Search results for: parameters of pollution

Authors: Kooshina Koosha, Sima Habibi, Azam Talebian

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Electrospinning is a simple, versatile and widely accepted technique to produce ultra-fine fibers ranging from nanometer to micron. Recently there has been great interest in developing this technique to produce nanofibers with novel properties and functionalities. The electrospinning field is extremely broad, and consequently there have been many useful reviews discussing various aspects from detailed fiber formation mechanism to the formation of nanofibers and to discussion on a wide range of applications. On the other hand, the focus of this study is quite narrow, highlighting electrospinning parameters. This work will briefly cover the solution and processing parameters (for instance; concentration, solvent type, voltage, flow rate, distance between the collector and the tip of the needle) impacting the morphological characteristics of nanofibers, such as diameter. In this paper, a comprehensive work would be presented on the research of producing nanofibers from natural polymer entitled Gelatin.

Keywords: Electro spinning, solution parameters, process parameters, natural fiber.

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Authors: Surinder Deswal, Mahesh Pal

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An Artificial Neural Network based modeling technique has been used to study the influence of different combinations of meteorological parameters on evaporation from a reservoir. The data set used is taken from an earlier reported study. Several input combination were tried so as to find out the importance of different input parameters in predicting the evaporation. The prediction accuracy of Artificial Neural Network has also been compared with the accuracy of linear regression for predicting evaporation. The comparison demonstrated superior performance of Artificial Neural Network over linear regression approach. The findings of the study also revealed the requirement of all input parameters considered together, instead of individual parameters taken one at a time as reported in earlier studies, in predicting the evaporation. The highest correlation coefficient (0.960) along with lowest root mean square error (0.865) was obtained with the input combination of air temperature, wind speed, sunshine hours and mean relative humidity. A graph between the actual and predicted values of evaporation suggests that most of the values lie within a scatter of ±15% with all input parameters. The findings of this study suggest the usefulness of ANN technique in predicting the evaporation losses from reservoirs.

Keywords: Artificial neural network, evaporation losses, multiple linear regression, modeling.

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Authors: S. Sabzchi Asl, N. Tahouni, M. H. Panjeshahi

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Benchmarking of a process with respect to energy consumption, without accomplishing a full retrofit study, can save both engineering time and money. In order to achieve this goal, the first step is to develop a conceptual-mathematical model that can easily be applied to a group of similar processes. In this research, we have aimed to identify a set of key parameters for the model which is supposed to be used for benchmarking of combined cycle power plants. For this purpose, three similar combined cycle power plants were studied. The results showed that ambient temperature, pressure and relative humidity, number of HRSG evaporator pressure levels and relative power in part load operation are the main key parameters. Also, the relationships between these parameters and produced power (by gas/ steam turbine), gas turbine and plant efficiency, temperature and mass flow rate of the stack flue gas were investigated.

Keywords: Combined cycle power plant, energy benchmarking, modelling, Retrofit.

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Authors: Bharat Raj Singh, Onkar Singh

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This paper deals with new concept of using compressed atmospheric air as a zero pollution power source for running motorbikes. The motorbike is equipped with an air turbine in place of an internal combustion engine, and transforms the energy of the compressed air into shaft work. The mathematical modeling and performance evaluation of a small capacity compressed air driven vaned type novel air turbine is presented in this paper. The effect of isobaric admission and adiabatic expansion of high pressure air for different rotor to casing diameter ratios with respect to different vane angles (number of vanes) have been considered and analyzed. It is found that the shaft work output is optimum for some typical values of rotor / casing diameter ratios at a particular value of vane angle (no. of vanes). In this study, the maximum power is obtained as 4.5kW - 5.3kW (5.5-6.25 HP) when casing diameter is taken 100 mm, and rotor to casing diameter ratios are kept from 0.65 to 0.55. This value of output is sufficient to run motorbike.

Keywords: zero pollution, compressed air, air turbine, vane angle, rotor / casing diameter ratio

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Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

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Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: Cross-validation, decision tree, lagged variables, short-term forecasting.

