Search results for: calorie estimation

Authors: Dong Sang Yoo

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We consider nonlinear uncertain systems such that a priori information of the uncertainties is not available. For such systems, we assume that the upper bound of the uncertainties is represented as a Fredholm integral equation of the first kind and we propose an adaptation law that is capable of estimating the upper bound and design a continuous robust control which renders nonlinear uncertain systems ultimately bounded.

Keywords: adaptive control, estimation, Fredholm integral, uncertain system

Procedia PDF Downloads 483

Authors: R. Lhissou , A. El Harti , K. Chokmani, E. Bachaoui, A. El Ghmari

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Soil salinity is a serious environmental hazard in many countries around the world especially the arid and semi-arid countries like Morocco. Salinization causes negative effects on the ground; it affects agricultural production, infrastructure, water resources and biodiversity. Remote sensing can provide soil salinity information for large areas, and in a relatively short time. In addition, remote sensing is not limited by extremes in terrain or hazardous condition. Contrariwise, experimental methods for monitoring soil salinity by direct measurements in situ are very demanding of time and resources, and also very limited in spatial coverage. In the irrigated perimeter of Tadla plain in central Morocco, the increased use of saline groundwater and surface water, coupled with agricultural intensification leads to the deterioration of soil quality especially by salinization. In this study, we assessed several spectral indices of soil salinity cited in the literature using Landsat TM satellite images and field measurements of electrical conductivity (EC). Three Landsat TM satellite images were taken during 3 months in the dry season (September, October and November 2011). Based on field measurement data of EC collected in three field campaigns over the three dates simultaneously with acquisition dates of Landsat TM satellite images, a two assessment techniques are used to validate a soil salinity spectral indices. Firstly, the spectral indices are validated locally by pixel. The second validation technique is made using a window of size 3x3 pixels. The results of the study indicated that the second technique provides getting a more accurate validation and the assessment has shown its limits when it comes to assess across the pixel. In addition, the EC values measured from field have a good correlation with some spectral indices derived from Landsat TM data and the best results show an r² of 0.88, 0.79 and 0.65 for Salinity Index (SI) in the three dates respectively. The results have shown the usefulness of spectral indices as an auxiliary variable in the spatial estimation and mapping salinity in irrigated land.

Keywords: remote sensing, spectral indices, soil salinity, irrigated land

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Authors: Syed Hammad Ali, Rijan Bhakta Kayastha, Danial Hashmi, Richard Armstrong, Ahuti Shrestha, Iram Bano, Javed Hassan

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This paper presents the results of a semi-distributed modified positive degree-day model (MPDDM) for estimating snow and ice melt contributions to discharge from the glacierized Hunza River basin, Pakistan. The model uses daily temperature data, daily precipitation data, and positive degree day factors for snow and ice melt. The model is calibrated for the period 1995-2001 and validated for 2002-2013, and demonstrates close agreements between observed and simulated discharge with Nash–Sutcliffe Efficiencies of 0.90 and 0.88, respectively. Furthermore, the Weather Research and Forecasting model projected temperature, and precipitation data from 2016-2050 are used for representative concentration pathways RCP4.5 and RCP8.5, and bias correction was done using a statistical approach for future discharge estimation. No drastic changes in future discharge are predicted for the emissions scenarios. The aggregate snow-ice melt contribution is 39% of total discharge in the period 1993-2013. Snow-ice melt contribution ranges from 35% to 63% during the high flow period (May to October), which constitutes 89% of annual discharge; in the low flow period (November to April) it ranges from 0.02% to 17%, which constitutes 11 % of the annual discharge. The snow-ice melt contribution to total discharge will increase gradually in the future and reach up to 45% in 2041-2050. From a sensitivity analysis, it is found that the combination of a 2°C temperature rise and 20% increase in precipitation shows a 10% increase in discharge. The study allows us to evaluate the impact of climate change in such basins and is also useful for the future prediction of discharge to define hydropower potential, inform other water resource management in the area, to understand future changes in snow-ice melt contribution to discharge, and offer a possible evaluation of future water quantity and availability.

