Markov chain Monte Carlo methods for high dimensional inversion in remote sensing

Summary.  We discuss the inversion of the gas profiles (ozone, NO₃, NO₂, aerosols and neutral density) in the upper atmosphere from the spectral occultation measurements. The data are produced by the 'Global ozone monitoring of occultation of stars' instrument on board the Envisat satellite that was launched in March 2002. The instrument measures the attenuation of light spectra at various horizontal paths from about 100 km down to 10–20 km. The new feature is that these data allow the inversion of the gas concentration height profiles. A short introduction is given to the present operational data management procedure with examples of the first real data inversion. Several solution options for a more comprehensive statistical inversion are presented. A direct inversion leads to a non-linear model with hundreds of parameters to be estimated. The problem is solved with an adaptive single-step Markov chain Monte Carlo algorithm. Another approach is to divide the problem into several non-linear smaller dimensional problems, to run parallel adaptive Markov chain Monte Carlo chains for them and to solve the gas profiles in repetitive linear steps. The effect of grid size is discussed, and we present how the prior regularization takes the grid size into account in a way that effectively leads to a grid-independent inversion.     

网络视频会议系统——一种现代远程教育解决方案

通过对目前现代远程教育应用的技术系统的分析比较 ,提出了一种基于网络视频会议系统的现代远程教育解决方案     

Model Diagnostics for Remote Access Regression Servers

To protect public-use microdata, one approach is not to allow users access to the microdata. Instead, users submit analyses to a remote computer that reports back basic output from the fitted model, such as coefficients and standard errors. To be most useful, this remote server also should provide some way for users to check the fit of their models, without disclosing actual data values. This paper discusses regression diagnostics for remote servers. The proposal is to release synthetic diagnostics—i.e. simulated values of residuals and dependent and independent variables–constructed to mimic the relationships among the real-data residuals and independent variables. Using simulations, it is shown that the proposed synthetic diagnostics can reveal model inadequacies without substantial increase in the risk of disclosures. This approach also can be used to develop remote server diagnostics for generalized linear models.     

基于客户/服务器模式的非正常RPC的研究

分析了客户／服务器模式下远程过程调用(RPC)原理及其实现方法，重点讨论了五种非正常情况下RPC的处理方法。     

Tree health mapping with multispectral remote sensing data at UC Davis, California

Tree health is a critical parameter for evaluating urban ecosystem health and sustainability. Traditionally, this parameter has been derived from field surveys. We used multispectral remote sensing data and GIS techniques to determine tree health at the University of California, Davis. The study area (363 ha) contained 8,962 trees of 215 species. Tree health conditions were mapped for each physiognomic type at two scales: pixel and whole tree. At the pixel scale, each tree pixel within the tree crown was classified as either healthy or unhealthy based on vegetation index values. At the whole tree scale, raster based statistical analysis was used to calculate tree health index which is the ratio of healthy pixels to entire tree pixels within the tree crown. The tree was classified as healthy if the index was greater than 70%. Accuracy was checked against a random sample of 1,186 trees. At the whole tree level, 86% of campus trees were classified as healthy with 88% mapping accuracy. At the pixel level, 86% of the campus tree cover was classified as healthy. This tree health evaluation approach allows managers to identify the location of unhealthy trees for further diagnosis and treatment. It can be used to track the spread of disease and monitor seasonal or annual changes in tree health. Also, it provides tree health information that is fundamental to modeling and analysis of the environmental, social, and economic services produced by urban forests.     

Mass-mediated surveillance: borders,mobility, and reality television

This article analyzes the social construction of border surveillance and policing in reality-based television. Utilizing content analytic methods to document and decode popular images of borders, mobility, and insecurity, it assesses three programs from Australia, the UK, and the United States. Despite claims of offering accurate and unfiltered depictions, the programs are ideological and provide visions of enforcement that reinforce stereotypes regarding the risks of permeable borders and exonerate intensive regimes of surveillance and securitization. Our findings suggest this occurs in three ways. First, the programs inflate the extent and seriousness of lawlessness associated with cross-border movement. Second, they offer individualistic explanations of crime that cite personal choices and pathologies as determinants. Finally, alongside neglecting their perspectives and interpretations of events, when compared to the reality of official statistics, the programs disproportionately feature suspected offenders as members of marginalized groups. The social and political implications of these findings are discussed.     

