Search results for: deep learning methods

Authors: Andre Bechuke

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The quality of every learning programme in Higher Education (HE) is dependent on the planning, design, and development of the curriculum decisions. These curriculum development decisions are highly influenced by the knowledge of the end-user, who are not always just the students. When curriculum experts plan, design and develop learning programmes, they always have the end-users in mind throughout the process. Without proper knowledge of the end-user(s), the design and development of a learning programme might be flawed. Curriculum experts often struggle to determine who the real end-user is. As such, it is even more challenging to establish what needs to be known about the end user that should inform the plan, design, and development of a learning programme. This research sought suggest approaches to guide curriculum experts to identify the end-user(s), taking into consideration the pressure and influence other agencies and structures or stakeholders (industry, students, government, universities context, lecturers, international communities, professional regulatory bodies) have on the design of a learning programme and the graduates of the programmes. Considering the influence of these stakeholders, which is also very important, the task of deciding who the real end-user of the learning programme becomes very challenging. This study makes use of criteria 1 and 18 of the Council on Higher Education criteria for programme accreditation to guide the process of identifying the end-users when developing a learning programme. Criterion 1 suggests that designers must ensure that the programme is consonant with the institution’s mission, forms part of institutional planning and resource allocation, meets national requirements and the needs of students and other stakeholders, and is intellectually credible. According to criterion 18, in designing a learning programme, steps must be taken to enhance the employability of students and alleviate shortages of expertise in relevant fields. In conclusion, there is hardly ever one group of end-users to be considered for developing a learning programme, and the notion that students are the end-users is not true, especially when the graduates are unable to use the qualification for employment.

Keywords: council on higher education, curriculum design and development, higher education, learning programme

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Authors: ShyamKrishna Kirithivasan, Shreyas Battula, Aditi Soori, Richa Ramesh, Ramamoorthy Srinath

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The human brain, among the most complex and mysterious aspects of the body, harbors vast potential for extensive exploration. Unraveling these enigmas, especially within neural perception and cognition, delves into the realm of neural decoding. Harnessing advancements in generative AI, particularly in Visual Computing, seeks to elucidate how the brain comprehends visual stimuli observed by humans. The paper endeavors to reconstruct human-perceived visual stimuli using Functional Magnetic Resonance Imaging (fMRI). This fMRI data is then processed through pre-trained deep-learning models to recreate the stimuli. Introducing a new architecture named LatentNeuroNet, the aim is to achieve the utmost semantic fidelity in stimuli reconstruction. The approach employs a Latent Diffusion Model (LDM) - Stable Diffusion v1.5, emphasizing semantic accuracy and generating superior quality outputs. This addresses the limitations of prior methods, such as GANs, known for poor semantic performance and inherent instability. Text conditioning within the LDM's denoising process is handled by extracting text from the brain's ventral visual cortex region. This extracted text undergoes processing through a Bootstrapping Language-Image Pre-training (BLIP) encoder before it is injected into the denoising process. In conclusion, a successful architecture is developed that reconstructs the visual stimuli perceived and finally, this research provides us with enough evidence to identify the most influential regions of the brain responsible for cognition and perception.

Keywords: BLIP, fMRI, latent diffusion model, neural perception.

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Authors: Amy Hodges, Deanna Rasmussen, Sherry Ward

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This paper examines the use of ePortfolios in a two-course sequence for ESL (English as a Second Language) students at an international branch campus in Doha, Qatar. ePortfolios support the transfer of language learning, but few have examined the sustainability of that transfer across an ESL program. Drawing upon surveys and interviews with students, we analyze three case studies that complicate previous research on metacognition, language learning, and ePortfolios. Our findings have implications for those involved in ESL programs and assessment of student writing.

Keywords: TESOL, electronic portfolios, assessment, technology

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Authors: Vani Singhal, Jitendra Parmar, Satyendra Singh Chouhan

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Unseen class discovery has now become an important part of a machine-learning algorithm to judge new classes. Unseen classes are the classes on which the machine learning model is not trained on. With the advancement in technology and AI replacing humans, the amount of data has increased to the next level. So while implementing a model on real-world examples, we come across unseen new classes. Our aim is to find the number of unseen classes by using a hierarchical-based active learning algorithm. The algorithm is based on hierarchical clustering as well as active sampling. The number of clusters that we will get in the end will give the number of unseen classes. The total clusters will also contain some clusters that have unseen classes. Instead of first discovering unseen classes and then finding their number, we directly calculated the number by applying the algorithm. The dataset used is for intent classification. The target data is the intent of the corresponding query. We conclude that when the machine learning model will encounter real-world data, it will automatically find the number of unseen classes. In the future, our next work would be to label these unseen classes correctly.

