Search results for: bilinear moving average model

Authors: Gyo Woo Lee, Man Young Kim

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A mathematical heat transfer model for the prediction of transient heating of the slab in a direct-fired walking beam type reheating furnace has been developed by considering the nongray thermal radiation with given furnace environments. The furnace is modeled as radiating nongray medium with carbon dioxide and water with five-zoned gas temperature and the furnace wall is considered as a constant temperature lower than furnace gas one. The slabs are moving with constant velocity depending on the residence time through the non-firing, charging, preheating, heating, and final soaking zones. Radiative heat flux obtained by considering the radiative heat exchange inside the furnace as well as convective one from the surrounding hot gases are introduced as boundary condition of the transient heat conduction within the slab. After validating thermal radiation model adopted in this work, thermal fields in both model and real reheating furnace are investigated in terms of radiative heat flux in the furnace and temperature inside the slab. The results show that the slab in the furnace can be more heated with higher slab emissivity and residence time.

Keywords: reheating furnace, steel slab, radiative heat transfer, WSGGM, emissivity, residence time

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Authors: Naragain Phumchusri, Kittitach Pongpairoj

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Overbooking is a very useful revenue management technique that could help reduce costs caused by either undersales or oversales. In this paper, we propose an overbooking model for two types of cars that can minimize the total cost for car rental service. With two types of cars, there is an upgrade possibility for lower type to upper type. This makes the model more complex than one type of cars scenario. We have found that convexity can be proved in this case. Sensitivity analysis of the parameters is conducted to observe the effects of relevant parameters on the optimal solution. Model simplification is proposed using multiple linear regression analysis, which can help estimate the optimal overbooking level using appropriate independent variables. The results show that the overbooking level from multiple linear regression model is relatively close to the optimal solution (with the adjusted R-squared value of at least 72.8%). To evaluate the performance of the proposed model, the total cost was compared with the case where the decision maker uses a naïve method for the overbooking level. It was found that the total cost from optimal solution is only 0.5 to 1 percent (on average) lower than the cost from regression model, while it is approximately 67% lower than the cost obtained by the naïve method. It indicates that our proposed simplification method using regression analysis can effectively perform in estimating the overbooking level.

Keywords: overbooking, car rental industry, revenue management, stochastic model

Procedia PDF Downloads 158

Authors: Suegnet Smit

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Prior to 1994, special education in South Africa was marginalized and fragmented. Moving away from a Medical model approach to special education, the Government, after 1994, promoted an Inclusive approach, as a means to transform education in general, and special education in particular. This transformation, however, is moving at too a slow pace for learners with barriers to learning and development to benefit fully from their education. The goal of the Department of Basic Education is to minimize, remove, and prevent barriers to learning and development in the educational setting, by attending to the unique needs of the individual learner. However, the implementation of Inclusive education is problematic, and general education remains poor. This paper highlights the historical development of special education in South Africa, underpinned by a bio-ecological perspective. Problematic areas within the systemic levels of the education system are highlighted in order to indicate how the interactive processes within the systemic levels affect special needs learners on the personal dimension of the bio-ecological approach. As part of the methodology, thorough document analysis was conducted on information collected from a large body of research literature, which included academic articles, reports, policies, and policy reviews. Through a qualitative analysis, data were grouped and categorized according to the bio-ecological model systems, which revealed various successes and challenges within the education system. The challenges inhibit change, growth, and development for the child, who experience barriers to learning. From these findings, it is established that special education in South Africa has been, and still is, on a bumpy road. Sadly, the transformation process of change, envisaged by implementing Inclusive education, is still yet a dream, not fully realized. Special education seems to be stuck at what is, and the education system has not moved forward significantly enough to reach what special education should and could be. The gap that exists between a vision of Inclusive quality education for all, and the current reality, is still too wide. Problems encountered in all the education system levels, causes a funnel-effect downward to learners with special educational needs, with negative effects for the development of these learners.

