Search results for: learning design

Authors: Madjid Nancy, Rakinaung Natalia, Lumowa Fresy

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Background: Bullying becomes one of the problems that concern the world of education, especially in adolescents, which has a negative impact on learning achievement, psychology, and physical health. The psychological impact is shame, depression, distress, fear, sadness, and anxiety, so that if prolonged leave can lead to depression in the victim. While the impact on physical health in the form of bruises on the hit area, blisters, swelling and in more severe cases will lead to death. Objectives: This study aims to explore the perception of bullying in adolescent students Sekolah Menengah Kejuruan (SMK) Negeri 1 Manado and the people associated with that adolescent students. Methods: This research uses descriptive qualitative research design and using thematic analysis, and supported by Urie Bronfenbrenner Ecological Framework. The data collection that will be used is by in-depth interview. Sampling using purposive sampling and snowball techniques. This research was conducted at SMK Negeri 1 Manado. Result: From the analysis obtained three themes with the categories: 1) the perception of bullying with categories are: Understanding of Bullying and The Impact of Bullying, 2) the originator of bullying with categories are: Fulfillment of Youth Development Tasks and Needs, Peers Influence, and Family Communication; 3) the effort to handle bullying with categories are: the Individual Coping and Teacher Role. Conclusion: This research get three themes, those are perception of bullying, bullying’s originator and the effort of handling bullying.

Keywords: adolscent, students, bullying, perception

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Satoshi Kusaka

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The term ‘competency’ is attracting considerable scholarly attention worldwide with the advance of globalization in the 21st century and with the arrival of a knowledge-based society. In the current world environment, familiarity with varied disciplines is regarded to be vital for personal success. The idea of a competency-based educational system was mooted by the ‘Definition and Selection of Competencies (DeSeCo)’ project that was conducted by the Organization for Economic Cooperation and Development (OECD). Further, attention to this topic is not limited to developed countries; it can also be observed in developing countries. For instance, the importance of a competency-based curriculum was mentioned in the ‘2013 Harmonized Curriculum Framework for the East African Community’, which recommends key competencies that should be developed in primary schools. The introduction of such curricula and the reviews of programs are actively being executed, primarily in the East African Community but also in neighboring nations. Taking Mozambique as a case in point, the present paper examines the conception of ‘competency’ as a target of frontline education in developing countries. It also aims to discover the manner in which the syllabus, textbooks and lessons, among other things, in primary-level math education are developed and to determine the challenges faced in the process. This study employs the perspective of competency-based education design to analyze how the term ‘competency’ is defined in the primary-level math syllabus, how it is reflected in the textbooks, and how the lessons are actually developed. ‘Practical competency’ is mentioned in the syllabus, and the description of the term lays emphasis on learners' ability to interactively apply socio-cultural and technical tools, which is one of the key competencies that are advocated in OECD's ‘Definition and Selection of Competencies’ project. However, most of the content of the textbooks pertains to ‘basic academic ability’, and in actual classroom practice, teachers often impart lessons straight from the textbooks. It is clear that the aptitude of teachers and their classroom routines are greatly dependent on the cultivation of their own ‘practical competency’ as it is defined in the syllabus. In other words, there is great divergence between the ‘syllabus’, which is the intended curriculum, and the content of the ‘textbooks’. In fact, the material in the textbooks should serve as the bridge between the syllabus, which forms the guideline, and the lessons, which represent the ‘implemented curriculum’. Moreover, the results obtained from this investigation reveal that the problem can only be resolved through the cultivation of ‘practical competency’ in teachers, which is currently not sufficient.

Keywords: competency, curriculum, mathematics education, Mozambique

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Authors: Gregor Bouville, Celine Schmidt

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This article presents a French case study on lean production drawing on a mixed method design which has received little attention in French management research-especially in French human resources research. The purpose is to show that using a mixed method approach in this particular case overstep the limitations of previous studies in lean production studies. The authors use the embedded design as a special articulation of mixed method to analyse and understand the effects of three organizational practices on job satisfaction and workers’ health. Results show that low scheduled autonomy, quality management, time constraint have deleterious effects on job satisfaction. Furthermore, these three practices have ambivalent effects on health work. Interest in the subjects of mixed method has been growing up among French health researchers and practioners, also recently among French management researchers. This study reinforces and refines how mixed methods may offer interesting perspectives in an integrated framework included human resources, management, and health fields. Finally, potentials benefits and limits for those interdisciplinary researches programs are discussed.

