Search results for: negative binomial model
19048 A Validated UPLC-MS/MS Assay Using Negative Ionization Mode for High-Throughput Determination of Pomalidomide in Rat Plasma
Authors: Muzaffar Iqbal, Essam Ezzeldin, Khalid A. Al-Rashood
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Pomalidomide is a second generation oral immunomodulatory agent, being used for the treatment of multiple myeloma in patients with disease refractory to lenalidomide and bortezomib. In this study, a sensitive UPLC-MS/MS assay was developed and validated for high-throughput determination of pomalidomide in rat plasma using celecoxib as an internal standard (IS). Liquid liquid extraction using dichloromethane as extracting agent was employed to extract pomalidomide and IS from 200 µL of plasma. Chromatographic separation was carried on Acquity BEHTM C18 column (50 × 2.1 mm, 1.7 µm) using an isocratic mobile phase of acetonitrile:10 mM ammonium acetate (80:20, v/v), at a flow rate of 0.250 mL/min. Both pomalidomide and IS were eluted at 0.66 ± 0.03 and 0.80 ± 0.03 min, respectively with a total run time of 1.5 min only. Detection was performed on a triple quadrupole tandem mass spectrometer using electrospray ionization in negative mode. The precursor to product ion transitions of m/z 272.01 → 160.89 for pomalidomide and m/z 380.08 → 316.01 for IS were used to quantify them respectively, using multiple reaction monitoring mode. The developed method was validated according to regulatory guideline for bioanalytical method validation. The linearity in plasma sample was achieved in the concentration range of 0.47–400 ng/mL (r2 ≥ 0.997). The intra and inter-day precision values were ≤ 11.1% (RSD, %) whereas accuracy values ranged from - 6.8 – 8.5% (RE, %). In addition, other validation results were within the acceptance criteria and the method was successfully applied in a pharmacokinetic study of pomalidomide in rats.Keywords: pomalidomide, pharmacokinetics, LC-MS/MS, celecoxib
Procedia PDF Downloads 39119047 On the Transition of Europe’s Power Sector: Economic Consequences of National Targets
Authors: Geoffrey J. Blanford, Christoph Weissbart
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The prospects for the European power sector indicate that it has to almost fully decarbonize in order to reach the economy-wide target of CO2-emission reduction. We apply the EU-REGEN model to explain the penetration of RES from an economic perspective, their spatial distribution, and the complementary role of conventional generation technologies. Furthermore, we identify economic consequences of national energy and climate targets. Our study shows that onshore wind power will be the most crucial generation technology for the future European power sector. Its geographic distribution is driven by resource quality. Gas power will be the major conventional generation technology for backing-up wind power. Moreover, a complete phase out of coal power proves to be not economically optimal. The paper demonstrates that existing national targets have a negative impact, especially on the German region with higher prices and lower revenues. The remaining regions profit are hardly affected. We encourage an EU-wide coordination on the expansion of wind power with harmonized policies. Yet, this requires profitable market structures for both, RES and conventional generation technologies.Keywords: European, policy evaluation, power sector investment, technology choices
Procedia PDF Downloads 28419046 Creeping Control Strategy for Direct Shift Gearbox Based on the Investigation of Temperature Variation of the Wet Clutch
Authors: Biao Ma, Jikai Liu, Man Chen, Jianpeng Wu, Liyong Wang, Changsong Zheng
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Proposing an appropriate control strategy is an effective and practical way to address the overheat problems of the wet multi-plate clutch in Direct Shift Gearbox under the long-time creeping condition. To do so, the temperature variation of the wet multi-plate clutch is investigated firstly by establishing a thermal resistance model for the gearbox cooling system. To calculate the generated heat flux and predict the clutch temperature precisely, the friction torque model is optimized by introducing an improved friction coefficient, which is related to the pressure, the relative speed and the temperature. After that, the heat transfer model and the reasonable friction torque model are employed by the vehicle powertrain model to construct a comprehensive co-simulation model for the Direct Shift Gearbox (DSG) vehicle. A creeping control strategy is then proposed and, to evaluate the vehicle performance, the safety temperature (250 ℃) is particularly adopted as an important metric. During the creeping process, the temperature of two clutches is always under the safety value (250 ℃), which demonstrates the effectiveness of the proposed control strategy in avoiding the thermal failures of clutches.Keywords: creeping control strategy, direct shift gearbox, temperature variation, wet clutch
Procedia PDF Downloads 13319045 Reliability Evaluation of a Payment Model in Mobile E-Commerce Using Colored Petri Net
Authors: Abdolghader Pourali, Mohammad V. Malakooti, Muhammad Hussein Yektaie
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A mobile payment system in mobile e-commerce generally have high security so that the user can trust it for doing business deals, sales, paying financial transactions, etc. in the mobile payment system. Since an architecture or payment model in e-commerce only shows the way of interaction and collaboration among users and mortgagers and does not present any evaluation of effectiveness and confidence about financial transactions to stakeholders. In this paper, we try to present a detailed assessment of the reliability of a mobile payment model in the mobile e-commerce using formal models and colored Petri nets. Finally, we demonstrate that the reliability of this system has high value (case study: a secure payment model in mobile commerce.Keywords: reliability, colored Petri net, assessment, payment models, m-commerce
