4,396 research outputs found
Trust and prosocial behaviour in a process of state capacity building: the case of the Palestinian territories
This paper contributes to the literature by conducting the first empirical
investigation into the determinants of prosocial behaviour in the Palestinian
territories, with a focus on the role of trust and institutions. Drawing on a
unique dataset collected through the administration of a questionnaire to a
representative sample of the population of the West Bank and the Gaza
Strip, we have found that institutional trust is the strongest predictor of
prosociality. This result suggests that, in collectivist societies with low
levels of generalized trust, the lack of citizens’ confidence in the fairness
and efficiency of public institutions may compromise social order. The
strengthening of institutional trust may also reinforce prosocial behaviour in
individualist societies, where a decline in generalized trust has been
documented by empirical studie
Low-cost RPAS navigation and guidance system using Square Root Unscented Kalman Filter
Multi-Sensor Data Fusion (MSDF) techniques involving satellite and inertial-based sensors are widely adopted to improve the navigation solution of a number of mission- and safety-critical tasks. Such integrated Navigation and Guidance Systems (NGS) currently do not meet the required level of performance in all flight phases of small Remotely Piloted Aircraft Systems (RPAS). In this paper an innovative Square Root-Unscented Kalman Filter (SR-UKF) based NGS is presented and compared with a conventional UKF governed design. The presented system architectures adopt state-of-the-art information fusion approach based on a number of low-cost sensors including; Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical System (MEMS) based Inertial Measurement Unit (IMU) and Vision Based Navigation (VBN) sensors. Additionally, an Aircraft Dynamics Model (ADM), which is essentially a knowledge based module, is employed to compensate for the MEMS-IMU sensor shortcomings in high-dynamics attitude determination tasks. The ADM acts as a virtual sensor and its measurements are processed with non-linear estimation in order to increase the operational validity time. An improvement in the ADM navigation state vector (i.e., position, velocity and attitude) measurements is obtained, thanks to the accurate modeling of aircraft dynamics and advanced processing techniques. An innovative SR-UKF based VBN-IMU-GNSS-ADM (SR-U-VIGA) architecture design was implemented and compared with a typical UKF design (U-VIGA) in a small RPAS (AEROSONDE) integration arrangement exploring a representative cross-section of the operational flight envelope. The comparison of position and attitude data shows that the SR-U-VIGA and U-VIGA NGS fulfill the relevant RNP criteria, including precision approach tasks
Multi-sensor data fusion techniques for RPAS detect, track and avoid
Accurate and robust tracking of objects is of growing interest amongst the computer vision scientific community. The ability of a multi-sensor system to detect and track objects, and accurately predict their future trajectory is critical in the context of mission- and safety-critical applications. Remotely Piloted Aircraft System (RPAS) are currently not equipped to routinely access all classes of airspace since certified Detect-and-Avoid (DAA) systems are yet to be developed. Such capabilities can be achieved by incorporating both cooperative and non-cooperative DAA functions, as well as providing enhanced communications, navigation and surveillance (CNS) services. DAA is highly dependent on the performance of CNS systems for Detection, Tacking and avoiding (DTA) tasks and maneuvers. In order to perform an effective detection of objects, a number of high performance, reliable and accurate avionics sensors and systems are adopted including non-cooperative sensors (visual and thermal cameras, Laser radar (LIDAR) and acoustic sensors) and cooperative systems (Automatic Dependent Surveillance-Broadcast (ADS-B) and Traffic Collision Avoidance System (TCAS)). In this paper the sensors and system information candidates are fully exploited in a Multi-Sensor Data Fusion (MSDF) architecture. An Unscented Kalman Filter (UKF) and a more advanced Particle Filter (PF) are adopted to estimate the state vector of the objects based for maneuvering and non-maneuvering DTA tasks. Furthermore, an artificial neural network is conceptualised/adopted to exploit the use of statistical learning methods, which acts to combined information obtained from the UKF and PF. After describing the MSDF architecture, the key mathematical models for data fusion are presented. Conceptual studies are carried out on visual and thermal image fusion architectures
Bowling alone but tweeting together: the evolution of human interaction in the social networking era
The objective of this paper is to theoretically analyze how human interaction may evolve in a world characterized by the explosion of online networking and other Web-mediated ways of building and nurturing relationships. The analysis shows that online networking yields a storage mechanism through which any individual contribution—e.g. a blog post, a comment, or a photo—is stored within a particular network and ready for virtual access by each member who connects to the network. When someone provides feedback, for example by commenting on a note, or by replying to a message, the interaction is finalized. These interactions are asynchronous, i.e. they allow individuals to relate in different moments, whenever they have time to. When the social environment is poor of participation opportunities and/or the pressure on time increases (for example due to the need to increase the working time), the stock of information and ties stored in the Internet can help individuals to defend their sociability