Keywords: lean production, mixed method, work organization practices, job satisfaction

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Authors: Rajender Dahiya

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Investigation outcomes of major process incidents have been consistent for decades and validate that the causes and consequences are often identical. The debate remains as we continue to experience similar process incidents even with enormous development of new tools, technologies, industry standards, codes, regulations, and learning processes? The objective of this paper is to investigate the most common causes of major industrial incidents and reveal industry challenges and best practices to prevent such incidents. The author, in his current role, performs audits and inspections of a variety of high-hazard industries in North America, including petroleum refineries, chemicals, petrochemicals, manufacturing, etc. In this paper, he shares real life scenarios, examples, and case studies from high hazards operating facilities including key challenges and best practices. This case study will provide a clear understanding of the importance of near miss incident investigation. The incident was a Safe operating limit excursion. The case describes the deficiencies in management programs, the competency of employees, and the culture of the corporation that includes hazard identification and risk assessment, maintaining the integrity of safety-critical equipment, operating discipline, learning from process safety near misses, process safety competency, process safety culture, audits, and performance measurement. Failure to identify the hazards and manage the risks of highly hazardous materials and processes is one of the primary root-causes of an incident, and failure to learn from past incidents is the leading cause of the recurrence of incidents. Several investigations of major incidents discovered that each showed several warning signs before occurring, and most importantly, all were preventable. The author will discuss why preventable incidents were not prevented and review the mutual causes of learning failures from past major incidents. The leading causes of past incidents are summarized below. Management failure to identify the hazard and/or mitigate the risk of hazardous processes or materials. This process starts early in the project stage and continues throughout the life cycle of the facility. For example, a poorly done hazard study such as HAZID, PHA, or LOPA is one of the leading causes of the failure. If this step is performed correctly, then the next potential cause is. Management failure to maintain the integrity of safety critical systems and equipment. In most of the incidents, mechanical integrity of the critical equipment was not maintained, safety barriers were either bypassed, disabled, or not maintained. The third major cause is Management failure to learn and/or apply learning from the past incidents. There were several precursors before those incidents. These precursors were either ignored altogether or not taken seriously. This paper will conclude by sharing how a well-implemented operating management system, good process safety culture, and competent leaders and staff contributed to managing the risks to prevent major incidents.

Keywords: incident investigation, risk management, loss prevention, process safety, accident prevention

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Authors: S. Mohamadi, T. Boudina, A. Rouabeh, A. Seridi

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Equivalent linear and non-linear ground response analyses are conducted at many representative sites at the mosque of Algeria, to compare the free field acceleration spectra with local code of practice. Spectral Analysis of Surface Waves (SASW) technique was adopted to measure the in-situ shear wave velocity profile at the representative sites. The seismic movement imposed on the rock is the NS component of Keddara station recorded during the earthquake in Boumerdes 21 May 2003. The site-specific elastic design spectra for each site are determined to further obtain site specific non-linear acceleration spectra. As a case study, the results of site-specific evaluations are presented for two building sites (site of minaret and site of the prayer hall) to demonstrate the influence of local geological conditions on ground response at Algerian sites. A comparison of computed response with the standard code of practice being used currently in Algeria for the seismic zone of Algiers indicated that the design spectra is not able to capture site amplification due to local geological conditions.

Keywords: equivalent linear, non-linear, ground response analysis, design response spectrum

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Authors: Saule Shazhanbayeva, Denise van der Merwe

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Study hypothesis: Nazarbayev Intellectual School of Kyzylorda’s Biology teachers can use STEM-integrated learning to improve students' problem-solving ability and responsibility as global citizens. The significance of this study is to indicate how the use of STEM integrative learning during Biology lessons could contribute to forming globally-minded students who are responsible community members. For the purposes of this study, worldview is defined as a view that is broader than the country of Kazakhstan, allowing students to see the significance of their scientific contributions to the world as global citizens. The context of worldview specifically indicates that most students have never traveled outside of their city or region within Kazakhstan. In order to broaden student understanding, it is imperative that students are exposed to different world views and contrasting ideas within the educational setting of Biology as the science being used for the research. This exposure promulgates students understanding of the significance they have as global citizens alongside the obligations which would rest on them as scientifically minded global citizens. Integrative learning should be Biological Science - with Technology and engineering in the form of problem-solving, and Mathematics to allow improved problem-solving skills to develop within the students of Nazarbayev Intellectual School (NIS) of Kyzylorda. The school's vision is to allow students to realise their role as global citizens and become responsible community members. STEM allows integrations by combining four subject skills to solve topical problems designed by educators. The methods used are based on qualitative analysis: for students’ performance during a problem-solution scenario; and Biology teacher interviews to ascertain their understanding of STEM implementation and willingness to integrate it into current lessons. The research indicated that NIS is ready for a shift into STEM lessons to promote globally responsible students. The only additional need is for proper STEM integrative lesson method training for teachers.

