Search results for: Ratio dependent models

Authors: Wai Pan Chan, Minkyu Je

Abstract:

A precision CMOS chopping amplifier is adopted in this work to improve a CMOS temperature sensor high sensitive enough for intracranial temperature monitoring. An amplified temperature sensitivity of 18.8 ± 3*0.2 mV/oC is attained over the temperature range from 20 oC to 80 oC from a given 10 samples of the same wafer. The analog frontend design outputs the temperature dependent and the temperature independent signals which can be directly interfaced to a 10 bit ADC to accomplish an accurate temperature instrumentation system.

Keywords: Chopping, analog frontend, CMOS temperature sensor, traumatic brain injury (TBI), intracranial temperature monitoring.

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Authors: Elena Carcano, Mirzi Betasolo

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This study aims to provide sub-hourly streamflow predictions and associated rating curves for small catchments of intermittent and torrential flow regime characterized by flash floods occurring especially during April and November. The methodology entails two lumped conceptual hydrological models which work in series. The total model is based upon eleven parameters and shows good flexibility in handling different input sets. Runoff Coefficient has contributed to improving the model’s performances and has been treated as an additional parameter; while Sensitivity Analysis has highlighted how slight changes in the model’s input can lead to changes in model’s output. The adopted procedure is steady and useful to give very practical engineering information at the expense of a parsimonious request both in input data and in the number of adopted parameters. According to the obtained results, the authors encourage the test of this combined procedure on different hydrological scenarios in order to provide information for poorly monitored catchments and not updated sites.

Keywords: Streamflow rating curve, chronological data, streamflow sequences, conceptual models.

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Authors: M. Sadeghi, H. Pezeshk, R. Tusserkani, A. Sharifi Zarchi, A. Malekpour, M. Foroughmand, S. Goliaei, M. Totonchi, N. Ansari–Pour

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The role and relative importance of intrinsic and extrinsic factors in the development of complex diseases such as cancer still remains a controversial issue. Determining the amount of variation explained by these factors needs experimental data and statistical models. These models are nevertheless based on the occurrence and accumulation of random mutational events during stem cell division, thus rendering cancer development a stochastic outcome. We demonstrate that not only individual genome sequencing is uninformative in determining cancer risk, but also assigning a unique genome sequence to any given individual (healthy or affected) is not meaningful. Current whole-genome sequencing approaches are therefore unlikely to realize the promise of personalized medicine. In conclusion, since genome sequence differs from cell to cell and changes over time, it seems that determining the risk factor of complex diseases based on genome sequence is somewhat unrealistic, and therefore, the resulting data are likely to be inherently uninformative.

Keywords: Cancer risk, extrinsic factors, genome sequencing, intrinsic factors.

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Authors: C. V. Pietreanu, S. E. Zaharia, C. Dinu

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The present research is built on three major pillars, commencing by making some considerations on accident investigation methods and pointing out both defining aspects and differences between linear and non-linear analysis. The traditional linear focus on accident analysis describes accidents as a sequence of events, while the latest systemic models outline interdependencies between different factors and define the processes evolution related to a specific (normal) situation. Linear and non-linear accident analysis methods have specific limitations, so the second point of interest is mirrored by the aim to discover the drawbacks of systemic models which becomes a starting point for developing new directions to identify risks or data closer to the cause of incidents/accidents. Since communication represents a critical issue in the interaction of human factor and has been proved to be the answer of the problems made by possible breakdowns in different communication procedures, from this focus point, on the third pylon a new error-modeling instrument suitable for risk assessment/accident analysis will be elaborated.

Keywords: Accident analysis, multi-factorial error modeling, risk, systemic methods.

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Authors: V. Sandeep Kumar, S. Anuradha

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The high Peak to Average Power Ratio (PAR) in Filter Bank Multicarrier with Offset Quadrature Amplitude Modulation (FBMC-OQAM) can significantly reduce power efficiency and performance. In this paper, we address the problem of PAPR reduction for FBMC-OQAM systems using Tone Reservation (TR) technique. Due to the overlapping structure of FBMCOQAM signals, directly applying TR schemes of OFDM systems to FBMC-OQAM systems is not effective. We improve the tone reservation (TR) technique by employing sliding window with Active Constellation Extension for the PAPR reduction of FBMC-OQAM signals, called sliding window tone reservation Active Constellation Extension (SW-TRACE) technique. The proposed SW-TRACE technique uses the peak reduction tones (PRTs) of several consecutive data blocks to cancel the peaks of the FBMC-OQAM signal inside a window, with dynamically extending outer constellation points in active(data-carrying) channels, within margin-preserving constraints, in order to minimize the peak magnitude. Analysis and simulation results compared to the existing Tone Reservation (TR) technique for FBMC/OQAM system. The proposed method SW-TRACE has better PAPR performance and lower computational complexity.

