Rain or Snow Detection in Image Sequences Through Use of a Histogram of Orientation of Streaks

The detection of bad weather conditions is crucial for meteorological centers, specially with demand for air, sea and ground traffic management. In this article, a system based on computer vision is presented which detects the presence of rain or snow. To separate the foreground from the background in image sequences, a classical Gaussian Mixture Model is used. The foreground model serves to detect rain and snow, since these are dynamic weather phenomena. Selection rules based on photometry and size are proposed in order to select the potential rain streaks. Then a Histogram of Orientations of rain or snow Streaks (HOS), estimated with the method of geometric moments, is computed, which is assumed to follow a model of Gaussian-uniform mixture. The Gaussian distribution represents the orientation of the rain or the snow whereas the uniform distribution represents the orientation of the noise. An algorithm of expectation maximization is used to separate these two distributions. Following a goodness-of-fit test, the Gaussian distribution is temporally smoothed and its amplitude allows deciding the presence of rain or snow. When the presence of rain or of snow is detected, the HOS makes it possible to detect the pixels of rain or of snow in the foreground images, and to estimate the intensity of the precipitation of rain or of snow. The applications of the method are numerous and include the detection of critical weather conditions, the observation of weather, the reliability improvement of video-surveillance systems and rain rendering.     

Derivation of imperfect interface models coupling damage and temperature

In this paper we introduce a model describing a layered structure composed by two thermoelastic adherents and a thin adhesive subject to a degradation process. By an asymptotic expansion method, we derive a model of imperfect interface coupling damage and temperature evolution. Moreover, assuming that the behaviour of the adhesive is ruled by two different regimes, one in traction and one in compression, we derive a second limit model where unilateral contact conditions on the interface are also included.     

A generic architecture to synchronise design models issued from heterogeneous business tools: towards more interoperability between design expertises

Product development involves many experts collaborating to the same design goal. Every expert has his own formalisms and tools leading to a high heterogeneity of information systems supporting design activities. Interoperability became a major challenge to avoid information incompatibility along the product life cycle. To synchronise heterogeneous representations of product will be a major step to integrate expert activities. In this paper, the authors propose a meta-model framework to connect together heterogeneous design models. This meta-model framework is used to formalise possible interactions between heterogeneous representations. Interaction formalisation is considered as a key point to synchronise heterogeneous models and to provide more interoperability between various computer assisted systems. The synchronisation loop is also presented as a major sequence of activities to manage collaborative design. Tools to support synchronisation are proposed. However, through a basic case study, authors highlight what can be automated and where human intervention is still expected.     

Learning Structure from Data and Its Application to Ozone Prediction

In this paper we propose an algorithm for structure learning in predictive expert systems based on a probabilistic network representation. The idea is to have the simplest structure (minimum number of links) with acceptable predictive capability. The algorithm starts by building a tree structure based on measuring mutual information between pairs of variables, and then it adds links as necessary to obtain certain predictive performance. We have applied this method for ozone prediction in México City, where the ozone level is used as a global indicator for the air quality in different parts of the city. It is important to predict the ozone level a day, or at least several hours in advance, to reduce the health hazards and industrial losses that occur when the ozone reaches emergency levels. We obtained as a first approximation a tree-structured dependency model for predicting ozone in one part of the city. We observe that even with only three parameters, its estimations are acceptable.A causal network representation and the structure learning techniques produced some very interesting results for the ozone prediction problem. Firstly, we got some insight into the dependence structure of the phenomena. Secondly, we got an indication of which are the important and not so important variables for ozone forecasting. Taking this into account, the measurement and computational costs for ozone prediction could be reduced. And thirdly, we have obtained satisfactory short term ozone predictions based on a small set of the most important parameters.     