Keywords: global citizen, STEM, Biology, high-school

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Authors: Haider M. Alsaeq

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The present research is an attempt to figure out the best configuration of composite cylindrical shells of the sandwich type, i.e. the lightest design of such shells required to sustain a certain load over a certain area. The optimization is based on elastic-plastic geometrically nonlinear incremental-iterative finite element analysis. The nine-node degenerated curved shell element is used in which five degrees of freedom are specified at each nodal point, with a layered model. The formulation of the geometrical nonlinearity problem is carried out using the well-known total Lagrangian principle. For the structural optimization problem, which is dealt with as a constrained nonlinear optimization, the so-called Modified Hooke and Jeeves method is employed by considering the weight of the shell as the objective function with stress and geometrical constraints. It was concluded that the optimum design of composite sandwich cylindrical shell that have a rigid polyurethane foam core and steel facing occurs when the area covered by the shell becomes almost square with a ratio of core thickness to facing thickness lies between 45 and 49, while the optimum height to length ration varies from 0.03 to 0.08 depending on the aspect ratio of the shell and its boundary conditions.

Keywords: composite structure, cylindrical shell, optimization, non-linear analysis, finite element

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Authors: Amir Ashraf

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Homoeopathy is an alternative system of medicine discovered by German physician Samuel Hahnemann in 1796. It has been used by several people for various health conditions globally for more than last 200 years. In India, homoeopathy is considered as a major system of alternative medicine. Homoeopathy is found effective in various medical conditions including Pyuria. Pyuria is the condition in which pus cells are found in urine. Homoeopathy is very useful for reducing pus cells, and homeopathically potentized Conium Mac (Hemlock) is an important remedy commonly used for reducing pyuria. Aim: To reduce the amount pus cells found in urine using Conium Mac 200C. Methods: Design. Small N Design. Samples: Purposive Sampling with 5 cases diagnosed as pyuria. Tools: Personal Data Schedule and ICD-10 Criteria for Pyuria. Techniques: Potentized homoeopathic medicine, Conium Mac 200th potency is used. Statistical Analysis: The statistical analyses were done using non-parametric tests. Results: There is significant pre/post difference has been identified. Conclusion: Homoeopathic potency, Conium Mac 200 C is effective in reducing the increased level of pus cells found in urine samples.

Keywords: homoeopathy, alternative medicine, Pyuria, Conim Mac, small N design, non-parametric tests, homeopathic physician, Ashirvad Hospital, Kannur

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Authors: Angeliki Chronopoulou, Eleni Alexandrou

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This paper thoroughly investigates residential buildings of the period 1920 – 1960 in Athens and evaluates their bioclimatic response and energy performance. A methodology adapted to the specific context of the city is proposed and applied in order to assess and extract results related to the climate analysis of the city of Athens, the general/architectural design and construction characteristics of the apartment buildings constructed during the period 1920 – 1960, the bioclimatic strategies applied on them, and the achieved thermal comfort based on questionnaires answered by their users. The results of the current study indicate that the residential architecture of that period in the city of Athens is adapted to an extend to the local climate with various climate responsive strategies. As an outcome of the analysis, the most frequently applied depending on the period of construction are presented. For this reason, the examined period is divided into 3 sub – periods: 1st period 1920s – 1930s (late neoclassicism & eclecticism), 2nd period 1930s – 1940s (modernism), 3rd period 1940s – 1960s (postwar modernism).

Keywords: Athens, climatic design strategies, residential buildings, middle war and post war architecture, thermal comfort

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Authors: Omar Faruqe Hamim, M. Shamsul Hoque, Rich C. McIlroy, Katherine L. Plant, Neville A. Stanton

