Search results for: preparatory experimental schools

Authors: A. Brahma

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Drying is a phenomenon that accompanies the hardening of hydraulic materials. It can, if it is not prevented, lead to significant spontaneous dimensional variations, which the cracking is one of events. In this context, cracking promotes the transport of aggressive agents in the material, which can affect the durability of concrete structures. Drying shrinkage develops over a long period almost 30 years although most occurred during the first three years. Drying shrinkage stabilizes when the material is water balance with the external environment. The drying shrinkage of cementitious materials is due to the formation of capillary tensions in the pores of the material, which has the consequences of bringing the solid walls of each other. Knowledge of the shrinkage characteristics of concrete is a necessary starting point in the design of structures for crack control. Such knowledge will enable the designer to estimate the probable shrinkage movement in reinforced or prestressed concrete and the appropriate steps can be taken in design to accommodate this movement. This study is concerned the modelling of drying shrinkage of the hydraulic materials and the prediction of the rate of spontaneous deformations of hydraulic materials during hardening. The model developed takes in consideration the main factors affecting drying shrinkage. There was agreement between drying shrinkage predicted by the developed model and experimental results. In last we show that developed model describe the evolution of the drying shrinkage of high performances concretes correctly.

Keywords: drying, hydraulic concretes, shrinkage, modeling, prediction

Procedia PDF Downloads 337

Authors: Alirıza Kaleli, M. Akif Ceviz, Erdoğan Güner, Köksal Erentürk

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The cyclic variations in spark ignition engines occurring especially under specific engine operating conditions make the maximum pressure variable for successive in-cylinder pressure cycles. Minimization of cyclic variations has a great importance in effectively operating near to lean limit, or at low speed and load. The cyclic variations may reduce the power output of the engine, lead to operational instabilities, and result in undesirable engine vibrations and noise. In this study, spark timing is controlled in order to reduce the cyclic variations in spark ignition engines. Firstly, an ARMAX model has developed between spark timing and maximum pressure using system identification techniques. By using this model, the maximum pressure of the next cycle has been predicted. Then, self-tuning minimum variance controller has been designed to change the spark timing for consecutive cycles of the first cylinder of test engine to regulate the in-cylinder maximum pressure. The performance of the proposed controller is illustrated in real time and experimental results show that the controller has a reliable effect on cycle to cycle variations of maximum cylinder pressure when the engine works under low speed conditions.

Keywords: cyclic variations, cylinder pressure, SI engines, self tuning controller

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Authors: Pratch Kittipongpattana, Thongchai Fongsamootr

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This research aimed to study the influences of a soot blowing operation and geometrical variables to the stress characteristic of water wall tubes located in soot blowing areas which caused the boilers of Mae Moh power plant to lose their generation hour. The research method is divided into 2 parts (a) measuring the strain on water wall tubes by using 3-element rosette strain gages orientation during a full capacity plant operation and in periods of soot blowing operations (b) creating a finite element model in order to calculate stresses on tubes and validating the model by using experimental data in a steady state plant operation. Then, the geometrical variables in the model were changed to study stresses on the tubes. The results revealed that the stress was not affected by the soot blowing process and the finite element model gave the results 1.24% errors from the experiment. The geometrical variables influenced the stress, with the most optimum tubes design in this research reduced the average stress from the present design 31.28%.

Keywords: boiler water wall tube, finite element, stress analysis, strain gage rosette

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Authors: Thomas Turner

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Due to the Covid-19 pandemic alternative ways of delivering dental education were required. As a result, many institutions moved teaching online. The impact of this is poorly understood. Is online problem-based learning (PBL) and case-based learning (CBL) effective and is it suitable in the post-pandemic era? PBL and CBL are both types of interactive, group-based learning which are growing in popularity within many dental schools. PBL was first introduced in the 1960’s and can be defined as learning which occurs from collaborative work to resolve a problem. Whereas CBL encourages learning from clinical cases, encourages application of knowledge and helps prepare learners for clinical practice. To evaluate the use of online PBL and CBL. A literature search was conducted using the CINAHL, Embase, PubMed and Web of Science databases. Literature was also identified from reference lists. Studies were only included from dental education. Seven suitable studies were identified. One of the studies found a high learner and facilitator satisfaction rate with online CBL. Interestingly one study found learners preferred CBL over PBL within an online format. A study also found, that within the context of distance learning, learners preferred a hybrid curriculum including PBL over a traditional approach. A further study pointed to the limitations of PBL within an online format, such as reduced interaction, potentially hindering the development of communication skills and the increased time and technology support required. An audience response system was also developed for use within CBL and had a high satisfaction rate. Interestingly one study found achievement of learning outcomes was correlated with the number of student and staff inputs within an online format. Whereas another study found the quantity of learner interactions were important to group performance, however the quantity of facilitator interactions was not. This review identified generally favourable evidence for the benefits of online PBL and CBL. However, there is limited high quality evidence evaluating these teaching methods within dental education and there appears to be limited evidence comparing online and faceto-face versions of these sessions. The importance of the quantity of learner interactions is evident, however the importance of the quantity of facilitator interactions appears to be questionable. An element to this may be down to the quality of interactions, rather than just quantity. Limitations of online learning regarding technological issues and time required for a session are also highlighted, however as learners and facilitators get familiar with online formats, these may become less of an issue. It is also important learners are encouraged to interact and communicate during these sessions, to allow for the development of communication skills. Interestingly CBL appeared to be preferred to PBL in an online format. This may reflect the simpler nature of CBL, however further research is required to explore this finding. Online CBL and PBL appear promising, however further research is required before online formats of these sessions are widely adopted in the post-pandemic era.