Keywords: active sampling, hierarchical clustering, open world learning, unseen class discovery

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Authors: Shalini Adiga, Shashikant Chetty, Jisha, Shobha Kamath

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Background: Moderate impairment of learning and memory has been observed in both type 1 and 2 diabetes mellitus in humans and experimental animals. A Change in glucose utilization and oxidative stress that occur in diabetes are considered the main reasons for cognitive dysfunction. Objective: Costus igneus (CI) which is known to possess hypoglycemic activity was evaluated in this study for its effect on learning and memory in normal and diabetic rats. Methods: Wistar rats were divided into control, CI-alcoholic extract treated normal (250 and 500mg/kg), diabetic control and CI-treated diabetic groups. CI treatment was continued for 4 weeks. For induction of diabetes, a single dose of streptozotocin was injected (30 mg/kg i.p). Entrance latency and time spent in the dark room during acquisition and at 24 and 48h after an aversive shock in a passive avoidance model was used as an index of learning and memory. Glutathione and malondialdehyde levels in brain and blood glucose were measured. Data was analysed using ANOVA. Results: During the three trials in exploration test, the diabetic control rats exhibited no significant change in entrance latency or in the total time spent in the dark compartment. During retention testing, the entrance latency of the diabetic treated groups was two times less at 24h and three times less at 48h after aversive stimulus as compared to diabetic rats. The normal drug-treated rats showed similar behaviour as the saline control. Treatment with CI significantly reduced the raised blood sugar and MDA levels of diabetic rats. Conclusion: Costus igneus prevented the cognitive dysfunction in diabetic rats which can be attributed to its antioxidant and antihyperglycemic activities.

Keywords: Costus igneous, diabetes, learning and memory, cognitive dysfunction

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Authors: Girish Choudhary

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Education is in a state of flux. Not only one need to acquire skills in order to cope with a fast changing global world, an explosive growth in technology, on the other hand is providing a new wave of teaching tools - computer aided video instruction, hypermedia, multimedia, CD-ROMs, Internet connections, and collaborative software environments. The emerging technology incorporates the group qualities of interactive, classroom-based learning while providing individual students the flexibility to participate in an educational programme at their own time and place. The technology facilitating self learning also seems to provide a cost effective solution to the dilemma of delivering education to masses. Online education is a unique learning domain that provides for many to many communications as well. The computer conferencing software defines the boundaries of the virtual classroom. The changing paradigm provides access of instruction to a large proportion of society, promises a qualitative change in the quality of learning and echoes a new way of thinking in educational theory that promotes active learning and open new learning approaches. Putting it to practice is challenging and may fundamentally alter the nature of educational institutions. The subsequent part of paper addresses such questions viz. 'Do we need to radically re-engineer the curriculum and foster an alternate set of skills in students?' in the onward journey.

Keywords: on-line education, self learning, energy and power engineering, future education

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Authors: Mohammad R. Jafari, Francois G. Bernardeau

