Search results for: steady state model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 22845

Search results for: steady state model

5835 A Theory of Vertical Partnerships Model as Responsive Failure in Alternative Arrangement for Infrastructural Development in the Third World Countries: A Comparative Public Administration Analysis

Authors: Cyril Ekuaze

Abstract:

This paper was instigated by a set of assumption drawn at the introduction to a research work on alternative institutional arrangements for sustaining rural infrastructure in developing countries. Of one of such assumption is the one held that, a problem facing developing countries is the sustaining of infrastructural investment long enough to allow the facility to at least repay the cost of the development as been due to insufficient maintenance. On the contrary, this work argues that, most international partnerships relation with developing nations in developing infrastructures is “vertical modeling” with the hierarchical authority and command flow from top to bottom. The work argued that where international donor partners/agencies set out infrastructural development agenda in the developing nations without cognizance of design suitability and capacity for maintenance by the recipient nations; and where public administrative capacity building in the field of science, technology and engineering requisite for design, development and sustenance of infrastructure in the recipient countries are negated, prospective output becomes problematic.

Keywords: vertical partnerships, responsive failure, infrastructural development, developing countries

Procedia PDF Downloads 327
5834 Negative Sequence-Based Protection Techniques for Microgrid Connected Power Systems

Authors: Isabelle Snyder, Travis Smith

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Microgrid protection presents challenges to conventional protection techniques due to the low-induced fault current. Protection relays present in microgrid applications require a combination of settings groups to adjust based on the architecture of the microgrid in islanded and grid-connected modes. In a radial system where the microgrid is at the other end of the feeder, directional elements can be used to identify the direction of the fault current and switch settings groups accordingly (grid-connected or microgrid-connected). However, with multiple microgrid connections, this concept becomes more challenging, and the direction of the current alone is not sufficient to identify the source of the fault current contribution. ORNL has previously developed adaptive relaying schemes through other DOE-funded research projects that will be evaluated and used as a baseline for this research. The four protection techniques in this study are labeled as follows: (1) Adaptive Current only Protection System (ACPS), Intentional (2) Unbalanced Control for Protection Control (IUCPC), (3) Adaptive Protection System with Communication Controller (APSCC) (4) Adaptive Model-Driven Protective Relay (AMDPR).

Keywords: adaptive relaying, microgrid protection, sequence components, islanding detection

Procedia PDF Downloads 94
5833 Effect of Oat-Protein Peptide in Cognitive Impairment Mice via Mediating Gut-Brain Axis

Authors: Hamad Rafique

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The bioactive peptide RDFPITWPW (RW-9) identified from oat protein has been reported to be positive in memory deficits. However, no clarity on the mechanisms responsible for the neuroprotective effects of RW-9 peptide against AD-like symptoms. Herein, it found that RW-9 intervention showed various improving effects in cognitive-behavioral tests and alleviated oxidative stress and inflammation in the scopolamine-induced mice model. The hippocampus proteomics analysis revealed the upregulation of memory-related proteins, including Grin3a, Ppp2r1b, Stat6, Pik3cd, Slc5a7, Chrm2, mainly involved in cAMP signaling, PI3K-Akt signaling, and JAK-STAT signaling pathways. The administration of RW-9 significantly upregulated the neurotransmitters, including 5-HT, DA, and Arg, in mice brains. Moreover, it regulated the serum metabolic profile and increased the expression levels of ABC transporters, biosynthesis of amino acids, and Amino acyl-tRNA biosynthesis, among others. The 16s-rRNA results illustrated that the RW-9 restored the abundance of Muribaculaceae, Lachnospiraceae, Lactobacillus, Clostridia and Bactericides. Taken together, our results suggest that the RW-9 may prevent the AD-like symptoms via modulation of the gut-serum-brain axis.

Keywords: oat protein, active peptide, neuroprotective, gut-brain axis

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5832 Convergence Analysis of Training Two-Hidden-Layer Partially Over-Parameterized ReLU Networks via Gradient Descent

Authors: Zhifeng Kong

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Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.

Keywords: over-parameterization, rectified linear units ReLU, convergence, gradient descent, neural networks

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5831 An Implicit High Order Difference Scheme for the Solution of 1D Pennes Bio-Heat Transfer Model

Authors: Swarn Singh, Suruchi Singh

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In this paper, we present a fourth order two level implicit finite difference scheme for 1D Pennes bio-heat equation. Unconditional stability and convergence of the proposed scheme is discussed. Numerical results are obtained to demonstrate the efficiency of the scheme. In this paper we present a fourth order two level implicit finite difference scheme for 1D Pennes bio-heat equation. Unconditional stability and convergence of the proposed scheme is discussed. Numerical results are obtained to demonstrate the efficiency of the scheme.

