The relationship between highly-cited papers and the frequency of citations to other papers within-issue among three top information science journals

Scientometrics - This study investigates a potential relationship between highly-cited scholarly papers and the number of citations received by other papers with which they share a journal issue....     

Impact of adhesive ingredients on adhesion between rubber and brass-plated steel wire in tire

Proficiency on underlying mechanism of rubber-metal adhesion has been increased significantly in the last few decades. Researchers have investigated the effect of various ingredients, such as hexamethoxymethyl melamine, resorcinol, cobalt stearate, and silica, on rubber-metal interface. The role of each ingredient on rubber-metal interfacial adhesion is still a subject of scrutiny. In this article, a typical belt skim compound of truck radial tire is selected and the effect of each adhesive ingredient on adhesion strength is explored. Out of these ingredients, the effect of cobalt stearate is found noteworthy. It has improved adhesion strength by 12% (without aging) and by 11% (humid-aged), respectively, over control compound. For detailed understanding of the effect of cobalt stearate on adhesion, scanning electron microscopy and energy dispersive spectroscopy are utilized to ascertain the rubber coverage and distribution of elements. X-ray photoelectron spectroscopy results helped us to understand the impact of Cu_XS layer depth on rubber-metal adhesion. The depth profile of the Cu_XS layer was found to be one of the dominant factors of rubber-metal adhesion retention. Thus, this study has made an attempt to find the impact of different adhesive ingredients on the formation of Cu_XS layer depth at rubber-metal interface and establish a correlation with adhesion strength simultaneously.     

Bounds on the number of samples needed for neural learning.

The relationship between the number of hidden nodes in a neural network, the complexity of a multiclass discrimination problem, and the number of samples needed for effect learning are discussed. Bounds for the number of samples needed for effect learning are given. It is shown that Omega(min (d,n) M) boundary samples are required for successful classification of M clusters of samples using a two-hidden-layer neural network with d-dimensional inputs and n nodes in the first hidden layer.     

A VLSI architecture for a half-edge-based corner detector

Corner detection is a low-level feature detection operator that is of great use in image processing applications, for example, optical flow and structure from motion by image correspondence. The detection of corners is a computationally intensive operation. Past implementations of corner detection techniques have been restricted to software. In this paper we propose an efficient very large-scale integration (VLSI) architecture for detection of corners in images. The corner detection technique is based on the half-edge concept and the first directional derivative of Gaussian. Apart from the location of the corner points, the algorithm also computes the corner orientation and the corner angle and outputs the edge map of the image. The symmetrical properties of the masks are utilized to reduce the number of convolutions effectively, from eight to two. Therefore, the number of multiplications required per pixel is reduced from 1800 to 392. Thus, the proposed architecture yields a speed-up factor of 4.6 over conventional convolution architectures. The architecture uses the principles of pipelining and parallelism and can be implemented in VLSI.     

FluNet: A hybrid internet simulator for fast queue regimes

Motivated by the scale and complexity of simulating large-scale networks, recent research has focused on hybrid fluid/packet simulators, where fluid models are combined with packet models in order to reduce simulation complexity as well as to track dynamics of end-sources accurately. However, these simulators still need to track the queuing dynamics of network routers, leading to considerable simulation complexity in a large-scale network model. In this paper, we propose a new hybrid simulator – FluNet – where queueing dynamics are not tracked, but instead, an equivalent rate-based model is used. The FluNet simulator is predicated on a fast-queueing regime at bottleneck routers, where the queue length fluctuates on a faster time-scale than end systems. This allows us to simulate large-scale systems, where the simulation “time step-size” is governed only by the time-scale of the end-systems, and not by that of the intermediate routers; whereas a queue-tracking based fluid simulator would require decreasingly smaller step-sizes as the system scale size increases. We validate our model using a ns-2 based implementation. Our results indicate a good match between packet systems and the associated FluNet system.     

Performance of hashed cache data migration schemes on multicomputers

Many researchers approach the problem of programming distributed memory machines by assuming a global shared name space. Thus the user views the distributed memory of the machine as though it were shared. A major issue that arises at this point is how to manage the memory. When a processor accesses data stored on another processor's memory, data must be moved between the two processors. Once these data are retrieved from another processor's memory, several interesting issues are raised. Where should these data be stored locally? What transformations must be performed to the code to guarantee that the nonlocal accesses reference the correct memory location? What optimizations can be performed to reduce the time spent in accessing the nonlocal data? In this paper we examine various data migration mechanisms that allow an explicit and controlled mapping of data to memory. We describe, experimentally evaluate, and model a set of schemes for storing and retrieving off-processor array elements. The schemes are all based on using hash tables for efficient access of nonlocal data. The three different techniques evaluated are the basic hashed cache, partial enumeration, and full enumeration, the details of which are described in the paper. In all three schemes, nonlocal data are stored in hash tables—the difference is in the amount of memory used by the schemes and the retrieval mechanisms for nonlocal data.     

An inverse solution methodology for estimating the diffusion coefficient of gases in Athabasca bitumen from pressure-decay data

An inverse solution methodology is developed for the estimation of diffusion coefficient of gases in highly viscous, oil-sands bitumens from isothermal, pressure-decay measurements. The approach involves modeling the rate of change in pressure using the diffusion equation for the liquid phase coupled with a mass balance equation for the gas phase. The inverse solution framework is utilized to arrive at two graphical techniques for estimating the diffusion coefficient. Both techniques involve the determination of the slope of a straight line resulting from plotting the experimental data in accordance with the developed model. An advantage of the proposed techniques is that the diffusion coefficient is estimated directly, i.e. without making it an adjustable parameter. The novelty of the proposed method is in its simplicity as well as its ability to isolate portions of the pressure-decay data affected by experimental fluctuations. The effect of the initial pressure on the predicted diffusion coefficient and pressure-decay profile was also investigated. The diffusion coefficients of CO₂, CH₄, C₂H₆ and N₂ in Athabasca bitumen at 50–90 °C and about 8 MPa were estimated and compared with literature values.     

Collection of biological materials in biodiversity prospecting in India: problems and solutions

Forests are the chief resource for the collection and exploration of biological materials. The past few decades have witnessed a large scale deforestation in India due to substantial pressures generated by population growth, leading to demand for more land for agriculture, urbanization and industrial activities, in addition to increased demand for fuel wood and timber. This has resulted in the loss of soil cover, habitat destruction, environmental degradation and ecological imbalance. This scenario has created a progressive awareness for the conservation and restoration of habitats and, thus, the declaration of many forest areas into protected zones, such as national parks, biosphere reserves, etc., including the protection of some marine areas, by both the National and State Governments. Normally, permission for biological collecting is not granted in these protected areas. In India, forests are a State subject and grant for collection permission is vested with the State Forest Departments. In the absence of any rules, regulations and guidelines, either from National or State Governments, forest authorities impose their terms and conditions, which are arbitrary and even contradictory at times, in the process of granting collecting permits. A set of new rules to be applied throughout the country is needed.