Search results for: learning design

Authors: HyunSu Seo, HoYoung Son, Sungjin Kim, WooYoung Jung

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In order to understand the seismic behavior of steel frame structure with infill FRP composite panel, simple models for simulation on the steel frame with the panel systems were developed in this study. To achieve the simple design method of the steel framed structure with the damping panel system, 2-D finite element analysis with the springs and dashpots models was conducted in ABAQUS. Under various applied spring stiffness and dashpot coefficient, the expected hysteretic energy responses of the steel frame with damping panel systems we re investigated. Using the proposed simple design method which decides the stiffness and the damping, it is possible to decide the FRP and damping materials on a steel frame system.

Keywords: numerical analysis, FEM, infill, GFRP, damping

Procedia PDF Downloads 405

Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

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Authors: Izharul Haq

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Every one of us seek to aspire to gain quality education. The biggest stake holders are students who labor through years acquiring knowledge and skill to help them prepare for their career. Parents spend a fortune on their children’s education. Companies spend billions of dollars to enhance standards by developing new education products and services. Quality education is the golden key to a long lasting prosperity for the individual and the nation. But unfortunately, education standards are continuously deteriorating and it has become a global phenomenon. Unfortunately, teaching is often described as a ‘popularity contest’ and those teachers who are usually popular with students are often those who compromise teaching to appease students. Such teachers also ‘teach-to-the-test’ ensuring high test scores. Such teachers, hence, receive good student rating. Teachers who are conscientious, rigorous and thorough are often the victims of good appraisal. Government and private organizations are spending billions of dollars trying to capture the characteristics of a good teacher. But the results are still vague and inconclusive. At present there is no objective way to measure teaching effectiveness. In this paper we present an innovative method to objectively measure teaching effectiveness using a new teaching tool (TSquare). The TSquare tool used in the study is practical, easy to use, cost effective and requires no special equipment to implement. Hence it has a global appeal for poor and the rich countries alike.

Keywords: measuring teaching effectiveness, quality in education, student learning, teaching styles

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Authors: Dijana Sulejmanović

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Cognitive-behavioral modification (CBM) is a combination of cognitive and behavioral learning principles to shape and encourage the desired behaviors. A crucial element of cognitive-behavioral modification is that a change the behavior precedes awareness of how it affects others. CBM is oriented toward changing inner speech and learning to control behaviors through self-regulation techniques. It aims to teach individuals how to develop the ability to recognize, monitor and modify their thoughts, feelings, and behaviors. The review of literature emphasizes the efficiency the CBM approach in the treatment of children's hyperactivity and negative emotions such as anger. The results of earlier research show how impulsive and hyperactive behavior, agitation, and aggression may slow down and block the child from being able to actively monitor and participate in regular classes, resulting in the disruption of the classroom and the teaching process, and the children may feel rejected, isolated and develop long-term poor image of themselves and others. In this article, we will provide how the use of CBM, adapted to child's age, can incorporate measures of cognitive and emotional functioning which can help us to better understand the children’s cognitive processes, their cognitive strengths, and weaknesses, and to identify factors that may influence their behavioral and emotional regulation. Such a comprehensive evaluation can also help identify cognitive and emotional risk factors associated with aggressive behavior, specifically the processes involved in modulating and regulating cognition and emotions.

Keywords: aggressive behavior, cognitive behavioral modification, cognitive behavioral theory, modification

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Authors: Jarwa Prasetya Sih Handoko

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The issue of energy crisis for big cities in Indonesia are issues raised in line with the development of the city is rapidly increasing. Various attempts were made by the government in overcoming problems of energy needs in Indonesia. In addition to the efforts of the government required the efforts made by the public to solve this problem. The concept of green building in the design of the building with efforts to use energy efficiently can be one of the efforts that can be applied to solve this problem. Jakarta is capital and the one of the major cities in Indonesia with high economic growth. This leads to increased demand for office space for the people. So that the construction of office buildings in big cities like Jakarta very numerous. Office building is one of the buildings that require large energy consumption. As a building that could potentially require huge amounts of energy, the design should consider the use of energy to help provide solutions to problems of energy crisis in Indonesia. The concept of energy efficient is one of the concepts addressed in an effort to use energy in buildings to save energy needs of the building operations. Therefore, it is necessary to have a study that explores the application of the concept of energy efficiency and conservation in office buildings in Jakarta. In this study using two (2) buildings case study that Sequis Center Building and Sampoerna Strategic Square. Both are office buildings in Jakarta have earned the Green Building Certificate of Green Building Council Indonesia (GBCI). The study used literature review methods to address issues raised earlier. Whether it's related to a literature review on the study of office buildings and green building. With this paper is expected to be obtained on the application of the concept of energy efficiency and conservation in office buildings that have earned recognition as a green building by GBCI. The result could be a reference to the architect in designing the next office buildings, especially related to the concept of energy use in buildings. From this study, it can be concluded that the concept of energy efficiency and conservation in the design of office buildings can be applied to its orientation, the openings, the use shade in buildings, vegetation and building material selection and efficient use of water. So that it can reduce energy requirements needed to meet the needs of the building user activity. So the concept of energy efficiency and conservation in office buildings can be one of the efforts to realize the Green Office Building. Recommendations from this study is that the design of office buildings should be able to apply the concept of energy utilization in the design office. This is to meet the energy needs of the office buildings in an effort to realize the Green Building.

