Local Conventions in Game Play in an Evolving Dual Social Network Framework

People usually perform economic interactions within the social setting of a small group, while they obtain relevant information from a broader source. We capture this feature with a dynamic interaction model based on two separate social networks. Individuals play a coordination game in an interaction network, while updating their strategies using information from a separate influence network through which information is disseminated. In each time period, the interaction and influence networks co-evolve, and the individuals’ strategies are updated through a modified naive learning process. We show that both network structures and players’ strategies always reach a steady state, in which players form fully connected groups and converge to local conventions. We also analyze the influence exerted by a minority group of strongly opinionated players on these outcomes.

Partial Encryption by Randomized Zig-Zag Scanning for Video Encoding

19.Wang, Y, O’Neill, M, Kurugollu, F, Partial Encryption by Randomized Zig-Zag Scanning for Video Encoding, IEEE International Symposium on Circuits and Systems (ISCAS), Beijing, May 2013

Improvisation, Indeterminacy and Game-Mediated Participation in Network Music Performance

This chapter focuses on the relationship between improvisation and indeterminacy. We discuss the two practices by referring to play theory and game studies and situate it in recent network music performance. We will develop a parallel with game theory in which indeterminacy is seen as a way of articulating situations where structural decisions are left to the discernment of the performers and discuss improvisation as a method of play. The improvisation-indeterminacy relationship is discussed in the context of network music performance, which employs digital networks in the exchange of data between performers and hence relies on topological structures with varying degrees of openness and flexibility. Artists such as Max Neuhaus and The League of Automatic Music Composers initiated the development of a multitude of practices and technologies exploring the network as an environment for music making. Even though the technologies behind “the network” have shifted dramatically since Neuhaus’ use of radio in the 1960’s, a preoccupation with distribution and sharing of artistic agency has remained at the centre of networked practices. Gollo Föllmer, after undertaking an extensive review of network music initiatives, produced a typology that comprises categories as diverse as remix lists, sound toys, real/virtual space installations and network performances. For Föllmer, “the term ‘Net music’ comprises all formal and stylistic kinds of music upon which the specifics of electronic networks leave considerable traces, whereby the electronic networks strongly influence the process of musical production, the musical aesthetic, or the way music is received” (2005: 185).

Evidential event inference in transport video surveillance

This paper presents a new framework for multi-subject event inference in surveillance video, where measurements produced by low-level vision analytics usually are noisy, incomplete or incorrect. Our goal is to infer the composite events undertaken by each subject from noise observations. To achieve this, we consider the temporal characteristics of event relations and propose a method to correctly associate the detected events with individual subjects. The Dempster–Shafer (DS) theory of belief functions is used to infer events of interest from the results of our vision analytics and to measure conflicts occurring during the event association. Our system is evaluated against a number of videos that present passenger behaviours on a public transport platform namely buses at different levels of complexity. The experimental results demonstrate that by reasoning with spatio-temporal correlations, the proposed method achieves a satisfying performance when associating atomic events and recognising composite events involving multiple subjects in dynamic environments.

Aggressiveness as a component of fighting ability in pigs using a game-theoretical framework

Understanding animal contests has benefited greatly from employing the concept of fighting ability, termed resource-holding potential (RHP), with body size/weight typically used as a proxy. However, victory does not always go to the larger/heavier contestant and the existing RHP approach thereby fails to accurately predict contest outcome. Aggressiveness, typically studied as a personality trait, might explain part of this discrepancy. We investigated whether aggressiveness forms a component of RHP, examining effects on contest outcome, duration and phases, plus physiological measures of costs (lactate and glucose). Furthermore, using the correct theoretical framework, we provide the first study to investigate whether individuals gather and use information on aggressiveness as part of an assessment strategy. Pigs, Sus scrofa, were assessed for aggressiveness in resident-intruder tests whereby attack latency reflects aggressiveness. Contests were then staged between size-matched animals diverging in aggressiveness. Individuals with a short attack latency in the resident-intruder test almost always initiated the first bite and fight in the subsequent contest. However, aggressiveness had no direct effect on contest outcome, whereas bite initiation did lead to winning in contests without an escalated fight. This indirect effect suggests that aggressiveness is not a component of RHP, but rather reflects a signal of intent. Winner and loser aggressiveness did not affect contest duration or its separate phases, suggesting aggressiveness is not part of an assessment strategy. A greater asymmetry in aggressiveness prolonged contest duration and the duration of displaying, which is in a direction contrary to assessment models based on morphological traits. Blood lactate and glucose increased with contest duration and peaked during escalated fights, highlighting the utility of physiological measures as proxies for fight cost. Integrating personality traits into the study of contest behaviour, as illustrated here, will enhance our understanding of the subtleties of agonistic interactions.

