Meeting detection in video through semantic analysis

In this paper we present a novel approach to detect people meeting. The proposed approach works by translating people behaviour from trajectory information into semantic terms. Having available a semantic model of the meeting behaviour, the event detection is performed in the semantic domain. The model is learnt employing a soft-computing clustering algorithm that combines trajectory information and motion semantic terms. A stable representation can be obtained from a series of examples. Results obtained on a series of videos with different types of meeting situations show that the proposed approach can learn a generic model that can effectively be applied on the behaviour recognition of meeting situations.

Rotational aesthetics: Michael Bay and contemporary cinema’s machine movement

Digital imaging technologies enable a mastery of the visual that in recent mainstream cinema frequently manifests as certain kinds of spatial reach, orientation and motion. In such a context Michael Bay’s Transformers franchise can be framed as a digital re-tooling of a familiar fantasy of vehicular propulsion, US car culture writ large in digitally crafted spectacles of diegetic speed, the vehicular chase film ‘2.0’. Movement is central to these films, calling up Scott Bukatman’s observation that in spectacular visual media ‘movement has become more than a tool of bodily knowledge; it has become an end in itself’ (2003: 125). Not all movements and not all instances of vehicular propulsion are the same however. How might we evaluate what is at stake in a film’s assertion of movement as an end in itself, and the form that assertion takes, its articulations of diegetic velocity, corporeality, and spatial penetration? Deploying an attentiveness towards the specificity of aesthetic detail and affective impact in Bay’s delineation of movement, this essay suggests that the franchise poses questions about the relationship of human movement to machine movement that exceed their narrative basis. Identifying a persistent rotational trope in the franchise that in its audio-visual articulation combines oddly anachronistic elements (evoking the mechanical rather than the digital), the article argues that the films prioritise certain fantasies of transformation and spatial penetration, and certain modes of corporeality, as one response to contemporary debates about digital technologisation, sustainable energy, and cinematic spectacle. In this way the franchise also represents a particular moment in a more widely discernible preoccupation in contemporary cinema with what we might call a ‘rotational aesthetics’ of action, a machine movement made possible by the digital, but which invokes earlier histories and fantasies of animation, propulsion, mechanization and mechanization to particular ends.

The fractured lives of German Bohemian children, born 1933-40 in the area known as Sudetenland: a memory study, Nablonz-Neugablonz

At the Paris Peace Conferences of 1918-1919, new states aspiring to be nation-states were created for 60 million people, but at the same time 25 million people found themselves as ethnic minorities. This change of the old order in Europe had a considerable impact on one such group, more than 3 million Bohemian German-speakers, later referred to as Sudeten Germans. After the demise of the Habsburg Empire In 1918, they became part of the new state of Czechoslovakia. In 1938, the Munich Agreement – prelude to the Second World War – integrated them into Hitler’s Reich; in 1945-1946 they were expelled from the reconstituted state of Czechoslovakia. At the centre of this War Child case study are German children from the Northern Bohemian town and district, formerly known as Gablonz an der Neisse, famous for exquisite glass art, now Jablonec nad Nisou in the Czech Republic. After their expulsion they found new homes in the post-war Federal Republic of Germany. In addition, testimonies have been drawn upon of some Czech eyewitnesses from the same area, who provided their perspective from the other side, as it were. It turned out to be an insightful case study of the fate of these communities, previously studied mainly within the context of the national struggle between Germans and Czechs. The inter-disciplinary research methodology adopted here combines history and sociological research to demonstrate the effect of larger political and social developments on human lives, not shying away from addressing sensitive political and historical issues, as far as these are relevant within the context of the study. The expellees started new lives in what became Neugablonz in post-war Bavaria where they successfully re-established the industries they had had to leave behind in 1945-1946. Part 1 of the study sheds light on the complex Czech-German relationship of this important Central European region, addressing issues of democracy, ethnicity, race, nationalism, geopolitics, economics, human geography and ethnography. It also charts the developments leading to the expulsion of the Sudeten Germans from Czechoslovakia after 1945. What is important in this War Child study is how the expellees remember their history while living as children in Sudetenland and later. The testimony data gained indicate that certain stereotypes often repeated within the context of Sudeten issues such as the confrontational nature of inter-ethnic relations are not reflected in the testimonies of the respondents from Gablonz. In Part 2 the War Child Study explores the memories of the former Sudeten war children using sociological research methods. It focuses on how they remember life in their Bohemian homeland and coped with the life-long effects of displacement after their expulsion. The study maps how they turned adversity into success by showing a remarkable degree of resilience and ingenuity in the face of testing circumstances due to the abrupt break in their lives. The thesis examines the reasons for the relatively positive outcome to respondents’ lives and what transferable lessons can be deduced from the results of this study.

