Multi-channel opportunistic spectrum access: A mixed-scale decision perspective

The scale-dependent market trend: Empirical evidences using the lagged DFA method

Energy barriers and the corresponding magnetization configurations of a nanowire of arbitrary length are derived analytically. The results interpolate between the Néel-Brown theory and the soliton-antisoliton mechanism for long samples. It is shown that the reversal mechanism depends on the time scale being probed. For sufficient size, one and the same particle reverses uniformly for fields close to the anisotropy field at short time scales, but reverses nonuniformly at low fields and large time scales. Remarkably, the energy barrier for nonuniform reversal is considerably lower than that for uniform reversal at small time scales.

We construct five new fractal traffic models based on the unified framework of fractal point processes (FPPs), and analyze their asymptotic statistical properties. Two of them are on-off types, suitable for characterizing an aggregate fractal traffic source. The other three provide a structure suitable for flow modeling, allowing one to gain a quantitative understanding of how application- or flow-level fractal dynamics (such as user activity, session/flow arrivals, duration, and volume distributions) affect packet-level fractal dynamics. Such a structure, together with analytic results obtained in this work, opens an entirely new horizon that enables us to explain the causes and origins of complex multiple-time-scale behavior of packet-level dynamics in a quantitative manner, i.e., multi-fractal patterns over small time scales and mono-fractal behavior over large time scales. Consequently, they provide network traffic engineering researchers and practitioners with practical and flexible tools for analyzing, devising and performing various traffic engineering studies. All of the FPPs are implemented in OPNET as IP-routable traffic generators.

Accurate disk workloads are crucial for storage systems design, but I/O traces are difficult to obtain, unwieldy to work with, and unparameterizable. I/O traces are often bursty and difficult to characterize. Although good models of I/O workloads would be extremely useful, such bursty traces cannot accurately be modeled using exponential or Poisson arrival times. Much experimental evidence suggests that I/O traces are self-similar, which researchers have hoped might help to model bursty traces. In this paper, we show that self-similarity at large time scales does not significantly affect disk behavior with respect to response times. This allows us to generate synthetic arrival patterns at relatively small time scales, improving the accuracy of trace generation. The relative error of our method, with input parameters suitable for the workload, ranges from approximately 8% to 12%.

It is an undoubted fact, within the scientific community, that the global temperature has increased by about 0.7°C over the last century, a figure that is considered disproportionally large. With the whole world being alarmed, the scientific community has assumed the task to explain this warming phenomenon. This has resulted in the formation of basically two schools of thought with two opposing theories. The first theory (the most popular one) claims that the prime guilty for the recent temperature increase is the release of greenhouse gases – mainly Carbon Dioxide (CO2) – coming mostly from the burning of fossil fuels, the clearing of land and the manufacture of cement. Due to these anthropogenic activities the concentration of CO2 has increased by about 35% from its ‘pre-industrial’ values, with all the resulting consequences. There are though other factors – besides the greenhouse gases – that affect the global temperature, like changes in solar activity, cloud cover, ocean circulation and others. Therefore, the ‘second’ theory claims that it is the Sun’s activity that has caused the recent warming that, incidentally in this theory, is considered to be in the generally expected limits of the physical temperature variation throughout the aeons. One assumption on how the Sun is affecting the climate is that the magnetic field and the solar wind modulate the amount of high energy cosmic radiation that the earth receives. This in turn affects the low altitude cloud cover and the amount of water vapor in the atmosphere and thus regulates the climate. (It must be noted that water vapor is considered as the main greenhouse gas.) In the sequel both of the above-mentioned theories are examined and conclusions about their soundness are drawn. Firstly (section 2), an analysis in past time of the temperature of the Earth is presented, showing that today’s temperatures are not in any way extraordinary, unnatural or exceptional, contrary to what many scientists claim. In fact, on large time scale today’s temperatures agree with what was expected for this geologic period, while on a small time scale the higher temperatures observed are the result of a natural recovery of the planet from the global coldness of the Little Ice age. In section 3, the view of the Intergovernmental Panel on Climate Change (IPCC) on the effect of the accumulation of the CO2 in the atmosphere is presented. Then, in section 4 the CO2 accumulation effect during the past is examined on large and small time scales. Note that Florides & Christodoulides (2009) using three independent sets of data (collected from ice-cores and Chemistry) presented a specific regression analysis and concluded that forecasts about the correlation between CO2-concentration and temperature rely heavily on the choice of data used, making it very doubtful if such a correlation exists or even, if

ABSTRACTA time evolution method is used to compute the electron escape time and dark current of a quantum dot under electric field. We found that for quantum dots with just one bound state, the ground state wave function can be well described by the product of a 2D confined wave function in the x, y plane and a 1D confined wave function in the z direction with an effective quantum well potential. A comparison of phase-shift analysis and the full time-dependent calculation is presented. Good agreement between the two in the large time scale is found, but discrepancy exists in the small time scale. Our study shows that the electron escape rate (which determines dark current) of quantum dots is much lower than that of quantum wells with the same bound-to-continuum transition energy.

