"The extremal index parameter theta characterizes the degree of local dependence in the extremes of a stationary time series and has important applications in a number of areas, such as hydrology, telecommunications, finance and environmental studies.…Further, a procedure for the automatic selection of its tuning parameter is developed and different types of confidence intervals that prove useful in practice proposed. The performance of the estimator is examined through simulations, which show its highly competitive behavior. Finally, the estimator is applied to three real data sets of daily crude oil prices, daily returns of the S&P 500 stock index, and high-frequency, intra-day traded volumes of a stock. These applications demonstrate additional diagnostic features of statistical plots based on the new estimator."

"I am listening to a presentation at the Homer Hoyt meetings on the condo meltdown in South Florida. Developers planned on building 95,000 units in the city of Miami between 2002 and 2007. In the 2000 census, the whole city had 163,000 units."

"Research into properties of heterogeneous artificial materials, consisting of arrangements of rigid scatterers embedded in a medium with different elastic properties, has been intense throughout last two decades. The capability to prevent the transmission of waves in predetermined bands of frequencies -called bandgaps- becomes one of the most interesting properties of these systems, and leads to the possibility of designing devices to control wave propagation. The underlying physical mechanism is destructive Bragg interference. Here we show a technique that enables the creation of a wide bandgap in these materials, based on fractal geometries. We have focused our work in the acoustic case where these materials are called Phononic/Sonic Crystals (SC) but, the technique could be applied any types of crystals and wave types in ranges of frequencies where the physics of the process is linear."

"The optimization formulation considered in this paper uses a penalized negative Poisson log-likelihood objective function with nonnegativity constraints (since Poisson intensities are naturally nonnegative). In particular, the proposed approach incorporates key ideas of using separable quadratic approximations to the objective function at each iteration and penalization terms related to l1 norms of coefficient vectors, total variation seminorms, and partition-based multiscale estimation methods."

"The obtained results and trends suggest a number of further investigations. For instance, it would be interest- ing to consider other network models and measurements, as well as to assess the effect of different types of hard- ware, compilers and operating systems."

"Random numbers play a crucial role in science and industry. Many numerical methods require the use of random numbers, in particular the Monte Carlo method. Therefore it is of paramount importance to have efficient random number generators. The differences, advantages and disadvantages of true and pseudo random number generators are discussed with an emphasis on the intrinsic details of modern and fast pseudo random number generators. Furthermore, standard tests to verify the quality of the random numbers produced by a given generator are outlined. Finally, standard scientific libraries with built-in generators are presented, as well as different approaches to generate nonuniform random numbers. Potential problems that one might encounter when using large parallel machines are discussed."

"In many networks, vertices have hidden attributes, or types, that are correlated with the networks topology. If the topology is known but these attributes are not, and if learning the attributes is costly, we need a method for choosing which vertex to query in order to learn as much as possible about the attributes of the other vertices. We assume the network is generated by a stochastic block model, but we make no assumptions about its assortativity or disassortativity. We choose which vertex to query using two methods: 1) maximizing the mutual information between its attributes and those of the others (a well-known approach in active learning) and 2) maximizing the average agreement between two independent samples of the conditional Gibbs distribution. Experimental results show that both these methods do much better than simple heuristics. They also consistently identify certain vertices as important by querying them early on."

"We propose a fluctuation analysis to quantify spatial correlations in complex networks. The approach considers the sequences of degrees along shortest paths in the networks and quantifies the fluctuations in analogy to time series. In this work, the Barabasi-Albert (BA) model, the Cayley tree at the percolation transition, a fractal network model, and examples of real-world networks are studied. While the fluctuation functions for the BA model show exponential decay, in the case of the Cayley tree and the fractal network model the fluctuation functions display a power-law behavior. The fractal network model comprises long-range anti-correlations. The results suggest that the fluctuation exponent provides complementary information to the fractal dimension."

"Wealth is no proof of moral character; nor poverty of the want of it.

On the contrary, wealth is often the presumptive evidence of dishonesty; and poverty the negative evidence of innocence. If therefore property, whether little or much, be made a criterion, the means by which that property has been acquired ought to be made a criterion also."