Keywords: bio-ecological perspective, education systems, inclusive education, special education

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Authors: Yasser El-Henawy, M. Abd El-Kader, Gamal H. Moustafa

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A theoretical study of a humidification dehumidification solar desalination unit has been carried out to increase understanding the effect of weather conditions on the unit productivity. A humidification-dehumidification (HD) solar desalination unit has been designed to provide fresh water for population in remote arid areas. It consists of solar water collector and air collector; to provide the hot water and air to the desalination chamber. The desalination chamber is divided into humidification and dehumidification towers. The circulation of air between the two towers is maintained by the forced convection. A mathematical model has been formulated, in which the thermodynamic relations were used to study the flow, heat and mass transfer inside the humidifier and dehumidifier. The present technique is performed in order to increase the unit performance. Heat and mass balance has been done and a set of governing equations has been solved using the finite difference technique. The unit productivity has been calculated along the working day during the summer and winter sessions and has compared with the available experimental results. The average accumulative productivity of the system in winter has been ranged between 2.5 to 4 kg/m2.day, while the average summer productivity has been found between 8 to 12 kg/m2 day.

Keywords: solar desalination, solar collector, humidification and dehumidification, simulation, finite difference, water productivity

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

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Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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Authors: Sajid Hussain

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The complex domain approach for image segmentation based on active contour has been designed, which deforms step by step to partition an image into numerous expedient regions. A novel region-based trigonometric complex pressure force function is proposed, which propagates around the region of interest using image forces. The signed trigonometric force function controls the propagation of the active contour and the active contour stops on the exact edges of the object accurately. The proposed model makes the level set function binary and uses Gaussian smoothing kernel to adjust and escape the re-initialization procedure. The working principle of the proposed model is as follows: The real image data is transformed into complex data by iota (i) times of image data and the average iota (i) times of horizontal and vertical components of the gradient of image data is inserted in the proposed model to catch complex gradient of the image data. A simple finite difference mathematical technique has been used to implement the proposed model. The efficiency and robustness of the proposed model have been verified and compared with other state-of-the-art models.

Keywords: image segmentation, active contour, level set, Mumford and Shah model

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Authors: Ali Mustafa Elshawesh, Mohamed Abdulali

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The paper presents an approach to dimension circuit switched networks and find the relationship between the parameters of the circuit switched networks on the condition of specific probability of call blocking. Our work is creating a Simulation code based on Erlang (B) formula to draw graphs which show two curves for each graph; one of simulation and the other of calculated. These curves represent the relationships between average number of calls and average call duration with the probability of call blocking. This simulation code facilitates to select the appropriate parameters for circuit switched networks.

Keywords: Erlang B formula, call blocking, telephone system dimension, Markov model, link capacity

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Authors: Arpit Panwar, Arvind Deshpande

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The study of external vehicle aerodynamics using Spalart-Allmaras turbulence model with adjoint method was conducted. The accessibility and ease of working with the Fluent module of ANSYS and OpenFOAM were considered. The objective of the study was to understand and analyze the possibility of bringing high-level aerodynamic simulation to the average consumer vehicle. A form-factor of BMW M6 vehicle was designed in Solidworks, which was analyzed in OpenFOAM and Fluent. The turbulence model being a single equation provides much faster convergence rate when clubbed with the adjoint method. Fluent being commercial software still does not allow us to solve Spalart-Allmaras turbulence model using the adjoint method. Hence, the turbulence model was solved using the SIMPLE method in Fluent. OpenFOAM being an open source provide flexibility in simulation but is not user-friendly. It supports solving the defined turbulence model with the adjoint method. The result generated from the simulation gives us acceptable values of drag, when validated with the result of percentage error in drag values for a notch-back vehicle model on an extensive simulation produced at 6th ANSA and μETA conference, Greece. The success of this approach will allow us to bring more aerodynamic vehicle body design to all segments of the automobile and not limiting it to just the high-end sports cars.

