The Meixner process for financial data

The most famous Black-Scholes model is based on the assumption that the log-returns of financial data follow a normal distribution. Several studies performed show empirical evidence against such normality since the log-returns of most financial data show a significant leptokurtosis. The Meixner distribution is an infinitely divisible distribution and therefore a Lévy process can be associated with it, which is called the Meixner process. The Meixner process because of its simple and extreme flexible structure was proposed as a model for representing efficiently the empirical distributions of the log-returns of financial data. In this paper we studied the dynamics of the USD/EuR exchange rates. After testing that the normal distribution provides a poor fit to the log-returns of the exchange rates, we applied the Meixner model fitting its underlying distribution to the data. performing a number of statistical tests we showed that the Meixner distribution provides an almost perfect fit to the data

Personal Heart Health Monitoring Based on 1D Convolutional Neural Network

The automated detection of suspicious anomalies in electrocardiogram (ECG) recordings allows frequent personal heart health monitoring and can drastically reduce the number of ECGs that need to be manually examined by the cardiologists, excluding those classified as normal, facilitating healthcare decision-making and reducing a considerable amount of time and money. In this paper, we present a system able to automatically detect the suspect of cardiac pathologies in ECG signals from personal monitoring devices, with the aim to alert the patient to send the ECG to the medical specialist for a correct diagnosis and a proper therapy. The main contributes of this work are: (a) the implementation of a binary classifier based on a 1D-CNN architecture for detecting the suspect of anomalies in ECGs, regardless of the kind of cardiac pathology; (b) the analysis was carried out on 21 classes of different cardiac pathologies classified as anomalous; and (c) the possibility to classify anomalies even in ECG segments containing, at the same time, more than one class of cardiac pathologies. Moreover, 1D-CNN based architectures can allow an implementation of the system on cheap smart devices with low computational complexity. The system was tested on the ECG signals from the MIT-BIH ECG Arrhythmia Database for the MLII derivation. Two different experiments were carried out, showing remarkable performance compared to other similar systems. The best result showed high accuracy and recall, computed in terms of ECG segments and even higher accuracy and recall in terms of patients alerted, therefore considering the detection of anomalies with respect to entire ECG recordings

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

Il modello integrale di Dagum come funzione di sviluppo

In questa nota abbiamo mostrato che l'integrale del modello distributivo delle grandezze economiche proposto da Dagum può essere utilizzato come modello di sviluppo di fenomeni economico-sociali, in particolare come modello di sviluppo di popolazioni, alternativo al modello logistico di Pearl-Verhulst o alle sue generalizzazioni. Abbiamo anche messo in evidenza le analogie e le differenze tra i modelli, segnalando la maggiore flessibilità di quello di Dagum. Ci proponiamo in futuro di adattare i metodi di calcolo dei parametri proposti da Dagum per la densità al caso della ripartizione, nonché di adattare l'integrale di Dagum dotato di un ulteriore parametro (per tener conto del limite asintotico di crescita) alla dinamica delle popolazioni di alcuni paesi

Una "cerca" di dati sulle prospettive della gente. Navigazione nel grande flusso di informazioni provenienti dalle indagini UE

Very large amounts of data are generated by the interaction of people with social networks, smartphones, GPS, etc., creating the need for specific technologies (Internet of Things, Big Data Analysis and so on). Such data and tools are key instruments for transforming traditional cities into Smart Cities, as well as for regional development. At the international level, six operational areas are recognised for development: smart economy, people, governance, mobility, living, environment. A model that takes into account and combines these operational areas can be used to better understand the smartness level of a city, and to monitor its performance for assessing progress. European governments, like those of the whole world, are familiar with the importance of these tools to organise urban and extra-urban services in the light of the needs of citizens, their mobility, the environment; in a nutshell, all the elements that form the operational areas of smart cities. In addition to experimenting with algorithms for collecting and using data automatically provided by the devices that people use in their daily lives, information is also gathered about the needs and opinions of citizens. The latter, unlike any information of "technological" origin, can only be obtained through sample surveys, however extensive, and its use combined with technological data requires some precautions and preliminary operations: for starters, to identify the subjective information that interacts the most with objective data, and therefore useful for their optimal use. In this article, data from the European Social Survey 2017 is used to test a useful methodology. The European Social Survey (ESS) is an academically driven cross-national survey, whose aims are: - to monitor and interpret changing public attitudes and values within Europe and to investigate how they interact with Europe's ever-changing institutions, - to advance and consolidate improved methods of cross-national survey measurement in Europe and beyond, - to develop a series of European social indicators, including attitudinal criteria. In the 2017 edition, Round 8, the survey covered 23 countries (largely EU countries, along with Switzerland, Israel and the Russian Federation) employing the most rigorous methodologies in order to collect several information and opinions (more than 400 variables) from circa 44.400 European citizens. The key issue is to identify, in this stream of information, the variables that are actually important for joint analyses with other data (for example, regional economic indicators), taking into account that methods of statistical inference are not useful with Large and Big Data. Therefore, we chose to test multivariate statistical methods such as Categorical Principal Component Analysis and Neural Network Analysis

