Search results for: learning strategy

Authors: Suman Dutta, Manish Agrawal, C. S. Jog

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Accurate computation of hydrodynamic forces on floating structures and their deformation finds application in the ocean and naval engineering and wave energy harvesting. This manuscript presents a monolithic, finite element strategy for fluid-structure interaction involving hyper-elastic solids partly submerged in an incompressible fluid. A velocity-based Arbitrary Lagrangian-Eulerian (ALE) formulation has been used for the fluid and a displacement-based Lagrangian approach has been used for the solid. The flexibility of the ALE technique permits us to treat the free surface of the fluid as a Lagrangian entity. At the interface, the continuity of displacement, velocity and traction are enforced using the mortar method. In the mortar method, the constraints are enforced in a weak sense using the Lagrange multiplier method. In the literature, the mortar method has been shown to be robust in solving various contact mechanics problems. The time-stepping strategy used in this work reduces to the generalized trapezoidal rule in the Eulerian setting. In the Lagrangian limit, in the absence of external load, the algorithm conserves the linear and angular momentum and the total energy of the system. The use of monolithic coupling with an energy-conserving time-stepping strategy gives an unconditionally stable algorithm and allows the user to take large time steps. All the governing equations and boundary conditions have been mapped to the reference configuration. The use of the exact tangent stiffness matrix ensures that the algorithm converges quadratically within each time step. The robustness and good performance of the proposed method are demonstrated by solving benchmark problems from the literature.

Keywords: ALE, floating body, fluid-structure interaction, monolithic, mortar method

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Authors: Igor Astrov, Natalya Berezovski

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This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for vectored thrust aerial vehicle (VTAV). With the SA strategy, we proposed a neural network motion control procedure to address the dynamics variation and performance requirement difference of flight trajectory for a VTAV. This control strategy with using of NARMA-L2 neurocontroller for chosen model of VTAV has been verified by simulation of take-off and forward maneuvers using software package Simulink and demonstrated good performance for fast stabilization of motors, consequently, fast SA with economy in energy can be asserted during search-and-rescue operations.

Keywords: NARMA-L2 neurocontroller, situational awareness, vectored thrust aerial vehicle, aviation

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Authors: Dahliz Abderrahmène, Lakhdari Wassim, Bouchikh Yamina, Hammi Hamida, Soud Adila, M’lik Randa, Benglia Sara

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Devastating insects constitute one of strains for cultivate tomato. Among this vandal insects, the tomato leafminer (T. absoluta), which has been introduced in Algeria constitute a challenge for both agricultures and scientists. Firstly, this insect is introduced without their natural enemies which may reduce their damage. Secondly, this species has developed insecticide resistance to many active matters. To contribute to establish a control strategy for T. absoluta we have mad an inventory for their enthomopathogenic fungi. Two fungi were identified among others taken from adults and pupae. These fungi are Aspergillus flavus and Metarhizium sp. A study was conducted in laboratory to recognize the efficiency of these antagonists. These species had unregistered a mortality mounts of 42% and 56% respectively.

Keywords: Tuta absoluta, enthomopathogenic fungi, Aspergillus flavus, Metarhizium sp, control strategy

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Authors: Yingling Chen

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Most current research has been focused on whether NESTs have advantages over NNESTs in English language Teaching. The purpose of this study was to investigate English learners’ preferences toward native English speaking teachers and non-English speaking teachers in four skills of English language learning. This qualitative study consists of 12 participants. Two open-ended questions were investigated and analyzed. The findings revealed that the participants held an overall preference for NESTs over NNESTs in reading, writing, and listening English skills; nevertheless, they believed both NESTs and NNESTs offered learning experiences strengths, and weaknesses to satisfy students’ need in their English instruction.

Keywords: EFL, instruction, Student Rating of Instructions (SRI), perception

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Authors: Evgeniia Surkova, Manal Assaad, Hleb Makeyeu, Juho Makio

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The main objective of STIMEY (Science, Technology, Innovation, Mathematics, Engineering for the Young) project is the delivery of a hybrid learning environment that combines multi-level components such as social media concepts, robotic artefacts, and radio, among others. It is based on a well-researched pedagogical framework to attract European youths to STEM (science, technology, engineering, and mathematics) education and careers. To develop and integrate these various components, STIMEY is executed in iterative research cycles leading to progressive improvements. Scrum was the development methodology of choice in the project, as studies indicated its benefits as an agile methodology in global software development, especially of e-learning and integrated learning projects. This paper describes the project partners’ experience with the Scrum framework, discussing the challenges faced in its implementation and the mitigation practices employed. The authors conclude with exploring user experience tools and principles for future research, as a novel direction in supporting the Scrum development team.

