Si informano tutti gli utenti interessati che al seguente link è disponibile il programma PHD Plus:

Programma PHD+ 2016 (italiano)

PhD+ Programme 2016 (english)

Le informazioni per partecipare alla selezione possono essere trovate ai seguenti link:

Informazioni

Modalità di partecipazione

L’invito a partecipare al PhD+ è rivolto anche ai ricercatori e docenti dell’Ateneo.

Hours:
20 hours (5 credits)

Room:
Aula Riunioni del Dipartimento di Ingegneria dell'Informazione, via G. Caruso 16, Pisa – Ground Floor

Short Abstract:
In this short course we will expose methods used in reliability, availability, performability and survivability modeling and analysis of systems in practice. Non-state-space solution methods are often used to solve reliability block diagrams, fault trees and reliability graphs. Relatively efficient algorithms are known to handle systems with hundreds of components and have been implemented in many software packages. We will show the usage of these model types through practical examples and via the software package SHARPE. Nevertheless many practical problems cannot be handled by such algorithms. Bounding algorithms are then used in such cases as was done for a major subsystem of Boeing 787. Non-state-space methods derive their efficiency from the independence assumption that is often violated in practice. State space methods based on Markov chains, stochastic Petri nets, semi-Markov and Markov regenerative processes can be used to capture various kinds of dependencies among system components. Markov models, Markov Reward models and stochastic Petri nets will be illustrated through practical problems and using the SHARPE software package. However, the resulting state space explosion severely restricts the size of the problems that can be solved. Hierarchical and fixed-point iterative methods provide a scalable alternative that combines the strengths of state space and non-state-space methods and have been extensively used to solve real-life problems. The use of hierarchical and fixed point iterative methods will be also illustrated via large system examples and the SHARPE software package.

Course Contents in brief:

• Reliability and Availability Modeling in Practice
• Markov Chains and Stochastic Petri Nets in Performance and Reliability Modeling
• Performance and Reliability of Clouds
• Software aging and rejuvenation; Software Fault Tolerance via Environmental Diversity

Schedule:

• Day 1: 8.30-13.30
  • covered subjects: Definitions, Reliability Block Diagrams, Fault Trees, Reliability Graphs with Applications and the use of the SHARPE software package
• Day 2: 8.30-13.30
  • covered subjects: Markov Chains and Stochastic Petri Nets in Performance and Reliability Modeling with Applications and the use of the SHARPE software package
• Day 3: 8.30-13.30
  • covered subjects: Performance, Availability, Power Modeling and Optimization of clouds
• Day 4: 8.30-13.30
  • covered subjects: Software reliability, software aging and rejuvenation; software Fault Tolerance via Environmental Diversity
• Day 5: 9.00-13.00
  • Final exam

Hours:
16 hours (4 credits)

Room:
Aula Riunioni del Dipartimento di Ingegneria dell'Informazione, via G. Caruso 16, Pisa – Ground Floor

Short Abstract:
This lecture is dedicated to the introduction of design methods for RF and microwave circuits for wireless applications. It introduces the concepts of transmission line and its application as distributed electronics. Matching techniques together with Smith chart as well as "S" matrix will be introduced and illustrated on worked examples. Then passive devices, such as resonators, couplers, and filters will be studied and developed on several examples. It follows active circuits such Low Noise Amplifiers and Power Amplifiers. Noise figure and Nonlinear parameters will be introduced. Frequency up-converter and down-converter will be described too. Then, integrated antenna constraints will be discussed. Finally link budget and noise figure of a wireless system will be discussed.

Course Contents in brief:

• Introduction (1 hrs.)
  
  • Emergence of RF Wireless systems
  • Electromagnetic spectrum and RF regulations
  • Distributed versus lumped electronics
• Transmission Line Theory (2 hrs.)
  • Concept of transmission lines
  • RLCG Model
  • Planar transmission lines : Microstrip
• Tools for RF circuits (3 hrs.)
  
  • Smith diagram and matching techniques
  • S Matrix
  • Measurements of RF circuits
• Passive Devices (3 hrs.)
  
  • Power dividers
  • Coupler
  • Filters
• Active circuits (2 hrs.)
  
  • Model of Transistor
  • Low Noise Amplifier
  • Stability of LNA
  • Gain definition
• Noise Figure and Non-Linear Parameters (2 hrs.)
  
  • Noise Figure
  • Design for Constant Noise Figures
• Lab : VNA demonstration (2 hrs.)
• Conclusions and Future Issues (1 hrs.)

