Loveparade 2010: Automatic video analysis of a crowd disaster

On July 24, 2010, 21 people died and more than 500 were injured in a stampede at the Loveparade, a music festival, in Duisburg, Germany. Although this tragic incident is but one among many terrible crowd disasters that occur during pilgrimage, sports events, or other mass gatherings, it stands out for it has been well documented: there were a total of seven security cameras monitoring the Loveparade and the chain of events that led to disaster was meticulously reconstructed.In this paper, we present an automatic, video-based analysis of the events in Duisburg. While physical models and simulations of human crowd behavior have been reported before, to the best of our knowledge, automatic vision systems that detect congestions and dangerous crowd turbulences in real world settings were not reported yet. Derived from lessons learned from the video footage of the Loveparade, our system is able to detect motion patterns that characterize crowd behavior in stampedes. Based on our analysis, we propose methods for the detection and early warning of dangerous situations during mass events. Since our approach mainly relies on optical flow computations, it runs in real-time and preserves privacy of the people being monitored.     

A globally optimal estimator for the delta-lognormal modeling of fast reaching movements

Fast reaching movements are an important component of our daily interaction with the world and are consequently under investigation in many fields of science and engineering. Today, useful models are available for such studies, with tools for solving the inverse dynamics problem involved by these analyses. These tools generally provide a set of model parameters that allows an accurate and locally optimal reconstruction of the original movements. Although the solutions that they generate may provide a data curve fitting that is sufficient for some pattern recognition applications, the best possible solution is often necessary in others, particularly those involving neuroscience and biomedical signal processing. To generate these solutions, we present a globally optimal parameter extractor for the delta-lognormal modeling of reaching movements based on the branch-and-bound strategy. This algorithm is used to test the impact of white noise on the delta-lognormal modeling of reaching movements and to benchmark the state-of-the-art locally optimal algorithm. Our study shows that, even with globally optimal solutions, parameter averaging is important for obtaining reliable figures. It concludes that physiologically derived rules are necessary, in addition to global optimality, to achieve meaningful ?Λ extractions which can be used to investigate the control patterns of these movement primitives.     

Clones: what is that smell?

Clones are generally considered bad programming practice in software engineering folklore. They are identified as a bad smell?(Fowler et?al. 1999) and a major contributor to project maintenance difficulties. Clones inherently cause code bloat, thus increasing project size and maintenance costs. In this work, we try to validate the conventional wisdom empirically to see whether cloning makes code more defect prone. This paper analyses the relationship between cloning and defect proneness. For the four medium to large open source projects that we studied, we find that, first, the great majority of bugs are not significantly associated with clones. Second, we find that clones may be less defect prone than non-cloned code. Third, we find little evidence that clones with more copies are actually more error prone. Fourth, we find little evidence to support the claim that clone groups that span more than one file or directory are more defect prone than collocated clones. Finally, we find that developers do not need to put a disproportionately higher effort to fix clone dense bugs. Our findings do not support the claim that clones are really a “bad smell”?(Fowler et?al. 1999). Perhaps we can clone, and breathe easily, at the same?time.     

A digital library framework for heterogeneous music collections: from document acquisition to cross-modal interaction

In this paper, we present a digital library system for managing heterogeneous music collections. The heterogeneity refers to various document types and formats as well as to different modalities, e. g., CD-audio recordings, scanned sheet music, and lyrics. The system offers a full-fledged, widely automated document processing chain: digitization, indexing, annotation, access, and presentation. Our system is implemented as a generic and modular music repository based on a service-oriented software architecture. As a particular strength of our approach, the various documents representing aspects of a piece of music are jointly considered in all stages of the document processing chain. Our user interfaces allow for a multimodal and synchronized presentation of documents (WYSIWYH: what you see is what you hear), a score- or lyrics-based navigation in audio, as well as a cross- and multimodal retrieval. Hence, our music repository may be called a truly cross-modal library system. In our paper, we describe the system components, outline the techniques of the document processing chain, and illustrate the implemented functionalities for user interaction. We describe how the system is put into practice at the Bavarian State Library (BSB) Munich as a part of the German PROBADO Digital Library Initiative (PDLI).     

A population-based iterated greedy algorithm for the minimum weight vertex cover problem

Given an undirected, vertex-weighted graph, the goal of the minimum weight vertex cover problem is to find a subset of the vertices of the graph such that the subset is a vertex cover and the sum of the weights of its vertices is minimal. This problem is known to be NP-hard and no efficient algorithm is known to solve it to optimality. Therefore, most existing techniques are based on heuristics for providing approximate solutions in a reasonable computation time.Population-based search approaches have shown to be effective for solving a multitude of combinatorial optimization problems. Their advantage can be identified as their ability to find areas of the space containing high quality solutions. This paper proposes a simple and efficient population-based iterated greedy algorithm for tackling the minimum weight vertex cover problem. At each iteration, a population of solutions is established and refined using a fast randomized iterated greedy heuristic based on successive phases of destruction and reconstruction. An extensive experimental evaluation on a commonly used set of benchmark instances shows that our algorithm outperforms current state-of-the-art approaches.     

