Analysis of information leakage from encrypted Skype conversations

Voice over IP (VoIP) has experienced a tremendous growth over the last few years and is now widely used among the population and for business purposes. The security of such VoIP systems is often assumed, creating a false sense of privacy. This paper investigates in detail the leakage of information from Skype, a widely used and protected VoIP application. Experiments have shown that isolated phonemes can be classified and given sentences identified. By using the dynamic time warping (DTW) algorithm, frequently used in speech processing, an accuracy of 60% can be reached. The results can be further improved by choosing specific training data and reach an accuracy of 83% under specific conditions. The initial results being speaker dependent, an approach involving the Kalman filter is proposed to extract the kernel of all training signals.

The Critical Reading of the Images Associated with Science-Related News Reports: Establishing a knowledge, skills, and attitudes framework

For the majority of adults, the media constitute their main source of information about science and science-related matters impacting on society. To help prepare young people to engage with science in the media, teachers are being exhorted to equip their students with the knowledge, skills, and attitudes to respond critically to science-related news reports. Typically, such reports comprise not only text, but also visual elements. These images are not simply adjuncts to the written word; they are integral to meaning-making. Though science teachers make considerable use of newspaper images, they tend to view these representations unproblematically, underestimating their potential ambiguity, complexity, and role in framing media messages. They rarely aim to develop students’ ability to ‘read’, critically, such graphics. Moreover, research into how this might be achieved is limited and, consequently, research-informed guidance which could support this instruction is lacking. This paper describes a study designed to formulate a framework for such teaching. Science communication scholars, science journalists and media educators with acknowledged relevant expertise were surveyed to ascertain what knowledge, skills, and attitudes they deemed useful to engagement with science related news images. Their proposals were recast as learning intentions (instructional objectives), and science and English teachers collaborated to suggest which could be addressed with secondary school students and the age group best suited to their introduction. The outcome is an inventory of learning intentions on which teachers could draw to support their planning of instructional sequences aimed at developing students’ criticality in respect of the totality of science news reports.

A Visual Analytics Framework for Strategic Airlift Decision Making

The foundational concept of Network Enabled Capability relies on effective, timely information sharing. This information is used in analysis, trade and scenario studies, and ultimately decision-making. In this paper, the concept of visual analytics is explored as an enabler to facilitate rapid, defensible, and superior decision-making. By coupling analytical reasoning with the exceptional human capability to rapidly internalize and understand visual data, visual analytics allows individual and collaborative decision-making to occur in the face of vast and disparate data, time pressures, and uncertainty. An example visual analytics framework is presented in the form of a decision-making environment centered on the Lockheed C-5A and C-5M aircraft. This environment allows rapid trade studies to be conducted on design, logistics, and capability within the aircraft?s operational roles. Through this example, the use of a visual analytics decision-making environment within a military environment is demonstrated.

A spatio-temporal 2D-models framework for human pose recovery in monocular sequences

This paper addresses the pose recovery problem of a particular articulated object: the human body. In this model-based approach, the 2D-shape is associated to the corresponding stick figure allowing the joint segmentation and pose recovery of the subject observed in the scene. The main disadvantage of 2D-models is their restriction to the viewpoint. To cope with this limitation, local spatio-temporal 2D-models corresponding to many views of the same sequences are trained, concatenated and sorted in a global framework. Temporal and spatial constraints are then considered to build the probabilistic transition matrix (PTM) that gives a frame to frame estimation of the most probable local models to use during the fitting procedure, thus limiting the feature space. This approach takes advantage of 3D information avoiding the use of a complex 3D human model. The experiments carried out on both indoor and outdoor sequences have demonstrated the ability of this approach to adequately segment pedestrians and estimate their poses independently of the direction of motion during the sequence. (c) 2008 Elsevier Ltd. All rights reserved.

An exploration of the attitudes and strategic responses of soleproprietor micro-enterprises in adopting information and communication technology

This article analyses longitudinal case-based research exploring the attitudes and strategic responses of micro-enterprise owners in adopting information and communication technology (ICT). In so doing, it contributes to the limited literature on micro-enterprise ICT adoption, with a particular focus on sole proprietors. It provides a basis for widening the theoretical base of the literature pertaining to ICT adoption on two levels. First, a framework is developed which integrates the findings to illustrate the relationships between attitudes towards ICT adoption, endogenous and exogenous influencers of these attitudes and subsequent strategic response in ICT adoption. Second, building upon this framework the article reveals the unique challenges, opportunities and implications of ICT adoption for sole-proprietor micro-enterprises. © The Author(s) 2012

Information aggregation and belief elicitation in experimental parimutuel betting markets

This paper studies the impact of belief elicitation on informational efficiency and individual behavior in experimental parimutuel betting markets. In one treatment, groups of eight participants, who possess a private signal about the eventual outcome, play a sequential betting game. The second treatment is identical, except that bettors are observed by eight other participants who submit incentivized beliefs about the winning probabilities of each outcome. In the third treatment, the same individuals make bets and assess the winning probabilities of the outcomes. Market probabilities more accurately reflect objective probabilities in the third than in the other two treatments. Submitting beliefs reduces the favorite-longshot bias and making bets improves the accuracy of elicited beliefs. A level-k framework provides some insights about why belief elicitation improves the capacity of betting markets to aggregate information. (C) 2012 Elsevier B.V. All rights reserved.

