Search results for: Environmental Parameters

Authors: Rinku Dhanker, Suman Chaudhary, Tanvi Bhatia, Sneh Goyal

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Municipal Solid Waste (MSW), being a rich source of organic materials, can be used for agricultural applications as an important source of nutrients for soil and plants. This is also an alternative beneficial management practice for MSW generated in developing countries. In the present study, MSW treated soil samples from last four to six years at farmer’s field in Rohtak and Gurgaon states (Haryana, India) were collected. The samples were analyzed for all-important agricultural parameters and compared with the control untreated soil samples. The treated soil at farmer’s field showed increase in total N by 48 to 68%, P by 45.7 to 51.3%, and K by 60 to 67% compared to untreated soil samples. Application of sewage sludge at different sites led to increase in microbial biomass C by 60 to 68% compared to untreated soil. There was significant increase in total Cu, Cr, Ni, Fe, Pb, and Zn in all sewage sludge amended soil samples; however, concentration of all the metals were still below the current permitted (EU) limits. To study the adverse effect of heavy metals accumulation on various soil microbial activities, the sewage sludge samples (from wastewater treatment plant at Gurgaon) were artificially contaminated with heavy metal concentration above the EU limits. They were then applied to soil samples with different rates (0.5 to 4.0%) and incubated for 90 days under laboratory conditions. The samples were drawn at different intervals and analyzed for various parameters like pH, EC, total N, P, K, microbial biomass C, carbon mineralization, and diethylenetriaminepentaacetic acid (DTPA) exactable heavy metals. The results were compared to the uncontaminated sewage sludge. The increasing level of sewage sludge from 0.5 to 4% led to build of organic C and total N, P and K content at the early stages of incubation. But, organic C was decreased after 90 days because of decomposition of organic matter. Biomass production was significantly increased in both contaminated and uncontaminated sewage soil samples, but also led to slight increases in metal accumulation and their bioavailability in soil. The maximum metal concentrations were found in treatment with 4% of contaminated sewage sludge amendment.

Keywords: Heavy metals, municipal sewage sludge, sustainable agriculture, soil fertility, quality.

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Authors: P. Kowalska, P. Gabka, K. Kamieniarz, M. Kamieniarz, W. Stryla, P. Guzik, T. Krauze

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We have developed a computer program consisting of 6 subtests assessing the children hand dexterity applicable in the rehabilitation medicine. We have carried out a normative study on a representative sample of 285 children aged from 7 to 15 (mean age 11.3) and we have proposed clinical standards for three age groups (7-9, 9-11, 12-15 years). We have shown statistical significance of differences among the corresponding mean values of the task time completion. We have also found a strong correlation between the task time completion and the age of the subjects, as well as we have performed the test-retest reliability checks in the sample of 84 children, giving the high values of the Pearson coefficients for the dominant and non-dominant hand in the range 0.740.97 and 0.620.93, respectively. A new MATLAB-based programming tool aiming at analysis of cardiologic RR intervals and blood pressure descriptors, is worked out, too. For each set of data, ten different parameters are extracted: 2 in time domain, 4 in frequency domain and 4 in Poincaré plot analysis. In addition twelve different parameters of baroreflex sensitivity are calculated. All these data sets can be visualized in time domain together with their power spectra and Poincaré plots. If available, the respiratory oscillation curves can be also plotted for comparison. Another application processes biological data obtained from BLAST analysis.

Keywords: Biomedical data base processing, Computer software, Hand dexterity, Heart rate and blood pressure variability.

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Authors: Jameela Ali Alkrimi, Loay E. George, Azizah Suliman, Abdul Rahim Ahmad, Karim Al-Jashamy

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Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. Anemia is a lack of RBCs is characterized by its level compared to the normal hemoglobin level. In this study, a system based image processing methodology was developed to localize and extract RBCs from microscopic images. Also, the machine learning approach is adopted to classify the localized anemic RBCs images. Several textural and geometrical features are calculated for each extracted RBCs. The training set of features was analyzed using principal component analysis (PCA). With the proposed method, RBCs were isolated in 4.3secondsfrom an image containing 18 to 27 cells. The reasons behind using PCA are its low computation complexity and suitability to find the most discriminating features which can lead to accurate classification decisions. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network RBFNN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained within short time period, and the results became better when PCA was used.

Keywords: Red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC.

