Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated Visual Odometry For Improved Autonomous Vehicle Navigation

Safe, efficient, and comfortable travel has always been a fundamental human necessity. From reducing commute time to saving lives, autonomous vehicles promise to be an indispensable tool in the age of modern urban transportation. However, implementing such a disruptive technology comes with significant challenges, a major one being accurate vehicle positioning and localization. In situations such as urban cores, parking lots, and under dense foliage, positioning information provided by the Global Navigation Satellite System (GNSS) deteriorates significantly. GNSS is increasingly integrated with other systems such as the inertial navigation system (INS) and Visual Odometry (VO) to bridge these outages. The major drawback of current integration systems is that they are unable to provide a stable navigation estimate during extended and frequent GNSS outages, situations common to autonomous vehicles. To improve the overall system accuracy, this thesis presents a multi-sensor navigation solution that integrates GNSS with a low-cost inertial measurement unit (IMU) and VO. Firstly, a switching architecture is detailed, which implements a loosely coupled extended Kalman filter (EKF) that fuses VO updates only when GPS is unavailable, reducing computational resources while limiting the errors inherent in an INS. Secondly, termed R-AVO (Reduced Aided Visual Odometry), the orientation i and translation of a vehicle, as determined by a low drift INS algorithm, is used to evaluate which feature matches from the processed image frames are to be considered in VO. This method is shown to be both more accurate and less computationally expensive than classic feature outlier rejection schemes, which are iterative in nature. Reducing the computation complexity of VO paves the way for even more sensors to be utilized by a vehicle. The developed algorithms are evaluated on several real road trajectories, including simulated outages that are as long as 10 minutes. To ensure generic implementations, two different land vehicles are used in the trajectories and two different IMUs were tested.
Essays on the economics of social interactions

This dissertation consists of three self-contained essays on the economics of social interactions. The rst chapter is coauthored with Lorenzo Verstraeten. Knowing that Individuals interact with their peers, we study how a social planner can intervene, changing these interactions, in order to achieve a particular objective. When the objective is welfare maximization, we describe the interventions for games of strategic complements and strategic substitutes. We show that, for strategic complements, the planner uses resources to target central players; while she divides individuals into separated communities in the case of strategic substitutes. We study which connections she targets in order to achieve these goals. The second chapter is coauthored with Lorenzo Verstraeten and analyzes a model of contagion on social network. We ask how a social planner should intervene to prevent contagion. We characterize the optimal intervention and the cost associated. We discuss the intuition behind the choice of the planner and we provide comparative static on the cost of intervention for di erent type of network. In the third chapter I develop a theoretical study about groups relationship and ask whether intragroup cooperation crowd-out intergroup cooperation. I consider a gift-giving game where cooperation endogenously arises, within and across groups. Cooperation is sustained through peer punishment with the help of a group speci c monitoring technology. I specify under which conditions cooperation crowding-out occur. I identify two classes of equilibrium: a Sorting equilibrium where guilty players prefer to be matched outside their group due to a less e cient Out-Group monitoring technology, and a Non Sorting equilibrium where the higher level of In-Group cooperation makes it more attractive for everybody. I then compare their welfare properties and draw conclusions on optimal punishment levels. Acknowledgments I am indebted to my advisors David K. Levine and Andrea Galeotti for their guidance. I would like to thank my coauthor Lorenzo Verstraeten, Gabriela Galassi for never-ending support and commitment, and all the participants to the EUI working group for helpful comments and discussions. I would also like to thank Arpad Abraham, Lian Allub, Ines Berniel, Elena Esposito, Gabriel Facchini, Matteo Foschi and Evi Pappa. Finally I would like to thank Jessica Spataro, Lucia Vigna, Sarah Simonsen, Julia Valerio, Anne Banks and Rossella Corridori who make our life at the EUI so pleasant and worry-free that we can focus on research.
Algorithms for Social Curation: Designing and evaluating an embodied and subjectively situated visual art Interpretation and navigation system (VAINS)

VAINS, the visual art Interpretation and navigation system, is an interdisciplinary work in progress, an interactive website which offers repository, search and content recommendation tools for art content in an online environment. This paper will put the VAINS system into a historical curatorial context as well as explaining and analysing the VAINS project and its methodology, outlining our reasons for placing the body at the forefront of its navigation systems. The paper will also present a narrative of interaction with the tools we have created, showing their impact on a range of users and illustrating the value of embodiment in the context of online curation.
Planning for a Small Team of Heterogeneous Robots: from Collaborative Exploration to Collaborative Localization

