Search results for: teaching models
Commenced in January 2007
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Paper Count: 9481

Search results for: teaching models

751 The Use of Random Set Method in Reliability Analysis of Deep Excavations

Authors: Arefeh Arabaninezhad, Ali Fakher

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Since the deterministic analysis methods fail to take system uncertainties into account, probabilistic and non-probabilistic methods are suggested. Geotechnical analyses are used to determine the stress and deformation caused by construction; accordingly, many input variables which depend on ground behavior are required for geotechnical analyses. The Random Set approach is an applicable reliability analysis method when comprehensive sources of information are not available. Using Random Set method, with relatively small number of simulations compared to fully probabilistic methods, smooth extremes on system responses are obtained. Therefore random set approach has been proposed for reliability analysis in geotechnical problems. In the present study, the application of random set method in reliability analysis of deep excavations is investigated through three deep excavation projects which were monitored during the excavating process. A finite element code is utilized for numerical modeling. Two expected ranges, from different sources of information, are established for each input variable, and a specific probability assignment is defined for each range. To determine the most influential input variables and subsequently reducing the number of required finite element calculations, sensitivity analysis is carried out. Input data for finite element model are obtained by combining the upper and lower bounds of the input variables. The relevant probability share of each finite element calculation is determined considering the probability assigned to input variables present in these combinations. Horizontal displacement of the top point of excavation is considered as the main response of the system. The result of reliability analysis for each intended deep excavation is presented by constructing the Belief and Plausibility distribution function (i.e. lower and upper bounds) of system response obtained from deterministic finite element calculations. To evaluate the quality of input variables as well as applied reliability analysis method, the range of displacements extracted from models has been compared to the in situ measurements and good agreement is observed. The comparison also showed that Random Set Finite Element Method applies to estimate the horizontal displacement of the top point of deep excavation. Finally, the probability of failure or unsatisfactory performance of the system is evaluated by comparing the threshold displacement with reliability analysis results.

Keywords: deep excavation, random set finite element method, reliability analysis, uncertainty

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750 The Maps of Meaning (MoM) Consciousness Theory

Authors: Scott Andersen

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Perhaps simply and rather unadornedly, consciousness is having multiple goals for action and the continuously adjudication of such goals to implement action, referred to as the Maps of Meaning (MoM) Consciousness Theory. The MoM theory triangulates through three parallel corollaries, action (behavior), mechanism (morphology/pathophysiology), and goals (teleology). (1) An organism’s consciousness contains a fluid, nested goals. These goals are not intentionality, but intersectionality, embodiment meeting the world. i.e., Darwinian inclusive fitness or randomization, then survival of the fittest. These goals form via gradual descent under inclusive fitness, the goals being the abstraction of a ‘match’ between the evolutionary environment and organism. Human consciousness implements the brain efficiency hypothesis, genetics, epigenetics, and experience crystallize efficiencies, not necessitating best or objective but fitness, i.e., perceived efficiency based on one’s adaptive environment. These efficiencies are objectively arbitrary, but determine the operation and level of one’s consciousness, termed extreme thrownness. Since inclusive fitness drives efficiencies in physiologic mechanism, morphology and behavior (action) and originates one’s goals, embodiment is necessarily entangled to human consciousness as its the intersection of mechanism or action (both necessitating embodiment) occurring in the world that determines fitness. Perception is the operant process of consciousness and is the consciousness’ de facto goal adjudication process. Goal operationalization is fundamentally efficiency-based via one’s unique neuronal mapping as a byproduct of genetics, epigenetics, and experience. Perception involves information intake and information discrimination, equally underpinned by efficiencies of inclusive fitness via extreme thrownness. Perception isn’t a ‘frame rate,’ but Bayesian priors of efficiency based on one’s extreme thrownness. Consciousness and human consciousness is a modular (i.e., a scalar level of richness, which builds up like building blocks) and dimensionalized (i.e., cognitive abilities become possibilities as emergent phenomena at various modularities, like stratified factors in factor analysis). The meta dimensions of human consciousness seemingly include intelligence quotient, personality (five-factor model), richness of perception intake, and richness of perception discrimination, among other potentialities. Future consciousness research should utilize factor analysis to parse modularities and dimensions of human consciousness and animal models.

Keywords: consciousness, perception, prospection, embodiment

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749 The Environmental Impacts of Textiles Reuse and Recycling: A Review on Life-Cycle-Assessment Publications

Authors: Samuele Abagnato, Lucia Rigamonti

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Life-Cycle-Assessment (LCA) is an effective tool to quantify the environmental impacts of reuse models and recycling technologies for textiles. In this work, publications in the last ten years about LCA on textile waste are classified according to location, goal and scope, functional unit, waste composition, impact assessment method, impact categories, and sensitivity analysis. Twenty papers have been selected: 50% are focused only on recycling, 30% only on reuse, the 15% on both, while only one paper considers only the final disposal of the waste. It is found that reuse is generally the best way to decrease the environmental impacts of textiles waste management because of the avoided impacts of manufacturing a new item. In the comparison between a product made with recycled yarns and a product from virgin materials, in general, the first option is less impact, especially for the categories of climate change, water depletion, and land occupation, while for other categories, such as eutrophication or ecotoxicity, under certain conditions the impacts of the recycled fibres can be higher. Cultivation seems to have quite high impacts when natural fibres are involved, especially in the land use and water depletion categories, while manufacturing requires a remarkable amount of electricity, with its associated impact on climate change. In the analysis of the reuse processes, relevant importance is covered by the laundry phase, with water consumption and impacts related to the use of detergents. About the sensitivity analysis, it can be stated that one of the main variables that influence the LCA results and that needs to be further investigated in the modeling of the LCA system about this topic is the substitution rate between recycled and virgin fibres, that is the amount of recycled material that can be used in place of virgin one. Related to this, also the yield of the recycling processes has a strong influence on the results of the impact. The substitution rate is also important in the modeling of the reuse processes because it represents the number of avoided new items bought in place of the reused ones. Another aspect that appears to have a large influence on the impacts is consumer behaviour during the use phase (for example, the number of uses between two laundry cycles). In conclusion, to have a deeper knowledge of the impacts of a life-cycle approach of textile waste, further data and research are needed in the modeling of the substitution rate and of the use phase habits of the consumers.

Keywords: environmental impacts, life-cycle-assessment, textiles recycling, textiles reuse, textiles waste management

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748 Factors Affecting Cesarean Section among Women in Qatar Using Multiple Indicator Cluster Survey Database

Authors: Sahar Elsaleh, Ghada Farhat, Shaikha Al-Derham, Fasih Alam

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Background: Cesarean section (CS) delivery is one of the major concerns both in developing and developed countries. The rate of CS deliveries are on the rise globally, and especially in Qatar. Many socio-economic, demographic, clinical and institutional factors play an important role for cesarean sections. This study aims to investigate factors affecting the prevalence of CS among women in Qatar using the UNICEF’s Multiple Indicator Cluster Survey (MICS) 2012 database. Methods: The study has focused on the women’s questionnaire of the MICS, which was successfully distributed to 5699 participants. Following study inclusion and exclusion criteria, a final sample of 761 women aged 19- 49 years who had at least one delivery of giving birth in their lifetime before the survey were included. A number of socio-economic, demographic, clinical and institutional factors, identified through literature review and available in the data, were considered for the analyses. Bivariate and multivariate logistic regression models, along with a multi-level modeling to investigate clustering effect, were undertaken to identify the factors that affect CS prevalence in Qatar. Results: From the bivariate analyses the study has shown that, a number of categorical factors are statistically significantly associated with the dependent variable (CS). When identifying the factors from a multivariate logistic regression, the study found that only three categorical factors -‘age of women’, ‘place at delivery’ and ‘baby weight’ appeared to be significantly affecting the CS among women in Qatar. Although the MICS dataset is based on a cluster survey, an exploratory multi-level analysis did not show any clustering effect, i.e. no significant variation in results at higher level (households), suggesting that all analyses at lower level (individual respondent) are valid without any significant bias in results. Conclusion: The study found a statistically significant association between the dependent variable (CS delivery) and age of women, frequency of TV watching, assistance at birth and place of birth. These results need to be interpreted cautiously; however, it can be used as evidence-base for further research on cesarean section delivery in Qatar.