Keywords: case-based learning, online, problem-based learning, remote, virtual

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Authors: T. S. Terence Ma, Irene T. Ho

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Conducting adequate assessment of the challenges students with ASD (Autism Spectrum Disorder) face and the support they need is imperative for promoting their school adjustment. Students with ASD often show deficits in communication, social interaction, emotional regulation, and self-management in learning. While targeting these areas in intervention is often helpful, we argue that not enough attention has been paid to weak self-regulation being a key factor underlying their manifest difficulty in all these areas. Self-regulation refers to one’s ability to moderate their behavioral or affective responses without assistance from others. Especially for students with high functioning autism, who often show problems not so much in acquiring the needed skills but rather in applying those skills appropriately in everyday problem-solving, self-regulation becomes a key to successful adjustment in daily life. Therefore, a greater understanding of the construct of self-regulation, its relationship with other daily skills, and its role in school functioning for students with ASD would generate insights on how students’ school adjustment could be promoted more effectively. There were two focuses in this study. Firstly, we examined the extent to which self-regulation is a distinct construct that is differentiable from other daily skills and the most salient indicators of this construct. Then we tested a model of relationships between self-regulation and other daily school skills as well as their relative and combined effects on school adjustment. A total of 1,345 Grade1 to Grade 6 students with ASD attending mainstream schools in Hong Kong participated in the research. In the first stage of the study, teachers filled out a questionnaire consisting of 136 items assessing a wide range of student skills in social, emotional and learning areas. Results from exploratory factor analysis (EFA) with 673 participants and subsequent confirmatory factor analysis (CFA) with another group of 672 participants showed that there were five distinct factors of school skills, namely (1) communication skills, (2) pro-social behavior, (3) emotional skills, (4) learning management, and (5) self-regulation. Five scales representing these skill dimensions were generated. In the second stage of the study, a model postulating the mediating role of self-regulation for the effects of the other four types of skills on school adjustment was tested with structural equation modeling (SEM). School adjustment was defined in terms of the extent to which the student is accepted well in school, with high engagement in school life and self-esteem as well as good interpersonal relationships. A 5-item scale was used to assess these aspects of school adjustment. Results showed that communication skills, pro-social behavior, emotional skills and learning management had significant effects on school adjustment only indirectly through self-regulation, and their total effects were found to be not high. The results indicate that support rendered to students with ASD focusing only on the training of well-defined skills is not adequate for promoting their inclusion in school. More attention should be paid to the training of self-management with an emphasis on the application of skills backed by self-regulation. Also, other non-skill factors are important in promoting inclusive education.

Keywords: autism, assessment, factor analysis, self-regulation, school adjustment

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Authors: Xiaozhou Liu, Guangyu Zhu, Yu Zhang, Hongwei Wu

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The wind-box is one of the important components of a Circulating Fluidized Bed (CFB) boiler. The uniformity of air flow in the wind-box of is very important for highly efficient operation of the CFB boiler. Non-uniform air flow distribution within the wind-box can reduce the boiler's thermal efficiency, leading to higher energy consumptions. An effective measure to solve this problem is to install an air flow distributing device in the wind-box. In order to validate the effectiveness of the air flow distributing device, visual and velocity distribution uniformity experiments have been carried out under five different test conditions by using a 1:64 scale model of a 220t/hr CFB boiler. It has been shown that the z component of flow velocity remains almost the same at control cross-sections of the wind-box, with a maximum variation of less than 10%. Moreover, the same methodology has been carried out to a full-scale 220t/hr CFB boiler. The hot test results depict that the thermal efficiency of the boiler has increased from 85.71% to 88.34% when tested with an air flow distributing device in place, which is equivalent to a saving of 5,000 tons of coal per year. The economic benefits of this energy-saving technology have been shown to be very significant, which clearly demonstrates that the technology is worth applying and popularizing.