Keywords: Spalart-Allmaras turbulence model, OpenFOAM, adjoint method, SIMPLE method, vehicle aerodynamic design

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Authors: Saeid Haghjoo, Ebrahim Reyhani, Fahimeh Kolahdouz

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The present study aimed to evaluate the understanding of the students in Tehran universities (Iran) about the numerical representation of the average rate of change based on the Structure of Observed Learning Outcomes (SOLO). In the present descriptive-survey research, the statistical population included undergraduate students (basic sciences and engineering) in the universities of Tehran. The samples were 604 students selected by random multi-stage clustering. The measurement tool was a task whose face and content validity was confirmed by math and mathematics education professors. Using Cronbach's Alpha criterion, the reliability coefficient of the task was obtained 0.95, which verified its reliability. The collected data were analyzed by descriptive statistics and inferential statistics (chi-squared and independent t-tests) under SPSS-24 software. According to the SOLO model in the prestructural, unistructural, and multistructural levels, basic science students had a higher percentage of understanding than that of engineering students, although the outcome was inverse at the relational level. However, there was no significant difference in the average understanding of both groups. The results indicated that students failed to have a proper understanding of the numerical representation of the average rate of change, in addition to missconceptions when using physics formulas in solving the problem. In addition, multiple solutions were derived along with their dominant methods during the qualitative analysis. The current research proposed to focus on the context problems with approximate calculations and numerical representation, using software and connection common relations between math and physics in the teaching process of teachers and professors.

Keywords: average rate of change, context problems, derivative, numerical representation, SOLO taxonomy

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Authors: Bara Yousef

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The development of independency and functional participation is an important therapeutic goal for many children with cerebral palsy,They was many therapeutic approach have been used for treatment those children like neurodevelopment treatment, balance training strengthening and stretching exercise. More recently, therapy for children with cerebral palsy has focused on achieving functional goals using task-oriented interventions and summer camping model, which focus on activities that relevant and meaningful to the child, to learn more efficient and effective motor skills. We explore the effectiveness of using functional rehabilitation comparing with regular rehabilitation among 40 Saudi children with cerebral palsy in pediatric unit at Sultan Bin Abdul Aziz Humanitarian City-Ksa ,where 20 children randomly assign in control group who received rehabilitation based on regular therapy approach and other 20 children assign on experiment group who received rehabilitation based on functional therapy approach with an average of 45min OT treatment and 45 min PT treatment- daily within a period of 6 week. Our finding reported that children in experiment group has improved in gross motor function with an average from 49.4 to 57.6 based on GMFM 66 as primary outcome measure and improved in WeeFIM with an average from 52 to 62 while children in control group has improved with an average from 48.4 to 53.7 in GMFM and from 53 to and 58 in WeeFIM. Consequently, there has been growing interest in determining the effects of functional training programs as promising approach for these children.

Keywords: Cerebral Palsy (CP), gross motor function measure (GMFM66), pediatric Functional Independent Measure (WeeFIM), rehabilitation, disability

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Authors: R. Saini, R. Lal

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The effect of non-homogeneity on the free transverse vibration of thin rectangular plates of bilinearly varying thickness has been analyzed using generalized differential quadrature (GDQ) method. The non-homogeneity of the plate material is assumed to arise due to linear variations in Young’s modulus and density of the plate material with the in-plane coordinates x and y. Numerical results have been computed for fully clamped and fully simply supported boundary conditions. The solution procedure by means of GDQ method has been implemented in a MATLAB code. The effect of various plate parameters has been investigated for the first three modes of vibration. A comparison of results with those available in literature has been presented.

Keywords: rectangular, non-homogeneous, bilinear thickness, generalized differential quadrature (GDQ)

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Authors: Murat İskender Aktaş, Selma Söyük

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The aim of this work is to specify the levels of organizational cynicism health workers. Organizational cynicism concept is evaluated in three sub-branches and these are cognitive, affective, and behavioral. The main objective of the work is to answer the questions about the relationship of demographic characteristics like sub-branches of cynicism and age, marital status, education level, total working hours, occupational groups and income levels. As works in our country are analyzed, there have been studies about cynicism in health and other sectors. However, there were no master’s thesis or organizational cynicism research found about the public health professionals. This is why the aim was chosen as to specify the levels of organizational cynicism of public health professionals. The average of the answers of the health workers to the questions about cynicism levels are 2.86. As organizational cynicism is evaluated according to the sub-branches, cognitive subscale average score is 3.21 affective subscale average score is 2.68 and behavioral subscale average score is counted as 2.67. As the results are analyzed, it is seen that the behavioral subscale has the highest average. This shows that the workers are often criticizing the internal complaints and organizational information with their friends out of the organization.