Keywords: convergence, finite difference scheme, Pennes bio-heat equation, stability

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5830 Autohydrolysis Treatment of Olive Cake to Extract Fructose and Sucrose

Authors: G. Blázquez, A. Gálvez-Pérez, M. Calero, I. Iáñez-Rodríguez, M. A. Martín-Lara, A. Pérez

Abstract:

The production of olive oil is considered as one of the most important agri-food industries. However, some of the by-products generated in the process are potential pollutants and cause environmental problems. Consequently, the management of these by-products is currently considered as a challenge for the olive oil industry. In this context, several technologies have been developed and tested. In this sense, the autohydrolysis of these by-products could be considered as a promising technique. Therefore, this study focused on autohydrolysis treatments of a solid residue from the olive oil industry denominated olive cake. This one comes from the olive pomace extraction with hexane. Firstly, a water washing was carried out to eliminate the water soluble compounds. Then, an experimental design was developed for the autohydrolysis experiments carried out in the hydrothermal pressure reactor. The studied variables were temperature (30, 60 and 90 ºC) and time (30, 60, 90 min). On the other hand, aliquots of liquid obtained fractions were analysed by HPLC to determine the fructose and sucrose contents present in the liquid fraction. Finally, the obtained results of sugars contents and the yields of the different experiments were fitted to a neuro-fuzzy and to a polynomial model.

Keywords: ANFIS, olive cake, polyols, saccharides

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5829 Evaluation of the Operating Parameters for Biodiesel Production Using a Membrane Reactor

Authors: S. S. L. Andrade, E. A. Souza, L. C. L. Santos, C. Moraes, A. K. C. L. Lobato

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Biodiesel production using membrane reactor has become increasingly studied, because this process minimizes some of the main problems encountered in the biodiesel purification. The membrane reactor tries to minimize post-treatment steps, resulting in cost savings and enabling the competitiveness of biodiesel produced by homogeneous alkaline catalysis. This is due to the reaction and product separation may occur simultaneously. In order to evaluate the production of biodiesel from soybean oils using a tubular membrane reactor, a factorial experimental design was conducted (2³) to evaluate the influence of following variables: temperature (45 to 60 °C), catalyst concentration (0.5 to 1% by weight) and molar ratio of oil/methanol (1/6 to 1/9). In addition, the parametric sensitivity was evaluated by the analysis of variance and model through the response surface. The results showed a tendency of influence of the variables in the reaction conversion. The significance effect was higher for the catalyst concentration followed by the molar ratio of oil/methanol and finally the temperature. The best result was obtained under the conditions of 1% catalyst (KOH), molar ratio oil/methanol of 1/9 and temperature of 60 °C, resulting in an ester content of 99.07%.

Keywords: biodiesel production, factorial design, membrane reactor, soybean oil

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5828 Structure-Based Virtual Screening to Identify CLDN4 Inhibitors

Authors: Jayanthi Sivaraman

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Claudins are the important components of the tight junctions that play a key role in paracellular permeability. Among various members of Claudin family, Claudin 4 (CLDN4) is found to be overexpressed in ovarian, pancreatic carcinomas and other epithelial malignancies. Therefore, in this study, an attempt has been made to identify potent inhibitors for CLDN4 from the ZINC database using virtual screening, molecular docking and molecular dynamics simulations. A well refined molecular model of CLDN4 was built using Prime of Schrodinger v10.2(Template- PDB ID: 4P79). Approximately, 6 million compounds from ZINC database are subjected to high-throughput virtual screening (HTVS) against the active site of CLDN4. Molecular docking using GLIDE predicted ARG31, ASN142, ASP146 and ARG158 as critically important residues. Furthermore, three compounds from ZINC database (ZINC96331839, ZINC36533519 and ZINC75819394) showed highly promising ADME properties and binding affinity with stable conformation. The therapeutic efficiency of these lead compounds is evaluated and confirmed by in-vitro and in-vivo studies which leads to the development of novel anti-cancer drugs.

Keywords: ADME property, inhibitors, molecular docking, virtual screening

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5827 MindFlow: A Collective Intelligence-Based System for Helping Stress Pattern Diagnosis

Authors: Andres Frederic

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We present the MindFlow system supporting the detection and the diagnosis of stresses. The heart of the system is a knowledge synthesis engine allowing occupational health stakeholders (psychologists, occupational therapists and human resource managers) to formulate queries related to stress and responding to users requests by recommending a pattern of stress if one exists. The stress pattern diagnosis is based on expert knowledge stored in the MindFlow stress ontology including stress feature vector. The query processing may involve direct access to the MindFlow system by occupational health stakeholders, online communication between the MindFlow system and the MindFlow domain experts, or direct dialog between a occupational health stakeholder and a MindFlow domain expert. The MindFlow knowledge model is generic in the sense that it supports the needs of psychologists, occupational therapists and human resource managers. The system presented in this paper is currently under development as part of a Dutch-Japanese project and aims to assist organisation in the quick diagnosis of stress patterns.