Keywords: circulating fluidized bed, CFB, wind-box, air flow distributing device, visual experiment, velocity distribution uniformity experiment, hot test

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Authors: Sarah Mhae Diaz, Erika Anna De Leon, Jacklin Alwil Cartagena, Geordan Caruncong, Micah Riezl Gonzales

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This study examined the intervention of threat and surveillance on the obedience of 100 preschool children through a task variable experiment replicated from the previous studies of Higbee (1979), and Chua, J., Chua, M., & Pico (1983). Nowadays, obedience among Filipino children to authority is disregarded since they are more outspoken and rebel due to social influences. With this, aside from corporal punishment, threat and surveillance became a mean of inducing obedience. Threat, according to the Dissonance Theory, can give attitudinal change. On the other hand, surveillance, according to the Theory of Social Facilitation, can either contribute to the completion or failure to do a task. Through a 2x2 factorial design, results show; (1) threat (F(1,96) = 12.487, p < 0.05) and (2) surveillance (F(1,96)=9.942, p<.05) had a significant main effect on obedience, suggesting that the Dissonance Theory and Theory of Social Facilitation is respectively true in the study. On the other hand, (3) no interaction (F(1,96)=1.303, p > .05) was seen since threat and surveillance both have a main effect that could be positive or negative, or could be because of their complementary property as supported by the post-hoc results. Also, (4) most effective commanding style is threat and surveillance setting (M = 30.04, SD = 7.971) due to the significant main effect of the two variables. With this, in the Filipino Setting, threat and surveillance has proven to be a very effective strategy to discipline and induce obedience from a child.

Keywords: experimental study, obedience, preschool children, surveillance, threat

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Authors: A. Pesin, D. Pustovoytov, M. Sverdlik

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Traditionally, the need in items represents a large body of rotation (e.g. shrouds of various process units: a converter, a mixer, a scrubber, a steel ladle and etc.) is satisfied by using them at engineering enterprises. At these enterprises large parts of bodies of rotation are made on stamping units or bending and forming machines. In Nosov Magnitogorsk State Technical University in alliance with JSC "Magnitogorsk Metal and Steel Works" there was suggested and implemented the technology for producing such items based on a combination of asymmetric rolling processes and plastic bending under conditions of the plate mill. In this paper, based on finite elemental mathematical simulation in technology of a combined process of asymmetric rolling and bending plastic has been improved. It is shown that for the same curvature along the entire length of the metal sheet it is necessary to introduce additional asymmetry speed when rolling front end and tape trailer. Production of large bodies of rotation at mill 4500 JSC "Magnitogorsk Metal and Steel Works" showed good convergence of theoretical and experimental values of the curvature of the metal. Economic effect obtained more than 1.0 million dollars.

Keywords: asymmetric rolling, plastic bending, combined process, FEM

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Authors: Mohd Moiz Khan, S. M. Mahajani, G. N. Jadhav

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Waste foundry sand (total clay content 15%) contains toxic heavy metals and particulate matter which make dumping of waste sand an environmental and health hazard. Disposal of waste foundry sand (WFS) remains one of the substantial challenges faced by Indian foundries nowadays. To cope up with this issue, the chemical method was used to reclaim WFS. A stirrer tank reactor was used for chemical reclamation. Experiments were performed to reduce the total clay content from 15% to as low as 0.9% in chemical reclamation. This method, although found to be effective for WFS reclamation, it may face a challenge due to the possibly high operating cost. Reclaimed sand was found to be satisfactory in terms of sand qualities such as total clay (0.9%), active clay (0.3%), acid demand value (ADV) (2.6%), loss on igniting (LOI) (3 %), grain fineness number (GFN) (56), and compressive strength (60 kPa). The experimental data generated on chemical reactor under different conditions is further used to optimize the design and operating parameters (rotation speed, sand to acidic solution ratio, acid concentration, temperature and time) for the best performance. The use of reclaimed sand within the foundry would improve the economics and efficiency of the process and reduce environmental concerns.

Keywords: chemical reclamation, clay content, environmental concerns, recycle, waste foundry sand

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Authors: Rylle Evan Gabriel Zamora, Micah Dennise Malia, Abygail Deniese Villabona

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The primary motivators of altruism are usually viewed as mutually exclusive. In this study, we wanted to know if the two primary motivators, reciprocity and empathy, can work together in motivating altruism. Therefore, we wanted to find out if there is a significant interaction of effects between reciprocity and empathy. To show how this may occur, we devised the combined altruism model, which is based on Batson’s empathy altruism hypothesis. A sample of 120, 6th-grade students were randomly selected and then randomly assigned to four treatment groups. A 2x2 between subjects’ design was used, which had empathy and reciprocity as independent variables, and altruism as the dependent variable. The study made use of materials that were effort based, where subjects were required to complete a task or a puzzle to help a person in a given scenario, two videos, one to prime empathy were also used. This along with Witt & Boleman’s adapted Self-Reported Altruism Scale was used to determine an individual’s altruism. It was found that both variables were significant in motivating altruism, with empathy being the greater of the two. However, there was no significant interaction of effects between the two variables. To explain why this occurred, we turned to the combined altruism model, where it was found that when empathically primed, we tend to not think of ourselves when helping others. Future studies could focus on other variables, especially age which is said to be one of the greatest factors that influenced the results of the experiment.

