546 research outputs found

    The use of snowcovered area in runoff forecasts

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    Long-term snowcovered area data from aircraft and satellite observations have proven useful in reducing seasonal runoff forecast error on the Kern river watershed. Similar use of snowcovered area on the Kings river watershed produced results that were about equivalent to methods based solely on conventional data. Snowcovered area will be most effective in reducing forecast procedural error on watersheds with: (1) a substantial amount of area within a limited elevation range; (2) an erratic precipitation and/or snowpack accumulation pattern not strongly related to elevation; and (3) poor coverage by precipitation stations or snow courses restricting adequate indexing of water supply conditions. When satellite data acquisition and delivery problems are resolved, the derived snowcover information should provide a means for enhancing operational streamflow forecasts for areas that depend primarily on snowmelt for their water supply

    A simulator for drones and Fanet management supporting multimedia traffic under human mobility

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    In this paper a simulator for the management of a team of Unmanned Aerial Vehicles (UAVs) and drones has been proposed. This new network is known as Fly Ad-Hoc Network (FANET), and it is a particular type of Mobile Ad-Hoc Network (MANET) but with some specific aspects that allow to provide new services in future generation networks. One of the possible applications is emergency situations or scenario where drones can provide an additional or complementary access networks supporting web services and multimedia traffic. In this paper a simulator for FANET deploying has been proposed providing the possibility to simulate different scenarios with different coverage areas. New coverage model has been included in the features and also interesting human mobility model to support more realistic users mobility. Moreover, additional modules for traffic pattern generation have been implemented to create scenario where mobile users can activate multimedia calls and traffic on FANET. Some simulations have been led out to show how the simulator works

    On packet marking and Markov modeling for IP Traceback: A deep probabilistic and stochastic analysis

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    From many years, the methods to defend against Denial of Service attacks have been very attractive from different point of views, although network security is a large and very complex topic. Different techniques have been proposed and so-called packet marking and IP tracing procedures have especially demonstrated a good capacity to face different malicious attacks. While host-based DoS attacks are more easily traced and managed, network-based DoS attacks are a more challenging threat. In this paper, we discuss a powerful aspect of the IP traceback method, which allows a router to mark and add information to attack packets on the basis of a fixed probability value. We propose a potential method for modeling the classic probabilistic packet marking algorithm as Markov chains, allowing a closed form to be obtained for evaluating the correct number of received marked packets in order to build a meaningful attack graph and analyze how marking routers must behave to minimize the overall overhead

    A new FANET simulator for managing drone networks and providing dynamic connectivity

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    In the last decade, the attention on unmanned aerial vehicles has rapidly grown, due to their ability to help in many human activities. Among their widespread benefits, one of the most important uses regards the possibility of distributing wireless connectivity to many users in a specific coverage area. In this study, we focus our attention on these new kinds of networks, called flying ad-hoc networks. As stated in the literature, they are suitable for all emergency situations where the traditional networking paradigm may have many issues or difficulties to be implemented. The use of a software simulator can give important help to the scientific community in the choice of the right UAV/drone parameters in many different situations. In particular, in this work, we focus our main attention on the new ways of area covering and human mobility behaviors with the introduction of a UAV/drone behavior model to take into account also drones energetic issues. A deep campaign of simulations was carried out to evaluate the goodness of the proposed simulator illustrating how it works

    Managing emergency situations in VANET through heterogeneous technologies cooperation

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    Nowadays, the research on vehicular computing enhanced a very huge amount of services and protocols, aimed to vehicles security and comfort. The investigation of the IEEE802.11p, Wireless Access in Vehicular Environments (WAVE) and Dedicated Short Range Communication (DSRC) standards gave to the scientific world the chance to integrate new services, protocols, algorithms and devices inside vehicles. This opportunity attracted the attention of private/public organizations, which spent lot of resources and money to promote vehicular technologies. In this paper, the attention is focused on the design of a new approach for vehicular environments able to gather information during mobile node trips, for advising dangerous or emergency situations by exploiting on-board sensors. It is assumed that each vehicle has an integrated on-board unit composed of several sensors and Global Position System (GPS) device, able to spread alerting messages around the network, regarding warning and dangerous situations/conditions. On-board units, based on the standard communication protocols, share the collected information with the surrounding road-side units, while the sensing platform is able to recognize the environment that vehicles are passing through (obstacles, accidents, emergencies, dangerous situations, etc.). Finally, through the use of the GPS receiver, the exact location of the caught event is determined and spread along the network. In this way, if an accident occurs, the arriving cars will, probably, avoid delay and danger situations