Machine Learning for Drug Overdose Surveillance

ABSTRACT

We describe two recently proposed machine learning approaches for discovering emerging trends in fatal accidental drug overdoses. The Gaussian Process Subset Scan (Herlands, McFowland, Wilson, & Neill, 2017 Neill, D. B. (2017). Multidimensional tensor scan for drug overdose surveillance. Journal of Public Health Informatics, 9(1), e20. doi:10.5210/ojphi.v9i1.7598[Crossref] , [Google Scholar]) enables early detection of emerging patterns in spatio-temporal data, accounting for both the complex, correlated nature of the data and the fact that detecting subtle patterns requires integration of information across multiple spatial areas and multiple time steps. We apply this approach to 17 years of county-aggregated data for monthly opioid overdose deaths in the New York City metropolitan area, showing clear advantages in the utility of discovered patterns as compared to typical anomaly detection approaches. To detect and characterize emerging overdose patterns that differentially affect a subpopulation of the data, including geographic, demographic, and behavioral patterns (e.g., which combinations of drugs are involved), we apply the Multidimensional Tensor Scan (Neill, 2017 Neill, D. B. (2017). Multidimensional tensor scan for drug overdose surveillance. Journal of Public Health Informatics, 9(1), e20. doi:10.5210/ojphi.v9i1.7598[Crossref] , [Google Scholar]) to 8 years of case-level overdose data from Allegheny County, Pennsylvania. We discover previously unidentified overdose patterns which reveal unusual demographic clusters, show impacts of drug legislation, and demonstrate potential for early detection and targeted intervention. These approaches to early detection of overdose patterns can inform prevention and response efforts, as well as understanding the effects of policy changes.     

Remote Work in Library Technical Services: Connecting Historical Perspectives to Realities of the Developing COVID-19 Pandemic

Abstract

The concept and practice of remote work in library technical services is not new, but the scale and speed of the transition to remote work for many libraries due to the COVID-19 pandemic is unprecedented. This column provides an overview of pre-pandemic literature on remote work in library technical services and briefly examines the history, planning, case studies, technology and equity concerns, challenges, and potential benefits of remote work. Initial connections are drawn between existing literature and the impact of the pandemic on remote work, and future directions for research and discussion are offered.     

Undercover policing and the spectre of ‘domestic extremism’: the covert surveillance of environmental activism in Britain

The spectre of environmental ‘domestic extremism’ has long been postulated by police leaders and security analysts in Britain. It is a narrative that has justified the commitment of enormous amounts of government resources towards police intelligence work directed at non-violent direct action campaigns. Most controversially, this has included the long-term infiltration of environmental (and other) activist groups by undercover police. This article provides a critical analysis of the justifications put forward in support of the covert surveillance of environmental activists in Britain. The paper proceeds by way of a single case study – a high profile, environmental direct action protest in the north of England – in order to reveal the levels of abuse, manipulation and deception at the basis of undercover protest policing. Through their court case, the activists involved with this action were able to obtain rare insights into the police authorisation documents for the undercover operation that had led to their arrests. An analysis of these documents provides us with a glimpse of the contradictory justifications given by senior police officers for infiltration – now under scrutiny by a public inquiry.     

Rating the revolution: Silicon Valley in normative perspective

Silicon Valley, California – home of Apple, Facebook, Twitter, Google, and so on – is widely regarded as the epicentre of the information revolution. However, it is not just a technical or economic phenomenon; it has also made a social revolution. The article evaluates Silicon Valley from a normative perspective, seeking to identify its real societal impact, negative as well as positive. A select review of significant literature is followed by exposition of primary data, based on in situ face-to-face interviews with Valley occupants; these range from the chief technology officer of a global brand to a homeless, unemployed Vietnam War veteran. The article organises its findings under three headings: the nature of information revolution; iCapitalism as a new technoeconomic synthesis; and the normative crisis of the information society. It concludes with a warning about ongoing attempts to clone Silicon Valley around the world.