Procedia PDF Downloads 53719044 A New Categorization of Image Quality Metrics Based on a Model of Human Quality Perception
Authors: Maria Grazia Albanesi, Riccardo Amadeo
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This study presents a new model of the human image quality assessment process: the aim is to highlight the foundations of the image quality metrics proposed in literature, by identifying the cognitive/physiological or mathematical principles of their development and the relation with the actual human quality assessment process. The model allows to create a novel categorization of objective and subjective image quality metrics. Our work includes an overview of the most used or effective objective metrics in literature, and, for each of them, we underline its main characteristics, with reference to the rationale of the proposed model and categorization. From the results of this operation, we underline a problem that affects all the presented metrics: the fact that many aspects of human biases are not taken in account at all. We then propose a possible methodology to address this issue.Keywords: eye-tracking, image quality assessment metric, MOS, quality of user experience, visual perception
Procedia PDF Downloads 41119043 Elevated of Interleukin-6 Serum Levels in Pregnant Women with Corona Virus Disease 2019
Authors: Dzatur Rizqi Fathienah Syarifuddin, Isharyah Sunarno, Eddy Hartono, Siti Maisuri T. Chalid
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Introduction: The potential impact of coronavirus disease 2019 (COVID-19) on the health of expectant mothers and fetuses has strained attention. Pregnant women are considered a vulnerable category to respiratory infections. Moreover, several inflammatory cytokines are 2-100 times more abundant in COVID-19 with cytokine storms than in normal individuals; interleukin 6 (IL-6) exhibits much higher elevations. Investigating potential relationships between IL-6 serum levels and the severity of COVID-19 symptoms in pregnant women is the aim of this study. Material and Methods: Sixty-two eligible pregnant women were divided into a positive COVID-19 group (n=31) and a negative COVID-19 group (n=31) in this cross-sectional study. The research subjects were selected using consecutive sampling. The IL-6 was measured from a vein blood specimen using ELISA methods. Results: The COVID-19 positive group had a higher median IL-6 serum level (45.35 (35.15- 153.99) vs. 38.86 ± 11.43 (15.02-59.52), p=0.03) than the negative group. On the other hand, the IL-6 serum level had comparable value according to the COVID-19 symptoms severity (88.35 ± 36.14 ng/mL vs. 51.09 ± 25.48 ng/mL vs. 56.02 ± 33.20 ng/mL in moderate symptoms, mild symptoms, and asymptomatic, respectively; p=0.152). Conclusion: Although the IL-6 serum levels are not related to COVID-19 symptoms severity, an elevated of this biomarker was found in pregnant women with affected diagnoses.Keywords: interleukin-6, pregnancy, COVID-19, several inflammatory
Procedia PDF Downloads 5819042 3D Hybrid Multiphysics Lattice Boltzmann Model for Studying the Flow Behavior of Emulsions in Structured Rectangular Microchannels
Authors: Luma Al-Tamimi, Hassan Farhat, Wessam Hasan
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A three-dimensional (3D) hybrid quasi-steady thermal lattice Boltzmann model is developed to couple the effects of surfactant, temperature, interfacial tension, and contact angle. This 3D model is an extended scheme of a previously introduced two-dimensional (2D) hybrid lattice Boltzmann model. The 3D model is used to study the combined multi-physics effects on emulsion systems flowing in rectangular microchannels with and without confinements, where the suspended phase is made of droplets, plugs, or a mixture of both. The simulation results show that emulsion systems with plugs as the suspended phase are more efficient than with droplets, whereas mixed systems that form large plugs through coalescence have even greater efficiency. The 3D contact angle model generates matching results to those of the 2D model, which were validated with experiments. Furthermore, the effects of various confinements on adhering single drop systems are investigated for delineating their influence on the power required for transporting the suspended phase through the channel. It is shown that the deeper the constriction is, the lower the system efficiency. Increasing the surfactant concentration or fluid temperature in a channel with confinement carries a substantial positive effect on oil droplet transportation.Keywords: lattice Boltzmann method, thermal, contact angle, surfactants, high viscosity ratio, porous media
Procedia PDF Downloads 17519041 Extension-Torsion-Inflation Coupling in Compressible Magnetoelastomeric Tubes with Helical Magnetic Anisotropy
Authors: Darius Diogo Barreto, Ajeet Kumar, Sushma Santapuri
