Search results for: dual phase lag model
17897 Greek Teachers' Understandings of Typical Language Development and of Language Difficulties in Primary School Children and Their Approaches to Language Teaching
Authors: Konstantina Georgali
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The present study explores Greek teachers’ understandings of typical language development and of language difficulties. Its core aim was to highlight that teachers need to have a thorough understanding of educational linguistics, that is of how language figures in education. They should also be aware of how language should be taught so as to promote language development for all students while at the same time support the needs of children with language difficulties in an inclusive ethos. The study, thus argued that language can be a dynamic learning mechanism in the minds of all children and a powerful teaching tool in the hands of teachers and provided current research evidence to show that structural and morphological particularities of native languages- in this case, of the Greek language- can be used by teachers to enhance children’s understanding of language and simultaneously improve oral language skills for children with typical language development and for those with language difficulties. The research was based on a Sequential Exploratory Mixed Methods Design deployed in three consecutive and integrative phases. The first phase involved 18 exploratory interviews with teachers. Its findings informed the second phase involving a questionnaire survey with 119 respondents. Contradictory questionnaire results were further investigated in a third phase employing a formal testing procedure with 60 children attending Y1, Y2 and Y3 of primary school (a research group of 30 language impaired children and a comparison group of 30 children with typical language development, both identified by their class teachers). Results showed both strengths and weaknesses in teachers’ awareness of educational linguistics and of language difficulties. They also provided a different perspective of children’s language needs and of language teaching approaches that reflected current advances and conceptualizations of language problems and opened a new window on how best they can be met in an inclusive ethos. However, teachers barely used teaching approaches that could capitalize on the particularities of the Greek language to improve language skills for all students in class. Although they seemed to realize the importance of oral language skills and their knowledge base on language related issues was adequate, their practices indicated that they did not see language as a dynamic teaching and learning mechanism that can promote children’s language development and in tandem, improve academic attainment. Important educational implications arose and clear indications of the generalization of findings beyond the Greek educational context.Keywords: educational linguistics, inclusive ethos, language difficulties, typical language development
Procedia PDF Downloads 38517896 A Physically-Based Analytical Model for Reduced Surface Field Laterally Double Diffused MOSFETs
Authors: M. Abouelatta, A. Shaker, M. El-Banna, G. T. Sayah, C. Gontrand, A. Zekry
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In this paper, a methodology for physically modeling the intrinsic MOS part and the drift region of the n-channel Laterally Double-diffused MOSFET (LDMOS) is presented. The basic physical effects like velocity saturation, mobility reduction, and nonuniform impurity concentration in the channel are taken into consideration. The analytical model is implemented using MATLAB. A comparison of the simulations from technology computer aided design (TCAD) and that from the proposed analytical model, at room temperature, shows a satisfactory accuracy which is less than 5% for the whole voltage domain.Keywords: LDMOS, MATLAB, RESURF, modeling, TCAD
Procedia PDF Downloads 20417895 Invasive Ranges of Gorse (Ulex europaeus) in South Australia and Sri Lanka Using Species Distribution Modelling
Authors: Champika S. Kariyawasam
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The distribution of gorse (Ulex europaeus) plants in South Australia has been modelled using 126 presence-only location data as a function of seven climate parameters. The predicted range of U. europaeus is mainly along the Mount Lofty Ranges in the Adelaide Hills and on Kangaroo Island. Annual precipitation and yearly average aridity index appeared to be the highest contributing variables to the final model formulation. The Jackknife procedure was employed to identify the contribution of different variables to gorse model outputs and response curves were used to predict changes with changing environmental variables. Based on this analysis, it was revealed that the combined effect of one or more variables could make a completely different impact to the original variables on their own to the model prediction. This work also demonstrates the need for a careful approach when selecting environmental variables for projecting correlative models to climatically distinct area. Maxent acts as a robust model when projecting the fitted species distribution model to another area with changing climatic conditions, whereas the generalized linear model, bioclim, and domain models to be less robust in this regard. These findings are important not only for predicting and managing invasive alien gorse in South Australia and Sri Lanka but also in other countries of the invasive range.Keywords: invasive species, Maxent, species distribution modelling, Ulex europaeus
