Bridging Between Computer and Robot Vision Through Data Augmentation: A Case Study on Object Recognition

Despite the impressive progress brought by deep network in visual object recognition, robot vision is still far from being a solved problem. The most successful convolutional architectures are developed starting from ImageNet, a large scale collection of images of object categories downloaded from the Web. This kind of images is very different from the situated and embodied visual experience of robots deployed in unconstrained settings. To reduce the gap between these two visual experiences, this paper proposes a simple yet effective data augmentation layer that zooms on the object of interest and simulates the object detection outcome of a robot vision system. The layer, that can be used with any convolutional deep architecture, brings to an increase in object recognition performance of up to 7{\%}, in experiments performed over three different benchmark databases. An implementation of our robot data augmentation layer has been made publicly available

Domain Generalization by Solving Jigsaw Puzzles

Human adaptability relies crucially on the ability to learn and merge knowledge both from supervised and unsupervised learning: the parents point out few important concepts, but then the children fill in the gaps on their own. This is particularly effective, because supervised learning can never be exhaustive and thus learning autonomously allows to discover invariances and regularities that help to generalize. In this paper we propose to apply a similar approach to the task of object recognition across domains: our model learns the semantic labels in a supervised fashion, and broadens its understanding of the data by learning from self-supervised signals how to solve a jigsaw puzzle on the same images. This secondary task helps the network to learn the concepts of spatial correlation while acting as a regularizer for the classification task. Multiple experiments on the PACS, VLCS, Office-Home and digits datasets confirm our intuition and show that this simple method outperforms previous domain generalization and adaptation solutions. An ablation study further illustrates the inner workings of our approach.Comment: Accepted at CVPR 2019 (oral

Effects of political-economic integration and trade liberalization on exports of Italian Quality Wines Produced in Determined Regions (QWPDR)

The aim of this work is to explain the magnitude of the trade flows for high quality wine from Italy to its main importing countries. This objective has been reached by establishing an appropriate econometric model derived from an extended form of the “Gravity Model”. This model has been broadly applied to the analysis of international trade because it provides robust estimates. The results obtained and the model itself are useful in forecasting potential trends in the exportation of high quality Italian wines. In particular, these estimates give a quantitative evaluation of the export gains that could result from the enlargement of the EU and from an increasing liberalization in international trade. Moreover, it is possible to identify the growing markets where Italian ventures could exploit certain promotional and communication strategies.Italy, Exports, QWPDR, Integration, Gravity Model

Agritourism flows to Italy: an analysis of determinants using the gravity model approach

Tourism represents one of the most important income sources for Italy. In recent years, apart from “traditional” destinations, tourism supply is widely changing in order to satisfy the customers “love for variety” and valorise marginal resources, then new formulas are emerging (e.g. agritourism). This work aims to elaborate and estimate an econometric model able to adequately explain the size of agritourists flows to Italy from main partner countries using the gravity model approach that has been broadly applied to the analysis of international flows. In this work, the “basic” model has been enlarged and improved with the introduction of other explicative variables. The results has allowed to confirm empirical validity of the gravity model in studying international flows of any nature. Furthermore, the estimated econometric model represents a useful analytical instrument to describe, and, eventually, predict demand of foreign visitors for agritourist vacations in Italy.Gravity Model, Agritourism, Rural tourism, Tourism flows, Research Methods/ Statistical Methods, Resource /Energy Economics and Policy,

New challenges and opportunities for Italian exports of table wines and high quality wines

Competition in international wine market has recently become more intense because of several factors and, in particular, the progressive reduction in world-wide consumption, the addition of new producing countries such as Australia, Chile, the USA and South Africa (the so called New World wine producers) and the increasing trade liberalization. In order to achieve a competitive advantage in the international marketplace, it is very important to identify which markets are characterized by bigger attractiveness. In particular, the ability of a producer, a region or a country to provide effective communication and promotion actions towards more profitable local markets is strategic in international trade. Italy, one of the first wine producing country in the world, exports its wines to almost all countries of the five continents. However, the five greater importing countries account for 70 percent of Italy’s total wine exports (the USA, Germany, the United Kingdom, Switzerland, and Canada) and so Italy shows only a moderate market diversification. In this paper, an econometric model able to explain the size of wine export flows from Italy to its main importing countries was elaborated and estimated. This model provides useful information that can help to identify the main growing markets where all participants in the wine supply-chain, such as private wineries, joint-ventures, regional and national agencies, and producers’ associations, can unite to concentrate product communication and promotional efforts. The model is an extended version of the “gravity model” that many economists believe a very powerful tool for international trade analysis. In fact, at the empirical level, the gravity model gives very robust estimates and provides a good fit to the observed data. The basic concept of the gravity model for trade analysis borrows the gravity equation from physics: the volume of trade between two countries is proportional to their economic “mass” and inversely proportional to their respective distance. In this work, the investigation about the features of Italian wine export flows is conducted through the estimation of two different econometric models; the first one is related to QWPDR and second one is related to table wine category. Both models derive from an extended version of the basic gravity model where dummies for groups of countries have been added. An important result is that Italy should increase the production of high quality wine because there are favorable conditions in place which would increase exportation. At the same time, Italy should decrease the production of table wine because its international demand is declining. Moreover, estimation results show that both QWPDR and table wine exportations are income elastic. Hence, if Italian wine producers intend to expand their exportations, it is natural to look at those countries where income growth is high but also constant and solid. It is interesting to highlight that, among countries with the highest income growth rates, there are three very big countries, China, Russia and India, where expansion possibilities for Italian wine exports are very attractive. Currently, these countries import less than 1% of total exports of Italian wine. At the same time, it is important to highlight that the main countries importing Italian wine (the United States, Germany, the United Kingdom, Switzerland, Canada, Japan and almost all western European countries) show a moderate but stable income growth and therefore it would be strategic to defend and consolidate Italian market shares against any possible aggressions by the new wine producing countries. The recent enlargement of the EU could represent a great opportunity for the exporters of Italian wine. In particular, it is interesting to note that all new EU members and, in particular, the Baltic Republics (Latvia, Estonia, Lithuania) show high income growth rates. In addition, as widely known, there are no customs barriers within the European Union but instead there is a common external tariff applied to imports from non-EU countries. Therefore, these countries represent very interesting, and as yet untapped, markets even if, in the next years, there are real possibilities to expand mainly table wine exports because the income, although rapidly increasing, remains still moderate.Italian Wine; Trade; Gravity model; Exports