Quinine, mosquitoes and empire: reassembling malaria in British India, 1890-1910

The drug quinine figured as an object of enforced consumption in British India between the late 1890s and the 1910s, when the corresponding diagnostic category malaria itself was redefined as a mosquito-borne fever disease. This article details an overlapping milieu in which quinine, mosquitoes and malaria emerged as intrinsic components of shared and symbiotic histories. It combines insights from new imperial histories, constructivism in the histories of medicine and literature about non-humans in science studies to examine the ways in which histories of insects, drugs, disease and empire interacted and shaped one another. Firstly, it locates the production of historical intimacies between quinine, malaria and mosquitoes within the exigencies and apparatuses of imperial rule. In so doing, it explores the intersections between the worlds of colonial governance, medical knowledge, vernacular markets and pharmaceutical business. Secondly, it outlines ways to narrate characteristics and enabling properties of non-humans (such as quinines and mosquitoes) while retaining a constructivist critique of scientism and empire. Thirdly, it shows how empire itself was reshaped and reinforced while occasioning the proliferation of categories and entities like malaria, quinine and mosquitoes.

Thermal aspects of satellite downscaling

The strong trend toward nanosatellites creates new challenges in terms of thermal balance control. The thermal balance of a satellite is determined by the heat dissipation in its subsystems and by the thermal connections between them. As satellites become smaller, heat dissipation in their subsystems tends to decrease and thermal connectivity scales down with dimension. However, these two terms do not necessarily scale in the same way, and so the thermal balance may alter and the temperature of subsystems may reach undesired levels. This paper focuses on low-Earth-orbit satellites. We constructed a generalized lumped thermal model that combines a generalized low-Earth-orbit satellite configuration with scaling trends in subsystem heat dissipation and thermal connectivity. Using satellite mass as a scaling parameter, we show that subsystems do not become thermally critical by scaling mass alone.

Clubroot (Plasmodiophora brassicae Woronin): an agricultural and biological challenge worldwide

Clubroot disease and the causal microbe Plasmodiophora brassicae offer abundant challenges to agriculturists and biological scientists. This microbe is well fitted for the environments which it inhabits. Plasmodiophora brassicae exists in soil as microscopic well protected resting spores and then grows actively and reproduces while shielded inside the roots of host plants. The pathogen is active outside the host for only short periods. Consequently, scientific studies are made challenging by the biological context of the host and pathogen and the technology required to investigate and understand that relationship. Controlling clubroot disease is a challenge for farmers, crop consultants and plant pathology practitioners because of the limited options which are available. Full symptom expression happens solely in members of the Brassicaceae family. Currently, only a few genes expressing strong resistance to P. brassicae are known and readily available. Agrochemical control is similarly limited by difficulties in molecule formulation which combines efficacy with environmental acceptability. Manipulation of husbandry encouraging improvements in soil structure, texture, nutrient composition and moisture content can reduce populations of P. brassicae. Integrating such strategies with rotation and crop management will reduce but not eliminate this disease. There are indications that forms of biological competition may be mobilised as additions to integrated control strategies. The aim of this review is to chart key themes in the development of scientific biological understanding of this host-pathogen relationship by offering signposts to grapple with clubroot disease which devastates crops and their profitability. Particular attention is given to the link between soil and nutrient chemistry and activity of this microbe.

A Variance-Minimizing Filter for Large-Scale Applications

A truly variance-minimizing filter is introduced and its per for mance is demonstrated with the Korteweg– DeV ries (KdV) equation and with a multilayer quasigeostrophic model of the ocean area around South Africa. It is recalled that Kalman-like filters are not variance minimizing for nonlinear model dynamics and that four - dimensional variational data assimilation (4DV AR)-like methods relying on per fect model dynamics have dif- ficulty with providing error estimates. The new method does not have these drawbacks. In fact, it combines advantages from both methods in that it does provide error estimates while automatically having balanced states after analysis, without extra computations. It is based on ensemble or Monte Carlo integrations to simulate the probability density of the model evolution. When obser vations are available, the so-called importance resampling algorithm is applied. From Bayes’ s theorem it follows that each ensemble member receives a new weight dependent on its ‘ ‘distance’ ’ t o the obser vations. Because the weights are strongly var ying, a resampling of the ensemble is necessar y. This resampling is done such that members with high weights are duplicated according to their weights, while low-weight members are largely ignored. In passing, it is noted that data assimilation is not an inverse problem by nature, although it can be for mulated that way . Also, it is shown that the posterior variance can be larger than the prior if the usual Gaussian framework is set aside. However , i n the examples presented here, the entropy of the probability densities is decreasing. The application to the ocean area around South Africa, gover ned by strongly nonlinear dynamics, shows that the method is working satisfactorily . The strong and weak points of the method are discussed and possible improvements are proposed.