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Authors: Govindaraju.M, Ganeshkumar.R.S, Suganthi.P, Muthukumaran.V.R, Visvanathan.P

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The present study was conducted to investigate the response of plants exposed to lignite-based thermal power plant emission. For this purpose, five plant species were collected from 1.0 km distance (polluted site) and control plants were collected from 20.0 km distance (control site) to thermal power plant. The common tree species Cassia siamea Lamk., Polyalthia longifolia. Sonn, Acacia longifolia (Andrews) Wild., Azadirachta indica A.Juss, Ficus religiosa L. were selected as test plants. Photosynthetic pigments changes (chlorophyll a, chlorophyll b and carotenoids) and rubisco enzyme modifications were studied. Reduction was observed in the photosynthetic pigments of plants growing in polluted site and also large sub unit of the rubisco enzyme was degraded in Azadirachta indica A. Juss collected from polluted site.

Keywords: Air pollution, Lignite-based thermal power plant, Photosynthetic pigments, Rubisco enzyme.

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Authors: Mahmoud Zarrini, R. N. Pralhad

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In this paper, mathematical modeling of detonation in the ground is studied. Estimation of flow parameters such as velocity, maximum velocity, acceleration, maximum acceleration, shock pressure as a result of an explosion in the ground have been computed in an appropriate dynamic model approach. The variation of these parameters with the diameter of detonation place (L), density of earth or stone (¤ü), time decay of detonation (T), peak pressure (Pm), and time (t) have been analyzed. The model has been developed from the concept of underwater explosions [Refs. [1]-[3]] with appropriate changes to the present model requirements.

Keywords: Shock velocity, detonation, shock acceleration, shock pressure.

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Authors: T. Hacib, M. R. Mekideche, N. Ferkha

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This paper presents an approach which is based on the use of supervised feed forward neural network, namely multilayer perceptron (MLP) neural network and finite element method (FEM) to solve the inverse problem of parameters identification. The approach is used to identify unknown parameters of ferromagnetic materials. The methodology used in this study consists in the simulation of a large number of parameters in a material under test, using the finite element method (FEM). Both variations in relative magnetic permeability and electrical conductivity of the material under test are considered. Then, the obtained results are used to generate a set of vectors for the training of MLP neural network. Finally, the obtained neural network is used to evaluate a group of new materials, simulated by the FEM, but not belonging to the original dataset. Noisy data, added to the probe measurements is used to enhance the robustness of the method. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.

Keywords: Inverse problem, MLP neural network, parametersidentification, FEM.

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Authors: Y. M. Al-Wahaibi, S. N. Al-Bahry, A. E. Elshafie, A. S. Al-Bemani, S. J. Joshi, A. K. Al-Bahri

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Crude oil is a major source of global energy. The major problem is its widespread use and demand resulted is in increasing environmental pollution. One associated pollution problem is ‘oil spills’. Oil spills can be remediated with the use of chemical dispersants, microbial biodegradation and microbial metabolites such as biosurfactants. Four different minimal salt media for biosurfactant production by Bacillus isolated from oil contaminated sites from Oman were screened. These minimal salt media were supplemented with either glucose or sucrose as a carbon source. Among the isolates, W16 and B30 produced the most active biosurfactants. Isolate W16 produced better biosurfactant than the rest, and reduced surface tension (ST) and interfacial tension (IFT) to 25.26mN/m and 2.29mN/m respectively within 48h which are characteristics for removal of oil in contaminated sites. Biosurfactant was produced in bulk and extracted using acid precipitation method. Thin Layer Chromatography (TLC) of acid precipitate biosurfactant revealed two concentrated bands. Further studies of W16 biosurfactant in bioremediation of oil spills are recommended.

Keywords: Oil contamination, remediation, Bacillus spp, biosurfactant, surface tension, interfacial tension.