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With its arid climate, Qatar experiences low annual rainfall, intense storms, and high evaporation rates. However, the fast-paced rate of infrastructure development in the capital city of Doha has led to recurring instances of surface water flooding as well as rising groundwater levels. Public Work Authority (PWA/ASHGHAL) has implemented an approach to collect and discharge the flood water into a) positive gravity systems; b) Emergency Flooding Area (EFA) – Evaporation, Infiltration or Storage off-site using tankers; and c) Discharge to deep injection wells. As part of the flood prevention scheme, 21 deep injection wells have been constructed to discharge the collected surface and groundwater table in Doha city. These injection wells function as an alternative in localities that do not possess either positive gravity systems or downstream networks that can accommodate additional loads. These injection wells are 400-m deep and are constructed in a complex karstic subsurface condition with large cavities. The injection well system will discharge collected groundwater and storm surface runoff into the permeable Umm Er Radhuma Formation, which is an aquifer present throughout the Persian Gulf Region. The Umm Er Radhuma formation contains saline water that is not being used for water supply. The injection zone is separated by an impervious gypsum formation which acts as a barrier between upper and lower aquifer. State of the art drilling, grouting, and geophysical techniques have been implemented in construction of the wells to assure that the shallow aquifer would not be contaminated and impacted by injected water. Injection and pumping tests were performed to evaluate injection well functionality (injectability). The results of these tests indicated that majority of the wells can accept injection rate of 200 to 300 m³ /h (56 to 83 l/s) under gravity with average value of 250 m³ /h (70 l/s) compared to design value of 50 l/s. This paper presents design and construction process and issues associated with these injection wells, performing injection/pumping tests to determine capacity and effectiveness of the injection wells, the detailed design of collection system and conveying system into the injection wells, and the operation and maintenance process. This system is completed now and is under operation, and therefore, construction of injection wells is an effective option for flood control.

Keywords: deep injection well, flood prevention scheme, geophysical tests, pumping and injection tests, wellhead assembly

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Authors: Taekyong Lee, Joon-Young Kim, Jae-Min Cha

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Piping and instrumentation diagram (P&ID) is an essential design drawing describing the interconnection of process equipment and the instrumentation installed to control the process. P&IDs are modified and managed throughout a whole life cycle of a process plant. For the ease of data transfer, P&IDs are generally handed over from a design company to an engineering company as portable document format (PDF) which is hard to be modified. Therefore, engineering companies have to deploy a great deal of time and human resources only for manually converting P&ID images into a computer aided design (CAD) file format. To reduce the inefficiency of the P&ID conversion, various symbols and texts in P&ID images should be automatically recognized. However, recognizing information in P&ID images is not an easy task. A P&ID image usually contains hundreds of symbol and text objects. Most objects are pretty small compared to the size of a whole image and are densely packed together. Traditional recognition methods based on geometrical features are not capable enough to recognize every elements of a P&ID image. To overcome these difficulties, state-of-the-art deep learning models, RetinaNet and connectionist text proposal network (CTPN) were used to build a system for recognizing symbols and texts in a P&ID image. Using the RetinaNet and the CTPN model carefully modified and tuned for P&ID image dataset, the developed system recognizes texts, equipment symbols, piping symbols and instrumentation symbols from an input P&ID image and save the recognition results as the pre-defined extensible markup language format. In the test using a commercial P&ID image, the P&ID information recognition system correctly recognized 97% of the symbols and 81.4% of the texts.

Keywords: object recognition system, P&ID, symbol recognition, text recognition

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Authors: Halimat M. Ajose-Adeogun, Zaynab A. Bello

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Artificial Intelligence (AI) and Natural Language Processing (NLP) have transformed computer language comprehension, allowing computers to comprehend spoken and written language with human-like cognition. NLP, a multidisciplinary area that combines rule-based linguistics, machine learning, and deep learning, enables computers to analyze and comprehend human language. NLP applications in medicine range from tackling issues in electronic health records (EHR) and psychiatry to improving diagnostic precision in orthopedic surgery and optimizing clinical procedures with novel technologies like chatbots. The technology shows promise in a variety of medical sectors, including quicker access to medical records, faster decision-making for healthcare personnel, diagnosing dysplasia in Barrett's esophagus, boosting radiology report quality, and so on. However, successful adoption requires training for healthcare workers, fostering a deep understanding of NLP components, and highlighting the significance of validation before actual application. Despite prevailing challenges, continuous multidisciplinary research and collaboration are critical for overcoming restrictions and paving the way for the revolutionary integration of NLP into medical practice. This integration has the potential to improve patient care, research outcomes, and administrative efficiency. The research methodology includes using NLP techniques for Sentiment Analysis and Emotion Recognition, such as evaluating text or audio data to determine the sentiment and emotional nuances communicated by users, which is essential for designing a responsive and sympathetic chatbot. Furthermore, the project includes the adoption of a Personalized Intervention strategy, in which chatbots are designed to personalize responses by merging NLP algorithms with specific user profiles, treatment history, and emotional states. The synergy between NLP and personalized medicine principles is critical for tailoring chatbot interactions to each user's demands and conditions, hence increasing the efficacy of mental health care. A detailed survey corroborated this synergy, revealing a remarkable 20% increase in patient satisfaction levels and a 30% reduction in workloads for healthcare practitioners. The poll, which focused on health outcomes and was administered to both patients and healthcare professionals, highlights the improved efficiency and favorable influence on the broader healthcare ecosystem.