Keywords: cynicism, organizational cynicism, health care workers

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Authors: Nieves M. C. Talavera-Prieto, Abel G. M. Ferreira, António T. G. Portugal, Rui J. Moreira, Jaime B. Santos

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The knowledge of biodiesel density over large ranges of temperature and pressure is important for predicting the behavior of fuel injection and combustion systems in diesel engines, and for the optimization of such systems. In this study, cottonseed oil was transesterified into biodiesel and its density was measured at temperatures between 288 K and 358 K and pressures between 0.1 MPa and 30 MPa, with expanded uncertainty estimated as ±1.6 kg.m^-3. Experimental pressure-volume-temperature (pVT) cottonseed data was used along with literature data relative to other 18 biodiesels, in order to build a database used to test the correlation of density with temperarure and pressure using the Goharshadi–Morsali–Abbaspour equation of state (GMA EoS). To our knowledge, this is the first that density measurements are presented for cottonseed biodiesel under such high pressures, and the GMA EoS used to model biodiesel density. The new tested EoS allowed correlations within 0.2 kg•m-3 corresponding to average relative deviations within 0.02%. The built database was used to develop and test a new full predictive model derived from the observed linear relation between density and degree of unsaturation (DU), which depended from biodiesel FAMEs profile. The average density deviation of this method was only about 3 kg.m-3 within the temperature and pressure limits of application. These results represent appreciable improvements in the context of density prediction at high pressure when compared with other equations of state.

Keywords: biodiesel density, correlation, equation of state, prediction

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Authors: Laras Tursilowati, Bambang Siswanto

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Urban climate change has short- and long-term implications for decision-makers in urban development. The problem for this important metropolitan regional of population and economic value is that there is very little usable information on climate change. Research about urban climate change has been carried out in Bali Indonesia by using Conformal Cubic Atmospheric Model (CCAM) that runs with Representative Concentration Pathway (RCP)4.5. The history data means average data from 1975 to 2005, climate projections with RCP4.5 scenario means average data from 2006 to 2099, and anomaly (urban climate change) is RCP4.5 minus history. The results are the history of temperature between 22.5-27.5 OC, and RCP4.5 between 25.5-29.5 OC. The temperature anomalies can be seen in most of northern Bali that increased by about 1.6 to 2.9 OC. There is a reduced humidity tendency (drier) in most parts of Bali, especially the northern part of Bali, while a small portion in the south increase moisture (wetter). The comfort index of Bali region in history is still relatively comfortable (20-26 OC), but on the condition RCP4.5 there is no comfortable area with index more than 26 OC (hot and dry). This research is expected to be useful to help the government make good urban planning.

Keywords: CCAM, comfort index, IPCC AR5, temperature, urban climate change

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Authors: Benedictus Asriparusa

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Solar radiation is a green renewable energy which has the potential to answer the needs of energy problems on the period. Knowing how to estimate the strength of the solar radiation force may be one solution of sustainable energy development in an integrated manner. Unfortunately, a fairly extensive area of Indonesia is still very low availability of solar radiation data. Therefore, we need a method to estimate the exact strength of solar radiation. In this study, author used a model Reference Evaluation of Solar Transmittance, 2 Bands (REST 2). Validation of REST 2 model has been performed in Spain, India, Colorado, Saudi Arabia, and several other areas. But it is not widely used in Indonesia. Indonesian region study area is represented by the area of Semarang, Central Java. Solar radiation values estimated using REST 2 model was then verified by field data and gives average RMSE value of 6.53%. Based on the value, it can be concluded that the model REST 2 can be used to estimate the value of solar radiation in clear sky conditions in parts of Indonesia.

Keywords: estimation, solar radiation power, REST 2, solar transmittance

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Authors: Entisar A. Elgmati

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Recurrent infant diarrhea is studied using daily data collected in Salvador, Brazil over one year and three months. A logistic regression model is fitted instead of Aalen's additive model using the same covariates that were used in the analysis with the additive model. The model gives reasonably similar results to that using additive regression model. In addition, the problem with the estimated conditional probabilities not being constrained between zero and one in additive model is solved here. Also martingale residuals that have been used to judge the goodness of fit for the additive model are shown to be useful for judging the goodness of fit of the logistic model.

