347 research outputs found
Two EGARCH models and one fat tail
We compare two EGARCH models which belong to a new class of models in which the dynamics are driven by the score of the conditional distribution of the observations. Models of this kind are called dynamic conditional score (DCS) models and their form facilitates the development of a comprehensive and relatively straightforward theory for the asymptotic distribution of the maximum likelihood estimator. The EGB2 distribution is light-tailed, but with higher kurtosis than the normal. Hence it is complementary to the fat-tailed t. The EGB2-EGARCH model gives a good fit to many exchange rate return series, prompting an investigation into the misleading conclusions liable to be drawn from tail index estimates
Robust time series models with trend and seasonal components
We describe observation driven time series models for Student-t and EGB2 conditional distributions in which the signal is a linear function of past values of the score of the conditional distribution. These specifications produce models that are easy to implement and deal with outliers by what amounts to a soft form of trimming in the case of t and a soft form of Winsorizing in the case of EGB2. We show how a model with trend and seasonal components can be used as the basis for a seasonal adjustment procedure. The methods are illustrated with US and Spanish data.This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s13209-015-0134-
A new methodology for thermostructural topology optimization: Analytical definition and validation
In the last few years, the rapid diffusion of components produced through additive manufacturing processes has boosted the research on design methodologies based on topology optimization algorithms. Structural topology optimization is largely employed since it permits to minimize the component weight and maximize its stiffness and, accordingly, optimize its resistance under structural loads. On the other hand, thermal topology optimization has been less investigated, even if in many applications, such as turbine blades, engines, heat exchangers, thermal loads have a crucial impact. Currently, structural and thermal optimizations are mainly considered separately, despite the fact that they are both present and coupled in components in service condition. In the present paper, a novel methodology capable of defining the optimized structure under simultaneous thermomechanical constraints is proposed. The mathematical formulation behind the optimization algorithm is reported. The proposed methodology is finally validated on literature benchmarks and on a real component, confirming that it permits to define the topology, which presents the maximized thermal and mechanical performance
Intrusion detection for in-vehicle communication networks: An unsupervised kohonen SOM approach
The diffusion of embedded and portable communication devices on modern vehicles entails new security risks since in-vehicle communication protocols are still insecure and vulnerable to attacks. Increasing interest is being given to the implementation of automotive cybersecurity systems. In this work we propose an efficient and high-performing intrusion detection system based on an unsupervised Kohonen Self-Organizing Map (SOM) network, to identify attack messages sent on a Controller Area Network (CAN) bus. The SOM network found a wide range of applications in intrusion detection because of its features of high detection rate, short training time, and high versatility. We propose to extend the SOM network to intrusion detection on in-vehicle CAN buses. Many hybrid approaches were proposed to combine the SOM network with other clustering methods, such as the k-means algorithm, in order to improve the accuracy of the model. We introduced a novel distance-based procedure to integrate the SOM network with the K-means algorithm and compared it with the traditional procedure. The models were tested on a car hacking dataset concerning traffic data messages sent on a CAN bus, characterized by a large volume of traffic with a low number of features and highly imbalanced data distribution. The experimentation showed that the proposed method greatly improved detection accuracy over the traditional approach
A Kohonen SOM architecture for intrusion detection on in-vehicle communication networks
The diffusion of connected devices in modern vehicles involves a lack in security of the in-vehicle communication networks such as the controller area network (CAN) bus. The CAN bus protocol does not provide security systems to counter cyber and physical attacks. Thus, an intrusion-detection system to identify attacks and anomalies on the CAN bus is desirable. In the present work, we propose a distance-based intrusion-detection network aimed at identifying attack messages injected on a CAN bus using a Kohonen self-organizing map (SOM) network. It is a power classifier that can be trained both as supervised and unsupervised learning. SOM found broad application in security issues, but was never performed on in-vehicle communication networks. We performed two approaches, first using a supervised X-Y fused Kohonen network (XYF) and then combining the XYF network with a K-means clustering algorithm (XYF-K) in order to improve the efficiency of the network. The models were tested on an open source dataset concerning data messages sent on a CAN bus 2.0B and containing large traffic volume with a low number of features and more than 2000 different attack types, sent totally at random. Despite the complex structure of the CAN bus dataset, the proposed architectures showed a high performance in the accuracy of the detection of attack messages
A germline de novo variant in NUMB associated with a double-outlet right ventricle in Chianina cattle.
