Group dynamics and record signals in the ant Temnothorax albipennis

Many purely physical complex systems, in which there are both stochasticity and local interactions between the components, exhibit record dynamics. The temporal statistics of record dynamics is a Poisson process operating on a logarithmic rather than a linear time scale (i.e. a log-Poisson process). Record dynamics often drive substantial changes in complex systems when new high water marks in partially stochastic processes trigger new events. Social insect colonies are exemplary complex biological systems in which many of the local interactions of the components have been moulded by natural selection for the common good. Here, we combine experimental manipulation of ant colony demography with modelling to test the hypothesis that social interactions are the mechanism underlying the record dynamics. We found that compared with the control, log-Poisson statistics were disrupted in colonies in which the pattern of interactions was modified by the removal of the brood, and disappeared completely in ‘callow’ colonies composed entirely of very young workers from the same age cohort. We conclude that a subtle interplay between the demography of the society and the pattern of the interactions between the ants is crucial for the emergence of record dynamics. This could help identify what makes an ant colony a cohesive society.     

Cost‐Efficient Virtual Optical Network Embedding for Manageable Inter‐Data‐Center Connectivity

Network virtualization opens the door to novel infrastructure services offering connectivity and node manageability. In this letter, we focus on the cost‐efficient embedding of on‐demand virtual optical network requests for interconnecting geographically distributed data centers. We present a mixed integer linear programming formulation that introduces flexibility in the virtual‐physical node mapping to optimize the usage of the underlying physical resources. Illustrative results show that flexibility in the node mapping can reduce the number of add‐drop ports required to serve the offered demands by 40%.     

Fractal modeling techniques for spatial data

The paper presents convolutional linear data models for the processing of one-dimensional (1D) and two-dimensional (2D) spatial data. The models assume that the measured data is the superposition of a stochastic innovation process and a deterministic system function. The innovation process is described by a fractal scaling noise, which has a power spectral density proportional to some power (-β) of the frequency. The system function is assumed to be symmetric and is constructed using autoregressive (AR) filtering procedures. Iterative deconvolution procedures are developed to recover the fractal innovation from the data. For computational convenience, these procedures assume a spectrally white (β=0) innovation, but modify the data prior to inversion by prewhitening the a priori assumed fractal innovation. The filter coefficients recovered by inverting the modified data are then applied to the original data to recover the fractal innovation. The ability of the deconvolution procedures to recover the fractal innovation is demonstrated using 1D and 2D synthetic data sets. As a practical example, the 2D deconvolution technique is applied to an aeromagnetic map from northeastern Ontario, Canada, and is shown to be effective in enhancing magnetic field anomalies     

A Matrix Formulation of Discrete Chirp Fourier Transform Algorithms

This work presents a computational matrix framework in terms of tensor signal algebra for the formulation of discrete chirp Fourier transform algorithms.These algorithms are used in this work to estimate the point target functions(impulse response functions)of multiple-input multiple-output(MIMO)synthetic aperture radar(SAR)systems.This estimation technique is being studied as an alternative to the estimation of point target functions using the discrete cross-ambiguity function for certain types of environmental surveillance applications.The tensor signal algebra is presented as a mathematics environment composed of signal spaces,finite dimensional linear operators,and special matrices where algebraic methods are used to generate these signal transforms as computational estimators.Also,the tensor signal algebra contributes to analysis,design,and implementation of parallel algorithms.An instantiation of the framework was performed by using the MATLAB Parallel Computing Toolbox,where all the algorithms presented in this paper were implemented.     

EEG complexity as a measure of depth of anesthesia for patients

A new approach for quantifying the relationship between brain activity patterns and depth of anesthesia (DOA) is presented by analyzing the spatio-temporal patterns in the electroencephalogram (EEG) using Lempel-Ziv complexity analysis. Twenty-seven patients undergoing vascular surgery were studied under general anesthesia with sevoflurane, isoflurane, propofol, or desflurane. The EEG was recorded continuously during the procedure and patients' anesthesia states were assessed according to the responsiveness component of the observer's assessment of alertness/sedation (OAA/S) score. An OAA/S score of zero or one was considered asleep and two or greater was considered awake. Complexity of the EEG was quantitatively estimated by the measure C(n), whose performance in discriminating awake and asleep states was analyzed by statistics for different anesthetic techniques and different patient populations. Compared with other measures, such as approximate entropy, spectral entropy, and median frequency, C(n) not only demonstrates better performance (93% accuracy) across all of the patients, but also is an easier algorithm to implement for real-time use. The study shows that C(n) is a very useful and promising EEG-derived parameter for characterizing the (DOA) under clinical situations.     

Distributed cross-layer coordination of congestion control and resource allocation in S-TDMA wireless networks

We consider the problem of joint congestion control and resource allocation in spatial-TDMA wireless networks. The design problem is posed as a utility maximization problem subject to link rate constraints which involve both transmission scheduling and power allocation. Starting from the performance limitations of a centralized optimization based on global network information, we proceed systematically in our development of two distributed and transparent protocols that rely on local information only. In the process, we introduce a novel decomposition method for convex optimization, establish its convergence for the utility maximization problem, and demonstrate how it suggests a distributed solution based on TCP/AQM and incremental updates of the transmission schedule. We develop a two-step procedure for finding the schedule updates and suggest two schemes for distributed link scheduling and power control under realistic interference models. Although the final protocols are suboptimal, we isolate and quantify the performance losses incurred by each simplification and demonstrate strong performance in examples.