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We present an axisymmetric variational formulation for coupled extension-torsion-inflation deformation in magnetoelastomeric thin tubes when both azimuthal and axial magnetic fields are applied. The tube's material is assumed to have a preferred magnetization direction which imparts helical magnetic anisotropy to the tube. We have also derived the expressions of the first derivative of free energy per unit tube's undeformed length with respect to various imposed strain parameters. On applying the thin tube limit, the two nonlinear ordinary differential equations to obtain the in-plane radial displacement and radial component of the Lagrangian magnetic field get converted into a set of three simple algebraic equations. This allows us to obtain simple analytical expressions in terms of the applied magnetic field, magnetization direction, and magnetoelastic constants, which tell us how these parameters can be tuned to generate positive/negative Poisson's effect in such tubes. We consider both torsionally constrained and torsionally relaxed stretching of the tube. The study can be useful in designing magnetoelastic tubular actuators.Keywords: nonlinear magnetoelasticity, extension-torsion coupling, negative Poisson's effect, helical anisotropy, thin tube
Procedia PDF Downloads 12019040 Generating Product Description with Generative Pre-Trained Transformer 2
Authors: Minh-Thuan Nguyen, Phuong-Thai Nguyen, Van-Vinh Nguyen, Quang-Minh Nguyen
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Research on automatically generating descriptions for e-commerce products is gaining increasing attention in recent years. However, the generated descriptions of their systems are often less informative and attractive because of lacking training datasets or the limitation of these approaches, which often use templates or statistical methods. In this paper, we explore a method to generate production descriptions by using the GPT-2 model. In addition, we apply text paraphrasing and task-adaptive pretraining techniques to improve the qualify of descriptions generated from the GPT-2 model. Experiment results show that our models outperform the baseline model through automatic evaluation and human evaluation. Especially, our methods achieve a promising result not only on the seen test set but also in the unseen test set.Keywords: GPT-2, product description, transformer, task-adaptive, language model, pretraining
Procedia PDF Downloads 19719039 Predicting Depth of Penetration in Abrasive Waterjet Cutting of Polycrystalline Ceramics
Authors: S. Srinivas, N. Ramesh Babu
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This paper presents a model to predict the depth of penetration in polycrystalline ceramic material cut by abrasive waterjet. The proposed model considered the interaction of cylindrical jet with target material in upper region and neglected the role of threshold velocity in lower region. The results predicted with the proposed model are validated with the experimental results obtained with Silicon Carbide (SiC) blocks.Keywords: abrasive waterjet cutting, analytical modeling, ceramics, micro-cutting and inter-grannular cracking
Procedia PDF Downloads 30519038 Academic Influence of Social Network Sites on the Collegiate Performance of Technical College Students
Authors: Jameson McFarlane, Thorne J. McFarlane, Leon Bernard
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Social network sites (SNS) is an emerging phenomenon that is here to stay. The popularity and the ubiquity of the SNS technology are undeniable. Because most SNS are free and easy to use people from all walks of life and from almost any age are attracted to that technology. College age students are by far the largest segment of the population using SNS. Since most SNS have been adapted for mobile devices, not only do you find students using this technology in their study, while working on labs or on projects, a substantial number of students have been found to use SNS even while listening to lectures. This study found that SNS use has a significant negative impact on the grade point average of college students particularly in the first semester. However, this negative impact is greatly diminished by the end of the third semester partly because the students have adjusted satisfactorily to the challenges of college or because they have learned how to adequately manage their time. It was established that the kinds of activities the students are engaged in during the SNS use are the leading factor affecting academic performance. Of those activities, using SNS during a lecture or while studying is the foremost contributing factor to lower academic performance. This is due to “cognitive” or “information” bottleneck, a condition in which the students find it very difficult to multitask or to switch between resources leading to inefficiency in information retention and thus, educational performance.Keywords: social network sites, social network analysis, regression coefficient, psychological engagement
Procedia PDF Downloads 17919037 Machine Learning for Feature Selection and Classification of Systemic Lupus Erythematosus
Authors: H. Zidoum, A. AlShareedah, S. Al Sawafi, A. Al-Ansari, B. Al Lawati
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Systemic lupus erythematosus (SLE) is an autoimmune disease with genetic and environmental components. SLE is characterized by a wide variability of clinical manifestations and a course frequently subject to unpredictable flares. Despite recent progress in classification tools, the early diagnosis of SLE is still an unmet need for many patients. This study proposes an interpretable disease classification model that combines the high and efficient predictive performance of CatBoost and the model-agnostic interpretation tools of Shapley Additive exPlanations (SHAP). The CatBoost model was trained on a local cohort of 219 Omani patients with SLE as well as other control diseases. Furthermore, the SHAP library was used to generate individual explanations of the model's decisions as well as rank clinical features by contribution. Overall, we achieved an AUC score of 0.945, F1-score of 0.92 and identified four clinical features (alopecia, renal disorders, cutaneous lupus, and hemolytic anemia) along with the patient's age that was shown to have the greatest contribution on the prediction.Keywords: feature selection, classification, systemic lupus erythematosus, model interpretation, SHAP, Catboost
