Search results for: Full Bayes models

Authors: Dražen Cvitanić, Biljana Maljković

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This paper presents models for predicting operating speeds on tangent sections of two-lane rural roads developed on continuous speed data. The data corresponds to 20 drivers of different ages and driving experiences, driving their own cars along an 18 km long section of a state road. The data were first used for determination of maximum operating speeds on tangents and their comparison with speeds in the middle of tangents i.e. speed data used in most of operating speed studies. Analysis of continuous speed data indicated that the spot speed data are not reliable indicators of relevant speeds. After that, operating speed models for tangent sections were developed. There was no significant difference between models developed using speed data in the middle of tangent sections and models developed using maximum operating speeds on tangent sections. All developed models have higher coefficient of determination then models developed on spot speed data. Thus, it can be concluded that the method of measuring has more significant impact on the quality of operating speed model than the location of measurement.

Keywords: operating speed, continuous speed data, tangent sections, spot speed, consistency

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Authors: Anne Eugenia Wright

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This study examines issues in accessibility to maritime cultural heritage. Using the Pillar Dollar Wreck in Biscayne National Park, Florida, this study presents an approach to public outreach based on the concept of Design for All. Design for All advocates creating products that are accessible and functional for all users, including those with visual, hearing, learning, mobility, or economic impairments. As a part of this study, a small exhibit was created that uses 3D products as a way to bring maritime cultural heritage to the public. It was presented to the public at East Carolina University’s Joyner Library. Additionally, this study presents a methodology for 3D printing scaled photogrammetry models of archaeological sites in full color. This methodology can be used to present a realistic depiction of underwater archaeological sites to those who are incapable of accessing them in the water. Additionally, this methodology can be used to present underwater archaeological sites that are inaccessible to the public due to conditions such as visibility, depth, or protected status. This study presents a practical use for 3D photogrammetry models, as well as an accessibility strategy to expand the outreach potential for maritime archaeology.

Keywords: Underwater Archaeology, 3D Printing, Photogrammetry, Design for All

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Authors: Razieh Arian, Hadi Adibi-Asl

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This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine

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Authors: Rehab Abdulmajed, Amr Hamada, Ahmed Elsaid, Hisashi Hayakawa, Ayman Mahrous

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Solar emissions have a high impact on the Earth’s magnetic field, and the prediction of solar events is of high interest. Various techniques have been used in the prediction of solar wind using mathematical models, MHD models, and neural network (NN) models. This study investigates the coronal hole (CH) derived high-speed streams (HSSs) and their correlation to the CH area and create a neural network model to predict the HSSs. Two different algorithms were used to compare different models to find a model that best simulates the HSSs. A dataset of CH synoptic maps through Carrington rotations 1601 to 2185 along with Omni-data set solar wind speed averaged over the Carrington rotations is used, which covers Solar cycles (sc) 21, 22, 23, and most of 24.

Keywords: artificial neural network, coronal hole area, feed-forward neural network models, solar high speed streams

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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There has been a need in recent years to predict student academic achievement prior to graduation. This is to assist them in improving their grades, especially for those who have struggled in the past. The purpose of this research is to use supervised learning techniques to create a model that predicts student academic progress. Many scholars have developed models that predict student academic achievement based on characteristics including smoking, demography, culture, social media, parent educational background, parent finances, and family background, to mention a few. This element, as well as the model used, could have misclassified the kids in terms of their academic achievement. As a prerequisite to predicting if the student will perform well in the future on related courses, this model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester. With a 96.7 percent accuracy, the model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost. This model is offered as a desktop application with user-friendly interfaces for forecasting student academic progress for both teachers and students. As a result, both students and professors are encouraged to use this technique to predict outcomes better.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Sibel Celik, Hüseyin Ergin

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The paper aims to find the best volatility forecasting model for stock markets in Turkey. For this purpose, we compare performance of different volatility models-both traditional GARCH model and high frequency based volatility models- and conclude that both in pre-crisis and crisis period, the performance of high frequency based volatility models are better than traditional GARCH model. The findings of paper are important for policy makers, financial institutions and investors.