Keywords: occupational stress, stress management, physiological measurement, accident prevention

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5826 Face Recognition Using Eigen Faces Algorithm

Authors: Shweta Pinjarkar, Shrutika Yawale, Mayuri Patil, Reshma Adagale

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Face recognition is the technique which can be applied to the wide variety of problems like image and film processing, human computer interaction, criminal identification etc. This has motivated researchers to develop computational models to identify the faces, which are easy and simple to implement. In this, demonstrates the face recognition system in android device using eigenface. The system can be used as the base for the development of the recognition of human identity. Test images and training images are taken directly with the camera in android device.The test results showed that the system produces high accuracy. The goal is to implement model for particular face and distinguish it with large number of stored faces. face recognition system detects the faces in picture taken by web camera or digital camera and these images then checked with training images dataset based on descriptive features. Further this algorithm can be extended to recognize the facial expressions of a person.recognition could be carried out under widely varying conditions like frontal view,scaled frontal view subjects with spectacles. The algorithm models the real time varying lightning conditions. The implemented system is able to perform real-time face detection, face recognition and can give feedback giving a window with the subject's info from database and sending an e-mail notification to interested institutions using android application. Face recognition is the technique which can be applied to the wide variety of problems like image and film processing, human computer interaction, criminal identification etc. This has motivated researchers to develop computational models to identify the faces, which are easy and simple to implement. In this , demonstrates the face recognition system in android device using eigenface. The system can be used as the base for the development of the recognition of human identity. Test images and training images are taken directly with the camera in android device.The test results showed that the system produces high accuracy. The goal is to implement model for particular face and distinguish it with large number of stored faces. face recognition system detects the faces in picture taken by web camera or digital camera and these images then checked with training images dataset based on descriptive features. Further this algorithm can be extended to recognize the facial expressions of a person.recognition could be carried out under widely varying conditions like frontal view,scaled frontal view subjects with spectacles. The algorithm models the real time varying lightning conditions. The implemented system is able to perform real-time face detection, face recognition and can give feedback giving a window with the subject's info from database and sending an e-mail notification to interested institutions using android application.

Keywords: face detection, face recognition, eigen faces, algorithm

Procedia PDF Downloads 358
5825 Six Years Antimicrobial Resistance Trends among Bacterial Isolates in Amhara National Regional State, Ethiopia

Authors: Asrat Agalu Abejew

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Background: Antimicrobial resistance (AMR) is a silent tsunami and one of the top global threats to health care and public health. It is one of the common agendas globally and in Ethiopia. Emerging AMR will be a double burden to Ethiopia, which is facing a series of problems from infectious disease morbidity and mortality. In Ethiopia, although there are attempts to document AMR in healthcare institutions, comprehensive and all-inclusive analysis is still lacking. Thus, this study is aimed to determine trends in AMR from 2016-2021. Methods: A retrospective analysis of secondary data recorded in the Amhara Public Health Institute (APHI) from 2016 to 2021 G.C was conducted. Blood, Urine, Stool, Swabs, Discharge, body effusions, and other Microbiological specimens were collected from each study participants, and Bacteria identification and Resistance tests were done using the standard microbiologic procedure. Data was extracted from excel in August 2022, Trends in AMR were analyzed, and the results were described. In addition, the chi-square (X2) test and binary logistic regression were used, and a P. value < 0.05 was used to determine a significant association. Results: During 6 years period, there were 25143 culture and susceptibility tests. Overall, 265 (46.2%) bacteria were resistant to 2-4 antibiotics, 253 (44.2%) to 5-7 antibiotics, and 56 (9.7%) to >=8 antibiotics. The gram-negative bacteria were 166 (43.9%), 155 (41.5%), and 55 (14.6%) resistant to 2-4, 5-7, and ≥8 antibiotics, respectively, whereas 99(50.8%), 96(49.2% and 1 (0.5%) of gram-positive bacteria were resistant to 2-4, 5-7 and ≥8 antibiotics respectively. K. pneumonia 3783 (15.67%) and E. coli 3199 (13.25%) were the most commonly isolated bacteria, and the overall prevalence of AMR was 2605 (59.9%), where K. pneumonia 743 (80.24%), E. cloacae 196 (74.81%), A. baumannii 213 (66.56%) being the most common resistant bacteria for antibiotics tested. Except for a slight decline during 2020 (6469 (25.4%)), the overall trend of AMR is rising from year to year, with a peak in 2019 (8480 (33.7%)) and in 2021 (7508 (29.9%). If left un-intervened, the trend in AMR will increase by 78% of variation from the study period, as explained by the differences in years (R2=0.7799). Ampicillin, Augmentin, ciprofloxacin, cotrimoxazole, tetracycline, and Tobramycin were almost resistant to common bacteria they were tested. Conclusion: AMR is linearly increasing during the last 6 years. If left as it is without appropriate intervention after 15 years (2030 E.C), AMR will increase by 338.7%. A growing number of multi-drug resistant bacteria is an alarm to awake policymakers and those who do have the concern to intervene before it is too late. This calls for a periodic, integrated, and continuous system to determine the prevalence of AMR in commonly used antibiotics.