"This means that each time the document is updated, the client will also store the previous version as an attachment to the latest version. At any time, a user can load any of the old versions."

"Community structure is one of the key properties of complex networks and plays a crucial role in their topology and function. While an impressive amount of work has been done on the issue of community detection, very little attention has been so far devoted to the investigation of communities in real networks. We present a systematic empirical analysis of the statistical properties of communities in large information, communication, technological, biological, and social networks. We find that the mesoscopic organization of networks of the same category is remarkably similar. This is reflected in several characteristics of community structure, which can be used as “fingerprints'' of specific network categories.…"

"… We find that SF networks generate oscillations much more easily than ER networks do, and this may explain why SF networks are more evolvable than ER networks are for oscillatory phenotypes. In spite of their greater evolvability, we find that networks with SFout topologies are also more robust to mutations than ER networks. Furthermore, the SFout topologies are more robust to changes in initial conditions (environmental robustness). For both topologies, we find that once a population of networks has reached the target state, further neutral evolution can lead to an increase in both the mutational robustness and the environmental robustness to changes in initial conditions."

"The Prediction API allows you to get more from your data and makes its patterns more accessible. Specifically, the Prediction API leverages Google's machine learning infrastructure to give you the tools to better analyze your data and reveal patterns that are often difficult to manually discover. The API also enables you to use those patterns to predict new outcomes, which facilitates the development of all types of software, from textual analysis systems to recommendation systems. Because the Prediction API is a RESTful HTTP service, you can easily access it from Google App Engine, Apps Script, and other Internet-connected desktop applications."

"Heterogeneity in the degree distribution is known to suppress global synchronization in complex networks of symmetrically coupled oscillators. Scale-free networks present strong heterogeneity, there are a few highly connected nodes, termed hubs, while the majority of nodes has only a few connections. We show that a stable partially synchronized state may take place in scale-free networks: hubs undergo a transition to synchronization while the remaining nodes are unsynchronized. This phenomenon may occur in any large heterogeneous network, regardless of the network global synchronization properties. We provide theory and numerical evidence to establish this phenomenon."

"… In this paper we present BRACE (Big Red Agent-based Computation Engine), which extends the MapReduce framework to process these simulations efficiently across a cluster. We can leverage spatial locality to treat behavioral simulations as iterated spatial joins and greatly reduce the communication between nodes. In our experiments we achieve nearly linear scale-up on several realistic simulations.…"

"A wide family of nonlinear sequence generators, the so-called clock-controlled shrinking generators, has been analyzed and identified with a subset of linear cellular automata. The algorithm that converts the given generator into a linear model based on automata is very simple and can be applied in a range of practical interest. Due to the linearity of these automata as well as the characteristics of this class of generators, a cryptanalytic approach can be proposed. Linear cellular structures easily model keystream generators with application in stream cipher cryptography."

"Connections in complex networks are inherently fluctuating over time and exhibit more dimensionality than analysis based on standard static graph measures can capture. Here, we introduce the concepts of temporal paths and distance in time-varying graphs. We define as temporal small world a time-varying graph in which the links are highly clustered in time, yet the nodes are at small average temporal distances. We explore the small-world behavior in synthetic time-varying networks of mobile agents, and in real social and biological time-varying systems."

"The inverse Ising problem is a difficult combinatorial optimization problem in the class known as “NP-hard”. In theory, only approximate schemes, or methods that take more than polynomial time to find the answer are possible. Boltzmann Learning [1] is an iterative method where in one step the correlation functions are computed given an Ising model, and in another step the Ising model couplings are modified to adjust to data. In principle, Boltzmann learning can be employed to find the couplings with arbi- trary accuracy given accurate data and sufficient time, but the slow convergence of the Boltzmann learning makes it a very inefficient algorithm for most practical purposes."

"Approximate dynamic programming has been used successfully in a large variety of domains, but it relies on a small set of provided approximation features to calculate solutions reliably. Large and rich sets of features can cause existing algorithms to overfit because of a limited number of samples. We address this shortcoming using $L_1$ regularization in approximate linear programming. Because the proposed method can automatically select the appropriate richness of features, its performance does not degrade with an increasing number of features. These results rely on new and stronger sampling bounds for regularized approximate linear programs. We also propose a computationally efficient homotopy method. The empirical evaluation of the approach shows that the proposed method performs well on simple MDPs and standard benchmark problems."