Keywords: FBMC-OQAM, peak-to-average power ratio, sliding window, tone reservation Active Constellation Extension.

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Authors: M. Alwetaishi

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One of the most common and traditional strategies in architecture is to design buildings passively. This is a way to ensure low building energy reliance with respect to specific micro-building locations. There are so many ways where buildings can be designed passively, some of which are applying thermal insulation, thermal mass, courtyard and glazing to wall ratio. This research investigates the impact of each of these aspects with respect to the hot and dry climate of the capital of Riyadh. Thermal Analysis Simulation (TAS) will be utilized which is powered by Environmental Design Simulation Limited company (EDSL). It is considered as one of the most powerful tools to predict energy performance in buildings. There are three primary building designs and methods which are using courtyard, thermal mass and thermal insulation. The same building size and fabrication properties have been applied to all designs. Riyadh city which is the capital of the country was taken as a case study of the research. The research has taken into account various zone directions within the building as it has a large contribution to indoor energy and thermal performance. It is revealed that it is possible to achieve nearly zero carbon building in the hot and dry region in winter with minimum reliance on energy loads for building zones facing south, west and east. Moreover, using courtyard is more beneficial than applying construction materials into building envelope. Glazing to wall ratio is recommended to be 10% and not exceeding 30% in all directions in hot and arid regions.

Keywords: Sustainable buildings, hot and arid climates, passive building design, Saudi Arabia.

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Authors: Hayder H. Kareem, Shunqi Pan

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The geological environment where the groundwater is collected represents the most important element that affects the behaviour of groundwater aquifer. As groundwater is a worldwide vital resource, it requires knowing the parameters that affect this source accurately so that the conceptualized mathematical models would be acceptable to the broadest ranges. Therefore, groundwater models have recently become an effective and efficient tool to investigate groundwater aquifer behaviours. Groundwater aquifer may contain aquitards, aquicludes, or interfaces within its geological formations. Aquitards and aquicludes have geological formations that forced the modellers to include those formations within the conceptualized groundwater models, while interfaces are commonly neglected from the conceptualization process because the modellers believe that the interface has no effect on aquifer behaviour. The current research highlights the impact of an interface existing in a real unconfined groundwater aquifer called Dibdibba, located in Al-Najaf City, Iraq where it has a river called the Euphrates River that passes through the eastern part of this city. Dibdibba groundwater aquifer consists of two types of soil layers separated by an interface soil layer. A groundwater model is built for Al-Najaf City to explore the impact of this interface. Calibration process is done using PEST 'Parameter ESTimation' approach and the best Dibdibba groundwater model is obtained. When the soil interface is conceptualized, results show that the groundwater tables are significantly affected by that interface through appearing dry areas of 56.24 km² and 6.16 km² in the upper and lower layers of the aquifer, respectively. The Euphrates River will also leak water into the groundwater aquifer of 7359 m³/day. While these results are changed when the soil interface is neglected where the dry area became 0.16 km², the Euphrates River leakage became 6334 m³/day. In addition, the conceptualized models (with and without interface) reveal different responses for the change in the recharge rates applied on the aquifer through the uncertainty analysis test. The aquifer of Dibdibba in Al-Najaf City shows a slight deficit in the amount of water supplied by the current pumping scheme and also notices that the Euphrates River suffers from stresses applied to the aquifer. Ultimately, this study shows a crucial need to represent the interface soil layer in model conceptualization to be the intended and future predicted behaviours more reliable for consideration purposes.

Keywords: Al-Najaf City, groundwater aquifer behaviour, groundwater modelling, interface soil layer, Visual MODFLOW.