Procedia PDF Downloads 13717894 Elastoplastic and Ductile Damage Model Calibration of Steels for Bolt-Sphere Joints Used in China’s Space Structure Construction
Authors: Huijuan Liu, Fukun Li, Hao Yuan
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The bolted spherical node is a common type of joint in space steel structures. The bolt-sphere joint portion almost always controls the bearing capacity of the bolted spherical node. The investigation of the bearing performance and progressive failure in service often requires high-fidelity numerical models. This paper focuses on the constitutive models of bolt steel and sphere steel used in China’s space structure construction. The elastoplastic model is determined by a standard tensile test and calibrated Voce saturated hardening rule. The ductile damage is found dominant based on the fractography analysis. Then Rice-Tracey ductile fracture rule is selected and the model parameters are calibrated based on tensile tests of notched specimens. These calibrated material models can benefit research or engineering work in similar fields.Keywords: bolt-sphere joint, steel, constitutive model, ductile damage, model calibration
Procedia PDF Downloads 14217893 42CrMo4 Steel Flow Behavior Characterization for High Temperature Closed Dies Hot Forging in Automotive Components Applications
Authors: O. Bilbao, I. Loizaga, F. A. Girot, A. Torregaray
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The current energetical situation and the high competitiveness in industrial sectors as the automotive one have become the development of new manufacturing processes with less energy and raw material consumption a real necessity. As consequence, new forming processes related with high temperature hot forging in closed dies have emerged in the last years as new solutions to expand the possibilities of hot forging and iron casting in the automotive industry. These technologies are mid-way between hot forging and semi-solid metal processes, working at temperatures higher than the hot forging but below the solidus temperature or the semi solid range, where no liquid phase is expected. This represents an advantage comparing with semi-solid forming processes as thixoforging, by the reason that no so high temperatures need to be reached in the case of high melting point alloys as steels, reducing the manufacturing costs and the difficulties associated to semi-solid processing of them. Comparing with hot forging, this kind of technologies allow the production of parts with as forged properties and more complex and near-net shapes (thinner sidewalls), enhancing the possibility of designing lightweight components. From the process viewpoint, the forging forces are significantly decreased, and a significant reduction of the raw material, energy consumption, and the forging steps have been demonstrated. Despite the mentioned advantages, from the material behavior point of view, the expansion of these technologies has shown the necessity of developing new material flow behavior models in the process working temperature range to make the simulation or the prediction of these new forming processes feasible. Moreover, the knowledge of the material flow behavior at the working temperature range also allows the design of the new closed dies concept required. In this work, the flow behavior characterization in the mentioned temperature range of the widely used in automotive commercial components 42CrMo4 steel has been studied. For that, hot compression tests have been carried out in a thermomechanical tester in a temperature range that covers the material behavior from the hot forging until the NDT (Nil Ductility Temperature) temperature (1250 ºC, 1275 ºC, 1300 ºC, 1325 ºC, 1350ºC, and 1375 ºC). As for the strain rates, three different orders of magnitudes have been considered (0,1 s-1, 1s-1, and 10s-1). Then, results obtained from the hot compression tests have been treated in order to adapt or re-write the Spittel model, widely used in automotive commercial softwares as FORGE® that restrict the current existing models up to 1250ºC. Finally, the obtained new flow behavior model has been validated by the process simulation in a commercial automotive component and the comparison of the results of the simulation with the already made experimental tests in a laboratory cellule of the new technology. So as a conclusion of the study, a new flow behavior model for the 42CrMo4 steel in the new working temperature range and the new process simulation in its application in automotive commercial components has been achieved and will be shown.Keywords: 42CrMo4 high temperature flow behavior, high temperature hot forging in closed dies, simulation of automotive commercial components, spittel flow behavior model
Procedia PDF Downloads 13417892 A Comparative Study of Generalized Autoregressive Conditional Heteroskedasticity (GARCH) and Extreme Value Theory (EVT) Model in Modeling Value-at-Risk (VaR)
Authors: Longqing Li