Keywords: AMR, trend, pattern, MDR

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5824 Motivation, Legal Knowledge and Preference Investigation of Hungarian Law Students

Authors: Zsofia Patyi

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While empirical studies under socialism in Hungary focused on the lawyer society as a whole, current research deals with law students in specific. The change of regime and the mutation of legal education have influenced the motivation, efficiency, social background and self-concept of law students. This shift needs to be acknowledged, and the education system improved for students and together with students. A new law student society requires a different legal education system, different legal studies, or, at the minimum, a different approach to teaching law. This is to ensure that competitive lawyers be trained who understand the constantly changing nature of the law and, as a result, can potentially transform or create legislation themselves. A number of developments can affect law students’ awareness of legal relations in a democratic state. In today’s Hungary, these decisive factors are primarily the new regulation of the financing of law students, and secondly, the new Hungarian constitution (henceforth: Alaptörvény), which has modified the base of the Hungarian legal system. These circumstances necessitate a new, comprehensive, and empirical, investigation of law students. To this end, our research team (comprising a professor, a Ph.D. student, and two law students), is conducting a new type of study in February 2017. The first stage of the research project uses the desktop method to open up the research antecedents. Afterward, a structured questionnaire draft will be designed and sent to the Head of Department of Sociology and the Associate Professor of the Department of Constitutional Law at the University of Szeged to have the draft checked and amended. Next, an open workshop for students and teachers will be organized with the aim to discuss the draft and create the final questionnaire. The research team will then contact each Hungarian university with a Faculty of Law to reach all 1st- and 4th-year law students. 1st-year students have not yet studied the Alaptörvény, while 4th-year students have. All students will be asked to fill in the questionnaire (in February). Results are expected to be in at the end of February. In March, the research team will report the results and present the conclusions. In addition, the results will be compared to previous researches. The outcome will help us answer the following research question: How should legal studies and legal education in Hungary be reformed in accordance with law students and the future lawyer society? The aim of the research is to (1) help create a new student- and career-centered teaching method of legal studies, (2) offer a new perspective on legal education, and (3) create a helpful and useful de lege ferenda proposal for the attorney general as regards legal education as part of higher education.

Keywords: change, constitution, investigation, law students, lawyer society, legal education, legal studies, motivation, reform

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5823 Magnetohydrodynamic (MHD) Flow of Cu-Water Nanofluid Due to a Rotating Disk with Partial Slip

Authors: Tasawar Hayat, Madiha Rashid, Maria Imtiaz, Ahmed Alsaedi

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This problem is about the study of flow of viscous fluid due to rotating disk in nanofluid. Effects of magnetic field, slip boundary conditions and thermal radiations are encountered. An incompressible fluid soaked the porous medium. In this model, nanoparticles of Cu is considered with water as the base fluid. For Copper-water nanofluid, graphical results are presented to describe the influences of nanoparticles volume fraction (φ) on velocity and temperature fields for the slip boundary conditions. The governing differential equations are transformed to a system of nonlinear ordinary differential equations by suitable transformations. Convergent solution of the nonlinear system is developed. The obtained results are analyzed through graphical illustrations for different parameters. Moreover, the features of the flow and heat transfer characteristics are analyzed. It is found that the skin friction coefficient and heat transfer rate at the surface are highest in copper-water nanofluid.

Keywords: MHD nanofluid, porous medium, rotating disk, slip effect

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5822 Combining Impedance and Hydrodynamic Methods toward Hydrogen Evolution Reaction to Characterize Pt(pc), Pt5Gd, and Nanostructure Pd Electrocatalyst

Authors: Kun-Ting Song, Christian Schott, Peter Schneider, Sebastian Watzele, Regina Kluge, Elena Gubanova, Aliaksandr S. Bandarenka

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The combination of electrochemical impedance spectroscopy (EIS) and the hydrodynamic technique like rotation disc electrode (RDE) provides a critical method for quantitively investigating mechanisms of hydrogen evolution reaction (HER) in acidic and alkaline media. Pt5Gd represented higher HER activities than polycrystalline Pt (Pt(pc)) by means of the surface strain effects. The model of the equivalent electric circuit to fit the impedance data under the RDE configurations is developed. To investigate the relative reaction contribution, the ratio of the charge transfer reactions of the Volmer-Heyrovsky and Volmer-Tafel pathways on Pt and Pt5Gd electrodes is determined. The ratio remains comparably similar in acidic media, but it changes in alkaline media with Volmer–Heyrovsky pathway dominating. This combined approach of EIS and RDE can help to study the electrolyte effects and other essential reactions for electrocatalysis in future work.

Keywords: hydrogen evolution reaction, electrochemical impedance spectroscopy, hydrodynamic methods, electrocatalysis, electrochemical interface

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5821 Investigation of a Hybrid Process: Multipoint Incremental Forming

Authors: Safa Boudhaouia, Mohamed Amen Gahbiche, Eliane Giraud, Wacef Ben Salem, Philippe Dal Santo

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Multi-point forming (MPF) and asymmetric incremental forming (ISF) are two flexible processes for sheet metal manufacturing. To take advantages of these two techniques, a hybrid process has been developed: The Multipoint Incremental Forming (MPIF). This process accumulates at once the advantages of each of these last mentioned forming techniques, which makes it a very interesting and particularly an efficient process for single, small, and medium series production. In this paper, an experimental and a numerical investigation of this technique are presented. To highlight the flexibility of this process and its capacity to manufacture standard and complex shapes, several pieces were produced by using MPIF. The forming experiments are performed on a 3-axis CNC machine. Moreover, a numerical model of the MPIF process has been implemented in ABAQUS and the analysis showed a good agreement with experimental results in terms of deformed shape. Furthermore, the use of an elastomeric interpolator allows avoiding classical local defaults like dimples, which are generally caused by the asymmetric contact and also improves the distribution of residual strain. Future works will apply this approach to other alloys used in aeronautic or automotive applications.