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Authors: J. Geiser, R. Röhle

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In this paper we present discretization and decomposition methods for a multi-component transport model of a chemical vapor deposition (CVD) process. CVD processes are used to manufacture deposition layers or bulk materials. In our transport model we simulate the deposition of thin layers. The microscopic model is based on the heavy particles, which are derived by approximately solving a linearized multicomponent Boltzmann equation. For the drift-process of the particles we propose diffusionreaction equations as well as for the effects of heat conduction. We concentrate on solving the diffusion-reaction equation with analytical and numerical methods. For the chemical processes, modelled with reaction equations, we propose decomposition methods and decouple the multi-component models to simpler systems of differential equations. In the numerical experiments we present the computational results of our proposed models.

Keywords: Chemical reactions, chemical vapor deposition, convection-diffusion-reaction equations, decomposition methods, multi-component transport.

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Authors: Sharareh Mohseni, Reihaneh Ahmadzadeh Ghavidel

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Tomato powder has good potential as substitute of tomato paste and other tomato products. In order to protect physicochemical properties and nutritional quality of tomato during dehydration process, investigation was carried out using different drying methods and pretreatments. Solar drier and continuous conveyor (tunnel) drier were used for dehydration where as calcium chloride (CaCl2), potassium metabisulphite (KMS), calcium chloride and potassium metabisulphite (CaCl2 +KMS), and sodium chloride (NaCl) selected for treatment.. lycopene content, dehydration ratio, rehydration ratio and non-enzymatic browning in addition to moisture, sugar and titrable acidity were studied. Results show that pre-treatment with CaCl2 and NaCl increased water removal and moisture mobility in tomato slices during drying of tomatoes. Where CaCl2 used along with KMS the NEB was recorded the least compared to other treatments and the best results were obtained while using the two chemicals in combination form. Storage studies in LDPE polymeric and metalized polyesters films showed less changes in the products packed in metallized polyester pouches and even after 6 months lycopene content did not decrease more than 20% as compared to the control sample and provide extension of shelf life in acceptable condition for 6 months. In most of the quality characteristics tunnel drier samples presented better values in comparison to solar drier.

Keywords: Dehydration, Tomato powder, Lycopene, Browning

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Authors: R. Blythman, N. Jeffers, T. Persoons, D. B. Murray

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The exploitation of flow pulsation in micro- and mini-channels is a potentially useful technique for enhancing cooling of high-end photonics and electronics systems. It is thought that pulsation alters the thickness of the hydrodynamic and thermal boundary layers, and hence affects the overall thermal resistance of the heat sink. Although the fluid mechanics and heat transfer are inextricably linked, it can be useful to decouple the parameters to better understand the mechanisms underlying any heat transfer enhancement. Using two-dimensional, two-component particle image velocimetry, the current work intends to characterize the heat transfer mechanisms in pulsating flow with a mean Reynolds number of 48 by experimentally quantifying the hydrodynamics of a generic liquid-cooled channel geometry. Flows circulated through the test section by a gear pump are modulated using a controller to achieve sinusoidal flow pulsations with Womersley numbers of 7.45 and 2.36 and an amplitude ratio of 0.75. It is found that the transient characteristics of the measured velocity profiles are dependent on the speed of oscillation, in accordance with the analytical solution for flow in a rectangular channel. A large velocity overshoot is observed close to the wall at high frequencies, resulting from the interaction of near-wall viscous stresses and inertial effects of the main fluid body. The steep velocity gradients at the wall are indicative of augmented heat transfer, although the local flow reversal may reduce the upstream temperature difference in heat transfer applications. While unsteady effects remain evident at the lower frequency, the annular effect subsides and retreats from the wall. The shear rate at the wall is increased during the accelerating half-cycle and decreased during deceleration compared to steady flow, suggesting that the flow may experience both enhanced and diminished heat transfer during a single period. Hence, the thickness of the hydrodynamic boundary layer is reduced for positively moving flow during one half of the pulsation cycle at the investigated frequencies. It is expected that the size of the thermal boundary layer is similarly reduced during the cycle, leading to intervals of heat transfer enhancement.

Keywords: Heat transfer enhancement, particle image velocimetry, localized and time-resolved velocity, photonics and electronics cooling, pulsating flow, Richardson’s annular effect.

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Authors: Anjaneyulu M.V.L.R., Harikrishna M., Chenchuobulu S.