Robots have become increasingly adept at performing a wide variety of tasks in the world. However, many of these tasks can benefit tremendously from having more than a single robot simultaneously working on the problem. Multiple robots can aid in a search and rescue mission each scouting a subsection of the entire area in order to cover it quicker than a single robot can. Alternatively, robots with different abilities can collaborate in order to achieve goals that individually would be more difficult, if not impossible, to achieve. In these cases, multi-robot collaboration can provide benefits in terms of shortening search times, providing a larger mix of sensing, computing, and manipulation capabilities, or providing redundancy to the system for communications or mission accomplishment. One principle drawback of multi-robot systems is how to efficiently and effectively generate plans that use each of the team members to their fullest extent, particularly with a heterogeneous mix of capabilities. Towards this goal, I have developed a series of planning algorithms that incorporate this collaboration into the planning process. Starting with systems that use collaboration in an exploration task I show teams of homogeneous ground robots planning to efficiently explore an initially unknown space. These robots share map information and in a centralized fashion determine the best goal location for each taking into account the information gained by other robots as they move. This work is followed up with a similar exploration scheme but this time expanded to a heterogeneous air-ground robot team operating in a full 3-dimensional environment. The extra dimension adds the requirement for the robots to reason about what portions of the environment they can sense during the planning process. With an air-ground team, there are portions of the environment that can only be sensed by one of the two robots and that information informs the algorithm during the planning process. Finally, I extend the air-ground robot team to moving beyond merely collaboratively constructing the map to actually using the other robots to provide pose information for the sensor and computationally limited team members. By explicitly reasoning about when and where the robots must collaborate during the planning process, this approach can generate trajectories that are not feasible to execute if planning occurred on an individual robot basis. An additional contribution of this thesis is the development of the State Lattice Planning with Controller-based Motion Primitives (SLC) framework. While SLC was developed to support the collaborative localization of multiple robots, it can also be used by a single robot to provide a more robust means of planning. For example, using the SLC algorithm to plan using a combination of vision-based and metric-based motion primitives allows a robot to traverse a GPS-denied region.
COOPERAÇÃO REGIONAL NA SEGURANÇA PÚBLICA: AVALIAÇÃO DO QUADRO NORMATIVO NO CONTEXTO DA UNASUL

This paper considers the normative framework that support regional cooperative practices in public security based on the activities carried out by UNASUR’s South American Council on Citizen Security, Justice and Coordination of Actions against Transnational Organized Crime. The article discusses differences and similarities between the conceptions of cooperation and public policies, analyzes the documents produced within the Council and presents limitations, obstacles and opportunities identified from the reading of these documents with regard to regional cooperation in public security.
Caractérisation des documents anciens par l'utilisation de la classification floue

Dans ce papier nous presentons un systeme de caracterisation des images de documents anciens base sur la logique floue. Le processus de caracterisation se divise en deux etapes : l'extraction de caracteristiques des images de documents anciens ensuite le groupement selon le meilleur score de correspondance entre l'image requete et les images contenus dans la base. Chaque image est caracterisee par sa dimension fractale ainsi que des caracteristiques structurelles basees sur les directions et pentes moyennes de chaque image. L'image cible est ainsi comparee avec l'image requete en utilisant une matrice de similarite. Plusieurs tests ont ete appliques, et ils ont montre la robustesse de notre systeme dans les termes de correspondance entre les images requetes et les images cibles
Analyzing Product Flows with the Supply Chain Visualizer

Globalization and technical advances have created a new level of competition and complexity for supply chains. The risk is high that due to this complexity and limited visibility causes of inefficiencies remain undiscovered. Radio Frequency IDentification (RFID) technology has recognized potential to increase the visibility along a supply chain due to cost-efficient gathering of process event data. With the Supply Chain Visualizer, we provide a tool for analyzing this event data and show how simple rules can reveal inefficiencies. By using a map-based user interface, a supply chain manager is finally able to pinpoint the sources of inefficiencies.
Effect of Feature Selection on Gene Expression Datasets Classification Accurac

Feature selection attracts researchers who deal with machine learning and data mining. It consists of selecting the variables that have the greatest impact on the dataset classification, and discarding the rest. This dimentionality reduction allows classifiers to be fast and more accurate. This paper traits the effect of feature selection on the accuracy of widely used classifiers in literature. These classifiers are compared with three real datasets which are pre-processed with feature selection methods. More than 9% amelioration in classification accuracy is observed, and k-means appears to be the most sensitive classifier to feature selection.
An architecture for mapping relational database to ontology