Keywords: climate variability, future discharge projection, positive degree day, regional climate model, water resource management

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Authors: U. Ali Rahoma, Nabil Esawy, Fawzia Ibrahim Moursy, A. H. Hassan, Samy A. Khalil, Ashraf S. Khamees

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The design of any solar energy conversion system requires the knowledge of solar radiation data obtained over a long period. Satellite data has been widely used to estimate solar energy where no ground observation of solar radiation is available, yet there are limitations on the temporal coverage of satellite data. Reanalysis is a “retrospective analysis” of the atmosphere parameters generated by assimilating observation data from various sources, including ground observation, satellites, ships, and aircraft observation with the output of NWP (Numerical Weather Prediction) models, to develop an exhaustive record of weather and climate parameters. The evaluation of the performance of reanalysis datasets (ERA-5) for North Africa against high-quality surface measured data was performed using statistical analysis. The estimation of global solar radiation (GSR) distribution over six different selected locations in North Africa during ten years from the period time 2011 to 2020. The root means square error (RMSE), mean bias error (MBE) and mean absolute error (MAE) of reanalysis data of solar radiation range from 0.079 to 0.222, 0.0145 to 0.198, and 0.055 to 0.178, respectively. The seasonal statistical analysis was performed to study seasonal variation of performance of datasets, which reveals the significant variation of errors in different seasons—the performance of the dataset changes by changing the temporal resolution of the data used for comparison. The monthly mean values of data show better performance, but the accuracy of data is compromised. The solar radiation data of ERA-5 is used for preliminary solar resource assessment and power estimation. The correlation coefficient (R2) varies from 0.93 to 99% for the different selected sites in North Africa in the present research. The goal of this research is to give a good representation for global solar radiation to help in solar energy application in all fields, and this can be done by using gridded data from European Centre for Medium-Range Weather Forecasts ECMWF and producing a new model to give a good result.

Keywords: solar energy, solar radiation, ERA-5, potential energy

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Authors: Marinka K. Baghdasaryan, Siranush M. Muradyan, Avgen A. Gasparyan

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Analytical expressions of the current and angular errors, as well as the frequency characteristics of an induction converter describing the relation with its structural parameters, the core and winding characteristics are obtained. Based on estimation of the dependences obtained, a mathematical problem of parametric optimization is formulated which can successfully be used for investigation and diagnosing an induction converter.

Keywords: induction converters, magnetic circuit material, current and angular errors, frequency response, mathematical formulation, structural parameters

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Authors: Sundus Mona, Atif Adnan, Babar Ali, Fareeha Arshad, Allah Rakha

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Molecular diversity is the variation in the abundance of species. Forensic entomology is a neglected field in Pakistan. Insects collected from the crime scene should be handled by forensic entomologists who are currently virtually non-existent in Pakistan. Correct identification of insect specimen along with knowledge of their biodiversity can aid in solving many problems related to complicated forensic cases. Inadequate morphological identification and insufficient thermal biological studies limit the entomological utility in Forensic Medicine. Recently molecular identification of entomological evidence has gained attention globally. DNA barcoding is the latest and established method for species identification. Only proper identification can provide a precise estimation of postmortem intervals. Arthropods are known to be the first tourists scavenging on decomposing dead matter. The objective of the proposed study was to identify species by molecular techniques and analyze their phylogenetic importance with barcoded necrophagous insect species of early succession on human cadavers. Based upon this identification, the study outcomes will be the utilization of established DNA bar codes to identify carrion feeding insect species for concordant estimation of post mortem interval. A molecular identification method involving sequencing of a 658bp ‘barcode’ fragment of the mitochondrial cytochrome oxidase subunit 1 (CO1) gene from collected specimens of unknown dipteral species from cadavers of Lahore was evaluated. Nucleotide sequence divergences were calculated using MEGA 7 and Arlequin, and a neighbor-joining phylogenetic tree was generated. Three species were identified, Chrysomya megacephala, Chrysomya saffranea, and Chrysomya rufifacies with low genetic diversity. The fixation index was 0.83992 that suggests a need for further studies to identify and classify forensically relevant insects in Pakistan. There is an exigency demand for further research especially when immature forms of arthropods are recovered from the crime scene.

