pinecone/core-2020-05-10-deduplication huggingface dataset:
Concise computer mathematics: tutorials on theory and problems

Adapted from a modular undergraduate course on computational mathematics, Concise Computer Mathematics delivers an easily accessible, self-contained introduction to the basic notions of mathematics necessary for a computer science degree. The text reflects the need to quickly introduce students from a variety of educational backgrounds to a number of essential mathematical concepts. The material is divided into four units: discrete mathematics (sets, relations, functions), logic (Boolean types, truth tables, proofs), linear algebra (vectors, matrices and graphics), and special topics (graph theory, number theory, basic elements of calculus). The chapters contain a brief theoretical presentation of the topic, followed by a selection of problems (which are direct applications of the theory) and additional supplementary problems (which may require a bit more work). Each chapter ends with answers or worked solutions for all of the problems
Branching for general relativists

The chapter develops a theory of branching spatiotemporal histories that\ud
accommodates indeterminism and the insights of general relativity. A model of this\ud
theory can be viewed as a collection of overlapping histories, where histories are\ud
defined as maximal consistent subsets of the model’s base set. Subsequently, generalized\ud
(non-Hausdorff) manifolds are constructed on the theory’s models, and the\ud
manifold topology is introduced. The set of histories in a model turns out to be\ud
identical with the set of maximal subsets of the model’s base set with respect to\ud
being Hausdorff and downward closed (in the manifold topology). Further postulates\ud
ensure that the topology is connected, locally Euclidean, and satisfies the countable\ud
sub-cover condition
Multiple Moving Object Recognitions in video based on Log Gabor-PCA
  Approach

Object recognition in the video sequence or images is one of the sub-field of
computer vision. Moving object recognition from a video sequence is an
appealing topic with applications in various areas such as airport safety,
intrusion surveillance, video monitoring, intelligent highway, etc. Moving
object recognition is the most challenging task in intelligent video
surveillance system. In this regard, many techniques have been proposed based
on different methods. Despite of its importance, moving object recognition in
complex environments is still far from being completely solved for low
resolution videos, foggy videos, and also dim video sequences. All in all,
these make it necessary to develop exceedingly robust techniques. This paper
introduces multiple moving object recognition in the video sequence based on
LoG Gabor-PCA approach and Angle based distance Similarity measures techniques
used to recognize the object as a human, vehicle etc. Number of experiments are
conducted for indoor and outdoor video sequences of standard datasets and also
our own collection of video sequences comprising of partial night vision video
sequences. Experimental results show that our proposed approach achieves an
excellent recognition rate. Results obtained are satisfactory and competent.Comment: 8,26,conferenc
Natural Color Image Enhancement based on Modified Multiscale Retinex
  Algorithm and Performance Evaluation usingWavelet Energy

This paper presents a new color image enhancement technique based on modified
MultiScale Retinex(MSR) algorithm and visual quality of the enhanced images are
evaluated using a new metric, namely, wavelet energy. The color image
enhancement is achieved by down sampling the value component of HSV color space
converted image into three scales (normal, medium and fine) following the
contrast stretching operation. These down sampled value components are enhanced
using the MSR algorithm. The value component is reconstructed by averaging each
pixels of the lower scale image with that of the upper scale image subsequent
to up sampling the lower scale image. This process replaces dark pixel by the
average pixels of both the lower scale and upper scale, while retaining the
bright pixels. The quality of the reconstructed images in the proposed method
is found to be good and far better then the other researchers method. The
performance of the proposed scheme is evaluated using new wavelet domain based
assessment criterion, referred as wavelet energy. This scheme computes the
energy of both original and enhanced image in wavelet domain. The number of
edge details as well as wavelet energy is less in a poor quality image compared
with naturally enhanced image. Experimental results presented confirms that the
proposed wavelet energy based color image quality assessment technique
efficiently characterizes both the local and global details of enhanced image.Comment: 10 pages, 3 figures, Recent Advances in Intelligent Informatics
  Advances in Intelligent Systems and Computing Volume 235, 2014, pp 83-9
Stability of mode-locked kinks in the ac driven and damped sine-Gordon
  lattice

Kink dynamics in the underdamped and strongly discrete sine-Gordon lattice
that is driven by the oscillating force is studied. The investigation is
focused mostly on the properties of the mode-locked states in the {\it
overband} case, when the driving frequency lies above the linear band. With the
help of Floquet theory it is demonstrated that the destabilizing of the
mode-locked state happens either through the Hopf bifurcation or through the
tangential bifurcation. It is also observed that in the overband case the
standing mode-locked kink state maintains its stability for the bias amplitudes
that are by the order of magnitude larger than the amplitudes in the
low-frequency case.Comment: To appear in Springer Series on Wave Phenomena, special volume
  devoted to the LENCOS'12 conference; 6 figure
Theory of a quodon gas. With application to precipitation kinetics in
  solids under irradiation