Procedia PDF Downloads 8419036 Dynamic Comovements between Exchange Rates, Stock Prices and Oil Prices: Evidence from Developed and Emerging Latin American Markets
Authors: Nini Johana Marin Rodriguez
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This paper applies DCC, EWMA and OGARCH models to compare the dynamic correlations between exchange rates, oil prices, exchange rates and stock markets to examine the time-varying conditional correlations to the daily oil prices and index returns in relation to the US dollar/local currency for developed (Canada and Mexico) and emerging Latin American markets (Brazil, Chile, Colombia and Peru). Changes in correlation interactions are indicative of structural changes in market linkages with implications to contagion and interdependence. For each pair of stock price-exchange rate and oil price-US dollar/local currency, empirical evidence confirms of a strengthening negative correlation in the last decade. Methodologies suggest only two events have significatively impact in the countries analyzed: global financial crisis and Europe crisis, both events are associated with shifts of correlations to stronger negative level for most of the pairs analyzed. While, the first event has a shifting effect on mainly emerging members, the latter affects developed members. The identification of these relationships provides benefits in risk diversification and inflation targeting.Keywords: crude oil, dynamic conditional correlation, exchange rates, interdependence, stock prices
Procedia PDF Downloads 30719035 Stochastic Modeling for Parameters of Modified Car-Following Model in Area-Based Traffic Flow
Authors: N. C. Sarkar, A. Bhaskar, Z. Zheng
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The driving behavior in area-based (i.e., non-lane based) traffic is induced by the presence of other individuals in the choice space from the driver’s visual perception area. The driving behavior of a subject vehicle is constrained by the potential leaders and leaders are frequently changed over time. This paper is to determine a stochastic model for a parameter of modified intelligent driver model (MIDM) in area-based traffic (as in developing countries). The parametric and non-parametric distributions are presented to fit the parameters of MIDM. The goodness of fit for each parameter is measured in two different ways such as graphically and statistically. The quantile-quantile (Q-Q) plot is used for a graphical representation of a theoretical distribution to model a parameter and the Kolmogorov-Smirnov (K-S) test is used for a statistical measure of fitness for a parameter with a theoretical distribution. The distributions are performed on a set of estimated parameters of MIDM. The parameters are estimated on the real vehicle trajectory data from India. The fitness of each parameter with a stochastic model is well represented. The results support the applicability of the proposed modeling for parameters of MIDM in area-based traffic flow simulation.Keywords: area-based traffic, car-following model, micro-simulation, stochastic modeling
Procedia PDF Downloads 14719034 A Bathtub Curve from Nonparametric Model
Authors: Eduardo C. Guardia, Jose W. M. Lima, Afonso H. M. Santos
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This paper presents a nonparametric method to obtain the hazard rate “Bathtub curve” for power system components. The model is a mixture of the three known phases of a component life, the decreasing failure rate (DFR), the constant failure rate (CFR) and the increasing failure rate (IFR) represented by three parametric Weibull models. The parameters are obtained from a simultaneous fitting process of the model to the Kernel nonparametric hazard rate curve. From the Weibull parameters and failure rate curves the useful lifetime and the characteristic lifetime were defined. To demonstrate the model the historic time-to-failure of distribution transformers were used as an example. The resulted “Bathtub curve” shows the failure rate for the equipment lifetime which can be applied in economic and replacement decision models.Keywords: bathtub curve, failure analysis, lifetime estimation, parameter estimation, Weibull distribution
Procedia PDF Downloads 44619033 Document Analysis for Modelling iTV Advertising towards Impulse Purchase
Authors: Azizah Che Omar
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The study provides a systematic literature review which analyzed the literature for the purpose of looking for concepts, theories, approaches and guidelines in order to propose a conceptual design model of interactive television advertising toward impulse purchase (iTVAdIP). An extensive review of literature was purposely carried out to understand the concepts of interactive television (iTV). Therefore, some elements; iTV guidelines, advertising theories, persuasive approaches, and the impulse purchase elements were analyzed to reach the scope of this work. The extensive review was also a necessity to achieve the objective of this study, which was to determine the concept of iTVAdIP design model. Through systematic review analysis, this study discovered that all the previous models did not emphasize the conceptual design model of interactive television advertising. As a result, the finding showed that the concept of the proposed model should contain the iTV guidelines, advertising theory, persuasive approach and impulse purchase elements. In addition, a summary diagram for the development of the proposed model is depicted to provide clearer understanding towards the concepts of conceptual design model of iTVAdIP.Keywords: impulse purchase, interactive television advertising, human computer interaction, advertising theories
