A Novel Self-Organizing Approach to Automatic Traffic Light Management System for Road Traffic Network

Wireless Personal Communications - Traffic network is basically a “network of networks” consisting of mainly two types of networks: road network and a travel network. Due to drastic...     

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....     

A Dynamic Inertial Weight Strategy in Micro PSO for Swarm Robots

Wireless Personal Communications - A relatively new area of research and development is Swarm Robotics. It is a part of the swarm intelligence field. In the proposed paper, we shall use swarm...     

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.     

Engineering New Microvascular Networks On-Chip: Ingredients,Assembly, and Best Practices

Tissue engineered grafts show great potential as regenerative implants for diseased or injured tissues within the human body. However, these grafts suffer from poor nutrient perfusion and waste transport, thus decreasing their viability post-transplantation. Graft vascularization is therefore a major area of focus within tissue engineering because biologically relevant conduits for nutrient and oxygen perfusion can improve viability post-implantation. Many researchers used microphysiological systems as testing platforms for potential grafts owing to an ability to integrate vascular networks as well as biological characteristics such as fluid perfusion, 3D architecture, compartmentalization of tissue-specific materials, and biophysical and biochemical cues. Although many methods of vascularizing these systems exist, microvascular self-assembly has great potential for bench-to-clinic translation as it relies on naturally occurring physiological events. In this review, the past decade of literature is highlighted, and the most important and tunable components yielding a self-assembled vascular network on chip are critically discussed: endothelial cell source, tissue-specific supporting cells, biomaterial scaffolds, biochemical cues, and biophysical forces. This paper discusses the bioengineered systems of angiogenesis, vasculogenesis, and lymphangiogenesis and includes a brief overview of multicellular systems. It concludes with future avenues of research to guide the next generation of vascularized microfluidic models.     

Conversion of acrylonitrile-based precursors to carbon fibres

The progress of stabilization of two compositions of acrylic fibres with various orientations has been followed by a variety of techniques. The thermooxidative treatments for stabilization have been carried out in a continuous process and also in a batch process under free shrinkage, constant length and constant tension conditions. The morphological model of acrylic fibres consists of an alternating sequence of laterally ordered and laterally disordered regions along the fibre direction. This structure is consistent with the observations based on small-angle X-ray scattering of copper- impregnated precursor fibres and thermomechanical response, thermal stress development, calorimetry, wide- and small-angle X-ray scattering and sonic modu-lus measured at different extents of stabilization. Lateral as well as orientational order in these fibres can be increased markedly through a high-temperature deformation process prior to stabilization. An increase in perfection and extent of order is observed in the early stages of stabilization. There is also a simultaneous decrease in the orientation of the disordered phase at this stage and the extent of this decrease depends on the axial constraints imposed on the fibre. Little difference in the rate of stabilization is observed as measured by density or oxygen uptake for fibres with different extents of orientation, lateral order or restraint. Fibres containing itaconic add, a stabilization catalyst did show an increased rate of stabilization. Inferences have been drawn regarding additional research pertaining to achieving high order in precursor fibres, minimizing orientational relaxation during oxidative stabilization, and the techniques for monitoring the extents of the stabilization treatment and the changes in relevant morphological parameters.     

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.