Schedule:

• Day 1 – 4 April 2016, 9:00 - 13:00
• Day 2 – 5 April 2016, 9:00 - 13:00
• Day 3 – 6 April 2016, 9:00 - 13:00
• Day 4 – 7 April 2016, 9:00 - 13:00

Hours:
20 hours (5 credits)

Room:
Aula Riunioni del Dipartimento di Ingegneria dell'Informazione, via G. Caruso 16, Pisa – Ground Floor

Short Abstract:
Multipole Analysis counts to the classical methods in Electromagnetics, and its outstanding mathematical and physical features are of practical importance for many areas of modern electromagnetic applications and developments. Of course, multipole techniques are not only used for analytically treating simple problems. Rather, they are applied to enhance the features of numerical methods (e.g., for the MultiLevel Fast Multipole Approach - MLFMA), for a very accurate probe-corrected near field antenna measurement, for investigating the general limits and features of radiating structures, or in the context of distinguishing very low quasi-stationary magnetic fields coming from the brain to those coming from external sources (Signal-Space Separation method), to mention just a few. Finally, multipole analysis allows a unique insight into - and thus deepens the understanding of - the mathematical and physical properties of electromagnetic fields.

After a brief introduction and motivation the course summarizes the derivation of the spherical-multipole expansion of the electromagnetic field including a discussion of its physical interpretation and low-frequency interpretation in case of a quasi-stationary magnetic field. In a kaleidoscopic manner then three examples of applications will be demonstrated: The process of radiation including the interpretation of radiated and reactive (non-radiated) energies, the spherical antenna near-field measurement, and the application of a spherical-multipole expansion for the noise reduction in sensoring bio-magnetic fields.

Course Contents in brief:

• Introduction (6 hrs.)
  
  • History and classical applications

  • Derivation of the spherical-multipole expansion

  • Physical interpretation as modes

  • Specialization to quasi-stationary magnetic field

• Radiated fields (5 hrs.)
  • Multipole interpretations of near-fields and far-fields

  • Inseparability of radiated and non-radiating field parts

  • What would be an optimal antenna?

• Spherical antenna near-field measurement (4 hrs.)
  • Basis outline of a measurement system

  • Summary of the multipole approach

  • Probe-corrected measurement system

• Noise reduction for bio-magnetic measurements (4 hrs.)
  • Bio-magnetic measurements

  • Example: Magnetoencephalography

  • Distinguishing between internal and external magnetic fields

• Summary, Conclusion and Outlook (1 hr.)

Schedule:

5 to 9 September, 2016: 9:00-13.00 each day

Hours:
16 hours (4 credits)

Room:
Aula Riunioni del Dipartimento di Ingegneria dell'Informazione, via G. Caruso 16, Pisa – Ground Floor

Short Abstract:
The ever-increasing demand for reliable and ubiquitous high-speed data communications and environment sensing services calls for new challenges in the design and the optimization of wireless networks, which may benefit from the adoption of sophisticated signal processing techniques at large. Recently, game theory has emerged as an effective framework for the network design, since it provides analytical tools to predict the outcome of interactions among rational entities.

This tutorial provides an overview of the relevant applications of game theory, focusing on state-of-the-art techniques for resource allocation in wireless and wired communication networks. In the first part, the very basics concepts are introduced by means of many simple examples, and special emphasis is put on how to translate a real-world problem to an analytical game model. In the second part, relevant applications of game theory to wireless networks design are reported, including power and rate control, bandwidth allocation, and spectrum sensing. Some clues will be given on how to extend such methods to MIMO, cognitive radio, and relay-assisted communications. The main focus will be on noncooperative techniques, although recent advances in the field of cooperative game theory will be also included in the discussion to provide a different perspective on certain classes of problems.

Course Contents in brief:

• Introduction and Motivation;
• Basics of noncooperative game theory:
  • historical notes
  • finite and infinite static games
  • potential games
  • supermodular games
  • generalized Nash games
  • dynamic games
  • repeated games
  • Bayesian games
• Basics of cooperative game theory:
  • Nash bargaining problems
  • Canonical coalitional games
  • Coalition formation games
• Discussion and perspectives

Schedule:

• 01 February 2016 – 9.00 to 13.00 (M. Luise)
• 02 February 2016 – 9.00 to 13.00 (L. Sanguinetti)
• 03 February 2016 – 9.00 to 13.00 (L. Sanguinetti)
• 04 February 2016 – 9.00 to 13.00 (L. Sanguinetti)

Hours:
15 hours (4 credits)

Room:
Aula Riunioni del Dipartimento di Ingegneria dell'Informazione, via G. Caruso 16, Pisa – Ground Floor

Short Abstract:
The course will focus on recent advances in electronics and ICT (Information Communication Technology) for Autonomous Driver Assistance Systems in new vehicle generations. Sensing technologies and HW-SW embedded systems (architecture, including mm-wave transceivers and antennas, and algorithm) for parking assistance, enhanced driver vision, collision avoidance, cruise control, tyre condition monitoring, will be discussed. To this aim, recent state of art in video- and radar-based systems will be reviewed. Automotive and railway example applications will be provided.