In recent years a number of researches have been written on the topic of definitions of mapping of a database to ontology. This dissertation presents the proposal and the construction of an architecture which enables an automatic mapping process of relational database to OWL ontology. For this purpose, it makes use of new and existent rules and offers as contributions naming and elimination of duplicated elements, increasing the legibility of the generated ontology. We stand out the structure of element mapping, which allows to maintain a source-to-target traceability for verifications. Validating of proposed architecture and rules is made by a case study using a dental care database. Key-words: Relational database. Ontology. Mapping.
Application of biclustering algorithm to extract rules from labeled data

Purpose For many pattern recognition problems, the relation between the sample vectors and the class labels are known during the data acquisition procedure. However, how to find the useful rules or knowledge hidden in the data is very important and challengeable. Rule extraction methods are very useful in mining the important and heuristic knowledge hidden in the original high-dimensional data. It can help us to construct predictive models with few attributes of the data so as to provide valuable model interpretability and less training times. Design/methodology/approach In this paper, a novel rule extraction method with the application of biclustering algorithm is proposed. Findings To choose the most significant biclusters from the huge number of detected biclusters, a specially modified information entropy calculation method is also provided. It will be shown that all of the important knowledge is in practice hidden in these biclusters. Originality/value The novelty of the new method lies in the detected biclusters can be conveniently translated into if-then rules. It provides an intuitively explainable and comprehensive approach to extract rules from high-dimensional data while keeping high classification accuracy.
COMITÊ DE AUDITORIA: PRINCIPAIS DISCUSSÕES E INCIDÊNCIA DE PESQUISAS CIENTÍFICAS

O objetivo do presente estudo foi fazer um resgate das principais discussoes sobre comite de auditoria desde a sua origem e revisar a incidencia de pesquisas cientificas sobre esse tema. Trata-se de uma pesquisa exploratoria-qualitativa, tendo a revisao de estudos proposta abrangido uma amostra de 39 investigacoes. Como resultado constatou-se que as principais abordagens sobre o tema estao voltadas a sua formacao voluntaria, independencia dos membros e vantagens proporcionadas as companhias. Em se tratando de tematica emergente a ser estudada, cita-se a estruturacao de um colegiado com maior poder coercitivo, pela sua independencia por meio da desvinculacao remuneratoria dos seus membros.
A cross-language perspective on the MAIDAN-concept

As the constituents of thoughts, concepts play a key role in human’s categorisation and interpretation of the surrounding world, in fixing our cognitive experience and forming individual judgements. The paper considers the representation of the nationally biased (ethno-specific) concept MAIDAN as one of those functioning not only in Ukrainian but also in pan-European and global socio-political discourses of the recent years. Specifically, leaning on lexicographic data the study focuses on reconstructing the notional layer (informative core) of the concept and on identifying the differences of its content as featured in kin Slavic (Ukrainian and Russian) and distant Germanic (English and German) languages and linguocultures. The paper suggests a consecutive methodology based on lexicographic methods of analysis. Such methodology helps to define the sets of notional conceptual features subjected to further comparative interpretation. The procedures described in this paper give way to subsequent stages of conceptual analysis and discourse representations. The paper also provides preliminaries to the state of inconsistency between the systemic and utterance meanings of the language expressions of MAIDAN-concept that pose a limitation for comprehending the concept when transmitted to a different linguoculture
Simulation of house prices for improved land valuation

The housing market is an important part of most economies in the developed world, but is also a significant factor in setting land valuation. Thus good housing models serve multiple purposes. Many studies use powerful statistical techniques to study pricing, but these are not so effective for handling large scale social or demographic shifts. Agent based modelling (ABM) is more flexible and therefore this paper describes a housing market simulation using ABM. A standard economic model is used for estimating utility, combined with a second price auction model and a decision forest for linking house features to price estimates at the beginning. Simulations are presented for a range of market temperatures, revealing different levels of price inflation.
Improving Motivation And Student Learning Outcomes Using Handout Based Student Centered Learning (SCL) Methods For Class VIII Students Of Junior High School 4 Gamping Sleman