Keywords: e-learning, global software development, scrum, STEM education

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Authors: Aparna Datey

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This paper explores the theoretical frameworks underpinning professional learning, professional development, and academic identity. The focus is on sessional teachers (also called tutors or adjuncts) in architectural design studios, who may be practitioners, masters or doctoral students and academics hired ‘as needed’. Drawing from Schön’s work on reflective practice, learning and developmental theories of Vygotsky (social constructionism and zones of proximal development), informal and workplace learning, this research proposes that sessional teachers not only develop their teaching skills but also shape their identities through their 'everyday' work. Continuing academic staff develop their teaching through a combination of active teaching, self-reflection on teaching, as well as learning to teach from others via formalised programs and informally in the workplace. They are provided professional development and recognised for their teaching efforts through promotion, student citations, and awards for teaching excellence. The teaching experiences of sessional staff, by comparison, may be discontinuous and they generally have fewer opportunities and incentives for teaching development. In the absence of access to formalised programs, sessional teachers develop their teaching informally in workplace settings that may be supportive or unhelpful. Their learning as teachers is embedded in everyday practice applying problem-solving skills in ambiguous and uncertain settings. Depending on their level of expertise, they understand how to teach a subject such that students are stimulated to learn. Adult learning theories posit that adults have different motivations for learning and fall into a matrix of readiness, that an adult’s ability to make sense of their learning is shaped by their values, expectations, beliefs, feelings, attitudes, and judgements, and they are self-directed. The level of expertise of sessional teachers depends on their individual attributes and motivations, as well as on their work environment, the good practices they acquire and enhance through their practice, career training and development, the clarity of their role in the delivery of teaching, and other factors. The architectural design studio is ideal for study due to the historical persistence of the vocational learning or apprenticeship model (learning under the guidance of experts) and a pedagogical format using two key approaches: project-based problem solving and collaborative learning. Hence, investigating the theoretical frameworks underlying academic roles and informal professional learning in the workplace would deepen understanding of their professional development and how they shape their academic identities. This qualitative research is ongoing at a major university in Australia, but the growing trend towards hiring sessional staff to teach core courses in many disciplines is a global one. This research will contribute to including transient sessional teachers in the discourse on institutional quality, effectiveness, and student learning.

Keywords: academic identity, architectural design learning, pedagogy, teaching and learning, sessional teachers

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Authors: Shamatha Shetty, Sakshi Dhabadi, Prerana M., Indushree B.

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About 66% of firms claim that insider attacks are more likely to happen. The frequency of insider incidents has increased by 47% in the last two years. The goal of this work is to prevent dangerous employee behavior by using keyloggers and the Machine Learning (ML) model. Every keystroke that the user enters is recorded by the keylogging program, also known as keystroke logging. Keyloggers are used to stop improper use of the system. This enables us to collect all textual data, save it in a CSV file, and analyze it using an ML algorithm and the VirusTotal API. Many large companies use it to methodically monitor how their employees use computers, the internet, and email. We are utilizing the SVM algorithm and the VirusTotal API to improve overall efficiency and accuracy in identifying specific patterns and words to automate and offer the report for improved monitoring.

Keywords: cyber security, machine learning, cyclic process, email notification

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Authors: Elham Fariborzi, Hoda Anvari Kazemabad

