Violent behaviour detection using local trajectory response

Surveillance systems in the United Kingdom are prominent, and the number of installed cameras is estimated to be around 1.8 million. It is common for a single person to watch multiple live video feeds when conducting active surveillance, and past research has shown that a person’s effectiveness at successfully identifying an event of interest diminishes the more monitors they must observe. We propose using computer vision techniques to produce a system that can accurately identify scenes of violent behaviour. In this paper we outline three measures of motion trajectory that when combined produce a response map that highlights regions within frames that contain behaviour typical of violence based on local information. Our proposed method demonstrates state-of-the-art classification ability when given the task of distinguishing between violent and non-violent behaviour across a wide variety of violent data, including real-world surveillance footage obtained from local police organisations

Excitability in autonomous Boolean networks

We demonstrate theoretically and experimentally that excitable systems can be built with autonomous Boolean networks. Their experimental implementation is realized with asynchronous logic gates on a reconfigurabe chip. When these excitable systems are assembled into time-delay networks, their dynamics display nanosecond time-scale spike synchronization patterns that are controllable in period and phase.Comment: 6 pages, 5 figures, accepted in Europhysics Letters (epljournal.edpsciences.org

Detecting violent and abnormal crowd activity using temporal analysis of grey level co-occurrence matrix (GLCM)-based texture measures

The severity of sustained injury resulting from assault-related violence can be minimized by reducing detection time. However, it has been shown that human operators perform poorly at detecting events found in video footage when presented with simultaneous feeds. We utilize computer vision techniques to develop an automated method of violence detection that can aid a human operator. We observed that violence in city centre environments often occur in crowded areas, resulting in individual actions being occluded by other crowd members. Measures of visual texture have shown to be effective at encoding crowd appearance. Therefore, we propose modelling crowd dynamics using changes in crowd texture. We refer to this approach as Violent Crowd Texture (VCT). Real-world surveillance footage of night time environments and the violent flows dataset were tested using a random forest classifier to evaluate the ability of the VCT method at discriminating between violent and non-violent behaviour. Our method achieves ROC values of 0.98 and 0.91 on our own real world CCTV dataset and the violent flows dataset respectively

Report on ARGOS' second qualitative interview

The primary objective of the ARGOS project is the transdisciplinary examination of the condition of sustainable agriculture in New Zealand (including environmental, economic and social aspects). In pursuit of this objective to date, considerable effort has been dedicated to assessing the comparative sustainability or resilience of designated management panels in three branches of the New Zealand agricultural sector (dairy, kiwifruit and sheep/beef). For this purpose, farms of comparable size and similar location were assigned panel membership as determined by an individual farmer’s compliance (or lack thereof) with existing market audit schemes which – to varying degrees – regulate farm management practice. By sector, the panels are comprised of conventional and organic methods of dairy farming, integrated pest management (Hayward, green, and Hort 16a, gold) and organic (Hayward) methods of kiwifruit production, and conventional, integrated and organic methods of sheep and beef farming. Due to the distinct nature of practices associated with each panel, differences in the assessed ecological, economic and social features of the participating farms and farm households offer the potential to distinguish the relative sustainability of systems based on these practices

An open-data, agent-based model of alcohol related crime

The allocation of resources to challenge city centre violent crime traditionally relies on historical data to identify hot-spots. The usefulness of such data-driven approaches is limited when historical data is scarce or unavailable (e.g. planning of a new city) or insufficiently representative (e.g. does not account for novel events, such as Olympic Games). In some cities, crime data is not systematically accumulated at all. We present a graph-constrained agent based simulation model of alcohol-related violent crime that is capable of predicting areas of likely violent crime without requiring any historical data. The only inputs to our simulation are publicly available geographical data, which makes our method immediately applicable to a wide range of tasks, such as optimal city planning, police patrol optimisation, devising alcohol licensing policies. In experiments, we evaluate our model and demonstrate agreement of our model's predictions on where and when violence will occur with real-world violent crime data. Analyses indicate that our agent based model may be able to make a significant contribution to attempts to prevent violence through deterrence or by design