Parimutuel betting under asymmetric information

This paper examines simple parimutuel betting games under asymmetric information, with particular attention to differences between markets in which bets are submitted simultaneously versus sequentially. In the simultaneous parimutuel betting market, all (symmetric and asymmetric) Bayesian-Nash equilibria are generically characterized as a function of the number of bettors and the quality of their private information. There always exists a separating equilibrium, in which all bettors follow their private signals. This equilibrium is unique if the number of bettors is sufficiently large. In the sequential framework, earlier bets have information externalities, because they may reveal private information of bettors. They also have payoff externalities, because they affect the betting odds. One effect of these externalities is that the separating equilibrium disappears if the number of betting periods is sufficiently large. (C) 2006 Elsevier B.V. All rights reserved.

Self-disclosure decision making based on intimacy and privacy

Autonomous agents may encapsulate their principals' personal data attributes. These attributes may be disclosed to other agents during agent interactions, producing a loss of privacy. Thus, agents need self-disclosure decision-making mechanisms to autonomously decide whether disclosing personal data attributes to other agents is acceptable or not. Current self-disclosure decision-making mechanisms consider the direct benefit and the privacy loss of disclosing an attribute. However, there are many situations in which the direct benefit of disclosing an attribute is a priori unknown. This is the case in human relationships, where the disclosure of personal data attributes plays a crucial role in their development. In this paper, we present self-disclosure decision-making mechanisms based on psychological findings regarding how humans disclose personal information in the building of their relationships. We experimentally demonstrate that, in most situations, agents following these decision-making mechanisms lose less privacy than agents that do not use them. (C) 2012 Elsevier Inc. All rights reserved.

Employer occupation of regulatory space of the Employee Information and Consultation (I&C) Directive in liberal market economies

This article shows how both employers and the state have influenced macro-level processes and structures concerning the content and transposition of the European Union (EU) Employee Information and Consultation (I&C) Directive. It argues that the processes of regulation occupied by employers reinforce a voluntarism which marginalizes rather than shares decision-making power with workers. The contribution advances the conceptual lens of ‘regulatory space’ by building on Lukes’ multiple faces of power to better understand how employment regulation is determined across transnational, national and enterprise levels. The research proposes an integrated analytical framework on which ‘occupancy’ of regulatory space can be evaluated in comparative national contexts.

Robust food supply supply chains:An integrated framework for vulnerability assessment and disturbance management