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The paper addresses the inefficiency of the classical model in measuring the Value-at-Risk (VaR) using a normal distribution or a Student’s t distribution. Specifically, the paper focuses on the one day ahead Value-at-Risk (VaR) of major stock market’s daily returns in US, UK, China and Hong Kong in the most recent ten years under 95% confidence level. To improve the predictable power and search for the best performing model, the paper proposes using two leading alternatives, Extreme Value Theory (EVT) and a family of GARCH models, and compares the relative performance. The main contribution could be summarized in two aspects. First, the paper extends the GARCH family model by incorporating EGARCH and TGARCH to shed light on the difference between each in estimating one day ahead Value-at-Risk (VaR). Second, to account for the non-normality in the distribution of financial markets, the paper applies Generalized Error Distribution (GED), instead of the normal distribution, to govern the innovation term. A dynamic back-testing procedure is employed to assess the performance of each model, a family of GARCH and the conditional EVT. The conclusion is that Exponential GARCH yields the best estimate in out-of-sample one day ahead Value-at-Risk (VaR) forecasting. Moreover, the discrepancy of performance between the GARCH and the conditional EVT is indistinguishable.Keywords: Value-at-Risk, Extreme Value Theory, conditional EVT, backtesting
Procedia PDF Downloads 32617891 Sound Performance of a Composite Acoustic Coating With Embedded Parallel Plates Under Hydrostatic Pressure
Authors: Bo Hu, Shibo Wang, Haoyang Zhang, Jie Shi
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With the development of sonar detection technology, the acoustic stealth technology of underwater vehicles is facing severe challenges. The underwater acoustic coating is developing towards the direction of low-frequency absorption capability and broad absorption frequency bandwidth. In this paper, an acoustic model of underwater acoustic coating of composite material embedded with periodical steel structure is presented. The model has multiple high absorption peaks in the frequency range of 1kHz-8kHz, where achieves high sound absorption and broad bandwidth performance. It is found that the frequencies of the absorption peaks are related to the classic half-wavelength transmission principle. The sound absorption performance of the acoustic model is investigated by the finite element method using COMSOL software. The sound absorption mechanism of the proposed model is explained by the distributions of the displacement vector field. The influence of geometric parameters of periodical steel structure, including thickness and distance, on the sound absorption ability of the proposed model are further discussed. The acoustic model proposed in this study provides an idea for the design of underwater low-frequency broadband acoustic coating, and the results shows the possibility and feasibility for practical underwater application.Keywords: acoustic coating, composite material, broad frequency bandwidth, sound absorption performance
Procedia PDF Downloads 17817890 Clinical Application of Mesenchymal Stem Cells for Cancer Therapy: A Review of Registered Clinical Trials
Authors: Tuong Thi Van Thuy, Dao Van Toan, Nguyen Duc Phuc
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Mesenchymal stem cells (MSCs) were discovered in the 1970s with their unique properties of differentiation, immunomodulation, multiple secreting, and homing factors to injured organs. MSC-based therapies have emerged as a promising strategy for various diseases such as cancer, tissue regeneration, or immunologic/inflammatory-related diseases. This study evaluated the clinical application of MSCs for cancer therapy in trials registered on Clinical Trial as of July 2022. The results showed 40 clinical trials used MSCs in various cancer conditions. 62% of trials used MSCs for therapeutic purposes to minimize the side effects of cancer treatment. Besides, 38% of trials were focused on using MSCs as a therapeutic agent to treat cancer directly. Most trials (38/40) are ongoing phase I/II, and 2 are entering phase III. 84% of trials used allogeneic MSCs compared with 13% using autologous sources and 3% using both. 25/40 trials showed participants received a single dose of MSCs, while the most times were 12 times in a pancreatic cancer treatment trial. Conclusion: MSC-based therapy for cancer in clinical trials should be applied to (1) minimize the side effects of oncological treatments and (2) directly affect the tumor via selectively delivering anti-cancer payloads to tumor cells. Allogeneic MSCs are a priority selected in clinical cancer therapy.Keywords: mesenchymal stem cells, MSC-based therapy, cancer condition, cancer treatment, clinical trials
Procedia PDF Downloads 9617889 Time and Energy Saving Kitchen Layout
Authors: Poonam Magu, Kumud Khanna, Premavathy Seetharaman