Keywords: energy crisis, energy efficiency, energy conservation, green building, office building

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Authors: Eugene Mashapa

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The age of information has witnessed countless unprecedented technological developments, which signal the articulation of succinct technological capabilities that can match these cutting-edge technological trends. These changes have impacted patterns in the production, distribution, and consumption of media content, a space that the Film and Publication Board (FPB) is concerned with. Consequently, the FPB is keen to understand the nature and impact of these technological changes on media content regulation. This exploratory study sought to investigate how content regulators in high and middle-income economies have adapted to the changes in this space, seeking insights into innovations, technological and operational, that facilitate continued relevance during this fast-changing environment. The study is aimed at developing recommendations that could assist and inform the organisation in regulating media content as it evolves. Thus, the overall research strategy in this analysis is applied research, and the analytical model adopted is a mixed research design guided by both qualitative and quantitative research instruments. It was revealed in the study that the FPB was significantly impacted by the unprecedented technological advancements in the media regulation space. Additionally, there exists a need for the FPB to understand the current and future penetrations of 4IR technology in the industry and its impact on media governance and policy implementation. This will range from reskilling officials to align with the technological skills to developing technological innovations as well as adopting co-regulatory or self-regulatory arrangements together with content distributors, where more content is distributed in higher volumes and with increased frequency. Importantly, initiating an interactive learning process for both FPB employees and the general public can assist the regulator and improve FPB’s operational efficiency and effectiveness.

Keywords: media, regulation, technology, film and publications board

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Authors: Laura Mendez

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Tribunals for the prosecution of crimes against humanity have been implemented in recent history via international intervention or imposed by one side of the conflict, as in the cases of Rwanda, Iraq, Argentina, and Chile. However, the creation of a criminal tribunal as the result of a peace agreement between formerly warring parties has been unique to the Colombian peace process. As such, the Colombian Jurisdiction for Peace (SJP), or JEP for its Spanish acronym, is viewed as a site of social contestation where actors shape its design and implementation. This study contributes to the literature of transitional justice by analyzing how the framing of the creation of the Colombian tribunal reveals the parties' interests. The analysis frames the interests of the power-brokers, i.e., the government and the Revolutionary Armed Forces of Colombia (FARC), and the victims in light of the tribunal’s functions. The purpose of this analysis is to understand how the interests of the parties are embedded in the designing of the SJP. This paper argues that the creation of the SJP rests on restorative justice, for which the victim, not the perpetrator, is at the center of prosecution. The SJP’s approach to justice moves from prosecution as punishment to prosecution as sanctions. SJP’s alternative sanctions focused on truth, reparation, and restoration are designed to humanize both the victim and the perpetrator in order to achieve reconciliation. The findings also show that requiring the perpetrator to perform labor to repair the victim as an alternative form of sanction aims to foster relations of reintegration and social learning between victims and perpetrators.

Keywords: transitional justice mechanisms, criminal tribunals, Colombia, Colombian Jurisdiction for Peace, JEP

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Authors: Abdulkabir Abdullahi

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Nigeria has not yet welcomed phonics into its primary schools. In government-owned primary schools teachers are functionally ignorant of the stories of the reading wars amongst international scholars. There are few or no Nigerian-authored phonics textbooks, and there has been no government-owned phonics curriculum either. There are few or no academic journal articles on phonics in the country and there is, in fact, a certain danger of confusion between phonics and phonetics among Nigerian publishers, authors, writers and academics as if Nigerian teachers of English and the educational policy makers of the country were unaware of reading failures/problems amongst Nigerian children, or had never heard of phonics or read of the stories of the reading wars or the annual phonics test in the United Kingdom, the United States of America and other parts of the world. It is on this note that this article reviews and examines, in the style of a qualitative inquiry, the body of arguments on phonics, and explores the effectiveness of phonics teaching, particularly, in a second-language learning contexts. While the merit of the paper is, perhaps, situated in its supreme effort to draw global attention to reading failures/problems in Nigeria and the ways the situation may affect English language learning, international academic relations and the educational future of the country, it leaves any quantitative verification of its claims to interested quantitative researchers in the world.

Keywords: graphemes, phonics, reading, reading wars, reading theories, phonemic awareness

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Authors: Galal Elkobrosy, Amr M. Abdelrazek, Bassuny M. Elsouhily, Mohamed E. Khidr

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Crank shaft length, connecting rod length, crank angle, engine rpm, cylinder bore, mass of piston and compression ratio are the inputs that can control the performance of the slider crank mechanism and then its efficiency. Several combinations of these seven inputs are used and compared. The throughput engine torque predicted by the simulation is analyzed through two different regression models, with and without interaction terms, developed according to multi-linear regression using LU decomposition to solve system of algebraic equations. These models are validated. A regression model in seven inputs including their interaction terms lowered the polynomial degree from 3^rd degree to 1^st degree and suggested valid predictions and stable explanations.