Keywords: reciprocity, empathy, altruism, experimental psychology, social psychology

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Authors: Fathi Kallel, Ahmed Ben Hamida, Christian Berger-Vachon

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In this paper, a Speech Enhancement Algorithm based on Multi-Band Spectral Subtraction (MBSS) principle is evaluated for Bilateral Cochlear Implant (BCI) users. Specifically, dual-channel noise power spectral estimation algorithm using Power Spectral Densities (PSD) and Cross Power Spectral Densities (CPSD) of the observed signals is studied. The enhanced speech signal is obtained using Dual-Channel Multi-Band Spectral Subtraction ‘DC-MBSS’ algorithm. For performance evaluation, objective speech assessment test relying on Perceptual Evaluation of Speech Quality (PESQ) score is performed to fix the optimal number of frequency bands needed in DC-MBSS algorithm. In order to evaluate the speech intelligibility, subjective listening tests are assessed with 3 deafened BCI patients. Experimental results obtained using French Lafon database corrupted by an additive babble noise at different Signal-to-Noise Ratios (SNR) showed that DC-MBSS algorithm improves speech understanding for single and multiple interfering noise sources.

Keywords: speech enhancement, spectral substracion, noise estimation, cochlear impalnt

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Authors: Sudha Arlikatti, Laura Siebeneck, Simon A. Andrew

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The objective of this research is to measure organizational resiliency through five attributes namely, rapidity, redundancy, resourcefulness, and robustness and to provide recommendations for resiliency building in flood risk communities. The research was conducted in Thailand following the severe floods of 2011 triggered by Tropical Storm Nock-ten. The floods lasted over eight months starting in June 2011 affecting 65 of the country’s 76 provinces and over 12 million people. Funding from a US National Science Foundation grant was used to collect ephemeral data in rural (Ayutthaya), suburban (Pathum Thani), and urban (Bangkok) provinces of Thailand. Semi-structured face-to-face interviews were conducted in Thai with 44 contacts from public, private, and non-profit organizations including universities, schools, automobile companies, vendors, tourist agencies, monks from temples, faith based organizations, and government agencies. Multiple triangulations were used to analyze the data by identifying selective themes from the qualitative data, validated with quantitative data and news media reports. This helped to obtain a more comprehensive view of how organizations in different geographic settings varied in their understanding of what enhanced or hindered their resilience and consequently their speed and capacities to respond. The findings suggest that the urban province of Bangkok scored highest in resourcefulness, rapidity of response, robustness, and ability to rebound. This is not surprising considering that it is the country’s capital and the seat of government, economic, military and tourism sectors. However, contrary to expectations all 44 respondents noted that the rural province of Ayutthaya was the fastest to recover amongst the three. Its organizations scored high on redundancy and rapidity of response due to the strength of social networks, a flood disaster sub-culture due to annual flooding, and the help provided by monks from and faith based organizations. Organizations in the suburban community of Pathum Thani scored lowest on rapidity of response and resourcefulness due to limited and ambiguous warnings, lack of prior flood experience and controversies that government flood protection works like sandbagging favored the capital city of Bangkok over them. Such a micro-level examination of organizational resilience in rural, suburban and urban areas in a country through mixed methods studies has its merits in getting a nuanced understanding of the importance of disaster subcultures and religious norms for resilience. This can help refocus attention on the strengths of social networks and social capital, for flood mitigation.

Keywords: disaster subculture, flood response, organizational resilience, Thailand floods, religious beliefs and response, social capital and disasters

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Authors: Clifford Irikefe Gbeyonron

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Applied linguists concur that there is low-level achievement in English language use among Nigerian secondary school students. One of the factors that exacerbate this is classroom feature of which large class size is obvious. This study investigated the impact of large classes on learning English as a second language (ESL) at junior secondary school (JSS) in Yobe State. To achieve this, Solomon four-group experimental design was used. 382 subjects were divided into four groups and taught ESL for thirteen weeks. 356 subjects wrote the post-test. Data from the systematic observation and post-test were analyzed via chi square and ANOVA. Results indicated that learners in large classes (LLC) attain lower linguistic progress than learners in small classes (LSC). Furthermore, LSC have more chances to access teacher evaluation and participate actively in classroom discourse than LLC. In consequence, large classes have adverse effects on learning ESL in Yobe State. This is inimical to English language education given that each learner of ESL has their individual peculiarity within each class. It is recommended that strategies that prioritize individualization, grouping, use of language teaching aides, and theorization of innovative models in respect of large classes be considered.