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The two important resources of any worker performing any type of work at any workplace are time and energy. These are important inputs of the worker and need to be utilised in the best possible manner. The kitchen is an important workplace where the homemaker performs many essential activities. Its layout should be so designed that optimum use of her resources can be achieved.Ideally, the shape of the kitchen, as determined by the physical space enclosed by the four walls, can be square, rectangular or irregular. But it is the shape of the arrangement of counter that one normally refers to while talking of the layout of the kitchen. The arrangement can be along a single wall, along two opposite walls, L shape, U shape or even island. A study was conducted in 50 kitchens belonging to middle income group families. These were DDA built kitchens located in North, South, East and West Delhi.The study was conducted in three phases. In the first phase, 510 non working homemakers were interviewed. The data related to personal characteristics of the homemakers was collected. Additional information was also collected regarding the kitchens-the size, shape , etc. The homemakers were also questioned about various aspects related to meal preparation-people performing the task, number of items cooked, areas used for meal preparation , etc. In the second phase, a suitable technique was designed for conducting time and motion study in the kitchen while the meal was being prepared. This technique was called Path Process Chart. The final phase was carried out in 50 kitchens. The criterion for selection was that all items for a meal should be cooked at the same time. All the meals were cooked by the homemakers in their own kitchens. The meal preparation was studied using the Path Process Chart technique. The data collected was analysed and conclusions drawn. It was found that of all the shapes, it was the kitchen with L shape arrangement in which, on an average a homemaker spent minimum time on meal preparation and also travelled the minimum distance. Thus, the average distance travelled in a L shaped layout was 131.1 mts as compared to 181.2 mts in an U shaped layout. Similarly, 48 minutes was the average time spent on meal preparation in L shaped layout as compared to 53 minutes in U shaped layout. Thus, the L shaped layout was more time and energy saving layout as compared to U shaped.Keywords: kitchen layout, meal preparation, path process chart technique, workplace
Procedia PDF Downloads 21217888 LGG Architecture for Brain Tumor Segmentation Using Convolutional Neural Network
Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan
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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG
Procedia PDF Downloads 18817887 Counseling Ethics in Turkish Counseling Programs
Authors: Umut Arslan, John Sommers Flanagan
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The purpose of this study was to investigate qualifications of ethics training in counselor education programs in Turkey. The survey data were collected from 251 Turkish counseling students to examine differences in ethical judgments between freshmen and seniors. Chi-square analysis was used to analyze the data from an ethical practice and belief survey. This survey was used to assess counselor candidates’ ethical judgments regarding Turkish counseling ethical codes and sources of ethics information. Statistically significant differences were found between university seniors and freshmen on items that are related to confidentiality, dual relationships, and professional relationships. Furthermore, patterns based on demographic information showed significant differences as a result of gender, economic status, and parents’ educational level. Participants gave the highest rating of information sources to Turkish counseling ethical codes.Keywords: ethics, training, Turkey, counselor, education
Procedia PDF Downloads 37517886 Machine Learning Data Architecture
Authors: Neerav Kumar, Naumaan Nayyar, Sharath Kashyap
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Most companies see an increase in the adoption of machine learning (ML) applications across internal and external-facing use cases. ML applications vend output either in batch or real-time patterns. A complete batch ML pipeline architecture comprises data sourcing, feature engineering, model training, model deployment, model output vending into a data store for downstream application. Due to unclear role expectations, we have observed that scientists specializing in building and optimizing models are investing significant efforts into building the other components of the architecture, which we do not believe is the best use of scientists’ bandwidth. We propose a system architecture created using AWS services that bring industry best practices to managing the workflow and simplifies the process of model deployment and end-to-end data integration for an ML application. This narrows down the scope of scientists’ work to model building and refinement while specialized data engineers take over the deployment, pipeline orchestration, data quality, data permission system, etc. The pipeline infrastructure is built and deployed as code (using terraform, cdk, cloudformation, etc.) which makes it easy to replicate and/or extend the architecture to other models that are used in an organization.Keywords: data pipeline, machine learning, AWS, architecture, batch machine learning
Procedia PDF Downloads 7017885 Data-Driven Dynamic Overbooking Model for Tour Operators
Authors: Kannapha Amaruchkul
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We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator
Procedia PDF Downloads 13817884 Neurocognitive Deficits Explaining Psychosocial Function and Relapse in Depression Remission: A Systematic Review
Authors: Nandini Mohan, Elayne Ahern