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Authors: P.Saravanan, Narayanan .C.K., P.V.S.S Prakash, Prabhakara Rao .G.V

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Video Mosaicing is the stitching of selected frames of a video by estimating the camera motion between the frames and thereby registering successive frames of the video to arrive at the mosaic. Different techniques have been proposed in the literature for video mosaicing. Despite of the large number of papers dealing with techniques to generate mosaic, only a few authors have investigated conditions under which these techniques generate good estimate of motion parameters. In this paper, these techniques are studied under different videos, and the reasons for failures are found. We propose algorithms with incorporation of outlier removal algorithms for better estimation of motion parameters.

Keywords: Motion parameters, Outlier removal algorithms, Registering , and Video Mosaicing.

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Authors: A. M. N. El-Khoja, A. F. Ashour, J. Abdalhmid, X. Dai, A. Khan

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In recent years, waste tyre problem is considered as one of the most crucial environmental pollution problems facing the world. Thus, reusing waste rubber crumb from recycled tyres to develop highly damping concrete is technically feasible and a viable alternative to landfill or incineration. The utilization of waste rubber in concrete generally enhances the ductility, toughness, thermal insulation, and impact resistance. However, the mechanical properties decrease with the amount of rubber used in concrete. The aim of this paper is to develop artificial neural network (ANN) models to predict the compressive strength of rubberised concrete (RuC). A trained and tested ANN was developed using a comprehensive database collected from different sources in the literature. The ANN model developed used 5 input parameters that include: coarse aggregate (CA), fine aggregate (FA), w/c ratio, fine rubber (Fr), and coarse rubber (Cr), whereas the ANN outputs were the corresponding compressive strengths. A parametric study was also conducted to study the trend of various RuC constituents on the compressive strength of RuC.

Keywords: Rubberized concrete, compressive strength, artificial neural network, prediction.

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Authors: T. Patrice Nna Nna, S. Ndjakomo Essiane, S. Pérabi Ngoffé, F. Amigue Fissou

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This paper deals with the harmonic decontamination of current in an electrical grid by an active shunt filter in order to improve power quality. The contribution of this paper is mainly based on the proposal of a control strategy for an active filter based on Duty Cycle Modulation (DCM). First, three-monophase method is applied for the identification of disturbing currents. A Simulink model of this method is given for one phase of the grid. Secondly, two orders were designed: the first one is the Hysteresis Control and the second one is the DCM Control. Finally, a comparative study of the two controls was performed. The results obtained show a significant improvement in the rate of harmonic distortion for both controls. The harmonic distortion for the Hysteresis control is limited by the non-controllability of the switching frequencies of the inverter's switches and reduces the harmonic distortion rate (THD) to 3.12% as opposed to the DCM control which limits the THD to 2.82% which makes it better.

Keywords: Harmonic pollution, shunt active filter, hysteresis, Duty Cycle Modulation.

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Authors: Shivakumar, G. S. Vijay, P. Srinivas Pai, B. R. Shrinivasa Rao

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In the present study, RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tex and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: Radial Basis Function networks, emissions, Performance parameters, Fuzzy c means.

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Authors: Farhad Kolahan, Mehdi Heidari

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Gas Metal Arc Welding (GMAW) processes is an important joining process widely used in metal fabrication industries. This paper addresses modeling and optimization of this technique using a set of experimental data and regression analysis. The set of experimental data has been used to assess the influence of GMAW process parameters in weld bead geometry. The process variables considered here include voltage (V); wire feed rate (F); torch Angle (A); welding speed (S) and nozzle-to-plate distance (D). The process output characteristics include weld bead height, width and penetration. The Taguchi method and regression modeling are used in order to establish the relationships between input and output parameters. The adequacy of the model is evaluated using analysis of variance (ANOVA) technique. In the next stage, the proposed model is embedded into a Simulated Annealing (SA) algorithm to optimize the GMAW process parameters. The objective is to determine a suitable set of process parameters that can produce desired bead geometry, considering the ranges of the process parameters. Computational results prove the effectiveness of the proposed model and optimization procedure.

