The impact of micro‐ and macroergonomics considerations on appropriate technology transfer decisions in developing countries: The case of Turkey

The research presented in this paper aims to support the decision process of appropriate technology transfer to industrially developing countries by improving a broader understanding of relationships between the key micro‐ and macroergonomics factors and the technology alternatives. The methodology involves knowledge acquisition, identifying and categorizing a holistic set of key criteria about technology transfer with respect to ergonomics. This work attempts briefly to identify factors affecting the success of technology transfer in order to reduce the potential of incompatibilities with respect to micro‐ and macroergonomics and to optimize the decision process of managers. The objective of the decision model, based on the analytic hierarchy process (AHP), determines the global priority weights for different technology alternatives and examines the critical factors and benefits, which affect the appropriateness of technology transfer. © 2007 Wiley Periodicals, Inc. Hum Factors Man 17: 1–19, 2007.     

Poly(Acrylamide-Sepiolite) Composite Hydrogels: Preparation, Swelling and Dye Adsorption Properties

Summary Polymer-clay hydrogel composite was prepared on the basis of polyacrylamide (PAAm) gel containing the clay mineral sepiolite. The properties of swelling and dye adsorption of poly(acrylamide-sepiolite) (AAm/Sep) composite hydrogel were investigated. The parameters of swelling and diffusion in water and dye solutions were calculated for the AAm and AAm/Sep hydrogels. It was found that the equilibrium swelling degree of obtained composite higher than that of AAm gel. Spectroscopic analysis of composite and composite-dye systems was done with FT-IR method. Adsorption of monovalent cationic dyes such as Basic Blue 12 (BB-12) Basic Blue 9 (BB-9), and Basic Violet 1 (BV-1), was studied on the composite. In the adsorption experiments, S (Sigmoidal) type for composite gel adsorption isotherms in the Giles classification system was found. Adsorption studies indicated that the amounts of adsorbed dyes on the AAm/Sep composite hydrogel were increased with following order; BB-12 > BB-9 > BV-1. The composite hydrogel may be considered as good candidate for environmental application to retain more water and dyes.     

Comparative study on classifying human activities with miniature inertial and magnetic sensors

This paper provides a comparative study on the different techniques of classifying human activities that are performed using body-worn miniature inertial and magnetic sensors. The classification techniques implemented and compared in this study are: Bayesian decision making (BDM), a rule-based algorithm (RBA) or decision tree, the least-squares method (LSM), the k-nearest neighbor algorithm (k-NN), dynamic time warping (DTW), support vector machines (SVM), and artificial neural networks (ANN). Human activities are classified using five sensor units worn on the chest, the arms, and the legs. Each sensor unit comprises a tri-axial gyroscope, a tri-axial accelerometer, and a tri-axial magnetometer. A feature set extracted from the raw sensor data using principal component analysis (PCA) is used in the classification process. A performance comparison of the classification techniques is provided in terms of their correct differentiation rates, confusion matrices, and computational cost, as well as their pre-processing, training, and storage requirements. Three different cross-validation techniques are employed to validate the classifiers. The results indicate that in general, BDM results in the highest correct classification rate with relatively small computational cost.     

An interdisciplinary heuristic evaluation method for universal building design

This study highlights how heuristic evaluation as a usability evaluation method can feed into current building design practice to conform to universal design principles. It provides a definition of universal usability that is applicable to an architectural design context. It takes the seven universal design principles as a set of heuristics and applies an iterative sequence of heuristic evaluation in a shopping mall, aiming to achieve a cost-effective evaluation process. The evaluation was composed of three consecutive sessions. First, five evaluators from different professions were interviewed regarding the construction drawings in terms of universal design principles. Then, each evaluator was asked to perform the predefined task scenarios. In subsequent interviews, the evaluators were asked to re-analyze the construction drawings. The results showed that heuristic evaluation could successfully integrate universal usability into current building design practice in two ways: (i) it promoted an iterative evaluation process combined with multi-sessions rather than relying on one evaluator and on one evaluation session to find the maximum number of usability problems, and (ii) it highlighted the necessity of an interdisciplinary ad hoc committee regarding the heuristic abilities of each profession. A multi-session and interdisciplinary heuristic evaluation method can save both the project budget and the required time, while ensuring a reduced error rate for the universal usage of the built environments.     

Leveraging technological knowledge transfer by using fuzzy linear programming technique for multiattribute group decision making with fuzzy decision variables

Despite the importance of knowledge transfer for firms involved in foreign direct investment activities, this area has not received appropriate attention from the perspectives of both the knowledge transferor (i.e., MNC parent) and the knowledge recipient. To fill in the gap in the current literature we propose a model to understand the links between criteria complicating the transfer of knowledge and preferences that the company has to focus. This model is based on both the existing literature as well as views of company representatives and provides a useful methodology for identifying decision making problems on the transfer of knowledge. In this paper, we investigate the fuzzy linear programming technique (FLP) to analyze these links and for multiple attribute group decision making (MAGDM) problems with preference information on criteria. To reflect the decision maker’s subjective preference information and to determine the weight vector of attributes, the technique for order preference by similarity to ideal solution (TOPSIS) developed by Hwang and Yoon (1995) and the linear programming technique for multidimensional analysis of preference (LINMAP) developed by Sirinivasan and Shocker (Psychometrica 38:337–369, 1973) are used.     

A new extended LMI-based robust gain scheduled state feedback <Emphasis Type="Italic">H</Emphasis><Subscript>2</Subscript> controller design

This paper proposes an improved robust H ₂ state feedback control synthesis for the Linear Parameter Varying (LPV) systems by attaining the affine quadratic stability. In place of standard H ₂ computation in the literature, a new H ₂ computation based on extended Linear Matrix Inequality (LMI) is improved by means of the slack variable, where it is obtained by separation Lyapunov matrix from system matrix. State feedback H ₂ synthesis is improved for the systems, and is more effective and less conservative than the common ones in the literature. Therefore, the less conservative results are obtained for gain scheduling controller design for LPV systems. The numerical examples are presented to show the superiority of the proposed controller design.     

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.

     

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.