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Authors: M. E. Silva, I. Brás

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To study the influence of different organic amendments on the quality of poultry manure compost, three pilot composting trials were carried out with different mixes: poultry manure/carcasse meal/ashes/grape pomace (Pile 1), poultry manure/ cellulosic sludge (Pile 2) and poultry manure (Pile 3). For all piles, wood chips were applied as bulking agent. The process was monitored, over time, by evaluating standard physical and chemical parameters, such as, pH, electric conductivity, moisture, organic matter and ash content, total carbon and total nitrogen content, carbon/nitrogen ratio (C/N) and content in mineral elements. Piles 1 and 2 reached a thermophilic phase, however having different trends. Pile 1 reached this phase earlier than Pile 2. For both, the pH showed a slight alkaline character and the electric conductivity was lower than 2 mS/cm. Also, the initial C/N value was 22 and reached values lower than 15 at the end of composting process. The total N content of the Pile 1 increased slightly during composting, in contrast with the others piles. At the end of composting process, the phosphorus content ranged between 54 and 236 mg/kg dry matter, for Pile 2 and 3, respectively. Generally, the Piles 1 and 3 exhibited similar heavy metals content. This study showed that organic amendments can be used as carbon source, given that the final composts presented parameters within the range of those recommended in the 2^nd Draft of EU regulation proposal (DG Env.A.2 2001) for compost quality.

Keywords: Co-composting, compost quality, organic amendments, poultry manure.

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Authors: S. Deswal, M. Pal

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Presently various computational techniques are used in modeling and analyzing environmental engineering data. In the present study, an intra-comparison of polynomial and radial basis kernel functions based on Support Vector Regression and, in turn, an inter-comparison with Multi Linear Regression has been attempted in modeling mass transfer capacity of vertical (θ = 90O) and inclined (θ multiple plunging jets (varying from 1 to 16 numbers). The data set used in this study consists of four input parameters with a total of eighty eight cases, forty four each for vertical and inclined multiple plunging jets. For testing, tenfold cross validation was used. Correlation coefficient values of 0.971 and 0.981 along with corresponding root mean square error values of 0.0025 and 0.0020 were achieved by using polynomial and radial basis kernel functions based Support Vector Regression respectively. An intra-comparison suggests improved performance by radial basis function in comparison to polynomial kernel based Support Vector Regression. Further, an inter-comparison with Multi Linear Regression (correlation coefficient = 0.973 and root mean square error = 0.0024) reveals that radial basis kernel functions based Support Vector Regression performs better in modeling and estimating mass transfer by multiple plunging jets.

Keywords: Mass transfer, multiple plunging jets, polynomial and radial basis kernel functions, Support Vector Regression.

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Authors: Zsolt Szilvágyi, Jakub Panuska, Orsolya Kegyes-Brassai, Ákos Wolf, Péter Tildy, Richard P. Ray

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Near-surface loose sediments and local ground conditions in general have a major influence on seismic response of structures. It is a difficult task to model ground behavior in seismic soil-structure-foundation interaction problems, fully account for them in seismic design of structures, or even properly consider them in seismic hazard assessment. In this study, we focused on applying seismic soil investigation methods, used for determining soil stiffness and damping properties, to response analysis used in seismic design. A site in Budapest, Hungary was investigated using Multichannel Analysis of Surface Waves, Seismic Cone Penetration Tests, Bender Elements, Resonant Column and Torsional Shear tests. Our aim was to compare the results of the different test methods and use the resulting soil properties for 1D ground response analysis. Often in practice, there are little-to no data available on dynamic soil properties and estimated parameters are used for design. Therefore, a comparison is made between results based on estimated parameters and those based on detailed investigations. Ground response results are also compared to Eurocode 8 design spectra.

Keywords: Bender element, ground response analysis, MASW, resonant column test, SCPT, torsional shear test.

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Authors: Racholsan Raj Nirmal, B. S. V. Patnaik, R. Jayaganthan

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The deformation behaviour of additively manufactured AlSi10Mg alloy under low strains, high strain rates and elevated temperature conditions is essential to analyse and predict its response against dynamic loading such as impact and thermomechanical fatigue. The constitutive relation of Johnson-Cook is used to capture the strain rate sensitivity and thermal softening effect in AlSi10Mg alloy. Johnson-Cook failure model is widely used for exploring damage mechanics and predicting the fracture in many materials. In this present work, Johnson-Cook material and damage model parameters for additively manufactured AlSi10Mg alloy have been determined numerically from four types of uniaxial tensile test. Three different uniaxial tensile tests with dynamic strain rates (0.1, 1, 10, 50, and 100 s^-1) and elevated temperature tensile test with three different temperature conditions (450 K, 500 K and 550 K) were performed on 3D printed AlSi10Mg alloy in ABAQUS/Explicit. Hexahedral elements are used to discretize tensile specimens and fracture energy value of 43.6 kN/m was used for damage initiation. Levenberg Marquardt optimization method was used for the evaluation of Johnson-Cook model parameters. It was observed that additively manufactured AlSi10Mg alloy has shown relatively higher strain rate sensitivity and lower thermal stability as compared to the other Al alloys.

Keywords: ABAQUS, additive manufacturing, AlSi10Mg, Johnson-Cook model.