    Brain mitochondria, aging, and Parkinson’s disease

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    This paper reconsiders the role of mitochondria in aging and in Parkinson\u2019s Disease (PD). The most important risk factor for PD is aging. Alterations in mitochondrial activity are typical of aging. Mitochondrial aging is characterized by decreased oxidative phosphorylation, proteasome activity decrease, altered autophagy, and mitochondrial dysfunction. Beyond declined oxidative phosphorylation, mitochondrial dysfunction consists of a decline of beta-oxidation as well as of the Krebs cycle. Not inherited mitochondrial DNA (mtDNA) mutations are acquired over time and parallel the decrease in oxidative phosphorylation. Many of these mitochondrial alterations are also found in the PD brain specifically in the substantia nigra (SN). mtDNA deletions and development of respiratory chain deficiency in SN neurons of aged individuals as well as of individuals with PD converge towards a shared pathway, which leads to neuronal dysfunction and death. Finally, several nuclear genes that are mutated in hereditary PD are usually implicated in mitochondrial functioning to a various extent and their mutation may cause mitochondrial impairment. In conclusion, a tight link exists between mitochondria, aging, and PD

    A New Distributed Predictive Congestion Aware Re-Routing Algorithm for CO2 Emissions Reduction

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    In the last years, vehicular networking has grown up in terms of interest and transmission capability, due to the possibility of exploiting the distributed communication paradigm in a mobile scenario, where moving nodes are represented by vehicles. The different existing standards for vehicular ad-hoc networks, such as dedicate short range communication (DSRC), wireless access for vehicular environment (WAVE)/IEEE802.11p, have given to the research community the possibility of developing new medium access control (MAC) and routing schemes, in order to enhance the quality and the comfort of mobile users who are driving their vehicles. In this paper, we focus our attention on the optimization of traffic flowing in a vehicular environment with vehicle-2-roadside capability. As shown later, the proposed idea exploits the information that is gathered by road-side units to redirect traffic flows (in terms of vehicles) to less congested roads, with an overall system optimization, also in terms of carbon dioxide emissions reduction. An analytical model, as well as a set of pseudo-code instructions, have been introduced in the paper. A deep campaign of simulations has been carried out to give more effectiveness to our proposal

    ПРОБЛЕМИ ФОРМУВАННЯ ЕФЕКТИВНОГО ІМІДЖУ В СУЧАСНІЙ ПОЛІТОЛОГІЇ

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    Проаналізовані поняття та структура політичного іміджу, визначені компоненти ефективного іміджу політика, виділені складові елементи та закономірності побудови сучасної іміджевої стратегії.Analyzed the concept and structure of political image, the image identified components of effective policy, special elements and patterns of modern image strategy

    A decentralized ITS architecture for efficient distribution of traffic task management

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    In this paper, the attention is focused on the design of a new multi-layered architecture for vehicular environment. System will be able to gather information from vehicular devices. This will allow system to faster respond at emergency situation such as traffic jams or collisions. Distributed entities work at different layers exploiting cloud and fog computing in order to better distribute tasks along the infrastructure. Lower layer is composed of On-Board Units (OBUs) and RoadSide Units (RSUs) that exploits Vehicular Ad-hoc Network (VANET) protocols for inner VANET communications. At the Edge layer we propose fog computing nodes that gather data from RSUs for local processing and after an aggregation step they send data to an Intelligent Transportation System (ITS) management system. The proposed architecture has the main goal to better respond to the network and traffic dynamics by improving performances of the ITS system

    Post-activation brain warming: A 1-H MRS thermometry study

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    Purpose Temperature plays a fundamental role for the proper functioning of the brain. However, there are only fragmentary data on brain temperature (Tbr) and its regulation under different physiological conditions. Methods We studied Tbr in the visual cortex of 20 normal subjects serially with a wide temporal window under different states including rest, activation and recovery by a visual stimulation- Magnetic Resonance Spectroscopy Thermometry combined approach.We also studied Tbr in a control region, the centrum semiovale, under the same conditions. Results Visual cortex mean baseline Tbr was higher than mean body temperature (37.38 vs 36.60, P<0.001). During activation Tbr remained unchanged at first and then showed a small decrease (-0.20 CA\ub0) around the baseline value. After the end of activation Tbr increased consistently (+0.60 CA\ub0) and then returned to baseline values after some minutes. Centrum semiovale Tbr remained unchanged through rest, visual stimulation and recovery. Conclusion These findings have several implications, among them that neuronal firing itself is not a major source of heat release in the brain and that there is an aftermath of brain activation that lasts minutes before returning to baseline conditions
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