Course Contents in brief:

• Introduction: Research trends in Electronics and ICT for Autonomous Driver Assistance Systems in new vehicle generations
• Video-based systems for ADAS: visible and infrared cameras for vehicles, fish-eye lens for large field of view cameras, real-time HW-SW solutions (architecture and algorithms) for video mosaicking (all-around view in parking assistance), cameras distortion correction, image enhancement in bad light conditions, automatic recognition of road and traffic signs
• Automotive radars for ADAS: radar vs. LIDAR or video-camera systems, specifications for Short-range and Long-range automotive radars, FMCW radar, architecture partitioning (Radar mm-wave front-end and antenna, HW/SW platforms for Radar signal acquisition and processing), examples of automotive and railway radar transceivers at 10 GHz, 24 GHz and 77 GHz
• Tyre monitoring: smart sensors for tyre monitoring (pressure, temperature, acceleration), wireless tyre monitoring (transceiver front-end and sub-GHz antenna, microcontroller-base processing platform)
• Final course evaluation

Schedule:

• July 11, 2016 – 14.30 to 18.30
• July 12, 2016 – 9.00 to 13.30
• July 13, 2016 – 9.00 to 13.30, 14.30-16 final exam

Hours:
16 hours (4 credits)

Room:
Aula Riunioni del Dipartimento di Ingegneria dell'Informazione, via G. Caruso 16, Pisa – Ground Floor

Short Abstract:
One of the most revolutionary and challenging features of the next generation of robots will be physical human-robot interaction (pHRI). pHRI robots will be designed to coexist and cooperate with humans in applications such as assisted industrial manipulation, collaborative assembly, domestic work, teleoperation, rehabilitation or medical applications. Clearly, such robots must fulfill different requirements from those typically met in conventional industrial applications. This course aims at introducing the underlying concepts and necessary tools for the realization of an effective human-robot interaction.

Course Contents in brief:

• Versatility and stability in human motor behavior
  • Human musculoskeletal structure
  • Dynamic modeling of the contact stability in humans
  • Human intention estimation: real-time applications
• Impedance and force control
• Human-in-the-loop control of adaptive robots
  • Teleimpedance
  • Rehabilitation robotics
  • Prosthetics: softness by control.
• Robot learning for physical human-robot interaction
  • Introduction to robot learning
  • Learning from demonstration – A probabilistic approach
  • Robot learning for human-robot collaboration

Schedule:

• Session 1: 18/4/2016 --- time: 10-13 (Arash Ajoudani)
• Session 2: 19/4/2016 --- time: 10-13 (Arash Ajoudani)
• Session 3: 21/4/2016 --- time: 10-13 (Arash Ajoudani)
• Session 4: 22/4/2016 --- time: 10-12 (Arash Ajoudani)
• Session 5: 26/4/2016 --- time: 10-12 (Leonel Rozo)
• Session 6: 27/4/2016 --- time: 10-12 (Leonel Rozo)
• Session 7: 28/4/2016 --- time: 10-12 (Leonel Rozo)

Hours:
10 hours (3 credits)

Room:
Day 1: Aula Riunioni del Dipartimento di Ingegneria dell'Informazione, Largo Lucio Lazzarino, Pisa
Day 2 - Day 4: Aula Riunioni del Dipartimento di Ingegneria dell'Informazione, via G. Caruso 16, Pisa – Ground Floor

Short Abstract:
YARP is an open source platform that was developed for robot programming (www.yarp.it). It supports code re-use by providing a platform independent interface to the hardware and operating system and by supporting modular programming. The main features are a library for interprocess communication that promotes peer-to-peer communication (synchronous and asynchronous) and a plugin-system that allows extending YARP adding support for new protocols and devices. This course will introduce the main features of YARP and will show in practical examples how it can be used to control a humanoid robot. The course is organized as a set of tutorials; students are invited to bring their own laptop to follow the tutorials.

Course Contents in brief:

• Robotic middleware and component based programming. Introduction to YARP.
• Ports, Modules and threading.
• Interface Definition Languages in YARP, interoperability with ROS.
• Interfacing with OpenCV, image processing and motor control.