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Authors: M. Linek

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This article presents the comparison of selected evaluation methods regarding microstructure modification of hardened cement concrete intended for airfield pavements. Basic test results were presented for two pavement quality concrete lots. Analysis included standard concrete used for airfield pavements and modern material solutions based on concrete composite modification. In case of basic grain size distribution of concrete cement CEM I 42,5HSR NA, fine aggregate and coarse aggregate fractions in the form of granite chippings, water and admixtures were considered. In case of grain size distribution of modified concrete, the use of modern modifier as substitute of fine aggregate was suggested. Modification influence on internal concrete structure parameters using scanning electron microscope was defined. Obtained images were compared to the results obtained using computed tomography. Opportunity to use this type of equipment for internal concrete structure diagnostics and an attempt of its parameters evaluation was presented. Obtained test results enabled to reach a conclusion that both methods can be applied for pavement quality concrete diagnostics, with particular purpose of airfield pavements.

Keywords: Scanning electron microscope, computed tomography, cement concrete, airfield pavements.

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Authors: Pinki Sharma, Himanshu Joshi

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Distillery spentwash contains high chemical oxygen demand (COD), biological oxygen demand (BOD), color, total dissolved solids (TDS) and other contaminants even after biological treatment. The effluent can’t be discharged as such in the surface water bodies or land without further treatment. Reverse osmosis (RO) treatment plants have been installed in many of the distilleries at tertiary level in many of the distilleries in India, but are not properly working due to fouling problem which is caused by the presence of high concentration of organic matter and other contaminants in biologically treated spentwash. In order to make the membrane treatment a proven and reliable technology, proper pre-treatment is mandatory. In the present study, ultra-filtration (UF) for pretreatment of RO at tertiary stage has been performed. Operating parameters namely initial pH (pHo: 2–10), trans-membrane pressure (TMP: 4-20 bars) and temperature (T: 15-43°C) were used for conducting experiments with UF system. Experiments were optimized at different operating parameters in terms of COD, color, TDS and TOC removal by using response surface methodology (RSM) with central composite design. The results showed that removal of COD, color and TDS was 62%, 93.5% and 75.5% respectively, with UF, at optimized conditions with increased permeate flux from 17.5 l/m2/h (RO) to 38 l/m2/h (UF-RO). The performance of the RO system was greatly improved both in term of pollutant removal as well as water recovery.

Keywords: Bio-digested distillery spentwash, reverse osmosis, Response surface methodology, ultra-filtration.

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Authors: J. Fenianos, C. Khater, D. Brouillet

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Ecological projects are often faced with reluctance from local communities hosting the project, especially when this project involves variation from preset ideas or classical practices. This paper aims at appreciating the contribution of environmental psychology through cognitive flexibility exercises to improve the acceptability of local communities in adopting more ecological rehabilitation scenarios. The study is based on a quarry site located in Bekaa- Lebanon. Four groups were considered with different levels of involvement, as follows: Group 1 is Training (T) – 50 hours of on-site training over 8 months, Group 2 is Awareness (A) – 2 hours of awareness raising session, Group 3 is Flexibility (F) – 2 hours of flexibility exercises and Group 4 is the Control (C). The results show that individuals in Group 3 (F) who followed flexibility sessions accept comparably the ecological rehabilitation option over the more classical one. This is also the case for the people in Group 1 (T) who followed a more time-demanding “on-site training”. Another experience was conducted on a second quarry site combining flexibility with awareness-raising. This research confirms that it is possible to reduce resistance to change thanks to a limited in-time intervention using cognitive flexibility. This methodological approach could be transferable to other environmental problems involving local communities and changes in preset perceptions.

Keywords: Acceptability, ecological restoration, environmental psychology, Lebanon, local communities, resistance to change.

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Authors: Vinod Kumar, Surjit Angra

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The objective of this theoretical study is to develop simple design formulas for the prediction of minimum film thickness and maximum mean film temperature rise in lightly loaded high-speed rolling/sliding lubricated elliptical contacts incorporating starvation effect. Herein, the reported numerical analysis focuses on thermoelastohydrodynamically lubricated rolling/sliding elliptical contacts, considering the Newtonian rheology of lubricant for wide range of operating parameters, namely load characterized by Hertzian pressure (PH = 0.01 GPa to 0.10 GPa), rolling speed (>10 m/s), slip parameter (S varies up to 1.0), and ellipticity ratio (k = 1 to 5). Starvation is simulated by systematically reducing the inlet supply. This analysis reveals that influences of load, rolling speed, and level of starvation are significant on the minimum film thickness. However, the maximum mean film temperature rise is strongly influenced by slip in addition to load, rolling speed, and level of starvation. In the presence of starvation, reduction in minimum film thickness and increase in maximum mean film temperature are observed. Based on the results of this study, empirical relations are developed for the prediction of dimensionless minimum film thickness and dimensionless maximum mean film temperature rise at the contacts in terms of various operating parameters.

