Piero Giacomelli

3D printing raised lot of attention from field outside the manufacturing one, in the last years. In these survey we will illustrate some recent advances of 3D printing technology
applied to the field of telemedicine and remote patient care. The potentiality of these technology will be detailed with out of the lab examples. Some crucial aspect as the regulation of these devices
and the need of some standards will also be discussed.

Cloud infrastructure has been one of the latest technologies in the e-health sector. Despite
many research studies focusing on the privacy of the e-health data stored on the cloud, the
ways of exchanging e-health information between client and cloud have not yet been fully
addressed. Moving from this initial consideration, in this chapter we evaluate the possibility
of using Message Oriented Middleware (MOMS) for exchanging data between the cloud
storage and the remote… Visualizza altro

Cloud infrastructure has been one of the latest technologies in the e-health sector. Despite
many research studies focusing on the privacy of the e-health data stored on the cloud, the
ways of exchanging e-health information between client and cloud have not yet been fully
addressed. Moving from this initial consideration, in this chapter we evaluate the possibility
of using Message Oriented Middleware (MOMS) for exchanging data between the cloud
storage and the remote device used in telemedicine and remote monitoring software. The
evaluation is done using a cloud testing environment and a low bandwidth connection
modem, and a simulation of 50 patients taking a 10 minutes 3Lead EGC test. Some possible
future directions on this architecture are suggested as well as some possible improvements. Meno dettagli

"Apache Mahout Cookbook" provides a fresh, scope-oriented approach to the Mahout world for both beginners as well as advanced users. The book gives an insight on how to write different data mining algorithms to be used in the Hadoop environment and choose the best one suiting the task in hand.

"Apache Mahout Cookbook" looks at the various Mahout algorithms available, and gives the reader a fresh solution-centered approach on how to solve different data mining tasks. The recipes start… Visualizza altro

"Apache Mahout Cookbook" provides a fresh, scope-oriented approach to the Mahout world for both beginners as well as advanced users. The book gives an insight on how to write different data mining algorithms to be used in the Hadoop environment and choose the best one suiting the task in hand.

"Apache Mahout Cookbook" looks at the various Mahout algorithms available, and gives the reader a fresh solution-centered approach on how to solve different data mining tasks. The recipes start easy but get progressively complicated. A step-by-step approach will guide the developer in the different tasks involved in mining a huge dataset. You will also learn how to code your Mahout’s data mining algorithm to determine the best one for a particular task. Coupled with this, a whole chapter is dedicated to loading data into Mahout from an external RDMS system. A lot of attention has also been put on using your data mining algorithm inside your code so as to be able to use it in an Hadoop environment. Theoretical aspects of the algorithms are covered for information purposes, but every chapter is written to allow the developer to get into the code as quickly and smoothly as possible. This means that with every recipe, the book provides the code for reusing it using Maven as well as the Maven Mahout source code.

By the end of this book you will be able to code your procedure to do various data mining tasks with different algorithms and to evaluate and choose the best ones for your tasks. Meno dettagli

Rethink the way you process messages in a stable, powerful and adaptive way, using the JBoss HornetQ messaging system.
Learn how to set up and code real-world, high performance message applications.
Real-world advanced medical scenario features as the main example that will lead you from the basics of enterprise messaging to the advanced features

CHRONIOUS is an Open, Ubiquitous and Adaptive Chronic Disease Management Platform for Chronic Obstructive Pulmonary Disease(COPD) Chronic Kidney Disease
(CKD) and Renal Insufficiency. It consists of several modules:
an ontology based literature search engine, a rule based decision support system, remote sensors interacting with lifestyle
interfaces (PDA, monitor touch screen) and a machine learning
module. All these modules interact each other to allow the
monitoring of two types… Visualizza altro

CHRONIOUS is an Open, Ubiquitous and Adaptive Chronic Disease Management Platform for Chronic Obstructive Pulmonary Disease(COPD) Chronic Kidney Disease
(CKD) and Renal Insufficiency. It consists of several modules:
an ontology based literature search engine, a rule based decision support system, remote sensors interacting with lifestyle
interfaces (PDA, monitor touch screen) and a machine learning
module. All these modules interact each other to allow the
monitoring of two types of chronic diseases and to help clinician
in taking decision for cure purpose. This paper illustrates how
some machine learning algorithms and a rule based decision
support system are used in the CHRONIOUS project, to
monitor chronic patient. We will analyse how a set of machine
learning algorithms can be used in smart devices to alert the
clinician in case of a patient health condition worsening trend. Meno dettagli

Chronic Obstructive Pulmonary Disease (COPD) is
a very prevalent disease which causes the deterioration of
patient’s quality of life and frequent hospitalizations.
Telemedicine can be a valid tool to reduce this burden.
CHRONIOUS is a FP7 EU project aimed to create a platform
for home monitoring of chronic ill patients.. It iscomposed of a
wearable system which is a sensorized T-shirt whichcollects
and transmits data coming from various sensors, among which… Visualizza altro