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Road safety has become an alarming issue, especially in low-middle income developing countries. The traditional approaches lack the out of the box thinking, making engineers confined to applying usual techniques in making roads safer. A socio-technical approach has recently been introduced in improving road intersections through designing with intent. This Design With Intent (DWI) approach aims to give practitioners a more nuanced approach to design and behavior, working with people, people’s understanding, and the complexities of everyday human experience. It's a collection of design patterns —and a design and research approach— for exploring the interactions between design and people’s behavior across products, services, and environments, both digital and physical. Through this approach, it can be seen that how designing with people in behavior change can be applied to social and environmental problems, as well as commercially. It has a total of 101 cards across eight different lenses, such as architectural, error-proofing, interaction, ludic, perceptual, cognitive, Machiavellian, and security lens each having its own distinct characteristics of extracting ideas from the participant of this approach. For this research purpose, a three-legged accident blackspot intersection of a national highway has been chosen to perform the DWI workshop. Participants from varying fields such as civil engineering, naval architecture and marine engineering, urban and regional planning, and sociology actively participated for a day long workshop. While going through the workshops, the participants were given a preamble of the accident scenario and a brief overview of DWI approach. Design cards of varying lenses were distributed among 10 participants and given an hour and a half for brainstorming and generating ideas to improve the safety of the selected intersection. After the brainstorming session, the participants spontaneously went through roundtable discussions regarding the ideas they have come up with. According to consensus of the forum, ideas were accepted or rejected. These generated ideas were then synthesized and agglomerated to bring about an improvement scheme for the intersection selected in our study. To summarize the improvement ideas from DWI approach, color coding of traffic lanes for separate vehicles, channelizing the existing bare intersection, providing advance warning traffic signs, cautionary signs and educational signs motivating road users to drive safe, using textured surfaces at approach with rumble strips before the approach of intersection were the most significant one. The motive of this approach is to bring about new ideas from the road users and not just depend on traditional schemes to increase the efficiency, safety of roads as well and to ensure the compliance of road users since these features are being generated from the minds of users themselves.

Keywords: design with intent, road safety, human experience, behavior

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Authors: Reza Hedayati, Meysam Jahanbakhshi

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Elastic energy absorbers which consist of a ring-liked plate and springs can be a good choice for increasing the impact duration during an accident. In the current project, an energy absorber system is optimized using four optimizing methods Kuhn-Tucker, Sequential Linear Programming (SLP), Concurrent Subspace Design (CSD), and Pshenichny-Lim-Belegundu-Arora (PLBA). Time solution, convergence, Programming Length and accuracy of the results were considered to find the best solution algorithm. Results showed the superiority of PLBA over the other algorithms.

Keywords: Concurrent Subspace Design (CSD), Kuhn-Tucker, Pshenichny-Lim-Belegundu-Arora (PLBA), Sequential Linear Programming (SLP)

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Authors: N. M. Zukani, E. O. Adu

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Homeschooling has been a primary method for parents to educate their children. It has become a growing educational phenomenon across the globe. However, homeschooling is, therefore, an alternative form of education in which children are instructed at home rather than in mainstream schools. This study evaluated the effectiveness of homeschooling in East London Education District, looking at the stakeholder’s perceptions, reviewing issues that impact on this as reflected in literature. This is a qualitative study done in selected homeschools. Semi structured interviews were used as a form of collecting data. Data was scrutinized and grouped into themes. The study revealed the importance of differentiation of instruction, and the need for flexibility in the process of homeschooling for children who faced difficulties, special needs in learning in mainstream schooling. It is therefore concluded that the participants in the study clearly showed that homeschooling is an educational choice for parents who have concerns about the quality of education of their children. Furthermore, homeschooling has the potential to be the most learner centered, nurturing educational approach. It was recommended that an effective homeschooling practice mainly, the practice should consider attention to children-parent’s goals and learning structure. Although homeschooling looks at how to overcome the drawbacks of mainstream schooling, there are also cases that reflected, the incompetency of parents or tutors conducting the homeschooling and also a need for the support material and other educational supports from the government.

Keywords: homeschooling, effectiveness, stakeholders, parents, perception

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Authors: Adnan Alhathal Alanezi

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The performance of vacuum membrane distillation (VMD) process for water desalination was investigated utilizing a new design membrane module using two commercial polytetrafluoroethylene (PTFE) and polyvinylidene fluoride (PVDF) flat sheet hydrophobic membranes. The membrane module's design demonstrated its suitability for achieving a high heat transfer coefficient of the order of 103 (W/m2K) and a high Reynolds number (Re). The heat and mass transport coefficients within the membrane module were measured using VMD experiments. The permeate flux has been examined in relation to process parameters such as feed temperature, feed flow rate, vacuum degree, and feed concentration. Because the feed temperature, feed flow rate, and vacuum degree all play a role in improving the performance of the VMD process, optimizing all of these parameters is the best method to achieve a high permeate flux. In VMD desalination, the PTFE membrane outperformed the PVDF membrane. When compared to previous studies, the obtained water flux is relatively high, reaching 43.8 and 52.6 (kg/m2h) for PVDF and PTFE, respectively. For both membranes, the salt rejection of NaCl was greater than 99%.