Application of data assimilation to ocean and climate prediction

Ocean prediction systems are now able to analyse and predict temperature, salinity and velocity structures within the ocean by assimilating measurements of the ocean’s temperature and salinity into physically based ocean models. Data assimilation combines current estimates of state variables, such as temperature and salinity, from a computational model with measurements of the ocean and atmosphere in order to improve forecasts and reduce uncertainty in the forecast accuracy. Data assimilation generally works well with ocean models away from the equator but has been found to induce vigorous and unrealistic overturning circulations near the equator. A pressure correction method was developed at the University of Reading and the Met Office to control these circulations using ideas from control theory and an understanding of equatorial dynamics. The method has been used for the last 10 years in seasonal forecasting and ocean prediction systems at the Met Office and European Center for Medium-range Weather Forecasting (ECMWF). It has been an important element in recent re-analyses of the ocean heat uptake that mitigates climate change.

Ecological and social drivers of coffee pollination in Santander, Colombia

Bees and other insects provide pollination services that are key to determining the fruit set on coffee plantations. These pollination services are influenced by local ecology as well as human factors, both social and economic. To better understand these different factors, we assessed their effect on pollinators and coffee pollination services in Santander, Colombia. We quantified the effect of key ecological drivers on pollinator community composition, such as the method of farm management (either conventional or organic) and the surrounding landscape composition, specifically the proximity to forest. We found that ambient levels of pollination services provided by the local pollinator fauna (open pollination) accounted for a 10.5 ± 2.0% increase in final coffee fruit set, and that the various pollinators are affected differently by the differing factors. For example, our findings indicate that conventional farm management, using synthetic inputs, can promote pollinators, especially if they are in close proximity to natural forest fragments. This is particularly true for stingless bees. Honeybee visitation to coffee is also positively influenced by the conventional management of farms. Factors associated with greater numbers of stingless bees on farms include greater shade cover, lower tree densities, smaller numbers and types of trees in bloom, and younger coffee plantations. A forested landscape close to farms appears to enhance these factors, giving increased stability and resilience to the pollinating bees and insects. However we found that organic farms also support diverse pollinator communities, even if distant from forest fragments. The contribution of honeybees to pollination value (US$129.6/ha of coffee) is greater than that of stingless bees (US$16.5/ha of coffee). Since the method of farm management has a major impact on the numbers and types of pollinators attracted to farms, we have analysed the statistically significant social factors that influence farmers’ decisions on whether to adopt organic or conventional practices. These include the availability of technology, the type of landowner (whether married couples or individual owners), the number of years of farmers’ formal education, the role of institutions, membership of community organizations, farm size, coffee productivity and the number of coffee plots per farm. It is hoped that the use of our holistic approach, which combines investigation of the social as well as the ecological drivers of pollination, will help provide evidence to underpin the development of best practices for integrating the management of pollination into sustainable agricultural practices.

Kazakhstan: long-term economic growth and the role of the oil sector

This study combines a narrative and modelling framework to analyse the development of Kazakhstan’s oil sector since its takeoff following separation from the USSR. As in the case of other emerging or transitional countries with large natural resource endowments, a key question is whether the exploitation of the natural resource is a benefit to longer term economic development: is it a curse, a blessing – or neither? Narrative evidence suggests that the establishment of good governance, in terms of institutions and policies, provides a background to sound long-term development, especially if combined with the development of sectors outside the natural resource sector, for example diversification into manufacturing and services, often through attracting FDI. The narrative is supported by econometric modelling of the relationship between domestic output, overseas output and exports of oil, which finds in favour of a sustained positive effect of oil exports on GDP. The model then provides a basis for projection of the growth in GDP given a consensus view of likely developments in the oil price.

Bayesian analysis of uncertainty in the GlobCover 2009 land cover product at climate model grid scale

Land cover data derived from satellites are commonly used to prescribe inputs to models of the land surface. Since such data inevitably contains errors, quantifying how uncertainties in the data affect a model’s output is important. To do so, a spatial distribution of possible land cover values is required to propagate through the model’s simulation. However, at large scales, such as those required for climate models, such spatial modelling can be difficult. Also, computer models often require land cover proportions at sites larger than the original map scale as inputs, and it is the uncertainty in these proportions that this article discusses. This paper describes a Monte Carlo sampling scheme that generates realisations of land cover proportions from the posterior distribution as implied by a Bayesian analysis that combines spatial information in the land cover map and its associated confusion matrix. The technique is computationally simple and has been applied previously to the Land Cover Map 2000 for the region of England and Wales. This article demonstrates the ability of the technique to scale up to large (global) satellite derived land cover maps and reports its application to the GlobCover 2009 data product. The results show that, in general, the GlobCover data possesses only small biases, with the largest belonging to non–vegetated surfaces. In vegetated surfaces, the most prominent area of uncertainty is Southern Africa, which represents a complex heterogeneous landscape. It is also clear from this study that greater resources need to be devoted to the construction of comprehensive confusion matrices.