Asynchronous spiking neural P systems

We consider here spiking neural P systems with a non-synchronized (i.e., asynchronous) use of rules: in any step, a neuron can apply or not apply its rules which are enabled by the number of spikes it contains (further spikes can come, thus changing the rules enabled in the next step). Because the time between two firings of the output neuron is now irrelevant, the result of a computation is the number of spikes sent out by the system, not the distance between certain spikes leaving the system. The additional non-determinism introduced in the functioning of the system by the non-synchronization is proved not to decrease the computing power in the case of using extended rules (several spikes can be produced by a rule). That is, we obtain again the equivalence with Turing machines (interpreted as generators of sets of (vectors of) numbers). However, this problem remains open for the case of standard spiking neural P systems, whose rules can only produce one spike. On the other hand we prove that asynchronous systems, with extended rules, and where each neuron is either bounded or unbounded, are not computationally complete.For these systems, the configuration reachability, membership (in terms of generated vectors), emptiness, infiniteness, and disjointness problems are shown to be decidable. However, containment and equivalence are undecidable.     

Recognizing human gestures in videos by modeling the mutual context of body position and hands movement

In our days, due the evolution of high-speed computers, the old Human–Computer Interface (HCI) legacies based on mouse and keyboard are slowly becoming obsolete and cannot be accurate enough and respond in a timely manner to the flow of information today. This is why new ways of communicating with the computer have to be researched, the most natural one being the use of gestures. In this paper, a two-level architecture for recognizing human gestures from video frames is proposed. The architecture makes use of several feed-forward neural networks to compute the gestures based on the Haar-like features of body, hand and finger as well as a stochastic-free context grammar that is employed to comprise the mutual context between body pose and hand movement. Trained and tested on 10 gestures (Swipe Right, Swipe Left, Swipe Up, Swipe Down, Horizontal Wave, Vertical Wave, Circle, Point, Palm Up and Fist) the over 94 % accuracy of the system surpasses the current state of the art and compared with a system with no mutual context between body position and hand movement our proposed architecture shows an increase in accuracy with up to 7 %.     

Efficient heuristics for energy-aware routing in networks with bundled links

Current networks are typically over-provisioned to ensure low delays, redundancy and reliability. These Quality of Service (QoS) guarantees are typically achieved using high end, high power network equipments. Their use, however, has led to concerns regarding green house gas emissions, which garnered a lot of attention recently and have resulted in a number of global initiatives aim at reducing the carbon footprint of Internet Service Providers (ISPs). These initiatives have motivated ISPs and researchers to design novel network algorithms and hardware that scale the usage or active time of a network according to traffic load. To this end, this paper considers the problem of shutting down a subset of bundled links during off-peak periods in order to minimize energy expenditure. Unfortunately, identifying the cables that minimize this objective is an NP-complete problem. Henceforth, we propose several practical heuristics based on Dijkstra’s algorithm and Yen’s k-shortest paths algorithm. We evaluated our heuristics on the Abilene network – with both real and synthetic traffic matrices and several larger random topologies with various loads. Our results show that the proposed heuristics to be effective and efficient. Moreover, our approaches could potentially reduce the energy usage of cables used in the Abilene network by up to 56.7%, assuming the traffic demands recorded on September 5, 2004.     

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.     

Quantitative Structural Analysis of Fat Crystal Networks by Means of Raman Confocal Imaging

The techniques that are currently available to assess fat crystal networks are compromised with respect to invasive sample preparation and ability to quantify compositional and structural features. Raman confocal hyperspectral imaging coupled to analysis with multivariate curve resolution can address these bottlenecks, as it provides label‐free, noninvasive chemical information in three dimensions (3D). We demonstrate the ability to acquire compositional maps of dispersions of micronized fat crystals (MFC) in oil, which contain local concentrations of liquid oil and solid fat with submicron spatial resolution and with acquisition times in the order of 10 min. From the compositional maps, we can derive quantitative information on the size and porosity of fat crystal flocs, as well as the solid fat content of the embedding continuous phase. Furthermore, the fractal dimension of the fat crystal network could be determined from the compositional maps via the box‐counting method and via the porosities of the crystal flocs. This makes it feasible to assess the validity of the weak‐link network theory under industrial relevant conditions. The confocal imaging mode allows for straightforward acquisition of 3D compositional cubes by recording a stack of two‐dimensional (2D) images. The box‐counting fractal dimension analysis performed on 2D maps can be extended to 3D cubes, which allows for straightforward verification that MFC networks are self‐similar rather than self‐affine.     

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.     

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.     

Ceria-based oxides as supports for LaCoO3 perovskite; catalysts for total oxidation of VOC

Supported LaCoO₃ perovskites with 10 and 20 wt.% loading were obtained by wet impregnation of different Ce_1−xZr_xO₂ (x = 0–0.3) supports with a solution prepared from La and Co nitrates, and citric acid. Supports were also prepared using the “citrate method”. All materials were calcined at 700 °C for 6 h and investigated by N₂ adsorption at −196 °C, XRD and XPS. XRD patterns and XPS measurements evidenced the formation of a pure perovskite phase, preferentially accumulated at the outer surface. These materials were comparatively tested in benzene and toluene total oxidation in the temperature range 100–500 °C. All catalysts showed a lower T₅₀ than the corresponding Ce_1−xZr_xO₂ supports. Twenty weight percent LaCoO₃ catalysts presented lower T₅₀ than bulk LaCoO₃. In terms of reaction rates per mass unit of perovskite calculated at 300 °C, two facts should be noted (i) the activity order is more than 10 times higher for toluene and (ii) the reverse variation with the loading as a function of the reactant, a better activity being observed for low loadings in the case of benzene. For the same loading, the support composition influences drastically the oxidative abilities of LaCoO₃ by the surface area and the oxygen mobility.