Search results for: PD Statistical parameters.

Authors: Ab. Rashid M.F.F., Gan S.Y., Muhammad N.Y.

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Surface roughness (Ra) is one of the most important requirements in machining process. In order to obtain better surface roughness, the proper setting of cutting parameters is crucial before the process take place. This research presents the development of mathematical model for surface roughness prediction before milling process in order to evaluate the fitness of machining parameters; spindle speed, feed rate and depth of cut. 84 samples were run in this study by using FANUC CNC Milling α-Τ14ιE. Those samples were randomly divided into two data sets- the training sets (m=60) and testing sets(m=24). ANOVA analysis showed that at least one of the population regression coefficients was not zero. Multiple Regression Method was used to determine the correlation between a criterion variable and a combination of predictor variables. It was established that the surface roughness is most influenced by the feed rate. By using Multiple Regression Method equation, the average percentage deviation of the testing set was 9.8% and 9.7% for training data set. This showed that the statistical model could predict the surface roughness with about 90.2% accuracy of the testing data set and 90.3% accuracy of the training data set.

Keywords: Surface roughness, regression analysis.

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Authors: Mustafa M. Donma, Orkide Donma, Savas Guzel

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Iron is physiologically essential. However, it also participates in the catalysis of free radical formation reactions. Its deficiency is associated with amplified health risks. This trace element establishes some links with another physiological process related to cell death, apoptosis. Both iron deficiency and iron overload are closely associated with apoptosis. Soluble tumor necrosis factor-like weak inducer of apoptosis (sTWEAK) has the ability to trigger apoptosis and plays a dual role in the physiological versus pathological inflammatory responses of tissues. The aim of this study was to investigate the status of these parameters as well as the associations among them in children with obesity, a low-grade inflammatory state. The study was performed on groups of children with normal body mass index (N-BMI) and obesity. 43 children were included in each group. Based upon age- and sex-adjusted BMI percentile tables prepared by the World Health Organization, children whose values varied between 85 and 15 were included in N-BMI group. Children, whose BMI percentile values were between 99 and 95, comprised obese (OB) group. Institutional ethical committee approval and informed consent forms were taken prior to the study. Anthropometric measurements (weight, height, waist circumference, hip circumference, head circumference, neck circumference) and blood pressure values (systolic blood pressure and diastolic blood pressure) were recorded. Routine biochemical analyses, including serum iron, total iron binding capacity (TIBC), transferrin saturation percent (Tf Sat %) and ferritin, were performed. sTWEAK levels were determined by enzyme-linked immunosorbent assay. study data were evaluated using appropriate statistical tests performed by the statistical program SPSS. Serum iron levels were 91 ± 34 mcrg/dl and 75 ± 31 mcrg/dl in N-BMI and OB children, respectively. The corresponding values for TIBC, Tf Sat %, ferritin were 265 mcrg/dl vs. 299 mcrg/dl, 37.2 ± 19.1% vs. 26.7 ± 14.6%, and 41 ± 25 ng/ml vs 44 ± 26 ng/ml. In N-BMI and OB groups, sTWEAK concentrations were measured as 351 ng/L and 325 ng/L, respectively (p > 0.05). Correlation analysis revealed significant associations between sTWEAK levels and iron related parameters (p < 0.05) except ferritin. In conclusion, iron contributes to apoptosis. Children with iron deficiency have decreased apoptosis rate in comparison with that of healthy children. sTWEAK is an inducer of apoptosis. OB children had lower levels of both iron and sTWEAK. Low levels of sTWEAK are associated with several types of cancers and poor survival. Although iron deficiency state was not observed in this study, the correlations detected between decreased sTWEAK and decreased iron as well as Tf Sat % values were valuable findings, which point out decreased apoptosis. This may induce a proinflammatory state, potentially leading to malignancies in the future lives of OB children.

Keywords: Apoptosis, children, iron-related parameters, obesity, soluble tumor necrosis factor-like weak inducer of apoptosis.