Keywords: molecular diversity, DNA barcoding, species identification, forensically relevant

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Authors: Akhila Vasudev, Himanshu Kaushik, Tadikonda Venkata Bharat

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A large number of mine tailings are produced every year as part of the extraction process of phosphates, gold, copper, and other materials. Mine tailings are high in water content and have very slow dewatering behavior. The efficient design of tailings dam and economical disposal of these slurries requires the knowledge of tailings consolidation behavior. The large-strain consolidation theory closely predicts the self-weight consolidation of these slurries as the theory considers the conservation of mass and momentum conservation and considers the hydraulic conductivity as a function of void ratio. Classical laboratory techniques, such as settling column test, seepage consolidation test, etc., are expensive and time-consuming for the estimation of hydraulic conductivity variation with void ratio. Inverse estimation of the constitutive relationships from the measured settlement versus time curves is explored. In this work, inverse analysis based on metaheuristics techniques will be explored for predicting the hydraulic conductivity parameters for mine tailings from the base excess pore water pressure dissipation curve and the initial conditions of the mine tailings. The proposed inverse model uses particle swarm optimization (PSO) algorithm, which is based on the social behavior of animals searching for food sources. The finite-difference numerical solution of the forward analytical model is integrated with the PSO algorithm to solve the inverse problem. The method is tested on synthetic data of base excess pore pressure dissipation curves generated using the finite difference method. The effectiveness of the method is verified using base excess pore pressure dissipation curve obtained from a settling column experiment and further ensured through comparison with available predicted hydraulic conductivity parameters.

Keywords: base excess pore pressure, hydraulic conductivity, large strain consolidation, mine tailings

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Authors: Alkaben Patel

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The proposed RP-HPLC method is easy, rapid, economical, precise and accurate stability indicating RP-HPLC method for simultaneous estimation of Astorvastatin and Methylcobalamine in their combined dosage form has been developed.The separation was achieved by LC-20 AT C18(250mm*4.6mm*2.6mm)Colum and water (pH 3.5): methanol 70:30 as mobile phase, at a flow rate of 1ml/min. wavelength of this dosage form is 215nm.The drug is related to stress condition of hydrolysis, oxidation, photolysis and thermal degradation.

Keywords: RP- HPLC, atorvastatin, methylcobalamine, method, development, validation

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Authors: Rafayel K. Kostanyan

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The opportunities of use of metallic magnesium as a generator of hydrogen gas, as well as thermal and electric energy is presented in the paper. Various schemes of magnesium application are discussed and power characteristics of corresponding devices are presented. Economic estimation of hydrogen price obtained by different methods is made, including the use of magnesium as a source of hydrogen for transportation in comparison with gasoline. Details and prospects of our new inexpensive technology of magnesium production from magnesium hydroxide and magnesium bearing rocks (which are available worldwide and in Armenia) are analyzed. It is estimated the threshold cost of Mg production at which application of this metal in power engineering is economically justified.

Keywords: energy, electrodialysis, magnesium, new technology

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Authors: Jie Yang, Jian-Min Meng

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A GPU-based floating object detection scheme is presented in this paper which is designed for floating mine detection tasks. This system uses contrast and motion information to eliminate as many false positives as possible while avoiding false negatives. The GPU computation platform is deployed to allow detecting objects in real-time. From the experimental results, it is shown that with certain configuration, the GPU-based scheme can speed up the computation up to one thousand times compared to the CPU-based scheme.

Keywords: object detection, GPU, motion estimation, parallel processing

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Authors: H. Tavakoli, S. S. Mohtasebi, R. Alimardani, R. Gebbers