Procedia PDF Downloads 37019032 Experiencing the Shattered: Managing Countertransference Experiences with Anorexia Patients in Psychotherapy
Authors: M. Card
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Working with anorexia patients can be a challenging experience for mental and health care professionals. The reasons for not wanting to work with this patient population stems from the numerous concerns surrounding the patient’s health – physically and mentally. Many health care professionals reported having strong negative feelings, such as; anger, hopelessness and helplessness when working with anorexia patients. These feelings often impaired their judgement to treatment and affected how they related to the patient. This research focused on psychotherapists who preferred to work with anorexia patients; what countertransference feelings were evoked in them during sessions with patients and most importantly, how they managed the feelings. The research used interpretative phenomenological analysis (IPA) as the theoretical framework and data analysis method. Semi-structured interviews were used with ten experienced psychotherapists to obtain their countertransference experiences with anorexia patients and how they manage it. There were three main themes discovered; (1) the use of supervision, (2) their own personal therapy and finally (3) experience and evolution. The research unearthed that experienced psychotherapists also experienced strong countertransference feelings towards their patients; some positive and some negative. However, these feelings could actually be interpreted as co-transference with their anorexia patients. The psychotherapists were able to own their part in the evocative unconscious nature of a relational therapeutic space, where their personal issues may be entangled in their anorexia patient’s symptomatology.Keywords: anorexia nervosa, countertransference, co-transference, psychotherapy, relational psychotherapy
Procedia PDF Downloads 16519031 Prediction of Nonlinear Torsional Behavior of High Strength RC Beams
Authors: Woo-Young Jung, Minho Kwon
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Seismic design criteria based on performance of structures have recently been adopted by practicing engineers in response to destructive earthquakes. A simple but efficient structural-analysis tool capable of predicting both the strength and ductility is needed to analyze reinforced concrete (RC) structures under such event. A three-dimensional lattice model is developed in this study to analyze torsions in high-strength RC members. Optimization techniques for determining optimal variables in each lattice model are introduced. Pure torsion tests of RC members are performed to validate the proposed model. Correlation studies between the numerical and experimental results confirm that the proposed model is well capable of representing salient features of the experimental results.Keywords: torsion, non-linear analysis, three-dimensional lattice, high-strength concrete
Procedia PDF Downloads 35119030 A Predictive Model for Turbulence Evolution and Mixing Using Machine Learning
Authors: Yuhang Wang, Jorg Schluter, Sergiy Shelyag
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The high cost associated with high-resolution computational fluid dynamics (CFD) is one of the main challenges that inhibit the design, development, and optimisation of new combustion systems adapted for renewable fuels. In this study, we propose a physics-guided CNN-based model to predict turbulence evolution and mixing without requiring a traditional CFD solver. The model architecture is built upon U-Net and the inception module, while a physics-guided loss function is designed by introducing two additional physical constraints to allow for the conservation of both mass and pressure over the entire predicted flow fields. Then, the model is trained on the Large Eddy Simulation (LES) results of a natural turbulent mixing layer with two different Reynolds number cases (Re = 3000 and 30000). As a result, the model prediction shows an excellent agreement with the corresponding CFD solutions in terms of both spatial distributions and temporal evolution of turbulent mixing. Such promising model prediction performance opens up the possibilities of doing accurate high-resolution manifold-based combustion simulations at a low computational cost for accelerating the iterative design process of new combustion systems.Keywords: computational fluid dynamics, turbulence, machine learning, combustion modelling
Procedia PDF Downloads 9119029 Numerical Study of Off-Design Performance of a Highly Loaded Low Pressure Turbine Cascade
Authors: Shidvash Vakilipour, Mehdi Habibnia, Rouzbeh Riazi, Masoud Mohammadi, Mohammad H. Sabour
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The flow field passing through a highly loaded low pressure (LP) turbine cascade is numerically investigated at design and off-design conditions. The Field Operation And Manipulation (OpenFOAM) platform is used as the computational Fluid Dynamics (CFD) tool. Firstly, the influences of grid resolution on the results of k-ε, k-ω, and LES turbulence models are investigated and compared with those of experimental measurements. A numerical pressure under-shoot is appeared near the end of blade pressure surface which is sensitive to grid resolution and flow turbulence modeling. The LES model is able to resolve separation on a coarse and fine grid resolutions. Secondly, the off-design flow condition is modeled by negative and positive inflow incidence angles. The numerical experiments show that a separation bubble generated on blade pressure side is predicted by LES. The total pressure drop is also been calculated at incidence angle between -20◦ and +8◦. The minimum total pressure drop is obtained by k-ω and LES at the design point.Keywords: low pressure turbine, off-design performance, openFOAM, turbulence modeling, flow separation