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Rapid urbanization, industrialization and population growth have led to an increase in number of automobiles that cause air pollution. It is estimated that road traffic contributes 60% of air pollution in urban areas. A case by case assessment is required to predict the air quality in urban situations, so as to evolve certain traffic management measures to maintain the air quality levels with in the tolerable limits. Calicut city in the state of Kerala, India has been chosen as the study area. Carbon Monoxide (CO) concentration was monitored at 15 links in Calicut city and air quality performance was evaluated over each link. The CO pollutant concentration values were compared with the National Ambient Air Quality Standards (NAAQS), and the CO values were predicted by using CALINE4 and IITLS and Linear regression models. The study has revealed that linear regression model performs better than the CALINE4 and IITLS models. The possible association between CO pollutant concentration and traffic parameters like traffic flow, type of vehicle, and traffic stream speed was also evaluated.

Keywords: CO pollution, Modelling, Traffic stream parameters.

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Authors: Ε. Giovanis

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In this paper we present a Adaptive Neuro-Fuzzy System (ANFIS) with inputs the lagged dependent variable for the prediction of Gross domestic Product growth rate in six countries. We compare the results with those of Autoregressive (AR) model. We conclude that the forecasting performance of neuro-fuzzy-system in the out-of-sample period is much more superior and can be a very useful alternative tool used by the national statistical services and the banking and finance industry.

Keywords: Autoregressive model, Forecasting, Gross DomesticProduct, Neuro-Fuzzy

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Authors: Kamel Hashem, David Mioduser

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This paper describes part of a project about Learningby- Modeling (LbM). Studying complex systems is increasingly important in teaching and learning many science domains. Many features of complex systems make it difficult for students to develop deep understanding. Previous research indicates that involvement with modeling scientific phenomena and complex systems can play a powerful role in science learning. Some researchers argue with this view indicating that models and modeling do not contribute to understanding complexity concepts, since these increases the cognitive load on students. This study will investigate the effect of different modes of involvement in exploring scientific phenomena using computer simulation tools, on students- mental model from the perspective of structure, behavior and function. Quantitative and qualitative methods are used to report about 121 freshmen students that engaged in participatory simulations about complex phenomena, showing emergent, self-organized and decentralized patterns. Results show that LbM plays a major role in students' concept formation about complexity concepts.

Keywords: Complexity, Educational technology, Learning by modeling, Mental models

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Authors: A. T. Eswara

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This paper analyses the unsteady, two-dimensional stagnation point flow of an incompressible viscous fluid over a flat sheet when the flow is started impulsively from rest and at the same time, the sheet is suddenly stretched in its own plane with a velocity proportional to the distance from the stagnation point. The partial differential equations governing the laminar boundary layer forced convection flow are non-dimensionalised using semi-similar transformations and then solved numerically using an implicit finitedifference scheme known as the Keller-box method. Results pertaining to the flow and heat transfer characteristics are computed for all dimensionless time, uniformly valid in the whole spatial region without any numerical difficulties. Analytical solutions are also obtained for both small and large times, respectively representing the initial unsteady and final steady state flow and heat transfer. Numerical results indicate that the velocity ratio parameter is found to have a significant effect on skin friction and heat transfer rate at the surface. Furthermore, it is exposed that there is a smooth transition from the initial unsteady state flow (small time solution) to the final steady state (large time solution).

Keywords: Forced flow, Keller-box method, Stagnation point, Stretching flat sheet, Unsteady laminar boundary layer, Velocity ratio parameter.

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Authors: Yu Zhang, Pedro Desouza

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Since big data has become substantially more accessible and manageable due to the development of powerful tools for dealing with unstructured data, people are eager to mine information from social media resources that could not be handled in the past. Sentiment analysis, as a novel branch of text mining, has in the last decade become increasingly important in marketing analysis, customer risk prediction and other fields. Scientists and researchers have undertaken significant work in creating and improving their sentiment models. In this paper, we present a concept of selecting appropriate classifiers based on the features and qualities of data sources by comparing the performances of five classifiers with three popular social media data sources: Twitter, Amazon Customer Reviews, and Movie Reviews. We introduced a couple of innovative models that outperform traditional sentiment classifiers for these data sources, and provide insights on how to further improve the predictive power of sentiment analysis. The modeling and testing work was done in R and Greenplum in-database analytic tools.