Keywords: cesarean section, factors, multiple indicator cluster survey, MICS database, Qatar

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747 Opening of North Sea Route and Geopolitics in Arctic: Impact and Possibilities of Route

Authors: Nikkey Keshri

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Arctic is a polar region located at the north of the earth. This consists of the Arctic Ocean and other parts of Canada, Russia, the United States, Denmark, Norway, Sweden, Finland, and Iceland. Arctic has vast natural resources which are exploited with modern technology, and the economic opening up of Russia has given new opportunities. All these states have connected with the Arctic region for economic activities and this effect the region ecology. The pollution problem is a serious threat to the people health living around pollution sources. Due to the prevailing worldwide sea and air currents, the Arctic area is the fallout region for long-range transport pollutants, and in some places the concentrations exceed the levels of densely populated urban areas. The Arctic is especially vulnerable to the effects of global warming, as has become apparent in the melting sea ice in recent years. Climate models predict much greater warming in the Arctic than the global average, resulting in significant international attention to the region. The global warming has an adverse impact on the climate, indigenous people, wildlife, and infrastructure. However, there are several opportunities that have emerged in the form of shipping routes, resources, and new territories. The shipping route through the Arctic is a reality and is currently navigable for a few weeks during summers. There are large deposits of oil and gas, minerals and fish and the surrounding countries with Arctic coastlines are becoming quite assertive about exercising their sovereignty over the newfound wealth. The main part of the research is that how the opening of Northern Sea Route is providing opportunities or problem in the Arctic and it is becoming geopolitically important. It focuses on the interest Arctic and non Arctic states, their present and anticipated global geopolitical aims. The Northern Sea Route might open up due to climate changes and that Iceland might benefit or has an impact from the situation. Efforts will be made to answer the research question: ‘Whether Opening of North Sea Route is providing opportunities or becoming a risk for Arctic region?’ Every research has a structure which usually called design. In this research, both Qualitative and Quantitative method is used in terms of various literature, maps, pie- charts, etc to find out the answer for the research question. The aim of this research is to find out the impact of Opening of North Sea Route over Arctic region and how this make arctic geopolitically important. The aim behind this research is to find out the impact of climate change and how the particular geographical area is being affected.

Keywords: climate change, geopolitics, international relation, Northern Sea Route

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746 Bionaut™: A Minimally Invasive Microsurgical Platform to Treat Non-Communicating Hydrocephalus in Dandy-Walker Malformation

Authors: Suehyun Cho, Darrell Harrington, Florent Cros, Olin Palmer, John Caputo, Michael Kardosh, Eran Oren, William Loudon, Alex Kiselyov, Michael Shpigelmacher

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The Dandy-Walker malformation (DWM) represents a clinical syndrome manifesting as a combination of posterior fossa cyst, hypoplasia of the cerebellar vermis, and obstructive hydrocephalus. Anatomic hallmarks include hypoplasia of the cerebellar vermis, enlargement of the posterior fossa, and cystic dilatation of the fourth ventricle. Current treatments of DWM, including shunting of the cerebral spinal fluid ventricular system and endoscopic third ventriculostomy (ETV), are frequently clinically insufficient, require additional surgical interventions, and carry risks of infections and neurological deficits. Bionaut Labs develops an alternative way to treat Dandy-Walker Malformation (DWM) associated with non-communicating hydrocephalus. We utilize our discreet microsurgical Bionaut™ particles that are controlled externally and remotely to perform safe, accurate, effective fenestration of the Dandy-Walker cyst, specifically in the posterior fossa of the brain, to directly normalize intracranial pressure. Bionaut™ allows for complex non-linear trajectories not feasible by any conventional surgical techniques. The microsurgical particle safely reaches targets in the lower occipital section of the brain. Bionaut™ offers a minimally invasive surgical alternative to highly involved posterior craniotomy or shunts via direct fenestration of the fourth ventricular cyst at the locus defined by the individual anatomy. Our approach offers significant advantages over the current standards of care in patients exhibiting anatomical challenge(s) as a manifestation of DWM, and therefore, is intended to replace conventional therapeutic strategies. Current progress, including platform optimization, Bionaut™ control, and real-time imaging and in vivo safety studies of the Bionauts™ in large animals, specifically the spine and the brain of ovine models, will be discussed.

Keywords: Bionaut™, cerebral spinal fluid, CSF, cyst, Dandy-Walker, fenestration, hydrocephalus, micro-robot

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745 Innovations in the Implementation of Preventive Strategies and Measuring Their Effectiveness Towards the Prevention of Harmful Incidents to People with Mental Disabilities who Receive Home and Community Based Services

Authors: Carlos V. Gonzalez

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Background: Providers of in-home and community based services strive for the elimination of preventable harm to the people under their care as well as to the employees who support them. Traditional models of safety and protection from harm have assumed that the absence of incidents of harm is a good indicator of safe practices. However, this model creates an illusion of safety that is easily shaken by sudden and inadvertent harmful events. As an alternative, we have developed and implemented an evidence-based resilient model of safety known as C.O.P.E. (Caring, Observing, Predicting and Evaluating). Within this model, safety is not defined by the absence of harmful incidents, but by the presence of continuous monitoring, anticipation, learning, and rapid response to events that may lead to harm. Objective: The objective was to evaluate the effectiveness of the C.O.P.E. model for the reduction of harm to individuals with mental disabilities who receive home and community based services. Methods: Over the course of 2 years we counted the number of incidents of harm and near misses. We trained employees on strategies to eliminate incidents before they fully escalated. We trained employees to track different levels of patient status within a scale from 0 to 10. Additionally, we provided direct support professionals and supervisors with customized smart phone applications to track and notify the team of changes in that status every 30 minutes. Finally, the information that we collected was saved in a private computer network that analyzes and graphs the outcome of each incident. Result and conclusions: The use of the COPE model resulted in: A reduction in incidents of harm. A reduction the use of restraints and other physical interventions. An increase in Direct Support Professional’s ability to detect and respond to health problems. Improvement in employee alertness by decreasing sleeping on duty. Improvement in caring and positive interaction between Direct Support Professionals and the person who is supported. Developing a method to globally measure and assess the effectiveness of prevention from harm plans. Future applications of the COPE model for the reduction of harm to people who receive home and community based services are discussed.