Keywords: large classes, achievement, classroom discourse

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Authors: Shirley S. Ho

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The advancement and development of social media have inadvertently brought about a new form of bullying – cyberbullying – that transcends across physical boundaries of space. Although extensive research has been conducted in the field of cyberbullying, most of these studies have taken an overwhelmingly empirical angle. Theories guiding cyberbullying research are few. Furthermore, very few studies have explored the association between parental mediation and cyberbullying, with majority of existing studies focusing on cyberbullying victimization rather than perpetration. Therefore, this present study investigates cyberbullying perpetration from a theoretical angle, with a focus on the Theory of Reasoned Action and the Parental Mediation Theory. More specifically, this study examines the direct effects of attitude, subjective norms, descriptive norms, injunctive norms and active mediation and restrictive mediation on cyberbullying perpetration on social media among children and adolescents in Singapore. Furthermore, the moderating role of age on the relationship between parental mediation and cyberbullying perpetration on social media are examined. A self-administered paper-and-pencil nationally-representative survey was conducted. Multi-stage cluster random sampling was used to ensure that schools from all the four (North, South, East, and West) regions of Singapore were equally represented in the sample used for the survey. In all 607 upper primary school children (i.e., Primary 4 to 6 students) and 782 secondary school adolescents participated in our survey. The total average response rates were 69.6% for student participation. An ordinary least squares hierarchical regression analysis was conducted to test the hypotheses and research questions. The results revealed that attitude and subjective norms were positively associated with cyberbullying perpetration on social media. Descriptive norms and injunctive norms were not found to be significantly associated with cyberbullying perpetration. The results also showed that both parental mediation strategies were negatively associated with cyberbullying perpetration on social media. Age was a significant moderator of both parental mediation strategies and cyberbullying perpetration. The negative relationship between active mediation and cyberbullying perpetration was found to be greater in the case of children than adolescents. Children who received high restrictive parental mediation were less likely to perform cyberbullying behaviors, while adolescents who received high restrictive parental mediation were more likely to be engaged in cyberbullying perpetration. The study reveals that parents should apply active mediation and restrictive mediation in different ways for children and adolescents when trying to prevent cyberbullying perpetration. The effectiveness of active parental mediation for reducing cyberbullying perpetration was more in the case of children than for adolescents. Younger children were found to be more likely to respond more positively toward restrictive parental mediation strategies, but in the case of adolescents, overly restrictive control was found to increase cyberbullying perpetration. Adolescents exhibited less cyberbullying behaviors when under low restrictive strategies. Findings highlight that the Theory of Reasoned Action and Parental Mediation Theory are promising frameworks to apply in the examination of cyberbullying perpetration. The findings that different parental mediation strategies had differing effectiveness, based on the children’s age, bring about several practical implications that may benefit educators and parents when addressing their children’s online risk.

Keywords: cyberbullying perpetration, theory of reasoned action, parental mediation, social media, Singapore

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Authors: Arthur D. Wiedemann, Christopher Fuller, Kyle A. Pascioni

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With the introduction of electric motors, small unmanned aerial vehicle designers have to consider trade-offs between acoustic noise and thrust generated. Currently, there are few low-computational tools available for predicting acoustic noise emitted by a propeller into the far-field. Artificial neural networks offer a highly non-linear and adaptive model for predicting isolated and interactive tonal noise. But neural networks require large data sets, exceeding practical considerations in modeling experimental results. A methodology known as physics guided machine learning has been applied in this study to reduce the required data set to train the network. After building and evaluating several neural networks, the best model is investigated to determine how the network successfully predicts the acoustic waveform. Lastly, a post-network transfer function is developed to remove discontinuity from the predicted waveform. Overall, methodologies from physics guided machine learning show a notable improvement in prediction performance, but additional loss functions are necessary for constructing predictive networks on small datasets.

Keywords: aeroacoustics, machine learning, propeller, rotor, neural network, physics guided machine learning

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Authors: Lianzhong Zhang, Chao Huang

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Sea-land segmentation is a basic step in many tasks such as sea surface monitoring and ship detection. The existing sea-land segmentation algorithms have poor segmentation accuracy, and the parameter adjustments are cumbersome and difficult to meet actual needs. Also, the current sea-land segmentation adopts traditional deep learning models that use Convolutional Neural Networks (CNN). At present, the transformer architecture has achieved great success in the field of natural images, but its application in the field of radar images is less studied. Therefore, this paper proposes a sea-land segmentation method based on the transformer architecture to strengthen edge supervision. It uses a self-attention mechanism with a gating strategy to better learn relative position bias. Meanwhile, an additional edge supervision branch is introduced. The decoder stage allows the feature information of the two branches to interact, thereby improving the edge precision of the sea-land segmentation. Based on the Gaofen-3 satellite image dataset, the experimental results show that the method proposed in this paper can effectively improve the accuracy of sea-land segmentation, especially the accuracy of sea-land edges. The mean IoU (Intersection over Union), edge precision, overall precision, and F1 scores respectively reach 96.36%, 84.54%, 99.74%, and 98.05%, which are superior to those of the mainstream segmentation models and have high practical application values.

