Document‐centric XML workflows with fragment digital signatures

The use of digital document management and processing is increasing. Traditional workflows of paper forms are being replaced by electronic workflows of digital documents. These workflows often require multiple signatures to be added to the documents for authorization and/or integrity. We describe examples of digital workflows that illustrate problems with digital signatures: i.e. the use of digital signatures across entire documents results in signatures that can be unnecessarily invalidated by subsequent modification of the document. We propose the use of fragment signatures, which reduce unnecessary invalidation of signatures and enable greater concurrency in workflows. Our approach is document‐centric and does not use a centralized database. We report on an implementation that allows fragment signatures over document fragments as well as the attachment (or embedding) of other documents. This allows collaborative or cooperative editing to occur on parts of a document without disturbing unrelated signatures. We describe the lessons learned from our deployments and offer further ways to embed such signatures into other document types. Copyright © 2010 John Wiley & Sons, Ltd.     

Cameo: an alternative model of concurrency for Eiffel

We present a new concurrency model for the Eiffel programming language. The model is motivated by describing a number of semantic problems with the leading concurrency model for Eiffel, namely SCOOP. Our alternative model aims to preserve the existing behaviour of sequential programs and libraries wherever possible. Comparison with the SCOOP model is made. The concurrency aspects of the alternative model are presented in CSP along with a model of exceptions. The results show that while the new model provides increased parallelism, this comes with the price of increased overhead due to lock management.     

Target coverage in camera networks for manufacturing workplaces

In this paper, we investigate the camera network placement problem for target coverage in manufacturing workplaces. The problem is formulated to find the minimum number of cameras of different types and their best configurations to maximise the coverage of the monitored workplace such that the given set of target points of interest are each k-covered with a predefined minimum spatial resolution. Since the problem is NP-complete, and even NP-hard to approximate, a novel method based on Simulated Annealing is presented to solve the optimisation problem. A new neighbourhood generation function is proposed to handle the discrete nature of the problem. The visual coverage is modelled using realistic and coherent assumptions of camera intrinsic and extrinsic parameters making it suitable for many real world camera based applications. Task-specific quality of coverage measure is proposed to assist selecting the best among the set of camera network placements with equal coverage. A 3D CAD of the monitored space is used to examine physical occlusions of target points. The results show the accuracy, efficiency and scalability of the presented solution method; which can be applied effectively in the design of practical camera networks.     

Analysis of the human immune response to vaccinia by use of a novel protein microarray suggests that antibodies recognize less than 10% of the total viral proteome

Control of smallpox by mass vaccination was one of the most effective public health measures ever employed for eradicating a devastating infectious disease. However, new methods are needed for monitoring smallpox immunity within current vulnerable populations, and for the development of replacement vaccines for use by immunocompromized or low-responding individuals. As a measure for achieving this goal, we developed a protein microarray of the vaccinia virus proteome by using high-throughput baculovirus expression and purification of individual elements. The array was validated with therapeutic-grade, human hyperimmune sera, and these data were compared to results obtained from individuals vaccinated against smallpox using Dryvax. A high level of reproducibility with a very low background were apparent in repetitive assays that confirmed previously reported antigens and identified new proteins that may be important for neutralizing viral infection. Our results suggest that proteins recognized by antibodies from all vaccinees constituted <10% of the total vaccinia proteome.     

Attachment, Self-Esteem, Worldviews, and Terror Management: Evidence for a Tripartite Security System.

On the basis of prior work integrating attachment theory and terror management theory, the authors propose a model of a tripartite security system consisting of dynamically interrelated attachment, self-esteem, and worldview processes. Four studies are presented that, combined with existing evidence, support the prediction derived from the model that threats to one component of the security system result in compensatory defensive activation of other components. Further, the authors predicted and found that individual differences in attachment style moderate the defenses. In Studies 1 and 2, attachment threats motivated worldview defense among anxiously attached participants and motivated self-enhancement (especially among avoidant participants), effects similar to those caused by mortality salience. In Studies 3 and 4, a worldview threat and a self-esteem threat caused attachment-related proximity seeking among fearful participants and avoidance of proximity among dismissing participants. The authors' model provides an overarching framework within which to study attachment, self-esteem, and worldviews. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Competitive Delivered Spatial Pricing

This paper contributes to the literature by studying price and production competition between spatially distributed profit maximizing firms. Firms compete by setting delivered prices, planning production, and sending output to each market. Both elastic demand and non-linear production costs are assumed. A non-cooperative game is defined, and its properties are characterized. We find spatial pricing patterns similar to those found by Hoover (1936). Existence and general properties of the Nash price and production equilibrium are shown and sufficient conditions that guarantee the existence of an unique price-production-transportation equilibrium are presented. A convergent algorithm is shown to find the equilibrium and is demonstrated with an example.     

天津办公建筑空间设计因素节能分析与优化

为改善天津地区办公建筑空间节能效果,以点式高层办公楼为例,研究空间设计因素对建筑能耗的影响及优化节能设计方案.首先基于案例调研总结其空间设计因素的典型值或值域,建立典型模型;然后选择6项空间设计因素展开分析,包括平面长宽比、建筑朝向、标准层面积、层高、窗墙比、外窗水平遮阳板长度,依次通过正交试验和列表法安排DesignBuilder能耗模拟试验,从而很快地获得优化节能设计方案.模拟试验考虑两种围护结构构造类型,分别代表常规构造和被动房构造.试验结果表明:层高与窗墙比构成建筑能耗的两项重要影响因素,其次为标准层面积、平面长宽比与建筑朝向、外窗水平遮阳板长度;优化节能设计方案中各因素的取值为:平面长宽比2∶1,建筑朝向南向,标准层面积1 024 m~2,层高3.6 m,窗墙比0.3,外窗水平遮阳板长度300 mm.经过试验设计与模拟分析,实现天津地区点式高层办公楼空间节能效果最大化,为该地区办公建筑节能设计提供参考.     

Mikrostrukturielle Charakterisierung von ultra-hochfesten Schweißgütern

Welded steel structures are a crucial part of lightweight constructions in several industrial segments. The filler metal plays a vital role in optimizing the properties of welded joints. In this study different methods were used to characterize the microstructure of ultra-high strength all-weld metal samples with different chemical compositions. It was evaluated which method can be used to link the grain size of a sample to its toughness.     

Advances in machine learning applications for scenario intelligence: deep learning

In this paper, we discuss the inextricable link between automating training environment adaptation and deep understanding of the context surrounding specific decisions and actions executed in the performance environment. To enable deep contextual understanding, psychological measurement strategies are needed to more accurately and rapidly model the psychologically meaningful details of the trainee's interactions with events, objects, and people in the training environment. As these interactions often entail complex, nonlinear cue-action relationships, the underlying models must effectively capture the nuance, complexity, and largely intuitive nature of human decision-making. This paper discusses the promise of an emerging field of machine learning – deep neural networks – for supporting this requirement.