Dual-timescale resource management for multi-type caching placement and multi-user computation offloading in Internet of Vehicle

We present an empirical analysis of the microstructure of financial markets and, in particular, of the static and dynamic properties of liquidity. We find that on relatively large time scales (15 min) large price fluctuations are connected to the failure of the subtle mechanism of compensation between the flows of market and limit orders: in other words, the missed revelation of the latent order book breaks the dynamical equilibrium between the flows, triggering the large price jumps. On smaller time scales (30 s), instead, the static depletion of the limit order book is an indicator of an intrinsic fragility of the system, which is related to a strongly nonlinear enhancement of the response. In order to quantify this phenomenon we introduce a measure of the liquidity imbalance present in the book and we show that it is correlated to both the sign and the magnitude of the next price movement. These findings provide a quantitative definition of the effective liquidity, which proves to be strongly dependent on the considered time scales.

Two time scales are distinguished in the geomagnetotail dynamics. The small scale (T1) corre� sponds to disturbances propagating in the tail lobes, which have a relatively strong magnetic field and low plasma density. The larger scale (T 2 ) corresponds to plasma motions in the plasma sheet and has a relatively weak magnetic field and a relatively higher density. A disturbance, which is initiated by a localized burst of magnetic reconnection and appears in the geomagnetotail on the time scale T1, generates the upset of equi� librium in the plasma sheet zones with intermediate spatial dimensions (about RE). The theoretical consid� erations and numerical simulation indicate that the relaxation process, which subsequently proceeds on the larger time scale (T 2 ), results in the appearance of extremely thin embedded current sheets and in the gener� ation of fast plasma flows. This process gives an effective mechanism by which the magnetic energy stored in the geomagnetotail is transformed into the plasma flow kinetic energy. Such fast flows can also generate eddy plasma motions on smaller spatial scales. On the one hand, fast MHD components of this process carry a dis� turbance in other plasma sheet zones, where new magnetic reconnection bursts can originate at a large dis� tance from the zone of an initial nonlinear disturbance. As a result, new recurrent processes of relaxation orig� inate on the T2 time scale. Alternation originating in such a way is apparently the characteristic feature of eddy disturbances actually observed in the plasma sheet.

The purpose of this article is analysing the variability of Buzau river monthly mean discharges, maximum and minimum over time and the impact of Siriu Dam on these discharges. Keeping a stable, moderate variability on the water flow has a significant importance, as this assures normality of life and functionality of the dams. On another hand, the dams are in-built with a range of parameters, decided according to this variability of the discharges. The used data has been collected from Nehoiu and Basca Roziliei hydrometric stations and spans on 55 years, from 1st January 1955 to 31st December 2010. Mid-period, on 30th September 1984, Siriu Dam started operating and the results reveal that its impact on the variability has been moderate on a large time scale. Important changes appear on smaller time scale, as months. The results are supported by graphs drawn in Excel and methods embedded by software.

The Advanced Research Projects Agency (ARPA) has initiated the Synthetic Theater of War (STOW) program to expand the current distributed interactive simulation (DIS) capability to handle larger exercises. Characterizations of the unclassified network traffic from the Synthetic Theater of War-Europe (STOW-E) demonstration are assessed in the context of self-similarity. At small time scales, the LAN traffic oscillates between burstiness and smoothness, whereas the WAN traffic exhibits smoothness. However, both the LAN and the WAN traffic exhibit high burstiness on larger time scales. Therefore, the traffic shows characteristics that would be produced by Poisson-type and self-similar processes. Additionally, in comparing the STOW-E traffic with an asymptotically self-similar process, we find that it has an unusually high Hurst parameter (i.e., H/spl sim/1). A simple mathematical model for the traffic is an uncorrelated process whose parameters vary according to another asymptotically self similar process of high burstiness. Since a combination of self-similar processes results in an asymptotically self-similar process, we conjecture that future STOW traffic should behave as asymptotically modulated self-similar processes.