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Neurocognitive deficits, as well as psychosocial dysfunction, are typically observed in major depressive disorder (MDD). These deficits persist even after a significant reduction of symptoms and remission from MDD. These deficits have also been linked to greater relapse rates. The link between neurocognitive deficits, relapse, and psychosocial functioning in MDD, on the other hand, has received little attention. This review aimed to conduct an in-depth review of the literature on the association between neurocognitive deficits, relapse, and psychosocial functioning in MDD remission. We used search terms related to MDD, MDD remission, psychosocial functioning, neurocognitive impairments, and relapse to conduct a systematic review of English-language literature in PubMed, PsycArticles, PsycINFO, Medline, and Web of Science to identify relevant studies in the area from which 15 studies were identified for inclusion following an examination against inclusion/ exclusion criteria. Executive functioning, psychomotor speed, and memory were closely related to the psychosocial deficits in the phase of MDD remission. Similarly, Executive function, divided attention, and inhibition were closely related to the relapse in the phase of MDD remission. The limitations of the present review include limited and contradicting evidence that led to fewer studies being included. The implications of this review include an understanding of the difference between clinical and full-functional recovery. This evidence can be the basis for incorporating treatment measures that focus on neurocognitive and psychosocial deficits along with the affective symptoms of MDD.Keywords: depression, MDD, remission, relapse, neurocognitive functioning, psychosocial deficits
Procedia PDF Downloads 6017883 PM Air Quality of Windsor Regional Scale Transport’s Impact and Climate Change
Authors: Moustafa Osman Mohammed
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This paper is mapping air quality model to engineering the industrial system that ultimately utilized in extensive range of energy systems, distribution resources, and end-user technologies. The model is determining long-range transport patterns contribution as area source can either traced from 48 hrs backward trajectory model or remotely described from background measurements data in those days. The trajectory model will be run within stable conditions and quite constant parameters of the atmospheric pressure at the most time of the year. Air parcel trajectory is necessary for estimating the long-range transport of pollutants and other chemical species. It provides a better understanding of airflow patterns. Since a large amount of meteorological data and a great number of calculations are required to drive trajectory, it will be very useful to apply HYPSLIT model to locate areas and boundaries influence air quality at regional location of Windsor. 2–days backward trajectories model at high and low concentration measurements below and upward the benchmark which was areas influence air quality measurement levels. The benchmark level will be considered as 30 (μg/m3) as the moderate level for Ontario region. Thereby, air quality model is incorporating a midpoint concept between biotic and abiotic components to broaden the scope of quantification impact. The later outcomes’ theories of environmental obligation suggest either a recommendation or a decision of what is a legislative should be achieved in mitigation measures of air emission impact ultimately.Keywords: air quality, management systems, environmental impact assessment, industrial ecology, climate change
Procedia PDF Downloads 25217882 Modeling and Statistical Analysis of a Soap Production Mix in Bejoy Manufacturing Industry, Anambra State, Nigeria
Authors: Okolie Chukwulozie Paul, Iwenofu Chinwe Onyedika, Sinebe Jude Ebieladoh, M. C. Nwosu
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The research work is based on the statistical analysis of the processing data. The essence is to analyze the data statistically and to generate a design model for the production mix of soap manufacturing products in Bejoy manufacturing company Nkpologwu, Aguata Local Government Area, Anambra state, Nigeria. The statistical analysis shows the statistical analysis and the correlation of the data. T test, Partial correlation and bi-variate correlation were used to understand what the data portrays. The design model developed was used to model the data production yield and the correlation of the variables show that the R2 is 98.7%. However, the results confirm that the data is fit for further analysis and modeling. This was proved by the correlation and the R-squared.Keywords: General Linear Model, correlation, variables, pearson, significance, T-test, soap, production mix and statistic
Procedia PDF Downloads 45117881 Composition and Catalytic Behaviour of Biogenic Iron Containing Materials Obtained by Leptothrix Bacteria Cultivation in Different Growth Media
Authors: M. Shopska, D. Paneva, G. Kadinov, Z. Cherkezova-Zheleva, I. Mitov
