Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantification of uncertainties from ensembles of simulations

Decision making for environmental issues increasingly relies on numerical simulations and various observational data. However, the numerical models are limited by strong uncertainties because of poor input data and inaccurate physical, chemical, biological or mathematical modeling. Moreover, measurement instruments do not allow for a complete observation of environmental systems, and they often acquire noisy observations. Nevertheless, there is a strong need to optimally and jointly exploit numerical simulations and field observations for an objective assessment of risks on present and future times. In this context, it is critical to quantify the uncertainties of all information sources (numerical models, empirical rules, fixed observations, mobile observations, qualitative observations) and to evaluate the best estimates that are derived from all the information. The final scientific products that may help decision-making are the probability distribution of the target quantities, confidence intervals or probabilistic forecasts. These various products can be derived from ensembles of simulations possibly combined with observations by the so-called data assimilation methods. The ensembles can be calibrated, including for the forecasts, in order to approximate the distribution of simulation errors. Such methods are for instance operationally applied for weather forecasting. The distribution of ensembles can be processed for a better quantification of the uncertainty. It is for instance possible to derive risk maps. Practical applications, like the protection of populations after a nuclear disaster as in Fukushima, can benefit from such risk maps, e.g., to determine an evacuation zone.
Active And Collaborative Learning Strategies For Teaching Computing

This paper is a survey of dozens of active and collaborative learning strategies that have been used in teaching computing. The most basic are “think-pair-share” exercises, where students think about a problem, discuss it with their neighbors, and then share it with the rest of the class. Teams may work together in class to solve problems, with the instructor providing written comments. Bringing competition into the picture always helps motivate students, e.g., having final projects compete against each other (e.g., a prey/predator game), or playing a Jeopardy-like game to review for an exam. Many such activities can be carried out online in a lab, or using laptops. A “scavenger hunt” gets students to work in pairs to surf the Web for answers to questions posed by the instructor. In another kind of exercise, students can be assigned to come up with new examples, or exercises, for the text, and then submit to an online peer-review system, where their work is reviewed by others, and the best work selected to be presented to future classes. Another strategy is to have students prepare resources to share with the class. They post these on a wiki, and the lectures become class meetings with an agenda posted on the wiki. The instructor moderates the meeting, and a student takes the minutes, and posts them on the Web. Peer assessment is used for all contributions. The paper concludes with a list of resources that include many more active and cooperative learning exercises.
Behavioral Types in Programming Languages

A recent trend in programming language research is to use behavioral type theory to ensure various correctness properties of large-scale, communication-intensive systems. Behavioral types encompass concepts such as interfaces, communication protocols, contracts, and choreography. The successful application of behavioral types requires a solid understanding of several practical aspects, from their representation in a concrete programming language, to their integration with other programming constructs such as methods and functions, to design and monitoring methodologies that take behaviors into account. Behavioral Types in Programming Languages provides the reader with the first comprehensive overview of the state of the art of these practical aspects, which are summarized as the pragmatics of behavioral types. Each section covers a particular programming paradigm or methodology, providing an ideal reference for programming languages researchers interested the topic, and in identifying the areas as yet unexplored.
Forecasting the Rates of Future Aftershocks of All Generations Is Essential to Develop Better Earthquake Forecast Models

Currently, one of the best performing earthquake forecasting models relies on the working hypothesis that the “locations of past background earthquakes reveal the probable location of future seismicity. ” As an alternative, we present a class of smoothed seismicity models (SSMs) based on the principles of the epidemic‐type aftershock sequence (ETAS) model, which forecast the location, time, and magnitude of all future earthquakes using the estimates of the background seismicity rate and the rates of future aftershocks of all generations. Using the Californian earthquake catalog, we formulate six controlled pseudo‐prospective experiments with different combinations of three target magnitude thresholds: 2.95, 3.95, or 4.95 and two forecasting time horizons: 1 or 5 years. In these experiments, we compare the performance of (1) the ETAS model with spatially homogenous parameters, or GETAS; (2) the ETAS model with spatially variable parameters, or SVETAS; (3) three declustering‐based SSMs; (4) a simple SSM based on undeclustered data, and (5) a model based on strain rate data, in forecasting the location and magnitude of all (undeclustered) target earthquakes during many testing periods. In all conducted experiments, the SVETAS model comes out with consistent superiority compared to all the competing models. Consistently better performance of the SVETAS model with respect to declustering‐based SSMs highlights the importance of forecasting the future aftershocks of all generations for developing better earthquake forecasting models. Among the two ETAS models themselves, accounting for the optimal spatial variation of the parameters leads to stronger improvements in forecasting performance.
Computational estimation of resolution in reconstruction techniques utilizing sparsity, total variation, and nonnegativity

