A new adaptive blind channel identification algorithm

This paper addresses the blind identification of single-input multiple-output (SIMO) finite-impulse-response (FIR) systems. We first propose a new adaptive algorithm for the blind identification of SIMO FIR systems. Then, its convergence property is analyzed systematically. It is shown that under some mild conditions, the proposed algorithm is guaranteed to converge in the mean to the true channel impulse responses in both noisy and noiseless cases. Simulations are carried out to demonstrate the theoretical results.

Some aspects of adaptive cluster sampling

The adaptive cluster sampling (ACS) procedure is difficult to apply if some of the networks appearing in the sample are large. To deal with such large networks, a two-stage adaptive cluster sampling (TACS) procedure and an adjusted two-stage adaptive cluster sampling (ATACS) procedure are discussed.

Uplink power control via adaptive hmm estimation

Transmit power control is an important consideration in the cellular system design since it increases system capacity, improves QoS and reduces multi-user interference. In this paper, an adaptive power control design based on the identification of the underlying pathloss of the fading channel is presented. Making power control decisions based on the measured received power allows to model the fading channel pathloss dynamics with a Hidden Markov Model. Applying the online HMM identification algorithm enables accurate estimation of the real pathloss which ensures efficient performance of the suggested power control scheme.

Incremental and adaptive clustering stream data over sliding window

Cluster analysis has played a key role in data stream understanding. The problem is difficult when the clustering task is considered in a sliding window model in which the requirement of outdated data elimination must be dealt with properly. We propose SWEM algorithm that is designed based on the Expectation Maximization technique to address these challenges. Equipped in SWEM is the capability to compute clusters incrementally using a small number of statistics summarized over the stream and the capability to adapt to the stream distribution’s changes. The feasibility of SWEM has been verified via a number of experiments and we show that it is superior than Clustream algorithm, for both synthetic and real datasets.

Adaptive hierarchical scheduling policy for enterprise grid computing systems

In an enterprise grid computing environments, users have access to multiple resources that may be distributed geographically. Thus, resource allocation and scheduling is a fundamental issue in achieving high performance on enterprise grid computing. Most of current job scheduling systems for enterprise grid computing provide batch queuing support and focused solely on the allocation of processors to jobs. However, since I/O is also a critical resource for many jobs, the allocation of processor and I/O resources must be coordinated to allow the system to operate most effectively. To this end, we present a hierarchical scheduling policy paying special attention to I/O and service-demands of parallel jobs in homogeneous and heterogeneous systems with background workload. The performance of the proposed scheduling policy is studied under various system and workload parameters through simulation. We also compare performance of the proposed policy with a static space–time sharing policy. The results show that the proposed policy performs substantially better than the static space–time sharing policy.

An efficient adaptive scheduling policy for high-performance computing

The advent of commodity-based high-performance clusters has raised parallel and distributed computing to a new level. However, in order to achieve the best possible performance improvements for large-scale computing problems as well as good resource utilization, efficient resource management and scheduling is required. This paper proposes a new two-level adaptive space-sharing scheduling policy for non-dedicated heterogeneous commodity-based high-performance clusters. Using trace-driven simulation, the performance of the proposed scheduling policy is compared with existing adaptive space-sharing policies. Results of the simulation show that the proposed policy performs substantially better than the existing policies.

Adaptive intelligent systems for energy management of vehicles

The thesis demonstrated the architecture of adaptive intelligent systems for energy management that is capable of interacting with complex systems including the vehicle, environment, and driver components, as well as the interrelationships between these variables, to deliver fuel consumption improvements.

On the influence of building design, occupants and heat waves on comfort and greenhouse gas emissions in naturally ventilated offices. A study based on the EN 15251 adaptive thermal comfort model in Athens, Greece

According to the Intergovernmental Panel on Climate Change the buildings sector has the largest mitigation potential for CO2 emissions. Especially in office buildings, where internal heat loads and a relatively high occupant density occur at the same time with solar heat gains, overheating has become a common problem. In Europe the adaptive thermal comfort model according to EN 15251 provides a method to evaluate thermal comfort in naturally ventilated buildings. However, especially in the context of the climate change and the occurrence of heat waves within the last decade, the question arises, how thermal comfort can be maintained without additional cooling, especially in warm climates. In this paper a parametric study for a typical cellular naturally ventilated office room has been conducted, using the building simulation software EnergyPlus. It is based on the Mediterranean climate of Athens, Greece. Adaptive thermal comfort is evaluated according to EN 15251. Variations refer to different building design priorities, and they consider the variability of occupant behaviour and internal heat loads by using an ideal and worst case scenario. The influence of heat waves is considered by comparing measured temperatures for an average and an exceptionally hot year within the last decade. Since the use of building controls for shading affects thermal as well as visual comfort, daylighting and view are evaluated as well. Conclusions are drawn regarding the influence and interaction of building design, occupants and heat waves on comfort and greenhouse gas emissions in naturally ventilated offices, and related optimisation potential.

Designing adaptive artificial agents for an economic production and conflict model

Production and conflict models have been used over the past 30 years to represent the effects of unproductive resource allocation in economics. Their major applications are in modelling the assignment of property rights, rentseeking and defense economics. This paper describes the process of designing an agent used in a production and conflict model. Using the capabilities of an agent-based approach to economic modelling, we have enriched a simple decision-maker of the kind used in classic general equilibrium economic models, to build an adaptive and interactive agent which uses its own attributes, its neighbors’ parameters and information from its environment to make resource allocation decisions. Our model presents emergent and adaptive behaviors than cannot be captured using classic production and conflict agents. Some possible extensions for future applications are also recommended.

Maternal stress to partner quality is linked to adaptive offspring sex ratio adjustment

Female birds have been shown to have a remarkable degree of control over the sex ratio of the offspring they produce. However, it remains poorly understood how these skews are achieved. Female condition, and consequent variation in circulating hormones, provides a plausible mechanistic link between offspring sex biases and the environmental and social stresses commonly invoked to explain adaptive sex allocation, such as diet, territory quality, and body condition. However, although experimental studies have shown that female perception of male phenotype alone can lead to sex ratio biases, it is unknown how partner quality influences female physiological state. Using a controlled within-female experimental design where female Gouldian finches (Erythrura gouldiae) bred with both high- and low-quality males, we found that partner quality directly affects female hormonal status and subsequent fitness. When constrained to breeding with low-quality males, females had highly elevated stress responses (corticosterone levels) and produced adaptive male-biased sex ratios, whereas when they bred with high-quality males, females had low corticosterone levels and produced an equal offspring sex ratio. There was no effect of other maternal hormones (e.g., testosterone) or body condition on offspring sex ratios. Female physiological condition during egg production, and variation in circulating hormones in particular, may provide a general mechanistic route for strategic sex allocation in birds.

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.