Keywords: design of experiments, regression analysis, SI engine, statistical modeling

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Authors: Chahad P. Alexandre

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PIBID-Institutional Program of Scholarships to Encourage Teaching - is a Brazilian government program that counts today with 48.000 students. It's goal is to motivate the students to stay in the teaching undergraduate programs and to help fill the gap of 100.000 teachers that are needed today in the under graduated schools. The major lack of teachers today is in physics, chemistry, mathematics, and biology. At IFSP-Itapetininga we formatted our physics PIBID based on practical activities. Our students are divided in two São Paulo state government high schools in the same city. The project proposes class activities based on experimentation, observation and understanding of physical phenomena. The didactical experiments are always in relation with the content that the teacher is working, he is the supervisor of the program in the school. Always before an experiment is proposed a little questionnaire to learn about the students preconceptions and one is filled latter to evaluate if now concepts have been created. This procedure is made in order to compare their previous knowledge and how it changed after the experiment is developed. The primary goal of our project is to make the Physics class more attractive to the students and to develop in high school students the interest in learning physics and to show the relation of Physics to the day by day and to the technological world. The objective of the experimental activities is to facilitate the understanding of the concepts that are worked on classes because under experimentation the PIBID scholarship student stimulate the curiosity of the high school student and with this he can develop the capacity to understand and identify the physical phenomena with concrete examples. Knowing how to identify this phenomena and where they are present at the high school student life makes the learning process more significant and pleasant. This proposal make achievable to the students to practice science, to appropriate of complex, in the traditional classes, concepts and overcoming the common preconception that physics is something distant and that is present only on books. This preconception is extremely harmful in the process of scientific knowledge construction. This kind of learning – through experimentation – make the students not only accumulate knowledge but also appropriate it, also to appropriate experimental procedures and even the space that is provided by the school. The PIBID scholarship students, as future teachers also have the opportunity to try experimentation classes, to intervene in the classes and to have contact with their future career. This opportunity allows the students to make important reflection about the practices realized and consequently about the learning methods. Due to this project, we found out that the high school students stay more time focused in the experiment compared to the traditional explanation teachers´ class. As a result in a class, as a participative activity, the students got more involved and participative. We also found out that the physics under graduated students drop out percentage is smaller in our Institute than before the PIBID program started.

Keywords: innovation, projects, PIBID, physics, pre-service teacher experiences

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Authors: Noa Shriki, Atara Shriki

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Lifelong learning is considered as essential for teacher's professional development, which in turn has implications for the improvement of the entire education system. In recent years, many programs designed to support teachers' professional development are criticized for not achieving their goal. A variety of reasons have been proposed for the purpose of explaining the causes of the ineffectiveness of such programs. In this study, we put to test the possibility that teachers do not change as a result of their participation in professional programs due to a gap between the contents and approaches included in them and teacher's beliefs about teaching and learning. Eighteen elementary school mathematics teachers participated in the study. These teachers were involved in collaborating with their students in inquiring mathematical ideas, while implementing action research. Employing educational theories, the results indicated that this experience had a positive effect on teacher's professional development. In particular, there was an evident change in their beliefs regarding their role as mathematics teachers. However, while employing a different perspective for analyzing the data, the lens of Kurt Lewin's theory of re-education, we realized that this change of beliefs must be questioned. Therefore, it is suggested that analysis of educational processes should be carried out not only through common educational theories, but also on the basis of social and organizational theories. It is assumed that both the field of education and the fields of social studies and organizational consulting will benefit from the multifocal viewpoint

Keywords: educational theories, professional development, re-education, teachers' beliefs

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Authors: Shan-Yu Hsu, Hsin-Shu Huang

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The main purpose of this teaching research is to design an interdisciplinary team-assisted teaching method for trainees and interns and review the effectiveness of this teaching method on trainees' understanding of peritoneal dialysis. The teaching research object is the fifth and sixth-grade trainees in a medical center's medical school. The teaching methods include media teaching, demonstration of technical operation, face-to-face communication with patients, special case discussions, and field visits to the peritoneal dialysis room. Evaluate learning effectiveness before, after, and verbally. Statistical analysis was performed using the SPSS paired-sample t-test to analyze whether there is a difference in peritoneal dialysis professional cognition before and after teaching intervention. Descriptive statistics show that the average score of the previous test is 74.44, the standard deviation is 9.34, the average score of the post-test is 95.56, and the standard deviation is 5.06. The results of the t-test of the paired samples are shown as p-value = 0.006, showing the peritoneal dialysis professional cognitive test. Significant differences were observed before and after. The interdisciplinary team-assisted teaching method helps trainees and interns to improve their professional awareness of peritoneal dialysis. At the same time, trainee physicians have positive feedback on the inter-professional team-assisted teaching method. This teaching research finds that the clinical ability development education of trainees and interns can provide cross-professional team-assisted teaching methods to assist clinical teaching guidance.