Chronic Obstructive Pulmonary Disease (COPD) is
a very prevalent disease which causes the deterioration of
patient’s quality of life and frequent hospitalizations.
Telemedicine can be a valid tool to reduce this burden.
CHRONIOUS is a FP7 EU project aimed to create a platform
for home monitoring of chronic ill patients.. It iscomposed of a
wearable system which is a sensorized T-shirt whichcollects
and transmits data coming from various sensors, among which
chestwall and abdomen respiratory volumes by means of two
inductive bands sewn into the T-shirt, a technique called
respiratory inductive plethysmography (RIP). The aim of this
study was to assess the functionality and stabilityof the RIP
included in the CHRONIOUS system for tidal volume (Vt)
measurement on home long term setting. COPD patients were
equipped with the CHRONIOUS system and were asked to
wear the T-shirt for 1 hour per day, 3 days a week,for 2
months. We analyzed the data of one COPD patient (72 years
old, BMI = 23 kg/m
2
, COPD stage III, FEV1% = 49%,
FEV1/FVC = 40%) who used the CHRONIOUS system for a
total of 40 days, performing a total of 17 acquisitions of one
hour each. We computed the average of Vt for each acquisition
session. Normalized Vt showed good stability in terms of
mean±sd during the whole period of acquisitions (1±0.3).
Moreover it has been possible to discriminate the breathing
activity in terms of compartmental contributions (abdominal
or thoracic). The preliminary results presented in this study
show the potential usefulness of this new telemedicine
approach for the long term monitoring of breathing pattern
parameters. Meno dettagli

presented at eTELEMED2012
Chronious is an Open, Ubiquitous and Adaptive Chronic Disease Management Platform for Chronic Obstructive Pulmonary Disease(COPD), Chronic Kidney Disease (CKD) and Renal Insufficiency. It consists of several modules: an ontology based literature search engine, a rule based decision support system, remote sensors interacting with lifestyle interfaces (PDA, monitor touch-screen) and a machine learning module. All these modules interact each other to allow the… Visualizza altro

presented at eTELEMED2012
Chronious is an Open, Ubiquitous and Adaptive Chronic Disease Management Platform for Chronic Obstructive Pulmonary Disease(COPD), Chronic Kidney Disease (CKD) and Renal Insufficiency. It consists of several modules: an ontology based literature search engine, a rule based decision support system, remote sensors interacting with lifestyle interfaces (PDA, monitor touch-screen) and a machine learning module. All these modules interact each other to allow the monitoring of two types of chronic diseases and to help clinician in taking decision for care purpose. This paper illustrates how the ontology search engine was created and fed and how some comparative test indicated that the ontology based approach give better results, on some estimation parameters, than the main reference web search engine. Meno dettagli

CHRONIOUS is an Open, Ubiquitous and Adaptive Chronic Disease Management Platform for Chronic Obstructive Pulmonary Disease(COPD) Chronic Kidney Disease (CKD) and Renal Insufficiency. It consists of several modules: an ontology based literature search engine, a rule based decision support system, remote sensors interacting with lifestyle interfaces (PDA, monitor touchscreen) and a machine learning module. All these modules interact each other to allow the monitoring of two types of chronic… Visualizza altro

CHRONIOUS is an Open, Ubiquitous and Adaptive Chronic Disease Management Platform for Chronic Obstructive Pulmonary Disease(COPD) Chronic Kidney Disease (CKD) and Renal Insufficiency. It consists of several modules: an ontology based literature search engine, a rule based decision support system, remote sensors interacting with lifestyle interfaces (PDA, monitor touchscreen) and a machine learning module. All these modules interact each other to allow the monitoring of two types of chronic diseases and to help clinician in taking decision for cure purpose. This paper illustrates how some machine learning algorithms and a rule based decision support system can be used in smart devices, to monitor chronic patient. We will analyse how a set of machine learning algorithms can be used in smart devices to alert the clinician in case of a patient health condition worsening trend. Meno dettagli

n these notes we address the study of the log-concave operator acting on Lucas Sequences of first kind. We will find for which initial values a generic Lucas sequence is log-concave, and using this we show when the same sequence is infinite log-concave. The main result will help to find the log-concavity of some well known recurrent sequences like Fibonacci and Mersenne. Some possible generalization for a complete classification of the log-concave operator applied to general linear recurrent… Visualizza altro

n these notes we address the study of the log-concave operator acting on Lucas Sequences of first kind. We will find for which initial values a generic Lucas sequence is log-concave, and using this we show when the same sequence is infinite log-concave. The main result will help to find the log-concavity of some well known recurrent sequences like Fibonacci and Mersenne. Some possible generalization for a complete classification of the log-concave operator applied to general linear recurrent sequences is proposed. Meno dettagli

In this paper a subset of High-Dimensional Random Apollonian networks, that we called Wheel Random Apollonian Graphs (WRAG), is considered. We show how to generate a Wheel Random Apollonian Graph from a wheel graph. We analyse some basic graph properties like vertices and edges cardinality, some question concerning cycles and the chromaticity in such type of graphs, we suggest further work on this type of graphs.