Keywords: Weld Bead Geometry, GMAW welding, Processparameters Optimization, Modeling, SA algorithm

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Authors: C. D. Naiju, K. Annamalai, Siva Prasad Darla, Y. Murali Krishna

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This work presents the results of a study carried out to determine the sliding wear behavior and its effect on the process parameters of components manufactured by direct metal laser sintering (DMLS). A standard procedure and specimen had been used in the present study to find the wear behavior. Using Taguchi-s experimental technique, an orthogonal array of modified L8 had been developed. Sliding wear testing using pin-on-disk machine was carried out and analysis of variance (ANOVA) technique was used to investigate the effect of process parameters and to identify the main process parameter that influences the properties of wear behavior on the DMLS components. It has been found that part orientation, one of the selected process parameter had more influence on wear as compared to other selected process parameters.

Keywords: ANOVA, DMLS, Taguchi, Wear.

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Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

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The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model.

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Authors: M.R.Shabgard, R.M.Shotorbani

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FW4 is a newly developed hot die material widely used in Forging Dies manufacturing. The right selection of the machining conditions is one of the most important aspects to take into consideration in the Electrical Discharge Machining (EDM) of FW4. In this paper an attempt has been made to develop mathematical models for relating the Material Removal Rate (MRR), Tool Wear Ratio (TWR) and surface roughness (Ra) to machining parameters (current, pulse-on time and voltage). Furthermore, a study was carried out to analyze the effects of machining parameters in respect of listed technological characteristics. The results of analysis of variance (ANOVA) indicate that the proposed mathematical models, can adequately describe the performance within the limits of the factors being studied.

Keywords: Electrical Discharge Machining (EDM), linearregression technique, Response Surface Methodology (RSM)

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Authors: Jieh-Shian Young, Chan Wei Hsu

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This paper mainly studies the analyses of parameters in the intersection collision avoidance (ICA) system based on the radar sensors. The parameters include the positioning errors, the repeat period of the radar sensor, the conditions of potential collisions of two cross-path vehicles, etc. The analyses of the parameters can provide the requirements, limitations, or specifications of this ICA system. In these analyses, the positioning errors will be increased as the measured vehicle approach the intersection. In addition, it is not necessary to implement the radar sensor in higher position since the positioning sensitivities become serious as the height of the radar sensor increases. A concept of the safety buffer distances for front and rear of the measured vehicle is also proposed. The conditions for potential collisions of two cross-path vehicles are also presented to facilitate the computation algorithm.

Keywords: Intersection Collision Avoidance (ICA), Positioning Errors, Radar Sensors, Sensitivity of Positioning.

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Authors: Erna Astuti, Supranto, Rochmadi, Agus Prasetya

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Biodiesel production from vegetable oil will produce glycerol as by-product about 10% of the biodiesel production. The amount of glycerol that was produced needed alternative way to handling immediately so as to not become the waste that polluted environment. One of the solutions was to process glycerol to polyglycidyl nitrate (PGN). PGN is synthesized from glycerol by three-step reactions i.e. nitration of glycerol, cyclization of 13- dinitroglycerine and polymerization of glycosyl nitrate. Optimum condition of nitration of glycerol with nitric acid has not been known. Thermodynamic feasibility should be done before run experiments in the laboratory. The aim of this study was to determine the parameters those affect nitration of glycerol and nitric acid and chose the operation condition. Many parameters were simulated to verify its possibility to experiment under conditions which would get the highest conversion of 1, 3-dinitroglycerine and which was the ideal condition to get it. The parameters that need to be studied to obtain the highest conversion of 1, 3-dinitroglycerine were mol ratio of nitric acid/glycerol, reaction temperature, mol ratio of glycerol/dichloromethane and pressure. The highest conversion was obtained in the range of mol ratio of nitric acid /glycerol between 2/1 – 5/1, reaction temperature of 5-25oC and pressure of 1 atm. The parameters that need to be studied further to obtain the highest conversion of 1.3 DNG are mol ratio of nitric acid/glycerol and reaction temperature.