Rate theory of the radiation-induced precipitation in solids is modified with
account of non-equilibrium fluctuations driven by the gas of lattice solitons
(a.k.a. quodons) produced by irradiation. According to quantitative
estimations, a steady-state density of the quodon gas under sufficiently
intense irradiation can be as high as the density of phonon gas. The quodon gas
may be a powerful driver of the chemical reaction rates under irradiation, the
strength of which exponentially increases with irradiation flux and may be
comparable with strength of the phonon gas that exponentially increases with
temperature. The modified rate theory is applied to modelling of copper
precipitation in FeCu binary alloys under electron irradiation. In contrast to
the classical rate theory, which disagrees strongly with experimental data on
all precipitation parameters, the modified rate theory describes quite well
both the evolution of precipitates and the matrix concentration of copper
measured by different methodsComment: V. Dubinko, R. Shapovalov, Theory of a quodon gas. With application
  to precipitation kinetics in solids under irradiation. (Springer
  International Publishing, Switzerland, 2014
Checking the validity of truncating the cumulant hierarchy description
  of a small system

We analyze the behavior of the first few cumulant in an array with a small
number of coupled identical particles. Desai and Zwanzig (J. Stat. Phys., {\bf
19}, 1 (1978), p. 1) studied noisy arrays of nonlinear units with global
coupling and derived an infinite hierarchy of differential equations for the
cumulant moments. They focused on the behavior of infinite size systems using a
strategy based on truncating the hierarchy. In this work we explore the
reliability of such an approach to describe systems with a small number of
elements. We carry out an extensive numerical analysis of the truncated
hierarchy as well as numerical simulations of the full set of Langevin
equations governing the dynamics. We find that the results provided by the
truncated hierarchy for finite systems are at variance with those of the
Langevin simulations for large regions of parameter space. The truncation of
the hierarchy leads to a dependence on initial conditions and to the
coexistence of states which are not consistent with the theoretical
expectations based on the multidimensional linear Fokker-Planck equation for
finite arrays
Finding new signature effects on galactic dynamics to constrain
  Bose-Einstein-condensed cold dark matter

If cosmological cold dark matter (CDM) consists of light enough bosonic
particles that their phase-space density exceeds unity, they will comprise a
Bose-Einstein condensate (BEC). The nature of this BEC-CDM as a quantum fluid
may then distinguish it dynamically from the standard form of CDM involving a
collisionless gas of non-relativistic particles that interact purely
gravitationally. We summarize some of the dynamical properties of BEC-CDM that
may lead to observable signatures in galactic halos and present some of the
bounds on particle mass and self-interaction coupling strength that result from
a comparison with observed galaxies.Comment: 10 pages, 5 figures; Minor corrections to reflect the published
  versio
Inhomogeneous and interacting vacuum energy

Vacuum energy is a simple model for dark energy driving an accelerated
expansion of the universe. If the vacuum energy is inhomogeneous in spacetime
then it must be interacting. We present the general equations for a
spacetime-dependent vacuum energy in cosmology, including inhomogeneous
perturbations. We show how any dark energy cosmology can be described by an
interacting vacuum+matter. Different models for the interaction can lead to
different behaviour (e.g., sound speed for dark energy perturbations) and hence
could be distinguished by cosmological observations. As an example we present
the cosmic microwave microwave background anisotropies and the matter power
spectrum for two different versions of a generalised Chaplygin gas cosmology.Comment: 10 pages, 5 figures; to appear in the proceedings of IV International
  Meeting on Gravitation and Cosmology, Guadalajara, May 201
Gravitational anomalies signaling the breakdown of classical gravity

Recent observations for three types of astrophysical systems severely
challenge the GR plus dark matter scenario, showing a phenomenology which is
what modified gravity theories predict. Stellar kinematics in the outskirts of
globular clusters show the appearance of MOND type dynamics on crossing the
$a_{0}$ threshold. Analysis shows a ``Tully-Fisher'' relation in these systems,
a scaling of dispersion velocities with the fourth root of their masses.
Secondly, an anomaly has been found at the unexpected scales of wide binaries
in the solar neighbourhood. Binary orbital velocities cease to fall along
Keplerian expectations, and settle at a constant value, exactly on crossing the
$a_{0}$ threshold. Finally, the inferred infall velocity of the bullet cluster
is inconsistent with the standard cosmological scenario, where much smaller
limit encounter velocities appear. This stems from the escape velocity limit
present in standard gravity; the ``bullet'' should not hit the ``target'' at
more than the escape velocity of the joint system, as it very clearly did.
These results are consistent with extended gravity, but would require rather
contrived explanations under GR, each. Thus, observations now put us in a
situation where modifications to gravity at low acceleration scales cease to be
a matter of choice, to now become inevitable.Comment: 10 pages, 5 figures, Astrophysics and Space Science Proceedings 38,
  4
PARP1 gene variation and microglial activity on [11C]PBR28 PET in older adults at risk for Alzheimer's disease