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Today, ICT plays an important role in all matters and it affects the development of creative cities. According to virtual space in this technology, it use especially for expand terms like smart schools, Virtual University, web-based training and virtual classrooms that is in parallel with the traditional teaching. Nowadays, the educational systems in different countries such as Iran are changing and start increasing creativity in the learning environment. It will contribute to the development of innovative ideas and thinking of the people in this environment; such opportunities might be cause scientific discovery and development issues. The creativity means the ability to generate ideas and numerous, new and suitable solutions for solving the problems of real and virtual individuals and society, which can play a significant role in the development of creative current physical cities or virtual borders ones in the future. The purpose of this paper is to study strategies to increase creativity in a virtual learning to develop a creative city. In this paper, citation/ library study was used. The full description given in the text, including how to create and enhance learning creativity in a virtual classroom by reflecting on performance and progress; attention to self-directed learning guidelines, efficient use of social networks, systematic discussion groups and non-intuitive targeted controls them by involved factors and it may be effective in the teaching process regarding to creativity. Meanwhile, creating a virtual classroom the style of class recognizes formally the creativity. Also the use of a common model of creative thinking between student/teacher is effective to solve problems of virtual classroom. It is recommended to virtual education’ authorities in Iran to have a special review to the virtual curriculum for increasing creativity in educational content and such classes to be witnesses more creative in Iran's cities.

Keywords: virtual learning, creativity, e-learning, bioinformatics, biomedicine

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Authors: Vinai K. Singh

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In Neural Network-based Learning techniques, there are several models of Convolutional Networks. Whenever the methods are deployed with large datasets, only then can their applicability and appropriateness be determined. Clinical and pathological pictures of lobular carcinoma are thought to exhibit a large number of random formations and textures. Working with such pictures is a difficult problem in machine learning. Focusing on wet laboratories and following the outcomes, numerous studies have been published with fresh commentaries in the investigation. In this research, we provide a framework that can operate effectively on raw photos of various resolutions while easing the issues caused by the existence of patterns and texturing. The suggested approach produces very good findings that may be used to make decisions in the diagnosis of cancer.

Keywords: lobular carcinoma, convolutional neural networks (CNN), deep learning, histopathological imagery scans

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Authors: Tuğçe Yücel

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A Wireless Sensor Network(WSN) is a collection of sensor nodes which are deployed randomly in an area for surveillance. Efficient utilization of limited battery energy of sensors for increased network lifetime as well as data security are major design objectives for WSN. Moreover secure transmission of data sensed to a base station for further processing. Producing multiple copies of data packets and sending them on different paths is one of the strategies for this purpose, which leads to redundant energy consumption and hence reduced network lifetime. In this work we develop a restricted multi-copy multipath strategy where data move through ‘frequently’ or ‘heavily’ used sensors is copied by the sensor incident to such central nodes and sent on node-disjoint paths. We develop a mixed integer programing(MIP) model and heuristic approach present some preleminary test results.

Keywords: MIP, sensor, telecommunications, WSN

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Authors: Shan Jiang, Xinyu Tang

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Game-based learning is an emerging pedagogy to make the learning experience more effective, enjoyable, and fun. However, most games used in classroom settings have been overly simplistic. This paper presents a case study on a Python-based online game designed to improve the effectiveness in both teaching and research in higher education. The proposed game system not only creates a fun and enjoyable experience for students to learn various topics in programming but also improves the effectiveness of teaching in several aspects, including material presentation, helping students to recognize the importance of the subjects, and linking theoretical concepts to practice. The proposed game system also serves as an information cyber-infrastructure that automatically collects and stores data from players. The data could be useful in research areas including human-computer interaction, decision making, opinion mining, and artificial intelligence. They further provide other possibilities beyond these areas due to the customizable nature of the game.

Keywords: game-based learning, programming, research-teaching integration, Hearthstone

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Authors: Zhiyuan Du, Baisravan Hom Chaudhuri, Pierluigi Pisu

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In connected vehicle systems where wireless communication is available among the involved vehicles and intersection controllers, it is possible to design an intersection coordination strategy that leads the connected and automated vehicles (CAVs) travel through the road intersections without the conventional traffic light control. In this paper, we present a distributed coordination strategy for the CAVs at multiple interconnected intersections that aims at improving system fuel efficiency and system mobility. We present a distributed control solution where in the higher level, the intersection controllers calculate the road desired average velocity and optimally assign reference velocities of each vehicle. In the lower level, every vehicle is considered to use model predictive control (MPC) to track their reference velocity obtained from the higher level controller. The proposed method has been implemented on a simulation-based case with two-interconnected intersection network. Additionally, the effects of mixed vehicle types on the coordination strategy has been explored. Simulation results indicate the improvement on vehicle fuel efficiency and traffic mobility of the proposed method.

