Estimating hidden message length in binary image embedded by using boundary pixels steganography

In this paper, we propose a new steganalytic method to detect the message hidden in a black and white image using the steganographic technique developed by Liang, Wang and Zhang. Our detection method estimates the length of hidden message embedded in a binary image. Although the hidden message embedded is visually imperceptible, it changes some image statistic (such as inter-pixels correlation). Based on this observation, we first derive the 512 patterns histogram from the boundary pixels as the distinguishing statistic, then we compute the histogram difference to determine the changes of the 512 patterns histogram induced by the embedding operation. Finally we propose histogram quotient to estimate the length of the embedded message. Experimental results confirm that the proposed method can effectively and reliably detect the length of the embedded message.

The applicability of biased estimation in model and model order selection

Biased estimation has the advantage of reducing the mean squared error (MSE) of an estimator. The question of interest is how biased estimation affects model selection. In this paper, we introduce biased estimation to a range of model selection criteria. Specifically, we analyze the performance of the minimum description length (MDL) criterion based on biased and unbiased estimation and compare it against modern model selection criteria such as Kay's conditional model order estimator (CME), the bootstrap and the more recently proposed hook-and-loop resampling based model selection. The advantages and limitations of the considered techniques are discussed. The results indicate that, in some cases, biased estimators can slightly improve the selection of the correct model. We also give an example for which the CME with an unbiased estimator fails, but could regain its power when a biased estimator is used.

Improving the performance of model-order selection criteria by partial-model selection search

The traditional searching method for model-order selection in linear regression is a nested full-parameters-set searching procedure over the desired orders, which we call full-model order selection. On the other hand, a method for model-selection searches for the best sub-model within each order. In this paper, we propose using the model-selection searching method for model-order selection, which we call partial-model order selection. We show by simulations that the proposed searching method gives better accuracies than the traditional one, especially for low signal-to-noise ratios over a wide range of model-order selection criteria (both information theoretic based and bootstrap-based). Also, we show that for some models the performance of the bootstrap-based criterion improves significantly by using the proposed partial-model selection searching method. Index Terms— Model order estimation, model selection, information theoretic criteria, bootstrap 1. INTRODUCTION Several model-order selection criteria can be applied to find the optimal order. Some of the more commonly used information theoretic-based procedures include Akaike’s information criterion (AIC) [1], corrected Akaike (AICc) [2], minimum description length (MDL) [3], normalized maximum likelihood (NML) [4], Hannan-Quinn criterion (HQC) [5], conditional model-order estimation (CME) [6], and the efficient detection criterion (EDC) [7]. From a practical point of view, it is difficult to decide which model order selection criterion to use. Many of them perform reasonably well when the signal-to-noise ratio (SNR) is high. The discrepancies in their performance, however, become more evident when the SNR is low. In those situations, the performance of the given technique is not only determined by the model structure (say a polynomial trend versus a Fourier series) but, more importantly, by the relative values of the parameters within the model. This makes the comparison between the model-order selection algorithms difficult as within the same model with a given order one could find an example for which one of the methods performs favourably well or fails [6, 8]. Our aim is to improve the performance of the model order selection criteria in cases where the SNR is low by considering a model-selection searching procedure that takes into account not only the full-model order search but also a partial model order search within the given model order. Understandably, the improvement in the performance of the model order estimation is at the expense of additional computational complexity.

More than a backchannel : Twitter and television

Twitter is a social media service that has managed very successfully to embed itself deeply in the everyday lives of its users. Its short message length (140 characters), and one-way connections (‘following’ rather than ‘friending’) lend themselves effectively to random and regular updates on almost any form of personal or professional activity – and it has found uses from the interpersonal (e.g. boyd et al., 2010) through crisis communication (e.g. Bruns et al., 2012) to political debate (e.g. Burgess & Bruns, 2012). In such uses, Twitter does not necessarily replace existing media channels, such as the broadcast or online offerings of the mainstream media, but often complements them, providing its users with alternative opportunities to contribute more actively to the wider mediasphere. This is true especially where Twitter is used alongside television, as a simple backchannel to live programming or for more sophisticated uses. In this article, we outline four aspects – dimensions – of the way that the ‘old’ medium of television intersects and, in some cases, interacts, with the ‘new’ medium of Twitter.

Shouting from the ivory tower : a marketing approach to improve communication of academic research to entrepreneurs

Evidence-based practice in entrepreneurship requires effective communication of research findings. We focus on how research synopses can “promote” research to entrepreneurs. Drawing on marketing communications literature, we examine how message characteristics of research synopses affect their appeal. We demonstrate the utility of conjoint analysis in this context and find message length, media richness and source credibility to have positive influences. We find mixed support for a hypothesized negative influence of jargon, and for our predictions that participants’ involvement with academic research moderates these effects. Exploratory analyses reveal latent classes of entrepreneurs with differing preferences, particularly for message length and jargon.