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Nitrogen (N) is one of the most important agricultural inputs affecting crop growth, yield and quality in rain-fed cereal production. N demand of crops varies spatially across fields due to spatial differences in soil conditions. In addition, the response of a crop to the fertilizer applications is heavily reliant on plant available water. Matching N supply to water availability is thus essential to achieve an optimal crop response. The objective of this study was to determine effect of drought stress on estimation of nitrogen status of winter wheat by some vegetation indices. During the 2012 growing season, a field experiment was conducted at the Bundessortenamt (German Plant Variety Office) Marquardt experimental station which is located in the village of Marquardt about 5 km northwest of Potsdam, Germany (52°27' N, 12°57' E). The experiment was designed as a randomized split block design with two replications. Treatments consisted of four N fertilization rates (0, 60, 120 and 240 kg N ha-1, in total) and two water regimes (irrigated (Irr) and non-irrigated (NIrr)) in total of 16 plots with dimension of 4.5 × 9.0 m. The indices were calculated using readings of a spectroradiometer made of tec5 components. The main parts were two “Zeiss MMS1 nir enh” diode-array sensors with a nominal rage of 300 to 1150 nm with less than 10 nm resolutions and an effective range of 400 to 1000 nm. The following vegetation indices were calculated: NDVI, GNDVI, SR, MSR, NDRE, RDVI, REIP, SAVI, OSAVI, MSAVI, and PRI. All the experiments were conducted during the growing season in different plant growth stages including: stem elongation (BBCH=32-41), booting stage (BBCH=43), inflorescence emergence, heading (BBCH=56-58), flowering (BBCH=65-69), and development of fruit (BBCH=71). According to the results obtained, among the indices, NDRE and REIP were less affected by drought stress and can provide reliable wheat nitrogen status information, regardless of water status of the plant. They also showed strong relations with nitrogen status of winter wheat.

Keywords: nitrogen status, drought stress, vegetation indices, precision agriculture

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Authors: Sarah Elsayed Mohammed, Lamiaa Ahmed Ahmed, Mahmoud Mohammed Khattab

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Aim: The aim of the present study was to investigate whether combined nicorandil and bone marrow-derived mesenchymal stem cells (BMDMSC) treatment could offer an additional benefit in ameliorating isoproterenol (ISO)-induced heart failure in rats. Methods: ISO (85 and 170 mg/kg/day) was injected subcutaneously for 2 successive days, respectively. By day 3, electrocardiographic changes were recorded and serum was separated for determination of CK-MB level for confirmation of myocardial damage. Nicorandil (3 mg/kg/day) was then given orally with or without a single i.v. BMDMSC administration. Electrocardiography and echocardiography were recorded 2 weeks after beginning of treatment. Rats were then sacrificed and ventricles were isolated for estimation of vascular endothelial growth factor (VEGF), tumor necrosis factor-alpha (TNF-α) and transforming growth factor-beta (TGF-β) contents, caspase-3 activity as well as inducible nitric oxide synthase (iNOS) and connexin-43 protein expressions. Moreover, histological analysis of myocardial fibrosis was performed and cryosections were done for estimation of homing of BMDMSC. Results: ISO induced a significant increase in ventricles/body weight ratio, left ventricular end diastolic (LVEDD) and systolic dimensions (LVESD), ST segment and QRS duration. Moreover, myocardial fibrosis as well as VEGF, TNF-α and TGF-β contents were significantly increased. On the other hand, connexin-43 protein expression was significantly decreased, while caspase-3 and iNOS protein expressions were significantly increased. Combined therapy provided additional improvement compared to cell treatment alone towards reducing cardiac hypertrophy, fibrosis and inflammation. Furthermore, combined therapy induced significant increase in angiogenesis and BMDMSC homing and prevented ISO induced changes in iNOS, connexin-43 and caspase-3 protein expressions. Conclusion: Combined nicorandil/BMDMSC treatment was superior to BMDMSC alone towards preventing ISO-induced heart failure in rats.

Keywords: fibrosis, isoproterenol, mesenchymal stem cells, nicorandil

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Authors: Mahdieh Khanmohammadi, Sune Darkner, Nicoletta Nava, Jens Randel Nyengaard, Jon Sporring

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We study the effect of stress on nervous system and we use two experimental groups of rats: sham rats and rats subjected to acute foot-shock stress. We investigate the synaptic vesicles density as a function of distance to the active zone in serial section transmission electron microscope images in 2 and 3 dimensions. By estimating the density in 2D and 3D we compare two groups of rats.