Keywords: Nitration, glycerol, thermodynamic, optimum condition.

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Authors: N. Arulanand, P. Dhara

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Optimizing the parameters in the controller plays a vital role in the control theory and its applications. Optimizing the PID parameters is finding out the best value from the feasible solutions. Finding the optimal value is an optimization problem. Inverted Pendulum is a very good platform for control engineers to verify and apply different logics in the field of control theory. It is necessary to find an optimization technique for the controller to tune the values automatically in order to minimize the error within the given bounds. In this paper, the algorithmic concepts of Harmony search (HS) and Genetic Algorithm (GA) have been analyzed for the given range of values. The experimental results show that HS performs well than GA.

Keywords: Genetic Algorithm, Harmony Search Algorithm, Inverted Pendulum, PID Controller.

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Authors: M. Cristea, F. Paran, P. Delhomme

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Eco-driving allows the driver to optimize his/her behaviour in order to achieve several types of benefits: reducing pollution emissions, increasing road safety, and fuel saving. One of the main rules for adopting eco-driving is to anticipate the traffic events by avoiding strong acceleration or braking and maintaining a steady speed when possible. Therefore, drivers have to comply with speed limits and time headway. The present study explored the role of three types of motivation and social norms in predicting French drivers- intentions to comply with speed limits and time headway as eco-driving practices as well as examine the variations according to gender and age. 1234 drivers with ages between 18 and 75 years old filled in a questionnaire which was presented as part of an online survey aiming to better understand the drivers- road habits. It included items assessing: a) behavioural intentions to comply with speed limits and time headway according to three types of motivation: reducing pollution emissions, increasing road safety, and fuel saving, b) subjective and descriptive social norms regarding the intention to comply with speed limits and time headway, and c) sociodemographical variables. Drivers expressed their intention to frequently comply with speed limits and time headway in the following 6 months; however, they showed more intention to comply with speed limits as compared to time headway regardless of the type of motivation. The subjective injunctive norms were significantly more important in predicting drivers- intentions to comply with speed limits and time headway as compared to the descriptive norms. In addition, the most frequently reported type of motivation for complying with speed limits and time headway was increasing road safety followed by fuel saving and reducing pollution emissions, hence underlining a low motivation to practice eco-driving. Practical implications of the results are discussed.

Keywords: Eco-driving, social norms, speed limits, time headway.

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Authors: N. C. Sarkar, A. Bhaskar, Z. Zheng

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The driving behavior in area-based (i.e., non-lane based) traffic is induced by the presence of other individuals in the choice space from the driver’s visual perception area. The driving behavior of a subject vehicle is constrained by the potential leaders and leaders are frequently changed over time. This paper is to determine a stochastic model for a parameter of modified intelligent driver model (MIDM) in area-based traffic (as in developing countries). The parametric and non-parametric distributions are presented to fit the parameters of MIDM. The goodness of fit for each parameter is measured in two different ways such as graphically and statistically. The quantile-quantile (Q-Q) plot is used for a graphical representation of a theoretical distribution to model a parameter and the Kolmogorov-Smirnov (K-S) test is used for a statistical measure of fitness for a parameter with a theoretical distribution. The distributions are performed on a set of estimated parameters of MIDM. The parameters are estimated on the real vehicle trajectory data from India. The fitness of each parameter with a stochastic model is well represented. The results support the applicability of the proposed modeling for parameters of MIDM in area-based traffic flow simulation.

Keywords: Area-based traffic, car-following model, micro-simulation, stochastic modeling.