More than a backchannel : Twitter and television

Twitter is a social media service that has managed very successfully to embed itself deeply in the daily lives of its users. Its short message length (140 characters), and one-way connections (‘following’ rather than ‘friending’), lead themselves effectively to random and regular updates on almost any form of personal or professional activity. Thus, it has found uses from the interpersonal (e.g. Boyd et al., 2010) through crisis communication (e.g. Bruns et al., 2012), to political debate (e.g. Burgess & Bruns, 2012). In such uses, Twitter does not necessarily replace existing media channels, such as broadcasting or online mainstream media, but often complements them, providing its users with alternative opportunities to contribute more actively to the wider media sphere. This is true especially where Twitter is used alongside television, as a simple backchannel to live programming or for more sophisticated uses. In this article, we outline four aspects and dimensions, of the way that the old medium of television intersects, and in some cases, interacts with the new medium of Twitter. Tweeting about the television has always been a social media form. It has also consistently provided key ‘talking points’ for western societies...

A cluster-voting approach for speaker diarization and linking of Australian broadcast news recordings

We present a clustering-only approach to the problem of speaker diarization to eliminate the need for the commonly employed and computationally expensive Viterbi segmentation and realignment stage. We use multiple linear segmentations of a recording and carry out complete-linkage clustering within each segmentation scenario to obtain a set of clustering decisions for each case. We then collect all clustering decisions, across all cases, to compute a pairwise vote between the segments and conduct complete-linkage clustering to cluster them at a resolution equal to the minimum segment length used in the linear segmentations. We use our proposed cluster-voting approach to carry out speaker diarization and linking across the SAIVT-BNEWS corpus of Australian broadcast news data. We compare our technique to an equivalent baseline system with Viterbi realignment and show that our approach can outperform the baseline technique with respect to the diarization error rate (DER) and attribution error rate (AER).

A multicast routing scheme for efficient safety message dissemination in VANET

Vehicular ad hoc network (VANET) is a wireless ad hoc network that operates in a vehicular environment to provide communication between vehicles. VANET can be used by a diverse range of applications to improve road safety. Cooperative collision warning system (CCWS) is one of the safety applications that can provide situational awareness and warning to drivers by exchanging safety messages between cooperative vehicles. Currently, the routing strategies for safety message dissemination in CCWS are scoped broadcast. However, the broadcast schemes are not efficient as a warning message is sent to a large number of vehicles in the area, rather than only the endangered vehicles. They also cannot prioritize the receivers based on their critical time to avoid collision. This paper presents a more efficient multicast routing scheme that can reduce unnecessary transmissions and also use adaptive transmission range. The multicast scheme involves methods to identify an abnormal vehicle, the vehicles that may be endangered by the abnormal vehicle, and the latest time for each endangered vehicle to receive the warning message in order to avoid the danger. We transform this multicast routing problem into a delay-constrained minimum Steiner tree problem. Therefore, we can use existing algorithms to solve the problem. The advantages of our multicast routing scheme are mainly its potential to support various road traffic scenarios, to optimize the wireless channel utilization, and to prioritize the receivers.

Context-aware multicast protocol for emergency message dissemination in vehicular networks

Road traffic accidents can be reduced by providing early warning to drivers through wireless ad hoc networks. When a vehicle detects an event that may lead to an imminent accident, the vehicle disseminates emergency messages to alert other vehicles that may be endangered by the accident. In many existing broadcast-based dissemination schemes, emergency messages may be sent to a large number of vehicles in the area and can be propagated to only one direction. This paper presents a more efficient context aware multicast protocol that disseminates messages only to endangered vehicles that may be affected by the emergency event. The endangered vehicles can be identified by calculating the interaction among vehicles based on their motion properties. To ensure fast delivery, the dissemination follows a routing path obtained by computing a minimum delay tree. The multicast protocol uses a generalized approach that can support any arbitrary road topology. The performance of the multicast protocol is compared with existing broadcast protocols by simulating chain collision accidents on a typical highway. Simulation results show that the multicast protocol outperforms the other protocols in terms of reliability, efficiency, and latency.

Enforcing minimum labour standards in Australia from 2010 : correcting or compounding problems

Fair Work Australia is to provide the institutional framework for the Australian industrial relations system from January 2010. Its creation provides the opportunity to improve minimum labour standards’ enforcement in Australia. However, the experience of the past must be appreciated and traditional assumptions about the operation of the Australian enforcement system discarded if the new institution is to be effective in its role. This paper focuses on the role of unions in enforcement as well as institutional location issues to expose a number of central enforcement problems that those seeking to establish new systems and processes should consider. A number of recommendations in respect of the structure of Fair Work Australia and the continuing role of unions are suggested.