Keywords: stress, 3-dimensional synaptic vesicle density, image registration, bioinformatics

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Authors: Dimiter M. Dimitrov, Abdullah Sadaawi

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The National Assessment for Schools (NAFS) in Saudi Arabia consists of standardized tests in Mathematics, Reading, and Science for school grade levels 3, 6, and 9. One main goal is to classify students into four categories of NAFS performance (minimal, basic, proficient, and advanced) by schools and the entire national sample. The NAFS scoring and equating is performed on a bounded scale (D-scale: ranging from 0 to 1) in the framework of the recently developed “D-scoring method of measurement.” The specificity of the NAFS measurement framework and data complexity presented both challenges and opportunities to (a) the estimation of score reliability for schools, (b) setting cut-scores for the classification of students into categories of performance, and (c) generating plausible values for distributions of student performance on the D-scale. The estimation of score reliability at the school level was performed in the framework of generalizability theory (GT), with students “nested” within schools and test items “nested” within test forms. The GT design was executed via a multilevel modeling syntax code in R. Cut-scores (on the D-scale) for the classification of students into performance categories was derived via a recently developed method of standard setting, referred to as “Response Vector for Mastery” (RVM) method. For each school, the classification of students into categories of NAFS performance was based on distributions of plausible values for the students’ scores on NAFS tests by grade level (3, 6, and 9) and subject (Mathematics, Reading, and Science). Plausible values (on the D-scale) for each individual student were generated via random selection from a statistical logit-normal distribution with parameters derived from the student’s D-score and its conditional standard error, SE(D). All procedures related to D-scoring, equating, generating plausible values, and classification of students into performance levels were executed via a computer program in R developed for the purpose of NAFS data analysis.

Keywords: large-scale assessment, reliability, generalizability theory, plausible values

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Authors: Hossein Kheiri, Bashir Naderi, Mohamad Reza Niknam

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In this paper we study the optimal synchronization of chaotic T-system with complete uncertain parameter. Optimal control laws and parameter estimation rules are obtained by using Hamilton-Jacobi-Bellman (HJB) technique and Lyapunov stability theorem. The derived control laws are optimal adaptive control and make the states of drive and response systems asymptotically synchronized. Numerical simulation shows the effectiveness and feasibility of the proposed method.

Keywords: Lyapunov stability, synchronization, chaos, optimal control, adaptive control

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Authors: I. Diamant, R. Srouji

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Applicant perceptions are attitudes, feelings, and cognitions which individuals have about selection procedures and have been mostly studied in the context of personnel selection. The main aim of the present study is to expand the understanding of applicant perceptions, using the framework of Organizational Justice Theory, in the domain of selection for higher education. The secondary aim is to explore the relationships between individual differences in social anxiety and applicants’ perceptions. The selection process is an accept/reject situation; it was hypothesized that applicants with higher social anxiety would experience negative perceptions and a lower success estimation, especially when subjected to social interaction elements in the process (interview and group simulation). Also, the effects of prior preparation and post-process explanations offered at the end of the selection process were explored. One hundred sixty psychology M.A. program applicants participated in this research, and following the selection process completed questionnaires measuring social anxiety, social exclusion, ratings on several justice dimensions for each of the methods in the selection process, feelings of success, and self-estimation of compatibility. About half of the applicants also received explanations regarding the significance and the aims of the selection process. Results provided support for most of our hypotheses: applicants with higher social anxiety experienced an increased level of social exclusion in the selection process, perceived the selection as less fair and ended with a lower feeling of success relative to those applicants without social anxiety. These relationships were especially salient in the selection procedures which included social interaction. Additionally, preparation for the selection process was positively related to the favorable perception of fairness in the selection process. Finally, contrary to our hypothesis, it was found that explanations did not affect the applicant’s perceptions. The results enhance our understanding of which factors affect applicant perceptions in applicants to higher education studies and contribute uniquely to the understanding of the effect of social anxiety on different aspects of selection experienced by applicants. The findings clearly show that some individuals may be predisposed to react unfavorably to certain selection situations. In an age of increasing awareness towards fairness in evaluation and selection and hiring procedures, these findings may be of relevance and may contribute to the design of future personnel selection methods in general and of higher education selection in particular.