Concomitant Carcinoma in situ in Cystectomy Specimens Is Not Associated with Clinical Outcomes after Surgery

Objective: The aim of this study was to externally validate the prognostic value of concomitant urothelial carcinoma in situ (CIS) in radical cystectomy (RC) specimens using a large international cohort of bladder cancer patients. Methods: The records of 3,973 patients treated with RC and bilateral lymphadenectomy for urothelial carcinoma of the bladder (UCB) at nine centers worldwide were reviewed. Surgical specimens were evaluated by a genitourinary pathologist at each center. Uni- and multivariable Cox regression models addressed time to recurrence and cancer-specific mortality after RC. Results: 1,741 (43.8%) patients had concomitant CIS in their RC specimens. Concomitant CIS was more common in organ-confined UCB and was associated with lymphovascular invasion (p < 0.001). Concomitant CIS was not associated with either disease recurrence or cancer-specific death regardless of pathologic stage. The presence of concomitant CIS did not improve the predictive accuracy of standard predictors for either disease recurrence or cancer-specific death in any of the subgroups. Conclusions: We could not confirm the prognostic value of concomitant CIS in RC specimens. This, together with the discrepancy between pathologists in determining the presence of concomitant CIS at the morphologic level, limits the clinical utility of concomitant CIS in RC specimens for clinical decision-making. Copyright (C) 2011 S. Karger AG, Base

Spring diet of the pine marten in Sardinia, Italy

Alimentación primaveral de la marta en Cerdeña, ItaliaEl conocimiento del comportamiento de alimentación de un carnívoro es esencial para entender su ecología. La marta Martes martes se define comúnmente como un depredador generalista oportunista, porque su dieta en Europa incluye mamíferos, frutas, aves y invertebrados. A partir del análisis de las heces, hemos descrito los hábitos alimenticios en primavera y la amplitud del nicho trófico de la marta en ambiente mediterráneo en Cerdeña (Italia central). Los pequeños mamíferos (sobre todo Apodemus sylvaticus, Mus musculus y Eliomys quercinus) representan la fuente más importante de alimentación de la marta, ya que constituyen aproximadamente el 52% del volumen medio. Otra fuente importante de alimentos secundarios la constituyen los invertebrados (especialmente escarabajos y larvas de insectos) y las aves (paseriformes casi exclusivamente), mientras que los grandes mamíferos, los lagomorfos, los reptiles y las frutas están poco representados en la dieta. La composición de la dieta y el valor del índice de Levins indican que la marta en Cerdeña es un depredador especialista facultativo, con una especialización en la depredación de los micromamíferos.Knowledge of a carnivore’s foraging behaviour is essential to understand its ecology. The pine marten Martes martes is commonly defined as an opportunistic generalist predator since its diet in Europe includes mammals, fruits, birds and invertebrates. Based on faecal analyses, we evaluated spring feeding habits and trophic niche breadth of the pine marten in a Mediterranean landscape on the island of Sardinia (Central Italy). The most important source of food for the pine marten was small mammals (mainly Apodemus sylvaticus, Mus musculus and Eliomys quercinus), accounting for 52% of the percent mean volume. Important secondary foods were invertebrates (mainly beetles and insect larvae) and birds (almost exclusively passerines), whereas large mammals, lagomorphs, reptiles and fruits made little contribution to the diet. The diet composition and the Levins’ index value suggest that the pine marten in Sardinia behaves as a facultative specialist predator, with a specialization towards small mammals.Alimentación primaveral de la marta en Cerdeña, ItaliaEl conocimiento del comportamiento de alimentación de un carnívoro es esencial para entender su ecología. La marta Martes martes se define comúnmente como un depredador generalista oportunista, porque su dieta en Europa incluye mamíferos, frutas, aves y invertebrados. A partir del análisis de las heces, hemos descrito los hábitos alimenticios en primavera y la amplitud del nicho trófico de la marta en ambiente mediterráneo en Cerdeña (Italia central). Los pequeños mamíferos (sobre todo Apodemus sylvaticus, Mus musculus y Eliomys quercinus) representan la fuente más importante de alimentación de la marta, ya que constituyen aproximadamente el 52% del volumen medio. Otra fuente importante de alimentos secundarios la constituyen los invertebrados (especialmente escarabajos y larvas de insectos) y las aves (paseriformes casi exclusivamente), mientras que los grandes mamíferos, los lagomorfos, los reptiles y las frutas están poco representados en la dieta. La composición de la dieta y el valor del índice de Levins indican que la marta en Cerdeña es un depredador especialista facultativo, con una especialización en la depredación de los micromamíferos