Keywords: incremental forming, numerical simulation, MPIF, multipoint forming

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5820 Comparison of the Common Factors of the Top Academic Elementary Schools to the Average Elementary Schools in California: Looking beyond School Leadership

Authors: Lindy Valdez, Daryl Parker

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Introduction: There has been much research on academic achievement in elementary schools. Most of the research has been on school leadership. While research has focused on the role of leadership on school improvement, little research has examined what variables the top elementary schools have in common. To undertake school improvement, it is important to understand what factors the best schools share. The purpose of this study was to examine data of the “Best Elementary Schools in California,” based on academic achievement as rated by three prominent websites and determine if these schools had any common factors which were different than the statewide averages. The variables examined included access to subject matter specialists (physical education, art, and music), librarians, after school programs, class size, socioeconomic status, and diversity. The participants consisted of the top public elementary schools in California based on the websites i)https://www.niche.com/k12/search/best-schools/, ii)https://www.finder.com/best-schools-california,and iii)https://www.schooldigger.com/go/CA/schoolrank.aspx. The data for subject matter specialists (physical education, art, and music), librarians, after school programs, class size, socioeconomic status, and diversity were collected from these top schools and compared to California statewide averages. Results indicate that top public elementary schools in California have a high number of subject matter specialists that teach physical education, art, and music. These positions are on the decline in the average public elementary school in California, but the top schools have abundant access to these specialists. The physical education specialist has the highest statistically significant difference between the nationwide average and the top schools—librarians, and after school programs are also most commonly high in top public elementary schools in California. The high presence of these programs may be aiding academic achievement in less visible ways. Class size is small, socio-economic status is high, and diversity is low among top public elementary schools in California when compared to the statewide average public elementary schools in California. The single largest area of discrepancy was between physical education specialists in a top school and their state and nationwide averages. The socioeconomic status of schools and parents may be an underlining factor affecting several other variables. This affluence could explain how these schools were able to have access to subject matter specialists, after-school activities, and, therefore, more opportunities for physical activity and greater learning opportunities affecting academic achievement.

Keywords: academic achievement, elementary education, factors, schools

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5819 Social Anxiety, Parental Criticism and the Mediating Role of Early Maladaptive Schemas

Authors: Tahmeena Ali, Andrew Francis, Keong Yap, Sharynn Schuster

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Social anxiety is a chronic and debilitating condition characterized by fear and avoidance of social situations. Several risk factors have emerged, which emphasize the role of early childhood experiences in the development of this condition. As such, the current study tested the hypothesis that early maladaptive schemas (EMSs) mediate the relationship between retrospectively reported parental criticism and social anxiety whilst controlling the effects of depression. Three hundred and thirty-four non-clinical participants completed an online questionnaire consisting of self-report measures of parental criticism, EMSs of disconnection and rejection, and symptoms of social anxiety and depression. The mediation analysis confirmed the hypothesized model, indicating that EMSs mediated the relationship between parental criticism and social anxiety symptoms when controlling for depression. Whilst the current study is limited due to its cross-sectional design, the findings lend support to the developmental formulations of social anxiety and have important therapeutic implications for treatment.

Keywords: early maladaptive schema, parental criticism, schema, social anxiety

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5818 Benefits of Monitoring Acid Sulfate Potential of Coffee Rock (Indurated Sand) across Entire Dredge Cycle in South East Queensland

Authors: S. Albert, R. Cossu, A. Grinham, C. Heatherington, C. Wilson

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Shipping trends suggest increasing vessel size and draught visiting Australian ports highlighting potential challenges to port infrastructure and requiring optimization of shipping channels to ensure safe passage for vessels. The Port of Brisbane in Queensland, Australia has an 80 km long access shipping channel which vessels must transit 15 km of relatively shallow coffee rock (generic class of indurated sands where sand grains are bound within an organic clay matrix) outcrops towards the northern passage in Moreton Bay. This represents a risk to shipping channel deepening and maintenance programs as the dredgeability of this material is more challenging due to its high cohesive strength compared with the surrounding marine sands and potential higher acid sulfate risk. In situ assessment of acid sulfate sediment for dredge spoil control is an important tool in mitigating ecological harm. The coffee rock in an anoxic undisturbed state does not pose any acid sulfate risk, however when disturbed via dredging it’s vital to ensure that any present iron sulfides are either insignificant or neutralized. To better understand the potential risk we examined the reduction potential of coffee rock across the entire dredge cycle in order to accurately portray the true outcome of disturbed acid sulfate sediment in dredging operations in Moreton Bay. In December 2014 a dredge trial was undertaken with a trailing suction hopper dredger. In situ samples were collected prior to dredging revealed acid sulfate potential above threshold guidelines which could lead to expensive dredge spoil management. However, potential acid sulfate risk was then monitored in the hopper and subsequent discharge, both showing a significant reduction in acid sulfate potential had occurred. Additionally, the acid neutralizing capacity significantly increased due to the inclusion of shell fragments (calcium carbonate) from the dredge target areas. This clearly demonstrates the importance of assessing potential acid sulfate risk across the entire dredging cycle and highlights the need to carefully evaluate sources of acidity.