Keywords: Starvation, lubrication, elliptical contact, traction, minimum film thickness.

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Authors: S.I Sulaiman, T.K Abdul Rahman, I. Musirin, S. Shaari

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This paper presents performance analysis of the Evolutionary Programming-Artificial Neural Network (EPANN) based technique to optimize the architecture and training parameters of a one-hidden layer feedforward ANN model for the prediction of energy output from a grid connected photovoltaic system. The ANN utilizes solar radiation and ambient temperature as its inputs while the output is the total watt-hour energy produced from the grid-connected PV system. EP is used to optimize the regression performance of the ANN model by determining the optimum values for the number of nodes in the hidden layer as well as the optimal momentum rate and learning rate for the training. The EPANN model is tested using two types of transfer function for the hidden layer, namely the tangent sigmoid and logarithmic sigmoid. The best transfer function, neural topology and learning parameters were selected based on the highest regression performance obtained during the ANN training and testing process. It is observed that the best transfer function configuration for the prediction model is [logarithmic sigmoid, purely linear].

Keywords: Artificial neural network (ANN), Correlation coefficient (R), Evolutionary programming-ANN (EPANN), Photovoltaic (PV), logarithmic sigmoid and tangent sigmoid.

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Authors: Majdi M. Alomari, Nafesah I. Alshdaifat, Mohammad S. Widyan

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Different countries have introduced different schemes and policies to counter global warming. The rationale behind the proposed policies and the potential barriers to successful implementation of the policies adopted by the countries were analyzed and estimated based on different models. It is argued that these models enhance the transparency and provide a better understanding to the policy makers. However, these models are underpinned with several structural and baseline assumptions. These assumptions, modeling features and future prediction of emission reductions and other implication such as cost and benefits of a transition to a low-carbon economy and its economy wide impacts were discussed. On the other hand, there are potential barriers in the form political, financial, and cultural and many others that pose a threat to the mitigation options.

Keywords: Economic wide impact, energy models, environmental policy instruments, mitigating CO2 emission.

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Authors: M. Farahnakian, M.R. Razfar, S. Elhami-Joosheghan

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This paper presents an approach for the determination of the optimal cutting parameters (spindle speed, feed rate, depth of cut and engagement) leading to minimum surface roughness in face milling of high silicon stainless steel by coupling neural network (NN) and Electromagnetism-like Algorithm (EM). In this regard, the advantages of statistical experimental design technique, experimental measurements, artificial neural network, and Electromagnetism-like optimization method are exploited in an integrated manner. To this end, numerous experiments on this stainless steel were conducted to obtain surface roughness values. A predictive model for surface roughness is created by using a back propogation neural network, then the optimization problem was solved by using EM optimization. Additional experiments were performed to validate optimum surface roughness value predicted by EM algorithm. It is clearly seen that a good agreement is observed between the predicted values by EM coupled with feed forward neural network and experimental measurements. The obtained results show that the EM algorithm coupled with back propogation neural network is an efficient and accurate method in approaching the global minimum of surface roughness in face milling.

Keywords: cutting parameters, face milling, surface roughness, artificial neural network, Electromagnetism-like algorithm,

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Authors: B. Thiagarajan, R. Bremananth

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Tumor is an uncontrolled growth of tissues in any part of the body. Tumors are of different types and they have different characteristics and treatments. Brain tumor is inherently serious and life-threatening because of its character in the limited space of the intracranial cavity (space formed inside the skull). Locating the tumor within MR (magnetic resonance) image of brain is integral part of the treatment of brain tumor. This segmentation task requires classification of each voxel as either tumor or non-tumor, based on the description of the voxel under consideration. Many studies are going on in the medical field using Markov Random Fields (MRF) in segmentation of MR images. Even though the segmentation process is better, computing the probability and estimation of parameters is difficult. In order to overcome the aforementioned issues, Conditional Random Field (CRF) is used in this paper for segmentation, along with the modified artificial bee colony optimization and modified fuzzy possibility c-means (MFPCM) algorithm. This work is mainly focused to reduce the computational complexities, which are found in existing methods and aimed at getting higher accuracy. The efficiency of this work is evaluated using the parameters such as region non-uniformity, correlation and computation time. The experimental results are compared with the existing methods such as MRF with improved Genetic Algorithm (GA) and MRF-Artificial Bee Colony (MRF-ABC) algorithm.

Keywords: Conditional random field, Magnetic resonance, Markov random field, Modified artificial bee colony.

