Defect formation in amorphous structures as revealed by computer simulation

Various types of defect in amorphous structures are discussed. It is shown that the formation, migration, redistribution and annihilation of defects in amorphous solids can be fully understood only by using computer simulation. More insight into the physics of amorphous thin films is given by the simulation of columnar growth and of the interface between a crystalline phase and an amorphous phase.     

A new route to graphene starting from heavily ozonized fullerenes: Part 1—thermal reduction under inert atmosphere

It is shown that heavily ozonized C₆₀ or C₇₀ fullerenes (known also as “fullerene ozopolymers”) are suitable substrates for the preparation of graphene or nanographene in place of graphite oxide (GO) by thermal reduction in inert atmosphere. TGA-FTIR study shows that the release profile of CO₂ and CO from fullerene ozopolymers in the temperature range between 25°C and 900°C is comparable to that shown by GO. Furthermore, the FT-IR spectral evolution of fullerene ozopolymers from room temperature to 630°C under inert atmosphere is once again strikingly comparable to that observed on GO under the same conditions.     

Surface modification of activated carbon fabric with ozone,part 1: Kinetics and oxidation degree

Two samples of activated carbon fabrics (ACF) with very high surface area (>1300 to >1800 m²/g) were reacted with ozone inside a closed flask under static conditions. The kinetics of ozone decomposition and reaction with the ACF surface was measured in the gas phase using Fourier transform infrared analysis (FT-IR) spectroscopy. The ozone consumption under these conditions was following the pseudofirst-order kinetics law and was accompanied by the production of CO₂ and CO. The ozone-oxidized ACF were studied by FT-IR spectroscopy following the growth of key oxidized functional groups, i.e. phenolic OH, ketone groups intended as carboxyl, lactone, and anhydride, as well as quinone groups as a function of the amount of ozone reacted. The weight uptake of the ACF reacted with ozone was followed gravimetrically. The ACF having >1800 m²/g was able to reach a weight increase of 25% of its original weight due to the formation of oxygenated surface functional groups. Raman spectroscopy was used for the evaluation of defective structures formed in ACF because of ozonization reaction.     

Quantum particles on graphenic systems. Part 2. Bondons by absorption Raman spectra

Intriguing micro-currents in the graphenic oxide flakes obtained from the cracked fullerenes ozopolymers were predicted from their Raman spectra. They are interpreted with the aid of the bondonic theory combined with the inverse information for the quantum observed vs. quantum free evolution ratio, respectively. The peculiar quantum dots of the bondonic propagation in these nanoscopic systems may suggest the potentially critical phenomenology of phase transition, and possible local superconductivity by passing from the C₆₀ derivative graphenic oxide to the C₇₀ based compound. These results may have an impact on the future design of the graphene-based semiconductors, of the quantum graphenic gates, as well as on and the integrated graphenic microcircuits in the generic new field of graphentronics.     

Combined thin-film and Navier–Stokes analysis in high Reynolds number lubrication

The classical theory of hydrodynamic lubrication assumes that the flow regime is laminar and the inertia forces in the fluid film are negligible. For large bearings using low viscosity lubricant or for high speed, the inertia forces could be important and non laminar flow occurs. In that presentation a general view of non-laminar lubrication is presented. The different flow regimes, which occur in bearings and seals, are shown. The theories to obtain the characteristics of bearings operating in turbulent flow regime are presented. The effects of inertia forces in laminar and in turbulent flows are shown. Finally results obtained using the complete Navier Stokes equations are presented and it is shown how they are included in the classic lubrication theory.     