Keywords: connected vehicles, automated vehicles, intersection coordination systems, multiple interconnected intersections, model predictive control

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Authors: Noran Adel Emara, Elham Ghazi Mohammad

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Qatar University is engaged in a systemic education reform that includes integrating the latest and most effective technologies for teaching and learning. ICube is high-immersive virtual reality technology is used to teach educational scenarios that are difficult to teach in real situations. The trends toward delivering science education via virtual reality applications have accelerated in recent years. However, research on students perceptions of integrating virtual reality especially ICube technology is somehow limited. Students often have difficulties focusing attention on learning science topics that require imagination and easily lose attention and interest during the lesson. The aim of this study was to examine students’ perception of integrating ICube technology in the solar system lesson. Moreover, to explore how ICube could engage students in learning scientific concept of the solar system. The research framework included the following quantitative research design with data collection and analysis from questionnaire results. The solar system lesson was conducted by teacher candidates (Diploma students) who taught in the ICube virtual lab in Qatar University. A group of 30 students from eighth grade were randomly selected to participate in the study. Results showed that the students were extremely engaged in learning the solar system and responded positively to integrating ICube in teaching. Moreover, the students showed interest in learning more lessons through ICube as it provided them with valuable learning experience about complex situations.

Keywords: ICube, integrating technology, science education, virtual reality

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Authors: Lavanya Madhuri Bollipo, K. V. Kadambari

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Objective: To discuss key issues in the diagnosis of Parkinson disease (PD), To discuss features influencing PD progression, To discuss importance of brain SPECT data in PD diagnosis, and To discuss the essentiality of machine learning techniques in early diagnosis of PD. An accurate and early diagnosis of PD is nowadays a challenge as clinical symptoms in PD arise only when there is more than 60% loss of dopaminergic neurons. So far there are no laboratory tests for the diagnosis of PD, causing a high rate of misdiagnosis especially when the disease is in the early stages. Recent neuroimaging studies with brain SPECT using 123I-Ioflupane (DaTSCAN) as radiotracer shown to be widely used to assist the diagnosis of PD even in its early stages. Machine learning techniques can be used in combination with image analysis procedures to develop computer-aided diagnosis (CAD) systems for PD. This paper addressed recent studies involving diagnosis of PD in its early stages using brain SPECT data with Machine Learning Techniques.

Keywords: Parkinson disease (PD), dopamine transporter, single-photon emission computed tomography (SPECT), support vector machine (SVM)

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Authors: Jorge Sandoval Lezama, Arturo Ivan Sandoval Rodriguez, Jose Arturo Correa Arredondo

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This work aims to share innovative educational experiences at IPN Mexico, that involve collaborative learning at institutional and global level through course competition and global collaboration projects. Students from universities in China, USA, South Korea, Canada and Mexico collaborate to design electric vehicles to solve global urban mobility problems. The participation of IPN students in the 2015-2016 global competition (São Paolo, Brazil and Cincinnati, USA) Reconfigurable Shared-Use Mobility Systems allowed to apply pedagogical strategies of groups of collaboration and of learning based on projects where they shared activities, commitments and goals, demonstrating that students were motivated to develop / self-generate their knowledge with greater meaning and understanding. One of the most evident achievements is that the students are self-managed, so the most advanced students train the students who join the project with CAD, CAE, CAM tools. Likewise, the motivation achieved is evident since in 2014 there were 12 students involved in the project, and there are currently more than 70 students.

Keywords: collaboration projects, global competency, course competition, active learning

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Authors: Budiman Budiman

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This research aimed at describing and testing whether the students’ ability in writing analytical exposition text is increased by using comic strips at SMAN 12 Pekanbaru. The respondents of this study were the second-grade students, especially XI Science 3 academic year 2011-2012. The total number of students in this class was forty-two (42) students. The quantitative and qualitative data was collected by using writing test and observation sheets. The research finding reveals that there is a significant increase of students’ writing ability in writing analytical exposition text through comic strips. It can be proved by the average score of pre-test was 43.7 and the average score of post-test was 65.37. Besides, the students’ interest and motivation in learning are also improved. These can be seen from the increasing of students’ awareness and activeness in learning process based on observation sheets. The findings draw attention to the use of comic strips in teaching and learning is beneficial for better learning outcome.