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Authors: Aleem Khalid Alvi, M. Yousuf Bin Azhar, Mehmood Usman, Suleman Mumtaz, Sameer Rafiq, RaziUr Rehman, Israr Ahmed

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Sign language recognition has been a topic of research since the first data glove was developed. Many researchers have attempted to recognize sign language through various techniques. However none of them have ventured into the area of Pakistan Sign Language (PSL). The Boltay Haath project aims at recognizing PSL gestures using Statistical Template Matching. The primary input device is the DataGlove5 developed by 5DT. Alternative approaches use camera-based recognition which, being sensitive to environmental changes are not always a good choice.This paper explains the use of Statistical Template Matching for gesture recognition in Boltay Haath. The system recognizes one handed alphabet signs from PSL.

Keywords: Gesture Recognition, Pakistan Sign Language, DataGlove, Human Computer Interaction, Template Matching, BoltayHaath

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Authors: S. E. Oraby, A.M. Alaskari

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The stochastic nature of tool life using conventional discrete-wear data from experimental tests usually exists due to many individual and interacting parameters. It is a common practice in batch production to continually use the same tool to machine different parts, using disparate machining parameters. In such an environment, the optimal points at which tools have to be changed, while achieving minimum production cost and maximum production rate within the surface roughness specifications, have not been adequately studied. In the current study, two relevant aspects are investigated using coated and uncoated inserts in turning operations: (i) the accuracy of using machinability information, from fixed parameters testing procedures, when variable parameters situations are emerged, and (ii) the credibility of tool life machinability data from prior discrete testing procedures in a non-stop machining. A novel technique is proposed and verified to normalize the conventional fixed parameters machinability data to suit the cases when parameters have to be changed for the same tool. Also, an experimental investigation has been established to evaluate the error in the tool life assessment when machinability from discrete testing procedures is employed in uninterrupted practical machining.

Keywords: Machinability, tool life, tool wear, wear variability

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Authors: A. M. Pashayev, D. D. Askerov, C. Ardil, R. A. Sadiqov, P. S. Abdullayev

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Researches show that probability-statistical methods application, especially at the early stage of the aviation Gas Turbine Engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods is considered. According to the purpose of this problem training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. For GTE technical condition more adequate model making dynamics of skewness and kurtosis coefficients- changes are analysed. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE workand output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-by-stage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine technical condition was made.

Keywords: aviation gas turbine engine, technical condition, fuzzy logic, neural networks, fuzzy statistics

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Authors: Chaudhary Itisha, Shankar Manu

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Patient satisfaction represents a crucial aspect in the evaluation of health care services. Preoperative teaching provides the patient with pertinent information concerning the surgical process and the intended surgical procedure as well as anticipated patient behavior (anxiety, fear), expected sensation, and the probable outcomes. Although patient education is part of Accreditation protocols, it is not uniform at most places. The aim of this study was to try to assess the benefit of preoperative patient education on selected post-operative outcome parameters; mainly, post-operative pain scores, requirement of additional analgesia, return to activity of daily living and overall patient satisfaction, and try to standardize few education protocols. Dependent variables were measured before and after the treatment on a study population of 302 volunteers. Educational intervention was provided by the Investigator in the preoperative period to the study group through personal counseling. An information booklet contained detailed information was also provided. Statistical Analysis was done using Chi square test, Mann Whitney u test and Fischer Exact Test on a total of 302 subjects. P value <0.05 was considered as level of statistical significance and p<0.01 was considered as highly significant. This study suggested that patients who are given a structured, individualized and elaborate preoperative education and counseling have a better ability to cope up with postoperative pain in the immediate post-operative period. However, there was not much difference when the patients have had almost complete recovery. There was no difference in the requirement of additional analgesia among the two groups. There is a positive effect of preoperative counseling on expected return to the activities of daily living and normal work schedule. However, no effect was observed on the activities in the immediate post-operative period. There is no difference in the overall satisfaction score among the two groups of patients. Thus this study concludes that there is a positive benefit as suggested by the results for pre-operative patient education. Although the difference in various parameters studied might not be significant over a long term basis, they definitely point towards the benefits of preoperative patient education. 

Keywords: Patient education, post-operative pain, patient satisfaction, post-operative outcome.