Abstract. Techniques which exploit properties such as sparsity and total variation have provided the ability to reconstruct images that surpass the conventional limits of imaging. This leads to difficulties in assessing the result, as conventional metrics for resolution are no longer valid. We develop a numerical approach to evaluating the second-order statistics of the estimate by relating a confidence interval on the solution to a confidence interval on a pixel value, and from this we formulate an approach to estimating the spatial resolution. With this estimate, we can calculate the resolution at each point subject to chosen bounds on the desired precision and confidence. We demonstrate the method for limited-angle tomographic reconstructions utilizing nonnegativity, sparse regularization, total-variation minimization, and their combinations. This provides a means to visualize and understand the effect on the image inherent in these penalties and constraints. Examples are provided using simulated data for different methods, and the results are shown to agree with resolution calculated empirically via the local edge response.
Database Physical Structure Optimization Technology

In face of the growing data volume and search requests,to meet the efficiency of users’ search requests,the database cannot depend just on the SQL query optimization.Improvement must be made upon the physical structures of databases and the search efficiency from the origin.The paper describes four physical structures optimized by commercial databases,summarizes several key technologies in physical structure optimization sphere and introduces several recommendation tools for physical structure optimization now utilized in commercial database.The research directions are presented at last.
Structures of magnetized thin accretion disks

We investigate the magnetohydrodynamic (MHD) process in thin accretion disks. The relevant momentum as well as magnetic reduction equations in the thin disk approximation are included. On the basis of these equations, we examine numerically the stationary structures, including distributions of the surface mass density, temperature and flow velocities of a disk around a young stellar object (YSO). The numerical results are as follows: (i) There should be an upper limit to the magnitude of magnetic field, such an upper limit corresponds to the equipartition field. For relevant magnitude of magnetic field of the disk’s interior the disk remains approximately Keplerian. (ii) The distribution of effective temperature T(r) is a smoothly decreasing function of radius with power index γ -1/2, corresponding to the observed radiation flux density, provided that the magnetic field is suitably chosen.
Content-based medical image retrieval

At first,this paper introduces text retrieval that has some disadvantages in the medical application and the concept of medical image retrieval based on contents is here illustrated.Then,features of medical image are analyzed and the feature-extract methods are discussed.And then,the problems in the practical use of imagal retrieval based on contents are presented and the international research situations on medical imagal retrieval based on contents are ana-lyzed.Finally,the future development trends are previewed.
Evaluating Compact Routing Algorithms on Real-World Networks

Compact routing has shown promise for reducing the forwarding state in Internetlike graphs, without badly impacting traffic flows. This dissertation compares two such compact routing algorithms on real Internet snapshots from router data across 12 years. The results indicate that these algorithms behave consistently over time, and exhibit extremely small forwarding tables with very low path inflation.
Partial Connection Availability Modeling for Wireless Networks

In energy-constrained wireless networks,alternately sleeping is an effective way to reduce power consumption.However,this method may destroy the connectivity of network.Such a network is called the partially connected network.The numerical evaluation for the availability of partial connection is essential for wireless network running in periodically sleeping mode.In this paper,a computing model of partial connection availability based on alternate activity model is introduced.A node with packet to be send can hold the packet for certain period and resume packet forwarding when the sleeping next-hop node wakes up.Based on the Poisson process model and complete probability method,the formula of the partial connection availability is deduced.The formula can be very close to the actual capacity of the partially connected network in alternately sleeping mode.It is proved that compared with the full connection availability,within tolerable delay the partial connection availability is much higher.The theoretical criterion is provided in the process of deployment of energy-constrained wireless networks.Numerical analysis is conducted on the relationship among relevant network parameters and performance of networks such as packet delivery ratio and delay.Methods for setting the parameters are introduced.Simulation validates the methods and results.
Online media in a context of proximity in Galicia and Portugal and its presence on the social networks