Keywords: Sentiment Analysis, Social Media, Twitter, Amazon, Data Mining, Machine Learning, Text Mining.

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Authors: Manash Pratim Sarma, Kandarpa Kumar Sarma

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A set of Artificial Neural Network (ANN) based methods for the design of an effective system of speech recognition of numerals of Assamese language captured under varied recording conditions and moods is presented here. The work is related to the formulation of several ANN models configured to use Linear Predictive Code (LPC), Principal Component Analysis (PCA) and other features to tackle mood and gender variations uttering numbers as part of an Automatic Speech Recognition (ASR) system in Assamese. The ANN models are designed using a combination of Self Organizing Map (SOM) and Multi Layer Perceptron (MLP) constituting a Learning Vector Quantization (LVQ) block trained in a cooperative environment to handle male and female speech samples of numerals of Assamese- a language spoken by a sizable population in the North-Eastern part of India. The work provides a comparative evaluation of several such combinations while subjected to handle speech samples with gender based differences captured by a microphone in four different conditions viz. noiseless, noise mixed, stressed and stress-free.

Keywords: Assamese, Recognition, LPC, Spectral, ANN.

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Authors: Hitoshi Takata, Tomohiro Hachino, Masaki Horai, Kazuo Komatsu

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In this paper, we are concerned with the design and its simulation studies of a modified extremum seeking control for nonlinear systems. A standard extremum seeking control has a simple structure, but it takes a long time to reach an optimal operating point. We consider a modification of the standard extremum seeking control which is aimed to reach the optimal operating point more speedily than the standard one. In the modification, PD acceleration term is added before an integrator making a principal control, so that it enables the objects to be regulated to the optimal point smoothly. This proposed method is applied to Monod and Williams-Otto models to investigate its effectiveness. Numerical simulation results show that this modified method can improve the time response to the optimal operating point more speedily than the standard one.

Keywords: Extremum seeking control, Monod model, Williams- Otto model, PD acceleration term, Optimal operating point.

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Authors: Z. Fang, X. P. Wang, G. Q. Lo, D. L. Kwong

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In this work, we demonstrated vertical RRAM device fabricated at the sidewall of contact hole structures for possible future 3-D stacking integrations. The fabricated devices exhibit polarity dependent bipolar resistive switching with small operation voltage of less than 1V for both set and reset process. A good retention of memory window ~50 times is maintained after 1000s voltage bias.

Keywords: Bipolar switching, non volatile memory, resistive random access memory, 3-D stacking.

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Authors: R. Jitrwung, K. Krekkeitsakul, C. Kumpidet, J. Tepkeaw, K. Jaikengdee, A. Wannajampa, W. Pathaveekongka

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Flue gas discharging from coal fired or gas combustion power plant is containing partially carbon dioxide (CO2). CO2 is a greenhouse gas which has been concerned to the global warming. Carbon Capture Storage and Utilization (CCSU) is a topic which is a tool to deal with this CO2 realization. In this paper, the Flue gas is drawn down from the chimney and filtered then it is compressed to build up the pressure until 8 barg. This compressed flue gas is sent to three stages Pressure Swing Adsorption (PSA) which is filled with activated carbon. The experiment showed the optimum adsorption pressure at 7 barg at which CO2 can be adsorbed step by step in 1st, 2nd, and 3rd stages obtaining CO2 concentration 29.8, 66.4, and 96.7% respectively. The mixed gas concentration from the last step composed of 96.7% CO2, 2.7% N2 and 0.6% O2. This mixed CO2 product gas obtained from 3 stages PSA contained high concentration of CO2 which is ready to be used for methanol synthesis. The mixed CO2 was experimented in 5-liter methanol synthesis reactor skid by 3 step processes: steam reforming, reverse water gas shift then hydrogenation. The result showed that the ratio of mixed CO2 and CH4 70/30, 50/50, 30/70 and 10/90 yielded methanol 2.4, 4.3, 5.6 and 5.3 L/day and saved 40, 30, 15, and 7% CO2 respectively. The optimum condition (positive in both methanol and CO2 consumption) was mixed CO2/CH4 ratio 47/53% by volume which yielded 4.2 L/day methanol and saved 32% CO2 compared with traditional methanol production from methane steam reforming (5 L/day) but no CO2 consumption.

Keywords: Carbon capture storage and utilization, pressure swing adsorption, reforming, methanol.