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Authors: N. R. N. Idris, S. Baharom

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A meta-analysis may be performed using aggregate data (AD) or an individual patient data (IPD). In practice, studies may be available at both IPD and AD level. In this situation, both the IPD and AD should be utilised in order to maximize the available information. Statistical advantages of combining the studies from different level have not been fully explored. This study aims to quantify the statistical benefits of including available IPD when conducting a conventional summary-level meta-analysis. Simulated meta-analysis were used to assess the influence of the levels of data on overall meta-analysis estimates based on IPD-only, AD-only and the combination of IPD and AD (mixed data, MD), under different study scenario. The percentage relative bias (PRB), root mean-square-error (RMSE) and coverage probability were used to assess the efficiency of the overall estimates. The results demonstrate that available IPD should always be included in a conventional meta-analysis using summary level data as they would significantly increased the accuracy of the estimates.On the other hand, if more than 80% of the available data are at IPD level, including the AD does not provide significant differences in terms of accuracy of the estimates. Additionally, combining the IPD and AD has moderating effects on the biasness of the estimates of the treatment effects as the IPD tends to overestimate the treatment effects, while the AD has the tendency to produce underestimated effect estimates. These results may provide some guide in deciding if significant benefit is gained by pooling the two levels of data when conducting meta-analysis.

Keywords: Aggregate data, combined-level data, Individual patient data, meta analysis.

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Authors: Mousavi Shirazi, Seyed Alireza, Rastayesh, Sima

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Whereas in the third generation nuclear reactors, dimensions of core and also the kind of coolant and enrichment percent of fuel have significantly changed than the second generation, therefore in this article the aim is based on a comparative investigation between two same power reactors of second and third generations, that the neutronic parameters of both reactors such as: K∞, Keff and its details and thermal hydraulic parameters such as: power density, specific power, volumetric heat rate, released power per fuel volume unit, volume and mass of clad and fuel (consisting fissile and fertile fuels), be calculated and compared together. By this comparing the efficiency and modification of third generation nuclear reactors than second generation which have same power can be distinguished. In order to calculate the cited parameters, some information such as: core dimensions, the pitch of lattice, the fuel matter, the percent of enrichment and the kind of coolant are used. For calculating the neutronic parameters, a neutronic program entitled: SIXFAC and also related formulas have been used. Meantime for calculating the thermal hydraulic and other parameters, analytical method and related formulas have been applied.

Keywords: Nuclear reactor, second generation, third generation, thermo-neutronics parameters.

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Authors: Aman Agarwal, Georg Klepp

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Impinging jets are used in various industrial areas as a cooling and drying technique. The current research is concerned with the means of improving the heat transfer for configurations with a minimum distance of the nozzle to the impingement surface. The impingement heat transfer is described using numerical methods over a wide range of parameters for an array of planar jets. These parameters include varying jet flow speed, width of nozzle, distance of nozzle, angle of the jet flow, velocity and geometry of the impingement surface. Normal pressure and shear stress are computed as additional parameters. Using dimensionless characteristic numbers the parameters and the results are correlated to gain generalized equations. The results demonstrate the effect of the investigated parameters on the flow.

Keywords: Heat Transfer Coefficient, Minimum distance jet impingement, Numerical simulation, Dimensionless coefficients.

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Authors: Tomohiro Ando, Satoshi Yamashita

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The objective of this study is to propose a statistical modeling method which enables simultaneous term structure estimation of the risk-free interest rate, hazard and loss given default, incorporating the characteristics of the bond issuing company such as credit rating and financial information. A reduced form model is used for this purpose. Statistical techniques such as spline estimation and Bayesian information criterion are employed for parameter estimation and model selection. An empirical analysis is conducted using the information on the Japanese bond market data. Results of the empirical analysis confirm the usefulness of the proposed method.

Keywords: Empirical Bayes, Hazard term structure, Loss given default.

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Authors: S. Srinivasa Moorthy, K. Manonmani

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The new, polymer composites consisting of e-glass fiber reinforcement with titanium oxide filler in the double bonded unsaturated polyester resin matrix were made. The glass fiber and titanium oxide reinforcement composites were made in three different fiber lengths (3cm, 5cm, and 7cm), filler content (2 wt%, 4 wt%, and 6 wt%) and fiber content (20 wt%, 40 wt%, and 60 wt%). 27 different compositions were fabricated and a sequence of experiments were carried out to determine tensile strength and impact strength. The vital influencing factors fiber length, fiber content and filler content were chosen as 3 factors in 3 levels of Taguchi’s L₉ orthogonal array. The influences of parameters were determined for tensile strength and impact strength by Analysis of variance (ANOVA) and S/N ratio. Using Artificial Neural Network (ANN) an expert system was devised to predict the properties of hybrid reinforcement GFRP composites. The predict models were experimentally proved with the maximum coincidence.