Keywords: monitor quality, patient safety, health promotion objective, cross-professional team-assisted teaching methods

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Authors: Roya Pournaghi

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Measuring the extent of daily use of the libraries study space is of utmost significance in order to develop, re-organize and maintain the efficiency of the study space. The current study aimed to employ GIS in analyzing the study halls space of the document center and central library of Tehran University and determine the extent of use of the study chairs and desks by the students-intended users. This combination of survey methods - descriptive design system. In order to collect the required data and a description of the method, To implement and entering data into ArcGIS software. It also analyzes the data and displays the results on the library floor map design method were used. And spatial database design and plan has been done at the Central Library of Tehran University through the amount of space used by members of the Library and Information halls plans. Results showed that Biruni's hall is allocated the highest occupancy rate to tables and chairs compared to other halls. In the Hall of Science and Technology, with an average occupancy rate of 0.39 in the tables represents the lowest users and Rashid al-Dins hall, and Science and Technology’s hall with an average occupancy rate (0.40) represents the lowest users of seats. In this study, the comparison of the space is occupied at different period as a study’s hall in the morning, evenings, afternoons, and several months was performed through GIS. This system analyzed the space relationship effectively and efficiently. The output of this study can be used by administrators and librarians to determine the exact amount of using the Equipment of study halls and librarians can use the output map to design more efficient space at the library.

Keywords: geospatial information system, spatial analysis, reading room, academic libraries, library’s user, central library of Tehran university

Procedia PDF Downloads 217

Authors: Kien-Trinh Thi Bui, Cuong Manh Nguyen

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In order to simulate and reproduce the operational characteristics of a dam visually, it is necessary to capture the displacement at different measurement points and analyze the observed movement data promptly to forecast the dam safety. The accuracy of forecasts is further improved by applying machine learning methods to data analysis progress. In this study, the horizontal displacement monitoring data of the Ialy hydroelectric dam was applied to machine learning algorithms: Gaussian processes, multi-layer perceptron neural networks, and the M5-rules algorithm for modelling and forecasting of horizontal displacement of the Ialy hydropower dam (Vietnam), respectively, for analysing. The database which used in this research was built by collecting time series of data from 2006 to 2021 and divided into two parts: training dataset and validating dataset. The final results show all three algorithms have high performance for both training and model validation, but the MLPs is the best model. The usability of them are further investigated by comparison with a benchmark models created by multi-linear regression. The result show the performance which obtained from all the GP model, the MLPs model and the M5-Rules model are much better, therefore these three models should be used to analyze and predict the horizontal displacement of the dam.

Keywords: Gaussian processes, horizontal displacement, hydropower dam, Ialy dam, M5-Rules, multi-layer perception neural networks

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Authors: Abdul Hafeez, Samiya Shehzadi

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This research paper presents a different approach towards eco-friendly textile design by developing a sustainable composite fabric from orange peel for ladies' undergarments. The research focuses on utilizing orange peel to develop a unique orange leather/composite (fabric) through a process involving heating, extracting, and subsequent sun-drying to obtain the composite. The sustainable composite fabric shows properties that are favorable to the development of environmentally friendly undergarments, which not only offer UV protection but also possess healing properties for the skin. Through comprehensive testing and analysis, it has been determined that the orange peel composite fabric has zero harmful effects on the skin, making it a safe and desirable material for intimate wear. Furthermore, the research suggests that the orange peel composite fabric has the potential to reduce the rate of cancer cell growth. While the exact mechanisms and factors contributing to this effect require further investigation, the initial findings indicate promising aspects of the fabric in terms of potential cancer-preventive properties. Research contribution to the field of sustainable textile design by introducing a usual and eco-friendly approach utilizing orange peel waste. This work opens up avenues for further exploration and development of innovative materials that are both sustainable and beneficial for human health.

Keywords: sustainability, composite textiles, extracting, undergarments, eco-friendly, orange peels

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Authors: Mehrdad Shafiei Dizaji, Hoda Azari

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The research explores the pioneering integration of Physics-Informed Neural Networks (PINNs) into the domain of Ground-Penetrating Radar (GPR) data prediction, akin to advancements in medical imaging for tracking tumor progression in the human body. This research presents a detailed development framework for a specialized PINN model proficient at interpreting and forecasting GPR data, much like how medical imaging models predict tumor behavior. By harnessing the synergy between deep learning algorithms and the physical laws governing subsurface structures—or, in medical terms, human tissues—the model effectively embeds the physics of electromagnetic wave propagation into its architecture. This ensures that predictions not only align with fundamental physical principles but also mirror the precision needed in medical diagnostics for detecting and monitoring tumors. The suggested deep learning structure comprises three components: a CNN, a spatial feature channel attention (SFCA) mechanism, and ConvLSTM, along with temporal feature frame attention (TFFA) modules. The attention mechanism computes channel attention and temporal attention weights using self-adaptation, thereby fine-tuning the visual and temporal feature responses to extract the most pertinent and significant visual and temporal features. By integrating physics directly into the neural network, our model has shown enhanced accuracy in forecasting GPR data. This improvement is vital for conducting effective assessments of bridge deck conditions and other evaluations related to civil infrastructure. The use of Physics-Informed Neural Networks (PINNs) has demonstrated the potential to transform the field of Non-Destructive Evaluation (NDE) by enhancing the precision of infrastructure deterioration predictions. Moreover, it offers a deeper insight into the fundamental mechanisms of deterioration, viewed through the prism of physics-based models.