Keywords: additive model, cumulative probabilities, infant diarrhoea, recurrent event

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

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Safe performance and efficient energy consumption are essential factors for designing a control system. This paper presents a reinforcement learning (RL) model that can be applied to control applications to improve safety and reduce energy consumption. As hardware constraints and environmental disturbances are imprecise and unpredictable, conventional control methods may not always be effective in optimizing control designs. However, RL has demonstrated its value in several artificial intelligence (AI) applications, especially in the field of control systems. The proposed model intelligently monitors a system's success by observing the rewards from the environment, with positive rewards counting as a success when the controlled reference is within the desired operating zone. Thus, the model can determine whether the system is safe to continue operating based on the designer/user specifications, which can be adjusted as needed. Additionally, the controller keeps track of energy consumption to improve energy efficiency by enabling the idle mode when the controlled reference is within the desired operating zone, thus reducing the system energy consumption during the controlling operation. Water temperature control for a hydroponic system is taken as a case study for the RL model, adjusting the variance of disturbances to show the model’s robustness and efficiency. On average, the model showed safety improvement by up to 15% and energy efficiency improvements by 35%- 40% compared to a traditional RL model.

Keywords: control system, hydroponics, machine learning, reinforcement learning

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Authors: Leon Pan

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The first programming course within post-secondary education has long been recognized as a challenging endeavor for both educators and students alike. Historically, these courses have exhibited high failure rates and a notable number of dropouts. Instructors often lament students' lack of effort in their coursework, and students often express frustration that the teaching methods employed are not effective. Drawing inspiration from the successful principles of Extreme Programming, this study introduces an approach—the Extremes-based teaching model — aimed at enhancing the teaching of introductory programming courses. To empirically determine the effectiveness of the model, a comparison was made between a section taught using the extreme-based model and another utilizing traditional teaching methods. Notably, the extreme-based teaching class required students to work collaboratively on projects while also demanding continuous assessment and performance enhancement within groups. This paper details the application of the extreme-based model within the post-secondary online classroom context and presents the compelling results that emphasize its effectiveness in advancing the teaching and learning experiences. The extreme-based model led to a significant increase of 13.46 points in the weighted total average and a commendable 10% reduction in the failure rate.

Keywords: extreme-based teaching model, innovative pedagogical methods, project-based learning, team-based learning

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Authors: Paul Kenneth D. Luzon, Maria Antonia N. Tanchuling

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The Quezon City Controlled Dumping facility also known as Payatas produces leachate which can contaminate soil and water environment in the area. The goal of this study is to quantify the leachate produced by the QCCDF using the Hydrologic Evaluation of Landfill Performance (HELP) model. Results could be used as input for groundwater contaminant transport studies. The HELP model is based on a simple water budget and is an essential “model requirement” used by the US Environmental Protection Agency (EPA). Annual waste profile of the QCCDF was calculated. Based on topographical maps and estimation of settlement due to overburden pressure and degradation, a total of 10M m^3 of waste is contained in the landfill. The input necessary for the HELP model are weather data, soil properties, and landfill design. Results showed that from 1988 to 2011, an average of 50% of the total precipitation percolates through the bottom layer. Validation of the results is still needed due to the assumptions made in the study. The decrease in porosity of the top soil cover showed the best mitigation for minimizing percolation rate. This study concludes that there is a need for better leachate management system in the QCCDF.

Keywords: help model, landfill, payatas trash slide, quezon city controlled dumping facility

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Authors: Islem Kedidi, Rihab Bedoui Bensalem, Faysal Manssouri

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In traditional models of insurance data, the number and size of claims are assumed to be independent. Relaxing the independence assumption, this article explores the Vine copula to model dependence structure between multivariate frequency and average severity of insurance claim. To illustrate this approach, we use the Wisconsin local government property insurance fund which offers several insurance protections for motor vehicles, property and contractor’s equipment claims. Results show that the C-vine copula can better characterize the multivariate dependence structure between frequency and severity. Furthermore, we find significant dependencies especially between frequency and average severity among different coverage types.