Keywords: Analysis of variance (ANOVA), Artificial neural network (ANN), Polymer composites, Taguchi’s orthogonal array.

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Authors: Jan Busch, Sebastian Schneider, Konja Knüppel, Peter Nyhuis

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In production processes, assembly conceals a considerable potential for increased efficiency in terms of lowering production costs. Due to the individualisation of customer requirements, product variants have increased in recent years. Simultaneously, the portion of automated production systems has increased. A challenge is to adapt the flexibility and adaptability of automated systems to these changes. The Institute for Production Systems and Logistics developed an aerodynamic orientation system for feeding technology. When changing to other components, only four parameters must be adjusted. The expenditure of time for setting parameters is high. An objective therefore is developing an optimisation algorithm for automatic parameter configuration. Know how regarding the interaction of the four parameters and their effect on the sizes to be optimised is required in order to be able to develop a more efficient algorithm. This article introduces an analysis of the interactions between parameters and their influence on the quality of feeding.

Keywords: Aerodynamic feeding system, design of experiments, interactions between parameters.

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Authors: K. Kalaiselvan, K. Sekar, S. Elavarasi

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The use of laser beam welding for joining titanium and aluminum offers more advantages compared with conventional joining processes. Dissimilar metal combination is very much needed for aircraft structural industries and research activities. The quality of a weld joint is directly influenced by the welding input parameters. The common problem that is faced by the manufactures is the control of the process parameters to obtain a good weld joint with minimal detrimental. To overcome this issue, various parameters can be preferred to obtain quality of weld joint. In this present study an overall literature review on processing parameters such as offset distance, welding speed, laser power, shielding gas and filler metals are discussed with the effects on quality weldment. Additionally, mechanical properties of welds joint are discussed. The aim of the report is to review the recent progress in the welding of dissimilar titanium (Ti) and aluminum (Al) alloys to provide a basis for follow up research.

Keywords: Laser beam welding, titanium, aluminum, process parameters.

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Authors: Sanjay Kumar Srivastava, Anu Rani Sharma, Kamna Sachdeva

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Every year, fog formation over the Indo-Gangetic Plains (IGPs) of Indian region during the winter months of December and January is believed to create numerous hazards, inconvenience, and economic loss to the inhabitants of this densely populated region of Indian subcontinent. The aim of the paper is to analyze the spatial and temporal variability of winter fog over IGPs. Long term ground observations of visibility and other meteorological parameters (1971-2010) have been analyzed to understand the formation of fog phenomena and its relevance during the peak winter months of January and December over IGP of India. In order to examine the temporal variability, time series and trend analysis were carried out by using the Mann-Kendall Statistical test. Trend analysis performed by using the Mann-Kendall test, accepts the alternate hypothesis with 95% confidence level indicating that there exists a trend. Kendall tau’s statistics showed that there exists a positive correlation between time series and fog frequency. Further, the Theil and Sen’s median slope estimate showed that the magnitude of trend is positive. Magnitude is higher during January compared to December for the entire IGP except in December when it is high over the western IGP. Decade wise time series analysis revealed that there has been continuous increase in fog days. The net overall increase of 99 % was observed over IGP in last four decades. Diurnal variability and average daily persistence were computed by using descriptive statistical techniques. Geo-statistical analysis of fog was carried out to understand the spatial variability of fog. Geo-statistical analysis of fog revealed that IGP is a high fog prone zone with fog occurrence frequency of more than 66% days during the study period. Diurnal variability indicates the peak occurrence of fog is between 06:00 and 10:00 local time and average daily fog persistence extends to 5 to 7 hours during the peak winter season. The results would offer a new perspective to take proactive measures in reducing the irreparable damage that could be caused due to changing trends of fog.

Keywords: Fog, climatology, Mann-Kendall test, trend analysis, spatial variability, temporal variability, visibility.