The purpose of this study was to determine the impact of the application of learning using the Student Centere Learning (SCL) method based on Handout in increasing the motivation and learning outcomes of social studies of eighth grade students of Junior High School 4 Gamping Sleman. This research is a classroom action research which is a research activity conducted in a classroom that is intended to improve classroom learning. Research starts from observations in schools to find out student learning outcomes, collecting research data, to making research reports. This research was carried out at Junior High School 4 Gamping where in that location had never used Student Centered Learning based on Handout learning methods. Researchers use three instruments of data collection, namely Observation Sheets, questionnaires and Student Learning Outcomes Test by doing two cycles. Student Centered Learning (SCL) based Handout for Grade VIII Students of Junior High School 4 Gamping Sleman has been proven to improved social studies motivation and learned outcomes in the second cycle. This decision is proven by three criteria, namely motivation, learning outcomes and gain in the second cycle. The percentage of student motivation above 65 reached 75%. Learning outcomes 78% of all students have reached the minimum completeness criteria, and 83.3% of all students have achieved the criteria for the gain score in the medium category (above 0.3). These results indicate that the Student Centered Learning (SCL) Based Handout Method for Grade VIII Students of Junior High School 4 Gamping Sleman has been proven to increase the Motivation and Learned Outcomes of Social
La realidad virtual como herramienta en el proceso de aprendizaje del cerebro

En este articulo se presenta el estudio del cerebro y otras aplicacionesclinicas mediante las herramientas de navegacionde la realidad virtual (RV), la capacidad de captar la interaccionreal por medio de imagenes en 3D, proyectadas a travesde un neuronavegador, entendiendose por neuronavegaciona la produccion de imagenes por medio de un programa quesirva como herramienta diagnostica o terapeutica en neurocirugiau otras areas medico-quirurgicas, basandose en unsistema informatico que permite visualizar y dar seguimientomediante un ordenador de la posicion y la orientacion de lasestructuras cerebrales. De esta forma, se pueden desarrollarprocesos para el aprendizaje significativos, permitiendoasi el abordaje anatomico en modelos de tercera dimensiondel cerebro humano. Por lo tanto, la neuronavegacion conayuda de sistemas de realidad virtual como lo son las gafasVR, Leap Motion, dispositivos de control gestual capaces decapturar con gran precision los dedos en forma virtual e instantaneay las tecnicas que permitan una identificacion masprecisa hacen que el aprendizaje mejore y se logre mitigarostensiblemente el tiempo destinado al estudio para el desempenoy conocimientos de las partes que conforman el cerebrohumano y sus organos adyacentes.
The Research of SAR Imaging Based on Co-Prime Arrays Sampling

High resolution wide Swath (HRWS) is one of the major development directions of synthetic aperture radar (SAR). However, the high resolution in azimuth direction and the wide range swath impose contradicting requirements on system design, and the conventional SAR systems cannot meet these rising demands. The compressive sensing (CS) theory put forward in recent years provides a way to resolve the contradiction. In the CS framework, the signal can be reconstructed with a sampling rate below the Nyquist frequency, which means that signal can be acquired and processed at a lower rate. This paper provides a sparse sampling method based on the co-prime arrays. The sparse co-prime array is utilized to reduce the echo signal sampling requirement, which can provide more signal sampling space. As a result, high resolution and wide swath can be realized simultaneously. Simulations are performed to validate the presented algorithm.
SSL/TLS Vulnerability Detection Using Black Box Approach

Socket Secure Layer (SSL) and Transport Layer Security (TLS) are cryptographic protocols that provide data encryption to secure the communication over a network. However, in some cases, there are vulnerability found in the implementation of SSL/TLS because of weak cipher key, certificate validation error or session handling error. One of the most vulnerable SSL/TLS bugs is heartbleed. As the security is essential in data communication, this research aims to build a scanner that detect the SSL/TLS vulnerability by using black box approach. This research will focus on heartbleed case. In addition, this research also gathers information about existing SSL in the server. The black box approach is used to test the output of a system without knowing the process inside the system itself. For testing purpose, this research scanned websites and found that some of the websites still have SSL/TLS vulnerability. Thus, the black box approach can be used to detect the vulnerability without considering the source code and the process inside the application.
Internet des objets et interopérabilité des flux logistiques : état de l'art et perspectives

L’Internet des Objets (IdO) est un concept en pleine expansion ces dernieres annees. Il permet de relever certains defis technologiques auxquels la communaute fait face dans la vie de tous les jours. Cet article a pour objectif de presenter une revue de litterature sur les developpements recents des technologies de l’IdO et sur leur utilisation dans la gestion de processus et des pratiques logistiques. Il accorde une importance particuliere a la collecte et le traitement des donnees issues des capteurs et des puces RFID, et a leur utilisation pour une chaine logistique communicante, integrative, flexible et collaborative.