Keywords: physics-informed neural networks, deep learning, ground-penetrating radar (GPR), NDE, ConvLSTM, physics, data driven

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Authors: Susana Olmos, Catherine Spencer

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Every year our School in DIT (Dublin Institute of Technology) hosts approximately 80 Erasmus students from partner universities across Europe. Our own students are required to spend a compulsory 3rd year abroad on study and/or work placements. This is an extremely rewarding experience for all of the students, however, it can also be a challenging one. With this in mind, we started a project which aimed to make this transition as easy and productive as possible. The project, which is called MEET: Maximise the Erasmus Experience Together, focuses on the students’ own active engagement in learning and preparation – outside of the classroom –and their own self-directed pursuit of opportunities to develop their confidence and preparedness, which would work as an important foundation for the transformative learning that study abroad implies. We focussed on creating more structured opportunities where Erasmus students from our partner universities (currently studying at DIT) and our second-year students could interact and learn from each other, and in so doing improve both their language and intercultural skills. Our experience so far has been quite positive and we have seen how students taking part in this project have developed as autonomous learners as well as enhanced both their linguistic and intercultural knowledge. As the linguistic element of our project was one of our main priorities, we asked the students to keep a reflective diary on the activities that were organised by the group in the TL. Also, we use questionnaires as well as personal interviews to assess their development. However, there are challenges and proposals we would make to bring this project forward for the near future.

Keywords: erasmus, intercultural competence, linguistic competence, extra curriculum activities

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Authors: Evan Lowhorn, Rocio Alba-Flores

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The purpose of this work is to develop a method for classifying hand signals and using the output in a drone control algorithm. To achieve this, methods based on Convolutional Neural Networks (CNN) were applied. CNN's are a subset of deep learning, which allows grid-like inputs to be processed and passed through a neural network to be trained for classification. This type of neural network allows for classification via imaging, which is less intrusive than previous methods using biosensors, such as EMG sensors. Classification CNN's operate purely from the pixel values in an image; therefore they can be used without additional exteroceptive sensors. A development bench was constructed using a desktop computer connected to a high-definition webcam mounted on a scissor arm. This allowed the camera to be pointed downwards at the desk to provide a constant solid background for the dataset and a clear detection area for the user. A MATLAB script was created to automate dataset image capture at the development bench and save the images to the desktop. This allowed the user to create their own dataset of 12,000 images within three hours. These images were evenly distributed among seven classes. The defined classes include forward, backward, left, right, idle, and land. The drone has a popular flip function which was also included as an additional class. To simplify control, the corresponding hand signals chosen were the numerical hand signs for one through five for movements, a fist for land, and the universal “ok” sign for the flip command. Transfer learning with PyTorch (Python) was performed using a pre-trained 18-layer residual learning network (ResNet-18) to retrain the network for custom classification. An algorithm was created to interpret the classification and send encoded messages to a Ryze Tello drone over its 2.4 GHz Wi-Fi connection. The drone’s movements were performed in half-meter distance increments at a constant speed. When combined with the drone control algorithm, the classification performed as desired with negligible latency when compared to the delay in the drone’s movement commands.

Keywords: classification, computer vision, convolutional neural networks, drone control

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Authors: Abram Zoltan

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Over the past hundred years, human activities, particularly the burning of fossil fuels, have released enough carbon dioxide and other greenhouse gases to dissipate additional heat into the lower atmosphere and affect the global climate. Climate change affects many social and environmental determinants of health: clean air, safe drinking water, and adequate food. Our aim is to draw attention to the effects of climate change on the health and health care system. Improving climate awareness and the knowledge related to climate change's health impacts are essential among medical students and practicing medical doctors. Therefore, in their everyday practice, they also need some assistance and up-to-date knowledge of how climate change can endanger human health and deal with these novel health problems. Our activity, based on the cooperation of more universities, aims to develop new curriculum outlines and learning materials on climate change's health impacts for medical schools. Special attention is intended to pay to the possible preventative measures against these impacts. For all of this, the project plans to create new curriculum outlines and learning materials for medical students, elaborate methodological guidelines and create training materials for medical doctors' postgraduate learning programs. The target groups of the project are medical students, educational staff of medical schools and universities, practicing medical doctors with special attention to the general practitioners and family doctors. We had searched various surveys, domestic and international studies about the effects of climate change and statistical estimation of the possible consequences. The health effects of climate change can be measured only approximately by considering only a fraction of the potential health effects and assuming continued economic growth and health progress. We can estimate that climate change is expected to cause about 250,000 more deaths. We conclude that climate change is one of the most serious problems of the 21st century, affecting all populations. In the short- to medium-term, the health effects of climate change will be determined mainly by human vulnerability. In the longer term, the effects depend increasingly on the extent to which transformational action is taken now to reduce emissions. We can contribute to reducing environmental pollution by raising awareness and by educating the population.

