121 research outputs found
Analytical calculation of critical perturbation amplitudes and critical densities by non-linear stability analysis of a simple traffic flow model
Driven many-particle systems with nonlinear interactions are known to often display multi-stability, i.e. depending on the respective initial condition, there may be different outcomes. Here, we study this phenomenon for traffic models, some of which show stable and linearly unstable density regimes, but areas of metastability in between. In these areas, perturbations larger than a certain critical amplitude will cause a lasting breakdown of traffic, while smaller ones will fade away. While there are common methods to study linear instability, non-linear instability had to be studied numerically in the past. Here, we present an analytical study for the optimal velocity model with a stepwise specification of the optimal velocity function and a simple kind of perturbation. Despite various approximations, the analytical results are shown to reproduce numerical results very wel
Simple Heuristics and the Modelling of Crowd Behaviours
A crowd of pedestrians is a complex system that exhibits a rich variety of self-organized collective behaviors, such as lane formation, stop-and-go waves, or crowd turbulence. Understanding the mechanisms of crowd dynamics requires establishing a link between the local behavior of pedestrians during interactions, and the global dynamics of the crowd at high density. For this, the elaboration of a model is necessary. In this contribution, we will make a distinction between two kinds of modelling methods: outcome models that are often based on analogies with Newtonian mechanics, and process models based on concepts of cognitive science. While outcome models describe directly the movements of a pedestrian by means of repulsive forces or probabilities to move from one place to another, process models generate the movement from the bottom-up by describing the underlying cognitive process used by the pedestrian during navigation. Here, we will describe and compare two representatives of outcome and process models, namely the social force model on the one hand, and the heuristic model on the other hand. In particular, we will describe the strength and the limitations of each approach, and discuss possible future improvements for process models
Contribution à l’étude de l’huile essentielle de Dipcadi serotinum (l.) Medik du Maroc
Dipcadi serotinum (L.) Medik, est une plante de la famille des Hyacinthaceae, elle est largement utilisée comme réchauffant et aussi pour combattre la jaunisse. Cette plante trouve une large utilisation par la population de la région côtière du Maroc. À notre connaissance l’huile essentielle de cette espèce n’a jamais été étudiée ni chimiquement ni biologiquement. Dans ce contexte, nous avons mené une étude comparative de l’huile essentielle extraite de la partie aérienne et la partie souterraine. Les résultats obtenus pour les rendements et la composition chimique de l’huile essentielle des deux parties étudiés montrent des différences considérables.Mots-clés : Dipcadi serotinum (L.) Medik, huile essentielle, composition chimique, médecine traditionnelle, Maroc.Contribution to the study of the essential oil of Dipcadi serotinum (l.) Medik of MoroccoDipcadi serotinum (L.) Medik, is a plant of the Hyacinthaceae’s family, it is widely used as warming and also to combat the jaundice. This plant is widespread use by the population of the coastal region of Morocco. To our knowledge the essential oil of this species has never been studied or chemically or biologically. In this context, we conducted a comparative study of the essential oil extracted from the aerial part and underground part. The results for yield and chemical composition of essential oil from both sides studied showed significant differences.Keywords : Dipcadi serotinum (L.) Medik, essential oil, chemical composition, traditional medicine, Morocco
A knowledge-based view of the extending enterprise for enhancing a collaborative innovation advantage
In animal societies as well as in human crowds, many observed collective
behaviours result from self-organized processes based on local interactions
among individuals. However, models of crowd dynamics are still lacking a
systematic individual-level experimental verification, and the local mechanisms
underlying the formation of collective patterns are not yet known in detail. We
have conducted a set of well-controlled experiments with pedestrians performing
simple avoidance tasks in order to determine the laws ruling their behaviour
during interactions. The analysis of the large trajectory dataset was used to
compute a behavioural map that describes the average change of the direction
and speed of a pedestrian for various interaction distances and angles. The
experimental results reveal features of the decision process when pedestrians
choose the side on which they evade, and show a side preference that is
amplified by mutual interactions. The predictions of a binary interaction model
based on the above findings were then compared to bidirectional flows of people
recorded in a crowded street. Simulations generate two asymmetric lanes with
opposite directions of motion, in quantitative agreement with our empirical
observations. The knowledge of pedestrian behavioural laws is an important step
ahead in the understanding of the underlying dynamics of crowd behaviour and
allows for reliable predictions of collective pedestrian movements under
natural conditions
How simple rules determine pedestrian behavior and crowd disasters
With the increasing size and frequency of mass events, the study of crowd
disasters and the simulation of pedestrian flows have become important research
areas. Yet, even successful modeling approaches such as those inspired by
Newtonian force models are still not fully consistent with empirical
observations and are sometimes hard to calibrate. Here, a novel cognitive
science approach is proposed, which is based on behavioral heuristics. We
suggest that, guided by visual information, namely the distance of obstructions
in candidate lines of sight, pedestrians apply two simple cognitive procedures
to adapt their walking speeds and directions. While simpler than previous
approaches, this model predicts individual trajectories and collective patterns
of motion in good quantitative agreement with a large variety of empirical and
experimental data. This includes the emergence of self-organization phenomena,
such as the spontaneous formation of unidirectional lanes or stop-and-go waves.