Keywords: dependency modeling, government insurance, insurance claims, vine copula

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Authors: Antonello Troncone, Luigi Pugliese, Andrea Parise, Enrico Conte

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The present study deals with the landslides periodically reactivated by groundwater level fluctuations owing to rainfall. The main type of movement which generally characterizes these landslides consists in sliding with quite small-displacement rates. Another peculiar characteristic of these landslides is that soil deformations are essentially concentrated within a thin shear band located below the body of the landslide, which, consequently, undergoes an approximately rigid sliding. In this context, a simple method is proposed in the present study to forecast the movements of this type of landslides owing to rainfall. To this purpose, the landslide body is schematized by means of a two-block model. Some analytical solutions are derived to relate rainfall measurements with groundwater level oscillations and these latter, in turn, to landslide mobility. The proposed method is attractive for engineering applications since it requires few parameters as input data, many of which can be obtained from conventional geotechnical tests. To demonstrate the predictive capability of the proposed method, the application to a well-documented landslide periodically reactivated by rainfall is shown.

Keywords: rainfall, water level fluctuations, landslide mobility, two-block model

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Authors: Andrey A. Lipovskii, Alexey V. Redkov, Vyacheslav V. Rusan, Dmitry K. Tagantsev, Valentina V. Zhurikhina

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The presented research is related to the development of recently proposed technique of the formation of composite materials, like optical glass-ceramics, with predetermined structure and properties of the crystalline component. The technique is based on the control of the size and concentration of the crystalline grains using the phenomenon of glass-ceramics decrystallization (vitrification) induced by ion-exchange. This phenomenon was discovered and explained in the beginning of the 2000s, while related theoretical description was given in 2016 only. In general, the developed theory enables one to model the process and optimize the conditions of ion-exchange processing of glass-ceramics, which provide given properties of crystalline component, in particular, profile of the average size of the crystalline grains. The optimization is possible if one knows two dimensionless parameters of the theoretical model. One of them (β) is the value which is directly related to the solubility of crystalline component of the glass-ceramics in the glass matrix, and another (γ) is equal to the ratio of characteristic times of ion-exchange diffusion and crystalline grain dissolution. The presented study is dedicated to the development of experimental technique and simulation which allow determining these parameters. It is shown that these parameters can be deduced from the data on the space distributions of diffusant concentrations and average size of crystalline grains in the glass-ceramics samples subjected to ion-exchange treatment. Measurements at least at two temperatures and two processing times at each temperature are necessary. The composite material used was a silica-based glass-ceramics with crystalline grains of Li2OSiO2. Cubical samples of the glass-ceramics (6x6x6 mm3) underwent the ion exchange process in NaNO3 salt melt at 520 oC (for 16 and 48 h), 540 oC (for 8 and 24 h), 560 oC (for 4 and 12 h), and 580 oC (for 2 and 8 h). The ion exchange processing resulted in the glass-ceramics vitrification in the subsurface layers where ion-exchange diffusion took place. Slabs about 1 mm thick were cut from the central part of the samples and their big facets were polished. These slabs were used to find profiles of diffusant concentrations and average size of the crystalline grains. The concentration profiles were determined from refractive index profiles measured with Max-Zender interferometer, and profiles of the average size of the crystalline grains were determined with micro-Raman spectroscopy. Numerical simulation were based on the developed theoretical model of the glass-ceramics decrystallization induced by ion exchange. The simulation of the processes was carried out for different values of β and γ parameters under all above-mentioned ion exchange conditions. As a result, the temperature dependences of the parameters, which provided a reliable coincidence of the simulation and experimental data, were found. This ensured the adequate modeling of the process of the glass-ceramics decrystallization in 520-580 oC temperature interval. Developed approach provides a powerful tool for fine tuning of the glass-ceramics structure, namely, concentration and average size of crystalline grains.

Keywords: diffusion, glass-ceramics, ion exchange, vitrification

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Authors: Frank Hespeler, Giuseppe Loiacono

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We propose measures for systemic risk generated through intra-sectorial interdependencies in the hedge fund sector. These measures are based on variations in the average cross-effects of funds showing significant interdependency between their individual returns and the moments of the sector’s return distribution. The proposed measures display a high ability to identify periods of financial distress, are robust to modifications in the underlying econometric model and are consistent with intuitive interpretation of the results.