Keywords: climate change, health impacts, medical students, education

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: Ruben Dario Tovar-Valencia, Eshan Ganju, Fei Han, Monica Prezzi, Rodrigo Salgado

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Particle breakage occurs even in strong silica sand particles. There is compelling evidence that suggests that particle breakage causes changes in several properties such as permeability, peak strength, dilatancy and critical state friction angle. Current pile design methods that are based on soil properties do not account for particle breakage that occurs during driving or jacking of displacement piles. This may lead to significant overestimation of pile capacity in sands dominated by particles susceptible to breakage, such as carbonate sands. The objective of this paper is to study the influence of shear displacement on particle breakage and friction angle of carbonate sands, and to furthermore quantify the change in friction angle observed with different levels of particle breakage. To study the phenomenon of particle breakage, multiple ring shear tests have been performed at different levels of vertical confinement on a thoroughly characterized carbonate sand to find i) the shear displacement necessary to reach stable friction angles and ii) the effect of particle breakage on the mobilized friction angle of the tested sand. The findings of this study can potentially be used to update the current pile design methods by developing a friction angle which is a function of shear displacement and breakage characteristics of the sand instead of being a constant value.

Keywords: breakage, carbonate sand, friction angle, pile design, ring shear test

Procedia PDF Downloads 289

Authors: Eiman Kattan

Abstract:

This study aims to evaluate the impact of classifying labelled remote sensing images conventional neural network (CNN) architecture, i.e., AlexNet on different land cover scenarios based on two remotely sensed datasets from different point of views such as the computational time and performance. Thus, a set of experiments were conducted to specify the effectiveness of the selected convolutional neural network using two implementing approaches, named fully trained and fine-tuned. For validation purposes, two remote sensing datasets, AID, and RSSCN7 which are publicly available and have different land covers features were used in the experiments. These datasets have a wide diversity of input data, number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in training, validation, and testing. As a result, the fully trained approach has achieved a trivial result for both of the two data sets, AID and RSSCN7 by 73.346% and 71.857% within 24 min, 1 sec and 8 min, 3 sec respectively. However, dramatic improvement of the classification performance using the fine-tuning approach has been recorded by 92.5% and 91% respectively within 24min, 44 secs and 8 min 41 sec respectively. The represented conclusion opens the opportunities for a better classification performance in various applications such as agriculture and crops remote sensing.

Keywords: conventional neural network, remote sensing, land cover, land use

Procedia PDF Downloads 351

Authors: Minho Kwak, Suhwan Yun, Choonsoo Park

Abstract:

Nose shape optimizations of high-speed train are performed for the improvement of aerodynamic characteristics. Based on the commercial train, KTX-Sancheon, multi-objective optimizations are conducted for the improvement of the side wind stability and the micro-pressure wave following the optimization for the reduction of aerodynamic drag. 3D nose shapes are modelled by the Vehicle Modeling Function. Aerodynamic drag and side wind stability are calculated by three-dimensional compressible Navier-Stokes solver, and micro pressure wave is done by axi-symmetric compressible Navier-Stokes solver. The Maxi-min Latin Hypercube Sampling method is used to extract sampling points to construct the approximation model. The kriging model is constructed for the approximation model and the NSGA-II algorithm was used as the multi-objective optimization algorithm. Nose length, nose tip height, and lower surface curvature are design variables. Because nose length is a dominant variable for aerodynamic characteristics of train nose, two optimization processes are progressed respectively with and without the design variable, nose length. Each pareto set was obtained and each optimized nose shape is selected respectively considering Honam high-speed rail line infrastructure in South Korea. Through the optimization process with the nose length, when compared to KTX Sancheon, aerodynamic drag was reduced by 9.0%, side wind stability was improved by 4.5%, micro-pressure wave was reduced by 5.4% whereas aerodynamic drag by 7.3%, side wind stability by 3.9%, micro-pressure wave by 3.9%, without the nose length. As a result of comparison between two optimized shapes, similar shapes are extracted other than the effect of nose length.