Keywords: volatility, GARCH model, realized volatility, high frequency data

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Authors: Ahmed Abada, Kadda Amara, Said Hiadsi, Bouhalouane Amrani

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Half-metallic properties of new predicted Mn2-based full Heusler alloys Mn2ZrSi and Mn2ZrGe have been studied by first-principles full-potential linearized augmented plane wave plus local orbital (FP-LAPW+lo) method based on density functional theory (DFT). Our investigation is focused on the structural, elastic, electronic and magnetic properties of these compounds. The AlCu2Mn-type structure is found to be energetically more favorable than the CuHg2Ti-type structure for both compounds and are half-metallic ferrimagnets (HMFIs) with total magnetic moments of 2.000 µB per formula unit, well consistent with Slater-Pauling rule (Mtot = ( 24 – Ztot ) µB). Calculations show that both the alloys have an indirect band gaps, in the majority-spin channel, with values of 0.505 eV and 0.278 eV for Mn2ZrSi and Mn2ZrGe, respectively. It was found that Mn2ZrSi and Mn2ZrGe preserved their half-metallicity for lattice constants range of 5.85–6.38 Å and 6.05–6.38 Å, respectively, and kept a 100% of spin polarization at the Fermi level. Moreover, the calculated formation energies and elastic constants confirm that these compounds are stable chemically and mechanically, and the good crystallographic compatibility with the lattice of semiconductors used industrially makes them promising magnetic materials in spintronic applications.

Keywords: first-principles calculations, full Heusler structure, half-metallic ferrimagnets, elastic properties

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Authors: Ashwini V. Chavan, Sukhanand S. Bhosale

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Challenges of weak soil subgrade are often resolved either by stabilization or reinforcing it. However, it is also practiced to reinforce the granular fill to improve the load-settlement behavior of over weak soil strata. The inclusion of reinforcement in the engineered granular fill provided a new impetus for the development of enhanced Soil-Structure Interaction (SSI) models, also known as mechanical foundation models or lumped parameter models. Several researchers have been working in this direction to understand the mechanism of granular fill-reinforcement interaction and the response of weak soil under the application of load. These models have been developed by extending available SSI models such as the Winkler Model, Pasternak Model, Hetenyi Model, Kerr Model etc., and are helpful to visualize the load-settlement behavior of a physical system through 1-D and 2-D analysis considering beam and plate resting on the foundation respectively. Based on the literature survey, these models are categorized as ‘Reinforced Pasternak Model,’ ‘Double Beam Model,’ ‘Reinforced Timoshenko Beam Model,’ and ‘Reinforced Kerr Model.’ The present work reviews the past 30+ years of research in the field of SSI models for reinforced foundation systems, presenting the conceptual development of these models systematically and discussing their limitations. Special efforts are taken to tabulate the parameters and their significance in the load-settlement analysis, which may be helpful in future studies for the comparison and enhancement of results and findings of physical models.

Keywords: geosynthetics, mathematical modeling, reinforced foundation, soil-structure interaction, ground improvement, soft soil

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Authors: R. A. Ribeiro, P. D. Angelo Assunção, E. M. Braga

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The microhardness in weld beads is a function of the microstructure obtained in the welding process, and this by its time is dependent of the input variables established at the outset of the process. In this study the influence of angle between the plate and the cold wire, the position in which the cold wire is introduced and the rate in which this introduction is made are assessed as input parameters in CW-GMAW process. This paper looks to show that ordinary changes in the frame of CW-GMAW can improve microhardness, which is expected to vary as the input parameters change. To properly correlate the changes in the input parameters to consequent changes in microhardness of the weld bead, a full factorial design was employed. In fact, changes in the operational parameters improved the overall microhardness of the weld bead, which in turns can be an indication of improvement in the resistance to abrasive wear, constituting a cheap way to augment the abrasion wear resistance of welds used for cladding.

Keywords: abrasion, CW-GMAW, full factorial design, microhardness

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Authors: Juan Manuel Sanchez-Cartas, Gonzalo Leon

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A price competition algorithm for ABMs based on game theory principles is proposed to deal with the simulation of theoretical market models. The algorithm is applied to the classical Hotelling’s model and to a two-sided market model to show it leads to the optimal behavior predicted by theoretical models. However, when theoretical models fail to predict the equilibrium, the algorithm is capable of reaching a feasible outcome. Results highlight that the algorithm can be implemented in other simulation models to guarantee rational users and endogenous optimal behaviors. Also, it can be applied as a tool of verification given that is theoretically based.