Choline-containing compounds quantification by 1H NMR spectroscopy using external reference and noise measurements
Ripensare le attività di apprendimento. Osservare e comunicare efficacemente in DAD per promuovere l’apprendimento significativo
La Ley Argentina de Arbitraje Comercial Internacional, a través de un enfoque comparativo con la Ley Peruana de Arbitraje
El 2018 ha sido un año productivo para el arbitraje latinoamericano. Los dos únicos paÃses de la región que aún no lo habÃan hecho, sancionaron sendas leyes sobre arbitraje comercial internacional que, coincidentemente, se publicaron en la misma fecha, 26 de julio de 2018. Nos referimos a la Ley Argentina, N° 27.4493 [en adelante, la LACI], y a la Ley Uruguaya, N° 19.636.
Cada paÃs posee una riqueza que lo caracteriza y basa su polÃtica legislativa en ello. Esto se ve en los considerandos de la ley argentina, en que se expresa el objetivo de incentivar el comercio internacional y dotar al paÃs de herramientas que lo faciliten. De manera similar, la polÃtica legislativa del Perú al expedir la Ley de Arbitraje en 2008 fue crear un ambiente sin trabas al firmado Tratado de Libre Comercio con los Estados Unidos, y su modificación de 2015 se propuso garantizar la seguridad jurÃdica, previniendo la comisión de fraudes y la afectación de derechos de terceros a través del uso indebido de la institución arbitral.
La fuente directa de la ley argentina –como lo es de casi todas las legislaciones sobre arbitraje sancionadas en las últimas décadas– es la Ley Modelo de Arbitraje Comercial Internacional elaborada por la Comisión de las Naciones Unidas para el Derecho Mercantil Internacional (CNUDMI/UNCITRAL) [en adelante, la LMU]. Tan asÃ, es que la LACI reproduce el texto de la LMU, con algunas pocas modificaciones.
La Ley de Arbitraje Peruana [en adelante, LAP] también se inspiró y tomó como fuente la LMU. Sin embargo, aunque tomó de la LMU sus principales instituciones, la LAP no siguió tan fielmente su texto como la LACI. La LAP se ha inspirado además en la Ley de Arbitraje Española de 2003, la Ley Federal Suiza en Derecho Internacional Privado, asà como, el Reglamento de Arbitraje de la Cámara de Comercio Internacional, y el Reglamento de la Corte de Arbitraje Internacional de Londres.
En este trabajo nos centraremos en analizar la LACI resaltando, en un enfoque comparativo, algunas de las principales diferencias que tiene con la LMU y con la LAP.Facultad de Ciencias JurÃdicas y Sociale
Volumetric and Dosimetric Assessment by Cone-Beam Computed Tomography Scans in Head and Neck Radiation Therapy: A Monitoring in Four Phases of Treatment
Due to the anatomical changes frequently occurring during the course of head and neck (H&N) cancer radiotherapy, the dose distribution, which was actually delivered to the patient, might significantly differ from that planned. The aim of this paper is to investigate these volumetric changes and the resulting dosimetric implications on organs at risk (OARs) and clinical target volumes (CTVs) by cone beam computed tomography (CBCT) scans throughout the treatment. Ten H&N patients, treated by Intensity Modulated Radiotherapy, were analyzed. CTVs and OARs were delineated on four CBCT, acquired at the 10th, 15th, 20th and 25th treatment session, and then compared with the ones at planning CT. The planned beams were applied to each CBCT to recalculate the dose distribution and the corresponding dose volume histograms were compared with those generated on planning CT. To evaluate the HU discrepancies between the conventional CT and CBCT images we used a Catphan® 504, observing a maximum discrepancy of about 30 HU. We evaluated the impact of this HU difference in dose calculation and a not clinically relevant error, within 2.8%, was estimated. No inhomogeneity correction was used. The results showed an increased CTV mean dose (Dmean) of about 3% was found, without significant reduction in volume. Due to the parotids' shrinkage (up to 42%), significant dosimetric increases were observed: ipsilateral gland at 15th CBCT (Dmean by 18%; V30 by 31%); controlateral gland at the 10th CBCT (Dmean by 12.2%; V30 by 18.7%). For the larynx, a significant increase of volume was found at the 20th (15.7%) and 25th CBCT (13.3%) but it complied with dose constraint. The differences observed for the spinal cord and mandible maximum doses were not clinically relevant. In conclusion, the dosimetric analysis on CBCT can help clinicians to monitor treatment progress and to evaluate whether and when a new plan is necessary. The main benefit of replanning could be to preserve the parotids and our data support the hypothesis that the 3rd week of radiotherapy should be a check point for parotids
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