Keywords: desalination, vacuum membrane distillation, PTFE and PVDF, hydrophobic membranes, O-ring membrane module

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Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

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Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

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Authors: Jae Hee Chung, Tae Uk Kang, Byung Seo Kim

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This study aims to propose design technologies for the energy-saving modular housing units considering environmental and aesthetic aspects. Modular houses are environmentally friendly based on 3R (Reduce, Reuse, Recycle) because they can dramatically reduce carbon dioxide and construction wastes generated during the construction, use, and disposal process by the pre-fabrication at the factory and the recyclability of the unit, compared to the existing construction methods. The existing modular housing, however, tends to focus on quantitative aspects of energy reduction, such as windows, insulation, and introduction of renewable energy, and there is not much research on energy-saving type units considering the environmental aspects such as daylighting and ventilation, and the design that goes beyond the standardized appearance. Therefore, this study conducts theoretical investigation and analytical case studies on the energy-saving methods through various architectural planning elements as well as materials like insulation considering the environmental and aesthetic aspects in the modular housing. Then, comparative analysis on the energy efficiency through the energy simulation is conducted. As a conclusion, the energy-saving modular housing units considering environmental and aesthetics aspects are proposed. It is expected that this study will contribute to the supply and activation of modular housing through deriving design technologies for the energy-saving modular housing units that consider not only quantitative aspects but also qualitative aspects.

Keywords: aesthetic aspects, energy-saving, environmental, modular housing

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Authors: Omer Cahana, Ofer Levi, Maya Herman

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Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: magnetic resonance imaging, image reconstruction, pyramid network, deep learning

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Authors: Piotr Jerzy Rugor, Julia Wajoras

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The presented work regards a single-stage aerodynamically controlled solid propulsion rocket. Steering a rocket to fly along a predetermined trajectory can be beneficial for minimizing aerodynamic losses and achieved by implementing an active control system on board. In this particular case, a canard configuration has been chosen, although other methods of control have been considered and preemptively analyzed, including non-aerodynamic ones. The objective of this work is to create a system capable of guiding the rocket, focusing on roll stabilization. The paper describes initial analysis of the problem, covers the main challenges of missile guidance and presents data acquired during the experimental study.

Keywords: active canard control system, rocket design, numerical simulations, flight optimization

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Authors: Athena Johnson

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Special education is an important field but often under-researched, particularly for the cause of learning deficiencies. Often times special education looks at the symptoms rather than the cause, and this can lead to many misdiagnoses. Student trauma, as measured by the Adverse Childhood Experiences (ACE) test, is extremely common, often resulting in Post Traumatic Stress Disorder (PTSD). PTSD affects the brain's ability to learn properly, making students have a much more difficult time with auditory learning and memory due to always being in flight or fight mode, and due to this, students with PTSD are often misdiagnosed with Attention Deficit and Hyperactivity Disorder (ADHD). This can lead to them getting the wrong support, with PTSD students needing more counseling than anything else. Through these research papers' methodologies, a literature review on article research from the perspectives of students who were misdiagnosed, and imperial research, the major findings of this study were the importance of trauma-informed care in schools. Trauma-informed care in the school system is crucial for helping the many students who experience traumatic life events and struggle in school due to it. It is important to support students with PTSD so that they are able to integrate and learn better in society and school with trauma-informed school care.

Keywords: ACE test, ADHD, misdiagnoses, special education, trauma, trauma-informed care, PTSD

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Authors: Gholba Niranjan Dilip, Anil Kumar

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Conduct of accurate reliable mapping of oil palm plantations and census of individual palm trees is a huge challenge. This study addresses this challenge and developed an optimized solution implemented deep learning techniques on remote sensing data. The oil palm is a very important tropical crop. To improve its productivity and land management, it is imperative to have accurate census over large areas. Since, manual census is costly and prone to approximations, a methodology for automated census using panchromatic images from Cartosat-2, SkySat and World View-3 satellites is demonstrated. It is selected two different study sites in Indonesia. The customized set of training data and ground-truth data are created for this study from Cartosat-2 images. The pre-trained model of Single Shot MultiBox Detector (SSD) Lite MobileNet V2 Convolutional Neural Network (CNN) from the TensorFlow Object Detection API is subjected to transfer learning on this customized dataset. The SSD model is able to generate the bounding boxes for each oil palm and also do the counting of palms with good accuracy on the panchromatic images. The detection yielded an F-Score of 83.16 % on seven different images. The detections are buffered and dissolved to generate polygons demarcating the boundaries of the oil palm plantations. This provided the area under the plantations and also gave maps of their location, thereby completing the automated census, with a fairly high accuracy (≈100%). The trained CNN was found competent enough to detect oil palm crowns from images obtained from multiple satellite sensors and of varying temporal vintage. It helped to estimate the increase in oil palm plantations from 2014 to 2021 in the study area. The study proved that high-resolution panchromatic satellite image can successfully be used to undertake census of oil palm plantations using CNNs.