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Authors: Imanda H. Pradana, Tillana Adilaviana, Christine Pretty Ballerena

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Ever since industrial revolution began, our ecosystem has changed. And indeed, the negatives outweigh the positives. Industrial waste usually released into all kinds of body of water, such as river or sea. Tempeh waste is one example of waste that carries many hazardous and unwanted substances that will affect the surrounding environment. Tempeh is a popular fermented food in Asia which is rich in nutrients and active substances. Tempeh liquid waste- in particular- can cause an air pollution, and if penetrates through the soil, it will contaminates ground-water, making it unavailable for the water to be consumed. Moreover, bacteria will thrive within the polluted water, which often responsible for causing many kinds of diseases. The treatment used for this chemical waste is biological treatment such as constructed wetland and activated sludge. These kinds of treatment are able to reduce both physical and chemical parameters altogether such as temperature, TSS, pH, BOD, COD, NH3-N, NO3-N, and PO4-P. These treatments are implemented before the waste is released into the water. The result is a comparation between constructed wetland and activated sludge, along with determining which method is better suited to reduce the physical and chemical subtances of the waste.

Keywords: activated sludge, constructed wetland, waste, watertreatment

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Authors: Bai Wei, Kong Ling-Wei, Guo Ai-Guo

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This experiment discusses the effects of fracture parameters such as depth, length, width, angle and the number of the fracture to the conductance properties of laterite using the DUK-2B digital electrical measurement system combined with the method of simulating the fractures. The results of experiment show that the changes of fracture parameters produce effects to the conductance properties of laterite. There is a clear degressive period of the conductivity of laterite during increasing the depth, length, width, or the angle and the quantity of fracture gradually. When the depth of fracture exceeds the half thickness of the soil body, the conductivity of laterite shows evidently non-linear diminishing pattern and the amplitude of decrease tends to increase. The length of fracture has fewer effects than the depth to the conductivity. When the width of fracture reaches some fixed values, the change of the conductivity is less sensitive to the change of the width, and at this time, the conductivity of laterite maintains at a stable level. When the angle of fracture is less than 45°, the decrease of the conductivity is more clearly as the angle increases. But when angle is more than 45°, change of the conductivity is relatively gentle as the angle increases. The increasing quantity of the fracture causes the other fracture parameters having great impact on the change of conductivity. When moisture content and temperature were unchanged, depth and angle of fractures are the major factors affecting the conductivity of laterite soil; quantity, length, and width are minor influencing factors. The sensitivity of fracture parameters affect conductivity of laterite soil is: depth >angles >quantity >length >width.

Keywords: laterite, fracture parameters, conductance properties, conductivity, uniform design, sensitivity analysis

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Authors: Jin Sun, Hongbin Gu

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An important step in three-dimensional reconstruction and computer vision is camera calibration, whose objective is to estimate the intrinsic and extrinsic parameters of each camera. In this paper, two linear methods based on the different planes are given. In both methods, the general plane is used to replace the calibration object with very good precision. In the first method, after controlling the camera to undergo five times- translation movements and taking pictures of the orthogonal planes, a set of linear constraints of the camera intrinsic parameters is then derived by means of homography matrix. The second method is to get all camera parameters by taking only one picture of a given radius circle. experiments on simulated data and real images,indicate that our method is reasonable and is a good supplement to camera calibration.

Keywords: camera calibration, 3D reconstruction, computervision

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Authors: Swapnil Singhal, Santosh Kumar Singh

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The emerging Cognitive Radio is combo of both the technologies i.e. Radio dynamics and software technology. It involve wireless system with efficient coding, designing, and making them artificial intelligent to take the decision according to the surrounding environment and adopt themselves accordingly, so as to deliver the best QoS. This is the breakthrough from fixed hardware and fixed utilization of the spectrum. This software-defined approach of research is centralized at user-definition and application driven model, various software method are used for the optimization of the wireless communication. This paper focused on the Spectrum allocation technique using genetic algorithm GA to evolve radio, represented by chromosomes. The chromosomes gene represents the adjustable parameters in given radio and by using GA, evolving over the generations, the optimized set of parameters are evolved, as per the requirement of user and availability of the spectrum, in our prototype the gene consist of 6 different parameters, and the best set of parameters are evolved according to the application need and availability of the spectrum holes and thus maintaining best QoS for user, simultaneously maintaining licensed user rights. The analyzing tool Matlab is used for the performance of the prototype.