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The iron containing materials are used as catalysts in different processes. The chemical methods of their synthesis use toxic and expensive chemicals; sophisticated devices; energy consumption processes that raise their cost. Besides, dangerous waste products are formed. At present time such syntheses are out of date and wasteless technologies are indispensable. The bioinspired technologies are consistent with the ecological requirements. Different microorganisms participate in the biomineralization of the iron and some phytochemicals are involved, too. The methods for biogenic production of iron containing materials are clean, simple, nontoxic, realized at ambient temperature and pressure, cheaper. The biogenic iron materials embrace different iron compounds. Due to their origin these substances are nanosized, amorphous or poorly crystalline, porous and have number of useful properties like SPM, high magnetism, low toxicity, biocompatibility, absorption of microwaves, high surface area/volume ratio, active sites on the surface with unusual coordination that distinguish them from the bulk materials. The biogenic iron materials are applied in the heterogeneous catalysis in different roles - precursor, active component, support, immobilizer. The application of biogenic iron oxide materials gives rise to increased catalytic activity in comparison with those of abiotic origin. In our study we investigated the catalytic behavior of biomasses obtained by cultivation of Leptothrix bacteria in three nutrition media – Adler, Fedorov, and Lieske. The biomass composition was studied by Moessbauer spectroscopy and transmission IRS. Catalytic experiments on CO oxidation were carried out using in situ DRIFTS. Our results showed that: i) the used biomasses contain α-FeOOH, γ-FeOOH, γ-Fe2O3 in different ratios; ii) the biomass formed in Adler medium contains γ-FeOOH as main phase. The CO conversion was about 50% as evaluated by decreased integrated band intensity in the gas mixture spectra during the reaction. The main phase in the spent sample is γ-Fe2O3; iii) the biomass formed in Lieske medium contains α-FeOOH. The CO conversion was about 20%. The main phase in the spent sample is α-Fe2O3; iv) the biomass formed in Fedorov medium contains γ-Fe2O3 as main phase. CO conversion in the test reaction was about 19%. The results showed that the catalytic activity up to 200°C resulted predominantly from α-FeOOH and γ-FeOOH. The catalytic activity at temperatures higher than 200°C was due to the formation of γ-Fe2O3. The oxyhydroxides, which are the principal compounds in the biomass, have low catalytic activity in the used reaction; the maghemite has relatively good catalytic activity; the hematite has activity commensurate with that of the oxyhydroxides. Moreover it can be affirmed that catalytic activity is inherent in maghemite, which is obtained by transformation of the biogenic lepidocrocite, i.e. it has biogenic precursor.Keywords: nanosized biogenic iron compounds, catalytic behavior in reaction of CO oxidation, in situ DRIFTS, Moessbauer spectroscopy
Procedia PDF Downloads 37517880 Machine Learning Analysis of Student Success in Introductory Calculus Based Physics I Course
Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu
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This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN
Procedia PDF Downloads 4617879 Model of Monitoring and Evaluation of Student’s Learning Achievement: Application of Value-Added Assessment
Authors: Jatuphum Ketchatturat
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Value-added assessment has been used for developing the model of monitoring and evaluation of student's learning achievement. The steps of model development consist of 1) study and analyisis of the school and the district report system of student achievement and progress, 2) collecting the data of student achievement to develop the value added indicator, 3) developing the system of value-added assessment by participatory action research approach, 4) putting the system of value-added assessment into the educational district of secondary school, 5) determining the quality of the developed system of value-added assessment. The components of the developed model consist of 1) the database of value-added assessment of student's learning achievement, 2) the process of monitoring and evaluation the student's learning achievement, and 3) the reporting system of value-added assessment of student's learning achievement.Keywords: learning achievement, monitoring and evaluation, value-added assessment
Procedia PDF Downloads 43117878 Performance Analysis of Heterogeneous Cellular Networks with Multiple Connectivity
Authors: Sungkyung Kim, Jee-Hyeon Na, Dong-Seung Kwon
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Future mobile networks following 5th generation will be characterized by one thousand times higher gains in capacity; connections for at least one hundred billion devices; user experience capable of extremely low latency and response times. To be close to the capacity requirements and higher reliability, advanced technologies have been studied, such as multiple connectivity, small cell enhancement, heterogeneous networking, and advanced interference and mobility management. This paper is focused on the multiple connectivity in heterogeneous cellular networks. We investigate the performance of coverage and user throughput in several deployment scenarios. Using the stochastic geometry approach, the SINR distributions and the coverage probabilities are derived in case of dual connection. Also, to compare the user throughput enhancement among the deployment scenarios, we calculate the spectral efficiency and discuss our results.Keywords: heterogeneous networks, multiple connectivity, small cell enhancement, stochastic geometry