Keywords: natural language processing, artificial intelligence, healthcare communication, electronic health records, patient care

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Authors: Ahcene Habbi, Yassine Boudouaoui

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This paper deals with the problem of automatic rule generation for fuzzy systems design. The proposed approach is based on hybrid artificial bee colony (ABC) optimization and weighted least squares (LS) method and aims to find the structure and parameters of fuzzy systems simultaneously. More precisely, two ABC based fuzzy modeling strategies are presented and compared. The first strategy uses global optimization to learn fuzzy models, the second one hybridizes ABC and weighted least squares estimate method. The performances of the proposed ABC and ABC-LS fuzzy modeling strategies are evaluated on complex modeling problems and compared to other advanced modeling methods.

Keywords: automatic design, learning, fuzzy rules, hybrid, swarm optimization

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Authors: Mohammad Shahid Jamil

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In this study we have investigated students’ learning and satisfaction in one of the course offered in the Foundation Program at Qatar University. We implied innovative teaching methodology that emphasizes on enhancing students’ thinking skills, decision making, and problem solving skills. Some interesting results were found which can be used to further improve the teaching methodology. To make sure the full use of technology in Foundation Program at Qatar University has started implementing new ways of teaching Math course by using Blackboard as an innovative interactive tool to support standard teaching such as Discussion board, Virtual class, and Study plan in My Math Lab “MML”. In MML Study Plan is designed in such a way that the student can improve their skills wherever they face difficulties with in their Homework, Quiz or Test. Discussion board and Virtual Class are collaborative learning tools encourages students to engage outside of class time. These tools are useful to share students’ knowledge and learning experiences, promote independent and active learning and they helps students to improve their critical thinking skills through the learning process.

Keywords: blackboard, discussion board, critical thinking, active learning, independent learning, problem solving

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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: E. Maoz

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Background: As a teaching method, project-based learning is strongly linked to developing students’ critical thinking skills. It combines creative independent thinking, team work, and disciplinary subject-field integration. In the 'Introduction to Nursing Research Methods' course (year 3, Generic Track), project based learning is used to teach the topic of 'Evidence-Based Nursing'. This topic examines a clinical care issue encountered by students in the field. At the end of their project, students present proposals for managing the said issue. Proposals are the product of independent integrative thinking integrating a wide range of factors influencing the issue’s management. Method: Papers by 27 groups of students (165 students) were content analyzed to identify which themes emerged from the students' recommendations for managing the clinical issue. Findings: Five main themes emerged—current management approach; adapting procedures in line with current recent research recommendations; training for change (veteran nursing staff, beginner students, patients, significant others); analysis of 'economic benefit vs. patient benefit'; multidisciplinary team engagement in implementing change in practice. Two surprising themes also emerged: advertising and marketing using new technologies, which reflects how the new generation thinks. Summary and Recommendations: Among the main challenges in nursing education is training nursing graduates to think independently, integratively, and critically. Combining PBL with classical teaching methods stimulates students cognitively while opening new vistas with implications on all levels of the profession: management, research, education, and practice. Advanced students can successfully grasp and interpret the current state of clinical practice. They are competent and open to leading change and able to consider the diverse factors and interconnections that characterize the nurse's work.

Keywords: evidence based nursing, critical thinking skills, project based learning, students education

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Authors: B. Ramesh Naik, T. Venugopal

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This paper presents a novel approach which improves the high-level semantics of images based on machine learning approach. The contemporary approaches for image retrieval and object recognition includes Fourier transforms, Wavelets, SIFT and HoG. Though these descriptors helpful in a wide range of applications, they exploit zero order statistics, and this lacks high descriptiveness of image features. These descriptors usually take benefit of primitive visual features such as shape, color, texture and spatial locations to describe images. These features do not adequate to describe high-level semantics of the images. This leads to a gap in semantic content caused to unacceptable performance in image retrieval system. A novel method has been proposed referred as discriminative learning which is derived from machine learning approach that efficiently discriminates image features. The analysis and results of proposed approach were validated thoroughly on WANG and Caltech-101 Databases. The results proved that this approach is very competitive in content-based image retrieval.