Conception assistée par ordinateur des circuits intégrés monolithiques hyperfréquences

Computer aided design of microwave monolithic integrated circuits must combine two different fields. The first domain is the simulation of microwave circuits taking into account non linear aspects development of time domain and harmonic balance simulation algorithms specialized for microwave circuits. In the second place are found, the layout algorithms which were developed for logic circuits (on Si or GaAs). The association of these two types of algorithms leads to the constitution of aCad workstation for microwave monolithic integrated circuits. Two examples of design and realization of integrated circuits with these tools are presented.     

基于模式覆盖的仿真数据匹配算法

研究仿真数据优化匹配传输效率问题,随着分布交互式仿真规模的扩大,如何高效地对仿真数据进行分发和过滤成为一个重要的问题.针对分布交互式仿真领域数据类型固定和属性个数跨度较大的特点,在分析和研究已有事件匹配算法的基础上,提出了模式覆盖集的概念,并设计了一种采用模式覆盖技术的仿真数据匹配算法.改进算法综合考虑了谓词之间的相互关系和订阅条件所属模式之间的覆盖关系,从减少无关的谓词匹配和高效组织订阅条件两方面加速了仿真数据的匹配过程.实验结果表明与谓词计数算法相比,改进算法能较大地提高匹配性能.     

Complement-Opsonized Nano-Carriers Are Bound by Dendritic Cells (DC) via Complement Receptor (CR)3, and by B Cell Subpopulations via CR-1/2, and Affect the Activation of DC and B-1 Cells

The development of nanocarriers (NC) for biomedical applications has gained large interest due to their potential to co-deliver drugs in a cell-type-targeting manner. However, depending on their surface characteristics, NC accumulate serum factors, termed protein corona, which may affect their cellular binding. We have previously shown that NC coated with carbohydrates to enable biocompatibility triggered the lectin-dependent complement pathway, resulting in enhanced binding to B cells via complement receptor (CR)1/2. Here we show that such NC also engaged all types of splenic leukocytes known to express CR3 at a high rate when NC were pre-incubated with native mouse serum resulting in complement opsonization. By focusing on dendritic cells (DC) as an important antigen-presenting cell type, we show that CR3 was essential for binding/uptake of complement-opsonized NC, whereas CR4, which in mouse is specifically expressed by DC, played no role. Further, a minor B cell subpopulation (B-1), which is important for first-line pathogen responses, and co-expressed CR1/2 and CR3, in general, engaged NC to a much higher extent than normal B cells. Here, we identified CR-1/2 as necessary for binding of complement-opsonized NC, whereas CR3 was dispensable. Interestingly, the binding of complement-opsonized NC to both DC and B-1 cells affected the expression of activation markers. Our findings may have important implications for the design of nano-vaccines against infectious diseases, which codeliver pathogen-specific protein antigen and adjuvant, aimed to induce a broad adaptive cellular and humoral immune response by inducing cytotoxic T lymphocytes that kill infected cells and pathogen-neutralizing antibodies, respectively. Decoration of nano-vaccines either with carbohydrates to trigger complement activation in vivo or with active complement may result in concomitant targeting of DC and B cells and thereby may strongly enhance the extent of dual cellular/humoral immune responses.     

Prediction of Functional Consequences of Missense Mutations in ANO4 Gene

The anoctamin (TMEM16) family of transmembrane protein consists of ten members in vertebrates, which act as Ca²⁺-dependent ion channels and/or Ca²⁺-dependent scramblases. ANO4 which is primarily expressed in the CNS and certain endocrine glands, has been associated with various neuronal disorders. Therefore, we focused our study on prioritizing missense mutations that are assumed to alter the structure and stability of ANO4 protein. We employed a wide array of evolution and structure based in silico prediction methods to identify potentially deleterious missense mutations in the ANO4 gene. Identified pathogenic mutations were then mapped to the modeled human ANO4 structure and the effects of missense mutations were studied on the atomic level using molecular dynamics simulations. Our data show that the G80A and A500T mutations significantly alter the stability of the mutant proteins, thus providing new perspective on the role of missense mutations in ANO4 gene. Results obtained in this study may help to identify disease associated mutations which affect ANO4 protein structure and function and might facilitate future functional characterization of ANO4.