Keywords: applicant perceptions, selection and assessment, organizational justice theory, social anxiety

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Authors: Juan M. Rodriguez-Diaz

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The precision of parameter estimators in the Gaussian linear model is traditionally accounted by the variance-covariance matrix of the asymptotic distribution. However, this measure can underestimate the true variance, specially for small samples. Traditionally, optimal design theory pays attention to this variance through its relationship with the model's information matrix. For this reason it seems convenient, at least in some cases, adapt the optimality criteria in order to get the best designs for the actual variance structure, otherwise the loss in efficiency of the designs obtained with the traditional approach may be very important.

Keywords: correlated observations, information matrix, optimality criteria, variance-covariance matrix

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Authors: Eslam Mohammed Abdelkader, Mohamed Marzouk, Tarek Zayed

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Infrastructure systems are crucial to every aspect of life on Earth. Existing Infrastructure is subjected to degradation while the demands are growing for a better infrastructure system in response to the high standards of safety, health, population growth, and environmental protection. Bridges play a crucial role in urban transportation networks. Moreover, they are subjected to high level of deterioration because of the variable traffic loading, extreme weather conditions, cycles of freeze and thaw, etc. The development of Bridge Management Systems (BMSs) has become a fundamental imperative nowadays especially in the large transportation networks due to the huge variance between the need for maintenance actions, and the available funds to perform such actions. Deterioration models represent a very important aspect for the effective use of BMSs. This paper presents a probabilistic time-based model that is capable of predicting the condition ratings of the concrete bridge decks along its service life. The deterioration process of the concrete bridge decks is modeled using semi-Markov process. One of the main challenges of the Markov Chain Decision Process (MCDP) is the construction of the transition probability matrix. Yet, the proposed model overcomes this issue by modeling the sojourn times based on some probability density functions. The sojourn times of each condition state are fitted to probability density functions based on some goodness of fit tests such as Kolmogorov-Smirnov test, Anderson Darling, and chi-squared test. The parameters of the probability density functions are obtained using maximum likelihood estimation (MLE). The condition ratings obtained from the Ministry of Transportation in Quebec (MTQ) are utilized as a database to construct the deterioration model. Finally, a comparison is conducted between the Markov Chain and semi-Markov chain to select the most feasible prediction model.

Keywords: bridge management system, bridge decks, deterioration model, Semi-Markov chain, sojourn times, maximum likelihood estimation

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Authors: E. V. Kuzmicheva

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An attention is concentrated on a service quality estimation of sport services. A typical mathematical model was developed at the base of the «general economic theory of mass service» accounting pedagogical requirements of fitness services. Also it took into account a dependence of the club member number versus on a value of square of sport facilities. Final recommendations were applied to the fitness club resulted in some improvement of the quality sport service, an increasing of the revenue from club members and profit of clubs.

Keywords: fitness club, efficiency of operation, facilities, service quality, mass service

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Authors: Gamze Ozel, Selen Cakmakyapan

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We introduce a new model called the Marshall-Olkin Rayleigh distribution which extends the Rayleigh distribution using Marshall-Olkin transformation and has increasing and decreasing shapes for the hazard rate function. Various structural properties of the new distribution are derived including explicit expressions for the moments, generating and quantile function, some entropy measures, and order statistics are presented. The model parameters are estimated by the method of maximum likelihood and the observed information matrix is determined. The potentiality of the new model is illustrated by means of real life data set.

Keywords: Marshall-Olkin distribution, Rayleigh distribution, estimation, maximum likelihood

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Authors: H. Yousefnia, S. Zolghadri, S. Shanesazzadeh, A.Lahooti, A. R. Jalilian

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In this study, 68Ga-ECC and 67Ga-ECC were both prepared with the radiochemical purity of higher than 97% in less than 30 min. The biodistribution data for 68Ga-ECC showed the extraction of the most of the activity from the urinary tract. The absorbed dose was estimated based on biodistribution data in mice by the medical internal radiation dose (MIRD) method. Comparison between human absorbed dose estimation for these two agents indicated the values of approximately ten-fold higher after injection of 67Ga-ECC than 68Ga-ECC in the most organs. The results showed that 68Ga-ECC can be considered as a more potential agent for renal imaging compared to 67Ga-ECC.