Keywords: CBIR, discriminative learning, region weight learning, scale invariant feature transforms

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Authors: Pauli P.Y. Lai

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Students with Special Education Needs (SEN) face many challenges in learning. Various challenges include difficulty in handwriting, slow understanding and assimilation, difficulty in paying attention during class, and lack of communication skills. To engage students with Special Education Needs in class with general students, Blackboard Collaborate is used as a teaching and learning tool to deliver a lecture with interactive activities. Blackboard Collaborate provides a good platform to create and enhance active, collaborative and interactive learning experience whereby the SEN students can easily interact with their general peers and the instructor by using the features of drawing on a virtual whiteboard, file sharing, classroom chatter, breakout room, hand-raising feature, polling, etc. By integrating a blended learning approach with Blackboard Collaborate, the students with Special Education Needs could engage in interactive activities with ease in class. Our research aims at exploring and discovering the use of Blackboard Collaborate for inclusive education based on a qualitative design with in-depth interviews. Being served in a general education environment, three university students with different kinds of learning disabilities have participated in our study. All participants agreed that functions provided by Blackboard Collaborate have enhanced their learning experiences and helped them learn better. Their academic performances also showed that SEN students could perform well with the help of technology. This research studies different aspects of using Blackboard Collaborate to create an inclusive learning environment for SEN students.

Keywords: blackboard collaborate, enhanced learning experience, inclusive education, special education needs

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Authors: Abdulkadir Mustapha Gana, Musa Baba Adamu, Edimeh Augustine Jr

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There are growing concerns over the astronomical decline inquality of teaching and learning amongst youths especially in developing countries, and handful research have been conducted in this regard. However, results from many of these studies revealed similar findings which all pointed to the steady decline in quality of teaching and learning across the globe. One common factor attributed for this drawback was the new media due to the evolution and advancement of technology as studies have revealed. In the beginning, what was then the new media (broadcast media of radio and television) was singled out as being responsible for diverting people’s attention from reading; particularly television. At present times, it was revealed that the social media and internet connectivity were responsible for diverting the attention of many, thus distracting attentions from reading. However, it is pertinent to note that the devastating effects, social media platforms have a couple of tools that could improve reading by extension teaching and learning amongst students. Therefore, this study reviewed the literature on the advantageous aspect of social media to reading and learning; whilst laying emphasis on how youths can utilize social media to improve their reading habits.

Keywords: ebook, reading, learning, students

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Authors: Dian Guan

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With the wide application of multimedia and the Internet, the development of teaching theories, and the implementation of teaching reforms, many different university English classroom teaching modes have emerged. The university English teaching mode is changing from the traditional teaching mode based on conversation and text to the multimodal English teaching mode containing discussion, pictures, audio, film, etc. Applying university English teaching models is conducive to cultivating lifelong learning skills. In addition, lifelong learning skills can also be called learners' autonomous learning skills. Learners' independent learning ability has a significant impact on English learning. However, many university students, especially art and design students, don't know how to learn individually. When they become university students, their English foundation is a relative deficiency because they always remember the language in a traditional way, which, to a certain extent, neglects the cultivation of English learners' independent ability. As a result, the autonomous learning ability of most university students is not satisfactory. The participants in this study were 60 students and one teacher in their first year at a university in western China. Two observations and interviews were conducted inside and outside the classroom to understand the impact of a multimodal teaching model of university English on students' autonomous learning ability. The results were analyzed, and it was found that the multimodal teaching model of university English significantly affected learners' autonomy. Incorporating classroom presentations and poster exhibitions into multimodal teaching can increase learners' interest in learning and enhance their learning ability outside the classroom. However, further exploration is needed to develop multimodal teaching materials and evaluate multimodal teaching outcomes. Despite the limitations of this study, the study adopts a scientific research method to analyze the impact of the multimodal teaching mode of university English on students' independent learning ability. It puts forward a different outlook for further research on this topic.

