A GENERALIZED BLOCK BOOTSTRAP FOR SEASONAL TIME SERIES

When time‐series data contain a periodic/seasonal component, the usual block bootstrap procedures are not directly applicable. We propose a modification of the block bootstrap – the generalized seasonal block bootstrap (GSBB) – and show its asymptotic consistency without undue restrictions on the relative size of the period and block size. Notably, it is exactly such restrictions that limit the applicability of other proposals of block bootstrap methods for time series with periodicities. The finite‐sample performance of the GSBB is also illustrated by means of a small simulation experiment.     

An online color naming experiment in Russian using Munsell color samples

Russian color naming was explored in a web‐based experiment. The purpose was 3‐fold: to examine (1) CIELAB coordinates of centroids for 12 Russian basic color terms (BCTs), including 2 Russian terms for “blue”, sinij “dark blue”, and goluboj “light blue”, and compare these with coordinates for the 11 English BCTs obtained in earlier studies; (2) frequent nonBCTs; and (3) gender differences in color naming. Native Russian speakers participated in the experiment using an unconstrained color‐naming method. Each participant named 20 colors, selected from 600 colors densely sampling the Munsell Color Solid. Color names and response times of typing onset were registered. Several deviations between centroids of the Russian and English BCTs were found. The 2 “Russian blues”, as expected, divided the BLUE area along the lightness dimension; their centroids deviated from a centroid of English blue. Further minor departures were found between centroids of Russian and English counterparts of “brown” and “red”. The Russian color inventory confirmed the linguistic refinement of the PURPLE area, with high frequencies of nonBCTs. In addition, Russian speakers revealed elaborated naming strategies and use of a rich inventory of nonBCTs. Elicitation frequencies of the 12 BCTs were comparable for both genders; however, linguistic segmentation of color space, employing a synthetic observer, revealed gender differences in naming colors, with more refined naming of the “warm” colors from females. We conclude that, along with universal perceptual factors, that govern categorical partition of color space, Russian speakers’ color naming reflects language‐specific factors, supporting the weak relativity hypothesis.     

Grammatical Evolution for Features of Epileptic Oscillations in Clinical Intracranial Electroencephalograms

This paper presents grammatical evolution (GE) as an approach to select and combine features for detecting epileptic oscillations within clinical intracranial electroencephalogram (iEEG) recordings of patients with epilepsy. Clinical iEEG is used in preoperative evaluations of a patient who may have surgery to treat epileptic seizures. Literature suggests that pathological oscillations may indicate the region(s) of brain that cause epileptic seizures, which could be surgically removed for therapy. If this presumption is true, then the effectiveness of surgical treatment could depend on the effectiveness in pinpointing critically diseased brain, which in turn depends on the most accurate detection of pathological oscillations. Moreover, the accuracy of detecting pathological oscillations depends greatly on the selected feature(s) that must objectively distinguish epileptic events from average activity, a task that visual review is inevitably too subjective and insufficient to resolve. Consequently, this work suggests an automated algorithm that incorporates grammatical evolution (GE) to construct the most sufficient feature(s) to detect epileptic oscillations within the iEEG of a patient. We estimate the performance of GE relative to three alternative methods of selecting or combining features that distinguish an epileptic gamma (~65-95 Hz) oscillation from normal activity: forward sequential feature-selection, backward sequential feature-selection, and genetic programming. We demonstrate that a detector with a grammatically evolved feature exhibits a sensitivity and selectivity that is comparable to a previous detector with a genetically programmed feature, making GE a useful alternative to designing detectors.     

Industrial growth, economic integration and structural change: evidence from the EU new member-states regions

The article evaluates the pre-accession experience of new European Union member-states, coming from the former Eastern bloc, estimating an empirical model used to account for regional–industrial employment growth in the early transition period, 1991–2000. The results obtained indicate the adverse impact of the economic integration dynamics and detect the interplay among structural characteristics and geographical coordinates that determines the relative winners. The findings of the article have important implications for both theory and policy.     

Human Motion Planning Based on Recursive Dynamics and Optimal Control Techniques

This paper presents an efficient optimal control and recursive dynamics-based computer animation system for simulating and controlling themotion of articulated figures. A quasi-Newton nonlinear programmingtechnique (super-linear convergence) is implemented to solve minimumtorque-based human motion-planning problems. The explicit analyticalgradients needed in the dynamics are derived using a matrix exponentialformulation and Lie algebra. Cubic spline functions are used to make thesearch space for an optimal solution finite. Based on our formulations,our method is well conditioned and robust, in addition to beingcomputationally efficient. To better illustrate the efficiency of ourmethod, we present results of natural looking and physically correcthuman motions for a variety of human motion tasks involving open andclosed loop kinematic chains.     

