Using online linear classifiers to filter spam emails

The performance of two online linear classifiers—the Perceptron and Littlestone’s Winnow—is explored for two anti-spam filtering benchmark corpora—PU1 and Ling-Spam. We study the performance for varying numbers of features, along with three different feature selection methods: information gain (IG), document frequency (DF) and odds ratio. The size of the training set and the number of training iterations are also investigated for both classifiers. The experimental results show that both the Perceptron and Winnow perform much better when using IG or DF than using odds ratio. It is further demonstrated that when using IG or DF, the classifiers are insensitive to the number of features and the number of training iterations, and not greatly sensitive to the size of training set. Winnow is shown to slightly outperform the Perceptron. It is also demonstrated that both of these online classifiers perform much better than a standard Naïve Bayes method. The theoretical and implementation computational complexity of these two classifiers are very low, and they are very easily adaptively updated. They outperform most of the published results, while being significantly easier to train and adapt. The analysis and promising experimental results indicate that the Perceptron and Winnow are two very competitive classifiers for anti-spam filtering.     

Frequency Domain Frequency Shift for Optimal Filtering of Cyclostationary Signals

Parker, G., Frequency Domain Frequency Shift for Optimal Filtering of Cyclostationary Signals, Digital Signal Processing12 (2002) 561–589Optimum reconstruction of corrupted cyclostationary signals is achieved using the filter class known as the frequency shift filter. This filter requires the received signal to be shifted by the frequencies of cyclostationarity of the signal and with a frequency domain implementation it will often be best to effect the frequency shifts directly in the frequency domain. This paper introduces techniques for exactly achieving these shifts as well as providing more computationally efficient approximate solutions.     

Exploitation of Social Media for Emergency Relief and Preparedness: Recent Research and Trends

Online Social Media, such as Twitter, Facebook and WhatsApp, are important sources of real-time information related to emergency events, including both natural calamities, man-made disasters, epidemics, and so on. There has been lot of recent work on designing information systems that would be useful for aiding post-disaster relief operations, as well as for pre-disaster preparedness. A special issue on “Exploitation of Social Media for Emergency Relief and Preparedness” was conducted for the journal Information Systems Frontiers. The objective of this special issue was to present a platform for dissemination of the empirical results of various technologies for extracting vital and actionable information from social media content in disaster situations. The papers included in this issue are expected to be the stepping stones for future explorations and technical innovations towards technologies meant for utilizing various online and offline information sources for enhancing pre-disaster preparedness and post-disaster relief operations.     

The regular polygon detector

This paper describes a robust regular polygon detector. Given image edges, we derive the a posteriori probability for a mixture of regular polygons, and thus the probability density function for the appearance of a set of regular polygons. Likely regular polygons can be isolated quickly by discretising and collapsing the search space into three dimensions. We derive a complete formulation for efficiently recovering the remaining dimensions using maximum likelihood at the locations of the most likely polygons. Results show robustness to noise, the ability to find and differentiate different shape types, and to perform real-time sign detection for driver assistance.     

Local Image Features Resulting from 3-Dimensional Geometric Features,Illumination, and Movement: I

We study images of smooth or piecewise smooth objects illuminated by a single light source, with only background illumination from other sources. The objects may have geometric features (F), namely surface markings, boundary edges, creases and corners; and shade features (S), namely shade curves and cast shadow curves. We determine the local stable interactions between these and apparent contours (C) for the various configurations of F, S, C, and we concisely summarize them using an “alphabet” of local curve configurations. We further determine the generic transitions for the configurations resulting from viewer movement. These classifications are obtained using the methods of singularity theory, which allows us to ensure that our lists are complete, in some cases correcting earlier attempts at similar classifications. Authors were partially supported by Insight 2+ grant from the European Commission. J. Damon was partially supported by the National Science Foundation grants DMS-0405947 and DMS-0706941.     

Situational awareness architecture for smart grids developed in accordance with dispatcher’s thought process: a review

The operational environment of today’s smart grids is becoming more complicated than ever before. A number of factors, including renewable penetration, marketization, cyber security, and hazards of nature, bring challenges and even threats to control centers. New techniques are anticipated to help dispatchers become aware of the accurate situations as they manipulate and navigate the situations as quickly as possible. To address the issues, we first introduce the background for this topic as well as the emerging technical demands of situational awareness in the dispatcher’s environment. The general concepts and technical requirements of situational awareness are then summarized, aimed at offering an overview for readers to understand the state-of-the-art progress in this area. In addition, we discuss the importance of integrating the architecture of support tools in accordance with the dispatcher’s thought process, which in fact guides correct and swift reactions in real-time operations. Finally, the prospects for situational awareness architecture are investigated with the goal of presenting situational awareness modules in an advanced and visualized manner.     

ONTRACK: Dynamically adapting music playback to support navigation

Listening to music on personal, digital devices whilst mobile is an enjoyable, everyday activity. We explore a scheme for exploiting this practice to immerse listeners in navigation cues. Our prototype, ONTRACK, continuously adapts audio, modifying the spatial balance and volume to lead listeners to their target destination. First we report on an initial lab-based evaluation that demonstrated the approach’s efficacy: users were able to complete tasks within a reasonable time and their subjective feedback was positive. Encouraged by these results we constructed a handheld prototype. Here, we discuss this implementation and the results of field-trials. These indicate that even with a low-fidelity realisation of the concept, users can quite effectively navigate complicated routes.

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Rates of mass transfer to patch electrodes in disturbed flows using oxygen reduction under limiting current conditions

The cases of a sudden pipe expansion and a sudden pipe contraction are simulated within a flow loop-based test section designed to approximate disturbed conduit flow. Mass transfer rates to patch electrodes at selected positions within the test section have been measured using a limiting current methodology applied to oxygen reduction at copper in 3.5% wt./vol. NaCl. Using both large-scale polarisation linear sweep voltammetry and a potential step current transient technique with hydrodynamic steps, absolute and relative rates of oxygen mass transfer have been examined as a function of Reynolds number and location within the test section. The highest rates of oxygen transfer were observed both within the high velocity area of the test section and close to known regions of flow disturbance. Under the flow conditions used, patch electrode mass transfer relates to wall shear stress, which allowed areas of high mean and high fluctuating wall shear stress to be identified.     

Problem-Based Learning Approach to Construction Management Teaching

This paper describes construction management teaching for the Master of Engineering in civil engineering course at the University of Glasgow in the United Kingdom. This course is a 5-yr undergraduate degree accredited by the Institution of Civil Engineers for membership in the Institution subject to graduates satisfying the appropriate postgraduate training objectives. Construction management teaching takes place in the third, fourth, and fifth years of the degree and is structured to make effective use of both traditional and problem-based learning teaching methods. Examples are given of two problem-based learning courses used in the fourth and fifth year of the degree course. Both are based on complex construction projects and provide students with the opportunity to apply and synthesis knowledge gained on the traditionally taught third year course. Formal feedback from students and informal feedback from local industry suggests that the courses are meeting their overall objective of producing graduates with relevant knowledge and skills in construction management.