Keywords: agent-based models, algorithmic game theory, multi-sided markets, price optimization

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Authors: Phanida Phukoetphim, Asaad Y. Shamseldin

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In this study, the novel Stochastic Gradient Boosting (SGB) combination method is addressed for producing daily river flows from four different rain-runoff models of Ohinemuri catchment, New Zealand. The selected rainfall-runoff models are two empirical black-box models: linear perturbation model and linear varying gain factor model, two conceptual models: soil moisture accounting and routing model and Nedbør-Afrstrømnings model. In this study, the simple average combination method and the weighted average combination method were used as a benchmark for comparing the results of the novel SGB combination method. The models and combination results are evaluated using statistical and graphical criteria. Overall results of this study show that the use of combination technique can certainly improve the simulated river flows of four selected models for Ohinemuri catchment, New Zealand. The results also indicate that the novel SGB combination method is capable of accurate prediction when used in a combination method of the simulated river flows in New Zealand.

Keywords: multi-model combination, rainfall-runoff modeling, stochastic gradient boosting, bioinformatics

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Authors: Ahmad Alwosheel, Ahmed Alqaraawi

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This work proposes an unsupervised text-independent probabilistic approach to recognize Quran reciter voice. It is an accurate approach that works on real time applications. This approach does not require a prior information about reciter models. It has two phases, where in the training phase the reciters' acoustical features are modeled using Gaussian Mixture Models, while in the testing phase, unlabeled reciter's acoustical features are examined among GMM models. Using this approach, a high accuracy results are achieved with efficient computation time process.

Keywords: Quran, speaker recognition, reciter recognition, Gaussian Mixture Model

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Authors: Jay L. Fu

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Patients with Alzheimer's disease progressively lose their memory and thinking skills and, eventually, the ability to carry out simple daily tasks. The disease is irreversible, but early detection and treatment can slow down the disease progression. In this research, publicly available MRI data and demographic data from 373 MRI imaging sessions were utilized to build models to predict dementia. Various machine learning models, including logistic regression, k-nearest neighbor, support vector machine, random forest, and neural network, were developed. Data were divided into training and testing sets, where training sets were used to build the predictive model, and testing sets were used to assess the accuracy of prediction. Key risk factors were identified, and various models were compared to come forward with the best prediction model. Among these models, the random forest model appeared to be the best model with an accuracy of 90.34%. MMSE, nWBV, and gender were the three most important contributing factors to the detection of Alzheimer’s. Among all the models used, the percent in which at least 4 of the 5 models shared the same diagnosis for a testing input was 90.42%. These machine learning models allow early detection of Alzheimer’s with good accuracy, which ultimately leads to early treatment of these patients.

Keywords: Alzheimer's disease, clinical diagnosis, magnetic resonance imaging, machine learning prediction

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Authors: K. Debkowska

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The aim of this article is presenting the possibilities of using Fuzzy Set Qualitative Comparative Analysis (fsQCA) in researches concerning business models of enterprises. FsQCA is a bridge between quantitative and qualitative researches. It's potential can be used in analysis and evaluation of business models. The article presents the results of a study conducted on the basis of enterprises belonging to different sectors: transport and logistics, industry, building construction, and trade. The enterprises have been researched taking into account the components of business models and the financial condition of companies. Business models are areas of complex and heterogeneous nature. The use of fsQCA has enabled to answer the following question: which components of a business model and in which configuration influence better financial condition of enterprises. The analysis has been performed separately for particular sectors. This enabled to compare the combinations of business models' components which actively influence the financial condition of enterprises in analyzed sectors. The following components of business models were analyzed for the purposes of the study: Key Partners, Key Activities, Key Resources, Value Proposition, Channels, Cost Structure, Revenue Streams, Customer Segment and Customer Relationships. These components of the study constituted the variables shaping the financial results of enterprises. The results of the study lead us to believe that fsQCA can help in analyzing and evaluating a business model, which is important in terms of making a business decision about the business model used or its change. In addition, results obtained by fsQCA can be applied by all stakeholders connected with the company.