Keywords: harm, patients, resilience, safety, mental illness, disability

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744 An Alternative to Problem-Based Learning in a Post-Graduate Healthcare Professional Programme

Authors: Brogan Guest, Amy Donaldson-Perrott

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The Master’s of Physician Associate Studies (MPAS) programme at St George’s, University of London (SGUL), is an intensive two-year course that trains students to become physician associates (PAs). PAs are generalized healthcare providers who work in primary and secondary care across the UK. PA programmes face the difficult task of preparing students to become safe medical providers in two short years. Our goal is to teach students to develop clinical reasoning early on in their studies and historically, this has been done predominantly though problem-based learning (PBL). We have had an increase concern about student engagement in PBL and difficulty recruiting facilitators to maintain the low student to facilitator ratio required in PBL. To address this issue, we created ‘Clinical Application of Anatomy and Physiology (CAAP)’. These peer-led, interactive, problem-based, small group sessions were designed to facilitate students’ clinical reasoning skills. The sessions were designed using the concept of Team-Based Learning (TBL). Students were divided into small groups and each completed a pre-session quiz consisting of difficult questions devised to assess students’ application of medical knowledge. The quiz was completed in small groups and they were not permitted access of external resources. After the quiz, students worked through a series of openended, clinical tasks using all available resources. They worked at their own pace and the session was peer-led, rather than facilitator-driven. For a group of 35 students, there were two facilitators who observed the sessions. The sessions utilised an infinite space whiteboard software. Each group member was encouraged to actively participate and work together to complete the 15-20 tasks. The session ran for 2 hours and concluded with a post-session quiz, identical to the pre-session quiz. We obtained subjective feedback from students on their experience with CAAP and evaluated the objective benefit of the sessions through the quiz results. Qualitative feedback from students was generally positive with students feeling the sessions increased engagement, clinical understanding, and confidence. They found the small group aspect beneficial and the technology easy to use and intuitive. They also liked the benefit of building a resource for their future revision, something unique to CAAP compared to PBL, which out students participate in weekly. Preliminary quiz results showed improvement from pre- and post- session; however, further statistical analysis will occur once all sessions are complete (final session to run December 2022) to determine significance. As a post-graduate healthcare professional programme, we have a strong focus on self-directed learning. Whilst PBL has been a mainstay in our curriculum since its inception, there are limitations and concerns about its future in view of student engagement and facilitator availability. Whilst CAAP is not TBL, it draws on the benefits of peer-led, small group work with pre- and post- team-based quizzes. The pilot of these sessions has shown that students are engaged by CAAP, and they can make significant progress in clinical reasoning in a short amount of time. This can be achieved with a high student to facilitator ratio.

Keywords: problem based learning, team based learning, active learning, peer-to-peer teaching, engagement

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743 Comparison of Spiral Circular Coil and Helical Coil Structures for Wireless Power Transfer System

Authors: Zhang Kehan, Du Luona

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Wireless power transfer (WPT) systems have been widely investigated for advantages of convenience and safety compared to traditional plug-in charging systems. The research contents include impedance matching, circuit topology, transfer distance et al. for improving the efficiency of WPT system, which is a decisive factor in the practical application. What is more, coil structures such as spiral circular coil and helical coil with variable distance between two turns also have indispensable effects on the efficiency of WPT systems. This paper compares the efficiency of WPT systems utilizing spiral or helical coil with variable distance between two turns, and experimental results show that efficiency of spiral circular coil with an optimum distance between two turns is the highest. According to efficiency formula of resonant WPT system with series-series topology, we introduce M²/R₋₁ to measure the efficiency of spiral circular coil and helical coil WPT system. If the distance between two turns s is too close, proximity effect theory shows that the induced current in the conductor, caused by a variable flux created by the current flows in the skin of vicinity conductor, is the opposite direction of source current and has assignable impart on coil resistance. Thus in two coil structures, s affects coil resistance. At the same time, when the distance between primary and secondary coils is not variable, s can also make the influence on M to some degrees. The aforementioned study proves that s plays an indispensable role in changing M²/R₋₁ and then can be adjusted to find the optimum value with which WPT system achieves the highest efficiency. In actual application situations of WPT systems especially in underwater vehicles, miniaturization is one vital issue in designing WPT system structures. Limited by system size, the largest external radius of spiral circular coil is 100 mm, and the largest height of helical coil is 40 mm. In other words, the turn of coil N changes with s. In spiral circular and helical structures, the distance between each two turns in secondary coil is set as a constant value 1 mm to guarantee that the R2 is not variable. Based on the analysis above, we set up spiral circular coil and helical coil model using COMSOL to analyze the value of M²/R₋₁ when the distance between each two turns in primary coil sp varies from 0 mm to 10 mm. In the two structure models, the distance between primary and secondary coils is 50 mm and wire diameter is chosen as 1.5 mm. The turn of coil in secondary coil are 27 in helical coil model and 20 in spiral circular coil model. The best value of s in helical coil structure and spiral circular coil structure are 1 mm and 2 mm respectively, in which the value of M²/R₋₁ is the largest. It is obviously to select spiral circular coil as the first choice to design the WPT system for that the value of M²/R₋₁ in spiral circular coil is larger than that in helical coil under the same condition.

Keywords: distance between two turns, helical coil, spiral circular coil, wireless power transfer

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742 Measuring Self-Regulation and Self-Direction in Flipped Classroom Learning

Authors: S. A. N. Danushka, T. A. Weerasinghe

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The diverse necessities of instruction could be addressed effectively with the support of new dimensions of ICT integrated learning such as blended learning –which is a combination of face-to-face and online instruction which ensures greater flexibility in student learning and congruity of course delivery. As blended learning has been the ‘new normality' in education, many experimental and quasi-experimental research studies provide ample of evidence on its successful implementation in many fields of studies, but it is hard to justify whether blended learning could work similarly in the delivery of technology-teacher development programmes (TTDPs). The present study is bound with the particular research uncertainty, and having considered existing research approaches, the study methodology was set to decide the efficient instructional strategies for flipped classroom learning in TTDPs. In a quasi-experimental pre-test and post-test design with a mix-method research approach, the major study objective was tested with two heterogeneous samples (N=135) identified in a virtual learning environment in a Sri Lankan university. Non-randomized informal ‘before-and-after without control group’ design was employed, and two data collection methods, identical pre-test and post-test and Likert-scale questionnaires were used in the study. Selected two instructional strategies, self-directed learning (SDL) and self-regulated learning (SRL), were tested in an appropriate instructional framework with two heterogeneous samples (pre-service and in-service teachers). Data were statistically analyzed, and an efficient instructional strategy was decided via t-test, ANOVA, ANCOVA. The effectiveness of the two instructional strategy implementation models was decided via multiple linear regression analysis. ANOVA (p < 0.05) shows that age, prior-educational qualifications, gender, and work-experiences do not impact on learning achievements of the two diverse groups of learners through the instructional strategy is changed. ANCOVA (p < 0.05) analysis shows that SDL is efficient for two diverse groups of technology-teachers than SRL. Multiple linear regression (p < 0.05) analysis shows that the staged self-directed learning (SSDL) model and four-phased model of motivated self-regulated learning (COPES Model) are efficient in the delivery of course content in flipped classroom learning.

Keywords: COPES model, flipped classroom learning, self-directed learning, self-regulated learning, SSDL model

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741 Influence of 3D Printing Parameters on Surface Finish of Ceramic Hip Prostheses Fixed by Means of Osteointegration

Authors: Irene Buj-Corral, Ali Bagheri, Alejandro Dominguez-Fernandez

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In recent years, use of ceramic prostheses as an implant in some parts of body has become common. In the present study, research has focused on replacement of the acetabulum bone, which is a part of the pelvis bone. Metallic prostheses have shown some problems such as release of metal ions into patient's blood. In addition, fracture of liners and squeezing between surface of femoral head and inner surface of acetabulum have been reported. Ceramic prostheses have the advantage of low debris and high strength, although they are more difficult to be manufactured than metallic ones. Specifically, new designs try to attempt an acetabulum in which the outer surface will be porous for proliferation of cells and fixation of the prostheses by means of osteointegration, while inner surface must be smooth enough to assure that the movement between femoral head and inner surface will be carried out with on feasibility. In the present study, 3D printing technologies are used for manufacturing ceramic prostheses. In Fused Deposition Modelling (FDM) process, 3D printed plastic prostheses are obtained by means of melting of a plastic filament and subsequent deposition on a glass surface. A similar process is applied to ceramics in which ceramic powders need to be mixed with a liquid polymer before depositing them. After 3D printing, parts are subjected to a sintering process in an oven so that they can achieve final strength. In the present paper, influence of printing parameters on surface roughness 3D printed ceramic parts are presented. Three parameter full factorial design of experiments was used. Selected variables were layer height, infill and nozzle diameter. Responses were average roughness Ra and mean roughness depth Rz. Regression analysis was applied to responses in order to obtain mathematical models for responses. Results showed that surface roughness depends mainly on layer height and nozzle diameter employed, while infill was found not to be significant. In order to get low surface roughness, low layer height and low infill should be selected. As a conclusion, layer height and infill are important parameters for obtaining good surface finish in ceramic 3D printed prostheses. However, use of too low infill could lead to prostheses with low mechanical strength. Such prostheses could not be able to bear the static and dynamic charges to which they are subjected once they are implanted in the body. This issue will be addressed in further research.