"There seems to be a brief recognition period for Bdellovibrio to identify its prey after a collision with another cell (Shilo, 1969). Initially, the attachment to a cell surface is reversible. Bdellovibrio is still able to swim away a few seconds after recognizing that the cell is not a right target (gram- positive bacteria). When a gram-negative bacterium is encountered, Bdellovibrio cell becomes committed to invasion. The whole process usually takes around 5 – 10 minutes. Bdellovibrio drops its flagellum. It has been hypothesized that Bdellovibrio may adhere to the cell surface using pilus-like fibre structure expressed on its penetration pole."

"Small world networks interpolate between fully regular and fully random topologies and simultaneously exhibit large local clustering as well as short average path length. Small world topology has therefore been suggested to support network synchronization. Here we study the asymptotic speed of synchronization of coupled oscillators in dependence on the degree of randomness of their interaction topology in generalized Watts-Strogatz ensembles. We find that networks with fixed in-degree synchronize faster the more random they are, with small worlds just appearing as an intermediate case. For any generic network ensemble, if synchronization speed is at all extremal at intermediate randomness, it is slowest in the small world regime. This phenomenon occurs for various types of oscillators, intrinsic dynamics and coupling schemes."

"Empirical studies show that real world networks often exhibit multiple scales of topological descriptions. However, it is still an open problem how to identify the intrinsic multiple scales of networks. In this article, we consider detecting the multi-scale community structure of networks from the perspective of dimension reduction. …Theoretical analysis indicates that all these three transformations are crucial to identify the multi-scale community structure of networks. Extensive tests on real world and artificial networks demonstrate that the correlation matrix significantly outperforms the modularity matrix as regards identifying the multi-scale community structure of networks."

"Now, to return to the news article. If the eigenvalue distribution is an attractor, this means that a lot of physical and social phenomena which can be modeled by eigenvalues (including, apparently, quantum energy levels and some properties of statistical tests) might have a common structure. Just as, at a similar level, we see the normal distribution and related functions in all sorts of unusual places."

"…Through several nu- merical experiments, we demonstrate that both matrix- and tensor-based techniques are effective for temporal link prediction despite the inherent difficulty of the problem. Additionally, we show that tensor-based techniques are particularly effective for temporal data with varying periodic patterns."

"I envision a future in which programmers are the conscious repositories of a body of knowledge. A future in which they regain their craft, instead of tweaking frameworks they don't understand. A future, eventually, in which programmers say "no" to demands at odds with their ethics.

It is crucial to create ways, spaces and formats for programmers to share their knowledge with other programmers. It is vital we keep this knowledge (especially verbalized knowledge) among programmers and out of salespeople's hands. And it is urgent the IT crowd recognize software making as a craft, instead of a commodity."

"We consider scheduling weighted packets in a capacity-bounded buffer. In this model, there is a buffer with a limited capacity B such that at any time, the buffer cannot accommodate more than B packets. Packets arrive over time. Each packet has a non-negative real value. Packets do not expire and they leave the buffer only because either we send them or we drop them. The packets that have left the buffer will not be reconsidered for delivery any more. In each time step, at most one packet in the buffer can be sent. The order in which the packets are sent should comply with the order of their arriving time. The objective is to maximize the total value of the packets sent in an online manner.…"

"Each combination of values was then fed into a simulator to give an idea of the grid's performance and its expected lifetime. If the performance was promising, the "genetic material" was subjected to further random changes, or mutation, and this process was repeated until no more improvements were forthcoming.