Keywords: business models, components of business models, data analysis, fsQCA

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Authors: Sheryl Avendaño, Miguel Ospina, Hebert Montegranario

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Full Wave Inversion (FWI) is a variant of seismic tomography for obtaining velocity profiles by an optimization process that combine forward modelling (or solution of wave equation) with the misfit between synthetic and observed data. In this research we are modelling wave propagation in a visco-acoustic medium in the frequency domain. We apply finite differences for the numerical solution of the wave equation with a mix between usual and rotated grids, where density depends on velocity and there exists a damping function associated to a linear dissipative medium. The velocity profiles are obtained from an initial one and the data have been modeled for a frequency range 0-120 Hz. By an iterative procedure we obtain an estimated velocity profile in which are detailed the remarkable features of the velocity profile from which synthetic data were generated showing promising results for our method.

Keywords: seismic inversion, full wave inversion, visco acoustic wave equation, finite diffrence methods

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

Abstract:

In recent years, there has been a desire to forecast student academic achievement prior to graduation. This is to help them improve their grades, particularly for individuals with poor performance. The goal of this study is to employ supervised learning techniques to construct a predictive model for student academic achievement. Many academics have already constructed models that predict student academic achievement based on factors such as smoking, demography, culture, social media, parent educational background, parent finances, and family background, to name a few. This feature and the model employed may not have correctly classified the students in terms of their academic performance. This model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester as a prerequisite to predict if the student will perform well in future on related courses. The model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost, returning a 96.7% accuracy. This model is available as a desktop application, allowing both instructors and students to benefit from user-friendly interfaces for predicting student academic achievement. As a result, it is recommended that both students and professors use this tool to better forecast outcomes.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Salah Al-Din I. Badran, Samad Ahmadi, Ismail Shahin

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A blind source separation method is proposed; in this method we use a non-uniform filter bank and a novel normalisation. This method provides a reduced computational complexity and increased convergence speed comparing to the full-band algorithm. Recently, adaptive sub-band scheme has been recommended to solve two problems: reduction of computational complexity and increase the convergence speed of the adaptive algorithm for correlated input signals. In this work the reduction in computational complexity is achieved with the use of adaptive filters of orders less than the full-band adaptive filters, which operate at a sampling rate lower than the sampling rate of the input signal. The decomposed signals by analysis bank filter are less correlated in each sub-band than the input signal at full bandwidth, and can promote better rates of convergence.

Keywords: blind source separation, computational complexity, subband, convergence speed, mixture

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Authors: Tadeusz Nowicki, Radosław Pytlak, Robert Waszkowski, Jerzy Bertrandt, Anna Kłos

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This paper presents methods for formal modeling of activities in the area of sanitary inspectors outbreak of food-borne diseases. The models allow you to measure the characteristics of the activities of sanitary inspection and as a result allow improving the performance of sanitary services and thus food security.

Keywords: food-borne disease, epidemic, sanitary inspection, mathematical models

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Authors: Sara R. Knigge, Sugat R. Tuladhar, Hans-Klaus HöFfler, Tobias Schilling, Tim Kaufeld, Axel Haverich

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Tissue engineered (TE) heart valves based on degradable electrospun fiber scaffold represent a promising approach to overcome the known limitations of mechanical or biological prostheses. But the mechanical stress in the high-pressure system of the human circulation is a severe challenge for the delicate materials. Hence, the prediction of the scaffolds` in vivo degradation kinetics must be as accurate as possible to prevent fatal events in future animal or even clinical trials. Therefore, this study investigates whether long-term testing in full blood provides more meaningful results regarding the degradation behavior than conventional tests in simulated body fluids (SBF) or Phosphate Buffered Saline (PBS). Fiber mats were produced from a polycaprolactone (PCL)/tetrafluoroethylene solution by electrospinning. The morphology of the fiber mats was characterized via scanning electron microscopy (SEM). A maximum physiological degradation environment utilizing a test set-up with porcine full blood was established. The set-up consists of a reaction vessel, an oxygenator unit, and a roller pump. The blood parameters (pO2, pCO2, temperature, and pH) were monitored with an online test system. All tests were also carried out in the test circuit with SBF and PBS to compare conventional degradation media with the novel full blood setting. The polymer's degradation is quantified by SEM picture analysis, differential scanning calorimetry (DSC), and Raman spectroscopy. Tensile and cyclic loading tests were performed to evaluate the mechanical integrity of the scaffold. Preliminary results indicate that PCL degraded slower in full blood than in SBF and PBS. The uptake of water is more pronounced in the full blood group. Also, PCL preserved its mechanical integrity longer when degraded in full blood. Protein absorption increased during the degradation process. Red blood cells, platelets, and their aggregates adhered on the PCL. Presumably, the degradation led to a more hydrophilic polymeric surface which promoted the protein adsorption and the blood cell adhesion. Testing degradable implants in full blood allows for developing more reliable scaffold materials in the future. Material tests in small and large animal trials thereby can be focused on testing candidates that have proven to function well in an in-vivo-like setting.