Moreover, the combination of pedestrian heuristics with body collisions
generates crowd turbulence at extreme densities-a phenomenon that has been
observed during recent crowd disasters. By proposing an integrated treatment of
simultaneous interactions between multiple individuals, our approach overcomes
limitations of current physics-inspired pair interaction models. Understanding
crowd dynamics through cognitive heuristics is therefore not only crucial for a
better preparation of safe mass events. It also clears the way for a more
realistic modeling of collective social behaviors, in particular of human
crowds and biological swarms. Furthermore, our behavioral heuristics may serve
to improve the navigation of autonomous robots.Comment: Article accepted for publication in PNA
A Cooperative and Hybrid Network Intrusion Detection Framework in Cloud Computing Based on Snort and Optimized Back Propagation Neural Network
AbstractCloud computing provides a framework for supporting end users easily attaching powerful services and applications through Internet. To give secure and reliable services in cloud computing environment is an important issue. Providing security requires more than user authentication with passwords or digital certificates and confidentiality in data transmission, because it is vulnerable and prone to network intrusions that affect confidentiality, availability and integrity of Cloud resources and offered services. To detect DoS attack and other network level malicious activities in Cloud, use of only traditional firewall is not an efficient solution. In this paper, we propose a cooperative and hybrid network intrusion detection system (CH-NIDS) to detect network attacks in the Cloud environment by monitoring network traffic, while maintaining performance and service quality. In our NIDS framework, we use Snort as a signature based detection to detect known attacks, while for detecting network anomaly, we use Back-Propagation Neural network (BPN). By applying snort prior to the BPN classifier, BPN has to detect only unknown attacks. So, detection time is reduced. To solve the problem of slow convergence of BPN and being easy to fall into local optimum, we propose to optimize the parameters of it by using an optimization algorithm in order to ensure high detection rate, high accuracy, low false positives and low false negatives with affordable computational cost. In addition, in this framework, the IDSs operate in cooperative way to oppose the DoS and DDoS attacks by sharing alerts stored in central log. In this way, unknown attacks that were detected by any IDS can easily be detected by others IDSs. This also helps to reduce computational cost for detecting intrusions at others IDS, and improve detection rate in overall the Cloud environment
Diachronous folding and cleavage in an intraplate setting (Central High Atlas, Morocco) determined through the study of remagnetizations
Remagnetizations are common in intraplate basins. When remagnetizations occur at an intermediate stage between different tectonic processes, they can be used for paleo-geometrical reconstructions and relative dating of different structures. This has a particular interest in geological frameworks where other geological time markers are absent. In order to apply this methodology, it is necessary to calculate the regional remagnetization direction and subsequently to use this reference direction to restore the attitude of the beds at the moment of remagnetization acquisition. In this work, we use this methodology for dating a pervasive cleavage (whose time of formation is controversial) and the associated structures in the Central High Atlas (Morocco). Paleomagnetic directions from 64 sites were used to calculate the remagnetization direction (D = 330.9°, I = 35.1°, A/n = 6.107) which is coincident with the Albian-Cenomanian (ca. 100 M.a.) expected direction for NW Africa. This direction was used to restore the Mesozoic paleo-geometry of beds allowing us to analyze bedding orientation, cleavage and folding relationships between the present day and the Cretaceous geometry. After restoration we conclude that the development of cleavage post-dates remagnetization, being in relation with Cenozoic basin inversion. However, the paleo-geometry shows incipient folds at Cretaceous times, which can be related to an intra-Mesozoic compressional event
Extensional vs. compressional deformation in the Central High Atlas salt province: a paleomagnetic approach
In this paper we address the problem of the distinction between diapiric, salt-driven and compressional structures, using the outstanding example of the Central High Atlas (Morocco). A remagnetized component carried by magnetite has been isolated in 32 new paleomagnetic sites. It is characterized by: maximum unblocking temperatures around 450 °C, syn-folding behavior and normal polarity.