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Authors: Vijay R. Khawale, Shashank B. Thakare

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The experiment was carried out to study the performance of solar crop dryer coupled with reversed absorber type solar air heater (SD2). Excel software is used to analyse the raw data obtained from the drying experiment to develop a model. An attempt is made in this paper to correlate the collector efficiency, dryer efficiency and pick-up efficiency. All these efficiencies are dependent on the parameters such as solar flux, ambient temperature, collector outlet temperature and moisture content. The simulation equation was developed to predict the values of collector efficiency. The parameters a, n and drying constant k were determined from a plot of curve using a drying models. Experimental data of drying red chili in conventional solar dryer and solar dryer coupled with reversed absorber solar air heater was compared by fitting with three drying models. The moisture content will be rapidly reduced in solar dryer with reversed absorber due to higher drying temperatures. The best fit model was selected to describe the drying behavior of red chili. For SD2 the values of the coefficient of determination (R²=0.997), mean bias error (MBE=0.00026) and root mean square error (RMSE=0.016) were used to determine the goodness or the quality of the fit. Pages model showed a better fit to drying red chili among Newton model and Henderson & Pabis model.

Keywords: Solar dryer, red chili, reversed absorber, reflector, Buckingham pi theorem, drying model.

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Authors: Sheetal Sharma

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Runoff,decreasing water levels and recharge in urban areas have been a complex issue now a days pointing defective urban design and increasing demography as cause. Very less has been discussed or analysed for water sensitive Urban Master Plans or local area plans. Land use planning deals with land transformation from natural areas into developed ones, which lead to changes in natural environment. Elaborated knowledge of relationship between the existing patterns of land use-land cover and recharge with respect to prevailing soil below is less as compared to speed of development. The parameters of incompatibility between urban functions and the functions of the natural environment are becoming various. Changes in land patterns due to built up, pavements, roads and similar land cover affects surface water flow seriously. It also changes permeability and absorption characteristics of the soil. Urban planners need to know natural processes along with modern means and best technologies available,as there is a huge gap between basic knowledge of natural processes and its requirement for balanced development planning leading to minimum impact on water recharge. The present paper analyzes the variations in land use land cover and their impacts on surface flows and sub-surface recharge in study area. The methodology adopted was to analyse the changes in land use and land cover using GIS and Civil 3d auto cad. The variations were used in  computer modeling using Storm-water Management Model to find out the runoff for various soil groups and resulting recharge observing water levels in POW data for last 40 years of the study area. Results were anlayzed again to find best correlations for sustainable recharge in urban areas.

Keywords: Geology, runoff, urban planning, land use-land cover.

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Authors: Amir Gandomkar, Tahereh Soltani Gord faramarzi, Parisa Safaripour Chafi, Abdol-Reza Amani

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Temperature, humidity and precipitation in an area, are parameters proved influential in the climate of that area, and one should recognize them so that he can determine the climate of that area. Climate changes are of primary importance in climatology, and in recent years, have been of great concern to researchers and even politicians and organizations, for they can play an important role in social, political and economic activities. Even though the real cause of climate changes or their stability is not yet fully recognized, they are a matter of concern to researchers and their importance for countries has prompted them to investigate climate changes in different levels, especially in regional, national and continental level. This issue has less been investigated in our country. However, in recent years, there have been some researches and conferences on climate changes. This study is also in line with such researches and tries to investigate and analyze the trends of climate changes (temperature and precipitation) in Sefid-roud (the name of a river) basin. Three parameters of mean annual precipitation, temperature, and maximum and minimum temperatures in 36 synoptic and climatology stations in a statistical period of 49 years (1956-2005) in the stations of Sefid-roud basin were analyzed by Mann-Kendall test. The results obtained by data analysis show that climate changes are short term and have a trend. The analysis of mean temperature revealed that changes have a significantly rising trend, besides the precipitation has a significantly falling trend.

Keywords: Trend, Climate changes, Sefid-roud, Mann-Kendall

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Authors: Sky Chou, Joseph C. Chen

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This paper focuses on using Six Sigma methodologies to improve the surface roughness of a manufactured part produced by the CNC milling machine. It presents a case study where the surface roughness of milled aluminum is required to reduce or eliminate defects and to improve the process capability index C_p and C_pk for a CNC milling process. The six sigma methodology, DMAIC (design, measure, analyze, improve, and control) approach, was applied in this study to improve the process, reduce defects, and ultimately reduce costs. The Taguchi-based six sigma approach was applied to identify the optimized processing parameters that led to the targeted surface roughness specified by our customer. A L₉ orthogonal array was applied in the Taguchi experimental design, with four controllable factors and one non-controllable/noise factor. The four controllable factors identified consist of feed rate, depth of cut, spindle speed, and surface roughness. The noise factor is the difference between the old cutting tool and the new cutting tool. The confirmation run with the optimal parameters confirmed that the new parameter settings are correct. The new settings also improved the process capability index. The purpose of this study is that the Taguchi–based six sigma approach can be efficiently used to phase out defects and improve the process capability index of the CNC milling process.