The online media in a context of proximity has experimented in recent years a series of transformations towards new communicative and business models, due to the economic recession and the crisis of the newspapers' traditional model suffered by the media industry. In a global context of crisis in the traditional local media sector, readers express a growing necessity of information about the geographical areas nearest to them. This has favored the proliferation of a great diversity of new communicative spaces on the internet. The online media in a context of proximity tends to be web-native, cover hyperlocal areas and built community projects where citizen participation becomes especially relevant. This research focus on the study of the local and hyperlocal online media of Galicia and Portugal, on the basis of a media of proximity map in the Iberian space that is being developed. In this way, we compare two areas that, although pertaining to different countries, are very close about cultural issues. The main objective of the present study is to measure and check the presence of this type of media on the social networks, observing which are the most used platforms and the importance of the communities that are maintained by the media in those spaces. It is therefore an exploratory and very descriptive work that allows a first approximation to the social networks' functions in the creation of spaces for socialization, participation and debate between the citizens of the local communities.
Matching Bibliographic Data from Publication Lists with Large Databases Using N-Grams

This paper presents a text matching process for identification and correct assignment of scholarly publications, extracted from publication lists provided by authors or research institutes, in large bibliographic databases such as Thomson Reuters’ Web of Science (WoS). An identification method is implemented by means of overlapping common 3-grams and the results are obtained from the match of the two sources according to the highest score of the applied cosine measure. Levenshtein similarities based on N-grams have been used to measure the closeness between the given CV publication and the retrieved best possible WoS match as a complementary and confirmatory measure. It is shown that the suggested method has an important potential on reducing the manual effort to find out whether a desired publication is indexed in WoS or not. The similarity scores derived by Levenshtein measure show consistency with those derived from Salton’s similarity measure. Incorrect matches are examined in depth and possible thresholds are suggested to decrease the effort for manual cleaning.
Overview of Algorithms for Detecting Community Structure in Complex Networks

Community structure is a very important property of complex networks.Detecting communities in networks is of great importance in biology,computer science,sociology and so on.In recent years,a lot of community discovery algorithms have been proposed aiming at different kinds of large scale complex networks.In this paper,we review some latest representative algorithms,focusing on the improved methods based on the modularity function,the algorithms which can detect overlapping and hierarchical community structure in networks,and the benchmark in detecting communities.Finally,some future directions are pointed out.
Stabilities of asteroid orbits in resonances

A map of the asteroid motion is studied carefully. An exponential diffusion law in the chaotic sea and an algebraic law in the mixed region are observed. The effects of perturbations on diffusion are also discussed. The fixed points, their stabilities and the diffusion properties of the map give qualitative explanations of the distribution of asteroids, i.e. the depletion and accumulation of asteroids in the outer main belt, particularly in the first order mean motion resonances with Jupiter.
The Ultimate Resource 2

Thank you very much for reading the ultimate resource 2. As you may know, people have look numerous times for their favorite books like this the ultimate resource 2, but end up in harmful downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they cope with some malicious bugs inside their laptop. the ultimate resource 2 is available in our book collection an online access to it is set as public so you can download it instantly. Our books collection spans in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the the ultimate resource 2 is universally compatible with any devices to read.
Design of Single-Stage Flyback PFC Converter for LED Driver

A light emitting diode (LED) driver based on single-stage power factor correction (PFC) is presented in this paper. The designed LED driver using flyback topology can achieve power factor correction and constant-current drive LED in boundary conduction mode. The circuit principle is described in detail, the formulas for MOS switch-on time, switching frequency and the main impact factor of power factor are proposed. The experiment results show that the designed LED driver has high power factor, stable output and it can drive the LED with high efficiency.
Efficient Algorithm for Energy-Aware Virtual Network Embedding