Keywords: object detection, oil palm tree census, panchromatic images, single shot multibox detector

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Authors: Coriolano Salvini, Ambra Giovannelli

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The use of renewable energy sources for electric power production leads to reduced CO2 emissions and contributes to improving the domestic energy security. On the other hand, the intermittency and unpredictability of their availability poses relevant problems in fulfilling safely and in a cost efficient way the load demand along the time. Significant benefits in terms of “grid system applications”, “end-use applications” and “renewable applications” can be achieved by introducing energy storage systems. Among the currently available solutions, CAES (Compressed Air Energy Storage) shows favorable features. Small-medium size plants equipped with artificial air reservoirs can constitute an interesting option to get efficient and cost-effective distributed energy storage systems. The present paper is addressed to the design and off-design analysis of the compression system of small size CAES plants suited to absorb electric power in the range of hundreds of kilowatt. The system of interest is constituted by an intercooled (in case aftercooled) multi-stage reciprocating compressor and a man-made reservoir obtained by connecting large diameter steel pipe sections. A specific methodology for the system preliminary sizing and off-design modeling has been developed. Since during the charging phase the electric power absorbed along the time has to change according to the peculiar CAES requirements and the pressure ratio increases continuously during the filling of the reservoir, the compressor has to work at variable mass flow rate. In order to ensure an appropriately wide range of operations, particular attention has been paid to the selection of the most suitable compressor capacity control device. Given the capacity regulation margin of the compressor and the actual level of charge of the reservoir, the proposed approach allows the instant-by-instant evaluation of minimum and maximum electric power absorbable from the grid. The developed tool gives useful information to appropriately size the compression system and to manage it in the most effective way. Various cases characterized by different system requirements are analysed. Results are given and widely discussed.

Keywords: artificial air storage reservoir, compressed air energy storage (CAES), compressor design, compression system management.

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Authors: Yin Yuanling

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A Deep Feedback Recurrent Neural Network (DFRNN) and Bidirectional Long Short-Term Memory (BiLSTM) are designed to address the problem of low accuracy of traditional relationship extraction models. This method combines a deep feedback-based recurrent neural network (DFRNN) with a bi-directional long short-term memory (BiLSTM) approach. The method combines DFRNN, which extracts local features of text based on deep feedback recurrent mechanism, BiLSTM, which better extracts global features of text, and Self-Attention, which extracts semantic information. Experiments show that the method achieves an F1 value of 76.69% on the CEC dataset, which is 0.0652 better than the BiLSTM+Self-ATT model, thus optimizing the performance of the deep learning method in the event relationship extraction task.

Keywords: event relations, deep learning, DFRNN models, bi-directional long and short-term memory networks

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Authors: Dongjae Kang, Sokho Son, Jinmee Kim

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Cloud service brokering is a new service paradigm that provides interoperability and portability of application across multiple Cloud providers. In this paper, we designed cloud service brokerage system, any broker, supporting integrated service provisioning and SLA based service life cycle management. For the system design, we introduce the system concept and whole architecture, details of main components and use cases of primary operations in the system. These features ease the Cloud service provider and customer’s concern and support new Cloud service open market to increase cloud service profit and prompt Cloud service echo system in cloud computing related area.

Keywords: cloud service brokerage, multiple Clouds, Integrated service provisioning, SLA, network service