Keywords: acid sulfate, coffee rock, indurated sand, dredging, maintenance dredging

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5817 Mikhail Bakhtin's Standpoint of Neo-Marxism and beyond: Bildungsroman as a Critique

Authors: Hsiao-Yung Wang

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This paper aims to elaborate the standpoint of neo-Marxism of Russian philosopher Mikhail Bakhtin by critical reading his concept of Bildungsroman; thereby, it aims to map the theoretical implication of spatial rhetoric and its time politics/emancipatory politics in late Bakhtin’s thought. First, it aims to outline the two revolving rings of spatiality in Bildungsroman, proceeding from 'recollecting the past' to 'foreseeing the future' on the basis of visuality and materialistic realism. Herein, Bakhtin has temporarily been leaving his previous research concern on polyphonic novel. Second, it aims to demonstrate that although Bakhtin has constantly emphasized the necessity of reconstructing opened future space, his insistence on 'emergence' has still generated a seemingly theoretical lacuna which needs to be filled. 'Doubled heterotopia,' as popularized by contemporary rhetorician Saindon, might be an adequate approach to articulate and present the rhetorical functions and dynamics of Bakhtin’s spatial rhetoric dialectically. Based on the research findings, this paper argues that Bakhtin indeed attempted to go beyond the deterministic model of Marxism and neo-Marxism strategically and reciprocally.

Keywords: Bildungsroman, double heterotopia, emergence, Mikhail Bakhtin, neo-Marxism, spatial rhetoric, time-politics, visuality

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5816 Behavioral Intentions and Cognitive-Affective Effects of Exposure to YouTube Advertisements among College Students

Authors: Abd El-Basit Ahmed Hashem Mahmoud, Othman Fekry Abdelbaki

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This study attempts to investigate the exposure to YouTube ads among Egyptian college students, their attitudes towards these ads, behavioral intentions to watch them, and the effects of this exposure and to examine the relationships among these variables as well. The current study is theoretically guided by the theory of reasoned action (TRA) and cognitive-affective behavioral model (CAB) through a questionnaire survey administered to a convenience sample of 390 college students who watch YouTube videos from Cairo University, Egypt from February to May 2019. The results showed that 98.7% of respondents exposed to YouTube ads, and both of their attitudes towards YouTube ads exposure and their intentions to this exposure were moderately positive. The findings also indicated that respondents' gender had a significant impact on their intention to expose these ads. One-way ANOVA indicated that their attitudes towards exposure to YouTube ads influenced their behavioral intentions to watch these ads, and it also demonstrated that their behavioral intentions to watch these ads had an impact on the exposure to such ads. Pearson correlation revealed that there was a significant positive relationship between respondents' attitudes towards YouTube ads exposure and the cognitive, affective, and behavioral effects of this exposure.

Keywords: attitudes, behavioral intentions, theory of reasoned action, YouTube ads

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5815 Promoting Diversity and Equity through Interdisciplinary Leadership Training

Authors: Sharon Milberger, Jane Turner, Denise White-Perkins

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Michigan shares the overall U.S. national need for more highly qualified professionals who have knowledge and experience in the use of evidence-based practices to meet the special health care needs of children, adolescents, and adults with neurodevelopmental disabilities including autism spectrum disorder (DD/ASD). The Michigan Leadership Education in Neurodevelopmental Disabilities (MI-LEND) program is a consortium of six universities that spans the state of Michigan and serves more than 181,800 undergraduate, graduate, and professional students. The purpose of the MI LEND program is to improve the health of infants, children and adolescents with disabilities in Michigan by training individuals from different disciplines to assume leadership roles in their respective fields and work across disciplines. The MI-LEND program integrates “L.I.F.E.” perspectives into all training components. L.I.F.E. is an acronym for Leadership, Interdisciplinary, Family-Centered and Equity perspectives. This paper will describe how L.I.F.E. perspectives are embedded into all aspects of the MI-LEND training program including the application process, didactic training, community and clinical experiences, discussions, journaling and projects. Specific curriculum components will be described including content from a training module dedicated to Equity. Upon completion of the Equity module, trainees are expected to be able to: 1) Use a population health framework to identify key social determinants impacting families and children; 2) Explain how addressing bias and providing culturally appropriate linguistic care/services can influence patient/client health and wellbeing; and 3) Describe the impact of policy and structural/institutional factors influencing care and services for children with DD/ASD and their families. Each trainee completes two self-assessments: the Cultural and Linguistic Competence Health Practitioner Assessment and the other assessing social attitudes/implicit bias. Trainees also conduct interviews with a family with a child with DD/ASD. In addition, interdisciplinary Equity-related group activities are incorporated into face-to-face training sessions. Each MI-LEND trainee has multiple ongoing opportunities for self-reflection through discussion and journaling and completion of a L.I.F.E. project as a culminating component of the program. The poster will also discuss the challenges related to teaching and measuring successful outcomes related to diversity/equity perspectives.