Keywords: ASDR, Cognitive Radio, QoS, Spectrum.

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Authors: Wassila Kiamouche, Malek Benslama

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In order to derive important parameters concerning mobile subscriber MS with ongoing calls in Low Earth Orbit Mobile Satellite Systems LEO MSSs, a positioning system had to be integrated into MSS in order to localize mobile subscribers MSs and track them during the connection. Such integration is regarded as a complex implementation. We propose in this paper a novel method based on advantages of mobility model of Low Earth Orbit Mobile Satellite System LEO MSS called Evaluation Parameters Method EPM which allows for such systems the evaluation of different information concerning a MS with a call in progress even if its location is unknown.

Keywords: Cellular layout, LEO mobile satellite system, mobilitymodel, positioning system.

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Authors: Violina R. Angelova, Sava G. Tabakov, Aleksander B. Peltekov, Krasimir I. Ivanov

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A field study was conducted to evaluate the chemical composition and quality of the Aronia fruits, as well as the possibilities of Aronia cultivation on soils contaminated with heavy metals. The experiment was performed on an agricultural field contaminated by the Non-Ferrous-Metal Works (NFMW) near Plovdiv, Bulgaria. The study included four varieties of Aronia; Aron variety, Hugin variety, Viking variety and Nero variety. The Aronia was cultivated according to the conventional technology on areas at a different distance from the source of pollution NFMW- Plovdiv (1 km, 3.5 km, and 15 km). The concentrations of macroelements, microelements, and heavy metals in Aronia fruits were determined. The dry matter content, ash, sugars, proteins, and fats were also determined. Aronia is a crop that is tolerant to heavy metals and can successfully be grown on soils contaminated with heavy metals. The increased content of heavy metals in the soil leads to less absorption of the nutrients (Ca, Mg and P) in the fruit of the Aronia. Soil pollution with heavy metals does not affect the quality of the Aronia fruit varieties.

Keywords: Aronia, chemical composition, fruits, quality.

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Authors: Touba Amirazodi

Abstract:

Rapid process of urbanism development has increased the demand for some infrastructures such as supplying potable water, electricity network and transportation facilities and etc. Nonefficiency of the existing system with parallel managements of urban traffic management has increased the gap between supply and demand of traffic facilities. A sustainable transport system requires some activities more important than air pollution control, traffic or fuel consumption reduction and the studies show that there is no unique solution for solving complicated transportation problems and solving such a problem needs a comprehensive, dynamic and reliable mechanism. Sustainable transport management considers the effects of transportation development on economic efficiency, environmental issues, resources consumption, land use and social justice and helps reduction of environmental effects, increase of transportation system efficiency as well as improvement of social life and aims to enhance efficiency, goods transportation, provide services with minimum access problems that cannot be realized without reorganization of strategies, policies and plans.

Keywords: Sustainable Urban Transport, Environment, Social Justice, Air Pollution

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Authors: Md. Anayet U. Patwari, Mohammad Ahsan Habib, Md. Tanzib Ehsan, Md Golam Ahnaf, Md. S. I. Chowdhury

Abstract:

Surface roughness is one of the key quality parameters of the finished product. During any machining operation, high temperatures are generated at the tool-chip interface impairing surface quality and dimensional accuracy of products. Cutting fluids are generally applied during machining to reduce temperature at the tool-chip interface. However, usages of cutting fluids give rise to problems such as waste disposal, pollution, high cost, and human health hazard. Researchers, now-a-days, are opting towards dry machining and other cooling techniques to minimize use of coolants during machining while keeping surface roughness of products within desirable limits. In this paper, a concept of using peltier cooling effects during aluminium milling operation has been presented and adopted with an aim to improve surface roughness of the machined surface. Experimental evidence shows that peltier cooling effect provides better surface roughness of the machined surface compared to dry machining.

Keywords: Aluminium, surface roughness, Peltier cooling effect, milling operation.

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