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Authors: Liudmyla Vesper

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The problems of modern education are large-scale and diverse. The aspirations of parents, teachers, and experts converge - everyone interested in growing up a generation of whole, well-educated persons. Both the family and society are expected in the future generation to be self-sufficient, desirable in the labor market, and capable of lifelong learning. Today's children have a powerful potential that is difficult to realize in the conditions of traditional school approaches. Focusing on STEM education in practice often ends with the simple use of computers and gadgets during class. "Science", "technology", "engineering" and "mathematics" are difficult to combine within school and university curricula, which have not changed much during the last 10 years. Solving the problems of modern education largely depends on teachers - innovators, teachers - practitioners who develop and implement effective educational methods and programs. Teachers who propose innovative pedagogical practices that allow students to master large-scale knowledge and apply it to the practical plane. Effective education considers the creation of stable neural structures during the learning process, which allow to preserve and increase knowledge throughout life. The author proposed a method of integrated lessons – cases based on the maths patterns for forming a holistic perception of the world. This method and program are scientifically substantiated and have more than 15 years of practical application experience in school and student classrooms. The first results of the practical application of the author's methodology and curriculum were announced at the International Conference "Teaching and Learning Strategies to Promote Elementary School Success", 2006, April 22-23, Yerevan, Armenia, IREX-administered 2004-2006 Multiple Component Education Project. This program is based on the concept of interdisciplinary connections and its implementation in the process of continuous learning. This allows students to save and increase knowledge throughout life according to a single pattern. The pattern principle stores information on different subjects according to one scheme (pattern), using long-term memory. This is how neural structures are created. The author also admits that a similar method can be successfully applied to the training of artificial intelligence neural networks. However, this assumption requires further research and verification. The educational method and program proposed by the author meet the modern requirements for education, which involves mastering various areas of knowledge, starting from an early age. This approach makes it possible to involve the child's cognitive potential as much as possible and direct it to the preservation and development of individual talents. According to the methodology, at the early stages of learning students understand the connection between school subjects (so-called "sciences" and "humanities") and in real life, apply the knowledge gained in practice. This approach allows students to realize their natural creative abilities and talents, which makes it easier to navigate professional choices and find their place in life.

Keywords: science education, maths education, AI, neuroplasticity, innovative education problem, creativity development, modern education problem

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Authors: J. Lino Alves, L. Lopes

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It is not new that industrial design projects are a result of cooperative work from different areas of knowledge. However, in the academic teaching of Industrial Design and Mechanical Engineering courses, it is not recurrent that those competences are mixed before the professional life arrives. This abstract intends to describe two semester experiences carried out by two professors - a mechanical engineer and an industrial designer - in the last two academic years, for which they created mixed teams of Industrial Design and Mechanical Engineering (UPorto University). The two experiences differ in several factors; the main one is related to the challenges of online education, a constraint that affected the second experience. In the first year, even before foreseeing the effects that the pandemic would reconfigure the education system, a partnership with the Education Service of Águas do Porto was established. The purpose of the exercise was the project development of a game that could be an interaction element oriented to potentiate a positive experience and as an educational contribution to the children. In the second year, already foreseeing that the teaching experience would be carried out online, it was decided to design an open briefing, which allowed the groups to choose among three themes: a hand scale game using additive manufacturing; a modular system for ventilated facade using a parametric design basis; or, a modular system for vertical gardens. In methodological terms, besides the weekly follow-up, with the simultaneous support of the two professors, a group self-evaluation was requested; and a form to be filled individually to evaluate other groups. One of the first conclusions is related to the briefing format. Industrial Design students seem comfortable working on an open briefing that allows them to draw the project on a conceptual basis created for that purpose; on the other hand, Mechanical Engineering students were uncomfortable and insecure in the initial phase due to the absence of concrete, closed "order." In other words, it is not recurrent for Mechanical Engineering students that the creative component is stimulated, seemingly leaving them reserved to the technical solution and execution, depriving them of the co-creation phase during the conceptual construction of the project's own brief. Another fact that was registered is related to the leadership positions in the groups, which alternated according to the state of development of the project: design students took the lead during the ideation/concept phase, while mechanical engineering ones took a greater lead during the intermediate development process, namely in the definition of constructive solutions, mass/volume calculations, manufacturing, and material resistance. Designers' competences were again more evident and assumed in the final phase, especially in communication skills, as well as in simulations in the context of use. However, at some moments, it was visible the capacity for quite balanced leadership between engineering and design, in a constant debate centered on the human factor of the project - evidenced in the final solution, in the compromise and balance between technical constraints, functionality, usability, and aesthetics.

Keywords: education, industrial design, mechanical engineering, teaching ethodologies

Procedia PDF Downloads 164

Authors: Sukant Mehra, Parth Gupta, Varun Arora, Sarvoday Singh, Amit Kohli

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The study was emphasised on dry sliding wear behavior of AISI 1042 steel. Dry sliding wear tests were performed using pin-on-disk apparatus under normal loads of 5, 7.5 and 10 kgf and at speeds 600, 750 and 900 rpm. Response surface methodology (RSM) was utilized for finding optimal values of process parameter and experiment was based on rotatable, central composite design (CCD). It was found that the wear followed linear pattern with the load and rpm. The obtained optimal process parameters have been predicted and verified by confirmation experiments.