De novo mutations in SMCHD1 cause Bosma arhinia microphthalmia syndrome and abrogate nasal development

Bosma arhinia microphthalmia syndrome (BAMS) is an extremely rare and striking condition characterized by complete absence of the nose with or without ocular defects. We report here that missense mutations in the epigenetic regulator SMCHD1 mapping to the extended ATPase domain of the encoded protein cause BAMS in all 14 cases studied. All mutations were de novo where parental DNA was available. Biochemical tests and in vivo assays in Xenopus laevis embryos suggest that these mutations may behave as gain-of-function alleles. This finding is in contrast to the loss-of-function mutations in SMCHD1 that have been associated with facioscapulohumeral muscular dystrophy (FSHD) type 2. Our results establish SMCHD1 as a key player in nasal development and provide biochemical insight into its enzymatic function that may be exploited for development of therapeutics for FSHD

Visualizing Natural Image Statistics

Natural image statistics is an important area of research in cognitive sciences and computer vision. Visualization of statistical results can help identify clusters and anomalies as well as analyze deviation, distribution and correlation. Furthermore, they can provide visual abstractions and symbolism for categorized data. In this paper, we begin our study of visualization of image statistics by considering visual representations of power spectra, which are commonly used to visualize different categories of images. We show that they convey a limited amount of statistical information about image categories and their support for analytical tasks is ineffective. We then introduce several new visual representations, which convey different or more information about image statistics. We apply ANOVA to the image statistics to help select statistically more meaningful measurements in our design process. A task-based user evaluation was carried out to compare the new visual representations with the conventional power spectra plots. Based on the results of the evaluation, we made further improvement of visualizations by introducing composite visual representations of image statistics

Virtual player design using self-learning via competitive coevolutionary algorithms

The Google Artificial Intelligence (AI) Challenge is an international contest the objective of which is to program the AI in a two-player real time strategy (RTS) game. This AI is an autonomous computer program that governs the actions that one of the two players executes during the game according to the state of play. The entries are evaluated via a competition mechanism consisting of two-player rounds where each entry is tested against others. This paper describes the use of competitive coevolutionary (CC) algorithms for the automatic generation of winning game strategies in Planet Wars, the RTS game associated with the 2010 contest. Three different versions of a prime algorithm have been tested. Their common nexus is not only the use of a Hall-of-Fame (HoF) to keep note of the winners of past coevolutions but also the employment of an archive of experienced players, termed the hall-of-celebrities (HoC), that puts pressure on the optimization process and guides the search to increase the strength of the solutions; their differences come from the periodical updating of the HoF on the basis of quality and diversity metrics. The goal is to optimize the AI by means of a self-learning process guided by coevolutionary search and competitive evaluation. An empirical study on the performance of a number of variants of the proposed algorithms is described and a statistical analysis of the results is conducted. In addition to the attainment of competitive bots we also conclude that the incorporation of the HoC inside the primary algorithm helps to reduce the effects of cycling caused by the use of HoF in CC algorithms.This work is partially supported by Spanish MICINN under Project ANYSELF (TIN2011-28627-C04-01),3 by Junta de Andalucía under Project P10-TIC-6083 (DNEMESIS) and by Universidad de Málaga, Campus de Excelencia Internacional Andalucía Tech