Keywords: art university, EFL education, learner autonomy, multimodal pedagogy

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Authors: C. Mayr, J. Periya, A. Kariminezhad

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In this paper, we developed a learning framework for the classification of vulnerable road users (VRU) by their range-Doppler signatures. The frequency-modulated continuous-wave (FMCW) radar raw data is first pre-processed to obtain robust object range-Doppler maps per coherent time interval. The complex-valued range-Doppler maps captured from our outdoor measurements are further fed into a convolutional neural network (CNN) to learn the classification. This CNN has gone through a hyperparameter optimization process for improved learning. By learning VRU range-Doppler signatures, the three classes 'pedestrian', 'dog', and 'noise' are classified with an average accuracy of almost 95%. Interestingly, this classification accuracy holds for a combined longitudinal and lateral object trajectories.

Keywords: machine learning, radar, signal processing, autonomous driving

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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: Kavita Goel, Donald Winchester

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In a world of information overload and work complexities, academics often struggle to create an online instructional environment enabling efficient and effective student learning. Research has established that students’ learning styles are different, some learn faster when taught using audio and visual methods. Attributes like prior knowledge and mental effort affect their learning. ‘Cognitive load theory’, opines learners have limited processing capacity. Cognitive load depends on the learner’s prior knowledge, the complexity of content and tasks, and instructional environment. Hence, the proper allocation of cognitive resources is critical for students’ learning. Consequently, a lecturer needs to understand the limits and strengths of the human learning processes, various learning styles of students, and accommodate these requirements while designing online assessments. As acknowledged in the cognitive load theory literature, visual and auditory explanations of worked examples potentially lead to a reduction of cognitive load (effort) and increased facilitation of learning when compared to conventional sequential text problem solving. This will help learner to utilize both subcomponents of their working memory. Instructional design changes were introduced at the case site for the delivery of the postgraduate business subjects. To make effective use of auditory and visual modalities, video recorded lectures, and key concept webinars were delivered to students. Videos were prepared to free up student limited working memory from irrelevant mental effort as all elements in a visual screening can be viewed simultaneously, processed quickly, and facilitates greater psychological processing efficiency. Most case study students in the postgraduate programs are adults, working full-time at higher management levels, and studying part-time. Their learning style and needs are different from other tertiary students. The purpose of the audio and visual interventions was to lower the students cognitive load and provide an online environment supportive to their efficient learning. These changes were expected to impact the student’s learning experience, their academic performance and retention favourably. This paper posits that these changes to instruction design facilitates students to integrate new knowledge into their long-term memory. A mixed methods case study methodology was used in this investigation. Primary data were collected from interviews and survey(s) of students and academics. Secondary data were collected from the organisation’s databases and reports. Some evidence was found that the academic performance of students does improve when new instructional design changes are introduced although not statistically significant. However, the overall grade distribution of student’s academic performance has changed and skewed higher which shows deeper understanding of the content. It was identified from feedback received from students that recorded webinars served as better learning aids than material with text alone, especially with more complex content. The recorded webinars on the subject content and assessments provides flexibility to students to access this material any time from repositories, many times, and this enhances students learning style. Visual and audio information enters student’s working memory more effectively. Also as each assessment included the application of the concepts, conceptual knowledge interacted with the pre-existing schema in the long-term memory and lowered student’s cognitive load.

Keywords: cognitive load theory, learning style, instructional environment, working memory

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Authors: Valerie Yocco Rossi

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Objective: The author will share why differentiation is necessary for all classrooms as well as strategies for differentiating content, process, and product. Through learning how to differentiate, teachers will be able to create activities and assessments to meet the abilities, readiness levels, and interests of all learners. Content and Purpose: This work will focus on how to create a learning experience for students that recognizes their different interests, abilities, and readiness levels by differentiating content, process, and product. Likewise, the best learning environments allow for choice. Choice boards allow students to select tasks based on interests. There can be challenging and basic tasks to meet the needs of various abilities. Equally, rubrics allow for personalized and differentiated assessments based on readiness levels and cognitive abilities. The principals of DI help to create a classroom where all students are learning to the best of their abilities. Outcomes: After reviewing the work, readers will be able to (1) identify the benefits of differentiated instruction; (2) convert traditional learning activities to differentiated ones; (3) differentiate, writing-based assessments.