In the emerging field of multiscale systems, many practical problems in the physical and biological sciences require the simulation of signals at the molecular level or the merging of signals generated over large and different spatial and time scales. Computationally, the former is intractable for large-sized systems (hundreds of millions of atoms) over large time scales (micro to miliseconds) while the compounding of information over different scales presents unique challenges and opportunities for wavelet-based as also other techniques. While the multiresolution aspect of wavelets has been explored in this context, the generation of a formal, rigorous methodology that would govern their use in the understanding of interscale phenomena still exists as an open problem. The purpose here is to provide a brief elementary introduction to the multiscale problem, to introduce the role that wavelets and in particular the Compound Wavelet Matrix have played in the bridging of information across scales, and to suggest related areas for exploration. A few simple illustrative multiscale simulation examples where wavelets are used to bridge scales are shown.

Land–air exchanges of energy and matter are modulated by several feedback processes at both small and large space and time scales, with implications for the linked carbon, water and energy cycles. This paper studies the influences of four local feedbacks, occurring at single‐patch spatial scales and subdiurnal temporal scales, on the surface energy balance (SEB) and land–air carbon fluxes. The feedbacks are: (i) radiative feedback, the modulation of available energy through the effect of surface temperature, Ts, on outgoing longwave radiation; (ii) physiological feedback, the interaction between vegetation physiology and the SEB through Ts; (iii) aerodynamic feedback, the modulation of turbulent heat and moisture transfer by atmospheric stability; and (iv) Convective Boundary Layer (CBL) feedback, the coupling between the daytime evolution of the SEB and CBL through saturation deficit.It is found that radiative feedback is significant only over very smooth surfaces. Physiological feedback is positive with respect to Ts at moderate to high temperatures, pushing stomata towards complete closure and the SEB towards very low evaporation rates. The SEB is quite sensitive to whether or not such closure occurs. Aerodynamic feedback, on the other hand, is negative with respect to Ts at these temperatures, reducing Ts and attenuating the tendency for heat‐induced stomatal closure. CBL feedback alone does not dampen the sensitivity of the SEB to physiological feedback and stomatal closure. However, when aerodynamic feedback is included, this sensitivity is greatly reduced.

The modeling of fluid-structure interactions, such as flow-induced vibrations, is a well-developed field of mechanical engineering. Many methods exist, and it seems natural to apply them to model the behavior of plants, and potentially other cantilever-like biological structures, under flow. Overcoming this disciplinary divide, and the application of such models to biological systems, will significantly advance our understanding of ecological patterns and processes and improve our predictive capabilities. Nonetheless, several methodological issues must first be addressed, which I describe here using two practical examples that have strong similarities: one from agricultural sciences and the other from nuclear engineering. Very similar issues arise in both: individual and collective behavior, small and large space and time scales, porous modeling, standard and extreme events, trade-off between the surface of exchange and individual or collective risk of damage, variability, hostile environments and, in some aspects, evolution. The conclusion is that, although similar issues do exist, which need to be exploited in some detail, there is a significant gap that requires new developments. It is obvious that living plants grow in and adapt to their environment, which certainly makes plant biomechanics fundamentally distinct from classical mechanical engineering. Moreover, the selection processes in biology and in human engineering are truly different, making the issue of safety different as well. A thorough understanding of these similarities and differences is needed to work efficiently in the application of a mechanistic approach to ecology.

The gas temperature (Tg) dependence of nucleation and growth processes of hydrocarbon nanoparticles in low pressure Ar/CH4 RF discharges has been investigated. Measuring the electron density with the microwave cavity resonance technique allowed us to monitor nucleation processes on small (µs) time scales. On larger time scales, coagulation times and growth rates are determined by means of measuring the phase angle between the RF voltage and current in correlation with laser light scattering. The experimental results show a significant gas temperature dependence of both powder nucleation and growth processes. Within the measured gas temperature range (20–130 °C) the particle growth rate decreases by a factor of ∼3.7, while the coagulation time increases by a factor of ∼6.5 with increasing Tg. Moreover, in this paper we present a simplified model which uses the experimentally determined growth rates and coagulation times to predict the value of the critical density of nanometre sized neutral particles, necessary to initiate coagulation. This model estimates a critical density of 3.5 × 1015 m−3 at room temperature which decreases with increasing temperature.