These 33 mean paleomagnetic directions were analyzed together with other 68 from published works around the study area to construct a robust paleomagnetic dataset along a cross-section perpendicular to the main structures. The remagnetization direction (n: 100, Dec: 332.2°, Inc: 34.5°, η: 6.2°, ξ: 2.0°, A/n: 6.427°) and the paleo-dip of beds (the attitude of the beds at the remagnetization occurrence) were calculated through small circle methods. The remagnetization can be dated as ca. 100 Ma. Because of its occurrence between the extensional and compressional periods, this remagnetization offers the possibility of restore the basin to its pre-inversion geometry.
Comparison between present-day and pre-inversion structure allows discriminating three different evolutionary patterns: (i) thrusted and welded salt-walls mainly structured during the extensional stage (Ikkou ridge) with steep limbs close to the salt-wall core. (ii) Jurassic salt-walls with weaker deformation, restricted to the areas adjacent to the structure (Tadaghmamt and Timedouine); in this case, Cenozoic compression is limited to welding of the salt-walls and buttressing of the sedimentary sequences against faults. (iii) salt-rollers gently initiated during the Jurassic (Toumliline diapir), thrusted during the Cenozoic compression. Results show the importance of salt tectonics both during extension and compression, as well as the control of the compressional features by the inherited extensional structures. The performed restorations prove that paleomagnetism is a useful, independent tool to obtain palinspastic restorations and to separate, and quantify, the imprint generated during the basinal stage from the inversional features.MINECO (Spanish Ministry of Economy and Competitiveness) cofinanced by the ERDF (European Union) (research projects CGL2012-38481 and CGL2016-77560
Pre-Cenomanian versus Cenozoic folding in the High Atlas revealed by palaeomagnetic data
Palaeomagnetic data, and specifically remagnetizations, are used to constrain the geometric reconstruction at 100 Ma of three anticlines cored by gabbroic intrusions and Triassic shales in the Central High Atlas, Morocco. Previous palaeomagnetic results have revealed that the Mesozoic sediments of this region acquired a pervasive remagnetization at the end of the Early Cretaceous. The restoration of palaeomagnetic vectors to the remagnetization stage (100 Ma) allows us to determine the dip of the beds during this period and, thereby, to reconstruct structures during that time and determine the relative contributions of Mesozoic magmatic/diapiric uplift vs. Cenozoic compression to the present-day dip. Our results indicate that three major anticlines in the Central High Atlas (Tasraft, Tassent and Tissila) were initiated to different degrees before the Late Cretaceous and were reactivated during Cenozoic compression to acquire their present-day geometry. We also discuss the origin of these structures
Entropic phase separation of linked beads
We study theoretically a model system of a transient network of microemulsion
droplets connected by telechelic polymers and explain recent experimental
findings. Despite the absence of any specific interactions between either the
droplets or polymer chains, we predict that as the number of polymers per drop
is increased, the system undergoes a first order phase separation into a dense,
highly connected phase, in equilibrium with dilute droplets, decorated by
polymer loops. The phase transition is purely entropic and is driven by the
interplay between the translational entropy of the drops and the
configurational entropy of the polymer connections between them. Because it is
dominated by entropic effects, the phase separation mechanism of the system is
extremely robust and does not depend on the particlular physical realization of
the network. The discussed model applies as well to other polymer linked
particle aggregates, such as nano-particles connected with short DNA linkers
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