Keywords: differentiation, personalized learning, design, instructional strategies

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Authors: Matshidiso Joyce Taole, Linley Cornish

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Teacher’s professional knowledge has become the focus of interest over decades and the interest has intensified in the 21st century. Teachers are expected to develop their professional academic expertise continually, on an ongoing basis. Such professional development may relate to acquiring enhanced expertise in terms of leadership, curriculum development, teaching and learning, assessment of/for learning and feedback for enhanced learning. The paper focuses on professional knowledge base required for teachers in multi-grade contexts. This paper argues that although teacher knowledge is strongly related to individual experiences and contexts, there are elements of teacher knowledge that are particular to multi-grade context. The study employed qualitative design using interviews and observations. The participants were multi-grade teachers and teaching principals. The study revealed that teachers need to develop skills such as learner grouping, differentiating the curriculum, planning, time management and be life-long learners so that they stay relevant and up to date with developments not only in the education sector but globally. This will help teachers to learn increasingly sophisticated methods for engaging the diverse needs of students in their classrooms.

Keywords: curriculum differentiation, multi-grade, planning, teacher knowledge

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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

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Authors: Leila Maleki, Ahmad Esmali Kooraneh, Hossein Taghi Derakhshi

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Neural activity in the human brain starts from the early stages of prenatal development. This activity or signals generated by the brain are electrical in nature and represent not only the brain function but also the status of the whole body. At the present moment, three methods can record functional and physiological changes within the brain with high temporal resolution of neuronal interactions at the network level: the electroencephalogram (EEG), the magnet oencephalogram (MEG), and functional magnetic resonance imaging (fMRI); each of these has advantages and shortcomings. EEG recording with a large number of electrodes is now feasible in clinical practice. Multichannel EEG recorded from the scalp surface provides a very valuable but indirect information about the source distribution. However, deep electrode measurements yield more reliable information about the source locations، Intracranial recordings and scalp EEG are used with the source imaging techniques to determine the locations and strengths of the epileptic activity. As a source localization method, Low Resolution Electro-Magnetic Tomography (LORETA) is solved for the realistic geometry based on both forward methods, the Boundary Element Method (BEM) and the Finite Difference Method (FDM). In this paper, we review The findings EEG- LORETA about epilepsy.

Keywords: epilepsy, EEG, EEG-LORETA

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Authors: Shuqi Zhang

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Federated learning allows users to participate in collaborative model training without sending data to third-party servers, reducing the risk of user data privacy leakage, and is widely used in smart finance and smart healthcare. However, the distributed architecture design of federation learning itself and the existence of secure aggregation protocols make it inherently vulnerable to backdoor attacks. To solve this problem, the federated learning backdoor defense framework FLEX based on group aggregation, cluster analysis, and neuron pruning is proposed, and inter-compatibility with secure aggregation protocols is achieved. The good performance of FLEX is verified by building a horizontal federated learning framework on the CIFAR-10 dataset for experiments, which achieves 98% success rate of backdoor detection and reduces the success rate of backdoor tasks to 0% ~ 10%.

Keywords: federated learning, secure aggregation, backdoor attack, cluster analysis, neuron pruning

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Authors: Somchai Buaroong

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This research aims to investigating strong points and challenges in application of an online learning management system to an English course. Data were collected from observation, learners’ oral and written reports, and the teacher’s journals. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, and multiple regression analysis. The findings show that the system was an additional channel to enhance English language learning through written class assignments that were digitally accessible by any group members, and through communication between the teacher and learners and among learners themselves. Thus, the learning management system could be a promising tool for foreign language teachers. Also revealed in the study were difficulties in its use. The article ends with discussions of findings of the system for foreign language classes in association to pedagogy are also included and in the level of signification.