Keywords: analytical exposition, comic strips, secondary school students, writing ability

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Authors: Chi H. Lin, Chi C. Lin, Chih L. Hsieh

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Motor Imagery (MI) alone or combined with action observation (AO) has been shown to enhance motor performance and skill learning. The most effective way to combine these techniques has received limited scientific scrutiny. In the present study, we examined the effects of simultaneous (i.e., observing an action whilst imagining carrying out the action concurrently), alternate (i.e., observing an action and then doing imagery related to that action consecutively) and synthesis (alternately perform action observation and imagery action and then perform observation and imagery action simultaneously) AOMI combinations on improving golf putting performance and learning. Participants, 45 university students who had no formal experience of using imagery for the study, were randomly allocated to one of four training groups: simultaneous action observation and motor imagery (S-AOMI), alternate action observation and motor imagery (A-AOMI), synthesis action observation and motor imagery (A-S-AOMI), and a control group. And it was applied 'Different Experimental Groups with Pre and Post Measured' designs. Participants underwent eighteen times of different interventions, which were happened three times a week and lasting for six weeks. We analyzed the information we received based on two-factor (group × times) mixed between and within analysis of variance to discuss the real effects on participants' golf putting performance and learning about different intervention methods of different types of combined action observation and motor imagery. After the intervention, we then used imagery questionnaire and journey to understand the condition and suggestion about different motor imagery and action observation intervention from the participants. The results revealed that the three experimental groups both are effective in putting performance and learning but not for the control group, and the A-S-AOMI group is significantly better effect than S-AOMI group on golf putting performance and learning. The results confirmed the effect of motor imagery combined with action observation on the performance and learning of golf putting. In particular, in the groups of synthesis, motor imagery, or action observation were alternately performed first and then performed motor imagery, and action observation simultaneously would have the best effectiveness.

Keywords: motor skill learning, motor imagery, action observation, simulation

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Authors: James P. Takona

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In a world that is experiencing sharp digital transformations guided by digital technologies, the potential of technology to drive transformation and evolution in the higher is apparent. Higher education is facing a paradigm shift that exposes susceptibilities and threats to fully online programs in the face of post-Covid-19 trends of commodification. This historical moment is likely to be remembered as a critical turning point from analog to digital degree-focused learning modalities, where the default became the pivot point of competition between higher education institutions. Fall 2020 marks a significant inflection point in higher education as students, educators, and government leaders scrutinize higher education's price and value propositions through the new lens of traditional lecture halls versus multiple digitized delivery modes. Online education has since tiled the way for a pedagogical shift in how teachers teach and students learn. The incremental growth of online education in the west can now be attributed to the increasing patronage among students, faculty, and institution administrators. More often than not, college instructors assume paraclete roles in this learning mode, while students become active collaborators and no longer passive learners. This paper offers valuable discernments into the threats, challenges, and opportunities of a massive digital revolution in servicing degree programs. To view digital instruction and learning demands for instructional practices that revolve around collaborative work, engaging students in learning activities, and an engagement that promotes active efforts to solicit strong connections between course activities and expected learning pace for all students. Appropriate digital technologies demand instructors and students need prior solid skills. Need for the use of digital technology to support instruction and learning, intelligent tutoring offers great promise, and failures at implementing digital learning may not improve outcomes for specific student populations. Digital learning benefits students differently depending on their circumstances and background and those of the institution and/or program. Students have alternative options, access to the convenience of learning anytime and anywhere, and the possibility of acquiring and developing new skills leading to lifelong learning.

Keywords: digi̇tized learning, digital education, collaborative work, high education, online education, digitize delivery

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Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

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Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: cycle consistency, deformable multimodal image registration, deep learning, GAN

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Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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Authors: Sun Lim, Kyun Jung

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In this paper, we describe the control strategy of high speed parallel robot system with EtherCAT network. This work deals the parallel robot system with centralized control on the real-time operating system such as window TwinCAT3. Most control scheme and algorithm is implemented master platform on the PC, the input and output interface is ported on the slave side. The data is transferred by maximum 20usecond with 1000byte. EtherCAT is very high speed and stable industrial network. The control strategy with EtherCAT is very useful and robust on Ethernet network environment. The developed parallel robot is controlled pre-design nonlinear controller for 6G/0.43 cycle time of pick and place motion tracking. The experiment shows the good design and validation of the controller.