Keywords: CNC machining, Six Sigma, Surface roughness, Taguchi methodology.

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Authors: Khaled S. Al Salhen

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Aldehyde oxidase is molybdo-flavoenzyme involved in the oxidation of hundreds of endogenous and exogenous and N-heterocyclic compounds and environmental pollutants. Uncharged N-heterocyclic aromatic compounds such phenanthridine are commonly distributed pollutants in soil, air, sediments, surface water and groundwater, and in animal and plant tissues. Phenanthridine as uncharged N-heterocyclic aromatic compound was incubated with partially purified aldehyde oxidase from rainbow trout fish liver. Reversed-phase HLPC method was used to separate the oxidation products from phenanthridine and the metabolite was identified. The 6(5H)-phenanthridinone was identified the major metabolite by partially purified aldehyde oxidase from fish liver. Kinetic constant for the oxidation reactions were determined spectrophotometrically and showed that this substrate has a good affinity (K_m = 78 ± 7.6µM) for hepatic aldehyde oxidase, will be a significant pathway. This study confirms that partially purified aldehyde oxidase from fish liver is indeed the enzyme responsible for the in vitro production 6(5H)-phenanthridinone metabolite as it is a major metabolite by mammalian aldehyde oxidase, coupled with a relatively high oxidation rate (0.77± 0.03 nmol/min/mg protein). In addition, the kinetic parameters of hepatic fish aldehyde oxidase towards the phenanthridine substrate indicate that in vitro biotransformation by hepatic fish aldehyde oxidase will be a significant pathway. This study confirms that partially purified aldehyde oxidase from fish liver is indeed the enzyme responsible for the in vitro production 6(5H)-phenanthridinone metabolite as it is a major metabolite by mammalian aldehyde oxidase.

Keywords: Aldehyde oxidase, Fish, Phenanthridine, Specificity.

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Authors: S. Hossainpour, A. R. Binesh

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High-velocity oxygen fuel (HVOF) thermal spraying uses a combustion process to heat the gas flow and coating material. A computational fluid dynamics (CFD) model has been developed to predict gas dynamic behavior in a HVOF thermal spray gun in which premixed oxygen and propane are burnt in a combustion chamber linked to a parallel-sided nozzle. The CFD analysis is applied to investigate axisymmetric, steady-state, turbulent, compressible, chemically reacting, subsonic and supersonic flow inside and outside the gun. The gas velocity, temperature, pressure and Mach number distributions are presented for various locations inside and outside the gun. The calculated results show that the most sensitive parameters affecting the process are fuel-to-oxygen gas ratio and total gas flow rate. Gas dynamic behavior along the centerline of the gun depends on both total gas flow rate and fuel-to-oxygen gas ratio. The numerical simulations show that the axial gas velocity and Mach number distribution depend on both flow rate and ratio; the highest velocity is achieved at the higher flow rate and most fuel-rich ratio. In addition, the results reported in this paper illustrate that the numerical simulation can be one of the most powerful and beneficial tools for the HVOF system design, optimization and performance analysis.

Keywords: HVOF, CFD, gas dynamics, thermal spray, combustion.

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Authors: Adriana Alexandru, Cristian Tantareanu, Elena Jitaru

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The paper presents the potential for RES in Romania and the results of the Romanian national research project “Romania contribution to the European targets regarding the development of renewable energy sources - PROMES". The objective of the project is the development of energy generation from renewable energy sources (RES) in Romania by drawing up scenarios and prognosis harmonized with national and European targets, RES development effects modeling (environmental, economic, social etc.), research of the impact of the penetration of RES into the main, implementation of an advanced software system tool for RES information recording and communication, experimental research based on demonstrative applications. The expected results are briefly presented, as well as the social, economic and environmental impact.

Keywords: Energy policy, Internet, renewable energy sources, potential.

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Authors: Mawloud Mosbah, Bachir Boucheham

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We present here the results for a comparative study of some techniques, available in the literature, related to the relevance feedback mechanism in the case of a short-term learning. Only one method among those considered here is belonging to the data mining field which is the K-nearest neighbors algorithm (KNN) while the rest of the methods is related purely to the information retrieval field and they fall under the purview of the following three major axes: Shifting query, Feature Weighting and the optimization of the parameters of similarity metric. As a contribution, and in addition to the comparative purpose, we propose a new version of the KNN algorithm referred to as an incremental KNN which is distinct from the original version in the sense that besides the influence of the seeds, the rate of the actual target image is influenced also by the images already rated. The results presented here have been obtained after experiments conducted on the Wang database for one iteration and utilizing color moments on the RGB space. This compact descriptor, Color Moments, is adequate for the efficiency purposes needed in the case of interactive systems. The results obtained allow us to claim that the proposed algorithm proves good results; it even outperforms a wide range of techniques available in the literature.

