Object manipulation with a variable-stiffness robotic mechanism using deep neural networks for visual semantics and load estimation

Neural Computing and Applications - In recent years, the computer vision applications in the robotics have been improved to approach human-like visual perception and scene/context understanding....     

An integrated interval-valued intuitionistic fuzzy AHP-TOPSIS methodology to determine the safest route for cash in transit operations: a real case in Istanbul

Neural Computing and Applications - The Cash in Transit (CIT) deals with the money distribution and picking up between depot(s), central bank, bank branches, Automated Teller Machines (ATMs),...     

Sorption of N-butane,propane, and ethane in ethylcellulose

The sorption of n-butane, propane, and ethane in ethylcellulose has been investigated between 0 and 200 mm Hg pressure over the temperature range from 30 to 70°C. Sorption isotherms of n-butane, propane, and ethane in ethylcellulose suggest that both Henry's law and the Langmuir forms of sorption, are operative. Sorption data were analyzed using the dual sorption model and sorption parameters determined. The sorption attributed to the Langmuir mode decreases as the temperature increases. This result indicates that the nonlinear Langmuir mode of sorption is more characteristic of the glassy state than sorption represented by the Henry's law mode. It was found that sorption attributed to the Henry's law and Langmuir modes decreases as the molecular size of gaseous hydrocarbon penetrants decrease. In this study, the molecular size of gaseous molecule decreased as the gases studied changed from n-butane to propane to ethane. A correlation of the Henry's law constants for the solution of n-butane, propane, and ethane in ethylcellulose with the Lennard-Jones force constants, ?/k at different temperatures was also determined. The temperature dependence of the Henry's law constants were correlated by a van't Hoff relationship and heats of sorption determined.     

Symptotics: a framework for estimating the scalability of real-world wireless networks

We present a framework for non-asymptotic analysis of real-world multi-hop wireless networks that captures protocol overhead, congestion bottlenecks, traffic heterogeneity and other real-world concerns. The framework introduces the concept of symptotic scalability to determine the number of nodes to which a network scales, and a metric called change impact value for comparing the impact of underlying system parameters on network scalability. A key idea is to divide analysis into generic and specific parts connected via a signature—a set of governing parameters of a network scenario—such that analyzing a new network scenario reduces mainly to identifying its signature. Using this framework, we present the first closed-form symptotic scalability expressions for line, grid, clique, randomized grid and mobile topologies. We model both TDMA and 802.11, as well as unicast and broadcast traffic. We compare the analysis with discrete event simulations and show that the model provides sufficiently accurate estimates of scalability. We show how our impact analysis methodology can be used to progressively tune network features to meet a scaling requirement. We uncover several new insights, for instance, on the limited impact of reducing routing overhead, the differential nature of flooding traffic, and the effect real-world mobility on scalability. Our work is applicable to the design and deployment of real-world multi-hop wireless networks including community mesh networks, military networks, disaster relief networks and sensor networks.     

Energy use,CO2 emission and foreign direct investment: Is there any inconsistence between causal relations?

In this study, the causal relations between inward foreign direct investment (FDI)-energy use per capita and inward FDI-CO₂ emission per capita were analyzed and the inconsistency between the causal relations was investigated via bootstrap-corrected panel causality test and cross-correlation analysis. In this direction, data from 76 countries including the period of 1980–2009 was processed. No supportive evidence was found for changing causal relations to country group which was classified into income level. The findings indicated that while the pollution haven hypothesis was supported for Mozambique, United Arab Emirates and Oman, the pollution halo hypothesis was supported in the case of India, Iceland, Panama and Zambia. For other countries, energy use and CO₂ emission were neutral to inward FDI flows in aggregated level. Furthermore, this study urged that increased (decreased) energy use due to the inward FDI flows did not necessarily mean an increase (decrease) in pollution level, and vice versa. For policy purpose, FDI attractive policy should be regulated by taking into account this possibility.     

Differential near-field scanning optical microscopy

We theoretically and experimentally illustrate a new apertured near-field scanning optical microscopy (NSOM) technique, termed differential NSOM (DNSOM). It involves scanning a relatively large (e.g., 0.3-2 mum wide) rectangular aperture (or a detector) in the near-field of an object and recording detected power as a function of the scanning position. The image reconstruction is achieved by taking a two-dimensional derivative of the recorded power map. Unlike conventional apertured NSOM, the size of the rectangular aperture/detector does not determine the resolution in DNSOM; instead, the resolution is practically determined by the sharpness of the corners of the rectangular aperture/detector. Principles of DNSOM can also be extended to other aperture/detector geometries such as triangles and parallelograms.     

Validated Simulation Models for Lateral Response of Bridge Abutments with Typical Backfills

Abutment-backfill soil interaction can significantly influence the seismic response of bridges. In the present study, we provide numerical simulation models that are validated using data from recent experiments on the lateral response of typical abutment systems. Those tests involve well-compacted clayey silt and silty sand backfill materials. The simulation methods considered include a method of slices approach for the backfill materials with an assumed log-spiral failure surface coupled with hyperbolic soil stress-strain relationships [referred to as “log-spiral hyperbolic (LSH) model”] as well as detailed finite-element models, both of which were found to compare well with test data. Through parametric studies on the validated LSH model, we develop equations for the lateral load-displacement backbone curves for abutments of varying height for the two aforementioned backfill types. The equations describe a hyperbolic relationship between lateral load per unit width of the abutment wall and the wall deflection and are amendable to practical application in seismic response simulations of bridge systems.     

Dynamic wind turbine output power reduction under varying wind speed conditions due to inertia

The inertia of wind turbines causes a reduction in their output power due to their inability to operate at the turbine maximum co‐efficient of performance point under dynamic wind conditions. In this paper, this dynamic power reduction is studied analytically and using simulations, assuming that a steady‐state optimal torque control strategy is used. The concepts of the natural and actual turbine time‐constant are introduced, and typical values for these parameters are examined. It is shown that for the typical turbine co‐efficient of performance curve used, the average turbine speed can be assumed to be determined by the average wind speed. With this assumption, analytical expressions for the power reduction with infinite and then finite turbine inertia are determined for sine‐wave wind speed variations. The results are then generalized for arbitrary wind speed profiles. A numerical wind turbine system simulation model is used to validate the analytical results for step and sine‐wave wind speed variations. Finally, it is used with real wind speed data to compare with the analytical predictions. Copyright © 2012 John Wiley & Sons, Ltd.     

Using data envelopment analysis for evaluating flexible manufacturing systems in the presence of imprecise data

The aim of this paper is to present a comprehensive methodology for evaluation and selection of advanced manufacturing technologies, incorporating both the economic and strategic aspects and the related imprecise as well as exact data into the decision making process. Initially, a data envelopment analysis (DEA) model that can take into account crisp, ordinal, and fuzzy data is introduced. Then, the developed framework is used for flexible manufacturing system (FMS) selection. The DEA approach is performed by employing capital and operating cost, required floor space and work-in-process (WIP) as the input variables, and using product flexibility, quality improvement and lead time reduction as the output variables. The assessment of FMS alternatives versus product flexibility and quality improvement are represented via ordinal data, while WIP and lead time reduction are stated using triangular fuzzy numbers. The proposed framework is illustrated through an application and comparative results are presented.