Effects of landscape structure on vegetation and some animal groups after agriculture abandonment

This research was carried out on the montane belt of a south-exposed watershed in the Intermediary Alps which have been hit by agriculture abandonment. The aim of the study was to study the relationships between vegetation, landscape mosaic, and two kinds of animals using this space at different scales: roe deer (Capreolus capreolus) and earthworms (lumbricids). Landscape dynamics (post-cultural recolonisation) and landscape structure have been approached by means of the Arc/Info geographical information system (GIS). Several methods used to study on one hand roe deer distribution, and, on the other, earthworm abundance and diversity are developed. Of these, in particular, GIS processing is used to sample earthworms according to vegetation dynamics, and roe deer distribution is related to landscape heterogeneity. Earthworms are more abundant and diversified in the key steps of vegetation dynamics. These lumbricids can be considered as functional indicators of these dynamics. Results also demonstrate that both the vegetation type and the landscape heterogeneity have a direct influence on the use of the space by the roe deer. They show themselves to be structural indicators of the landscape.     

Reservoir Management Using a Network Flow Optimization Model Considering Quadratic Convex Cost Functions on Arcs

The allocation of water resources between different users is a hard task for water managers because they must deal with conflicting objectives. The main objective is to obtain the most accurate distribution of the resource and the associated circulating flows through the system. This induces the need for a river basin optimization model that provides optimized results. This article presents a network flow optimization model to solve the water allocation problem in water resource systems. Managing a water system consists in providing water in the right proportion, at the right place and at the right time. Time expanded network allows to take into consideration the temporal dimension in the decision making. Since linear cost functions on arcs present many limitations and are not realistic, quadratic convex cost functions on arcs are considered here. The optimization algorithm developed herein extend the cycle canceling algorithm developed for linear cost functions. The methodology is applied to manage the three reservoirs of La Haute-Vilaine’s watershed located in the north west of France to protect a three vulnerable areas from flooding. The results obtained with the algorithm are compared to a reference scenario which consists in considering reservoirs transparent. The results show that the algorithm succeeds in managing the reservoir releases efficiently and keeps the flow rates below the vigilance flow in the vulnerable areas.     

Artificial anisotropy and polarizing filters

The calculated spectral transmittance of a multilayer laser mirror is used to determine the effective index of the single layer equivalent to the multilayer stack. We measure the artificial anisotropy of photoresist thin films whose structure is a one-dimensional, subwavelength grating obtained from interference fringes. The limitation of the theory of the first-order effective index homogenization is discussed. We designed normal-incidence, polarizing coating and a polarization rotator by embedding anisotropic films in simple multilayer structures.     

Learning of grasp selection based on shape-templates

The ability to grasp unknown objects still remains an unsolved problem in the robotics community. One of the challenges is to choose an appropriate grasp configuration, i.e., the 6D pose of the hand relative to the object and its finger configuration. In this paper, we introduce an algorithm that is based on the assumption that similarly shaped objects can be grasped in a similar way. It is able to synthesize good grasp poses for unknown objects by finding the best matching object shape templates associated with previously demonstrated grasps. The grasp selection algorithm is able to improve over time by using the information of previous grasp attempts to adapt the ranking of the templates to new situations. We tested our approach on two different platforms, the Willow Garage PR2 and the Barrett WAM robot, which have very different hand kinematics. Furthermore, we compared our algorithm with other grasp planners and demonstrated its superior performance. The results presented in this paper show that the algorithm is able to find good grasp configurations for a large set of unknown objects from a relatively small set of demonstrations, and does improve its performance over time.     

Processing intrusion detection alert aggregates with time series modeling

The main use of intrusion detection systems (IDS) is to detect attacks against information systems and networks. Normal use of the network and its functioning can also be monitored with an IDS. It can be used to control, for example, the use of management and signaling protocols, or the network traffic related to some less critical aspects of system policies. These complementary usages can generate large numbers of alerts, but still, in operational environment, the collection of such data may be mandated by the security policy. Processing this type of alerts presents a different problem than correlating alerts directly related to attacks or filtering incorrectly issued alerts.We aggregate individual alerts to alert flows, and then process the flows instead of individual alerts for two reasons. First, this is necessary to cope with the large quantity of alerts – a common problem among all alert correlation approaches. Second, individual alert’s relevancy is often indeterminable, but irrelevant alerts and interesting phenomena can be identified at the flow level. This is the particularity of the alerts created by the complementary uses of IDSes.Flows consisting of alerts related to normal system behavior can contain strong regularities. We propose to model these regularities using non-stationary autoregressive models. Once modeled, the regularities can be filtered out to relieve the security operator from manual analysis of true, but low impact alerts. We present experimental results using these models to process voluminous alert flows from an operational network.     

OCEAN,a flexible adaptive Network-On-Chip for dynamic applications

The dynamic and partial reconfiguration of FPGAs enables the dynamic placement of applicatives tasks in reconfigurable zones. However, the dynamic management of the tasks impacts the communications since they are not present in the FPGA during all computation time. So, the task manager should ensure the allocation of each new task and their interconnection which is performed by a flexible interconnection network. In this article, various interconnection networks are studied. Each architecture is evaluated with respect to its suitability for the paradigm of the dynamic and partial reconfiguration in FPGA implementations. This study leads us to propose the OCEAN network that supports the communication constraints into the context of dynamic reconfigurations. Thanks to a generic platform allowing in situ characterizations of network performances, fair comparisons of various Networks-On-Chip can be realized. The FPGA and ASICs implementations of the OCEAN network are also discussed.     

Need for recovery from work: evaluating short-term effects of working hours,patterns and schedules

In this paper working hours, patterns and work schedules of employees were evaluated in terms of need for recovery from work. Self-administered questionnaire data from employees of the Maastricht Cohort Study on Fatigue at Work (n = 12,095) were used. Poisson regression analyses and multivariate logistic regression analyses revealed that higher working hours a day and working hours a week generally went together with more need for recovery from work. Overtime work was particularly associated with higher need for recovery from work in both genders. Both male and female three-shift or irregular shift workers had higher odds of elevated need for recovery compared to day workers. When additionally controlling for work-related factors, need for recovery levels among shift workers substantially lowered. This study clearly showed that working hours and schedules are associated with need for recovery from work, with different associations for men and women. Especially the associations between work schedules and need for recovery from work were very interrelated with other work-related factors. Future studies could further investigate the possibility that shift work might function as a proxy of other work-related factors that explain the different levels in need for recovery from work, or that job demands are perceived higher among shift workers and may therefore lead to more need for recovery from work.