Transmission pricing and recovery of investment costs in the deregulated power system based on optimal circuit prices

Transmission pricing has become a major issue in the discussions about the deregulated electricity markets.Conse-quently,open access to the transmission system is one of the basic topics to allow compe...     

Evaluation of Centrifugal Casting Process Parameters for In Situ Fabricated Functionally Gradient Fe-TiC Composite

A gradient Fe-TiC composite was successfully produced via combination of in situ reaction with centrifugal casting techniques. Additionally, some of the effective parameters of the centrifugal casting process have been studied. Cast iron and ferrotitanium, which were used as raw materials, were melted using a high-frequency induction furnace coupled with centrifugal equipment. The microstructure and phase characterization of the fabricated composite was studied by scanning electron microscopy, optical microscopy, and X-ray diffraction. The results show that the production of a pearlite matrix composite reinforced by TiC particles is feasible. The distribution of TiC in the pearlitic matrix is completely uneven as a result of density difference between molten medium and TiC in the centrifugal casting process.     

Cavity Control of Prefoldin Nano Actuator (PNA) by Temperature and pH

Nano-Micro Letters - A molecular dynamics study to investigate the cavity control of Prefoldin based bio nano actuator is presented in this paper. Prefoldin is a molecular chaperone with a...     

Proximity effects of a layered periodic structure on miniaturization of patch antennas

A miniaturized microstrip antenna on a planar layered periodic structure is proposed, designed and fabricated. The proposed structure miniaturizes patch antennas in the microwave band. With varying the parameters of the proposed structure, the achieved miniaturization factor can be adjusted in the range 2.6–4.2. Numerical and experimental results are presented. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.     

Physical and mechanical properties of a poly-3-hydroxybutyrate-coated nanocrystalline hydroxyapatite scaffold for bone tissue engineering

A major challenge for tissue engineers is the design of scaffolds with appropriate physical and mechanical properties. The present research discusses the formation of ceramic scaffolding in tissue engineering. Hydroxyapatite (HAp) powder was made from bovine bone by thermal treatment at 900?°C; 40, 50 and 60%wt porous HAp was then produced using the polyurethane sponge replication method. Scaffolds were coated with poly-3-hydroxybutyrate (P3HB) for 30?s and 1?min in order to increase the scaffold??s mechanical properties. XRD, SEM and FT-IR were used to study phase structure, morphology and agent groups, respectively. In XRD and FT-IR data, established hydrogen bands between polymer and ceramic matrix confirm that the scaffold is formed as a composite. The scaffold obtained with 50%wt HAp and a 30?s coating was 90% porous, with an average diameter of 100?C400???m, and demonstrated a compressive strength and modulus of 1.46 and 21.27?MPa, respectively. Based on these results, this scaffold is optimised for the aforementioned properties and can be utilised in bone tissue engineering.     

Cyclic scheduling of a robotic flexible cell with load lock and swap

In this paper, we study the problem of robotic cell scheduling with m machines with flexibility, load lock and swap assumptions. The robotic cell repetitively produces parts of identical types. We determine the cycle time of all 1-unit cycles in this type of robotic cell and present two new lower bounds for robot move cycles with load lock and swap, either there is flexibility or inflexibility. We also provide a new robot move cycle and prove that it dominates all classical robot move cycles considered in the existing literature of m-machine robotic cells.     

Combination of multiple diverse classifiers using belief functions for handling data with imperfect labels

This paper addresses the supervised learning in which the class memberships of training data are subject to ambiguity. This problem is tackled in the ensemble learning and the Dempster-Shafer theory of evidence frameworks. The initial labels of the training data are ignored and by utilizing the main classes’ prototypes, each training pattern is reassigned to one class or a subset of the main classes based on the level of ambiguity concerning its class label. Multilayer perceptron neural network is employed to learn the characteristics of the data with new labels and for a given test pattern its outputs are considered as basic belief assignment. Experiments with artificial and real data demonstrate that taking into account the ambiguity in labels of the learning data can provide better classification results than single and ensemble classifiers that solve the classification problem using data with initial imperfect labels.