Keywords: Electrospun scaffold, full blood degradation test, long-term polymer degradation, tissue engineered aortic heart valve

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Authors: A. G. Kovalenko, Y. N. Amirgaliyev, A. U. Kalizhanova, L. S. Balgabayeva, A. H. Kozbakova, Z. S. Aitkulov

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It is known that statistical information on operation of the compound multisite system is often far from the description of actual state of the system and does not allow drawing any conclusions about the correctness of its operation. For example, from the world practice of operation of systems of water supply, water disposal, it is known that total measurements at consumers and at suppliers differ between 40-60%. It is connected with mathematical measure of inaccuracy as well as ineffective running of corresponding systems. Analysis of widely-distributed systems is more difficult, in which subjects, which are self-maintained in decision-making, carry out economic interaction in production, act of purchase and sale, resale and consumption. This work analyzed mathematical models of sellers, consumers, arbitragers and the models of their interaction in the provision of dispersed single-product market of perfect competition. On the basis of these models, the methods, allowing estimation of every subject’s operating options and systems as a whole are given.

Keywords: dispersed systems, models, hydraulic network, algorithms

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Authors: Anthony Usoro

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In this paper, two classes of bilinear time series model are obtained under certain conditions from the general bilinear autoregressive moving average model. Bilinear Autoregressive (BAR) and Bilinear Moving Average (BMA) Models have been identified. From the general bilinear model, BAR and BMA models have been proved to exist for q = Q = 0, => j = 0, and p = P = 0, => i = 0 respectively. These models are found useful in modelling most of the economic and financial data.

Keywords: autoregressive model, bilinear autoregressive model, bilinear moving average model, moving average model

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Authors: Young Nam Jo, Moon Jeong Kang, Hong Hee Yoo

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Most human vibration models have been modeled as a multibody system consisting of some rigid bodies and spring-dampers. These models are developed for certain posture and conditions. So, the models cannot be used in vibration analysis in various posture and conditions. The purpose of this study is to develop a human vibration model that represent human vibration characteristics under various conditions by employing a musculoskeletal model. To do this, the human vibration model is developed based on biomechanical models. In addition, muscle models are employed instead of spring-dampers. Activations of muscles are controlled by PD controller to maintain body posture under vertical vibration is applied. Each gain value of the controller is obtained to minimize the difference of apparent mass and acceleration transmissibility between experim ent and analysis by using an optimization method.

Keywords: human vibration analysis, hill type muscle model, PD control, whole-body vibration

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Authors: Saih Mohamed, Rouijaa Hicham, Ghammaz Abdelilah

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This paper presents circuit models to analyze the conducted susceptibility of multiconductor shielded cables in frequency domains using Branin’s method, which is referred to as the method of characteristics. These models, Which can be used directly in the time and frequency domains, take into account the presence of both the transfer impedance and admittance. The conducted susceptibility is studied by using an injection current on the cable shield as the source. Two examples are studied, a coaxial shielded cable and shielded cables with two parallel wires (i.e., twinax cables). This shield has an asymmetry (one slot on the side). Results obtained by these models are in good agreement with those obtained by other methods.

