On trading wavelengths with fibers: a cost-performance based study

We consider the effect of multiple fibers on wavelength division multiplexing networks without wavelength conversion. We study networks with dynamic wavelength routing and develop accurate analytical models to compare various possible options using single- and multiple-fiber networks. We use results of an analytical model and simulation-based studies to evaluate the blocking performance and cost of multifiber networks. The number of fibers required providing high performance in multifiber networks and their costs are compared. A case is made for using multiple fibers in each link with fewer wavelengths instead of using a single fiber with many wavelengths. In particular, we show that a network with four fibers per link and with four wavelengths on each fiber without any wavelength conversion on any node yields similar same performance as the networks with one fiber per link and 16 wavelengths per fiber on each link and with full wavelength conversion capability on all nodes. In addition, the multifiber network may also offer the cost advantage depending on the relative cost of components. We develop a parametric cost model to show that multiple fibers in each link are an attractive option. Finally, such multifiber networks also has fault tolerance, with respect to a single fiber failure, already built into the system.     

Strategies for Coping With Business Trips: A Qualitative Exploratory Study.

This study aimed to better understand the impact of business trips on the traveler, the family, and the organization; to learn about maximizing the positive aspects of business travel; and to suggest measures to prevent and manage travel stress. Thirty-five business travelers (American, Israeli, and Swedish) were interviewed about the costs and benefits of their traveling, with a focus on gaining insight into coping strategies. Content analysis of the interviews showed that trips consist of 4 phases--(a) pretrip, (b) journey, (c) stay, and (d) posttrip--and that each phase is characterized by different coping strategies. Business travelers reported using proactive individual and organizational coping strategies in the pretrip phase and a combination of proactive and reactive coping strategies in the other phases. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Effect of surfactants on phenol removal by the method of polymerization and precipitation catalysed by Coprinus cinereus peroxidase

The removal of phenol by peroxidase‐catalysed polymerization was examined using Coprinus cinereus peroxidase in the presence of surfactants. The non‐ionic surfactants with poly(oxyethene) residues, Triton X‐100, Triton X‐405 and Tween 20, enhanced the phenol removal efficiency at a level similar to high relative molecular mass poly(ethylene glycol) (relative molecular mass 3000). Although the improvement in the removal efficiency was less than that of Triton X‐100, Span 20, sodium lauryl sulfate (SDS) and lauryl trimethylammonium bromide (DTAB) also enhanced the removal efficiency. The requirement of the enzyme for almost 100% removal of 100 mg dm^?3 phenol decreased to one‐fourth by the addition of 30 mg dm^?3 Triton X‐100. Triton X‐100, Triton X‐405, Tween 20 and DTAB could reactivate the enzyme precipitated with the phenol polymer, leading to the restarting of the phenol removal reaction. Copyright © 2003 Society of Chemical Industry     

Exploration of unknown object by active touch of robot hand

This paper proposes a method of exploring the local shape of an unknown object using the force and torque information obtained from active touch. In the first, we present a method to estimate an unknown curvature, using rolling and sliding motion with a force/torque sensor attached to the fingertip of the hand. Then, the normal curvature equation from 2D curvatures is obtained. Finally we present a reconstruction algorithm of local geometry by using a normal curvature equation, which is composed of principal curvatures and principal directions. The method is tested by using a hand-arm system consisting of an industrial robot arm and an anthropomorphic robot hand with 6-axis force/torque sensor. The feasibility of the proposed method is experimentally validated for objects with simple geometries such as cylinder, spheres etc.     

Microhardness studies of PMMA/natural rubber blends

The microhardness, H, of PMMA/natural rubber blends, prepared following the solution method has been investigated by means of the microindentation technique. Hardness changes are correlated with the variation of the glass transition temperature. The influence of temperature and degree of deformation on H were additionally examined. The inclusion of rubber particles in the PMMA matrix is shown to soften the blends. The variation of the micromechanical property at the phase boundary of polymer/rubber particle has been studied. Results reveal that H drastically drops at the interphase. In the case of the drawn materials, the indentation anisotropy (ΔH) is shown to gradually increase with the draw ratio, where ΔH is found to be higher for the PMMA/rubber blend than for the original PMMA. This result is explained by the higher orientation of the PMMA molecules near the periphery of stretched rubber particles. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 91: 205–210, 2004     

TVD-MRDL: traffic violation detection system using MapReduce-based deep learning for large-scale data

Maintaining a fluid and safe traffic is a major challenge for human societies because of its social and economic impacts. Various technologies have considerably paved the way for the elimination of traffic problems and have been able to effectively detect drivers’ violations. However, the high volume of the real-time data collected from surveillance cameras and traffic sensors along with the data obtained from individuals have made the use of traditional methods ineffective. Therefore, using Hadoop for processing large-scale structured and unstructured data as well as multimedia data can be of great help. In this paper, the TVD-MRDL system based on the MapReduce techniques and deep learning was employed to discover effective solutions. The Distributed Deep Learning System was implemented to analyze traffic big data and to detect driver violations in Hadoop. The results indicated that more accurate monitoring automatically creates the power of deterrence and behavior change in drivers and it prevents drivers from committing unusual behaviors in society. So, if the offending driver is identified quickly after committing the violation and is punished with the appropriate punishment and dealt with decisively and without negligence, we will surely see a decrease in violations at the community level. Also, the efficiency of the TVD-MRDL performance increased by more than 75% as the number of data nodes increased.

     

A Model for Identifying the Behavior of Alzheimer’s Disease Patients in Smart Homes

Wireless Personal Communications - In recent years, Smart Cities and Smart Homes have been studied as an important field of research. The design and construction of smart homes have flourished so...     

A hybrid OBL-based firefly algorithm with symbiotic organisms search algorithm for solving continuous optimization problems

The metaheuristic optimization algorithms are relatively new optimization algorithms introduced to solve optimization problems in recent years. For example, the firefly algorithm (FA) is one of the metaheuristic algorithms inspired by the fireflies' flashing behavior. However, its weakness in terms of exploration and early convergence has been pointed out. In this paper, two approaches were proposed to improve the FA. In the first proposed approach, a new improved opposition-based learning FA (IOFA) method was presented to accelerate the convergence and improve the FA's exploration capability. In the second proposed approach, a symbiotic organisms search (SOS) algorithm improved the exploration and exploitation of the first approach; two new parameters set these two goals, and the second approach was named IOFASOS. The purpose of the second method is that in the process of the SOS algorithm, the whole population is effective in the IOFA method to find solutions in the early stages of implementation, and with each iteration, fewer solutions are affected in the population. The experiments on 24 standard benchmark functions were conducted, and the first proposed approach showed a better performance in the small and medium dimensions and exhibited a relatively moderate performance in the higher dimensions. In contrast, the second proposed approach was better in increasing dimensions. In general, the empirical results showed that the two new approaches outperform other algorithms in most mathematical benchmarking functions. Thus, The IOFASOS model has more efficient solutions.