Keywords: ceramic, hip prostheses, surface roughness, 3D printing

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740 Gamification of eHealth Business Cases to Enhance Rich Learning Experience

Authors: Kari Björn

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Introduction of games has expanded the application area of computer-aided learning tools to wide variety of age groups of learners. Serious games engage the learners into a real-world -type of simulation and potentially enrich the learning experience. Institutional background of a Bachelor’s level engineering program in Information and Communication Technology is introduced, with detailed focus on one of its majors, Health Technology. As part of a Customer Oriented Software Application thematic semester, one particular course of “eHealth Business and Solutions” is described and reflected in a gamified framework. Learning a consistent view into vast literature of business management, strategies, marketing and finance in a very limited time enforces selection of topics relevant to the industry. Health Technology is a novel and growing industry with a growing sector in consumer wearable devices and homecare applications. The business sector is attracting new entrepreneurs and impatient investor funds. From engineering education point of view the sector is driven by miniaturizing electronics, sensors and wireless applications. However, the market is highly consumer-driven and usability, safety and data integrity requirements are extremely high. When the same technology is used in analysis or treatment of patients, very strict regulatory measures are enforced. The paper introduces a course structure using gamification as a tool to learn the most essential in a new market: customer value proposition design, followed by a market entry game. Students analyze the existing market size and pricing structure of eHealth web-service market and enter the market as a steering group of their company, competing against the legacy players and with each other. The market is growing but has its rules of demand and supply balance. New products can be developed with an R&D-investment, and targeted to market with unique quality- and price-combinations. Product cost structure can be improved by investing to enhanced production capacity. Investments can be funded optionally by foreign capital. Students make management decisions and face the dynamics of the market competition in form of income statement and balance sheet after each decision cycle. The focus of the learning outcome is to understand customer value creation to be the source of cash flow. The benefit of gamification is to enrich the learning experience on structure and meaning of financial statements. The paper describes the gamification approach and discusses outcomes after two course implementations. Along the case description of learning challenges, some unexpected misconceptions are noted. Improvements of the game or the semi-gamified teaching pedagogy are discussed. The case description serves as an additional support to new game coordinator, as well as helps to improve the method. Overall, the gamified approach has helped to engage engineering student to business studies in an energizing way.

Keywords: engineering education, integrated curriculum, learning experience, learning outcomes

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739 In silico Statistical Prediction Models for Identifying the Microbial Diversity and Interactions Due to Fixed Periodontal Appliances

Authors: Suganya Chandrababu, Dhundy Bastola

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Like in the gut, the subgingival microbiota plays a crucial role in oral hygiene, health, and cariogenic diseases. Human activities like diet, antibiotics, and periodontal treatments alter the bacterial communities, metabolism, and functions in the oral cavity, leading to a dysbiotic state and changes in the plaques of orthodontic patients. Fixed periodontal appliances hinder oral hygiene and cause changes in the dental plaques influencing the subgingival microbiota. However, the microbial species’ diversity and complexity pose a great challenge in understanding the taxa’s community distribution patterns and their role in oral health. In this research, we analyze the subgingival microbial samples from individuals with fixed dental appliances (metal/clear) using an in silico approach. We employ exploratory hypothesis-driven multivariate and regression analysis to shed light on the microbial community and its functional fluctuations due to dental appliances used and identify risks associated with complex disease phenotypes. Our findings confirm the changes in oral microbiota composition due to the presence and type of fixed orthodontal devices. We identified seven main periodontic pathogens, including Bacteroidetes, Actinobacteria, Proteobacteria, Fusobacteria, and Firmicutes, whose abundances were significantly altered due to the presence and type of fixed appliances used. In the case of metal braces, the abundances of Bacteroidetes, Proteobacteria, Fusobacteria, Candidatus saccharibacteria, and Spirochaetes significantly increased, while the abundance of Firmicutes and Actinobacteria decreased. However, in individuals With clear braces, the abundance of Bacteroidetes and Candidatus saccharibacteria increased. The highest abundance value (P-value=0.004 < 0.05) was observed with Bacteroidetes in individuals with the metal appliance, which is associated with gingivitis, periodontitis, endodontic infections, and odontogenic abscesses. Overall, the bacterial abundances decrease with clear type and increase with metal type of braces. Regression analysis further validated the multivariate analysis of variance (MANOVA) results, supporting the hypothesis that the presence and type of the fixed oral appliances significantly alter the bacterial abundance and composition.

Keywords: oral microbiota, statistical analysis, fixed or-thodontal appliances, bacterial abundance, multivariate analysis, regression analysis

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738 Second Time’s a Charm: The Intervention of the European Patent Office on the Strategic Use of Divisional Applications

Authors: Alissa Lefebre

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It might seem intuitive to hope for a fast decision on the patent grant. After all, a granted patent provides you with a monopoly position, which allows you to obstruct others from using your technology. However, this does not take into account the strategic advantages one can obtain from keeping their patent applications pending. First, you have the financial advantage of postponing certain fees, although many applicants would probably agree that this is not the main benefit. As the scope of the patent protection is only decided upon at the grant, the pendency period introduces uncertainty amongst rivals. This uncertainty entails not knowing whether the patent will actually get granted and what the scope of protection will be. Consequently, rivals can only depend upon limited and uncertain information when deciding what technology is worth pursuing. One way to keep patent applications pending, is the use of divisional applications. These applicants can be filed out of a parent application as long as that parent application is still pending. This allows the applicant to pursue (part of) the content of the parent application in another application, as the divisional application cannot exceed the scope of the parent application. In a fast-moving and complex market such as the tele- and digital communications, it might allow applicants to obtain an actual monopoly position as competitors are discouraged to pursue a certain technology. Nevertheless, this practice also has downsides to it. First of all, it has an impact on the workload of the examiners at the patent office. As the number of patent filings have been increasing over the last decades, using strategies that increase this number even more, is not desirable from the patent examiners point of view. Secondly, a pending patent does not provide you with the protection of a granted patent, thus not only create uncertainty for the rivals, but also for the applicant. Consequently, the European patent office (EPO) has come up with a “raising the bar initiative” in which they have decided to tackle the strategic use of divisional applications. Over the past years, two rules have been implemented. The first rule in 2010 introduced a time limit, upon which divisional applications could only be filed within a 24-month limit after the first communication with the patent office. However, after carrying-out a user feedback survey, the EPO abolished the rule again in 2014 and replaced it by a fee mechanism. The fee mechanism is still in place today, which might be an indication of a better result compared to the first rule change. This study tests the impact of these rules on the strategic use of divisional applications in the tele- and digital communication industry and provides empirical evidence on their success. Upon using three different survival models, we find overall evidence that divisional applications prolong the pendency time and that only the second rule is able to tackle the strategic patenting and thus decrease the pendency time.