Keywords: CBIR, Category Search, Relevance Feedback (RFB), Query Point Movement, Standard Rocchio’s Formula, Adaptive Shifting Query, Feature Weighting, Optimization of the Parameters of Similarity Metric, Original KNN, Incremental KNN.

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Authors: Shrikant Charhate, Gayatri Deshpande

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Permeable pavements have significant benefits like managing runoff, infiltration, and carrying traffic over conventional pavements in terms of sustainability and environmental impact. Some of the countries are using this technique, especially at locations where durability and other parameters are of importance in nature; however, sparse work has been done on this concept. In India, this is yet to be adopted. In this work, the progress in the characterization and development of Permeable Articulated Concrete Blocks (PACB) pavement design is described and discussed with reference to Indian conditions. The experimentation and in-depth analysis was carried out considering conditions like soil erosion, water logging, and dust which are significant challenges caused due to impermeability of pavement. Concrete blocks with size 16.5’’x 6.5’’x 7’’ consisting of arch shape (4’’) at beneath and ½” PVC holes for articulation were casted. These blocks were tested for flexural strength. The articulation process was done with nylon ropes forming series of concrete block system. The total spacing between the blocks was kept about 8 to 10% of total area. The hydraulic testing was carried out by placing the articulated blocks with the combination of layers of soil, geotextile, clean angular aggregate. This was done to see the percentage of seepage through the entire system. The experimental results showed that with the shape of concrete block the flexural strength achieved was beyond the permissible limit. Such blocks with the combination could be very useful innovation in Indian conditions and useful at various locations compared to the traditional blocks as an alternative for long term sustainability.

Keywords: Connections, geotextile, permeable ACB, pavements, stone base.

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Authors: Joseph C. Chen, Venkata Karthik Jakka

Abstract:

The main objective of this research is to optimize tensile strength and dimensional accuracy in injection molding processes using Taguchi Parameter Design. An L16 orthogonal array (OA) is used in Taguchi experimental design with five control factors at four levels each and with non-controllable factor vibration. A total of 32 experiments were designed to obtain the optimal parameter setting for the process. The optimal parameters identified for the shrinkage are shot volume, 1.7 cubic inch (A4); mold term temperature, 130 ºF (B1); hold pressure, 3200 Psi (C4); injection speed, 0.61 inch3/sec (D2); and hold time of 14 seconds (E2). The optimal parameters identified for the tensile strength are shot volume, 1.7 cubic inch (A4); mold temperature, 160 ºF (B4); hold pressure, 3100 Psi (C3); injection speed, 0.69 inch3/sec (D4); and hold time of 14 seconds (E2). The Taguchi-based optimization framework was systematically and successfully implemented to obtain an adjusted optimal setting in this research. The mean shrinkage of the confirmation runs is 0.0031%, and the tensile strength value was found to be 3148.1 psi. Both outcomes are far better results from the baseline, and defects have been further reduced in injection molding processes.

Keywords: Injection molding processes, Taguchi Parameter Design, tensile strength, shrinkage test, high-density polyethylene, HDPE.

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Authors: Y. Sunecher, N. Mamode Khan, V. Jowaheer

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This paper considers the modelling of a non-stationary bivariate integer-valued autoregressive moving average of order one (BINARMA(1,1)) with correlated Poisson innovations. The BINARMA(1,1) model is specified using the binomial thinning operator and by assuming that the cross-correlation between the two series is induced by the innovation terms only. Based on these assumptions, the non-stationary marginal and joint moments of the BINARMA(1,1) are derived iteratively by using some initial stationary moments. As regards to the estimation of parameters of the proposed model, the conditional maximum likelihood (CML) estimation method is derived based on thinning and convolution properties. The forecasting equations of the BINARMA(1,1) model are also derived. A simulation study is also proposed where BINARMA(1,1) count data are generated using a multivariate Poisson R code for the innovation terms. The performance of the BINARMA(1,1) model is then assessed through a simulation experiment and the mean estimates of the model parameters obtained are all efficient, based on their standard errors. The proposed model is then used to analyse a real-life accident data on the motorway in Mauritius, based on some covariates: policemen, daily patrol, speed cameras, traffic lights and roundabouts. The BINARMA(1,1) model is applied on the accident data and the CML estimates clearly indicate a significant impact of the covariates on the number of accidents on the motorway in Mauritius. The forecasting equations also provide reliable one-step ahead forecasts.