Identificazione di dati di prospettiva delle popolazioni europee nelle indagini UE

Very large amounts of data are generated by the interaction of people with social networks, smartphones, GPS, etc., creating the need for specific technologies (Internet of Things, Big Data Analysis and so on). Such data and tools are key instruments for transforming traditional cities into Smart Cities, as well as for regional development. At the international level, six operational areas are recognised for development: smart economy, people, governance, mobility, living, en-vironment. A model that considers and combines these operational areas can be used to better understand the smartness level of a city, and to monitor its performance for assessing progress. European governments, like those of the whole world, are familiar with the importance of these tools to organise urban and extra-urban services in the light of the needs of citizens, their mobili-ty, the environment; in a nutshell, all the elements that form the operational areas of smart cities. In addition to experimenting with algorithms for collecting and using data automatically provid-ed by the devices that people use in their daily lives, information is also gathered about the needs and opinions of citizens. The latter, unlike any information of "technological" origin, can only be obtained through sam-ple surveys, however extensive, and its use combined with technological data requires some precautions and preliminary operations: for starters, to identify the subjective information that interacts the most with objective data, and therefore useful for their optimal use. In this article, data from the European Social Survey 2017 are used to test a useful methodology. The European Social Survey (ESS) is an academically driven cross-national survey, whose aims are: - to monitor and interpret changing public attitudes and values within Europe and to investigate how they interact with Europe's ever-changing institutions, - to advance and consolidate improved methods of cross-national survey measurement in Eu-rope and beyond, - to develop a series of European social indicators, including attitudinal criteria. In the 2017 edition, Round 8, the survey covered 23 countries (largely EU countries, along with Switzerland, Israel and the Russian Federation) employing the most rigorous methodologies in order to collect several information and opinions (more than 400 variables) from circa 44.400 European citizens. The key issue is to identify, in this stream of information, the variables that are actually im-portant for joint analyses with other data (for example, regional economic indicators), consider-ing that methods of statistical inference are not useful with Large and Big Data. Therefore, we chose to test multivariate statistical methods such as Categorical Principal Component Analysis (CatPCA) and Artificial Neural Network Analysis, particularly Self-Organizing Maps

A Spell Checking Web Service API for Smart City Communication Platforms

The Internet of Things becomes Internet of Everything when in the process of communication machine-to-machine also intelligent forms of communication between human and machine are involved. Cities can be viewed as a microcosm of this interconnected system where ICT and emerging technologies can be enabling factors to transform cities in Smart Cities. Cities can take great advantage by using information intelligence to achieve important public-policy goals and, in particular, by enabling network communication channels between citizens and public administrators in order to provide information and online services in real time through platform systems rather than by means of humans, using Artificial Intelligence and Natural Language Processing techniques. This work was the first step of a wider project aimed at providing a Spell Checking Web Service API for Smart City communication platforms able to automatically select, among the large availability of open source spell checking tools, the most suitable tool based on the semantic structure of the specific textual data. The system should manage an enhanced Italian Vocabulary Database, specifically implemented to support all the tools of the system. The goal of the present work was to test, through an experimental research, the feasibility of the entire project by implementing a Spell Checking Prototype System designed to manage two selected spell checking tools. Results showed that the Spell Checking Prototype System significantly improves performances by allowing the user to select the most suitable tool for the specific semantic structure of the text. The system also enables to manage the list of exceptions, which continuously enhance the Italian Vocabulary Database. The experimentation proved scientific evidence of the validity of the project aimed at implementing a Spell Checking Web Service API in order to improve the quality of natural language data to be stored or processed in Smart City NCeSDP systems, through the use of existing spell checking tools