Keywords: central composite design (CCD), optimization, response surface methodology (RSM), wear

Procedia PDF Downloads 562

Authors: A. R. Mirzaee, M. Khajehpour

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Due to Simple Design, reasonable cost and easy implementation most people are reluctant to build buildings with masonry construction. Masonry Structures performance at earthquake are so limited. Of most earthquakes occurred in Iran and other countries, we can easily see that most of the damages are for masonry constructions and this is the evidence that we lack proper understanding of the performance of masonry buildings in earthquake. In this paper, according to field studies, conducted in past earthquakes. To evaluate the strengths and weaknesses points of the masonry constructions and also provide a solution to prevent such damage should be presented, and also program Examples of the correct bearing wall and tie-column design with the valid regulations (MSJC-08 (ASD)) will be explained.

Keywords: Masonry constructions, performance at earthquake, MSJC-08 (ASD), bearing wall, tie-column

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

Procedia PDF Downloads 158

Authors: Achim Kampker, Heiner Hans Heimes, Nemanja Sarovic, Jan-Philip Ganser, Saskia Wessel, Christoph Lienemann

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The electrification of the power train is a fundamental technical transition in the automotive industry and poses a major challenge for established car companies. Providing the traction energy, requiring an ever greater amount of space within the car and having a high share of value-add the lithium-ion battery is a central component of the electric power train and a completely new component to car manufacturers at the same time. Being relatively new to the automotive industry, the current design of the product architecture and production process (including manufacturing and assembling processes) of lithium-ion battery modules do not allow for an easy and cost-efficient disassembly or product design change. Yet these two requirements will increase in importance with rising sales volumes of electric cars in the near future and need to be addressed for the electric car to be competitive with conventional power train systems. This paper focuses on the current product architecture and production process of common automotive battery modules from prismatic lithium-ion battery cells to derive impacts for a remanufacturing concept. The information necessary for this purpose were gathered by literature research, patent inquiries, industry expert interviews and first-hand experiences of the authors. On the basis of these results, the underlying causes for the design´s lack of remanufacturability and flexibility with regards to product design changes are examined. In all, this paper gives an extensive and detailed overview of the state of the art of the product architecture and production process of lithium-ion battery modules from prismatic battery cells, identifies its deficiencies and derives improvement measures.

Keywords: battery module, prismatic lithium-ion battery cell, product architecture, production process, remanufacturing, flexibility

Procedia PDF Downloads 252

Authors: Cesar Vazquez-Gonzalez, Sophie Avila-Foucat, Leonardo Ortiz-Lozano, Patricia Moreno-Casasola, Alejandro Granados-Barba

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In the last twenty years, academic and scientific literature has been focused on understanding the processes and factors of coastal social-ecological systems vulnerability and resilience. Some scholars argue that resilience and vulnerability are isolated concepts due to their epistemological origin, while others note the existence of a strong resilience-vulnerability relationship. Here we present an ordinal logistic regression model based on the analytical framework about dynamic resilience-vulnerability interaction along adaptive cycle of complex systems and disasters process phases (during, recovery and learning). In this way, we demonstrate that 1) during the disturbance, absorptive capacity (resilience as a core of attributes) and external response capacity explain the probability of households capitals to diminish the damage, and exposure sets the thresholds about the amount of disturbance that households can absorb, 2) at recovery, absorptive capacity and external response capacity explain the probability of households capitals to recovery faster (resilience as an outcome) from damage, and 3) at learning, adaptive capacity (resilience as a core of attributes) explains the probability of households adaptation measures based on the enhancement of physical capital. As a result, during the disturbance phase, exposure has the greatest weight in the probability of capital’s damage, and households with absorptive and external response capacity elements absorbed the impact of floods in comparison with households without these elements. At the recovery phase, households with absorptive and external response capacity showed a faster recovery on their capital; however, the damage sets the thresholds of recovery time. More importantly, diversity in financial capital increases the probability of recovering other capital, but it becomes a liability so that the probability of recovering the household finances in a longer time increases. At learning-reorganizing phase, adaptation (modifications to the house) increases the probability of having less damage on physical capital; however, it is not very relevant. As conclusion, resilience is an outcome but also core of attributes that interacts with vulnerability along the adaptive cycle and disaster process phases. Absorptive capacity can diminish the damage experienced by floods; however, when exposure overcomes thresholds, both absorptive and external response capacity are not enough. In the same way, absorptive and external response capacity diminish the recovery time of capital, but the damage sets the thresholds in where households are not capable of recovering their capital.

Keywords: absorptive capacity, adaptive capacity, capital, floods, recovery-learning, social-ecological systems

Procedia PDF Downloads 123