Keywords: circuit models, multiconductor shielded cables, Branin’s method, coaxial shielded cable, twinax cables

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Authors: Tri Harianto, Lawalenna Samang, St. Hijraini Nur, Arwin

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Recently, a port development is constructed in Makassar city, South Sulawesi Province, Indonesia. Makassar city is located in lowland area that dominated by soft marine clay deposit. A two kilometers causeway construction was built which is situated on the soft clay layer. In order to investigate the behavior of causeway embankment, a full-scale test was conducted of high embankment built on a soft clay deposit. The embankment with 3,5 m high was supported by two types of reinforcement such as raft and raft-aggregate column foundation. Since the ground was undergoing consolidation due to the preload, the raft and raft-aggregate column foundations were monitored in order to analyze the vertical ground movement by inducing the settlement of the foundation. In this study, two types of foundation (raft and raft-aggregate column) were tested to observe the effectiveness of raft-aggregate column compare to raft foundation in reducing the settlement. The settlement monitored during the construction stage by using the settlement plates, which is located in the center and toe of the embankment. Measurements were taken every day for each embankment construction stage (4 months). In addition, an analytical calculation was conducted in this study to compare the full-scale test result. The result shows that the raft-aggregate column foundation significantly reduces the settlement by 30% compared to the raft foundation. A raft-aggregate column foundation also reduced the time period of each loading stage. The Good agreement of analytical calculation compared to the full-scale test result also found in this study.

Keywords: full-scale, preloading, raft-aggregate column, soft clay

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Authors: Olawale Babatunde Olatinsu, Deborah Oluwaseun Olorode

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Industrial rocks were collected from a quarry site at Ewekoro in south-western Nigeria and analysed using Nuclear Magnetic Resonance (NMR) technique. NMR measurement was conducted on the samples in partial water-saturated and full brine-saturated conditions. Raw NMR data were analysed with the aid of T2 curves and T2 spectra generated by inversion of raw NMR data using conventional regularized least-squares inversion routine. Results show that NMR transverse relaxation (T2) signatures fairly adequately distinguish between the rock types. Similar T2 curve trend and rates at partial saturation suggests that the relaxation is mainly due to adsorption of water on micropores of similar sizes while T2 curves at full saturation depict relaxation decay rate as: 1/T2(shale)>1/ T2(glauconite)>1/ T2(limestone) and 1/T2(sandstone). NMR T2 distributions at full brine-saturation show: unimodal distribution in shale; bimodal distribution in sandstone and glauconite; and trimodal distribution in limestone. Full saturation T2 distributions revealed the presence of well-developed and more abundant micropores in all the samples with T2 in the range, 402-504 μs. Mesopores with amplitudes much lower than those of micropores are present in limestone, sandstone and glauconite with T2 range: 8.45-26.10 ms, 6.02-10.55 ms, and 9.45-13.26 ms respectively. Very low amplitude macropores of T2 values, 90.26-312.16 ms, are only recognizable in limestone samples. Samples with multiple peaks showed well-connected pore systems with sandstone having the highest degree of connectivity. The difference in T2 curves and distributions for the rocks at full saturation can be utilised as a potent diagnostic tool for discrimination of these rock types found at Ewekoro.

Keywords: Ewekoro, NMR techniques, industrial rocks, characterization, relaxation

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Authors: T. H. Huang, C. Y. Gao, C. H. Lin, J. L. Kwo, Y. K. Tseng

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The design and reliability of solar photovoltaic modules are crucial to the development of solar energy, and efforts are still being made to extend the life of photovoltaic modules to improve their efficiency because natural aging is time-consuming and does not provide manufacturers and investors with timely information, accelerated aging is currently the best way to estimate the life of photovoltaic modules. In this study, the accelerated aging of different light sources was combined with spectral response measurements to understand the effect of light sources on aging tests. In this study, there are two types of experimental samples: packaged and unpackaged and then irradiated with full-spectrum and UVC light sources for accelerated aging, as well as a control group without aging. The full-spectrum aging was performed by irradiating the solar cell with a xenon lamp like the solar spectrum for two weeks, while the accelerated aging was performed by irradiating the solar cell with a UVC lamp for two weeks. The samples were first visually observed, and infrared thermal images were taken, and then the electrical (IV) and Spectral Responsivity (SR) data were obtained by measuring the spectral response of the samples, followed by Scanning Electron Microscopy (SEM), Raman spectroscopy (Raman), and X-ray Diffraction (XRD) analysis. The results of electrical (IV) and Spectral Responsivity (SR) and material analyses were used to compare the differences between packaged and unpackaged solar cells with full spectral aging, accelerated UVC aging, and unaged solar cells. The main objective of this study is to compare the difference in the aging of packaged and unpackaged solar cells by irradiating different light sources. We determined by infrared thermal imaging that both full-spectrum aging and UVC accelerated aging increase the defects of solar cells, and IV measurements demonstrated that the conversion efficiency of solar cells decreases after full-spectrum aging and UVC accelerated aging. SEM observed some scorch marks on both unpackaged UVC accelerated aging solar cells and unpackaged full-spectrum aging solar cells. Raman spectroscopy examines the Si intensity of solar cells, and XRD confirms the crystallinity of solar cells by the intensity of Si and Ag winding peaks.