The operation of supply chains (SCs) has for many years been focused on efficiency, leanness and responsiveness. This has resulted in reduced slack in operations, compressed cycle times, increased productivity and minimised inventory levels along the SC. Combined with tight tolerance settings for the realisation of logistics and production processes, this has led to SC performances that are frequently not robust. SCs are becoming increasingly vulnerable to disturbances, which can decrease the competitive power of the entire chain in the market. Moreover, in the case of food SCs non-robust performances may ultimately result in empty shelves in grocery stores and supermarkets.
The overall objective of this research is to contribute to Supply Chain Management (SCM) theory by developing a structured approach to assess SC vulnerability, so that robust performances of food SCs can be assured. We also aim to help companies in the food industry to evaluate their current state of vulnerability, and to improve their performance robustness through a better understanding of vulnerability issues. The following research questions (RQs) stem from these objectives:
RQ1: What are the main research challenges related to (food) SC robustness?
RQ2: What are the main elements that have to be considered in the design of robust SCs and what are the relationships between these elements?
RQ3: What is the relationship between the contextual factors of food SCs and the use of disturbance management principles?
RQ4: How to systematically assess the impact of disturbances in (food) SC processes on the robustness of (food) SC performances?
To answer these RQs we used different methodologies, both qualitative and quantitative. For each question, we conducted a literature survey to identify gaps in existing research and define the state of the art of knowledge on the related topics. For the second and third RQ, we conducted both exploration and testing on selected case studies. Finally, to obtain more detailed answers to the fourth question, we used simulation modelling and scenario analysis for vulnerability assessment.
Main findings are summarised as follows.
Based on an extensive literature review, we answered RQ1. The main research challenges were related to the need to define SC robustness more precisely, to identify and classify disturbances and their causes in the context of the specific characteristics of SCs and to make a systematic overview of (re)design strategies that may improve SC robustness. Also, we found that it is useful to be able to discriminate between varying degrees of SC vulnerability and to find a measure that quantifies the extent to which a company or SC shows robust performances when exposed to disturbances.
To address RQ2, we define SC robustness as the degree to which a SC shows an acceptable performance in (each of) its Key Performance Indicators (KPIs) during and after an unexpected event that caused a disturbance in one or more logistics processes. Based on the SCM literature we identified the main elements needed to achieve robust performances and structured them together to form a conceptual framework for the design of robust SCs. We then explained the logic of the framework and elaborate on each of its main elements: the SC scenario, SC disturbances, SC performance, sources of food SC vulnerability, and redesign principles and strategies.
Based on three case studies, we answered RQ3. Our major findings show that the contextual factors have a consistent relationship to Disturbance Management Principles (DMPs). The product and SC environment characteristics are contextual factors that are hard to change and these characteristics initiate the use of specific DMPs as well as constrain the use of potential response actions. The process and the SC network characteristics are contextual factors that are easier to change, and they are affected by the use of the DMPs. We also found a notable relationship between the type of DMP likely to be used and the particular combination of contextual factors present in the observed SC.
To address RQ4, we presented a new method for vulnerability assessments, the VULA method. The VULA method helps to identify how much a company is underperforming on a specific Key Performance Indicator (KPI) in the case of a disturbance, how often this would happen and how long it would last. It ultimately informs the decision maker about whether process redesign is needed and what kind of redesign strategies should be used in order to increase the SC’s robustness. The VULA method is demonstrated in the context of a meat SC using discrete-event simulation. The case findings show that performance robustness can be assessed for any KPI using the VULA method.
To sum-up the project, all findings were incorporated within an integrated framework for designing robust SCs. The integrated framework consists of the following steps: 1) Description of the SC scenario and identification of its specific contextual factors; 2) Identification of disturbances that may affect KPIs; 3) Definition of the relevant KPIs and identification of the main disturbances through assessment of the SC performance robustness (i.e. application of the VULA method); 4) Identification of the sources of vulnerability that may (strongly) affect the robustness of performances and eventually increase the vulnerability of the SC; 5) Identification of appropriate preventive or disturbance impact reductive redesign strategies; 6) Alteration of SC scenario elements as required by the selected redesign strategies and repeat VULA method for KPIs, as defined in Step 3.
Contributions of this research are listed as follows. First, we have identified emerging research areas - SC robustness, and its counterpart, vulnerability. Second, we have developed a definition of SC robustness, operationalized it, and identified and structured the relevant elements for the design of robust SCs in the form of a research framework. With this research framework, we contribute to a better understanding of the concepts of vulnerability and robustness and related issues in food SCs. Third, we identified the relationship between contextual factors of food SCs and specific DMPs used to maintain robust SC performances: characteristics of the product and the SC environment influence the selection and use of DMPs; processes and SC networks are influenced by DMPs. Fourth, we developed specific metrics for vulnerability assessments, which serve as a basis of a VULA method. The VULA method investigates different measures of the variability of both the duration of impacts from disturbances and the fluctuations in their magnitude.
With this project, we also hope to have delivered practical insights into food SC vulnerability. First, the integrated framework for the design of robust SCs can be used to guide food companies in successful disturbance management. Second, empirical findings from case studies lead to the identification of changeable characteristics of SCs that can serve as a basis for assessing where to focus efforts to manage disturbances. Third, the VULA method can help top management to get more reliable information about the “health” of the company.
The two most important research opportunities are: First, there is a need to extend and validate our findings related to the research framework and contextual factors through further case studies related to other types of (food) products and other types of SCs. Second, there is a need to further develop and test the VULA method, e.g.: to use other indicators and statistical measures for disturbance detection and SC improvement; to define the most appropriate KPI to represent the robustness of a complete SC. We hope this thesis invites other researchers to pick up these challenges and help us further improve the robustness of (food) SCs.

Discovery and Evidence in Transnational Antitrust Cases: Current Framework and the Way Forward

This paper identifies and analyses the means of accessing and collecting foreign-based evidence in transnational antitrust cases. It makes an original contribution to the existing scholarship by critically addressing the available mechanisms of judicial cooperation, the possibility of reliance on domestic discovery in transnational context, as well as the existing instruments allowing for cooperation between antitrust agencies. It identifies the shortcomings of the current regulatory framework and points out to the existing good practices in those jurisdictions which provide their antitrust agencies with more leeway in sharing confidential information with foreign counterparts.

A Chronological Framework for the Period 208 BC to AD 600

The period, from the Iron Age through to what is sometimes
called the Early Christian Period or the Early Middle Ages, includes
some of the most enigmatic centuries in the whole of Irish
history. In this article we intend to look at various strands of evidence
that have become available from the perspective of dendrochronology.
However, interpretation of dendrochronological
results works best when there is other information to push
against. In the case of this period one of the best sources of parallel
information – information essentially as well dated as tree
rings – has to be records of atmospheric chemistry from the ice
cores that have been drilled at several locations across Greenland.
Combining such information with evidence from tree rings,
palaeoecological research, and occasionally from history, allows
us to trace out a series of events and episodes that form the beginnings
of an understanding of this period between the Iron
Age flowering – with sites such as Emain Mache, Tara, Cruachain
– and the Early Christian flowering – widespread foundation of churches and monasteries.