Keywords: hedge funds, systemic risk, vector autoregressive model, risk monitoring

Procedia PDF Downloads 310

Authors: Andi Hasizah Mochtar, Meta Mahendradatta, Amran Laga, Metusalach Metusalach, Salengke Salengke, Mariati Bilang, Andi Amijoyo Mochtar, Reta Reta, Aminah Muhdar, Sri Suhartini

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This study aims to determine the effect of alcohol type on the quality of iota carrageenan-based on extraction technology through the application of ohmic reactor. Results of this analysis will be used as a reference for selecting the proper type of alcohol used for carrageenan precipitated after extraction by technology based ohmic. The results of analysis performed included analysis of viscosity, gel strength, and yield of iota carrageenan. Viscosity is the highest obtained at precipitated by using isopropyl alcohol with an average of 291.5 Cp (at 160 rpm), then with methanol at an average of 282 Cp, then precipitated by using ethanol at an average of 206.5 Cp. Gel strength is the lowest obtained 67.74 on precipitated by using ethanol, then an average of 74.34 in precipitated that using methanol, and the highest average of 80.11 in precipitated that using isopropyl alcohol.

Keywords: extraction of carrageenan, gel strength, ohmic technology, precipitated, seaweed (Eucheuma spinosum), viscosity

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Authors: Salako Rotimi, Oshungade Stephen, Ojewoye Opeyemi

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The maintenance of price stability is one of the macroeconomic challenges facing Nigeria as a nation. This paper attempts to build a co-integration multivariate time series model for inflation movement in Nigeria using data extracted from the abstract of statistics of the Central Bank of Nigeria (CBN) from 2008 to 2017. The Johansen cointegration test suggests at least one co-integration vector describing the long run relationship between Consumer Price Index (CPI), Food Price Index (FPI) and Non-Food Price Index (NFPI). All three series show increasing pattern, which indicates a sign of non-stationary in each of the series. Furthermore, model predictability was established with root-mean-square-error, mean absolute error, mean average percentage error, and Theil’s unbiased statistics for n-step forecasting. The result depicts that the long run coefficient of a consumer price index (CPI) has a positive long-run relationship with the food price index (FPI) and non-food price index (NFPI).

Keywords: economic, inflation, model, series

Procedia PDF Downloads 233

Authors: Michelle Eliane Hernández-García, Angélica Lozano

Abstract:

The traffic accidents study usually contemplates the relation between factors such as the type of vehicle, its operation, and the road infrastructure. Traffic accidents can be explained by different factors, which have a greater or lower relevance. Two zones are studied, a mixed industrial zone and the extended zone of it. The first zone has mainly residential (57%), and industrial (23%) land uses. Trucks are mainly on the roads where industries are located. Four sensors give information about traffic and speed on the main roads. The extended zone (which includes the first zone) has mainly residential (47%) and mixed residential (43%) land use, and just 3% of industrial use. The traffic mix is composed mainly of non-trucks. 39 traffic and speed sensors are located on main roads. The traffic mix in a mixed land use zone, could be related to traffic accidents. To understand this relation, it is required to identify the elements of the traffic mix which are linked to traffic accidents. Models that attempt to explain what factors are related to traffic accidents have faced multiple methodological problems for obtaining robust databases. Poisson regression models are used to explain the accidents. The objective of the Poisson analysis is to estimate a vector to provide an estimate of the natural logarithm of the mean number of accidents per period; this estimate is achieved by standard maximum likelihood procedures. For the estimation of the relation between traffic accidents and the traffic mix, the database is integrated of eight variables, with 17,520 observations and six vectors. In the model, the dependent variable is the occurrence or non-occurrence of accidents, and the vectors that seek to explain it, correspond to the vehicle classes: C1, C2, C3, C4, C5, and C6, respectively, standing for car, microbus, and van, bus, unitary trucks (2 to 6 axles), articulated trucks (3 to 6 axles) and bi-articulated trucks (5 to 9 axles); in addition, there is a vector for the average speed of the traffic mix. A Poisson model is applied, using a logarithmic link function and a Poisson family. For the first zone, the Poisson model shows a positive relation among traffic accidents and C6, average speed, C3, C2, and C1 (in a decreasing order). The analysis of the coefficient shows a high relation with bi-articulated truck and bus (C6 and the C3), indicating an important participation of freight trucks. For the expanded zone, the Poisson model shows a positive relation among traffic accidents and speed average, biarticulated truck (C6), and microbus and vans (C2). The coefficients obtained in both Poisson models shows a higher relation among freight trucks and traffic accidents in the first industrial zone than in the expanded zone.