Keywords: solar cell, aging, spectral response measurement

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Authors: L. Hamra, J. F. Demonceau, V. Denoël

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The aim of this paper is to study a beam extracted from a frame and subjected to blast loading. The demand of ductility depends on six dimensionless parameters: two related to the blast loading, two referring to the bending behavior of the beam and two corresponding to the dynamic behavior of the rest of the structure. We develop a full analytical procedure that provides the ductility demand as a function of these six dimensionless parameters.

Keywords: analytical procedure, blast loading, membrane force, P-I diagram

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Authors: Sidique Gawusu, Xiaobing Zhang

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Turbulence models play a significant role in all computational fluid dynamics based modelling approaches. There is, however, no general turbulence model suitable for all flow scenarios. Therefore, a successful numerical modelling approach is only achievable if a more appropriate closure model is used. This paper evaluates different turbulence models in numerical modelling of oil-water flow within the Eulerian-Eulerian approach. A comparison among the obtained numerical results and published benchmark data showed reasonable agreement. The domain was meshed using structured mesh, and grid test was performed to ascertain grid independence. The evaluation of the models was made through analysis of velocity and pressure profiles across the domain. The models were tested for their suitability to accurately obtain a scalable and precise numerical experience. As a result, it is found that all the models except Standard-ω provide comparable results. The study also revealed new insights on flow in porous media, specifically oil reservoirs.

Keywords: turbulence modelling, simulation, multi-phase flows, water-flooding, heavy oil

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Authors: Katja Ignatieva, Patrick Wong

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We investigated the dynamics of high frequency energy prices, including crude oil and electricity prices. The returns of underlying quantities are modelled using various parametric models such as stochastic framework with jumps and stochastic volatility (SVCJ) as well as non-parametric alternatives, which are purely data driven and do not require specification of the drift or the diffusion coefficient function. Using different statistical criteria, we investigate the performance of considered parametric and nonparametric models in their ability to forecast price series and volatilities. Our models incorporate possible seasonalities in the underlying dynamics and utilise advanced estimation techniques for the dynamics of energy prices.

Keywords: stochastic volatility, affine jump-diffusion models, high frequency data, model specification, markov chain monte carlo

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Authors: Hadi Rad

Abstract:

Unrestricted somatic stem cells (USSCs) loaded in nanofibrous PHBV scaffold can be used for skin regeneration when grafted into full-thickness skin defects of rats. Nanofibrous PHBV scaffolds were designed using electrospinning method and then, modified with the immobilized collagen via the plasma method. Afterward, the scaffolds were evaluated using scanning electron microscopy, physical and mechanical assays. In this study; nanofibrous PHBV scaffolds loaded with and without USSCs were grafted into the skin defects. The wounds were subsequently investigated at 21 days after grafting. Results of mechanical and physical analyses showed good resilience and compliance to movement as a skin graft. In animal models; all study groups excluding the control group exhibited the most pronounced effect on wound closure, with the statistically significant improvement in wound healing being seen on post-operative Day 21. Histological and immunostaining examinations of healed wounds from all groups, especially the groups treated with stem cells, showed a thin epidermis plus recovered skin appendages in the dermal layer. Thus, the graft of collagen-coated nanofibrous PHBV scaffold loaded with USSC showed better results during the healing process of skin defects in rat model.

Keywords: collagen, nanofibrous PHBV scaffold, unrestricted somatic stem cells, wound healing.

Procedia PDF Downloads 349