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Authors: Mark Schudeleit, Christian Sieg, Ferit Küçükay

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This paper describes how to dimension the electric components of a 48V hybrid system considering real customer use. Furthermore, it provides information about savings in energy and CO2 emissions by a customer-tailored 48V hybrid. Based on measured customer profiles, the electric units such as the electric motor and the energy storage are dimensioned. Furthermore, the CO2 reduction potential in real customer use is determined compared to conventional vehicles. Finally, investigations are carried out to specify the topology design and preliminary considerations in order to hybridize a conventional vehicle with a 48V hybrid system. The emission model results from an empiric approach also taking into account the effects of engine dynamics on emissions. We analyzed transient engine emissions during representative customer driving profiles and created emission meta models. The investigation showed a significant difference in emissions when simulating realistic customer driving profiles using the created verified meta models compared to static approaches which are commonly used for vehicle simulation.

Keywords: Customer use, dimensioning, hybrid electric vehicles, vehicle simulation, 48V hybrid system.

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Authors: Vickneswaran Jeyabalan, Andrews Samraj, Loo Chu Kiong

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The noteworthy point in the advancement of Brain Machine Interface (BMI) research is the ability to accurately extract features of the brain signals and to classify them into targeted control action with the easiest procedures since the expected beneficiaries are of disabled. In this paper, a new feature extraction method using the combination of adaptive band pass filters and adaptive autoregressive (AAR) modelling is proposed and applied to the classification of right and left motor imagery signals extracted from the brain. The introduction of the adaptive bandpass filter improves the characterization process of the autocorrelation functions of the AAR models, as it enhances and strengthens the EEG signal, which is noisy and stochastic in nature. The experimental results on the Graz BCI data set have shown that by implementing the proposed feature extraction method, a LDA and SVM classifier outperforms other AAR approaches of the BCI 2003 competition in terms of the mutual information, the competition criterion, or misclassification rate.

Keywords: Adaptive autoregressive, adaptive bandpass filter, brain machine Interface, EEG, motor imaginary.

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Authors: Ndidi F. Amulu, Godian O. Mbah, Maxwel I. Onyiah, Callistus N. Ude

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Analysis of the properties of coconut (Cocos nucifera) and its oil was evaluated in this work using standard analytical techniques. The analyses carried out include proximate composition of the fruit, extraction of oil from the fruit using different process parameters and physicochemical analysis of the extracted oil. The results showed the percentage (%) moisture, crude lipid, crude protein, ash and carbohydrate content of the coconut as 7.59, 55.15, 5.65, 7.35 and 19.51 respectively. The oil from the coconut fruit was odourless and yellowish liquid at room temperature (30oC). The treatment combinations used (leaching time, leaching temperature and solute: solvent ratio) showed significant differences (P<0.05) in the yield of oil from coconut flour. The oil yield ranged between 36.25%-49.83%. Lipid indices of the coconut oil indicated the acid value (AV) as 10.05Na0H/g of oil, free fatty acid (FFA) as 5.03%, saponification values (SV) as 183.26mgKOH-1g of oil, iodine value (IV) as 81.00 I2/g of oil, peroxide value (PV) as 5.00 ml/ g of oil and viscosity (V) as 0.002. A standard statistical package minitab version 16.0 program was used in the regression analysis and analysis of variance (ANOVA). The statistical software mentioned above was also used to generate various plots such as single effect plot, interactions effect plot and contour plot. The response or yield of oil from the coconut flour was used to develop a mathematical model that correlates the yield to the process variables studied. The maximum conditions obtained that gave the highest yield of coconut oil were leaching time of 2hrs, leaching temperature of 50oC and solute/solvent ratio of 0.05g/ml.

Keywords: Coconut, oil-extraction, optimization, physicochemical, proximate.

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Authors: Ahmed, M., Yasser A., Mahmoud H., Ahmed, A., Abdulla M. S., Nazar, S.