Network virtualization is a promising approach for resource management that allows customized Virtual Networks (VNs) to be multiplexed on a shared physical infrastructure. A key function that network virtualization can provide is Virtual Network Embedding (VNE), which maps virtual networks requested by users to a shared substrate network maintained by an Internet service provider. Existing research has worked on this, but has primarily focused on maximizing the revenue of the Internet service provider. In this paper, we consider energy-aware virtual network embedding, which aims at minimizing the energy consumption for embedding virtual networks in a substrate network. In our optimization model, we consider energy consumption of both links and nodes. We propose an efficient heuristic to assign virtual nodes to appropriate substrate nodes based on priority, where existing activated nodes have higher priority for hosting newly arrived virtual nodes. In addition, our proposed algorithm can take advantage of activated links for embedding virtual links so as to minimize total energy consumption. The simulation results show that, for all the cases considered, our algorithm can improve upon previous work by an average of 12.6% on acceptance rate, while the consumed energy can be reduced by 12.34% on average.
Wireless Nurse Call System

This paper introduces a nurse call system using the wireless communication to resolve the portable problem of established nurse call system. The established nurse call system has a problem that it can not be used outside the sickroom because it uses a wire communication. The proposed nurse in this study call system is composed of a terminal for nurse, a terminal for patient and a server part. The efficacy of the proposed system is verified by means of experimental. Experimental results are presented to show the effectiveness.
Merging Two Steganography Techniques Adjusted to Improve Arabic Text Data Security

: Securing private texts to fully prevent any detection, is a technique called Steganography. This research work of Arabic text steganography focuses on improving the hiding secrets within Arabic language text utilizing the redundant extension “Kashida” letter as covering media. We propose modifying the “Kashida” stego-cover technique merging with a new way of embedding sensitive data within whitespaces. This modified merging was tested on hiding data within Arabic text of the last 30 Chapters of the Holy Quran (Sura Al-Buruj #85 to Sura An-Nas #114) comparing with both the normal method and the improved proposed one. The results demonstrated clear increase in the capacity as expected without degrading the security, which justifies this work for real promising research direction.
Eleven years of monitoring the Seyfert 1 Mrk 335 with Swift: Characterizing the X-ray and UV/optical variability

The narrow-line Seyfert 1 galaxy (NLS1) Mrk 335 has been continuously monitored with Swift since May 2007 when it fell into a long-lasting, X-ray low-flux interval. Results from the nearly 11 years of monitoring are presented here. Structure functions are used to measure the UV-optical and X-ray power spectra. The X-ray structure function measured between 10-100 days is consistent with the flat, low-frequency part of the power spectrum measured previously in Mrk 335. The UV-optical structure functions of Mrk 335 are comparable with those of other Seyfert 1 galaxies and of Mrk 335 itself when it was in a normal bright state. There is no indication that the current X-ray low-flux state is attributed to changes in the accretion disc structure of Mrk 335. The characteristic timescales measured in the structure functions can be attributed to thermal (for the UV) and dynamic (for the optical) timescales in a standard accretion disc. The high-quality UVW2 (~1800 A in the source frame) structure function appears to have two breaks and two different slopes between 10-160 days. Correlations between the X-ray and other bands are not highly significant when considering the entire 11-year light curves, but more significant behaviour is present when considering segments of the light curves. A correlation between the X-ray and UVW2 in 2014 (Year-8) may be predominately caused by an giant X-ray flare that was interpreted as jet-like emission. In 2008 (Year-2), possible lags between the UVW2 emission and other UV-optical waveband may be consistent with reprocessing of X-ray or UV emission in the accretion disc.
Power estimation for diverse field programmable gate array architectures

This thesis presents a new power model, which is capable of modelling the power usage of many different field-programmable gate array (FPGA) architectures. FPGA power models have been developed in the past; however, they were designed for a single, simple architecture, with known circuitry. This work explores a method for estimating power usage for many different user-created architectures. This requires a fundamentally new technique. Although the user specifies the functionality of the FPGA architecture, the physical circuitry is not specified. Central to this work is an algorithm which translates these functional descriptions into physical circuits. After this translation to circuit components, standard methods can be used to estimate power dissipation. In addition to enlarged architecture support, this model also provides support for modern FPGA features such as fracturable look-up tables and hard blocks. Compared to past models, this work provides substantially more detailed static power estimations, which is increasingly relevant as CMOS is scaled to smaller technologies. The model is designed to operate with modern CMOS technologies, and is validated against SPICE using 22 nm, 45 nm and 130 nm technologies.