Solving the electricity production planning problem by a column generation based heuristic

This paper presents a heuristic method based on column generation for the EDF (Electricité De France) long-term electricity production planning problem proposed as subject of the ROADEF/EURO 2010 Challenge. This is to our knowledge the first-ranked method among those methods based on mathematical programming, and was ranked fourth overall. The problem consists in determining a production plan over the whole time horizon for each thermal power plant of the French electricity company, and for nuclear plants, a schedule of plant outages which are necessary for refueling and maintenance operations. The average cost of the overall outage and production planning, computed over a set of demand scenarios, is to be minimized. The method proceeds in two stages. In the first stage, dates for outages are fixed once for all for each nuclear plant. Data are aggregated with a single average scenario and reduced time steps, and a set-partitioning reformulation of this aggregated problem is solved for fixing outage dates with a heuristic based on column generation. The pricing problem associated with each nuclear plant is a shortest path problem in an appropriately constructed graph. In the second stage, the reload level is determined at each date of an outage, considering now all scenarios. Finally, the production quantities between two outages are optimized for each plant and each scenario by solving independent linear programming problems.     

虚拟群体与动态视频场景的在线实时融合

将虚拟人群与实拍视频场景融合实现虚拟人群对现实场景中动态目标的合理避让,是增强现实技术有待解决的一个新问题.文中首先对实拍视频流进行分析,获取真实动态目标在三维空间中的运动信息;然后将动态目标的运动转化为每个虚拟角色的约束条件,实时更新虚拟角色的运动决策,实现其对现实场景中动态目标的避让以及虚拟角色之间的避让.为了清晰地展示现实世界中多个目标的空间位置关系,还对视频画面中的目标体做了精确的实时分割,以产生正确的遮挡关系和目标定位.最后通过实验结果表明了该算法的有效性.     

The Identification and Influence of Social Roles in a Social Media Product Community

This research focuses on the identification of social roles and an investigation of their influence in online context. Relying on a systemic approach for role conceptualization, we investigate member's activity, shared content and position in the network within a consumer to consumer social media‐based community (SMC) around a product. This investigation led to the identification of ten core roles, based on three key elements: object of interest (product, practice, and community), main contribution type (sharing information and seeking information), individual orientation (factual, emotional). We propose an explanation about how these roles, through their positioning, participate in the community dynamics and how they contribute to the creation and diffusion of cookery as a social practice, shaping the periphery around this practice.     

Multimodal person discovery in broadcast TV: lessons learned from MediaEval 2015

Multimedia Tools and Applications - We describe the “Multimodal Person Discovery in Broadcast TV” task of MediaEval 2015 benchmarking initiative. Participants were asked to return the...     

River: an intermediate language for stream processing

This paper presents both a calculus for stream processing, named Brooklet, and its realization as an intermediate language, named River. Because River is based on Brooklet, it has a formal semantics that enables reasoning about the correctness of source translations and optimizations. River builds on Brooklet by addressing the real‐world details that the calculus elides. We evaluated our system by implementing front‐ends for three streaming languages, and three important optimizations, and a back‐end for the System S distributed streaming runtime. Overall, we significantly lower the barrier to entry for new stream‐processing languages and thus grow the ecosystem of this crucial style of programming. Copyright © 2015 John Wiley & Sons, Ltd.     

Real‐time hybrid control of electrohydraulic active suspension

Electrohydraulic actuators are an attractive choice for active suspension, because these systems provide a high power‐to‐weight ratio. However, their dynamics are highly nonlinear. In addition, the use of one simple controller for both position and force is complicated, because there is a compromise between them in the case of active suspension. Most existing controllers do not efficiently fulfill the requirements, because only one state variable is considered. In this paper, we address these problems by developing a new hybrid controller for both position and force and implementing it in a real‐time test bench. Our goal is to control the vertical position of the passenger seat while tracking the force transmitted to passengers and keeping it within tolerable and comfortable limits. Therefore, the proposed controller is a combination of two controllers. Its flexible structure redirects the control signal to control the proper controlled state variable. The real‐time results of the newly designed hybrid controller are compared with those obtained using a classical proportional integral derivative controller, because this is the most widely used controller in the industry. As expected, the proposed controller demonstrates better performance in real‐time operation. Copyright © 2017 John Wiley & Sons, Ltd.