Keywords: divisional applications, regulatory changes, strategic patenting, EPO

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737 Nutrition Program Planning Based on Local Resources in Urban Fringe Areas of a Developing Country

Authors: Oktia Woro Kasmini Handayani, Bambang Budi Raharjo, Efa Nugroho, Bertakalswa Hermawati

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Obesity prevalence and severe malnutrition in Indonesia has increased from 2007 to 2013. The utilization of local resources in nutritional program planning can be used to program efficiency and to reach the goal. The aim of this research is to plan a nutrition program based on local resources for urban fringe areas in a developing country. This research used a qualitative approach, with a focus on local resources including social capital, social system, cultural system. The study was conducted in Mijen, Central Java, as one of the urban fringe areas in Indonesia. Purposive and snowball sampling techniques are used to determine participants. A total of 16 participants took part in the study. Observation, interviews, focus group discussion, SWOT analysis, brainstorming and Miles and Huberman models were used to analyze the data. We have identified several local resources, such as the contributions from nutrition cadres, social organizations, social financial resources, as well as the cultural system and social system. The outstanding contribution of nutrition cadres is the participation and creativity to improve nutritional status. In addition, social organizations, like the role of the integrated health center for children (Pos Pelayanan Terpadu), can be engaged in the nutrition program planning. This center is supported by House of Nutrition to assist in nutrition program planning, and provide social support to families, neighbors and communities as social capitals. The study also reported that cultural systems that show appreciation for well-nourished children are a better way to improve the problem of balanced nutrition. Social systems such as teamwork and mutual cooperation can also be a potential resource to support nutritional programs and overcome associated problems. The impact of development in urban areas such as the introduction of more green areas which improve the perceived status of local people, as well as new health services facilitated by people and companies, can also be resources to support nutrition programs. Local resources in urban fringe areas can be used in the planning of nutrition programs. The expansion of partnership with all stakeholders, empowering the community through optimizing the roles of nutrition care centers for children as our recommendation with regard to nutrition program planning.

Keywords: developing country, local resources, nutrition program, urban fringe

Procedia PDF Downloads 235
736 Cytokine Profiling in Cultured Endometrial Cells after Hormonal Treatment

Authors: Mark Gavriel, Ariel J. Jaffa, Dan Grisaru, David Elad

Abstract:

The human endometrium-myometrium interface (EMI) is the uterine inner barrier without a separatig layer. It is composed of endometrial epithelial cells (EEC) and endometrial stromal cells (ESC) in the endometrium and myometrial smooth muscle cells (MSMC) in the myometrium. The EMI undergoes structural remodeling during the menstruation cycle which are essential for human reproduction. Recently, we co-cultured a layer-by-layer in vitro model of EEC, ESC and MSMC on a synthetic membrane for mechanobiology experiments. We also treated the model with progesterone and β-estradiol in order to mimic the in vivo receptive uterus In the present study we analyzed the cytokines profile in a single layer of EEC the hormonal treated in vitro model of the EMI. The methodologies of this research include simple tissue-engineering . First, we cultured commercial EEC (RL95-2, ATCC® CRL-1671™) in 24-wellplate. Then, we applied an hormonal stimuli protocol with 17-β-estradiol and progesterone in time dependent concentration according to the human physiology that mimics the menstrual cycle. We collected cell supernatant samples of control, pre-ovulation, ovulation and post-ovulaton periods for analysis of the secreted proteins and cytokines. The cytokine profiling was performed using the Proteome Profiler Human XL Cytokine Array Kit (R&D Systems, Inc., USA) that can detect105 human soluble cytokines. The relative quantification of all the cytokines will be analyzed using xMAP – LUMINEX. We conducted a fishing expedition with the 4 membranes Proteome Profiler. We processed the images, quantified the spots intensity and normalized these values by the negative control and reference spots at the membrane. Analyses of the relative quantities that reflected change higher than 5% of the control points of the kit revealed the The results clearly showed that there are significant changes in the cytokine level for inflammation and angiogenesis pathways. Analysis of tissue-engineered models of the uterine wall will enable deeper investigation of molecular and biomechanical aspects of early reproductive stages (e.g. the window of implantation) or developments of pathologies.

Keywords: tissue-engineering, hormonal stimuli, reproduction, multi-layer uterine model, progesterone, β-estradiol, receptive uterine model, fertility

Procedia PDF Downloads 106
735 Structuring Highly Iterative Product Development Projects by Using Agile-Indicators

Authors: Guenther Schuh, Michael Riesener, Frederic Diels

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Nowadays, manufacturing companies are faced with the challenge of meeting heterogeneous customer requirements in short product life cycles with a variety of product functions. So far, some of the functional requirements remain unknown until late stages of the product development. A way to handle these uncertainties is the highly iterative product development (HIP) approach. By structuring the development project as a highly iterative process, this method provides customer oriented and marketable products. There are first approaches for combined, hybrid models comprising deterministic-normative methods like the Stage-Gate process and empirical-adaptive development methods like SCRUM on a project management level. However, almost unconsidered is the question, which development scopes can preferably be realized with either empirical-adaptive or deterministic-normative approaches. In this context, a development scope constitutes a self-contained section of the overall development objective. Therefore, this paper focuses on a methodology that deals with the uncertainty of requirements within the early development stages and the corresponding selection of the most appropriate development approach. For this purpose, internal influencing factors like a company’s technology ability, the prototype manufacturability and the potential solution space as well as external factors like the market accuracy, relevance and volatility will be analyzed and combined into an Agile-Indicator. The Agile-Indicator is derived in three steps. First of all, it is necessary to rate each internal and external factor in terms of the importance for the overall development task. Secondly, each requirement has to be evaluated for every single internal and external factor appropriate to their suitability for empirical-adaptive development. Finally, the total sums of internal and external side are composed in the Agile-Indicator. Thus, the Agile-Indicator constitutes a company-specific and application-related criterion, on which the allocation of empirical-adaptive and deterministic-normative development scopes can be made. In a last step, this indicator will be used for a specific clustering of development scopes by application of the fuzzy c-means (FCM) clustering algorithm. The FCM-method determines sub-clusters within functional clusters based on the empirical-adaptive environmental impact of the Agile-Indicator. By means of the methodology presented in this paper, it is possible to classify requirements, which are uncertainly carried out by the market, into empirical-adaptive or deterministic-normative development scopes.

Keywords: agile, highly iterative development, agile-indicator, product development

Procedia PDF Downloads 224
734 “I” on the Web: Social Penetration Theory Revised

Authors: Dr. Dionysis Panos Dpt. Communication, Internet Studies Cyprus University of Technology

Abstract:

The widespread use of New Media and particularly Social Media, through fixed or mobile devices, has changed in a staggering way our perception about what is “intimate" and "safe" and what is not, in interpersonal communication and social relationships. The distribution of self and identity-related information in communication now evolves under new and different conditions and contexts. Consequently, this new framework forces us to rethink processes and mechanisms, such as what "exposure" means in interpersonal communication contexts, how the distinction between the "private" and the "public" nature of information is being negotiated online, how the "audiences" we interact with are understood and constructed. Drawing from an interdisciplinary perspective that combines sociology, communication psychology, media theory, new media and social networks research, as well as from the empirical findings of a longitudinal comparative research, this work proposes an integrative model for comprehending mechanisms of personal information management in interpersonal communication, which can be applied to both types of online (Computer-Mediated) and offline (Face-To-Face) communication. The presentation is based on conclusions drawn from a longitudinal qualitative research study with 458 new media users from 24 countries for almost over a decade. Some of these main conclusions include: (1) There is a clear and evidenced shift in users’ perception about the degree of "security" and "familiarity" of the Web, between the pre- and the post- Web 2.0 era. The role of Social Media in this shift was catalytic. (2) Basic Web 2.0 applications changed dramatically the nature of the Internet itself, transforming it from a place reserved for “elite users / technical knowledge keepers" into a place of "open sociability” for anyone. (3) Web 2.0 and Social Media brought about a significant change in the concept of “audience” we address in interpersonal communication. The previous "general and unknown audience" of personal home pages, converted into an "individual & personal" audience chosen by the user under various criteria. (4) The way we negotiate the nature of 'private' and 'public' of the Personal Information, has changed in a fundamental way. (5) The different features of the mediated environment of online communication and the critical changes occurred since the Web 2.0 advance, lead to the need of reconsideration and updating the theoretical models and analysis tools we use in our effort to comprehend the mechanisms of interpersonal communication and personal information management. Therefore, is proposed here a new model for understanding the way interpersonal communication evolves, based on a revision of social penetration theory.