Procedia PDF Downloads 36219028 Efficacy of Technology for Successful Learning Experience; Technology Supported Model for Distance Learning: Case Study of Botho University, Botswana
Authors: Ivy Rose Mathew
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The purpose of this study is to outline the efficacy of technology and the opportunities it can bring to implement a successful delivery model in Distance Learning. Distance Learning has proliferated over the past few years across the world. Some of the current challenges faced by current students of distance education include lack of motivation, a sense of isolation and a need for greater and improved communication. Hence the author proposes a creative technology supported model for distance learning exactly mirrored on the traditional face to face learning that can be adopted by distance learning providers. This model suggests the usage of a range of technologies and social networking facilities, with the aim of creating a more engaging and sustaining learning environment to help overcome the isolation often noted by distance learners. While discussing the possibilities, the author also highlights the complexity and practical challenges of implementing such a model. Design/methodology/approach: Theoretical issues from previous research related to successful models for distance learning providers will be considered. And also the analysis of a case study from one of the largest private tertiary institution in Botswana, Botho University will be included. This case study illustrates important aspects of the distance learning delivery model and provides insights on how curriculum development is planned, quality assurance is done, and learner support is assured for successful distance learning experience. Research limitations/implications: While some of the aspects of this study may not be applicable to other contexts, a number of new providers of distance learning can adapt the key principles of this delivery model.Keywords: distance learning, efficacy, learning experience, technology supported model
Procedia PDF Downloads 24719027 On the Use of Analytical Performance Models to Design a High-Performance Active Queue Management Scheme
Authors: Shahram Jamali, Samira Hamed
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One of the open issues in Random Early Detection (RED) algorithm is how to set its parameters to reach high performance for the dynamic conditions of the network. Although original RED uses fixed values for its parameters, this paper follows a model-based approach to upgrade performance of the RED algorithm. It models the routers queue behavior by using the Markov model and uses this model to predict future conditions of the queue. This prediction helps the proposed algorithm to make some tunings over RED's parameters and provide efficiency and better performance. Widespread packet level simulations confirm that the proposed algorithm, called Markov-RED, outperforms RED and FARED in terms of queue stability, bottleneck utilization and dropped packets count.Keywords: active queue management, RED, Markov model, random early detection algorithm
Procedia PDF Downloads 53919026 Singularization: A Technique for Protecting Neural Networks
Authors: Robert Poenaru, Mihail Pleşa
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In this work, a solution that addresses the protection of pre-trained neural networks is developed: Singularization. This method involves applying permutations to the weight matrices of a pre-trained model, introducing a form of structured noise that obscures the original model’s architecture. These permutations make it difficult for an attacker to reconstruct the original model, even if the permuted weights are obtained. Experimental benchmarks indicate that the application of singularization has a profound impact on model performance, often degrading it to the point where retraining from scratch becomes necessary to recover functionality, which is particularly effective for securing intellectual property in neural networks. Moreover, unlike other approaches, singularization is lightweight and computationally efficient, which makes it well suited for resource-constrained environments. Our experiments also demonstrate that this technique performs efficiently in various image classification tasks, highlighting its broad applicability and practicality in real-world scenarios.Keywords: machine learning, ANE, CNN, security
Procedia PDF Downloads 1419025 Domain Adaptive Dense Retrieval with Query Generation
Authors: Rui Yin, Haojie Wang, Xun Li
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Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.Keywords: dense retrieval, query generation, contrastive learning, unsupervised training
Procedia PDF Downloads 10419024 Prediction of the Tunnel Fire Flame Length by Hybrid Model of Neural Network and Genetic Algorithms
Authors: Behzad Niknam, Kourosh Shahriar, Hassan Madani