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Strut-and-Tie Models (STM) for the design of concrete beams, comprising of struts, ties, nodes as the basic tools, is conceptually simple, but its realization for complex concrete structure is not straightforward and depends on flow of internal forces in the structure. STM technique has won wide acceptance for deep member and shear design. STM technique is a unified approach that considers all load effects (bending, axial, shear, and torsion) simultaneously, not just applicable to shear loading only. The present study is to portray Strut-and-Tie Modeling based on Load-Transfer-Mechanisms as a unified method to analyze, design and detailing for deep and slender concrete beams. Three shear span- effective depth ratio (a/ d) are recommended for the modeling of STM elements corresponding to dominant load paths. The study also discusses the research work conduct on effective stress of concrete, tie end anchorage, and transverse reinforcement demand under different load transfer mechanism. It is also highlighted that to make the STM versatile tool for design of beams applicable to all shear spans, the effective stress of concrete and, transverse reinforcement demand, inclined angle of strut, and anchorage requirements of tie bars is required to be correlated with respect to load transfer mechanism. The country code provisions are to be modified and updated to apply for generalized design of concrete deep and slender member using load transfer mechanism based STM technique. Examples available in literature are reanalyzed with refined STM based on load transfer mechanisms and results are compared. It is concluded from the results that proposed approach will require true reinforcement demand depending on dominant force transfer action in concrete beam.

Keywords: Deep member, Load transfer mechanism, Strut-and-Tie Model, Strut, Truss.

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Authors: Patil Ashwini, Archana Thosar

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This paper addresses the mathematical model of wind energy system useful for designing fault tolerant control. To serve the demand of power, large capacity wind energy systems are vital. These systems are installed offshore where non planned service is very costly. Whenever there is a fault in between two planned services, the system may stop working abruptly. This might even lead to the complete failure of the system. To enhance the reliability, the availability and reduce the cost of maintenance of wind turbines, the fault tolerant control systems are very essential. For designing any control system, an appropriate mathematical model is always needed. In this paper, the two-mass model is modified by considering the frequent mechanical faults like misalignments in the drive train, gears and bearings faults. These faults are subject to a wear process and cause frictional losses. This paper addresses these faults in the mathematics of the wind energy system. Further, the work is extended to study the variations of the parameters namely generator inertia constant, spring constant, viscous friction coefficient and gear ratio; on the pole-zero plot which is related with the physical design of the wind turbine. Behavior of the wind turbine during drive train faults are simulated and briefly discussed.

Keywords: Mathematical model of wind energy system, stability analysis, shaft stiffness, viscous friction coefficient, gear ratio, generator inertia, fault tolerant control.

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Authors: Ali Ghaffari, Mansour Nikkhah Bahrami, Hesam Parsa

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In this paper a comprehensive model of a fossil fueled power plant (FFPP) is developed in order to evaluate the performance of a newly designed turbine follower controller. Considering the drawbacks of previous works, an overall model is developed to minimize the error between each subsystem model output and the experimental data obtained at the actual power plant. The developed model is organized in two main subsystems namely; Boiler and Turbine. Considering each FFPP subsystem characteristics, different modeling approaches are developed. For economizer, evaporator, superheater and reheater, first order models are determined based on principles of mass and energy conservation. Simulations verify the accuracy of the developed models. Due to the nonlinear characteristics of attemperator, a new model, based on a genetic-fuzzy systems utilizing Pittsburgh approach is developed showing a promising performance vis-à-vis those derived with other methods like ANFIS. The optimization constraints are handled utilizing penalty functions. The effect of increasing the number of rules and membership functions on the performance of the proposed model is also studied and evaluated. The turbine model is developed based on the equation of adiabatic expansion. Parameters of all evaluated models are tuned by means of evolutionary algorithms. Based on the developed model a fuzzy PI controller is developed. It is then successfully implemented in the turbine follower control strategy of the plant. In this control strategy instead of keeping control parameters constant, they are adjusted on-line with regard to the error and the error rate. It is shown that the response of the system improves significantly. It is also shown that fuel consumption decreases considerably.