A Steganalysis System Utilizing Temporal Pixel Correlation Of HEVC Video

High Efficiency Video Coding (HEVC) is the most recent video codec coming after currently most popular H.264/MPEG4 codecs and has promising compression capabilities. It is conjectured that it will be a substitute for current video compression standards. However, to the best knowledge of the authors, none of the current video steganalysis methods designed or tested with HEVC video. In this paper, pixel domain steganography applied on HEVC video is targeted for the first time. Also, its the first paper that employs accordion unfolding transformation, which merges temporal and spatial correlation, in pixel domain video steganalysis. With help of the transformation, temporal correlation is incorporated into the system. Its demonstrated for three different feature sets that integrating temporal dependency substantially increased the detection accuracy.

Neurology assessment by objective structured video examination (OSVE)

Summary
Background
The ability to carry out a neurological examination and make an appropriate differential diagnosis is one of the mainstays of our final Bachelor of Medicine (MB) exam; however, with the introduction of objective structured clinical examinations (OSCEs) it has become impossible to arrange for adequate numbers of suitable real patients to participate in the exam.

Context
It is vital that newly qualified doctors can perform a basic neurological examination, interpret the physical signs and formulate a differential diagnosis.

It is vital that newly qualified doctors can perform a basic neurological examination

Innovation
Since 2010 we have introduced an objective structured video examination (OSVE) of a neurological examination of a real patient as part of our final MB OSCE exam. The students view clips of parts of the examination process. They answer questions on the signs that are demonstrated and formulate a differential diagnosis.

Implications
This type of station is logistically a lot easier to organise than a large number of real patients at different examination sites. The featured patients have clearly demonstrated signs and, as every student sees the same patient, are perfectly standardised. It is highly acceptable to examiners and performed well as an assessment tool. There are, however, certain drawbacks in that we are not examining the student's examination technique or their interaction with the patient. Also, certain signs, in particular the assessment of muscle tone and power, are more difficult for a student to estimate in this situation

The Development of TASTER, a Cognitive Training Game Using Human-Centered Design, Tailored for Children with Global and Specific Cognitive Impairments

Children with Prader-Willi syndrome often exhibit challenging behavior in response to changes to routine. This phenomenon has been linked to a deficit in task switching ability which has been observed in children with the syndrome. TASTER is a cognitive training game which is being designed with input from a group of children with Prader- Willi syndrome, which aims to train task switching ability and thus reduce associated challenging behavior.

Recurrent Convolutional Network for Video-based Person Re-Identification

In this paper we propose a novel recurrent neural networkarchitecture for video-based person re-identification.Given the video sequence of a person, features are extracted from each frame using a convolutional neural network that incorporates a recurrent final layer, which allows information to flow between time-steps. The features from all time steps are then combined using temporal pooling to give an overall appearance feature for the complete sequence. The convolutional network, recurrent layer, and temporal pooling layer, are jointly trained to act as a feature extractor for video-based re-identification using a Siamese network architecture.Our approach makes use of colour and optical flow information in order to capture appearance and motion information which is useful for video re-identification. Experiments are conduced on the iLIDS-VID and PRID-2011 datasets to show that this approach outperforms existing methods of video-based re-identification.

https://github.com/niallmcl/Recurrent-Convolutional-Video-ReID
Project Source Code

Employment regulation, game theory, and the lacuna in employee participation in liberal economies

Employee participation is a vital ingredient of what the International Labour Organization (ILO) calls ‘representation security’. This article provides theoretical and empirical insights relating to social policy impact of worker participation, specifically the European Information and Consultation Directive (ICD) for employee voice rights. While existing research on the ICD offers important empirical insights, there is a need for further theoretical analysis to examine the potential effectiveness of the regulations in liberal market economies (LMEs). Drawing on data from 16 case studies, the article uses game theory and the prisoner's dilemma framework to explain why national implementing legislation is largely ineffective in diffusing mutual gains cooperation in two LMEs: UK and the Republic of Ireland. Three theoretical (metaphorical) propositions advance understanding of the policy impact of national information & consultation regulations in LMEs.

Spatio-temporal Rich Model Based Video Steganalysis on Cross Sections of Motion Vector Planes

A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.