Keywords: SAR, sea-land segmentation, deep learning, transformer

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Authors: Reza Salehi, Peter L. Dold, Yves Comeau

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The aim of the present study was to investigate the effect of a total of 6 operating parameters including pH (X1), temperature (X2), stirring speed (X3), chemical oxygen demand (COD) (X4), volatile suspended solids (VSS) (X5) and time (X6) on anaerobic orthophosphate release from enhanced biological phosphorus removal (EBPR) sludge. An 8-run Plackett Burman design was applied and the statistical analysis of the experimental data was performed using Minitab16.2.4 software package. The Analysis of variance (ANOVA) results revealed that temperature, COD, VSS and time had a significant effect with p-values of less than 0.05 whereas pH and stirring speed were identified as non-significant parameters, but influenced orthophosphate release from the EBPR sludge. The mathematic expression obtained by the first-order multiple linear regression model between orthophosphate release from the EBPR sludge (Y) and the operating parameters (X1-X6) was Y=18.59+1.16X1-3.11X2-0.81X3+3.79X4+9.89X5+4.01X6. The model p-value and coefficient of determination (R2) value were 0.026 and of 99.87%, respectively, which indicates the model is significant and the predicted values of orthophosphate release from the EBPR sludge have been excellently correlated with the observed values.

Keywords: anaerobic, operating parameters, orthophosphate release, Plackett-Burman design

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.

Keywords: human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, prior distribution and approximate posterior distribution, KTH dataset

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Authors: Mohammad Ahmad, Sander Gersen, Erwin Wilbers

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Carbon capture, transport and underground storage have become a major solution to reduce CO2 emissions from power plants and other large CO2 sources. A big part of this captured CO2 stream is transported at high pressure dense phase conditions and stored in offshore underground depleted oil and gas fields. CO2 is also transported in offshore pipelines to be used for enhanced oil and gas recovery. The captured CO2 stream with impurities may contain water that causes severe corrosion problems, flow assurance failure and might damage valves and instrumentations. Thus, free water formation should be strictly prevented. The purpose of this work is to study the solubility of water in pure CO2 and in CO2 mixtures under real pipeline pressure (90-150 bar) and temperature operation conditions (5-35°C). A set up was constructed to generate experimental data. The results show the solubility of water in CO2 mixtures increasing with the increase of the temperature or/and with the increase in pressure. A drop in water solubility in CO2 is observed in the presence of impurities. The data generated were then used to assess the capabilities of two mixture models: the GERG-2008 model and the EOS-CG model. By generating the solubility data, this study contributes to determine the maximum allowable water content in CO2 pipelines.

Keywords: carbon capture and storage, water solubility, equation of states, fluids engineering

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Authors: Jamshaid Ul Rahman, Faiza Makhdoom, Dianchen Lu

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Activation functions play a decisive role in determining the capacity of Deep Neural Networks (DNNs) as they enable neural networks to capture inherent nonlinearities present in data fed to them. The prior research on activation functions primarily focused on the utility of monotonic or non-oscillatory functions, until Growing Cosine Unit (GCU) broke the taboo for a number of applications. In this paper, a Convolutional Neural Network (CNN) model named as ASU-CNN is proposed which utilizes recently designed activation function ASU across its layers. The effect of this non-monotonic and oscillatory function is inspected through feature map visualizations from different convolutional layers. The optimization of proposed network is offered by Adam with a fine-tuned adjustment of learning rate. The network achieved promising results on both training and testing data for the classification of CIFAR-10. The experimental results affirm the computational feasibility and efficacy of the proposed model for performing tasks related to the field of computer vision.

Keywords: amplifying sine unit, activation function, convolutional neural networks, oscillatory activation, image classification, CIFAR-10

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Authors: Philippe Gugler

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Goal of the study: The concept of competitiveness has been addressed by economic theorists and policymakers for several hundreds of years, with both groups trying to understand the drivers of economic prosperity and social welfare. The goal of this contribution is to address the major useful theoretical contributions that permit to identify the main drivers of a territory’s competitiveness. We first present the major contributions found in the classical and neo-classical theories. Then, we concentrate on two majors schools providing significant thoughts on the competitiveness of locations: the Economic Geography (EG) School and the International Business (IB) School. Methodology: The study is based on a literature review of the classical and neo-classical theories, on the economic geography theories and on the international business theories. This literature review establishes links between these theoretical mainstreams. This work is based on the academic framework establishing a meaningful literature review aimed to respond to our research question and to develop further research in this field. Results: The classical and neo-classical pioneering theories provide initial insights that territories are different and that these differences explain the discrepancies in their levels of prosperity and standards of living. These theories emphasized different factors impacting the level and the growth of productivity in a given area and therefore the degree of their competitiveness. However, these theories are not sufficient to more precisely identify the drivers and enablers of location competitiveness and to explain, in particular, the factors that drive the creation of economic activities, the expansion of economic activities, the creation of new firms and the attraction of foreign firms. Prosperity is due to economic activities created by firms. Therefore, we need more theoretical insights to scrutinize the competitive advantages of territories or, in other words, their ability to offer the best conditions that enable economic agents to achieve higher rates of productivity in open markets. Two major theories provide, to a large extent, the needed insights: the economic geography theory and the international business theory. The economic geography studies scrutinized in this study from Marshall to Porter, aim to explain the drivers of the concentration of specific industries and activities in specific locations. These activity agglomerations may be due to the creation of new enterprises, the expansion of existing firms, and the attraction of firms located elsewhere. Regarding this last possibility, the international business (IB) theories focus on the comparative advantages of locations as far as multinational enterprises (MNEs) strategies are concerned. According to international business theory, the comparative advantages of a location serves firms not only by exploiting their ownership advantages (mostly as far as market seeking, resource seeking and efficiency seeking investments are concerned) but also by augmenting and/or creating new ownership advantages (strategic asset seeking investments). The impact of a location on the competitiveness of firms is considered from both sides: the MNE’s home country and the MNE’s host country.