Keywords: parallel robot control, etherCAT, nonlinear control, parallel robot inverse kinematic

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Authors: Dalila Souilem, Salma Boumiza, Abdelkarim Abdelkader

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The Clarifier Dialogue Interface (CDI) is a part of an online teaching system based on human-machine communication in learning situation. This interface used in the system during the learning action specifically in the evaluation step, to clarify ambiguities in the learner's response. The CDI can generate patterns allowing access to an information system, using the selectors associated with lexical units. To instantiate these patterns, the user request (especially learner’s response), must be analyzed and interpreted to deduce the canonical form, the semantic form and the subject of the sentence. For the efficiency of this interface at the interpretation level, a set of substitution operators is carried out in order to extend the possibilities of manipulation with a natural language. A second approach that will be presented in this paper focuses on the object languages with new prospects such as combination of natural language with techniques of handling information system in the area of online education. So all operators, the CDI and other interfaces associated to the domain expertise and teaching strategies will be unified using FRAME representation form.

Keywords: dialogue, e-learning, FRAME, information system, natural language

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Authors: Javad Abdi, Azam Famil Khalili

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Modeling emotions have attracted much attention in recent years, both in cognitive psychology and design of artificial systems. However, it is a negative factor in decision-making; emotions have shown to be a strong faculty for making fast satisfying decisions. In this paper, we have adapted a computational model based on the limbic system in the mammalian brain for control engineering applications. Learning in this model based on Temporal Difference (TD) Learning, we applied the proposed controller (termed BELBIC) for a simple model of a submarine. The model was supposed to reach the desired depth underwater. Our results demonstrate excellent control action, disturbance handling, and system parameter robustness for TDBELBIC. The proposal method, regarding the present conditions, the system action in the part and the controlling aims, can control the system in a way that these objectives are attained in the least amount of time and the best way.

Keywords: artificial neural networks, temporal difference, brain emotional learning based intelligent controller, heating- ventilating and air conditioning

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Authors: Maria Ahmad, Michael Page, Danë Goodsman

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‘Educational’ debriefing – a construct distinct from clinical debriefing – is used following simulated scenarios and is central to learning and development in fields ranging from aviation to emergency medicine. However, little research into educational debriefing in prehospital medicine exists. This qualitative study explored the facilitation and effects of prehospital educational debriefing and identified obstacles to debriefing, using the London’s Air Ambulance Pre-Hospital Care Course (PHCC) as a model. Method: Ethnographic observations of moulages and debriefs were conducted over two consecutive days of the PHCC in October 2019. Detailed contemporaneous field notes were made and analysed thematically. Subsequently, seven one-to-one, semi-structured interviews were conducted with four PHCC debrief facilitators and three course participants to explore their experiences of prehospital educational debriefing. Interview data were manually transcribed and analysed thematically. Results: Four overarching themes were identified: the approach to the facilitation of debriefs, effects of debriefing, facilitator development, and obstacles to debriefing. The unpredictable debriefing environment was seen as both hindering and paradoxically benefitting educational debriefing. Despite using varied debriefing structures, facilitators emphasised similar key debriefing components, including exploring participants’ reasoning and sharing experiences to improve learning and prevent future errors. Debriefing was associated with three principal effects: releasing emotion; learning and improving, particularly participant compound learning as they progressed through scenarios; and the application of learning to clinical practice. Facilitator training and feedback were central to facilitator learning and development. Several obstacles to debriefing were identified, including mismatch of participant and facilitator agendas, performance pressure, and time. Interestingly, when used appropriately in the educational environment, these obstacles may paradoxically enhance learning. Conclusions: Educational debriefing in prehospital medicine is complex. It requires the establishment of a safe learning environment, an understanding of participant agendas, and facilitator experience to maximise participant learning. Aspects unique to prehospital educational debriefing were identified, notably the unpredictable debriefing environment, interdisciplinary working, and the paradoxical benefit of educational obstacles for learning. This research also highlights aspects of educational debriefing not extensively detailed in the literature, such as compound participant learning, display of ‘professional honesty’ by facilitators, and facilitator learning, which require further exploration. Future research should also explore educational debriefing in other prehospital services.