multiobjective optimization of the breathing system of an aircraft two stroke supercharged diesel engine

Abstract One of the factors limiting the utilization of piston internal combustion engines for aircraft propulsion is the performance decrease increasing the altitude of operation. This is due to the negative effect of air density reduction increasing the altitude on cylinder filling. A solution to this problem is represented by the engine supercharging. Unfortunately, in two stroke engines, the cylinder filling efficiency is antithetical to the cylinder scavenging efficiency. With the aim of guaranteeing an optimal balance between engine performance and specific consumption, an engine breathing system optimization is needed. In this work, the results obtained running a multi-objective optimization procedure aiming at performance increase and fuel consumption reduction of an aircraft two stroke supercharged diesel engine at various altitudes are analyzed. During the optimization procedure, several geometric parameters of the intake and exhaust systems as well as geometric and operating engine parameters have been varied. Then, a multi-objective optimization algorithm based on genetic algorithms has been run to obtain the configurations optimizing the engine performance at Sea Level (take-off conditions) and fuel consumption at 10680 m (cruise conditions)

Detailed Thermal Characterization on a 48V Lithium-Ion Battery Pack during Charge-Discharge Cycles

This study experimentally investigates the temperature distribution and behavior of a 48V Lithium-Ion (Li-ion) battery pack during two charge-discharge cycles using 25 thermocouples. Results indicate that better convective heat transfer occurs at the external surfaces of the pack, while middle cells reach maximum temperatures. Differences are also observed in the behavior of the three modules. The discharge cycle shows a temperature rise of 5.8{\deg}C with a pack temperature gradient increasing from 1.3{\deg}C to 2.7{\deg}C. The study highlights the importance of assessing the thermal behavior of each module and the complexity of the Li-ion battery pack system. Findings on the battery cells, modules, and pack in the same study can provide valuable insights for designing efficient cooling systems for Li-ion battery packs.Comment: 11 pages, 4 figure

Addressing Load Sensitivity of Rational Macromodels

Behavioral models are effective tools used to relieve the computational burden of large-scale system-level simulations. In electrical and electronic applications, the Vector Fitting (VF) iteration often represents the algorithm of choice for generating low order equivalent circuits for complex multiport components in a data-driven setting. Although accurate and reliable in general, macromodels generated via VF are inherently represented in terms of a rational approximation of one specific input-output transfer function of the structure under modeling, e.g., its scattering matrix. However, accuracy in the scattering representation does not necessarily imply a good accuracy when solving the macromodel in a system-level setting, under different termination conditions. In fact, the sensitivity of the macromodel with respect to its loading conditions may be large and needs to be addressed and controlled. In this work, we present a modified VF scheme that overcomes this issue, by introducing in the rational approximation algorithm the requirement that the macromodel remains accurate when interconnected with a known class of admissible networks. The proposed formulation is based on an augmentation of the cost function minimized at each VF iteration; further, it does not require additional expensive data gathering steps when compared to standard approaches. The effectiveness of the scheme is tested over a set of relevant examples, in particular for Power Integrity applications

Potential Application of Photo-thermal Volumetric Ignition of Carbon Nanotubes in Internal Combustion Engines

In internal combustion engines, an ignition source is required to initiate the combustion process. This is commonly obtained either through an electric spark generation or by physical act of compression-ignition. In order to improve performance and lower pollutants levels, researchers have proposed alternatives to conventional ignition or combustion processes, such as homogeneously-charge compression-ignition (HCCI) combustion, whose critical operational requirement is precise control of the autoignition timing within the engine operating cycle. In this work, an innovative volumetrically-distributed ignition approach is proposed to control the onset of the autoignition process, by taking advantage of the optical ignition properties of carbon nanotubes when exposed to a low-consumption light source. It is shown that this ignition method enhanced the combustion of methane, hydrogen, LPG, and gasoline (injected to chamber in liquid phase). The results for this new ignition method show that pressure gradient and combustion efficiency are increased, while combustion duration and ignition delay time are decreased. A direct observation of the combustion process indicates that these benefits are due to the spatially-distributed ignition followed by a faster initial consumption of the air/fuel mixture. The use of this ignition system is therefore proposed as a promising technology for the combustion management in internal combustion engines, specifically for the HCCI engines