Emulation-based transient thermal modeling of 2D/3D systems-on-chip with active cooling

State-of-the-art devices in the consumer electronics market are relying more and more on Multi-Processor Systems-On-Chip (MPSoCs) as an efficient solution to meet their multiple design constrains, such as low cost, low power consumption, high performance and short time-to-market. In fact, as technology scales down, logic density and power density increase, generating hot spots that seriously affect the MPSoC performance and can physically damage the final system behavior. Moreover, forthcoming three-dimensional (3D) MPSoCs can achieve higher system integration density, but the aforementioned thermal problems are seriously aggravated. Thus, new thermal exploration tools are needed to study the temperature variation effects inside 3D MPSoCs. In this paper, we present a novel approach for fast transient thermal modeling and analysis of 3D MPSoCs with active (liquid) cooling solutions, while capturing the hardware-software interaction. In order to preserve both accuracy and speed, we propose a close-loop framework that combines the use of Field Programmable Gate Arrays (FPGAs) to emulate the hardware components of 2D/3D MPSoC platforms with a highly optimized thermal simulator, which uses an RC-based linear thermal model to analyze the liquid flow. The proposed framework offers speed-ups of more than three orders of magnitude when compared to cycle-accurate 3D MPSoC thermal simulators. Thus, this approach enables MPSoC designers to validate different hardware- and software-based 3D thermal management policies in real-time, and while running real-life applications, including liquid cooling injection control.     

Reducing channel change delay in IPTV by predictive pre-joining of TV channels

One of the major concerns of IPTV network deployment is channel change delay (also known as zapping delay). This delay can add up to 2 s or more, and its main culprits are synchronisation and buffering of the media streams. Proving the importance of the problem is the already significant amount of literature addressing it. We start this paper with a survey of techniques proposed to reduce IPTV channel change delay.Then, by analysing an extensive dataset from an operational IPTV provider - comprising 255 thousand users, 150 TV channels, and covering a 6-month period - we have observed that most channel switching events are relatively predictable: users very frequently switch linearly, up or down to the next TV channel. This fact motivated us to use this dataset to analyse in detail a specific type of solutions to this problem, namely, predictive pre-joining of TV channels. In these schemes each set top box (STB) simultaneously joins additional multicast groups (TV channels) along with the one that is requested by the user. If the user switches to any of these channels the switching latency is virtually eliminated, not affecting therefore user's experience.We start by evaluating a simple scheme, where the neighbouring channels (i.e., channels adjacent to the requested one) are pre-joined by the STB during zapping periods. Notwithstanding the simplicity of this scheme, trace-driven simulations show that the zapping delay can be virtually eliminated for a significant percentage of channel switching requests. For example, when sending the previous and the next channel concurrently with the requested one, for only 1 min after a zapping event, switching delay is eliminated for close to half of all channel switching requests. Importantly, this result is achieved with a negligible increase of bandwidth utilisation in the access link. Other more complex schemes where user behaviour is tracked were also evaluated, but the improvement over the simple scheme was insignificant.     

Effects of JPEG2000 data compression on an automated system for detecting clustered microcalcifications in digital mammograms.

The functionalities of the JPEG2000 standard have led to its incorporation into digital imaging and communications in medicine (DICOM), which makes this compression method available for medical systems. In this study, we evaluated the compression of mammographic images with JPEG2000 (16 : 1, 20 : 1, 40 : 1, 60.4 : 1, 80: 1, and 106 : 1) for applications with a computer-aided detection (CAD) system for clusters of microcalcifications. Jackknife free-response receiver operating characteristic (JAFROC) analysis indicated that differences in the detection of clusters of microcalcifications were not statistically significant for uncompressed versus 16: 1 (T = -0.7780; p = 0.4370), 20 : 1 (T = 1.0361; p = 0.3007), and 40 : 1 (T = 1.6966; p = 0.0904); and statistically significant for uncompressed versus 60.4 : 1 (T = 5.8883; p < 0.008), 80 : 1 (T = 7.8414; p < 0.008), and 106 : 1 (T = 17.5034; p = < 0.008). Although there is a small difference in peak signal-to-noise ratio (PSNR) between compression ratios, the true-positive (TP) and false-positive (FP) rates, and the free-response receiver operating characteristic (FROC), figure of merit values considerably decreased from a 60 : 1 compression ratio. The performance of the CAD system is significantly reduced when using images compressed at ratios greater than 40 : 1 with JPEG2000 compared to uncompressed images. Mammographic images compressed up to 20 : 1 provide a percentage of correct detections by our CAD system similar to uncompressed images, regardless of the characteristics of the cluster. Further investigation is required to determine how JPEG2000 affects the detectability of clusters of microcalcifications as a function of their characteristics.     

Dynamic modelling of service delivery

Planning to deliver excellent service by balancing demand and supply in the context of a set of business policies is not an easy task. How an organisation dynamically deploys its resources and people in response to external demand determines how quickly an organisation can deliver service to its customers. To model this you need to represent the flows of work through the organisation, the resources available and the relationships between intake of work, outputs, workstacks and time-to-deliver. You also need to understand how flexible the organisation is in dealing with uncertain and fluctuating intakes and the policies the organisation adopts in deploying this flexibility. We have constructed a model of the operations of a telecommunications company that incorporates all of these elements using the system dynamics approach. This paper describes how the model is constructed and gives examples of how it can be used to explain observed behaviours. It also explains how it has been used to guide decision making on resource requirements and the optimum mix between proactive and reactive approaches to service assurance.