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This paper demonstrates the applicability of Hybrid Neural Networks that combine with back propagation networks (BPN) and Genetic Algorithms (GAs) for predicting the flame length of tunnel fire A hybrid neural network model has been developed to predict the flame length of tunnel fire based parameters such as Fire Heat Release rate, air velocity, tunnel width, height and cross section area. The network has been trained with experimental data obtained from experimental work. The hybrid neural network model learned the relationship for predicting the flame length in just 3000 training epochs. After successful learning, the model predicted the flame length.Keywords: tunnel fire, flame length, ANN, genetic algorithm
Procedia PDF Downloads 64319023 When Women Cheat: DNA Testing and Discourses of Femininity in the Closure DNA Show Zimbabwe
Authors: Shingirai Mandizadza
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‘The Closure’ DNA Show is a publicly hosted program on Youtube, the brainchild of a private citizen, Tinashe Mugabe, who started uploading episodes of the Show in 2020. The Show captures the paternity confirmation journeys of different families who approach the Show to share their stories and have the paternity results aired. Since the show started, a discourse on women’s sexuality has circulated in Zimbabwe, with cases of misattribution of paternity revealing social anxieties as well as a discursive space in which to think through a range of issues that include gender and sexuality. When paternity results are negative, they show misattribution of paternity by women, who, in most cases, are seen to have cheated. Men and women in Zimbabwe have traditionally been subjected to different ‘rules’ guiding sexual behavior. Gender roles in heterosexual intimate relationships frame different expectations for physical intimacy, including sexual and non-sexual touch, emotional intimacy, and commitment. This paper seeks to analyze discourses of femininity and sexuality engendered by negative paternity results. It analyses how sexuality and feminity are produced, reproduced and contested using the textual forms and communicative practices in the comments section of episodes of The Closure DNA Show. A Feminist Critical Discourse (FCDA) is used to review how language is used to frame the sexuality and femininity of the women on the show and Zimbabwean women in general.Keywords: gender, sexuality, paternity, discourse
Procedia PDF Downloads 1119022 The Foundation Binary-Signals Mechanics and Actual-Information Model of Universe
Authors: Elsadig Naseraddeen Ahmed Mohamed
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In contrast to the uncertainty and complementary principle, it will be shown in the present paper that the probability of the simultaneous occupation event of any definite values of coordinates by any definite values of momentum and energy at any definite instance of time can be described by a binary definite function equivalent to the difference between their numbers of occupation and evacuation epochs up to that time and also equivalent to the number of exchanges between those occupation and evacuation epochs up to that times modulus two, these binary definite quantities can be defined at all point in the time’s real-line so it form a binary signal represent a complete mechanical description of physical reality, the time of these exchanges represent the boundary of occupation and evacuation epochs from which we can calculate these binary signals using the fact that the time of universe events actually extends in the positive and negative of time’s real-line in one direction of extension when these number of exchanges increase, so there exists noninvertible transformation matrix can be defined as the matrix multiplication of invertible rotation matrix and noninvertible scaling matrix change the direction and magnitude of exchange event vector respectively, these noninvertible transformation will be called actual transformation in contrast to information transformations by which we can navigate the universe’s events transformed by actual transformations backward and forward in time’s real-line, so these information transformations will be derived as an elements of a group can be associated to their corresponded actual transformations. The actual and information model of the universe will be derived by assuming the existence of time instance zero before and at which there is no coordinate occupied by any definite values of momentum and energy, and then after that time, the universe begin its expanding in spacetime, this assumption makes the need for the existence of Laplace’s demon who at one moment can measure the positions and momentums of all constituent particle of the universe and then use the law of classical mechanics to predict all future and past of universe’s events, superfluous, we only need for the establishment of our analog to digital converters to sense the binary signals that determine the boundaries of occupation and evacuation epochs of the definite values of coordinates relative to its origin by the definite values of momentum and energy as present events of the universe from them we can predict approximately in high precision it's past and future events.Keywords: binary-signal mechanics, actual-information model of the universe, actual-transformation, information-transformation, uncertainty principle, Laplace's demon
Procedia PDF Downloads 17519021 The Effect of Radish (Raphanus Sativus L.) Leaves Ethanol Extract on Blood Glucose Levels in Streptozotocin-Nicotinamide-Induced Type-2 Diabetic Rats
Authors: Satria B. Mahathma, Asri Hendrawati