Keywords: new media, interpersonal communication, social penetration theory, communication exposure, private information, public information

Procedia PDF Downloads 345
733 Evaluation of the CRISP-DM Business Understanding Step: An Approach for Assessing the Predictive Power of Regression versus Classification for the Quality Prediction of Hydraulic Test Results

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

Digitalisation in production technology is a driver for the application of machine learning methods. Through the application of predictive quality, the great potential for saving necessary quality control can be exploited through the data-based prediction of product quality and states. However, the serial use of machine learning applications is often prevented by various problems. Fluctuations occur in real production data sets, which are reflected in trends and systematic shifts over time. To counteract these problems, data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets to extract stable features. Successful process control of the target variables aims to centre the measured values around a mean and minimise variance. Competitive leaders claim to have mastered their processes. As a result, much of the real data has a relatively low variance. For the training of prediction models, the highest possible generalisability is required, which is at least made more difficult by this data availability. The implementation of a machine learning application can be interpreted as a production process. The CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model with six phases that describes the life cycle of data science. As in any process, the costs to eliminate errors increase significantly with each advancing process phase. For the quality prediction of hydraulic test steps of directional control valves, the question arises in the initial phase whether a regression or a classification is more suitable. In the context of this work, the initial phase of the CRISP-DM, the business understanding, is critically compared for the use case at Bosch Rexroth with regard to regression and classification. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. Suitable methods for leakage volume flow regression and classification for inspection decision are applied. Impressively, classification is clearly superior to regression and achieves promising accuracies.

Keywords: classification, CRISP-DM, machine learning, predictive quality, regression

Procedia PDF Downloads 120
732 The Importance of School Culture in Supporting Student Mental Health Following the COVID-19 Pandemic: Insights from a Qualitative Study

Authors: Rhiannon Barker, Gregory Hartwell, Matt Egan, Karen Lock

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Background: Evidence suggests that mental health (MH) issues in children and young people (CYP) in the UK are on the rise. Of particular concern is data that indicates that the pandemic, together with the impact of school closures, have accentuated already pronounced inequalities; children from families on low incomes or from black and minority ethnic groups are reportedly more likely to have been adversely impacted. This study aimed to help identify specific support which may facilitate the building of a positive school climate and protect student mental health, particularly in the wake of school closures following the pandemic. It has important implications for integrated working between schools and statutory health services. Methods: The research comprised of three parts; scoping, case studies, and a stakeholder workshop to explore and consolidate results. The scoping phase included a literature review alongside interviews with a range of stakeholders from government, academia, and the third sector. Case studies were then conducted in two London state schools. Results: Our research identified how student MH was being impacted by a range of factors located at different system levels, both internal to the school and in the wider community. School climate, relating both to a shared system of beliefs and values, as well as broader factors including style of leadership, teaching, discipline, safety, and relationships -all played a role in the experience of school life and, consequently, the MH of both students and staff. Participants highlighted the importance of a whole school approach and ensuring that support for student MH was not separated from academic achievement, as well as the importance of identifying and applying universal measuring systems to establish levels of MH need. Our findings suggest that a school’s climate is influenced by the style and strength of its leadership, while this school climate - together with mechanisms put in place to respond to MH needs (both statutory and non-statutory) - plays a key role in supporting student MH. Implications: Schools in England have a responsibility to decide on the nature of MH support provided for their students, and there is no requirement for them to report centrally on the form this provision takes. The reality on the ground, as our study suggests, is that MH provision varies significantly between schools, particularly in relation to ‘lower’ levels of need which are not covered by statutory requirements. A valid concern may be that in the huge raft of possible options schools have to support CYP wellbeing, too much is left to chance. Work to support schools in rebuilding their cultures post-lockdowns must include the means to identify and promote appropriate tools and techniques to facilitate regular measurement of student MH. This will help establish both the scale of the problem and monitor the effectiveness of the response. A strong vision from a school’s leadership team that emphasises the importance of student wellbeing, running alongside (but not overshadowed by) academic attainment, should help shape a school climate to promote beneficial MH outcomes. The sector should also be provided with support to improve the consistency and efficacy of MH provision in schools across the country.

Keywords: mental health, schools, young people, whole-school culture

Procedia PDF Downloads 42
731 Locus of Control and Self-Esteem as Predictors of Maternal and Child Healthcare Services Utilization in Nigeria

Authors: Josephine Aikpitanyi, Friday Okonofua, Lorrettantoimo, Sandy Tubeuf

Abstract:

Every day, 800 women die from conditions related to pregnancy and childbirth, resulting in an estimated 300,000 maternal deaths worldwide per year. Over 99 percent of all maternal deaths occur in developing countries, with more than half of them occurring in sub-Saharan Africa. Nigeria being the most populous nation in sub-Saharan Africa bears a significant burden of worsening maternal and child health outcomes with a maternal mortality rate of 917 per 100,000 live births and child mortality rate of 117 per 1,000 live births. While several studies have documented that financial barriers disproportionately discourage poor women from seeking needed maternal and child healthcare, other studies have indicated otherwise. Evidence shows that there are instances where health facilities with skilled healthcare providers exist, and yet maternal, and child health outcomes remain abysmally low, indicating the presence of non-cognitive and behavioural factors that may affect the utilization of healthcare services. This study investigated the influence of locus of control and self-esteem on utilization of maternal and child healthcare services in Nigeria. Specifically, it explored the differences in utilization of antenatal care, skilled birth care, postnatal care, and child vaccination by women having an internal and external locus of control and women having high and low self-esteem. We collected information on non-cognitive traits of 1411 randomly selected women, along with information on utilization of the various indicators of maternal and child healthcare. Estimating logistic regression models for various components of healthcare services utilization, we found that women’s internal locus of control was a significant predictor of utilization of antenatal care, skilled birth care, and completion of child vaccination. We also found that having high self-esteem was a significant predictor of utilization of antenatal care, postnatal care, and completion of child vaccination after adjusting for other control variables. By improving our understanding of non-cognitive traits as possible barriers to maternal and child healthcare utilization, our findings offer important insights for enhancing participant engagement in intervention programs that are initiated to improve maternal and child health outcomes in low-and-middle-income countries.

Keywords: behavioural economics, health-seeking behaviour, locus of control and self-esteem, maternal and child healthcare, non-cognitive traits, and healthcare utilization

Procedia PDF Downloads 137
730 A Randomised Simulation Study to Assess the Impact of a Focussed Crew Resource Management Course on UK Medical Students

Authors: S. MacDougall-Davis, S. Wysling, R. Willmore

Abstract:

Background: The application of good non-technical skills, also known as crew resource management (CRM), is central to the delivery of safe, effective healthcare. The authors have been running remote trauma courses for over 10 years, primarily focussing on developing participants’ CRM in time-critical, high-stress clinical situations. The course has undergone an iterative process over the past 10 years. We employ a number of experiential learning techniques for improving CRM, including small group workshops, military command tasks, high fidelity simulations with reflective debriefs, and a ‘flipped classroom’, where participants are asked to create their own simulations and assess and debrief their colleagues’ CRM. We created a randomised simulation study to assess the impact of our course on UK medical students’ CRM, both at an individual and a teams level. Methods: Sixteen students took part. Four clinical scenarios were devised, designed to be of similar urgency and complexity. Professional moulage effects and experienced clinical actors were used to increase fidelity and to further simulate high-stress environments. Participants were block randomised into teams of 4; each team was randomly assigned to one pre-course simulation. They then underwent our 5 day remote trauma CRM course. Post-course, students were re-randomised into four new teams; each was randomly assigned to a post-course simulation. All simulations were videoed. The footage was reviewed by two independent CRM-trained assessors, who were blinded to the before/after the status of the simulations. Assessors used the internationally validated team emergency assessment measure (TEAM) to evaluate key areas of team performance, as well as a global outcome rating. Prior to the study, assessors had scored two unrelated scenarios using the same assessment tool, demonstrating 89% concordance. Participants also completed pre- and post-course questionnaires. Likert scales were used to rate individuals’ perceived NTS ability and their confidence to work in a team in time-critical, high-stress situations. Results: Following participation in the course, a significant improvement in CRM was observed in all areas of team performance. Furthermore, the global outcome rating for team performance was markedly improved (40-70%; mean 55%), thus demonstrating an impact at Level 4 of Kirkpatrick’s hierarchy. At an individual level, participants’ self-perceived CRM improved markedly after the course (35-70% absolute improvement; mean 55%), as did their confidence to work in a team in high-stress situations. Conclusion: Our study demonstrates that with a short, cost-effective course, using easily reproducible teaching sessions, it is possible to significantly improve participants’ CRM skills, both at an individual and, perhaps more importantly, at a teams level. The successful functioning of multi-disciplinary teams is vital in a healthcare setting, particularly in high-stress, time-critical situations. Good CRM is of paramount importance in these scenarios. The authors believe that these concepts should be introduced from the earliest stages of medical education, thus promoting a culture of effective CRM and embedding an early appreciation of the importance of these skills in enabling safe and effective healthcare.

Keywords: crew resource management, non-technical skills, training, simulation

Procedia PDF Downloads 119
729 Development of Vertically Integrated 2D Lake Victoria Flow Models in COMSOL Multiphysics

Authors: Seema Paul, Jesper Oppelstrup, Roger Thunvik, Vladimir Cvetkovic

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Lake Victoria is the second largest fresh water body in the world, located in East Africa with a catchment area of 250,000 km², of which 68,800 km² is the actual lake surface. The hydrodynamic processes of the shallow (40–80 m deep) water system are unique due to its location at the equator, which makes Coriolis effects weak. The paper describes a St.Venant shallow water model of Lake Victoria developed in COMSOL Multiphysics software, a general purpose finite element tool for solving partial differential equations. Depth soundings taken in smaller parts of the lake were combined with recent more extensive data to resolve the discrepancies of the lake shore coordinates. The topography model must have continuous gradients, and Delaunay triangulation with Gaussian smoothing was used to produce the lake depth model. The model shows large-scale flow patterns, passive tracer concentration and water level variations in response to river and tracer inflow, rain and evaporation, and wind stress. Actual data of precipitation, evaporation, in- and outflows were applied in a fifty-year simulation model. It should be noted that the water balance is dominated by rain and evaporation and model simulations are validated by Matlab and COMSOL. The model conserves water volume, the celerity gradients are very small, and the volume flow is very slow and irrotational except at river mouths. Numerical experiments show that the single outflow can be modelled by a simple linear control law responding only to mean water level, except for a few instances. Experiments with tracer input in rivers show very slow dispersion of the tracer, a result of the slow mean velocities, in turn, caused by the near-balance of rain with evaporation. The numerical and hydrodynamical model can evaluate the effects of wind stress which is exerted by the wind on the lake surface that will impact on lake water level. Also, model can evaluate the effects of the expected climate change, as manifest in changes to rainfall over the catchment area of Lake Victoria in the future.

Keywords: bathymetry, lake flow and steady state analysis, water level validation and concentration, wind stress

Procedia PDF Downloads 204
728 Understanding the Effect of Material and Deformation Conditions on the “Wear Mode Diagram”: A Numerical Study

Authors: A. Mostaani, M. P. Pereira, B. F. Rolfe

Abstract:

The increasing application of Advanced High Strength Steel (AHSS) in the automotive industry to fulfill crash requirements has introduced higher levels of wear in stamping dies and parts. Therefore, understanding wear behaviour in sheet metal forming is of great importance as it can help to reduce the high costs currently associated with tool wear. At the contact between the die and the sheet, the tips of hard tool asperities interact with the softer sheet material. Understanding the deformation that occurs during this interaction is important for our overall understanding of the wear mechanisms. For these reasons, the scratching of a perfectly plastic material by a rigid indenter has been widely examined in the literature; with finite element modelling (FEM) used in recent years to further understand the behaviour. The ‘wear mode diagram’ has been commonly used to classify the deformation regime of the soft work-piece during scratching, into three modes: ploughing, wedge formation, and cutting. This diagram, which is based on 2D slip line theory and upper bound method for perfectly plastic work-piece and rigid indenter, relates different wear modes to attack angle and interfacial strength. This diagram has been the basis for many wear studies and wear models to date. Additionally, it has been concluded that galling is most likely to occur during the wedge formation mode. However, there has been little analysis in the literature of how the material behaviour and deformation conditions associated with metal forming processes influence the wear behaviour. Therefore, the first aim of this work is first to use a commercial FEM package (Abaqus/Explicit) to build a 3D model to capture wear modes during scratching with indenters with different attack angles and different interfacial strengths. The second goal is to utilise the developed model to understand how wear modes might change in the presence of bulk deformation of the work-piece material as a result of the metal forming operation. Finally, the effect of the work-piece material properties, including strain hardening, will be examined to understand how these influence the wear modes and wear behaviour. The results show that both strain hardening and substrate deformation can change the critical attack angle at which the wedge formation regime is activated.

Keywords: finite element, pile-up, scratch test, wear mode

Procedia PDF Downloads 309
727 Development of Coir Reinforced Composite for Automotive Parts Application

Authors: Okpala Charles Chikwendu, Ezeanyim Okechukwu Chiedu, Onukwuli Somto Kenneth

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The demand for lightweight and fuel-efficient automobiles has led to the use of fiber-reinforced polymer composites in place of traditional metal parts. Coir, a natural fiber, offers qualities such as low cost, good tensile strength, and biodegradability, making it a potential filler material for automotive components. However, poor interfacial adhesion between coir and polymeric matrices has been a challenge. To address poor interfacial adhesion with polymeric matrices due to their moisture content and method of preparation, the extracted coir was chemically treated using NaOH. To develop a side view mirror encasement by investigating the mechanical effect of fiber percentage composition, fiber length and percentage composition of Epoxy in a coir fiber reinforced composite, polyester was adopted as the resin for the mold, while that of the product is Epoxy. Coir served as the filler material for the product. Specimens with varied compositions of fiber loading (15, 30 and 45) %, length (10, 15, 20, 30 and 45) mm, and (55, 70, 85) % weight of epoxy resin were fabricated using hand lay-up technique, while those specimens were later subjected to mechanical tests (Tensile, Flexural and Impact test). The results of the mechanical test showed that the optimal solution for the input factors is coir at 45%, epoxy at 54.543%, and 45mm coir length, which was used for the development of a vehicle’s side view mirror encasement. The optimal solutions for the response parameters are 49.333 Mpa for tensile strength, flexural for 57.118 Mpa, impact strength for 34.787 KJ/M2, young modulus for 4.788 GPa, stress for 4.534 KN, and 20.483 mm for strain. The models that were developed using Design Expert software revealed that the input factors can achieve the response parameters in the system with 94% desirability. The study showed that coir is quite durable for filler material in an epoxy composite for automobile applications and that fiber loading and length have a significant effect on the mechanical behavior of coir fiber-reinforced epoxy composites. The coir's low density, considerable tensile strength, and bio-degradability contribute to its eco-friendliness and potential for reducing the environmental hazards of synthetic automotive components.