Keywords: Non-stationary, BINARMA(1, 1) model, Poisson Innovations, CML

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Authors: Vitomir Struc, Nikola Pavesic

Abstract:

Over the past decades, automatic face recognition has become a highly active research area, mainly due to the countless application possibilities in both the private as well as the public sector. Numerous algorithms have been proposed in the literature to cope with the problem of face recognition, nevertheless, a group of methods commonly referred to as appearance based have emerged as the dominant solution to the face recognition problem. Many comparative studies concerned with the performance of appearance based methods have already been presented in the literature, not rarely with inconclusive and often with contradictory results. No consent has been reached within the scientific community regarding the relative ranking of the efficiency of appearance based methods for the face recognition task, let alone regarding their susceptibility to appearance changes induced by various environmental factors. To tackle these open issues, this paper assess the performance of the three dominant appearance based methods: principal component analysis, linear discriminant analysis and independent component analysis, and compares them on equal footing (i.e., with the same preprocessing procedure, with optimized parameters for the best possible performance, etc.) in face verification experiments on the publicly available XM2VTS database. In addition to the comparative analysis on the XM2VTS database, ten degraded versions of the database are also employed in the experiments to evaluate the susceptibility of the appearance based methods on various image degradations which can occur in "real-life" operating conditions. Our experimental results suggest that linear discriminant analysis ensures the most consistent verification rates across the tested databases.

Keywords: Biometrics, face recognition, appearance based methods, image degradations, the XM2VTS database.

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Authors: Vasudha Bansal, M. L. Singla, C. Ghanshyam

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The effect of nonthermal pulsed electric field (PEF) and thermal treatment (90⁰C for 60s) was studied on quality parameters of emblica officinalis juice for the period of 6 weeks at 4⁰C using monopolar rectangular pulse of 1µs width. The PEF treatment was given using static chamber at 24kV/cm for 500µs. The quality of emblica officinalis juice was investigated in terms of non enzymatic browning index (NEBI), 5-hydroxymethyl-2-furfural (HMF), total polyphenol content and antioxidant capacity. ⁰Brix, pH and conductivity were evaluated as physical parameters. The aim of the work was to investigate the effect of PEF on the retention of bioactive compounds and retardation of browning activity. The results showed that conventional thermal treatment had led to a significant (p < 0.05) decrease of 48.15% in polyphenol content (129.56 mg of GAE L^-1), with higher NEBI and HMF formation (p < 0.05) whilst PEF suppressed NEBI and retained higher polyphenol compounds (168.59 mg GAE L^-1) with limiting the loss to 32.56% along maximum free radical scavenging activity (92.07%). However, pH, ⁰brix and electrical conductivity of treated juice samples remain unaffected. Therefore, PEF can be considered as an effective nonthermal treatment for retaining bioactive compounds along suppressing browning of emblica juice.

 

Keywords: Emblica officinalis juice, Free radical scavenging activity, Pulsed electric field, Total polyphenol content.

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Authors: Peter Takáč, Dana Šimová, Terézia Szabová, Tomáš Bakalár

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The direct sewage sludge application is a relative cheap method for their liquidation. In the past heavy metal contents increase in soils treated with sewage sludge was observed. In 2003 there was acceptance on act n.188/2003 about sewage sludge application on soils. The basic philosophy of act is a safety of the environmental proof of sludge application on soils. The samples of soils from wastewater treatment plant (WTP) Poprad (35) and WTP Michalovce (33 samples) were analyzed which were chosen for sludge application on soils. According to the results only 14 areas for Poprad and 25 areas for Michalovce are suitable for sludge application according to act No. 188/2003. The application dose of sludge was calculated 50 t.ha-1 or 75 t. ha-1 once in 5 years to ensure that heavy metal contents in treated soils will be kept.

Keywords: Environmental safety, heavy metals in soils, sewagesludge application.

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Authors: Isabela Moreira Queiroz

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Slope stability analyses are largely carried out by deterministic methods and evaluated through a single security factor. Although it is known that the geotechnical parameters can present great dispersal, such analyses are considered fixed and known. The probabilistic methods, in turn, incorporate the variability of input key parameters (random variables), resulting in a range of values of safety factors, thus enabling the determination of the probability of failure, which is an essential parameter in the calculation of the risk (probability multiplied by the consequence of the event). Among the probabilistic methods, there are three frequently used methods in geotechnical society: FOSM (First-Order, Second-Moment), Rosenblueth (Point Estimates) and Monte Carlo. This paper presents a comparison between the results from deterministic and probabilistic analyses (FOSM method, Monte Carlo and Rosenblueth) applied to a hypothetical slope. The end was held to evaluate the behavior of the slope and consequent risk analysis, which is used to calculate the risk and analyze their mitigation and control solutions. It can be observed that the results obtained by the three probabilistic methods were quite close. It should be noticed that the calculation of the risk makes it possible to list the priority to the implementation of mitigation measures. Therefore, it is recommended to do a good assessment of the geological-geotechnical model incorporating the uncertainty in viability, design, construction, operation and closure by means of risk management. 

Keywords: Probabilistic methods, risk assessment, risk management, slope stability.

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