Keywords: disability, diversity, equity, training

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5814 Food Insecurity Determinants Amidst the Covid-19 Pandemic: An Insight from Huntsville, Texas

Authors: Peter Temitope Agboola

Abstract:

Food insecurity continues to affect a large number of U.S households during this coronavirus COVID-19 pandemic. The pandemic has threatened the livelihoods of people, making them vulnerable to severe hardship and has had an unanticipated impact on the U.S economy. This study attempts to identify the food insecurity status of households and the determinant factors driving household food insecurity. Additionally, it attempts to discover the mitigation measures adopted by households during the pandemic in the city of Huntsville, Texas. A structured online sample survey was used to collect data, with a household expenditures survey used in evaluating the food security status of the household. Most survey respondents disclosed that the COVID-19 pandemic had affected their life and source of income. Furthermore, the main analytical tool used for the study is descriptive statistics and logistic regression modeling. A logistic regression model was used to determine the factors responsible for food insecurity in the study area. The result revealed that most households in the study area are food secure, with the remainder being food insecure.

Keywords: food insecurity, household expenditure survey, COVID-19, coping strategies, food pantry

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5813 Modeling of Transformer Winding for Transients: Frequency-Dependent Proximity and Skin Analysis

Authors: Yazid Alkraimeen

Abstract:

Precise prediction of dielectric stresses and high voltages of power transformers require the accurate calculation of frequency-dependent parameters. A lack of accuracy can result in severe damages to transformer windings. Transient conditions is stuided by digital computers, which require the implementation of accurate models. This paper analyzes the computation of frequency-dependent skin and proximity losses included in the transformer winding model, using analytical equations and Finite Element Method (FEM). A modified formula to calculate the proximity and the skin losses is presented. The results of the frequency-dependent parameter calculations are verified using the Finite Element Method. The time-domain transient voltages are obtained using Numerical Inverse Laplace Transform. The results show that the classical formula for proximity losses is overestimating the transient voltages when compared with the results obtained from the modified method on a simple transformer geometry.

Keywords: fast front transients, proximity losses, transformer winding modeling, skin losses

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5812 Coexistence of Superconductivity and Spin Density Wave in Ferropnictide Ba₁₋ₓKₓFe₂As₂

Authors: Tadesse Desta Gidey, Gebregziabher Kahsay, Pooran Singh

Abstract:

This work focuses on the theoretical investigation of the coexistence of superconductivity and Spin Density Wave (SDW)in Ferropnictide Ba₁₋ₓKₓFe₂As₂. By developing a model Hamiltonian for the system and by using quantum field theory Green’s function formalism, we have obtained mathematical expressions for superconducting transition temperature TC), spin density wave transition temperature (Tsdw), superconductivity order parameter (Sc), and spin density wave order parameter (sdw). By employing the experimental and theoretical values of the parameters in the obtained expressions, phase diagrams of superconducting transition temperature (TC) versus superconducting order parameter (Sc) and spin density wave transition temperature (Tsdw), versus spin density wave order parameter (sdw) have been plotted. By combining the two phase diagrams, we have demonstrated the possible coexistence of superconductivity and spin density wave (SDW) in ferropnictide Ba1−xKxFe2As2.

Keywords: Superconductivity, Spin density wave, Coexistence, Green function, Pnictides, Ba₁₋ₓKₓFe₂As₂

Procedia PDF Downloads 172
5811 Development of Fake News Model Using Machine Learning through Natural Language Processing

Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

Abstract:

Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

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5810 Numerical Study for Examination of Flow Characteristics in Fractured Gas Reservoirs

Authors: M. K. Kim, C. H. Shin, W. G. Park

Abstract:

Recently, natural gas resources are issued due to alternative and eco-friendly energy policies, and development of even unconventional gas resources including tight gas, coal bed methane and shale gas is being rapidly expanded from North America all over the world. For developing these gas reservoirs, it is necessary to investigate reservoir characteristics by using reservoir simulation. In reservoir simulation, calculation of permeability of fractured zone is very important to predict the gas production. However, it is difficult to accurately calculate the permeability by using conventional methods which use analytic solution for laminar flow. The flow in gas reservoirs exhibits complex flow behavior such as slip around the wall roughness effect and turbulence because the size of the apertures of fractures is ranged over various scales from nano-scale to centi-scale. Therefore, it is required to apply new reservoir flow analysis methods which can accurately consider complex gas flow owing to the geometric characteristics and distributions of various pores and flow paths within gas reservoirs. Hence, in this study, the flow characteristics and the relation between each characteristic variable was investigated and multi-effect was quantified when the fractures are compounded for devising a new calculation model of permeability of fractured zone in gas reservoirs by using CFD.