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Authors: F. Urem, K. Fertalj, Ž. Mikulić

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This paper presents the possibilities of using Weibull statistical distribution in modeling the distribution of defects in ERP systems. There follows a case study, which examines helpdesk records of defects that were reported as the result of one ERP subsystem upgrade. The result of the applied modeling is in modeling the reliability of the ERP system from a user perspective with estimated parameters like expected maximum number of defects in one day or predicted minimum of defects between two upgrades. Applied measurement-based analysis framework is proved to be suitable in predicting future states of the reliability of the observed ERP subsystems.

Keywords: ERP, reliability, Weibull

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Authors: A. Pashayev, C. Ardil, R. Sadiqov

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Various methods of geofield parameters restoration (by algebraic polynoms; filters; rational fractions; interpolation splines; geostatistical methods – kriging; search methods of nearest points – inverse distance, minimum curvature, local – polynomial interpolation; neural networks) have been analyzed and some possible mistakes arising during geofield surface modeling have been presented.

Keywords: interpolation methods, geofield parameters, neural networks.

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Authors: Nazif Çalış, Murat Erişoğlu, Hamza Erol, Tayfun Servi

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In the recent works related with mixture discriminant analysis (MDA), expectation and maximization (EM) algorithm is used to estimate parameters of Gaussian mixtures. But, initial values of EM algorithm affect the final parameters- estimates. Also, when EM algorithm is applied two times, for the same data set, it can be give different results for the estimate of parameters and this affect the classification accuracy of MDA. Forthcoming this problem, we use Self Organizing Mixture Network (SOMN) algorithm to estimate parameters of Gaussians mixtures in MDA that SOMN is more robust when random the initial values of the parameters are used [5]. We show effectiveness of this method on popular simulated waveform datasets and real glass data set.

Keywords: Self Organizing Mixture Network, MixtureDiscriminant Analysis, Waveform Datasets, Glass Identification, Mixture of Multivariate Normal Distributions

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Authors: Jung-Hong Hong, Jing-Cen Yang, Cai-Yu Ou

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The analysis of geographic inequality heavily relies on the use of location-enabled statistical data and quantitative measures to present the spatial patterns of the selected phenomena and analyze their differences. To protect the privacy of individual instance and link to administrative units, point-based datasets are spatially aggregated to area-based statistical datasets, where only the overall status for the selected levels of spatial units is used for decision making. The partition of the spatial units thus has dominant influence on the outcomes of the analyzed results, well known as the Modifiable Areal Unit Problem (MAUP). A new spatial reference framework, the Taiwan Geographical Statistical Classification (TGSC), was recently introduced in Taiwan based on the spatial partition principles of homogeneous consideration of the number of population and households. Comparing to the outcomes of the traditional township units, TGSC provides additional levels of spatial units with finer granularity for presenting spatial phenomena and enables domain experts to select appropriate dissemination level for publishing statistical data. This paper compares the results of respectively using TGSC and township unit on the mortality data and examines the spatial characteristics of their outcomes. For the mortality data between the period of January 1^st, 2008 and December 31^st, 2010 of the Taitung County, the all-cause age-standardized death rate (ASDR) ranges from 571 to 1757 per 100,000 persons, whereas the 2^nd dissemination area (TGSC) shows greater variation, ranged from 0 to 2222 per 100,000. The finer granularity of spatial units of TGSC clearly provides better outcomes for identifying and evaluating the geographic inequality and can be further analyzed with the statistical measures from other perspectives (e.g., population, area, environment.). The management and analysis of the statistical data referring to the TGSC in this research is strongly supported by the use of Geographic Information System (GIS) technology. An integrated workflow that consists of the tasks of the processing of death certificates, the geocoding of street address, the quality assurance of geocoded results, the automatic calculation of statistic measures, the standardized encoding of measures and the geo-visualization of statistical outcomes is developed. This paper also introduces a set of auxiliary measures from a geographic distribution perspective to further examine the hidden spatial characteristics of mortality data and justify the analyzed results. With the common statistical area framework like TGSC, the preliminary results demonstrate promising potential for developing a web-based statistical service that can effectively access domain statistical data and present the analyzed outcomes in meaningful ways to avoid wrong decision making.

Keywords: Mortality map, spatial patterns, statistical area, variation.

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Authors: Rashid S. S., Alam M. Z.