Increasing evidence suggests that inflammation is one pathophysio-logical mechanism in Alzheimer's disease (AD). Recent studies have identified an association between the poly (ADP-ribose) polymerase 1 (PARP1) gene and AD. This gene encodes a protein that is involved in many biological functions, including DNA repair and chromatin remodeling, and is a mediator of inflammation. Therefore, we performed a targeted genetic association analysis to investigate the relationship between the PARP1 polymorphisms and brain micro-glial activity as indexed by [11C]PBR28 positron emission tomography (PET). Participants were 26 non-Hispanic Caucasians in the Indiana Memory and Aging Study (IMAS). PET data were intensity-normalized by injected dose/total body weight. Average PBR standardized uptake values (SUV) from 6 bilateral regions of interest (thalamus, frontal, parietal, temporal, and cingulate cortices, and whole brain gray matter) were used as endophenotypes. Single nucleotide polymorphisms (SNPs) with 20% minor allele frequency that were within +/− 20 kb of the PARP1 gene were included in the analyses. Gene-level association analyses were performed using a dominant genetic model with translocator protein (18-kDa) (TSPO) genotype, age at PET scan, and gender as covariates. Analyses were performed with and without APOE ε4 status as a covariate. Associations with PBR SUVs from thalamus and cingulate were significant at corrected p<0.014 and <0.065, respectively. Subsequent multi-marker analysis with cingulate PBR SUV showed that individuals with the “C” allele at rs6677172 and “A” allele at rs61835377 had higher PBR SUV than individuals without these alleles (corrected P<0.03), and individuals with the “G” allele at rs6677172 and “G” allele at rs61835377 displayed the opposite trend (corrected P<0.065). A previous study with the same cohort showed an inverse relationship between PBR SUV and brain atrophy at a follow-up visit, suggesting possible protective effect of microglial activity against cortical atrophy. Interestingly, all 6 AD and 2 of 3 LMCI participants in the current analysis had one or more copies of the “GG” allele combination, associated with lower cingulate PBR SUV, suggesting that this gene variant warrants further investigation
A graph-based integration of multimodal brain imaging data for the detection of early mild cognitive impairment (E-MCI)

Alzheimer's disease (AD) is the most common cause of dementia in older adults. By the time an individual has been diagnosed with AD, it may be too late for potential disease modifying therapy to strongly influence outcome. Therefore, it is critical to develop better diagnostic tools that can recognize AD at early symptomatic and especially pre-symptomatic stages. Mild cognitive impairment (MCI), introduced to describe a prodromal stage of AD, is presently classified into early and late stages (E-MCI, L-MCI) based on severity. Using a graph-based semi-supervised learning (SSL) method to integrate multimodal brain imaging data and select valid imaging-based predictors for optimizing prediction accuracy, we developed a model to differentiate E-MCI from healthy controls (HC) for early detection of AD. Multimodal brain imaging scans (MRI and PET) of 174 E-MCI and 98 HC participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort were used in this analysis. Mean targeted region-of-interest (ROI) values extracted from structural MRI (voxel-based morphometry (VBM) and FreeSurfer V5) and PET (FDG and Florbetapir) scans were used as features. Our results show that the graph-based SSL classifiers outperformed support vector machines for this task and the best performance was obtained with 66.8% cross-validated AUC (area under the ROC curve) when FDG and FreeSurfer datasets were integrated. Valid imaging-based phenotypes selected from our approach included ROI values extracted from temporal lobe, hippocampus, and amygdala. Employing a graph-based SSL approach with multimodal brain imaging data appears to have substantial potential for detecting E-MCI for early detection of prodromal AD warranting further investigation
Network-guided sparse learning for predicting cognitive outcomes from MRI measures

Alzheimer's disease (AD) is characterized by gradual neurodegeneration and loss of brain function, especially for memory during early stages. Regression analysis has been widely applied to AD research to relate clinical and biomarker data such as predicting cognitive outcomes from MRI measures. In particular, sparse models have been proposed to identify the optimal imaging markers with high prediction power. However, the complex relationship among imaging markers are often overlooked or simplified in the existing methods. To address this issue, we present a new sparse learning method by introducing a novel network term to more flexibly model the relationship among imaging markers. The proposed algorithm is applied to the ADNI study for predicting cognitive outcomes using MRI scans. The effectiveness of our method is demonstrated by its improved prediction performance over several state-of-the-art competing methods and accurate identification of cognition-relevant imaging markers that are biologically meaningful
Cuckoo Search: A Brief Literature Review