Keywords: fractured zone, gas reservoir, permeability, CFD

Procedia PDF Downloads 249
5809 Institutional Legitimacy and Professional Boundary: Western Medicine-Trained Doctors' Attitudes and Behaviors toward Traditional Chinese Medicine

Authors: Xiaoli Tian

Abstract:

The recent growing interest in and use of complementary and alternative medicine is a global phenomenon. In many regions, traditional Chinese medicine (TCM), an important type of complementary and alternative medicine, has been formally integrated into the healthcare system. Consequently, today’s doctors face increasing requests and questions from patients regarding TCM. However, studies of TCM focus either on patients’ approaches to TCM and Western medicine (WM) or on the politics involved in the institutionalization of TCM. To our knowledge, sociological studies on doctors’ attitudes toward TCM are rare. This paper compares the receptivity of WM-trained Chinese doctors to TCM in Hong Kong and mainland China, in order to evaluate the interplay between professional training and dominant medical paradigms, on the one hand, and institutional legitimacy and government and client pressures to accept TCM, on the other. Based on survey and in-depth interviews with Western-medicine doctors in Hong Kong and mainland China, this research finds that: there is major difference between Western-medicine doctors’ attitude toward traditional Chinese medicine (TCM) in Hong Kong and mainland China. Doctors in Hong Kong are still suspicious toward TCM, no matter if they have exposure to TCM or not. Even some doctors who have much knowledge about TCM, such as got a diploma or certificate in TCM or tried TCM themselves, are still suspicious. This is because they hold up to the ideal of 'evidence-based medicine' and emphasize the kind of evidence based on randomized controlled trial (RCT). To Western medicine doctors in Hong Kong, this is the most reliable type of evidence for any medical practice, but it is lacking in TCM. This is the major reason why they do not trust TCM and would not refer patients to TCM in clinical practices. In contrast, western medicine doctors in mainland China also know about randomized controlled trial (RCT) and believe that’s the most reliable evidence, but they tend to think experience-based evidence is also reliable. On this basis, they think TCM also has clinical effectiveness. Research findings reveal that legitimacy based on institutional arrangements is a relevant factor, but how doctors understand their professional boundaries also play an important role. Doctors in Hong Kong are more serious about a strict professional boundary between Western medicine and TCM because they benefited from it, such as a very prestigious status and high income. Doctors in mainland China tend to be flexible about professional boundaries because they never benefited from a well-defined strict professional boundary. This is related to a long history of the lack of professionalism in China but is also aggravated by the increasing state support of TCM.

Keywords: evidence-based decision-making, institutional legitimacy, professional behavior, traditional Chinese medicine

Procedia PDF Downloads 182
5808 Machine Learning Approach for Automating Electronic Component Error Classification and Detection

Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

Abstract:

The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

Procedia PDF Downloads 134
5807 Analysis of Human Mental and Behavioral Models for Development of an Electroencephalography-Based Human Performance Management System

Authors: John Gaber, Youssef Ahmed, Hossam A. Gabbar, Jing Ren

Abstract:

Accidents at Nuclear Power Plants (NPPs) occur due to various factors, notable among them being poor safety management and poor safety culture. During abnormal situations, the likelihood of human error is many-fold higher due to the higher cognitive workload. The most common cause of human error and high cognitive workload is mental fatigue. Electroencephalography (EEG) is a method of gathering the electromagnetic waves emitted by a human brain. We propose a safety system by monitoring brainwaves for signs of mental fatigue using an EEG system. This requires an analysis of the mental model of the NPP operator, changes in brain wave power in response to certain stimuli, and the risk factors on mental fatigue and attention that NPP operators face when performing their tasks. We analyzed these factors and developed an EEG-based monitoring system, which aims to alert NPP operators when levels of mental fatigue and attention hinders their ability to maintain safety.

Keywords: brain imaging, EEG, power plant operator, psychology

Procedia PDF Downloads 101
5806 The Role and Position of Chinese Modern Martial Art in the School Physical Education (1912-1945)

Authors: Hsien-Wei Kuo

Abstract:

The thoughts of the military citizens, pragmatism, naturalism and nationalism related to physical education were developed during the warring period of the Republic of China. Moreover, the development of martial art formed by nationalism and political party was to utilize to save the nation, the people and the world. The martial art was also promoted in the system of school physical education gradually at the same time. The aim of this study is to explore the role, duty and position of the martial art education with the political color and advocacy in the system of school physical education. This study focuses on the practice, course hours, selective materials and competitive rules of physical education in the school system in modern China. Therefore, the methods of the historical research and content analysis were used to collect the historical materials and documents for going into them. The results will give a detailed account of the developed model of institutionalization, unification and regularization of martial art, and its growing, golden and stagnant periods in the school physical education system under the impact of western sport and physical education. It may sum up the meaning relationships among the politics, education practice and sport for all.

Keywords: martial art education, national martial arts institution, sick man of East Asia, the may 4th movement

Procedia PDF Downloads 378