Procedia PDF Downloads 33717877 Spectrophotometric Methods for Simultaneous Determination of Binary Mixture of Amlodipine Besylate and Atenolol Based on Dual Wavelength
Authors: Nesrine T. Lamie
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Four, accurate, precise, and sensitive spectrophotometric methods are developed for the simultaneous determination of a binary mixture containing amlodipine besylate (AM) and atenolol (AT) where AM is determined at its λmax 360 nm (0D), while atenolol can be determined by different methods. Method (A) is absorpotion factor (AFM). Method (B) is the new Ratio Difference method(RD) which measures the difference in amplitudes between 210 and 226 nm of ratio spectrum., Method (C) is novel constant center spectrophotometric method (CC) Method (D) is mean centering of the ratio spectra (MCR) at 284 nm. The calibration curve is linear over the concentration range of 10–80 and 4–40 μg/ml for AM and AT, respectively. These methods are tested by analyzing synthetic mixtures of the cited drugs and they are applied to their commercial pharmaceutical preparation. The validity of results was assessed by applying standard addition technique. The results obtained were found to agree statistically with those obtained by a reported method, showing no significant difference with respect to accuracy and precision.Keywords: amlodipine, atenolol, absorption factor, constant center, mean centering, ratio difference
Procedia PDF Downloads 30817876 Application of Random Forest Model in The Prediction of River Water Quality
Authors: Turuganti Venkateswarlu, Jagadeesh Anmala
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Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.Keywords: water quality, land use factors, random forest, fecal coliform
Procedia PDF Downloads 20117875 An Adaptive Hybrid Surrogate-Assisted Particle Swarm Optimization Algorithm for Expensive Structural Optimization
Authors: Xiongxiong You, Zhanwen Niu
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Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms
Procedia PDF Downloads 14417874 Spin-Flip and Magnetoelectric Coupling in Acentric and Non-Polar Pb₂MnO₄
Authors: K. D. Chandrasekhar, H. C. Wu, D. J. Hsieh, B. J. Song, J. -Y. Lin, J. L. Her, L. Z. Deng, M. Gooch, C. W. Chu, H. D. Yang
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Stress-mediated coupling of electrical and magnetic dipoles in a single phase multiferroic is rare. Pb₂MnO₄ belong to multi-piezo crystal class with the space group P⁻42₁Keywords: multiferroic, multipiezo, Pb₂MnO₄, spin-flip
Procedia PDF Downloads 24017873 Hybrid Inventory Model Optimization under Uncertainties: A Case Study in a Manufacturing Plant
Authors: E. Benga, T. Tengen, A. Alugongo
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Periodic and continuous inventory models are the two classical management tools used to handle inventories. These models have advantages and disadvantages. The implementation of both continuous (r,Q) inventory and periodic (R, S) inventory models in most manufacturing plants comes with higher cost. Such high inventory costs are due to the fact that most manufacturing plants are not flexible enough. Since demand and lead-time are two important variables of every inventory models, their effect on the flexibility of the manufacturing plant matter most. Unfortunately, these effects are not clearly understood by managers. The reason is that the decision parameters of the continuous (r, Q) inventory and periodic (R, S) inventory models are not designed to effectively deal with the issues of uncertainties such as poor manufacturing performances, delivery performance supplies performances. There is, therefore, a need to come up with a predictive and hybrid inventory model that can combine in some sense the feature of the aforementioned inventory models. A linear combination technique is used to hybridize both continuous (r, Q) inventory and periodic (R, S) inventory models. The behavior of such hybrid inventory model is described by a differential equation and then optimized. From the results obtained after simulation, the continuous (r, Q) inventory model is more effective than the periodic (R, S) inventory models in the short run, but this difference changes as time goes by. Because the hybrid inventory model is more cost effective than the continuous (r,Q) inventory and periodic (R, S) inventory models in long run, it should be implemented for strategic decisions.Keywords: periodic inventory, continuous inventory, hybrid inventory, optimization, manufacturing plant
Procedia PDF Downloads 38517872 A Fishery Regulation Model: Bargaining over Fishing Pressure
Authors: Duplan Yves Jamont Junior
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The Diamond-Mortensen-Pissarides model widely used in labor economics is tailored to fishery. By this way, a fishing function is defined to depict the fishing technology, and Bellman equations are established to describe the behaviors of fishermen and conservationists. On this basis, a negotiation takes place as a Nash-bargaining over the upper limit of the fishing pressure between both political representative groups of fishermen and conservationists. The existence and uniqueness conditions of the Nash-bargained fishing pressure are established. Given the biomass evolution equation, the dynamics of the model variables (fishing pressure, biomass, fish need) is studied.Keywords: conservation, fishery, fishing, Nash bargaining