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Background: Diabetes mellitus (DM) is a metabolic disorder syndrome characterized by chronic hyperglycemia. The number of people with diabetes rose from 108 million in 1980 to 422 million in 2014. In general, almost 90% of the prevalence of DM is type 2 DM which marked by insulin resistance and decreased receptor sensitivity. Aside from conventional antidiabetic therapy, the utilization of medicinal plants as alternative medicine has beneficial effects in diabetic patients. Flavonoid contents in radish leaves such as quercetin, pelargonidin, and kaempferol are thought to have antidiabetic activity on decreasing blood glucose levels by tricyclic nucleotide modulation of pancreatic beta cells and ameliorating insulin resistance. This study aimed to determine the effect of variant concentration of radish leaves ethanol extract on blood glucose levels in diabetic rats. Method: This study used pretest-posttest control group design by using 16 male Wistar rats which were induced type-2 diabetic by streptozotocin 60 mg/kg BW-nicotinamide 120 mg/kg BW intraperitoneally. Rats who had developed type-2 DM later divided randomly into 4 groups; negative control received placebo, positive control received glibenclamide 5 mg/kg BW/day, rats intervention I and intervention II received 100% and 50% of radish leaves ethanol extract, respectively. Treatments were administered orally for four weeks. The blood glucose levels were measured using the Enzymatic Colorimetric Test “GOD-PAP”. Data were analyzed by the dependent t-test for pretest-posttest intervention difference and one-way ANOVA followed by post hoc test to determine the significant difference of each treatment to obtain the significant data. Result: The result revealed that intervention group had lower blood glucose levels mean than control group which the lowest was intervention II group (negative control: 540,9 ± 191,7 mg/dl, positive control: 494, 97 ± 64,91 mg/dl, intervention I: 301,92 ± 165,70 mg/dl, and intervention II group: 276,1 ± 139,02 mg/dl. Intervention II group had the highest antidiabetic activity, followed by the intervention I group with the amount of decrease in blood glucose levels were -151,85 ± 77,43 mg/dl and -11,08 ± 186,62 mg/dl, however negative and positive control group didn’t have antidiabetic activity. The dependent t-test result showed there is a significant difference in decreasing blood glucose levels in the intervention II pretest-posttest intervention (p=0,03) while the other group didn’t. Data analyzed by one-way ANOVA also revealed the intervention II group significantly declined blood glucose levels compared to the negative and positive control group (p = 0,033 and p=0,032, respectively). Conclusion: There is a significant effect of radish leaves ethanol extract on blood glucose levels in streptozotocin-nicotinamide-induced diabetic rats with the optimal therapeutic effect at a concentration of 50%.Keywords: blood glucose levels, medicinal plant, radish leaves, type-2 diabetes mellitus
Procedia PDF Downloads 13519020 Biomechanical Performance of the Synovial Capsule of the Glenohumeral Joint with a BANKART Lesion through Finite Element Analysis
Authors: Duvert A. Puentes T., Javier A. Maldonado E., Ivan Quintero., Diego F. Villegas
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Mechanical Computation is a great tool to study the performance of complex models. An example of it is the study of the human body structure. This paper took advantage of different types of software to make a 3D model of the glenohumeral joint and apply a finite element analysis. The main objective was to study the change in the biomechanical properties of the joint when it presents an injury. Specifically, a BANKART lesion, which consists in the detachment of the anteroinferior labrum from the glenoid. Stress and strain distribution of the soft tissues were the focus of this study. First, a 3D model was made of a joint without any pathology, as a control sample, using segmentation software for the bones with the support of medical imagery and a cadaveric model to represent the soft tissue. The joint was built to simulate a compression and external rotation test using CAD to prepare the model in the adequate position. When the healthy model was finished, it was submitted to a finite element analysis and the results were validated with experimental model data. With the validated model, it was sensitized to obtain the best mesh measurement. Finally, the geometry of the 3D model was changed to imitate a BANKART lesion. Then, the contact zone of the glenoid with the labrum was slightly separated simulating a tissue detachment. With this new geometry, the finite element analysis was applied again, and the results were compared with the control sample created initially. With the data gathered, this study can be used to improve understanding of the labrum tears. Nevertheless, it is important to remember that the computational analysis are approximations and the initial data was taken from an in vitro assay.Keywords: biomechanics, computational model, finite elements, glenohumeral joint, bankart lesion, labrum
Procedia PDF Downloads 16119019 A Model for Reverse-Mentoring in Education
Authors: Sabine A. Zauchner-Studnicka
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As the term indicates, reverse-mentoring flips the classical roles of mentoring: In school, students take over the role of mentors for adults, i.e. teachers or parents. Originally reverse-mentoring stems from US enterprises, which implemented this innovative method in order to benefit from the resources of skilled younger employees for the enhancement of IT competences of senior colleagues. However, reverse-mentoring in schools worldwide is rare. Based on empirical studies and theoretical approaches, in this article an implementation model for reverse-mentoring is developed in order to bring the significant potential reverse-mentoring has for education into practice.Keywords: reverse-mentoring, innovation in education, implementation model, school education
Procedia PDF Downloads 248