Keywords: Attemperator, Evolutionary algorithms, Fossil fuelled power plant (FFPP), Fuzzy set theory, Gain scheduling

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Authors: Krasimir I. Ivanov, Elitsa N. Kolentsova, Dimitar Y. Dimitrov

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The development of active and stable catalysts without noble metals for low temperature oxidation of exhaust gases remains a significant challenge. The purpose of this study is to determine the influence of the preparation method on the catalytic activity of the supported copper-manganese mixed oxides in terms of VOCs oxidation. The catalysts were prepared by impregnation of γ- Al2O3 with copper and manganese nitrates and acetates and the possibilities for CO, CH3OH and dimethyl ether (DME) oxidation were evaluated using continuous flow equipment with a four-channel isothermal stainless steel reactor. Effect of the support, Cu/Mn mole ratio, heat treatment of the precursor and active component loading were investigated. Highly active alumina supported Cu-Mn catalysts for CO and VOCs oxidation were synthesized. The effect of preparation conditions on the activity behavior of the catalysts was discussed. The synergetic interaction between copper and manganese species increases the activity for complete oxidation over mixed catalysts. Type of support, calcination temperature and active component loading along with catalyst composition are important factors, determining catalytic activity. Cu/Mn molar ratio of 1:5, heat treatment at 450oC and 20 % active component loading are the best compromise for production of active catalyst for simultaneous combustion of CO, CH3OH and DME.

Keywords: Copper-manganese catalysts, Preparation methods, Exhaust gases oxidation.

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Authors: Reihaneh Ahmadzadeh Ghavidel, Mehdi Ghiafeh Davoodi

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Tomato powder has good potential as substitute of tomato paste and other tomato products. In order to protect physicochemical properties and nutritional quality of tomato during dehydration process, investigation was carried out using different drying methods and pretreatments. Solar drier and continuous conveyor (tunnel) drier were used for dehydration where as calcium chloride (CaCl2), potassium metabisulphite (KMS), calcium chloride and potassium metabisulphite (CaCl2 +KMS), and sodium chloride (NaCl) selected for treatment.. lycopene content, dehydration ratio, rehydration ratio and non-enzymatic browning in addition to moisture, sugar and titrable acidity were studied. Results show that pre-treatment with CaCl2 and NaCl increased water removal and moisture mobility in tomato slices during drying of tomatoes. Where CaCl2 used along with KMS the NEB was recorded the least compared to other treatments and the best results were obtained while using the two chemicals in combination form. Storage studies in LDPE polymeric and metalized polyesters films showed less changes in the products packed in metallized polyester pouches and even after 6 months lycopene content did not decrease more than 20% as compared to the control sample and provide extension of shelf life in acceptable condition for 6 months. In most of the quality characteristics tunnel drier samples presented better values in comparison to solar drier.

Keywords: Dehydration, Tomato powder, Lycopene, Browning

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Authors: Ali Faal Ghayoumi, Mahmoud Dehghan Nayeri, Manouchehre Ansari, Taha Raeesi

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This study aims to investigate empirically the valuerelevance of accounting information to domestic investors in Tehran stock exchange from 1999 to 2006. During the present research impacts of two factors, including positive vs. negative earnings and the firm size are considered as well. The authors used earnings per share and annual change of earnings per share as the income statement indices, and book value of equity per share as the balance sheet index. Return and Price models through regression analysis are deployed in order to test the research hypothesis. Results depicted that accounting information is value-relevance to domestic investors in Tehran Stock Exchange according to both studied models. However, income statement information has more value-relevance than the balance sheet information. Furthermore, positive vs. negative earnings and firm size seems to have significant impact on valuerelevance of accounting information.

Keywords: Value-Relevance of Accounting Information, Iranianstock exchange, Return Model, Price Model

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Authors: Pradeep Kumar, Abdul Wahid

Abstract:

Accurate software reliability prediction not only enables developers to improve the quality of software but also provides useful information to help them for planning valuable resources. This paper examines the performance of three well-known data mining techniques (CART, TreeNet and Random Forest) for predicting software reliability. We evaluate and compare the performance of proposed models with Cascade Correlation Neural Network (CCNN) using sixteen empirical databases from the Data and Analysis Center for Software. The goal of our study is to help project managers to concentrate their testing efforts to minimize the software failures in order to improve the reliability of the software systems. Two performance measures, Normalized Root Mean Squared Error (NRMSE) and Mean Absolute Errors (MAE), illustrate that CART model is accurate than the models predicted using Random Forest, TreeNet and CCNN in all datasets used in our study. Finally, we conclude that such methods can help in reliability prediction using real-life failure datasets.

Keywords: Classification, Cascade Correlation Neural Network, Random Forest, Software reliability, TreeNet.

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Authors: Zhifeng Kong

Abstract:

Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.

Keywords: Over-parameterization, Rectified Linear Units (ReLU), convergence, gradient descent, neural networks.

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