Keywords: coir, composite, coir fiber, coconut husk, polymer, automobile, mechanical test

Procedia PDF Downloads 38
726 Diverse High-Performing Teams: An Interview Study on the Balance of Demands and Resources

Authors: Alana E. Jansen

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With such a large proportion of organisations relying on the use of team-based structures, it is surprising that so few teams would be classified as high-performance teams. While the impact of team composition on performance has been researched frequently, there have been conflicting findings as to the effects, particularly when examined alongside other team factors. To broaden the theoretical perspectives on this topic and potentially explain some of the inconsistencies in research findings left open by other various models of team effectiveness and high-performing teams, the present study aims to use the Job-Demands-Resources model, typically applied to burnout and engagement, as a framework to examine how team composition factors (particularly diversity in team member characteristics) can facilitate or hamper team effectiveness. This study used a virtual interview design where participants were asked to both rate and describe their experiences, in one high-performing and one low-performing team, over several factors relating to demands, resources, team composition, and team effectiveness. A semi-structured interview protocol was developed, which combined the use of the Likert style and exploratory questions. A semi-targeted sampling approach was used to invite participants ranging in age, gender, and ethnic appearance (common surface-level diversity characteristics) and those from different specialties, roles, educational and industry backgrounds (deep-level diversity characteristics). While the final stages of data analyses are still underway, thematic analysis using a grounded theory approach was conducted concurrently with data collection to identify the point of thematic saturation, resulting in 35 interviews being completed. Analyses examine differences in perceptions of demands and resources as they relate to perceived team diversity. Preliminary results suggest that high-performing and low-performing teams differ in perceptions of the type and range of both demands and resources. The current research is likely to offer contributions to both theory and practice. The preliminary findings suggest there is a range of demands and resources which vary between high and low-performing teams, factors which may play an important role in team effectiveness research going forward. Findings may assist in explaining some of the more complex interactions between factors experienced in the team environment, making further progress towards understanding the intricacies of why only some teams achieve high-performance status.

Keywords: diversity, high-performing teams, job demands and resources, team effectiveness

Procedia PDF Downloads 170
725 Handling, Exporting and Archiving Automated Mineralogy Data Using TESCAN TIMA

Authors: Marek Dosbaba

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Within the mining sector, SEM-based Automated Mineralogy (AM) has been the standard application for quickly and efficiently handling mineral processing tasks. Over the last decade, the trend has been to analyze larger numbers of samples, often with a higher level of detail. This has necessitated a shift from interactive sample analysis performed by an operator using a SEM, to an increased reliance on offline processing to analyze and report the data. In response to this trend, TESCAN TIMA Mineral Analyzer is designed to quickly create a virtual copy of the studied samples, thereby preserving all the necessary information. Depending on the selected data acquisition mode, TESCAN TIMA can perform hyperspectral mapping and save an X-ray spectrum for each pixel or segment, respectively. This approach allows the user to browse through elemental distribution maps of all elements detectable by means of energy dispersive spectroscopy. Re-evaluation of the existing data for the presence of previously unconsidered elements is possible without the need to repeat the analysis. Additional tiers of data such as a secondary electron or cathodoluminescence images can also be recorded. To take full advantage of these information-rich datasets, TIMA utilizes a new archiving tool introduced by TESCAN. The dataset size can be reduced for long-term storage and all information can be recovered on-demand in case of renewed interest. TESCAN TIMA is optimized for network storage of its datasets because of the larger data storage capacity of servers compared to local drives, which also allows multiple users to access the data remotely. This goes hand in hand with the support of remote control for the entire data acquisition process. TESCAN also brings a newly extended open-source data format that allows other applications to extract, process and report AM data. This offers the ability to link TIMA data to large databases feeding plant performance dashboards or geometallurgical models. The traditional tabular particle-by-particle or grain-by-grain export process is preserved and can be customized with scripts to include user-defined particle/grain properties.

Keywords: Tescan, electron microscopy, mineralogy, SEM, automated mineralogy, database, TESCAN TIMA, open format, archiving, big data

Procedia PDF Downloads 89
724 A Digital Twin Approach to Support Real-time Situational Awareness and Intelligent Cyber-physical Control in Energy Smart Buildings

Authors: Haowen Xu, Xiaobing Liu, Jin Dong, Jianming Lian

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Emerging smart buildings often employ cyberinfrastructure, cyber-physical systems, and Internet of Things (IoT) technologies to increase the automation and responsiveness of building operations for better energy efficiency and lower carbon emission. These operations include the control of Heating, Ventilation, and Air Conditioning (HVAC) and lighting systems, which are often considered a major source of energy consumption in both commercial and residential buildings. Developing energy-saving control models for optimizing HVAC operations usually requires the collection of high-quality instrumental data from iterations of in-situ building experiments, which can be time-consuming and labor-intensive. This abstract describes a digital twin approach to automate building energy experiments for optimizing HVAC operations through the design and development of an adaptive web-based platform. The platform is created to enable (a) automated data acquisition from a variety of IoT-connected HVAC instruments, (b) real-time situational awareness through domain-based visualizations, (c) adaption of HVAC optimization algorithms based on experimental data, (d) sharing of experimental data and model predictive controls through web services, and (e) cyber-physical control of individual instruments in the HVAC system using outputs from different optimization algorithms. Through the digital twin approach, we aim to replicate a real-world building and its HVAC systems in an online computing environment to automate the development of building-specific model predictive controls and collaborative experiments in buildings located in different climate zones in the United States. We present two case studies to demonstrate our platform’s capability for real-time situational awareness and cyber-physical control of the HVAC in the flexible research platforms within the Oak Ridge National Laboratory (ORNL) main campus. Our platform is developed using adaptive and flexible architecture design, rendering the platform generalizable and extendable to support HVAC optimization experiments in different types of buildings across the nation.

Keywords: energy-saving buildings, digital twins, HVAC, cyber-physical system, BIM

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723 Modeling Floodplain Vegetation Response to Groundwater Variability Using ArcSWAT Hydrological Model, Moderate Resolution Imaging Spectroradiometer - Normalised Difference Vegetation Index Data, and Machine Learning

Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

Abstract:

This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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722 Towards End-To-End Disease Prediction from Raw Metagenomic Data

Authors: Maxence Queyrel, Edi Prifti, Alexandre Templier, Jean-Daniel Zucker

Abstract:

Analysis of the human microbiome using metagenomic sequencing data has demonstrated high ability in discriminating various human diseases. Raw metagenomic sequencing data require multiple complex and computationally heavy bioinformatics steps prior to data analysis. Such data contain millions of short sequences read from the fragmented DNA sequences and stored as fastq files. Conventional processing pipelines consist in multiple steps including quality control, filtering, alignment of sequences against genomic catalogs (genes, species, taxonomic levels, functional pathways, etc.). These pipelines are complex to use, time consuming and rely on a large number of parameters that often provide variability and impact the estimation of the microbiome elements. Training Deep Neural Networks directly from raw sequencing data is a promising approach to bypass some of the challenges associated with mainstream bioinformatics pipelines. Most of these methods use the concept of word and sentence embeddings that create a meaningful and numerical representation of DNA sequences, while extracting features and reducing the dimensionality of the data. In this paper we present an end-to-end approach that classifies patients into disease groups directly from raw metagenomic reads: metagenome2vec. This approach is composed of four steps (i) generating a vocabulary of k-mers and learning their numerical embeddings; (ii) learning DNA sequence (read) embeddings; (iii) identifying the genome from which the sequence is most likely to come and (iv) training a multiple instance learning classifier which predicts the phenotype based on the vector representation of the raw data. An attention mechanism is applied in the network so that the model can be interpreted, assigning a weight to the influence of the prediction for each genome. Using two public real-life data-sets as well a simulated one, we demonstrated that this original approach reaches high performance, comparable with the state-of-the-art methods applied directly on processed data though mainstream bioinformatics workflows. These results are encouraging for this proof of concept work. We believe that with further dedication, the DNN models have the potential to surpass mainstream bioinformatics workflows in disease classification tasks.

Keywords: deep learning, disease prediction, end-to-end machine learning, metagenomics, multiple instance learning, precision medicine

Procedia PDF Downloads 103