Aerosol lidar intercomparison in the framework of the EARLINET project. 1. Instruments

In the framework of the European Aerosol Research Lidar Network to Establish an Aerosol Climatology (EARLINET), 19 aerosol lidar systems from 11 European countries were compared. Aerosol extinction or backscatter coefficient profiles were measured by at least two systems for each comparison. Aerosol extinction coefficients were derived from Raman lidar measurements in the UV (351 or 355 nm), and aerosol backscatter profiles were calculated from pure elastic backscatter measurements at 351 or 355, 532, or 1064 nm. The results were compared for height ranges with high and low aerosol content. Some systems were additionally compared with sunphotometers and starphotometers. Predefined maximum deviations were used for quality control of the results. Lidar systems with results outside those limits could not meet the quality assurance criterion. The algorithms for deriving aerosol backscatter profiles from elastic lidar measurements were tested separately, and the results are described in Part 2 of this series of papers [Appl. Opt. 43, 977-989 (2004)]. In the end, all systems were quality assured, although some had to be modified to improve their performance. Typical deviations between aerosol backscatter profiles were 10% in the planetary boundary layer and 0.1 x 10(-6) m(-1) sr(-1) in the free troposphere.     

Combining low-, high-level and empirical domain knowledge for automated segmentation of ultrasonic breast lesions

Breast cancer is the most frequently diagnosed malignancy and the second leading cause of mortality in women. In the last decade, ultrasound along with digital mammography has come to be regarded as the gold standard for breast cancer diagnosis. Automatically detecting tumors and extracting lesion boundaries in ultrasound images is difficult due to their specular nature and the variance in shape and appearance of sonographic lesions. Past work on automated ultrasonic breast lesion segmentation has not addressed important issues such as shadowing artifacts or dealing with similar tumor like structures in the sonogram. Algorithms that claim to automatically classify ultrasonic breast lesions, rely on manual delineation of the tumor boundaries. In this paper, we present a novel technique to automatically find lesion margins in ultrasound images, by combining intensity and texture with empirical domain specific knowledge along with directional gradient and a deformable shape-based model. The images are first filtered to remove speckle noise and then contrast enhanced to emphasize the tumor regions. For the first time, a mathematical formulation of the empirical rules used by radiologists in detecting ultrasonic breast lesions, popularly known as the "Stavros Criteria" is presented in this paper. We have applied this formulation to automatically determine a seed point within the image. Probabilistic classification of image pixels based on intensity and texture is followed by region growing using the automatically determined seed point to obtain an initial segmentation of the lesion. Boundary points are found on the directional gradient of the image. Outliers are removed by a process of recursive refinement. These boundary points are then supplied as an initial estimate to a deformable model. Incorporating empirical domain specific knowledge along with low and high-level knowledge makes it possible to avoid shadowing artifacts and lowers the chance of confusing similar tumor like structures for the lesion. The system was validated on a database of breast sonograms for 42 patients. The average mean boundary error between manual and automated segmentation was 6.6 pixels and the normalized true positive area overlap was 75.1%. The algorithm was found to be robust to 1) variations in system parameters, 2) number of training samples used, and 3) the position of the seed point within the tumor. Running time for segmenting a single sonogram was 18 s on a 1.8-GHz Pentium machine.     

Amplitude Variability in Simulated Incoherent Seismic Ground Motions

This note compares in detail four commonly used schemes for the simulation of spatially variable ground motions. Emphasis is placed not only on the conformity of the simulations with the power and cross spectral density of the random field but, also, on the examination of the consistency of the simulations with the homogeneity condition, and the (Fourier) amplitude variability of the simulations. It is shown that, whereas three techniques that simulate ground motions in parallel satisfy the homogeneity requirement, produce simulations with random amplitudes, and amplitude and phase variability consistent with that of recorded data, one technique that simulates motions in sequence does not.     

Development of NiO-based thin film structures as efficient H2 gas sensors operating at room temperatures

P-type NiO thin films have been developed on high resistivity Si and SiO₂ substrates by a pulsed laser deposition technique using an ArF^? 193 nm excimer laser at deposition temperature of 300 °C and in 40 Pa partial oxygen pressure. Structures based on such NiO films as host material in the form of Au-NiO Schottky diodes have been subsequently developed under vacuum. In a different procedure, an n-SnO₂ layer has been deposited by a CVD technique on a NiO film to produce a p/n heterojunction. The sensing properties of all above structures have been tested upon exposure to a H₂ flow in air ambient gas at various operating temperature ranging from 30 to 180 °C. For the NiO films, the optimum temperature was about 150 °C exhibiting a sensitivity of 94%. After surface sensitization of NiO by Au the NiO films showed an H₂ response at operating temperature of 30 °C. The sensitivity of p-NiO/n-SnO₂ heterojunction devices was extracted from I-V measurements in air and under H₂ flow mixed in air. In this case a dramatic increase of the sensitivity was achieved at operating temperature of 30 °C for a forward bias of 0,2 V.     

Detecting unauthorized and compromised nodes in mobile ad hoc networks

Security of mobile ad hoc networks (MANET) has become a more sophisticated problem than security in other networks, due to the open nature and the lack of infrastructure of such networks. In this paper, the security challenges in intrusion detection and authentication are identified and the different types of attacks are discussed. We propose a two-phase detection procedure of nodes that are not authorized for specific services and nodes that have been compromised during their operation in MANET. The detection framework is enabled with the main operations of ad hoc networking, which are found at the link and network layers. The proposed framework is based on zero knowledge techniques, which are presented through proofs.