Keywords: aerodynamic characteristics, design variable, multi-objective optimization, train nose shape

Procedia PDF Downloads 339

Authors: Mark Archei O. Javier

Abstract:

The Fourth Industrial Revolution (FIR) is a major industrial era characterized by the fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. Since this era teaches us how to thrive in the fast-paced developing world, it is important to be able to adapt. With this, there is a need to make learning and teaching in the bioscience laboratory more challenging and engaging. The goal of the research is to find out if using in silico and in vitro laboratory activities compared to the conventional conduct laboratory activities would have positive impacts on the academic performance of the learners. The potential contribution of the research is that it would improve the teachers’ methods in delivering the content to the students when it comes to topics that need laboratory activities. This study will develop a method by which teachers can provide learning materials to the students. A one-tailed t-Test for independent samples was used to determine the significant difference in the pre- and post-test scores of students. The tests of hypotheses were done at a 0.05 level of significance. Based on the results of the study, the gain scores of the experimental group are greater than the gain scores of the control group. This implies that using in silico and in vitro labs for the experimental group is more effective than the conventional method of doing laboratory activities.

Keywords: academic performance, general biology, in silico laboratory, in vivo laboratory, virtual laboratory

Procedia PDF Downloads 182

Authors: Lindsey D. Sams, Dean R. Gorman, Cathy D. Lirgg, Steve W. Dittmore, Jack C. Kern

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Golf is a lifetime sport that provides numerous physical and psychological benefits. The game has struggled with attrition and retention within minority groups and this has exposed the lack of a modified introduction to the game that is uniformly accessible and developmentally appropriate. Factors that have been related to sport participatory behaviors include perceived competence, enjoyment and intention. The purpose of this study was to examine self-reported perception differences in competence and enjoyment between learners using modified and traditional equipment as well as the potential effects these factors could have on intent for future participation. For this study, SNAG Golf was chosen to serve as the scaled equipment used by the modified equipment group. The participants in this study were 99 children (24 traditional equipment users/ 75 modified equipment users) located across the U.S. with ages ranging from 7 to 12 years (2nd-5th grade). Utilizing a convenience sampling method, data was obtained on a voluntary basis through surveys measuring children’s golf participation and self-perceptions concerning perceived competence, enjoyment and intention to continue participation. The scales used for perceived competence and enjoyment included Susan Harter’s Self-Perception Profile for Children (SPPC) along with the Physical Activity Enjoyment Scale (PACES). Analysis revealed no significant differences for enjoyment, perceived competence or intention between children learning with traditional golf equipment and modified golf equipment. This was true even though traditional equipment users reported significantly higher experience levels than that of modified users. Intention was regressed on the enjoyment and perceived competence variables. Congruent with current literature, enjoyment was a strong predictor of intention to continue participation, for both groups. Modified equipment users demonstrated significantly lower experience levels but reported similar levels of competence, enjoyment and intent to continue participation as reported by the more experienced, and potentially more skilled, traditional users. The ability to immediately generate these positive affects suggests the potential adoption of a more effective way to learn golf and a method that is conducive to participatory behaviors related to attrition and retention. These implications in turn, highlight an equipment candidate ideal for inception into physical education programs where new learners are introduced to various sports in safe and developmentally appropriate environments. A major goal of this study was to provide foundational research that instigates the further examination of golf’s introductory teaching methodologies, as there is a lack of its presence in current literature. Future research recommendations range from improvements in the current research design to expansive approaches related to the topic, such as progressive skill development, knowledge of the game’s tactical and strategic concepts, playing ability and teaching effectiveness when utilizing modified versus traditional equipment.

Keywords: adaptive sports, enjoyment, golf participation, modified equipment, perceived competence, SNAG golf

Procedia PDF Downloads 326

Authors: Sara Muhammad Elqudah, Vigh László Gergely

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Catastrophic events, such as earthquakes, are sudden, short, and devastating, threatening lives, demolishing futures, and causing huge economic losses. Current seismic analyses and design standards are based on life safety levels where only some residual strength and stiffness are left in the structure leaving it beyond economical repair. Consequently, it has become necessary to introduce and implement the concept of resilient design. Resilient design is about designing for ductility over time by resisting, absorbing, and recovering from the effects of a hazard in an appropriate and efficient time manner while maintaining the functionality of the structure in the aftermath of the incident. Resilient analysis is mainly based on the fragility, vulnerability, and functionality curves where eventually a resilience index is generated from these curves, and the higher this index is, the better is the performance of the structure. In this paper, seismic performances of a simple two story reinforced concrete building, located in a moderate seismic region, has been evaluated using the conventional seismic analyses methods, which are the linear static analysis, the response spectrum analysis, and the pushover analysis, and the generated results of these analyses methods are compared to those of the resilient analysis. Results highlight that the resilience analysis was the most convenient method in generating a more ductile and functional structure from a socio-economic perspective, in comparison to the standard seismic analysis methods.

Keywords: conventional analysis methods, functionality, resilient analysis, seismic performance

Procedia PDF Downloads 91

Authors: N. Ojaroudi Parchin, H. Jahanbakhsh Basherlou, Y. Al-Yasir, A. M. Abdulkhaleq, R. A. Abd-Alhameed, P. S. Excell

Abstract:

A compact design of multi-sector patch antenna array for 60 GHz applications is presented and discussed in details. The proposed design combines five 1×8 linear patch antenna arrays, referred to as sectors, in a multi-sector configuration. The coaxial-fed radiation elements of the multi-sector array are designed on 0.2 mm Rogers RT5880 dielectrics. The array operates in the frequency range of 58-62 GHz and provides switchable directional/omnidirectional radiation beams with high gain and high directivity characteristics. The designed multi-sector array exhibits good performances and could be used in the fifth generation (5G) cellular networks.