Keywords: english course, foreign language system, online learning management system, teacher’s journals

Procedia PDF Downloads 275

Authors: Armin Eilaghi, Ahmad Sedaghat, Hayder Abdurazzak, Fadi Alkhatib, Shiva Sadeghi, Martin Jaeger

Abstract:

A summary of experiences, recommendations, and lessons learnt in the application of PBL in the course of “Engineering Skills” in the School of Engineering at Australian College of Kuwait in Kuwait is presented. Four projects were introduced as part of the PBL course “Engineering Skills” to 24 students in School of Engineering. These students were grouped in 6 teams to develop their skills in 10 learning outcomes. The learning outcomes targeted skills such as drawing, design, modeling, manufacturing and analysis at a preliminary level; and also some life line learning and teamwork skills as these students were exposed for the first time to the PBL (project based learning). The students were assessed for 10 learning outcomes of the course and students’ feedback was collected using an anonymous survey at the end of the course. Analyzing the students’ feedbacks, it is observed that 67% of students preferred multiple smaller projects than a single big project because it provided them with more time and attention focus to improve their “soft skills” including project management, risk assessment, and failure analysis. Moreover, it is found that 63% of students preferred to work with different team members during the course to improve their professional communication skills. Among all, 62% of students believed that working with team members from other departments helped them to increase the innovative aspect of projects and improved their overall performance. However, 70% of students counted extra time needed to regenerate momentum with the new teams as the major challenge. Project based learning provided a suitable platform for introducing students to professional engineering practice and meeting the needs of students, employers and educators. It was found that students achieved their 10 learning outcomes and gained new skills developed in this PBL unit. This was reflected in their portfolios and assessment survey.

Keywords: project-based learning, engineering skills, undergraduate engineering, problem-based learning

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Authors: R. Alias, A. Kasa, M. R. Taha

Abstract:

The effect of particle size on shear strength of granular materials are investigated using direct shear tests. Small direct shear test (60 mm by 60 mm by 24 mm deep) were conducted for particles passing the sieves with opening size of 2.36 mm. Meanwhile, particles passing the standard 20 mm sieves were tested using large direct shear test (300 mm by 300 mm by 200 mm deep). The large direct shear tests and the small direct shear tests carried out using the same shearing rate of 0.09 mm/min and similar normal stresses of 100, 200, and 300 kPa. The results show that the peak and residual shear strength decreases as particle size increases.

Keywords: particle size, shear strength, granular material, direct shear test

Procedia PDF Downloads 481

Authors: Clifford De Raffaele, Luana Bugeja, Serengul Smith

Abstract:

The adaptation of social networking sites within higher education has garnered significant interest in the recent years with numerous researches considering it as a possible shift from the traditional classroom based learning paradigm. Notwithstanding this increase in research and conducted studies however, the adaption of SNS based modules have failed to proliferate within Universities. This paper, commences its contribution by analyzing the various models and theories proposed in literature and amalgamates together various effective aspects for the inclusion of social technology within e-Learning. A three phased framework is further proposed which details the necessary considerations for the successful adaptation of SNS in enhancing the students learning experience. This proposal outlines the theoretical foundations which will be analyzed in practical implementation across international university campuses.

Keywords: eLearning, higher education, social network sites, student learning

Procedia PDF Downloads 335

Authors: Fazilet Alachaher (Benzerdjeb)

Abstract:

From the chalkboard to the abacus and beyond, technology has always played an important role in education. Educational technology refers to any teaching tool that helps supports learning, and given the rapid advancements in Information Technology and multimedia applications, the potential to support the teaching of foreign languages in our universities is ever greater. In language teaching and learning, we have a lot of to choose from the world of technology: TV, CDs, DVDs, Computers, the Internet, Email, and Blogs. The use of modern technologies can enrich the experience of learning a foreign language because they provide features that are not present in traditional technology. They can offer a wide range of multimedia resources, opportunities for intensive one-to-one learning in language labs and resources for authentic materials, which can be motivating to both students and teachers. The advent of Information and Communication Technology (ICT) and online interaction can also open up new range of self-access and distance learning opportunities The two last decades have witnessed a revolution due to the onset of technology, and has changed the dynamics of various industries, and has also influenced the way people live and work in society. That is why using the multimedia to create a certain context to teach English has its unique advantages. This paper tries then to analyse the necessity of multimedia technology to language teaching and brings out the problems faced by using these technologies. It also aims at making English teachers aware of the strategies to use it in an effective manner.

Keywords: strategies English teaching, multimedia technology, advantages, disadvantages, English learning

Procedia PDF Downloads 453