Keywords: debriefing, prehospital medicine, prehospital medical education, pre-hospital care course

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Authors: E. Lam, Z. D. Yang, B. Li, I. Ho, T. Wong, V. Wong

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This paper reports some of the recent studies on strengthening of reinforced concrete members by ferrocement. Using mortar in ferrocement with high tensile strength, tensile properties of (high performance) ferrocement can be enhanced. In the proposed strengthening strategy, defective concrete cover of structural members is replaced by ferrocement so as to increase the load carrying capacity. This has been successfully applied to strengthen columns and beam-column joints. To facilitate the ease of application of the proposed strengthening strategy, mortar in ferrocement is applied through dry spray shotcrete.

Keywords: ferrocement, high performance ferrocement, dry, spray shotcrete, column, beam-column joint, strengthening

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Authors: Luigi Pintacuda

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What characterize the phenomenology of Bucharest is that all operations of modernization have never been completed, creating a city made up of fragments. Understood this fragmented nature, the traces and fractures, the acceptance of their scars must represent the basis for the design of development for Bucharest. From this insight comes a new analysis of this city: a city of two million inhabitants that does not need a project on an urban scale (as all other major projects for the city have failed), but, starting from the study of all these interstitial spaces of public property, it must find its own strategy, a strategy on a large-scale that reflects on the sites on an architectural one. It is a city composed by fragments, not waste, but places for the project: ‘waiting spaces’ for a possible continuation of the process of genesis of a city which is often incomplete.

Keywords: public spaces, traces fractures, urban design, urban development

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Authors: C. K. Peter Chuah

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Essentially, the intention of reflective journal is meant for students to develop higher-order thinking skills and to provide a 'space' to make their learning experience and thinking, making and feeling visible, i.e., it provides students an opportunity to evaluate their learning critically by focusing on the rationale behind their thinking, making and feeling. In addition, reflective journal also gets the students to focus on how could things be done differently—the possibility, alternative point of views, and opportunities for change. It is hoped that by getting communication design students to reflect at various intervals, they could move away from mere working on the design project and pay more attention to what they thought they have learned in relation to the development of their design ability. Unfortunately, a closer examination—through content analysis—of the learning journals submitted by a group of design students revealed that most of the reflections were descriptive and tended to be a summary of what occurred in the learning experience. While many students were able to describe what they did, very few were able to explain how they were able to do something critically. It can be concluded that to get design students to reflect is a fairly easy task, but to get them to reflect critically could be very challenging. To ensure that design students could benefit from the use of reflective journal as a tool to develop their critical thinking skills, a more systematic and structured approach to the introduction of critical thinking and reflective journal should be built into the design curriculum to provide as much practice and sufficient feedback as other studio subjects.

Keywords: communication design education, critical thinking, reflection, reflective journal

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Authors: Murtala Sale

Abstract:

The use of instructional materials is an indispensable tool that enhances qualitative teaching and learning especially at the primary level. Instructional materials are used to facilitate comprehension of ideas in the learners as well as ensure long term retention of ideas and topics taught to pupils. This study examined the relevance of using instructional materials in primary schools in Katsina State, Nigeria. It employed survey design using cluster sampling technique. The questionnaire was used to gather data for analysis, and statistical and frequency tables were used to analyze the data gathered. The results show that teachers and students alike have realized the effectiveness of modern instructional materials in teaching and learning for the attainment of set objectives in the basic primary education policy. It also discovered that reluctance in the use of instructional materials will hamper the achievement of qualitative primary education. The study therefore suggests that there should be the provision of adequate and up-to-date instructional materials to all primary schools in Katsina State for effective teaching and learning process.

Keywords: instructional materials, effective teaching, learning quality, indispensable aspect

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Authors: Sean Paulsen, Michael Casey

Abstract:

In this work we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training

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Authors: Jordan Shuler

Abstract:

The goal of this study is to determine whether real-time language translation benefits ESL learners by contributing to overall equity in the classroom. Equity will be measured quantitatively through assessment performance and qualitatively through student survey. Two separate sections of students studying the same course will receive identical curriculum: one group, the control, will be taught in English and the other group in English with real-time translation into the students' first languages. The professor will use Microsoft Translator during lectures, in-class discussions, and Q&A time. The college is committed to finding new ways of teaching and learning, as outlined in Strategy 2022. If this research finds a positive relationship between language translation and student academic success, the technology will surely be encouraged for adoption by all George Brown College faculty. With greater acceptance, this technology could influence equity and pedagogy in the larger educational community.

Keywords: ESL learners, equity, innovative teaching strategies, language translation

Procedia PDF Downloads 109