Humberto Gutierrez-Pulido, Veronica Vargas-Alejo

Abstract:

Identifying and modeling random phenomena is a fundamental cognitive process to understand and transform reality. Recognizing situations governed by chance and giving them a scientific interpretation, without being carried away by beliefs or intuitions, is a basic training for citizens. Hence the importance of generating teaching-learning processes, supported using technology, paying attention to model creation rather than only executing mathematical calculations. In order to develop the student's knowledge about basic probability distributions and decision making; in this work a model eliciting activity (MEA) is reported. The intention was applying the Model and Modeling Perspective to design an activity related to civil engineering that would be understandable for students, while involving them in its solution. Furthermore, the activity should imply a decision-making challenge based on sample data, and the use of the computer should be considered. The activity was designed considering the six design principles for MEA proposed by Lesh and collaborators. These are model construction, reality, self-evaluation, model documentation, shareable and reusable, and prototype. The application and refinement of the activity was carried out during three school cycles in the Probability and Statistics class for Civil Engineering students at the University of Guadalajara. The analysis of the way in which the students sought to solve the activity was made using audio and video recordings, as well as with the individual and team reports of the students. The information obtained was categorized according to the activity phase (individual or team) and the category of analysis (sample, linearity, probability, distributions, mechanization, and decision-making). With the results obtained through the MEA, four obstacles have been identified to understand and apply the binomial distribution: the first one was the resistance of the student to move from the linear to the probabilistic model; the second one, the difficulty of visualizing (infering) the behavior of the population through the sample data; the third one, viewing the sample as an isolated event and not as part of a random process that must be viewed in the context of a probability distribution; and the fourth one, the difficulty of decision-making with the support of probabilistic calculations. These obstacles have also been identified in literature on the teaching of probability and statistics. Recognizing these concepts as obstacles to understanding probability distributions, and that these do not change after an intervention, allows for the modification of these interventions and the MEA. In such a way, the students may identify themselves the erroneous solutions when they carrying out the MEA. The MEA also showed to be democratic since several students who had little participation and low grades in the first units, improved their participation. Regarding the use of the computer, the RStudio software was useful in several tasks, for example in such as plotting the probability distributions and to exploring different sample sizes. In conclusion, with the models created to solve the MEA, the Civil Engineering students improved their probabilistic knowledge and understanding of fundamental concepts such as sample, population, and probability distribution.

Keywords: linear model, models and modeling, probability, randomness, sample

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Authors: Colm Barcoe, Garvan Whelan

Abstract:

In tourism, engagement has been found to boost awareness of a destination and subsequently increase visits. Customer engagement in this industry is now facilitated by social media. This phenomenon is not very well researched in relation to Ireland and the North American tourism market. The objective of this paper is to present research findings on two related topics; the first is an investigation into the effectiveness of social media channels as components of a digital marketing campaign when promoting Ireland as a brand in North America. Secondly, this study reveals how Irish marketers have embraced social media platforms and channels with an innovative strategy that has successfully attracted growing numbers of US and Canadian holidaymakers to Ireland. A range of methodological approaches was applied in order to achieve the study’s objective. The methods used were both quantitative and qualitative, and the data was obtained from both Irish marketers and North American holidaymakers. Surveys of these holidaymakers in the pre, during and post-trip phases revealed their attitudes towards social media and Ireland as a destination. Semi-structured interviews with those responsible for implementing relationship marketing strategies for this segment provide insight into the effectiveness of social media when used to capitalise on the cultural link between Ireland and North America. Further analysis involved using Nvivo 11+ software to investigate the activities of the Irish destination marketer (DMO) and the engagement of the US and Canadian audiences through a detailed study of social media platform content. The findings from this investigation will extend an under-researched body of literature pertaining to Ireland as a destination and the successful digital marketing campaigns that have achieved exponential growth in this sector over the past five years. The empirical evidence presented also illustrates how the innovative use of social media has assisted the DMO to engage with the North American holidaymaker as part of an effective digital marketing strategy.

Keywords: channels, digital, engagement, marketing, strategies

Procedia PDF Downloads 141