Keywords: mm-wave communications, multi-sector array, patch antenna, small cell networks

Procedia PDF Downloads 136

Authors: Rong-Yang Lai, Jia-Yu Wu, Chih-Han Chang, Yung-Chung Chen

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The dental bridge is one of the clinical methods of the treatment for missing teeth. The dental bridge is generally designed for two layers, containing the inner layer of the framework(zirconia) and the outer layer of the porcelain-fused to framework restorations. The design of a conventional bridge is generally based on the antagonist tooth profile so that the framework evenly indented by an equal thickness from outer contour. All-ceramic dental bridge made of zirconia have well demonstrated remarkable potential to withstand a higher physiological occlusal load in posterior region, but it was found that there is still the risk of all-ceramic bridge failure in five years. Thus, how to reduce the incidence of failure is still a problem to be solved. Therefore, the objective of this study is to develop mechanical designs for all-ceramic dental bridges framework by reducing the stress and enhancing fracture resistance under given loading conditions by finite element method. In this study, dental design software is used to design dental bridge based on tooth CT images. After building model, Bi-directional Evolutionary Structural Optimization (BESO) Method algorithm implemented in finite element software was employed to analyze results of finite element software and determine the distribution of the materials in dental bridge; BESO searches the optimum distribution of two different materials, namely porcelain and zirconia. According to the previous calculation of the stress value of each element, when the element stress value is higher than the threshold value, the element would be replaced by the framework material; besides, the difference of maximum stress peak value is less than 0.1%, calculation is complete. After completing the design of dental bridge, the stress distribution of the whole structure is changed. BESO reduces the peak values of principle stress of 10% in outer-layer porcelain and avoids producing tensile stress failure.

Keywords: dental bridge, finite element analysis, framework, automatic program

Procedia PDF Downloads 270

Authors: Robin Ratnasingham, Maher Elshakankiri

Abstract:

This research report will look at how to make a smart washroom to increase public hygiene and cleanliness. The system would use IoT devices to pick up various activities in the washroom and notify the appropriate stakeholders or devices to regulate the condition of the washroom. As more people are required to physically go back to the office or school, ensuring a clean and sanitized washroom is even more important now than before. It would help prevent virus outbreaks and safeguard the organization from shutdowns or slowdowns in their business. A framework of the suggested smart washroom was introduced to help reduce the chances of a virus outbreak. Most organizations outsource renovation or implementation to an external party. Using the smart washroom framework, we looked at vendors that provide smart washroom solutions. There are IoT vendors that cannot match the framework, and there are vendors that can support the framework design. This segment is a niche market, and most of the devices are similar in their basic functions. However, all the vendors have unique characteristics to give them a competitive advantage over the rest of the IoT washroom companies. Ultimately, the organization would need to decide if they want to add IoT devices to enable smart capability or renovate the washroom to create a fluid IoT smart washroom design. The report would introduce an IoT smart washroom framework to help organizations design a cohesive preventive measure network for the daily maintenance routine. The framework is designed to help understand how to manage washroom cleanliness more efficiently and to provide guidance in achieving this goal. The leading result is eliminating potential viral outbreaks that could jeopardize the organization.

Keywords: IoT, smart washroom, public hygiene, cleanliness, virus outbreaks, safeguard

Procedia PDF Downloads 81

Authors: Ming Ma, Zhenyu Cai, Rui Li

Abstract:

People are more vulnerable to health problems than ever before, such as overweight and obesity due to the change of built environment. In the high-rise buildings, the core-tube layout is closely associated with user’s physical activities which will affect human’s health in a long-term. As for the white-collars who spends the amount of time working in the office tower, using staircase seems to provide an opportunity for them to increase the physical activities in the workplaces. This paper is aiming to find out the specific relationship between health and core-tube in the office tower through analyzing the correlation between staircase’s layout and user’s health. The variables of staircase’s layout are consisted of two indicators: plan layout and space design, including nine factors while health variable is applying BIM as the only main factor. 14 office towers in downtown Shanghai are selected as the research samples because of its typical users’ pattern and similar core-tube layout. In the result, it is obvious that the users from these 14 cases have higher BMI than average partly because that the staircases are mainly designed for emergency and fire instead of daily use. After the regression and correlation analysis of the variables of health and staircases, it’s found that users’ BMI is significantly associated with the factors of floor guide-signs and distance from lobby to the staircase. In addition, the factors of comfort level of staircase such as width and daylighting have a certain correlation with users’ BMI.

Keywords: office tower, staircase, design, obesity, physical activity

Procedia PDF Downloads 215