Analysis of Optimum Frame Synchronization Based on Periodically Embedded Sync Words

We present new tight bounds for evaluating the performance of sync word-based frame synchronization algorithms in the periodically embedded case. We consider antipodal signaling with coherent detection over additive white Gaussian noise and both optimal and suboptimal search techniques. Our bounds are very close to results obtained through simulation and tend asymptotically (for increasing signal-to-noise ratios) to the exact performance.     

伦敦证明交通拥堵收费政策如何在大城市发挥效用

一百年以前，在马车时代，穿越伦敦中心区的道路交通平均速度为每小时11英里。到20世纪末，城市交通的速度仍为每小时11英里，而这还只是平均速度。大多数时间，街道拥堵，车辆只能蠕动或者根本就无法移动。     

SESF-Fuse: an unsupervised deep model for multi-focus image fusion

Neural Computing and Applications - Muti-focus image fusion is the extraction of focused regions from different images to create one all-in-focus fused image. The key point is that only objects...     

Electrochemical behaviour of Invar in phosphate solutions at pH=6.0

Electrochemical studies were carried out with disk electrodes of Invar (Fe-36%Ni) in phosphate solution at pH 6.0, using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) techniques, comparing the results with those for low carbon steel and pure Ni. Invar shows a reduced corrosion when compared to carbon steel in the weakly inhibitive solution though inferior to pure Ni. Phosphate anion is responsible for the formation of a protecting and stable film on the alloy surface at pH 6.0.Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) with Invar disk electrodes (Fe-36%Ni) in phosphate solutions at pH=6.0 were carried out. Results were compared with those of carbon steel and pure Ni.     

Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks

Anomaly detection in resource constrained wireless networks is an important challenge for tasks such as intrusion detection, quality assurance and event monitoring applications. The challenge is to detect these interesting events or anomalies in a timely manner, while minimising energy consumption in the network. We propose a distributed anomaly detection architecture, which uses multiple hyperellipsoidal clusters to model the data at each sensor node, and identify global and local anomalies in the network. In particular, a novel anomaly scoring method is proposed to provide a score for each hyperellipsoidal model, based on how remote the ellipsoid is relative to their neighbours. We demonstrate using several synthetic and real datasets that our proposed scheme achieves a higher detection performance with a significant reduction in communication overhead in the network compared to centralised and existing schemes.     

Who and what links to the Internet Archive

The Internet Archive’s (IA) Wayback Machine is the largest and oldest public Web archive and has become a significant repository of our recent history and cultural heritage. Despite its importance, there has been little research about how it is discovered and used. Based on Web access logs, we analyze what users are looking for, why they come to IA, where they come from, and how pages link to IA. We find that users request English pages the most, followed by the European languages. Most human users come to Web archives because they do not find the requested pages on the live Web. About 65 % of the requested archived pages no longer exist on the live Web. We find that more than 82 % of human sessions connect to the Wayback Machine via referrals from other Web sites, while only 15 % of robots have referrers. Most of the links (86 %) from Websites are to individual archived pages at specific points in time, and of those 83 % no longer exist on the live Web. Finally, we find that users who come from search engines browse more pages than users who come from external Web sites.     

<Emphasis Type="Italic">In situ</Emphasis> monitoring of solid fat content by means of pulsed nuclear magnetic resonance spectrometry and ultrasonics

An ultrasonic technique was developed to study the crystallization process of edible fats on-line. A chirp wave was used instead of the conventional pulser signal, thus achieving a higher signal-to-noise ratio. This enabled measurements to be made in concentrated systems [≈20% solid fat content (SFC)] through a 8.11-cm thick sample without significant signal loss. Fat samples were crystallized at 20, 25, and 30°C at a constant agitation rate of 400 rpm for 90 min. The crystallization process was followed by ultrasonic spectroscopy and a low-resolution pulsed nuclear magnetic resonance spectrometer. Specific relationships were found between ultrasonic parameters [integrated response, time of flight (TF), and full width half maximum] and SFC. TF, which is an indirect measurement of the ultrasonic velocity (v), was highly correlated to SFC (r ²>0.9) in a linear fashion (v=2.601 SFC+1433.0).     

Preface

Annals of Mathematics and Artificial Intelligence -     

A lagrangian propagator for artificial neural networks in constraint programming

This paper discusses a new method to perform propagation over a (two-layer, feed-forward) Neural Network embedded in a Constraint Programming model. The method is meant to be employed in Empirical Model Learning, a technique designed to enable optimal decision making over systems that cannot be modeled via conventional declarative means. The key step in Empirical Model Learning is to embed a Machine Learning model into a combinatorial model. It has been showed that Neural Networks can be embedded in a Constraint Programming model by simply encoding each neuron as a global constraint, which is then propagated individually. Unfortunately, this decomposition approach may lead to weak bounds. To overcome such limitation, we propose a new network-level propagator based on a non-linear Lagrangian relaxation that is solved with a subgradient algorithm. The method proved capable of dramatically reducing the search tree size on a thermal-aware dispatching problem on multicore CPUs. The overhead for optimizing the Lagrangian multipliers is kept within a reasonable level via a few simple techniques. This paper is an extended version of [27], featuring an improved structure, a new filtering technique for the network inputs, a set of overhead reduction techniques, and a thorough experimentation.