Procedia PDF Downloads 26217871 Model for Remanufacture of Medical Equipment in Cross Border Collaboration
Authors: Kingsley Oturu, Winifred Ijomah, Wale Coker, Chibueze Achi
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With the impact of BREXIT and the need for cross-border collaboration, this international research investigated the use of a conceptual model for remanufacturing medical equipment (with a focus on anesthetic machines and baby incubators). Early findings of the research suggest that contextual factors need to be taken into consideration, as well as an emphasis on cleaning (e.g., sterilization) during the process of remanufacturing medical equipment. For example, copper tubings may be more important in the remanufacturing of anesthetic equipment in tropical climates than in cold climates.Keywords: medical equipment remanufacture, sustainability, circular business models, remanufacture process model
Procedia PDF Downloads 17617870 An Investigation about Rate Of Evaporation from the Water Surface and LNG Pool
Authors: Farokh Alipour, Ali Falavand, Neda Beit Saeid
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The calculation of the effect of accidental releases of flammable materials such as LNG requires the use of a suitable consequence model. This study is due to providing a planning advice for developments in the vicinity of LNG sites and other sites handling flammable materials. In this paper, an applicable algorithm that is able to model pool fires on water is presented and applied to estimate pool fire damage zone. This procedure can be used to model pool fires on land and could be helpful in consequence modeling and domino effect zone measurements of flammable materials which is needed in site selection and plant layout.Keywords: LNG, pool fire, spill, radiation
Procedia PDF Downloads 40917869 The Rapid Industrialization Model
Authors: Fredrick Etyang
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This paper presents a Rapid Industrialization Model (RIM) designed to support existing industrialization policies, strategies and industrial development plans at National, Regional and Constituent level in Africa. The model will reinforce efforts to attainment of inclusive and sustainable industrialization of Africa by state and non-state actors. The overall objective of this model is to serve as a framework for rapid industrialization in developing economies and the specific objectives range from supporting rapid industrialization development to promoting a structural change in the economy, a balanced regional industrial growth, achievement of local, regional and international competitiveness in areas of clear comparative advantage in industrial exports and ultimately, the RIM will serve as a step-by-step guideline for the industrialization of African Economies. This model is a product of a scientific research process underpinned by desk research through the review of African countries development plans, strategies, datasets, industrialization efforts and consultation with key informants. The rigorous research process unearthed multi-directional and renewed efforts towards industrialization of Africa premised on collective commitment of individual states, regional economic communities and the African union commission among other strategic stakeholders. It was further, established that the inputs into industrialization of Africa outshine the levels of industrial development on the continent. The RIM comes in handy to serve as step-by-step framework for African countries to follow in their industrial development efforts of transforming inputs into tangible outputs and outcomes in the short, intermediate and long-run. This model postulates three stages of industrialization and three phases toward rapid industrialization of African economies, the model is simple to understand, easily implementable and contextualizable with high return on investment for each unit invested into industrialization supported by the model. Therefore, effective implementation of the model will result into inclusive and sustainable rapid industrialization of Africa.Keywords: economic development, industrialization, economic efficiency, exports and imports
Procedia PDF Downloads 8917868 Self-Compacting White Concrete Mix Design Using the Particle Matrix Model
Authors: Samindi Samarakoon, Ørjan Sletbakk Vie, Remi Kleiven Fjelldal
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White concrete facade elements are widely used in construction industry. It is challenging to achieve the desired workability in casting of white concrete elements. Particle Matrix model was used for proportioning the self-compacting white concrete (SCWC) to control segregation and bleeding and to improve workability. The paper presents how to reach the target slump flow while controlling bleeding and segregation in SCWC. The amount of aggregates, binders and mixing water, as well as type and dosage of superplasticizer (SP) to be used are the major factors influencing the properties of SCWC. Slump flow and compressive strength tests were carried out to examine the performance of SCWC, and the results indicate that the particle matrix model could produce successfully SCWC controlling segregation and bleeding.Keywords: white concrete, particle matrix model, mix design, construction industry
Procedia PDF Downloads 271