The Development and Examination of a Teaching Commitment Scale for Elementary School Health and Physical Education Teachers

The purpose of this study was to develop and examine a Teaching Commitment Scale of Health and Physical Education (TCS-HPE) for Taiwanese elementary school teachers. First of all, based on teaching commitment related theory and literatures to develop a original scale with 40 items, later both stratified random sampling and cluster sampling were used to sample participants. During the first stage, 300 teachers were sampled and 251 valid scales (83.7%) returned. Later, the data was analyzed by exploratory factor analysis to obtain 74.30% of total variance for the construct validity. The Cronbach-s alpha coefficient of sum scale reliability was 0.94, and subscale coefficients were between 0.80 and 0.96. In the second stage, 400 teachers were sampled and 318 valid scales (79.5%) returned. Finally, this study used confirmatory factor analysis to test validity and reliability of TCS-HPE. The result showed that the fit indexes reached acceptable criteria(¤ç2 (246 ) =557.64 , p

A New Approach to Workforce Planning

In today-s global and competitive market, manufacturing companies are working hard towards improving their production system performance. Most companies develop production systems that can help in cost reduction. Manufacturing systems consist of different elements including production methods, machines, processes, control and information systems. Human issues are an important part of manufacturing systems, yet most companies do not pay sufficient attention to them. In this paper, a workforce planning (WP) model is presented. A non-linear programming model is developed in order to minimize the hiring, firing, training and overtime costs. The purpose is to determine the number of workers for each worker type, the number of workers trained, and the number of overtime hours. Moreover, a decision support system (DSS) based on the proposed model is introduced using the Excel-Lingo software interfacing feature. This model will help to improve the interaction between the workers, managers and the technical systems in manufacturing.

Geochemical Assessment of Metal Concentrations in Mangrove Sediments along Mumbai Coast, India

Two short sediment cores collected from mangrove areas of Manori and Thane creeks along Mumbai coast were analysed for sediment composition and metals (Fe, Mn, Cu, Pb, Co, Ni, Zn, Cr and V). The statistical analysis of Pearson correlation matrix proved that there is a significant relationship between metal concentration and finer grain size in Manori creek while poor correlation was observed in Thane creek. Based on the enrichment factor, the present metal to background metal ratios clearly reflected maximum enrichment of Cu and Pb in Manori creek and Mn in Thane creek. Geoaccumulation index calculated indicate that the study area is unpolluted with respect to Fe, Mn, Co, Ni, Zn and Cr in both the cores while moderately polluted with Cu and Pb in Manori creek. Based on contamination degree, both the core sediments were found to be considerably contaminated with metals.

Influence of Garbage Leachate on Soil Reaction,Salinity and Soil Organic Matter in East of Isfahan

During this day a considerable amount of Leachate is produced with high amounts of organic material and nutrients needed plants. This study has done in order to scrutinize the effect of Leachate compost on the pH, EC and organic matter percentage in the form of statistical Factorial plan through randomizing block design with three main and two minor treatments and also three replications during three six month periods. Major treatments include N: Irrigation with the region-s well water as a control, I: Frequent irrigation with well water and Leachate, C: Mixing Leachate and water well (25 percent leachate + 75 percent ordinary well water) and secondary treatments, include DI: surface drip irrigation and SDI: sub surface drip irrigation. Results of this study indicated significant differences between treatments and also there were mixing up with the control treatment in the reduction of pH, increasing soluble salts and also increasing the organic matter percentage. This increase is proportional to the amount of added Leachate and in the treatment also proportional to higher mixture of frequent treatment. Therefore, since creating an acidic pH increases the ability to absorb some nutrient elements such as phosphorus, iron, zinc, copper and manganese are increased and the other hand, organic materials also improve many physical and chemical properties of soil are used in Leachate trash Consider health issues as refined in the green belts around cities as a liquid fertilizer recommended.

Diagnostics of Fatigue Damage of Gas Turbine Engine Blades by Acoustic Emission Method

the work contains the results of complex investigation related to the evaluation of condition of working blades of gas turbine engines during fatigue tests by applying the acoustic emission method. It demonstrates the possibility of estimating the fatigue damage of blades in the process of factory tests. The acoustic emission criteria for detecting and testing the kinetics of fatigue crack distribution were detected. It also shows the high effectiveness of the method for non-destructive testing of condition of solid and cooled working blades for high-temperature gas turbine engines.

Lean Changeability – Evaluation and Design of Lean and Transformable Factories

In today-s turbulent environment, companies are faced with two principal challenges. On the one hand, it is necessary to produce ever more cost-effectively to remain competitive. On the other hand, factories need to be transformable in order to manage unpredictable changes in the corporate environment. To deal with these different challenges, companies use the philosophy of lean production in the first case, in the second case the philosophy of transformability. To a certain extent these two approaches follow different directions. This can cause conflicts when designing factories. Therefore, the Institute of Production Systems and Logistics (IFA) of the Leibniz University of Hanover has developed a procedure to allow companies to evaluate and design their factories with respect to the requirements of both philosophies.

DEA Method for Evaluation of EU Performance

The paper deals with an application of quantitative analysis – the Data Envelopment Analysis (DEA) method to performance evaluation of the European Union Member States, in the reference years 2000 and 2011. The main aim of the paper is to measure efficiency changes over the reference years and to analyze a level of productivity in individual countries based on DEA method and to classify the EU Member States to homogeneous units (clusters) according to efficiency results. The theoretical part is devoted to the fundamental basis of performance theory and the methodology of DEA. The empirical part is aimed at measuring degree of productivity and level of efficiency changes of evaluated countries by basic DEA model – CCR CRS model, and specialized DEA approach – the Malmquist Index measuring the change of technical efficiency and the movement of production possibility frontier. Here, DEA method becomes a suitable tool for setting a competitive/uncompetitive position of each country because there is not only one factor evaluated, but a set of different factors that determine the degree of economic development.

Three-dimensional Finite Element Analysis of the Front Cross Member of the Peugeot 405

Undoubtedly, chassis is one of the most important parts of a vehicle. Chassis that today are produced for vehicles are made up of four parts. These parts are jointed together by screwing. Transverse parts are called cross member. This study reviews the stress generated by cyclic laboratory loads in front cross member of Peugeot 405. In this paper the finite element method is used to simulate the welding process and to determine the physical response of the spot-welded joints. Analysis is done by the Abaqus software. The Stresses generated in cross member structure are generally classified into two groups: The stresses remained in form of residual stresses after welding process and the mechanical stress generated by cyclic load. Accordingly the total stress must be obtained by determining residual stress and mechanical stress separately and then sum them according to the superposition principle. In order to improve accuracy, material properties including physical, thermal and mechanical properties were supposed to be temperature-dependent. Simulation shows that maximum Von Misses stresses are located at special points. The model results are then compared to the experimental results which are reported by producing factory and good agreement is observed.

Reliability Analysis of Tubular Joints of Offshore Platforms in Malaysia

The oil and gas industry has moved towards Load and Resistance Factor Design through API RP2A - LRFD and the recently published international standard, ISO-19902, for design of fixed steel offshore structures. The ISO 19902 is intended to provide a harmonized design practice that offers a balanced structural fitness for the purpose, economy and safety. As part of an ongoing work, the reliability analysis of tubular joints of the jacket structure has been carried out to calibrate the load and resistance factors for the design of offshore platforms in Malaysia, as proposed in the ISO. Probabilistic models have been established for the load effects (wave, wind and current) and the tubular joints strengths. In this study the First Order Reliability Method (FORM), coded in MATLAB Software has been employed to evaluate the reliability index of the typical joints, designed using API RP2A - WSD and ISO 19902.

In Search of an SVD and QRcp Based Optimization Technique of ANN for Automatic Classification of Abnormal Heart Sounds

Artificial Neural Network (ANN) has been extensively used for classification of heart sounds for its discriminative training ability and easy implementation. However, it suffers from overparameterization if the number of nodes is not chosen properly. In such cases, when the dataset has redundancy within it, ANN is trained along with this redundant information that results in poor validation. Also a larger network means more computational expense resulting more hardware and time related cost. Therefore, an optimum design of neural network is needed towards real-time detection of pathological patterns, if any from heart sound signal. The aims of this work are to (i) select a set of input features that are effective for identification of heart sound signals and (ii) make certain optimum selection of nodes in the hidden layer for a more effective ANN structure. Here, we present an optimization technique that involves Singular Value Decomposition (SVD) and QR factorization with column pivoting (QRcp) methodology to optimize empirically chosen over-parameterized ANN structure. Input nodes present in ANN structure is optimized by SVD followed by QRcp while only SVD is required to prune undesirable hidden nodes. The result is presented for classifying 12 common pathological cases and normal heart sound.

Bridging Quantitative and Qualitative of Glaucoma Detection

Glaucoma diagnosis involves extracting three features of the fundus image; optic cup, optic disc and vernacular. Present manual diagnosis is expensive, tedious and time consuming. A number of researches have been conducted to automate this process. However, the variability between the diagnostic capability of an automated system and ophthalmologist has yet to be established. This paper discusses the efficiency and variability between ophthalmologist opinion and digital technique; threshold. The efficiency and variability measures are based on image quality grading; poor, satisfactory or good. The images are separated into four channels; gray, red, green and blue. A scientific investigation was conducted on three ophthalmologists who graded the images based on the image quality. The images are threshold using multithresholding and graded as done by the ophthalmologist. A comparison of grade from the ophthalmologist and threshold is made. The results show there is a small variability between result of ophthalmologists and digital threshold.

Factors Influencing B2c eCommerce Diffusion

Despite the fact that B2c eCommerce has become important in numerous economies, its adoption varies from country to country. This paper aims to identify the factors affecting (enabling or inhibiting) B2c eCommerce and to determine their quantitative impact on the diffusion of online sales across countries. A dynamic panel model analyzing the relationship between 13 factors (Macroeconomic, Demographic, Socio-Cultural, Infrastructural and Offer related) stemming from a complete literature analysis and the B2c eCommerce value in 45 countries over 9 years has been developed. Having a positive correlation coefficient, GDP, mobile penetration, Internet user penetration and credit card penetration resulted as enabling drivers of the B2c eCommerce value across countries, whereas, having a negative correlation coefficient,equal distribution of income and the development of traditional retailing network act as inhibiting factors.

Simultaneous HPAM/SDS Injection in Heterogeneous/Layered Models

Although lots of experiments have been done in enhanced oil recovery, the number of experiments which consider the effects of local and global heterogeneity on efficiency of enhanced oil recovery based on the polymer-surfactant flooding is low and rarely done. In this research, we have done numerous experiments of water flooding and polymer-surfactant flooding on a five spot glass micromodel in different conditions such as different positions of layers. In these experiments, five different micromodels with three different pore structures are designed. Three models with different layer orientation, one homogenous model and one heterogeneous model are designed. In order to import the effect of heterogeneity of porous media, three types of pore structures are distributed accidentally and with equal ratio throughout heterogeneous micromodel network according to random normal distribution. The results show that maximum EOR recovery factor will happen in a situation where the layers are orthogonal to the path of mainstream and the minimum EOR recovery factor will happen in a situation where the model is heterogeneous. This experiments show that in polymer-surfactant flooding, with increase of angles of layers the EOR recovery factor will increase and this recovery factor is strongly affected by local heterogeneity around the injection zone.

Efficient System for Speech Recognition using General Regression Neural Network

In this paper we present an efficient system for independent speaker speech recognition based on neural network approach. The proposed architecture comprises two phases: a preprocessing phase which consists in segmental normalization and features extraction and a classification phase which uses neural networks based on nonparametric density estimation namely the general regression neural network (GRNN). The relative performances of the proposed model are compared to the similar recognition systems based on the Multilayer Perceptron (MLP), the Recurrent Neural Network (RNN) and the well known Discrete Hidden Markov Model (HMM-VQ) that we have achieved also. Experimental results obtained with Arabic digits have shown that the use of nonparametric density estimation with an appropriate smoothing factor (spread) improves the generalization power of the neural network. The word error rate (WER) is reduced significantly over the baseline HMM method. GRNN computation is a successful alternative to the other neural network and DHMM.

Performance Evaluation of Powder Metallurgy Electrode in Electrical Discharge Machining of AISI D2 Steel Using Taguchi Method

In this paper an attempt has been made to correlate the usefulness of electrodes made through powder metallurgy (PM) in comparison with conventional copper electrode during electric discharge machining. Experimental results are presented on electric discharge machining of AISI D2 steel in kerosene with copper tungsten (30% Cu and 70% W) tool electrode made through powder metallurgy (PM) technique and Cu electrode. An L18 (21 37) orthogonal array of Taguchi methodology was used to identify the effect of process input factors (viz. current, duty cycle and flushing pressure) on the output factors {viz. material removal rate (MRR) and surface roughness (SR)}. It was found that CuW electrode (made through PM) gives high surface finish where as the Cu electrode is better for higher material removal rate.

Issues in Spectral Source Separation Techniques for Plant-wide Oscillation Detection and Diagnosis

In the last few years, three multivariate spectral analysis techniques namely, Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Non-negative Matrix Factorization (NMF) have emerged as effective tools for oscillation detection and isolation. While the first method is used in determining the number of oscillatory sources, the latter two methods are used to identify source signatures by formulating the detection problem as a source identification problem in the spectral domain. In this paper, we present a critical drawback of the underlying linear (mixing) model which strongly limits the ability of the associated source separation methods to determine the number of sources and/or identify the physical source signatures. It is shown that the assumed mixing model is only valid if each unit of the process gives equal weighting (all-pass filter) to all oscillatory components in its inputs. This is in contrast to the fact that each unit, in general, acts as a filter with non-uniform frequency response. Thus, the model can only facilitate correct identification of a source with a single frequency component, which is again unrealistic. To overcome this deficiency, an iterative post-processing algorithm that correctly identifies the physical source(s) is developed. An additional issue with the existing methods is that they lack a procedure to pre-screen non-oscillatory/noisy measurements which obscure the identification of oscillatory sources. In this regard, a pre-screening procedure is prescribed based on the notion of sparseness index to eliminate the noisy and non-oscillatory measurements from the data set used for analysis.

Quantitative Genetics Researches on Milk Protein Systems of Romanian Grey Steppe Breed

The paper makes part from a complex research project on Romanian Grey Steppe, a unique breed in terms of biological and cultural-historical importance, on the verge of extinction and which has been included in a preservation programme of genetic resources from Romania. The study of genetic polymorphism of protean fractions, especially kappa-casein, and the genotype relations of these lactoproteins with some quantitative and qualitative features of milk yield represents a current theme and a novelty for this breed. In the estimation of the genetic parameters we used R.E.M.L. (Restricted Maximum Likelihood) method. The main lactoprotein from milk, kappa - casein (K-cz), characterized in the specialized literature as a feature having a high degree of hereditary transmission, behaves as such in the nucleus under study, a value also confirmed by the heritability coefficient (h2 = 0.57 %). We must mention the medium values for milk and fat quantity (h2=0.26, 0.29 %) and the fat and protein percentage from milk having a high hereditary influence h2 = 0.71 - 0.63 %. Correlations between kappa-casein and the milk quantity are negative and strong. Between kappa-casein and other qualitative features of milk (fat content 0.58-0.67 % and protein content 0.77- 0.87%), there are positive and very strong correlations. At the same time, between kappa-casein and β casein (β-cz), β lactoglobulin (β- lg) respectively, correlations are positive having high values (0.37 – 0.45 %), indicating the same causes and determining factors for the two groups of features.

Using Interval Constrained Petri Nets and Fuzzy Method for Regulation of Quality: The Case of Weight in Tobacco Factory

The existence of maximal durations drastically modifies the performance evaluation in Discrete Event Systems (DES). The same particularity may be found on systems where the associated constraints do not concern the time. For example weight measures, in chemical industry, are used in order to control the quantity of consumed raw materials. This parameter also takes a fundamental part in the product quality as the correct transformation process is based upon a given percentage of each essence. Weight regulation therefore increases the global productivity of the system by decreasing the quantity of rejected products. In this paper we present an approach based on mixing different characteristics theories, the fuzzy system and Petri net system to describe the behaviour. An industriel application on a tobacco manufacturing plant, where the critical parameter is the weight is presented as an illustration.