After 100 generations, the GA spawned a geometry/voltage set that boosted the ion engine grid's lifetime to 5.1 years – at least in the simulator (Journal of Propulsion and Power, DOI: 10.2514/1.44358). Factors optimised included grid hole diameter, hole spacing and the thickness of the grids. The engine could be improved further, says Farnell, by evolving the other parts too.…"

"Results on a commodities basket"

"In this paper we consider spatial networks that realize a balance between an infrastructure cost (the cost of wire needed to connect the network in space) and communication efficiency, measured by average shortest pathlength. A global optimization procedure yields network topologies in which this balance is optimized. These are compared with network topologies generated by a competitive process in which each node strives to optimize its own cost-communication balance. Three phases are observed in globally optimal configurations for different cost-communication trade-offs: (i) regular small worlds, (ii) star-like networks and (iii) trees with a centre of interconnected hubs. In the latter regime, i.e. for very expensive wire, power laws in the link length distributions $P(w)\propto w^{-\alpha}$ are found, which can be explained by a hierarchical organization of the networks…"

"We present a near-linear time algorithm that approximates the edit distance between two strings within a polylogarithmic factor; specifically, for strings of length n and every fixed epsilon>0, it can compute a (log n)^O(1/epsilon) approximation in n^(1+epsilon) time. This is an exponential improvement over the previously known factor, 2^(O (sqrt(log n))), with a comparable running time (Ostrovsky and Rabani J.ACM 2007; Andoni and Onak STOC 2009). Previously, no efficient polylogarithmic approximation algorithm was known for any computational task involving edit distance (e.g., nearest neighbor search or sketching). "

"In many dynamical systems there is a large separation of time scales between typical events and "rare" events which can be the cases of interest. Rare-event rates are quite difficult to compute numerically, but they are of considerable practical importance in many fields: for example transition times in chemical physics and extinction times in epidemiology can be very long, but are quite important. We present a very fast numerical technique that can be used to find long transition times (very small rates) in low-dimensional systems, even if they lack detailed balance. We illustrate the method for a bistable non-equilibrium system introduced by Maier and Stein and a two-dimensional (in parameter space) epidemiology model."

"Image Effects With Cellular Automata (PDF) Abstract:This paper presents some techniques for creating various artistic effects on digital photography using the concept of cellular automata. All examples in this paper are created by “Image Infector” program, which is a plugin for Pixopedia 24 image editor and painter (www.sigmapi-design.com)."

"I'll start by highlighting that while all the software in this post is indeed free (true to FOSS), an account with Interactive Brokers is needed to make use of it. For those not familiar with IB, they offer a trading platform that excels on numerous fronts but is most appealing to those of us who trade algorithmically. IB makes available a rather comprehensive API that makes data access and trade execution entirely possible programmatically via a handful of "supported" languages. These include Java (the language of the platform), C#, VBA and even Excel. The also have a POSIX compliant C++ version for those who enjoy C++ but dislike Windows.

For those who dislike Windows and C++, the community of IB users have a few "non-official" options. They include some nice implementations in C, Python (2), Matlab, and something even more abstracted in the trading-shim. While all well and good, there was one missing: R.…"

"This paper aims at generating a new face based on the human like description using a new concept. The FASY (FAce SYnthesis) System is a Face Database Retrieval and new Face generation System that is under development. One of its main features is the generation of the requested face when it is not found in the existing database, which allows a continuous growing of the database also."

"The performance assessment of algorithms for multiobjective optimization problems is far from being a trivial issue. Recent results indicate that unary performance measures, i.e. performance measures which assign a single value to each non-dominated point set, are inherently limited in their inferential power. Despite these limitations, the hypervolume indicator (also known as Lebesgue measure or S metric) is still considered to possess some reasonable properties, having also been proposed as a guidance criterion for accepting solutions in Multiobjective Evolutionary Algorithms. Therefore, the computational time taken for computing the hypervolume indicator is a crucial factor for the performance of such algorithms.…"

"Unfortunately, our political leaders don't give a damn about mundane issues such as unemployment and economic growth. It is far easier for them to bandy about silly cliches about fiscal responsibility and generational equity, even though the policies they are pushing are 180 degrees at odds with anything that will help our children or grandchildren. Their main concern is pushing policies that keep the financial industry happy. And 10 million unemployed never bothered anyone at Goldman Sachs, just as Fabulous Fabio."

"We believe that our result could shed the light on the relation between the distribution of motifs and the struc- ture of the adjacency matrix of a hierarchical network. However to make this relation more profound the “in- verse” problem should be considered as well. Namely, it would be desirable to check if the stable distribution of motifs is uniquely related to any kind of hierarchical organization of the network."