Rassegna sulla differenza media di distribuzioni teoriche continue

La differenza media,come indice di variabilità di una serie di osservazioni,in alternativa ad altre misure di variabilità, quali lo scarto quadratico e lo scarto semplice medio, è stata introdotta nella metodologia statistica da Corrado Gini nel 1912 .L'utilizzo della differenza media è stato per molto tempo limitato per due ordini di ragioni:la maggiore complessità del calcolo e la carenza di contributi inferenziali.A partire dal 2007 alcuni studiosi di statistica dell'Università di Bari hanno pubblicato una serie di contributi volti a colmare detta lacuna.Finalità di questo lavoro è quella di presentare in maniera sintetica detti contributi affiancandone altri del tutto nuovi,limitatamente alle distribuzioni teoriche continue

Managing a Smart City Integrated Model through Smart Program Management

Context. A Smart city is intended as a city able to offer advanced integrated services, based on information and communication technology (ICT) technologies and intelligent (smart) use of urban infrastructures for improving the quality of life of its citizens. This goal is pursued by numerous cities worldwide, through smart projects that should contribute to the realization of an integrated vision capable of harmonizing the technologies used and the services developed in various application domains on which a Smart city operates. However, the current scenario is quite different. The projects carried out are independent of each other, often redundant in the services provided, unable to fully exploit the available technologies and reuse the results already obtained in previous projects. Each project is more like a silo than a brick that contributes to the creation of an integrated vision. Therefore, reference models and managerial practices are needed to bring together the efforts in progress towards a shared, integrated, and intelligent vision of a Smart city. Objective. Given these premises, the goal of this research work is to propose a Smart City Integrated Model together with a Smart Program Management approach for managing the interdependencies between project, strategy, and execution, and investigate the potential benefits that derive from using them. Method. Starting from a Smart city worldwide analysis, the Italian scenario was selected, and we carried out a retrospective analysis on a set of 378 projects belonging to nine different Italian Smart cities. Each project was evaluated according to three different perspectives: application domain transversality, technological depth, and interdependences. Results. The results obtained show that the current scenario is far from being considered “smart” and motivates the adoption of a Smart integrated model and Smart program management in the context of a Smart city. Conclusions. The development of a Smart city requires the use of Smart program management, which may significantly improve the level of integration between the application domain transversality and technological depth

Factors Affecting Asbestosis Mortality Among Asbestos-Cement Workers in Italy

Objectives This study was performed with the aim of investigating the temporal patterns and determinants associated with mortality from asbestosis among 21 cohorts of Asbestos-Cement (AC) workers who were heavily exposed to asbestos fibres. Methods Mortality for asbestosis was analysed for a cohort of 13 076 Italian AC workers (18.1% women). Individual cumulative asbestos exposure index was calculated by factory and period of work weighting by the different composition of asbestos used (crocidolite, amosite, and chrysotile). Two different approaches to analysis, based on Standardized Mortality Ratios (SMRs) and Age-Period-Cohort (APC) models were applied. Results Among the considered AC facilities, asbestos exposure was extremely high until the end of the 1970s and, due to the long latency, a peak of asbestosis mortality was observed after the 1990s. Mortality for asbestosis reached extremely high SMR values [SMR: males 508, 95% confidence interval (CI): 446–563; females 1027, 95% CI: 771–1336]. SMR increased steeply with the increasing values of cumulative asbestos exposure and with Time Since the First Exposure. APC analysis reported a clear age effect with a mortality peak at 75–80 years; the mortality for asbestosis increased in the last three quintiles of the cumulative exposure; calendar period did not have a significant temporal component while the cohort effect disappeared if we included in the model the cumulative exposure to asbestos. Conclusions Among heaviest exposed workers, mortality risk for asbestosis began to increase before 50 years of age. Mortality for asbestosis was mainly determined by cumulative exposure to asbestos