Cuckoo search (CS) was introduced in 2009, and it has attracted great
attention due to its promising efficiency in solving many optimization problems
and real-world applications. In the last few years, many papers have been
published regarding cuckoo search, and the relevant literature has expanded
significantly. This chapter summarizes briefly the majority of the literature
about cuckoo search in peer-reviewed journals and conferences found so far.
These references can be systematically classified into appropriate categories,
which can be used as a basis for further research.Comment: 14 pages 3 figure
A Dissipative-Particle-Dynamics Model for Simulating Dynamics of Charged
  Colloid

A mesoscopic colloid model is developed in which a spherical colloid is
represented by many interacting sites on its surface. The hydrodynamic
interactions with thermal fluctuations are taken accounts in full using
Dissipative Particle Dynamics, and the electrostatic interactions are simulated
using Particle-Particle-Particle Mesh method. This new model is applied to
investigate the electrophoretic mobility of a charged colloid under an external
electric field, and the influence of salt concentration and colloid charge are
systematically studied. The simulation results show good agreement with
predictions from the electrokinetic theory.Comment: 17 pages, 8 figures, submitted to the proceedings of High Performance
  Computing in Science & Engineering '1
An Arduino compatible CAN Bus architecture for sailing applications

International audienceThis paper describes a Controller Area Network (CAN) Bus architecture based on Arduino compatible boards, to be used as an alternative communication system for robotic applications. This combines both, the robustness of CAN and the accessibility of Arduino software. The architecture is developed here to improve a Navigational Assistance System, which was initially created for disabled people. The system is composed of Arduino compatible boards, wired with various sensors and actuators, and communicating with an Human Machine Interface (HMI), directly accessible via a mobile phone or a tablet running on the open-source operating system Android. Information is transferred through the CAN bus architecture between multiple nodes (i.e. Arduino compatible boards) and the implementation of a CAN bootloader allows the reconfiguration of the nodes directly through the bus. The aim is to create a generic system able to work in various kinds of situations, adaptable to all kinds of users, including persons with all sorts of disabilities. This work will result in a demonstrator on a Miniji for the WRSC 2013 and an entirely joystick controlled boat for single handed sailing
Bilingual Education in Aotearoa/New Zealand

Bilingual education in the context of New Zealand is now over 30 years old. The two largest linguistic minority groups involved in this type of education – the Indigenous Māori and Pasifika peoples of Samoan, Tongan, Cook Islands and Niuean and Tokelauan backgrounds – have made many gains but have struggled in a national context where minority languages have low status. Māori bilingual programs are well established and have made a significant contribution towards reducing Māori language shift that in the 1970s looked to be beyond regeneration. Pasifika bilingual education by contrast is not widely available and not well resourced by the New Zealand government. Both forms continue to need support and a renewed focus at local and national levels.

This chapter provides an overview of past development of Māori and Pasifika bilingual education and present progress. For Māori, the issues relate primarily to how to boost language regeneration, particularly between the generations. Gaining greater support for immersion programs and further strengthening bilingual education pedagogies, particularly relating to achieving biliteracy objectives, are key. In the context of Pasifika, extending government and local support would not only safeguard the languages but has the potential to counteract long-established patterns of low Pasifika student achievement in mainstream/English-medium schooling contexts. Finally, the future of both forms of bilingual education can be safeguarded if they are encompassed within a national languages policy that ensures minority language development in the predominantly English monolingual national context of New Zealand
Novel method for vehicle and pedestrian detection based on information fusion

A novel approach for vehicle and pedestrian detection based on data fusion techniques is presented. The work fuses information from a 2D laser scanner and a computer camera, to provide detection and classification of vehicles and pedestrians in road environments. Thanks to the data fusion approach, the limitations of each sensor are overcome. Thus reliable system is provided, fulfilling the demands of road safety applications. Classification is performed using each sensor independently. Laser scanner approach is based in pattern matching and vision approach is based in the classical Histogram of Oriented Gradients features approach. A higher stage performs data fusion using Kalman Filter and Global Nearest Neighbors.This work was supported by the Spanish Government through the Cicyt
projects (GRANT TRA2010-20225-C03-01) and (GRANT TRA 2011-29454-C03-02). CAM
through SEGAUTO-II (S2009/DPI-1509)
Personal learning environments (PLEs): visions and concepts

Personal learning environments (PLEs) hold the potential to address the needs of formal and informal learners for multi-sourced content and easily customisable learning environments. This chapter presents an overview of the European project ROLE (Responsive Open Learning Environments), which specialises in the development and evaluation of learning environments that can be personalised by individual learners according to their particular needs, thus enabling them to become self-regulated learners