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A statistical optimization of the saccharification process of EFB was studied. The statistical analysis was done by applying faced centered central composite design (FCCCD) under response surface methodology (RSM). In this investigation, EFB dose, enzyme dose and saccharification period was examined, and the maximum 53.45% (w/w) yield of reducing sugar was found with 4% (w/v) of EFB, 10% (v/v) of enzyme after 120 hours of incubation. It can be calculated that the conversion rate of cellulose content of the substrate is more than 75% (w/w) which can be considered as a remarkable achievement. All the variables, linear, quadratic and interaction coefficient, were found to be highly significant, other than two coefficients, one quadratic and another interaction coefficient. The coefficient of determination (R2) is 0.9898 that confirms a satisfactory data and indicated that approximately 98.98% of the variability in the dependent variable, saccharification of EFB, could be explained by this model.

Keywords: Face centered central composite design (FCCCD), Liquid state bioconversion (LSB), Palm oil mill effluent, Trichoderma reesei RUT C-30.

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Authors: Nebi Gedik

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One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: Wave atom transform, statistical features, multi-resolution representation, mammogram.

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Authors: M.Ghazvini, S. A. Monadjemi, N. Movahhedinia, K. Jamshidi

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In this article, a method has been offered to classify normal and defective tiles using wavelet transform and artificial neural networks. The proposed algorithm calculates max and min medians as well as the standard deviation and average of detail images obtained from wavelet filters, then comes by feature vectors and attempts to classify the given tile using a Perceptron neural network with a single hidden layer. In this study along with the proposal of using median of optimum points as the basic feature and its comparison with the rest of the statistical features in the wavelet field, the relational advantages of Haar wavelet is investigated. This method has been experimented on a number of various tile designs and in average, it has been valid for over 90% of the cases. Amongst the other advantages, high speed and low calculating load are prominent.

Keywords: Defect detection, tile and ceramic quality inspection, wavelet transform, classification, neural networks, statistical features.

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Authors: Famoriji J.Oluwole

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This research work examines the effect of variations of metrological parameters on the tropospheric radio refractivity during dry and raining seasons for Akure in 2013. The daily averages of radio refractivity during dry (January) and raining (August) seasons were calculated from the data obtained from the Nigeria Metrological Agency (NIMET). The data that was used for the computation of radio refractivity is a daily interval of the variations of metrological parameters for each day in the troposphere for Akure. Consequently, the daily averages of radio refractivity during raining season (August) were greater than the results in dry season (January) as a result of the variations in meteorological parameters such as temperature, humidity and atmospheric pressure in the lower troposphere.

Keywords: Troposphere, Radio refractivity, Akure, Meteorological parameters.

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Authors: Abdullah Y. Al-Hossain

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This paper considers inference under progressive type II censoring with a compound Rayleigh failure time distribution. The maximum likelihood (ML), and Bayes methods are used for estimating the unknown parameters as well as some lifetime parameters, namely reliability and hazard functions. We obtained Bayes estimators using the conjugate priors for two shape and scale parameters. When the two parameters are unknown, the closed-form expressions of the Bayes estimators cannot be obtained. We use Lindley.s approximation to compute the Bayes estimates. Another Bayes estimator has been obtained based on continuous-discrete joint prior for the unknown parameters. An example with the real data is discussed to illustrate the proposed method. Finally, we made comparisons between these estimators and the maximum likelihood estimators using a Monte Carlo simulation study.

Keywords: Progressive type II censoring, compound Rayleigh failure time distribution, maximum likelihood estimation, Bayes estimation, Lindley's approximation method, Monte Carlo simulation.

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Authors: Hossam El-din H. Ahmed, Hamdy M. Kalash, Osama S. Farag Allah

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This paper investigates the encryption efficiency of RC6 block cipher application to digital images, providing a new mathematical measure for encryption efficiency, which we will call the encryption quality instead of visual inspection, The encryption quality of RC6 block cipher is investigated among its several design parameters such as word size, number of rounds, and secret key length and the optimal choices for the best values of such design parameters are given. Also, the security analysis of RC6 block cipher for digital images is investigated from strict cryptographic viewpoint. The security estimations of RC6 block cipher for digital images against brute-force, statistical, and differential attacks are explored. Experiments are made to test the security of RC6 block cipher for digital images against all aforementioned types of attacks. Experiments and results verify and prove that RC6 block cipher is highly secure for real-time image encryption from cryptographic viewpoint. Thorough experimental tests are carried out with detailed analysis, demonstrating the high security of RC6 block cipher algorithm. So, RC6 block cipher can be considered to be a real-time secure symmetric encryption for digital images.

