Adaptive data based neural network leader-follower control of multi-agent networks

In this paper, we propose a data based neural network leader-follower control for multi-agent networks where each agent is described by a class of high-order uncertain nonlinear systems with input perturbation. The control laws are developed using multiple-surface sliding control technique. In particular, novel set of sliding variables are proposed to guarantee leader-follower consensus on the sliding surfaces. Novel switching is proposed to overcome the unavailability of instantaneous control output from the neighbor. By utilizing RBF neural network and Fourier series to approximate the unknown functions, leader-follower consensus can be reached, under the condition that the dynamic equations of all agents are unknown. An O(n) data based algorithm is developed, using only the network’s measurable input/output data to generate the distributed virtual control laws. Simulation results demonstrate the effectiveness of the approach.

Comparison of the EN 15251 and Ashrae Standard 55 adaptive thermal comfort models in the context of a Mediterranean climate

Strong heat waves in the past decade and resulting legal cases which gave full responsibility for indoor thermal comfort to building professionals lead to an increased uncertainty how to maintain thermal comfort in offices without the use of a cooling system. Adaptive thermal comfort standards such as EN 15251 and Ashrae Standard 55 provide methodologies to evaluate comfort in naturally ventilated spaces. Based on a parametric study for a typical cellular office in the context of Athens, Greece, and using the building simulation software EnergyPlus, this study investigates the potentials for the applicability of natural ventilation in a Mediterranean climate. The Ashrae Standard 55 and EN 15251 adaptive thermal comfort models are compared in this context, and conclusions are drawn how the use of natural ventilation based on adaptive models can be further encourgaged.

Origins of adaptive immunity

Adaptive immunity, involving distinctive antibody- and cell-mediated responses to specific antigens based on "memory" of previous exposure, is a hallmark of higher vertebrates. It has been argued that adaptive immunity arose rapidly, as articulated in the "big bang theory" surrounding its origins, which stresses the importance of coincident whole-genome duplications. Through a close examination of the key molecules and molecular processes underpinning adaptive immunity, this review suggests a less-extreme model, in which adaptive immunity emerged as part of longer evolutionary journey. Clearly, whole-genome duplications provided additional raw genetic materials that were vital to the emergence of adaptive immunity, but a variety of other genetic events were also required to generate some of the key molecules, whereas others were preexisting and simply co-opted into adaptive immunity.

Adaptive cruise control look-ahead system for energy management of vehicles

Cruise control in motor vehicles enhances safe and efficient driving by maintaining a constant speed at a preset level. Adaptive Cruise Control (ACC) is the latest development in cruise control. It controls engine throttle position and braking to maintain a safe distance behind a vehicle in front by responding to the speed of this vehicle, thus providing a safer and more relaxing driving environment. ACC can be further developed by including the look-ahead method of predicting environmental factors such as wind speed and road slope. The conventional analytical control methods for adaptive cruise control can generate good results; however they are difficult to design and computationally expensive. In order to achieve a robust, less computationally expensive, and at the same time more natural human-like speed control, intelligent control techniques can be used. This paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS) based on ACC systems that reduces the energy consumption of the vehicle and improves its efficiency. The Adaptive Cruise Control Look-Ahead (ACC-LA) system works as follows: It calculates the energy consumption of the vehicle under combined dynamic loads like wind drag, slope, kinetic energy and rolling friction using road data, and it includes a look-ahead strategy to predict the future road slope. The cruise control system adaptively controls the vehicle speed based on the preset speed and the predicted future slope information. By using the ANFIS method, the ACC-LA is made adaptive under different road conditions (slope angle and wind direction and speed). The vehicle was tested using the adaptive cruise control look-ahead energy management system, the results compared with the vehicle running the same test but without the adaptive cruise control look-ahead energy management system. The evaluation outcome indicates that the vehicle speed was efficiently controlled through the look-ahead methodology based upon the driving cycle, and that the average fuel consumption was reduced by 3%.

Adaptive depletion for improvement of MPEG video compression

Traditional data compression algorithms for 2D images work using the information theoretic paradigm, attempting to reduce redundant information by as much as possible. However, through the use of a depletion algorithm that takes advantage of characteristics of the human visual system, images can be displayed using only half or a quarter of the original information with no appreciable loss of quality.

The characteristics of the human visual system that allows the viewer to perceive a higher rate of information than is actually displayed is known as the beta or picket fence effect. It is called the picket fence effect because its effect is noticeable when a person is travelling along a picket fence. Despite the person not having an unimpeded view of the objects behind the fence at any instant, as the person is moving, the objects behind the picket fence are clearly visible. In fact, in most cases the fence is hardly noticeable at all.

The techniques we have developed uses this effect to achieve higher levels of compression than would otherwise be possible. As a fundamental characteristic of the beta effect is the requirement that there is movement of the fence in relation to the object, the beta effect can only be used in image sequences where movement between the depletion pattern and objects within the image can be achieved.

As MPEG is the recognised standard by which image sequences are coded, compatibility with MPEG is essential. We have modified our technique such that it performs in conjunction with MPEG, providing further compression over MPEG.

Adaptive speech enhancement with varying noise backgrounds

We present a new approach for speech enhancement in the presence of non-stationary and rapidly changing background noise. A distributed microphone system is used to capture the acoustic characteristics of the environment. The input of each microphone is then classified either as speech or one of the predetermined noise types. Further enhancement of speech in respective microphones is carried out using a modified spectral subtraction algorithm that incorporates multiple noise models to quickly adapt to rapid background noise changes. Tests on real world speech captured under diverse conditions demonstrate the effectiveness of this method.