Keywords: effective absorbed dose, ethylenecysteamine cysteine, Ga-67, Ga-68

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Authors: Faruk Ortes, Derya Karabulut, Yunus Ziya Arslan

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Myoelectric features gathering from musculature environment are considered on a preferential basis to perceive muscle activation and control human arm prostheses according to recent experimental researches. EMG (electromyography) signal based human arm prostheses have shown a promising performance in terms of providing basic functional requirements of motions for the amputated people in recent years. However, these assistive devices for neurorehabilitation still have important limitations in enabling amputated people to perform rather sophisticated or functional movements. Surface electromyogram (EMG) is used as the control signal to command such devices. This kind of control consists of activating a motion in prosthetic arm using muscle activation for the same particular motion. Extraction of clear and certain neural information from EMG signals plays a major role especially in fine control of hand prosthesis movements. Many signal processing methods have been utilized for feature extraction from EMG signals. The specific objective of this study was to compare widely used time domain features of EMG signal including integrated EMG(IEMG), root mean square (RMS) and waveform length(WL) for prediction of externally applied forces to human hands. Obtained features were classified using artificial neural networks (ANN) to predict the forces. EMG signals supplied to process were recorded during only type of muscle contraction which is isometric and isotonic one. Experiments were performed by three healthy subjects who are right-handed and in a range of 25-35 year-old aging. EMG signals were collected from muscles of the proximal part of the upper body consisting of: biceps brachii, triceps brachii, pectorialis major and trapezius. The force prediction results obtained from the ANN were statistically analyzed and merits and pitfalls of the extracted features were discussed with detail. The obtained results are anticipated to contribute classification process of EMG signal and motion control of powered human arm prosthetics control.

Keywords: assistive devices for neurorehabilitation, electromyography, feature extraction, force estimation, human arm prosthesis

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Authors: Vaibhav Rathi, Soumen Maity, Achu R. Sekhar, Abhijit Banerjee

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Construction sector in India is extremely resource and carbon intensive. It contributes to significantly to national greenhouse emissions. At the resource end the industry consumes significant portions of the output from mining. Resources such as sand and soil are most exploited and their rampant extraction is becoming constant source of impact on environment and society. Cement is another resource that is used in abundance in building and construction and has a direct impact on limestone resources. Though India is rich in cement grade limestone resource, efforts have to be made for sustainable consumption of this resource to ensure future availability. Use of these resources in high volumes in India is a result of rapid urbanization. More cities have grown to a population of million plus in the last decade and million plus cities are growing further. To cater to needs of growing urban population of construction activities are inevitable in the coming future thereby increasing material consumption. Increased construction will also lead to substantial increase in end of life waste generation from Construction and Demolition (C&D). Therefore proper management of C&D waste has the potential to reduce environmental pollution as well as contribute to the resource efficiency in the construction sector. The present study deals with estimation, characterisation and documenting current management practices of C&D waste in 10 Indian cities of different geographies and classes. Based on primary data the study draws conclusions on the potential of C&D waste to be used as an alternative to primary raw materials. The estimation results show that India generates 716 million tons of C&D waste annually, placing the country as second largest C&D waste generator in the world after China. The study also aimed at utilization of C&D waste in to building materials. The waste samples collected from various cities have been used to replace 100% stone aggregates in paver blocks without any decrease in strength. However, management practices of C&D waste in cities still remains poor instead of notification of rules and regulations notified for C&D waste management. Only a few cities have managed to install processing plant and set up management systems for C&D waste. Therefore there is immense opportunity for management and reuse of C&D waste in Indian cities.

Keywords: building materials, construction and demolition waste, cities, environmental pollution, resource efficiency

