Rising product variety and complexity, shorter time frames to respond, and the continual need to gain new capabilities through innovativeness force the trend of outsourcing to be replaced by strategic alliances, where enterprises or individuals work together towards a common goal and share their responsibilities as well as their profits. Recent developments in information technology have enabled relatively inexpensive, reliable and fast networking to support such alliances in real time. In this context, the virtual enterprise (VE) represents an appropriate cooperation alternative and competitive advantage for the enterprises. VE is a temporary network of independent companiessuppliers, customers, even rivals -linked by information technology (IT) to share skills, costs and access to one another's markets. In this emerging business model of virtual enterprise, the decision support functionality, which addresses issues such as partner company selection, is an important domain to be studied. In this paper, we propose an analytic hierarchy process model to contribute in the selection of the partner companies in the virtual enterprises.A case example is also covered to validate the feasibility of the adoption of the model in virtual enterprise situations.

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Compression stockings, which constitute one of the most important groups of compression garments, are engineered to regulate blood flow in venous systems in order to use in many medical fields such as supporting muscles and preventing edema. In the present study, it was aimed to analyze the effects of production parameters such as tightness, elastane yarn feeding tension and elastane yarn counts on pressure behavior of compression stockings, which are commonly used to adjust pressure values. The results of the statistical analysis indicated that the tested parameters had significant effects on pressure characteristics of compression stockings. Moreover, multiple regression analysis was used to investigate the relationship between the fabric parameters and pressure values. The analysis exhibited the strong impact of thickness and traversal elasticity on pressure characteristics. All parameters have positive impacts except traversal elasticity.

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Microwave sensors can probe intrinsic material properties of analytes in a microfluidic channel at physiologically relevant ion concentrations. While microwave sensors have been used to detect single cells and microparticles in earlier studies, the synergistic use and comparative analysis of microwave sensors with optical microscopy for material classification and size tracking applications have been scarcely investigated so far. Here we combined microwave and optical sensing to differentiate microscale objects based on their dielectric properties. We designed and fabricated two types of planar sensor: a Coplanar Waveguide Resonator (CPW) and a Split-Ring Resonator (SRR). Both sensors possessed sensing electrodes with a narrow gap to detect single cells passing through a microfluidic channel integrated on the same chip. We also show that standalone microwave sensors can track the relative changes in cellular size in real-time. In sensing single 20-micron diameter polystyrene particles, Signal-to-Noise ratio values of approximately 100 for CPW and 70 for SRR sensors were obtained. These findings demonstrate that microwave sensing technology can serve as a complementary technique for single-cell biophysical experiments and microscale pollutant screening.

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