Keywords: Block cipher, Image encryption, Encryption quality, and Security analysis.

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Authors: Mustafa M. Donma, Orkide Donma

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Obesity and weight gain are associated with increased risk of developing cardiovascular diseases and the progression of liver fibrosis. Aspartate transaminase–to-platelet count ratio index (APRI) and fibrosis-4 (FIB-4) were primarily considered as the formulas capable of differentiating hepatitis from cirrhosis. However, to the best of our knowledge, their status in children is not clear. The aim of this study is to determine APRI and FIB-4 status in obese (OB) children and compare them with values found in children with normal body mass index (N-BMI). A total of 68 children examined in the outpatient clinics of the Pediatrics Department in Tekirdag Namik Kemal University Medical Faculty were included in the study. Two groups were constituted. In the first group, 35 children with N-BMI, whose age- and sex-dependent BMI indices vary between 15 and 85 percentiles, were evaluated. The second group comprised 33 OB children whose BMI percentile values were between 95 and 99. Anthropometric measurements and routine biochemical tests were performed. Using these parameters, values for the related indices, BMI, APRI, and FIB-4, were calculated. Appropriate statistical tests were used for the evaluation of the study data. The statistical significance degree was accepted as p < 0.05. In the OB group, values found for APRI and FIB-4 were higher than those calculated for the N-BMI group. However, there was no statistically significant difference between the N-BMI and OB groups in terms of APRI and FIB-4. A similar pattern was detected for triglyceride (TRG) values. The correlation coefficient and degree of significance between APRI and FIB-4 were r = 0.336 and p = 0.065 in the N-BMI group. On the other hand, they were r = 0.707 and p = 0.001 in the OB group. Associations of these two indices with TRG have shown that this parameter was strongly correlated (p < 0.001) both with APRI and FIB-4 in the OB group, whereas no correlation was calculated in children with N-BMI. TRG are associated with an increased risk of fatty liver, which can progress to severe clinical problems such as steatohepatitis, which can lead to liver fibrosis. TRG are also independent risk factors for cardiovascular disease. In conclusion, the lack of correlation between TRG and APRI as well as FIB-4 in children with N-BMI, along with the detection of strong correlations of TRG with these indices in OB children, was the indicator of the possible onset of the tendency towards the development of fatty liver in OB children. This finding also pointed out the potential risk for cardiovascular pathologies in OB children. The nature of the difference between APRI vs. FIB-4 correlations in N-BMI and OB groups (no correlation vs. high correlation), respectively, may be the indicator of the importance of involving age and alanine transaminase parameters in addition to AST and PLT in the formula designed for FIB-4.

Keywords: APRI, FIB-4, obesity, triglycerides.

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Authors: Houman Saedi

Abstract:

Hot Mix Asphalt (HMA) is one of the most commonest constructed asphalts in Iran and the quality control of constructed roads with HMA have been always paid due attention by researchers. The quality control of constructed roads with this method is being usually carried out by measuring volumetric parameters of HMA marshall samples. One of the important parameters that has a critical role in changing these volumetric parameters is “compaction temperature"; which as a result of its changing, volumetric parameters of Marshall Samples and subsequently constructed asphalt is encountered with variations. In this study, considering the necessity of preservation of the compaction temperature, the effect of various temperatures on Hot Mix Asphalt (HMA) samples properties has been evaluated. As well, to evaluate the effect of this parameter on different grading, two different grading (Top coat index grading and binder index grading) have been used and samples were compacted at 5 various temperatures.

Keywords: Compaction Temperature, HMA, Volumetric Parameters, Marshall Method

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Authors: S. Grouni, R. Ibtiouen, M. Kidouche, O. Touhami

Abstract:

Induction machine models used for steady-state and transient analysis require machine parameters that are usually considered design parameters or data. The knowledge of induction machine parameters is very important for Indirect Field Oriented Control (IFOC). A mismatched set of parameters will degrade the response of speed and torque control. This paper presents an improvement approach on rotor time constant adaptation in IFOC for Induction Machines (IM). Our approach tends to improve the estimation accuracy of the fundamental model for flux estimation. Based on the reduced order of the IM model, the rotor fluxes and rotor time constant are estimated using only the stator currents and voltages. This reduced order model offers many advantages for real time identification parameters of the IM.

Keywords: Indirect Field Oriented Control (IFOC), InductionMachine (IM), Rotor Time Constant, Parameters ApproachAdaptation. Optimum rotor flux.

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Authors: Meriem Bahij, Ahmed Nafidi, Boujemâa Achchab, Sílvio M. A. Gama, José A. O. Matos

Abstract:

Stochastic modeling concerns the use of probability to model real-world situations in which uncertainty is present. Therefore, the purpose of stochastic modeling is to estimate the probability of outcomes within a forecast, i.e. to be able to predict what conditions or decisions might happen under different situations. In the present study, we present a model of a stochastic diffusion process based on the bi-Weibull distribution function (its trend is proportional to the bi-Weibull probability density function). In general, the Weibull distribution has the ability to assume the characteristics of many different types of distributions. This has made it very popular among engineers and quality practitioners, who have considered it the most commonly used distribution for studying problems such as modeling reliability data, accelerated life testing, and maintainability modeling and analysis. In this work, we start by obtaining the probabilistic characteristics of this model, as the explicit expression of the process, its trends, and its distribution by transforming the diffusion process in a Wiener process as shown in the Ricciaardi theorem. Then, we develop the statistical inference of this model using the maximum likelihood methodology. Finally, we analyse with simulated data the computational problems associated with the parameters, an issue of great importance in its application to real data with the use of the convergence analysis methods. Overall, the use of a stochastic model reflects only a pragmatic decision on the part of the modeler. According to the data that is available and the universe of models known to the modeler, this model represents the best currently available description of the phenomenon under consideration.

Keywords: Diffusion process, discrete sampling, likelihood estimation method, simulation, stochastic diffusion equation, trends functions, bi-parameters Weibull density function.

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Authors: V. Markogianni, D. Kalivas, G. Petropoulos, E. Dimitriou

Abstract:

Lake water quality monitoring in combination with the use of earth observation products constitutes a major component in many water quality monitoring programs. Landsat 8 images of Trichonis Lake (Greece) acquired on 30/10/2013 and 30/08/2014 were used in order to explore the possibility of Landsat 8 to estimate water quality parameters and particularly CDOM absorption at specific wavelengths, chlorophyll-a and nutrient concentrations in this oligotrophic freshwater body, characterized by inexistent quantitative, temporal and spatial variability. Water samples have been collected at 22 different stations, on late August of 2014 and the satellite image of the same date was used to statistically correlate the in-situ measurements with various combinations of Landsat 8 bands in order to develop algorithms that best describe those relationships and calculate accurately the aforementioned water quality components. Optimal models were applied to the image of late October of 2013 and the validation of the results was conducted through their comparison with the respective available in-situ data of 2013. Initial results indicated the limited ability of the Landsat 8 sensor to accurately estimate water quality components in an oligotrophic waterbody. As resulted by the validation process, ammonium concentrations were proved to be the most accurately estimated component (R = 0.7), followed by chl-a concentration (R = 0.5) and the CDOM absorption at 420 nm (R = 0.3). In-situ nitrate, nitrite, phosphate and total nitrogen concentrations of 2014 were measured as lower than the detection limit of the instrument used, hence no statistical elaboration was conducted. On the other hand, multiple linear regression among reflectance measures and total phosphorus concentrations resulted in low and statistical insignificant correlations. Our results were concurrent with other studies in international literature, indicating that estimations for eutrophic and mesotrophic lakes are more accurate than oligotrophic, owing to the lack of suspended particles that are detectable by satellite sensors. Nevertheless, although those predictive models, developed and applied to Trichonis oligotrophic lake are less accurate, may still be useful indicators of its water quality deterioration.

Keywords: Landsat 8, oligotrophic lake, remote sensing, water quality.

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Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

Abstract:

Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: Classification, fuzzy, inspection system, image analysis.

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