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Authors: Saeed Qaisrani

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The study was conducted to observe carbon and nutrient loss by burning of rice residues on rice-wheat cropping system The rice crop was harvested to conduct the experiment in a randomized complete block design (RCBD) with factors and 4 replications with a net plot size of 10 m x 20 m. Rice stubbles were managed by two methods i.e. Incorporation & burning of rice residues. Soil samples were taken to a depth of 30 cm before sowing & after harvesting of wheat. Wheat was sown after harvesting of rice by three practices i.e. Conventional tillage, Minimum tillage and Zero tillage to observe best tillage practices. Laboratory and field experiments were conducted on wheat to assess best tillage practice and residues management method with estimation of carbon losses. Data on the following parameters; establishment count, plant height, spike length, number of grains per spike, biological yield, fat content, carbohydrate content, protein content, and harvest index were recorded to check wheat quality & ensuring food security in the region. Soil physico-chemical analysis i.e. pH, electrical conductivity, organic matter, nitrogen, phosphorus, potassium, and carbon were done in soil fertility laboratory. Substantial results were found on growth, yield and related parameters of wheat crop. The collected data were examined statistically with economic analysis to estimate the cost-benefit ratio of using different tillage techniques and residue management practices. Obtained results depicted that Zero tillage method have positive impacts on growth, yield and quality of wheat, Moreover, it is cost effective methodology. Similarly, Incorporation is suitable and beneficial method for soil due to more nutrients provision and reduce the need of fertilizers. Burning of rice stubbles has negative impact including air pollution, nutrient loss, microbes died and carbon loss. Recommended the zero tillage technology to reduce carbon losses along with food security in Pakistan.

Keywords: agricultural agronomy, food security, carbon sequestration, rice-wheat cropping system

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Authors: R. L. Ujjwal, Abhishek Jain

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In the field of computer vision, most facial variations such as identity, expression, emotions and gender have been extensively studied. Automatic age estimation has been rarely explored. With age progression of a human, the features of the face changes. This paper is providing a new comparable study of different type of algorithm to feature extraction [Hybrid features using HAAR cascade & HOG features] & classification [KNN & SVM] training dataset. By using these algorithms we are trying to find out one of the best classification algorithms. Same thing we have done on the feature selection part, we extract the feature by using HAAR cascade and HOG. This work will be done in context of age group classification model.

Keywords: computer vision, age group, face detection

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Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

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We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

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Authors: Clive L. Morley

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Gravity models and panel data modelling of tourism flows are receiving renewed attention, after decades of general neglect. Such models have quite different underpinnings from conventional demand models derived from micro-economic theory. They operate at a different level of data and with different theoretical bases. These differences have important consequences for the interpretation of the results and their policy and managerial implications. This review compares and contrasts the two model forms, clarifying the distinguishing features and the estimation requirements of each. In general, gravity models are not recommended for use to address specific management and marketing purposes.

Keywords: gravity models, micro-economics, demand models, marketing

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Authors: Mounir Bekaik, Messaoud Ramdani

Abstract:

We present in this work a new technique of stabilization for fault nonlinear systems. The approach we adopt focus on a fuzzy Luenverger observer. The T-S approximation of the nonlinear observer is based on fuzzy C-Means clustering algorithm to find local linear subsystems. The MOESP identification approach was applied to design an empirical model describing the subsystems state variables. The gain of the observer is given by the minimization of the estimation error through Lyapunov-krasovskii functional and LMI approach. We consider a three tank hydraulic system for an illustrative example.

Keywords: nonlinear system, fuzzy, faults, TS, Lyapunov-Krasovskii, observer

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Authors: Mouna Zitouni, Mariem Tounsi

Abstract:

This research introduces an application of the Riesz mixture model for medical image segmentation for accurate diagnosis and treatment of brain tumors. We propose a pixel classification technique based on the Riesz distribution, derived from an extended Bartlett decomposition. To our knowledge, this is the first study addressing this approach. The Expectation-Maximization algorithm is implemented for parameter estimation. A comparative analysis, using both synthetic and real brain images, demonstrates the superiority of the Riesz model over a recent method based on the Wishart distribution.

Keywords: EM algorithm, segmentation, Riesz probability distribution, Wishart probability distribution

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Authors: Said Elkassimi, Said Safi, B. Manaut

Abstract:

This paper presented a study of three algorithms, the equalization algorithm to equalize the transmission channel with ZF and MMSE criteria, application of channel Bran A, and adaptive filtering algorithms LMS and RLS to estimate the parameters of the equalizer filter, i.e. move to the channel estimation and therefore reflect the temporal variations of the channel, and reduce the error in the transmitted signal. So far the performance of the algorithm equalizer with ZF and MMSE criteria both in the case without noise, a comparison of performance of the LMS and RLS algorithm.

Keywords: adaptive filtering second equalizer, LMS, RLS Bran A, Proakis (B) MMSE, ZF

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