Keywords: competitiveness, economic geography, international business, attractiveness of businesses

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Authors: Antonio Gioiosa, Simone Doanti, Eric Flumerfelt, Luca Morescalchi, Elena Pedreschi, Gianantonio Pezzullo, Ryan A. Rivera, Franco Spinella

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The Mu2e experiment at Fermilab aims to measure the charged-lepton flavour violating neutrino-less conversion of a negative muon into an electron in the field of an aluminum nucleus. With the expected experimental sensitivity, Mu2e will improve the previous limit of four orders of magnitude. The Mu2e data acquisition (DAQ) system provides hardware and software to collect digitized data from the tracker, calorimeter, cosmic ray veto, and beam monitoring systems. Mu2e’s trigger and data acquisition system (TDAQ) uses otsdaq as its solution. developed at Fermilab, otsdaq uses the artdaq DAQ framework and art analysis framework, under-the-hood, for event transfer, filtering, and processing. Otsdaq is an online DAQ software suite with a focus on flexibility and scalability while providing a multi-user, web-based interface accessible through the Chrome or Firefox web browser. The detector read out controller (ROC) from the tracker and calorimeter stream out zero-suppressed data continuously to the data transfer controller (DTC). Data is then read over the PCIe bus to a software filter algorithm that selects events which are finally combined with the data flux that comes from a cosmic ray veto system (CRV).

Keywords: trigger, daq, mu2e, Fermilab

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

Abstract:

Accurate Liver, spleen and kidneys segmentation in abdominal CT images is one of the most important steps for computer aided abdominal organs pathology diagnosis. In this paper, we have proposed a new semi-automatic algorithm for Liver, spleen and kidneys area extraction in abdominal CT images. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. The algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.

Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, multi-abdominal organ segmentation, mosaic image, the watershed algorithm

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Authors: Juan Eduardo Rolon Rios, Fredy Alejandro Orjuela, Alexander Garcia Mariaca

Abstract:

For banana and potato wastes, their peels are processed in order to make animal food with the condition that those wastes must not have started the decomposition process. One alternative to taking advantage of those wastes is to obtain a bioplastic based on starch from banana and potato shells. These products are 100% biodegradables, and researchers have been studying them for different applications, helping in the reduction of organic wastes and ordinary plastic wastes. Without petroleum affecting the prices of bioplastics, bioplastics market has a growing tendency and it is seen that it can keep this tendency in the medium term up to 350%. In this work, it will be shown the results for elasticity module and percent elongation for bioplastics obtained from a mixture of starch of bananas and potatoes peels, with glycerol as plasticizer. The experimental variables were the plasticizer percentage and the mixture between banana starch and potato starch. The results show that the bioplastics obtained can be used in different applications such as plastic bags or sorbets, verifying their admissible degradation percentages for each one of these applications. The results also show that they agree with the data found in the literature due to the fact that mixtures with a major amount of potato starch had the best mechanical properties because of the potato starch characteristics.

Keywords: bioplastics, fruit waste, mechanical testing, mechanical properties

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Authors: Francisco J. Arias

Abstract:

Consideration is given to a mechanism of heat and mass transport in solutions similar than that of natural convection but with one important difference. Here the mechanism is not promoted by density differences in the fluid occurring due to temperature gradients (coefficient of thermal expansion) but rather by solubility differences due to the thermal dependence of the solubility (coefficient of thermal solubility). Utilizing a simplified physical model, it is shown that by the proper choice of the concentration of a given solution, convection might be induced by the alternating precipitation of the solute -when the solution becomes supersaturated, and its posterior recombination when changes in temperature occurs. The spontaneous change in the Gibbs free energy during the mixing is the driven force for the mechanism. The maximum extractable energy from this new type of thermal convection was derived. Experimental data from a closed-loop circuit was obtained demonstrating the feasibility for continuous separation and recombination of the solution. This type of heat and mass transport -which doesn’t depend on gravity, might potentially be interesting for heat and mass transport downwards (as in solar-roof collectors to inside homes), horizontal (e.g., microelectronic applications), and in microgravity (space technology). Also, because the coefficient of thermal solubility could be positive or negative, the investigated thermo-osmosis convection can be used either for heating or cooling.