Keywords: freight transport, industrial zone, traffic accidents, traffic mix, trucks

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Authors: Rasool Sadeghi, Sayed Mahdi Faghih Imani, Negar Najafi

Abstract:

The inherent features of Named Data Networking (NDN) provides a robust solution for Internet of Thing (IoT). Therefore, NDN-IoT has emerged as a combined architecture which exploits the benefits of NDN for interconnecting of the heterogeneous objects in IoT. In NDN-IoT, caching schemes are a key role to improve the network performance. In this paper, we consider the effectiveness of cache replacement schemes in NDN-IoT scenarios. We investigate the impact of replacement schemes on average delay, average hop count, and average interest retransmission when replacement schemes are Least Frequently Used (LFU), Least Recently Used (LRU), First-In-First-Out (FIFO) and Random. The simulation results demonstrate that LFU and LRU present a stable performance when the cache size changes. Moreover, the network performance improves when the number of consumers increases.

Keywords: NDN-IoT, cache replacement, performance, ndnSIM

Procedia PDF Downloads 351

Authors: Lamia Bourdache, Amar Djema

Abstract:

The effect of non-Newtonian property (power law index n) on traveling waves of thin layer of power law fluid flowing over an inclined plane is investigated. For this, a simplified second-order two-equation model (SM) is used. The complete model is second-order four-equation (CM). It is derived by combining the weighted residual integral method and the lubrication theory. This is due to the fact that at the beginning of the instability waves, a very small number of waves is observed. Using a suitable set of test functions, second order terms are eliminated from the calculus so that the model is still accurate to the second order approximation. Linear, spatial, and temporal stabilities are studied. For travelling waves, a particular type of wave form that is steady in a moving frame, i.e., that travels at a constant celerity without changing its shape is studied. This type of solutions which are characterized by their celerity exists under suitable conditions, when the widening due to dispersion is balanced exactly by the narrowing effect due to the nonlinearity. Changing the parameter of celerity in some range allows exploring the entire spectrum of asymptotic behavior of these traveling waves. The (SM) model is converted into a three dimensional dynamical system. The result is that the model exhibits bifurcation scenarios such as heteroclinic, homoclinic, Hopf, and period-doubling bifurcations for different values of the power law index n. The influence of the non-Newtonian parameter on the nonlinear development of these travelling waves is discussed. It is found at the end that the qualitative characters of bifurcation scenarios are insensitive to the variation of the power law index.

Keywords: inclined plane, nonlinear stability, non-Newtonian, thin film

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Authors: Doan Van Chinh, Bui Thi Kien Trinh

Abstract:

This paper outlines some statistical properties of residual sea level (RSL) at six representative tidal stations located along the coast of Vietnam. It was found that the positive RSL varied on average between 9.82 and 19.96cm and the negative RSL varied on average between -16.62 and -9.02cm. The maximum positive RSL varied on average between 102.8 and 265.5cm with the maximum negative RSL varied on average between -250.4 and -66.4cm. It is seen that the biggest positive RSL ere appeared in the summer months and the biggest negative RSL ere appeared in the winter months. The cumulative frequency of RSL less than 50 cm occurred between 95 and 99% of the times while the frequency of RSL higher than 100 cm accounted for between 0.01 and 0.2%. It also was found that the cumulative frequency of duration of RSL less than 24 hours occurred between 90 and 99% while the frequency of duration longer than 72 hours was in the order of 0.1 and 1%.

Keywords: coast of Vietnam, residual sea level, residual water, surge, cumulative frequency

Procedia PDF Downloads 272