Schedule:

• May 10, 10:30-12:30
• May 13, 15:00-17:00
• May 18, 15:00-18:00
• May 20, 15:00-18:00

Hours:
20 hours (5 credits)

Room:
Day 1, Day 4: Aula Riunioni del Dipartimento di Ingegneria dell'Informazione, Largo Lucio Lazzarino, Pisa
Day 2, Day 3, Day 5: Aula Riunioni del Dipartimento di Ingegneria dell'Informazione, via G. Caruso 16, Pisa – Ground Floor

Short Abstract:
Big Data analytics is gaining large interest in both public and scientific agendas, because it has demonstrated that it is possible to extract valid information from a large amount of noisy data and to produce valuable information for decision makers. Applications of Big Data analytics can be found in a large variety of domains, including economics, physics, healthcare and biology. In this last domain, analytics have been used, for example, to predict climate change impact on species' distribution, to monitor the effect of overfishing on economy and marine biodiversity and to prevent ecosystems collapse.

In this course, practical applications of Big Data analytics will be shown, with focus on several signal processing and machine learning-based techniques. The course will clarify the general concepts behind these techniques, with an educational approach making these concepts accessible also to students with intermediate mathematical skills. The examples will regard real cases involving data that would have been unpractical to be human-analyzed and corrected, especially in the biology domain: time series forecasting, periodicities detection, comparison of geographical distribution maps, assessment of environmental similarities between different areas, global scale species distributions.

The above techniques have a general purpose applicability and the students will be able to use them in other domains too. Cloud computing, data sharing, experiments reproducibility, usage of data representation standards and most of the requirements of Big Data analytics systems will be explained and practiced. To execute the experiments, students will use a distributed e-Infrastructure (D4Science) developed at ISTI-CNR, also used in the European Laboratory on Big Data Analytics and Social Mining (SoBigData). This web-based platform hides the complexity of implementing Big Data analytics processes from scratch and allows students to concentrate on experiments configuration and output evaluation, and to understand models' behaviours. For this reason, the course does not require any programming skill and is suited for students in Computer Engineering, Informatics, Telecommunications engineering, Statistics and Computational Biology.

Course Contents in brief:

• Cloud and distributed computing
• Big Data analysis
• e-Infrastructures
• Large time series forecasting
• Automatic periodicities detection
• Neural Networks
• Large scale probabilistic GIS maps

Schedule:

from 2 to 6 May

• Day1 – Introduction and presentation of the tools: the D4Science e-Infrastructure, Cloud and distributed computing for community-provided processes – 9.00 – 13.00
• Day2 –Features analysis: Clustering, Principal Component Analysis and applications– 9.00 – 13.00
• Day3 –Large time series analysis: Fourier Transform, Short-Time Fourier Transform, Singular Spectrum Analysis and applications – 9.00 – 13.00
• Day4 –Large time Series forecasting: Caterpillar Singular Spectrum Analysis and applications– 9.00 – 13.00
• Day5 –Modeling: Neural Networks, Maximum Entropy, Geographical Distribution Maps and applications– 9.00 – 13.00

Hours:
20 hours (5 credits)

Room:
Aula Riunioni del Dipartimento di Ingegneria dell'Informazione, Largo Lucio Lazzarino 2, Pisa

Short Abstract:
Aim of this short course is to introduce basic notions and methodologies for modeling and control humanoid robots. Starting from the analysis of biped locomotion dynamics and the most popular approaches to walking motion generation, the course will also tackle the problem of generating motion of the whole humanoid body for accomplishing both locomotion and manipulation tasks. State of the art techniques for whole-body motion generation, possibly taking into account the presence of obstacles, will be illustrated. The concluding lectures of the course will deal with problems related to the interaction of humanoids with the real world recently challenging the robotics community.

Course Contents in brief:

• Humanoid robots timeline
• The dynamics of biped locomotion
  • Lagrangian dynamics and Newton-Euler equations of motion
  • contact modeling
  • stability analysis
• Generation of walking motion
  • ZMP-based
  • The Model Predictive Control approach
  • Capturability-based
• Whole-body motion generation
• Whole-body contact detection, force estimation and reaction strategies
• Motion planning
  • Footstep planning
  • Whole-body collision free motion generation
  • Task-driven whole-body motion generation
• Vision-based state estimation and control
  • Localization
  • Locomotion
  • Task execution

Schedule:

• Lunedì 16 Novembre ore 15.30-17.30
• Martedì 17 Novembre ore 09.30-12.30
• Martedì 24 Novembre ore 09.30-12.30
• Mercoledì 25 Novembre ore 09.30-11.30
• Lunedì 30 Novembre ore 15.30-17.30
• Martedì 01 Dicembre ore 09.30-12.30
• Lunedì 14 Dicembre ore 15.30-17.30
• Martedì 15 Dicembre ore 09.30-12.30