Structural analysis of combinatorial optimization problem characteristics and their resolution using hybrid approaches

Many combinatorial problems coming from the real world may not have a clear and well defined structure, typically being dirtied by side constraints, or being composed of two or more sub-problems, usually not disjoint. Such problems are not suitable to be solved with pure approaches based on a single programming paradigm, because a paradigm that can effectively face a problem characteristic may behave inefficiently when facing other characteristics. In these cases, modelling the problem using different programming techniques, trying to ”take the best” from each technique, can produce solvers that largely dominate pure approaches. We demonstrate the effectiveness of hybridization and we discuss about different hybridization techniques by analyzing two classes of problems with particular structures, exploiting Constraint Programming and Integer Linear Programming solving tools and Algorithm Portfolios and Logic Based Benders Decomposition as integration and hybridization frameworks.

Politiche pubbliche per la stagionalità del turismo da una prospettiva territoriale. Casi di studio in Scozia e in Sardegna

Rita Cannas presents a PhD thesis in Economics (Geo-Economic curriculum) which is titled “Public Policies for Seasonality in Tourism from a Territorial Perspective. Case Studies in Scotland and Sardinia”. The specific area of the research is public policies for contrasting seasonality in tourism in peripheral areas. Seasonality has seen such as a problem in terms of social and economics patterns especially for those local communities which are situated in peripheral areas. The research explores what, how and for who, public policies, that have been in place in Scotland and Sardinia over the last 10-5 years, are working and what kind of results these have produced. The research has empirical and theoretical implications for studying tourism seasonality. It aims to highlight the local supply patterns of the phenomenon investigated, and to improve knowledge about the strategies and the policies that have been adopted in the two territorial contexts (Scotland and Sardinia) for contrasting or modifying seasonality in tourism. The type of subject and the research questions have suggested the adoption of an interpretative theoretical perspective and a qualitative methodological approach, although a set of quantitative secondary data is also required for understanding main tourism's characteristics and for analyzing the specificity of seasonality. Interview with key actors of the local system in Scotland and Sardinia is the method chosen to collect primary data. In total the researcher has done 20 interviews in deep. Case studies are chosen both as unity of analysis and research strategy. The main findings of the research show a different and complex scenario about quality and quantity of public policies and strategies in tourism in the two case studies. The role of local resources is quite strategic on delivering tourism services and on counteracting seasonality. Events, festival are the main demand-side strategies. From a supply-side the principles policies are focused on quality of services, technology, high skills, sustainability. Partnership between public and private sector seems to be a fundamental way to work in order to attain changes and outcomes. The research has a strong research design, provides coherent results, and it has been done paying attention to the validation of the whole process.

Un approccio innovativo alla pianificazione della mobilità ciclabile

L’approccio innovativo di questa tesi alla pianificazione ciclabile consiste nell’integrare le linee guida per la redazione di un biciplan con aspetti, metodologie e strumenti nuovi, per rendere più efficace la programmazione di interventi. I limiti del biciplan risiedono nella fase di pianificazione e di monitoraggio, quindi, nel 1° capitolo, vengono esaminate le differenze esistenti tra la normativa americana (AASHTO) e quella italiana (D.P.R. 557/99). Nel 2° capitolo vengono analizzati gli indicatori usati nella fase di monitoraggio e la loro evoluzione fino alla definizione degli attuali indici per la determinazione del LOS delle infrastrutture ciclabili: BLOS e BCI. L’analisi è integrata con le nuove applicazioni di questi indici e con lo studio del LOS de HCM 2010. BCI e BISI sono stati applicati alla rete di Bologna per risolvere problemi di pianificazione e per capire se esistessero problemi di trasferibilità. Gli indici analizzati prendono in considerazione solo il lato offerta del sistema di trasporto ciclabile; manca un giudizio sui flussi, per verificare l’efficacia delle policy. