Honeymoon with IWBs: A qualitative insight in primary students' views on instruction with interactive whiteboard

The main purpose of this study was to investigate the views of primary students about interactive whiteboard [IWB] use in their classes from attitudinal and pedagogical perspectives. Research was designed as an empirical approach to phenomenology. Data was collected from fifty primary students (fourth to eighth) through focus group interviews. Nvivo 9 qualitative data analysis software was used to analyze data. Results showed that students like instruction with IWB especially for such reasons/capabilities as practical and economical use, better visual presentation, and test-based use. Students were predominantly uncomfortable with the technical problems. They believed that instruction with IWB positively impacted their learning especially because of visualization and contextualization, effective presentation, test-based use, and motivational factors. Finally it was inferred that IWBs were not used to their full potential, and both technical problems and common practices indicated that teachers were still at an initial stage of transmission to instruction with IWB and they needed both technical and pedagogical training.     

A combination of Genetic Algorithm,Particle Swarm Optimization and Neural Network for palmprint recognition

In this study, a new approach to the palmprint recognition phase is presented. 2D Gabor filters are used for feature extraction of palmprints. After Gabor filtering, standard deviations are computed in order to generate the palmprint feature vector. Genetic Algorithm-based feature selection is used to select the best feature subset from the palmprint feature set. An Artificial Neural Network (ANN) based on hybrid algorithm combining Particle Swarm Optimization (PSO) algorithm with back-propagation algorithms has been applied to the selected feature vectors for recognition of the persons. Network architecture and connection weights of ANN are evolved by a PSO method, and then, the appropriate network architecture and connection weights are fed into ANN. Recognition rate equal to 96% is obtained by using conjugate gradient descent algorithm.

     

WATER QUALITY ASSESSMENT AND APPORTIONMENT OF POLLUTION SOURCES OF TIGRIS RIVER (TURKEY) USING MULTIVARIATE STATISTICAL TECHNIQUES—A CASE STUDY

The Tigris is one of the most important transboundary rivers in western Asia and originates in the Toros mountains of the Eastern Anatolia region of Turkey. Multivariate statistical techniques, such as cluster analysis (CA), principal component analysis (PCA) and factor analysis (FA), were applied for the evaluation of temporal/spatial variations and the interpretation of a water quality data set for the Tigris River, which was obtained during 1 year of monitoring. This study presents the usefulness of multivariate statistical techniques for the evaluation and interpretation of complex water quality data sets and apportionment of pollution sources/factors to obtain better information about water quality and the design of a monitoring network for the effective management of water resources. Hierarchical CA grouped 12 months into two periods (the first and second periods) and classified seven monitoring sites into three groups, that is, less polluted sites, medium polluted sites and highly polluted sites, based on similarities in the water quality characteristics. PCA/FA identified five factors in the data structure, which explained 77.5% of the total variance of the data set. This allowed us to group the selected parameters according to common features and to evaluate the influence of each group on the overall variation in water quality. Varifactors obtained from the factor analysis indicated that the parameters responsible for water quality variation were mainly related to soluble salts (natural), organic pollution and nutrients (anthropogenic). Copyright © 2011 John Wiley & Sons, Ltd.     

The ratio of crystallinity and thermodynamical interactions of polycaprolactone with some aliphatic esters and aromatic solvents by inverse gas chromatography

Summary The retention diagrams of benzene, toluene, ethyl benzene, chloro benzene, n-propyl benzene, isopropyl benzene, methyl acetate, ethyl acetate, n-propyl acetate, n-butyl acetate and isoamyl acetate on the polycaprolactone were plotted at temperatures between 70 and 140^oC by inverse gas chromatography technique. Percent crystallinity of polycaprolactone were obtained at temperatures below melting point from the retention diagrams of benzene, toluene and ethyl benzene. It was concluded that the data obtained by inverse gas chromatography were comparable those of obtained by differential scanning calorimetry. Specific retention volume, V_g^o, Flory-Huggins polymer-solvent interaction parameters, ₁₂, the weight fraction activity coefficients of the solvents at infinite dilution, ₁, effective exchange energy parameters, X_eff were determined. Later, the partial molar heat of sorption, H_1,sorp and the partial molar heat of mixing, H₁ were obtained from the slope of the logarithm of specific retention volume, Ln V_g^o versus 1/T plot and from the slope of the logarithm of the weight fraction activity coefficients, ₁versus 1/T plot, respectively.     

Experimental investigation of steel fiber reinforced concrete box beams under bending

Reduction of dead weight of a reinforced-concrete (RC) structure without too much concession in its load carrying capacity has always been an attractive study subject because it engenders (1) a decrease in dimensions of the members, (2) a decrease in the reinforcement steel, and (3) a decrease in lateral inertia forces during severe earthquakes. In this study, nine RC beams of outer dimensions of 300 × 300 × 2000 mm, six of which are box beams, designed and produced using a C20 class steel fiber concrete, (SFRC) with the commonly used steel fiber type of Dramix-RC-80/0.60-BN at a dosage of 30 kg/m³, are tested under bending. The mechanical behaviours of all these nine beams under bending are recorded from the beginning of the test till the ultimate failure of the tensile reinforcement in a two-point beam-loading setup. The proportions of (1) loss in ultimate load versus reduction in dead weight and (2) (ultimate experimental load)/(ultimate theoretical load) of the SFRC box beams are determined for two different box thicknesses. Dimensionless behaviour relationships of all the SFRC beams are determined, and the experimentally obtained relationship between the ratio of (actual ultimate load)/(theoretical ultimate load) and the ratio of (wall thickness)/(beam height) for the SFRC box beams is expressed diagrammatically.     

About the Collatz conjecture

This paper refers to the Collatz conjecture. The origin and the formalization of the Collatz problem are presented in the first section, named “Introduction”. In the second section, entitled “Properties of the Collatz function”, we treat mainly the bijectivity of the Collatz function. Using the obtained results, we construct a (set of) binary tree(s) which “simulate(s)”– in a way that will be specified – the computations of the values of the Collatz function. In the third section, we give an “efficient” algorithm for computing the number of iterations (recursive calls) of the Collatz function. A comparison between our algorithm and the standard one is also presented, the first being at least 2.25 “faster” (3.00 in medium). Finally, we describe a class of natural numbers for which the conjecture is true. Received 28 April 1997 / 10 June 1997     

Comparison of a new algorithm with the supervised classifications

In this study, a new classification algorithm in which only the selected pixels have been attempted to be classified (selected pixels classification: SPC) has been introduced and compared with the well known supervised classification methods such as maximum likelihood, minimum distance, nearest neighbour and condensed nearest neighbour. To examine the algorithm, Landsat Thematic Mapper (TM) data have been used to classify the crop cover in the selected region. It is clearly demonstrated that the SPC method has the higher accuracy with comparable CPU times.     

An exponential approach for the system of nonlinear delay integro-differential equations describing biological species living together

Neural Computing and Applications - In this paper, we consider a system of nonlinear delay integro-differential equations with convolution kernels, which arises in biology. This problem...     

Investigating the effect of production process of ball mill refiner on some physical quality parameters of compound chocolate: response surface methodology approach

Chocolate compound was produced using ball mill refiner, and the effect of agitator shaft speed and refining time on the physical quality parameters (particle size, colour and steady‐state rheology) of compound chocolate was determined using response surface methodology. The shaft speed and refining time range were selected between 40–60 r.p.m. and 10–30 min, respectively. Determination coefficient of the models established for particle size, Newtonian viscosity and colour parameters (brightness, chroma and hue angle) were found to be very close to unity. Increasing shaft speed and time induced a reduction in particle size and an increase in viscosity of the samples. Temperature sweep test was also performed, and the obtained data were successfully fitted to Arrhenius equation to calculate the corresponding parameters representing temperature dependency of the compounds. The results highlighted that the establishment of such models can provide essential information in terms of optimisation of production processes regarding usage purpose of the compound chocolate.