Adaptive model for foreground extraction in adverse lighting conditions

Background elimination models are widely used in motion tracking systems. Our aim is to develop a system that performs reliably under adverse lighting conditions. In particular, this includes indoor scenes lit partly or entirely by diffuse natural light. We present a modified "median value" model in which the detection threshold adapts to global changes in illumination. The responses of several models are compared, demonstrating the effectiveness of the new model.

A globally convergent MC algorithm with an adaptive learning rate

This brief deals with the problem of minor component analysis (MCA). Artificial neural networks can be exploited to achieve the task of MCA. Recent research works show that convergence of neural networks based MCA algorithms can be guaranteed if the learning rates are less than certain thresholds. However, the computation of these thresholds needs information about the eigenvalues of the autocorrelation matrix of data set, which is unavailable in online extraction of minor component from input data stream. In this correspondence, we introduce an adaptive learning rate into the OJAn MCA algorithm, such that its convergence condition does not depend on any unobtainable information, and can be easily satisfied in practical applications.

Infusion with the antioxidant N-acetylcysteine attenuates early adaptive responses to exercise in human skeletal muscle

Aim:  Production of reactive oxygen species (ROS) in skeletal muscle is markedly increased during exercise and may be essential for exercise adaptation. We, therefore, investigated the effects of infusion with the antioxidant N-acetylcysteine (NAC) on exercise-induced activation of signalling pathways and genes involved in exercise adaptation in human skeletal muscle.

Methods:  Subjects completed two exercise tests, 7 days apart, with saline (control, CON) or NAC infusion before and during exercise. Exercise tests comprised of cycling at 71%inline image2peak for 45 min, and then 92% \dot{{V}}\hbox{O}2peak to fatigue, with vastus lateralis biopsies at pre-infusion, after 45-min cycling and at fatigue.

Results:  Analysis was conducted on the mitogen-activated protein kinase signalling pathways, demonstrating that NAC infusion blocked the exercise-induced increase in JNK phosphorylation, but not ERK1/2, or p38 MAPK. Nuclear factor-κB p65 phosphorylation was unaffected by exercise; however, it was reduced in NAC at fatigue by 14% (P < 0.05) compared with pre-infusion. Analysis of exercise and/or ROS-sensitive genes demonstrated that exercise-induced mRNA expression is ROS dependent of MnSOD, but not PGC-1α, interleukin-6, monocyte chemotactic protein-1, or heat-shock protein 70.

Conclusion:  These results suggest that inhibition of ROS attenuates some skeletal muscle cell signalling pathways and gene expression involved in adaptations to exercise.

RNA interference : more than a research tool in the vertebrates' adaptive immunity

In recent years, RNA silencing, usage of small double stranded RNAs of ~21 – 25 base pairs to regulate gene expression, has emerged as a powerful research tool to dissect the role of unknown host cell factors in this 'post-genomic' era. While the molecular mechanism of RNA silencing has not been precisely defined, the revelation that small RNA molecules are equipped with this regulatory function has transformed our thinking on the role of RNA in many facets of biology, illustrating the complexity and the dynamic interplay of cellular regulation. As plants and invertebrates lack the protein-based adaptive immunity that are found in jawed vertebrates, the ability of RNA silencing to shut down gene expression in a sequence-specific manner offers an explanation of how these organisms counteract pathogen invasions into host cells. It has been proposed that this type of RNA-mediated defence mechanism is an ancient form of immunity to offset the transgene-, transposon- and virus-mediated attack. However, whether 1) RNA silencing is a natural immune response in vertebrates to suppress pathogen invasion; or 2) vertebrate cells have evolved to counteract invasion in a 'RNA silencing' independent manner remains to be determined. A number of recent reports have provided tantalizing clues to support the view that RNA silencing functions as a physiological response to regulate viral infection in vertebrate cells. Amongst these, two manuscripts that are published in recent issues of Science and Immunity, respectively, have provided some of the first direct evidences that RNA silencing is an important component of antiviral defence in vertebrate cells. In addition to demonstrating RNA silencing to be critical to vertebrate innate immunity, these studies also highlight the potential of utilising virus-infection systems as models to refine our understanding on the molecular determinants of RNA silencing in vertebrate cells.

Adaptive mechanically controlled lubrication mechanism found in articular joints

Articular cartilage is a highly efficacious water-based tribological system that is optimized to provide low friction and wear protection at both low and high loads (pressures) and sliding velocities that must last over a lifetime. Although many different lubrication mechanisms have been proposed, it is becoming increasingly apparent that the tribological performance of cartilage cannot be attributed to a single mechanism acting alone but on the synergistic action of multiple "modes" of lubrication that are adapted to provide optimum lubrication as the normal loads, shear stresses, and rates change. Hyaluronic acid (HA) is abundant in cartilage and synovial fluid and widely thought to play a principal role in joint lubrication although this role remains unclear. HA is also known to complex readily with the glycoprotein lubricin (LUB) to form a cross-linked network that has also been shown to be critical to the wear prevention mechanism of joints. Friction experiments on porcine cartilage using the surface forces apparatus, and enzymatic digestion, reveal an "adaptive" role for an HA-LUB complex whereby, under compression, nominally free HA diffusing out of the cartilage becomes mechanically, i.e., physically, trapped at the interface by the increasingly constricted collagen pore network. The mechanically trapped HA-LUB complex now acts as an effective (chemically bound) "boundary lubricant"-reducing the friction force slightly but, more importantly, eliminating wear damage to the rubbing/shearing surfaces. This paper focuses on the contribution of HA in cartilage lubrication; however, the system as a whole requires both HA and LUB to function optimally under all conditions.