Keywords: natural convection, thermal gradient, solubility, osmotic pressure

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Authors: Sonia Perez-Gamboa, Qingquan Sun, Yan Zhang

Abstract:

Non-intrusive sensor-based human activity recognition (HAR) is utilized in a spectrum of applications, including fitness tracking devices, gaming, health care monitoring, and smartphone applications. Deep learning models such as convolutional neural networks (CNNs) and long short term memory (LSTM) recurrent neural networks (RNNs) provide a way to achieve HAR accurately and effectively. In this paper, we design a multi-layer hybrid architecture with CNN and LSTM and explore a variety of multi-layer combinations. Based on the exploration, we present a lightweight, hybrid, and multi-layer model, which can improve the recognition performance by integrating local features and scale-invariant with dependencies of activities. The experimental results demonstrate the efficacy of the proposed model, which can achieve a 94.7% activity recognition rate on a benchmark human activity dataset. This model outperforms traditional machine learning and other deep learning methods. Additionally, our implementation achieves a balance between recognition rate and training time consumption.

Keywords: deep learning, LSTM, CNN, human activity recognition, inertial sensor

Procedia PDF Downloads 150

Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

Abstract:

Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square

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Authors: Kwestan Salimi, Jenna Jacoby, Michelle Basham, Amy Cerato

Abstract:

The extreme annual weather patterns of the central United States have increased the need for underground shelters for protection from destructive tornadic activity. However, very few residential homes have basements due to the added construction expense and the prevalence of expansive soils covering the central portion of the United States. These expansive soils shrink and swell, increasing earth pressure on basement walls. To mitigate the effect of expansive soils on basement walls, this study performed bench-scale tests using a common natural expansive soil mitigated with a backfill layer of crumb rubber. The results revealed that at 80% soil compaction, a 1:6 backfill height to total height ratio produced a 66% reduction in swell pressure. However, this percent reduction decreased to 27% for 90% soil compaction. It was also found that there is a strong linear correlation between compaction percentage and reduction in swell pressure when using the same backfill height to total height ratio. Using this correlation and extrapolating to 95% compaction, the percent reduction in swell pressure was approximately 12%.

Keywords: expansive soils, swell/shrink, swell pressure, stabilization, crumb rubber

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Authors: J. Satya Eswari, Ch. Venkateswarlu

Abstract:

The formulation of a commercial pharmaceutical product involves several composition factors and response characteristics. When the formulation requires to satisfy multiple response characteristics which are conflicting, an optimal solution requires the need for an efficient multiobjective optimization technique. In this work, a regression is combined with a non-dominated sorting differential evolution (NSDE) involving Naïve & Slow and ε constraint techniques to derive different multiobjective optimization strategies, which are then evaluated by means of a trapidil pharmaceutical formulation. The analysis of the results show the effectiveness of the strategy that combines the regression model and NSDE with the integration of both Naïve & Slow and ε constraint techniques for Pareto optimization of trapidil formulation. With this strategy, the optimal formulation at pH=6.8 is obtained with the decision variables of micro crystalline cellulose, hydroxypropyl methylcellulose and compression pressure. The corresponding response characteristics of rate constant and release order are also noted down. The comparison of these results with the experimental data and with those of other multiple regression model based multiobjective evolutionary optimization strategies signify the better performance for optimal trapidil formulation.

Keywords: pharmaceutical formulation, multiple regression model, response surface method, radial basis function network, differential evolution, multiobjective optimization

Procedia PDF Downloads 409

Authors: Jayarama Reddy, Anand S., H., Sundaram, Jeldi Hemachandran

Abstract:

Forty two strains of Trichoderma sp. were isolated from cultivated lands around Bangalore and analyzed for their antagonistic potential against Macrophomina phaseolina. The potential of biocontrol agents ultimately lies in their capacity to control pathogens in vivo. Bioefficacy studies were hence conducted using chickpea (Cicer arientum c.v. Annigeri) as an experimental plant by the roll paper towel method. Overall the isolates T6, T35, T30, and T25 showed better antagonistic potential in addition to enhancing plant growth. The production of chitinases to break down the mycelial cell walls of fungal plant pathogens has been implicated as a major cause of biocontrol activity. In order to study the mechanism of biocontrol against Macrophomina phaseolina, ten better performing strains were plated on media, amended with colloidal chitin and Sclerotium rolfsii cell wall extract. All the isolates showed chitinolytic activity on day three as well as day five. Production of endochitinase and exochitinase were assayed in liquid media using colloidal chitin amended broth. Strains T35 and T6 displayed maximum endochitinase and exochitinase activity. Although all strains exhibited cellulase activity, the quantum of enzyme produced was higher in T35 and T6. The results also indicate a positive correlation between enzyme production and bioefficacy.

Keywords: biocontrol, bioefficacy, cellulase, chitinase

Procedia PDF Downloads 379