The occurrence of Calanidae species in waters off Argentina
As food of planktivorous fish and likely good predictors of natural perturbations, members of the family Calanidae are recognised to be key species in ecosystems worldwide. The distribution and seasonal relative abundance of the Calanidae species occurring in the Argentine Sea were reviewed from published and unpublished data collected over the last three decades. Species are also figured in order to elucidate any possible taxonomic uncertainty. Calanoides ef. carinatus, Calanus australis and Calanus simillimus are the most abundant calanids in the region. The former two species typically inhabit inner and middle shelf waters decreasing offshore, while Calanus simillimus is distributed in the middle and outer shelf, its abundance increasing towards the shelf-break. The southern limit of the distribution of Calanoides ef. carinatus appears to be ∼46° S. Calanus australis is the most common large copepod in coastal and inner shelf waters off southern Patagonia. Neocalanus tonsus and Calanoides patagoniensis are a much rarer species. The latter is recorded in the southwestern Atlantic, for the first time, immediately east of Magallanes Strait and the Beagle Channel. The taxonomic status and worldwide biogeographic distribution of the region's calanids are briefly described and the patterns identified off Argentina are discussed in relation to the major hydrographic characteristics.Fil: RamÃrez, F. C.. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Subsede Instituto Nacional de Investigación y Desarrollo Pesquero; ArgentinaFil: Sabatini, Marina Elena. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Centro CientÃfico Tecnológico Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Subsede Instituto Nacional de Investigación y Desarrollo Pesquero; Argentin
Unveiling the inner morphology and gas kinematics of NGC 5135 with ALMA
The local Seyfert 2 galaxy NGC5135, thanks to its almost face-on appearance,
a bulge overdensity of stars, the presence of a large-scale bar, an AGN and a
Supernova Remnant, is an excellent target to investigate the dynamics of
inflows, outflows, star formation and AGN feedback. Here we present a
reconstruction of the gas morphology and kinematics in the inner regions of
this galaxy, based on the analysis of Atacama Large Millimeter Array (ALMA)
archival data. To our purpose, we combine the available 100 pc resolution
ALMA 1.3 and 0.45 mm observations of dust continuum emission, the spectroscopic
maps of two transitions of the CO molecule (tracer of molecular mass in star
forming and nuclear regions), and of the CS molecule (tracer of the dense star
forming regions) with the outcome of the SED decomposition. By applying the
BAROLO software (3D-Based Analysis of Rotating Object via Line
Observations), we have been able to fit the galaxy rotation curves
reconstructing a 3D tilted-ring model of the disk. Most of the observed
emitting features are described by our kinematic model. We also attempt an
interpretation for the emission in few regions that the axisymmetric model
fails to reproduce. The most relevant of these is a region at the northern edge
of the inner bar, where multiple velocity components overlap, as a possible
consequence of the expansion of a super-bubble.Comment: 15 pages, 13 figures, resubmitted to MNRAS after moderate revision
Simultaneous multi-band detection of Low Surface Brightness galaxies with Markovian modelling
We present an algorithm for the detection of Low Surface Brightness (LSB)
galaxies in images, called MARSIAA (MARkovian Software for Image Analysis in
Astronomy), which is based on multi-scale Markovian modeling. MARSIAA can be
applied simultaneously to different bands. It segments an image into a
user-defined number of classes, according to their surface brightness and
surroundings - typically, one or two classes contain the LSB structures. We
have developed an algorithm, called DetectLSB, which allows the efficient
identification of LSB galaxies from among the candidate sources selected by
MARSIAA. To assess the robustness of our method, the method was applied to a
set of 18 B and I band images (covering 1.3 square degrees in total) of the
Virgo cluster. To further assess the completeness of the results of our method,
both MARSIAA, SExtractor, and DetectLSB were applied to search for (i) mock
Virgo LSB galaxies inserted into a set of deep Next Generation Virgo Survey
(NGVS) gri-band subimages and (ii) Virgo LSB galaxies identified by eye in a
full set of NGVS square degree gri images. MARSIAA/DetectLSB recovered ~20%
more mock LSB galaxies and ~40% more LSB galaxies identified by eye than
SExtractor/DetectLSB. With a 90% fraction of false positives from an entirely
unsupervised pipeline, a completeness of 90% is reached for sources with r_e >
3" at a mean surface brightness level of mu_g=27.7 mag/arcsec^2 and a central
surface brightness of mu^0 g=26.7 mag/arcsec^2. About 10% of the false
positives are artifacts, the rest being background galaxies. We have found our
method to be complementary to the application of matched filters and an
optimized use of SExtractor, and to have the following advantages: it is
scale-free, can be applied simultaneously to several bands, and is well adapted
for crowded regions on the sky.Comment: 39 pages, 18 figures, accepted for publication in A
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