Obstacle avoidance of redundant manipulators using neural networks based reinforcement learning

This paper proposes a new approach for solving the problem of obstacle avoidance during manipulation tasks performed by redundant manipulators. The developed solution is based on a double neural network that uses Q-learning reinforcement technique. Q-learning has been applied in robotics for attaining obstacle free navigation or computing path planning problems. Most studies solve inverse kinematics and obstacle avoidance problems using variations of the classical Jacobian matrix approach, or by minimizing redundancy resolution of manipulators operating in known environments. Researchers who tried to use neural networks for solving inverse kinematics often dealt with only one obstacle present in the working field. This paper focuses on calculating inverse kinematics and obstacle avoidance for complex unknown environments, with multiple obstacles in the working field. Q-learning is used together with neural networks in order to plan and execute arm movements at each time instant. The algorithm developed for general redundant kinematic link chains has been tested on the particular case of PowerCube manipulator. Before implementing the solution on the real robot, the simulation was integrated in an immersive virtual environment for better movement analysis and safer testing. The study results show that the proposed approach has a good average speed and a satisfying target reaching success rate.     

Role of obligations in multiagent coordination

Carrying out distributed business processes over networks is rapidly shifting the nature of application architectures from the simple command and control client-server model to complex peer-to-peer models supporting dynamic patterns of social interaction and behavior among autonomous, proactive, goal oriented agents. Trusting agents to autonomously make decisions and execute actions on behalf of humans, as part of global business processes, requires both understanding and modeling of the social laws that govern collective behavior and a practically useful operationalization of the models into agent programming tools. In this article we present a solution to these problems based on a representation of obliged and forbidden behavior in an organizational framework, together with an inference method that also decides which obligations to break in conflicting situations. These are integrated into an operational, practically useful agent development language that covers the spectrum from the definition of organizations, roles, agents, obligations, goals, and conversations to inferring and executing coordinated agent behaviors in multiagent applications. The major strength of the approach is the way it supports coordination by exchanging constraints about obliged and forbidden behavior among agents. We illustrate this and the entire system with solution examples to the feature interaction problem in the telecommunications industry and to integrated supply chain management.     

Autonomous Adaptive Control System for Airplane Landing

The paper presents a new autonomous adaptive system for the control of airplanes during landing in longitudinal plane. For the first stage of landing in longitudinal plane, the main variables to be controlled are the glide slope angle and longitudinal velocity; during the second main stage of landing in longitudinal plane, the vertical velocity error and the airplane's longitudinal velocity are controlled. The new robust control architecture has linear subsystems, for which the relative degrees are calculated; the new architecture will also consists of a dynamic compensator, a linear observer, and two reference models, their design being accomplished with respect to the calculated relative degrees. The signal estimated by the observer is useful for training a neural network – an adaptive subsystem of the architecture that provides the adaptive component of the control law. In the case of actuators having nonlinear dynamics, pseudo control hedging blocks are used to cancel the adapting difficulties of the neural networks. The new adaptive architecture is software implemented and validated by complex numerical simulations.     

An autonomous GP-based system for regression and classification problems

The aim of this research is to develop an autonomous system for solving data analysis problems. The system, called Genetic Programming-Autonomous Solver (GP-AS) contains most of the features required by an autonomous software: it decides if it knows or not how to solve a particular problem, it can construct solutions for new problems, it can store the created solutions for later use, it can improve the existing solutions in the idle-time it can efficiently manage the computer resources for fast running speed and it can detect and handle failure cases. The generator of solutions for new problems is based on an adaptive variant of Genetic Programming. We have tested this part by solving some well-known problems in the field of symbolic regression and classification. Numerical experiments show that the GP-AS system is able to perform very well on the considered test problems being able to successfully compete with standard GP having manually set parameters.     

The 2007 procurement challenge: A competition to evaluate mixed procurement strategies

Global competition is putting a premium on the ability to manage risk through flexible and agile web-enabled procurement practices. This article discusses the design of the 2007 “supply chain management – procurement challenge” (SCM-PC), a competition designed by the first three authors to evaluate the performance of mixed procurement strategies that balance risk through combinations of long-term, quantity-flexible contracts and one-off contracts. Specifically, the SCM-PC challenge revolves around a PC assembly scenario, where web-enabled trading agents developed by different teams compete for components required to assemble different types of PCs.Collectively the authors represent the top three entries in the 2007 procurement challenge. They present the strategies their teams developed for the competition, compare their performances, and discuss lessons learned from the competition.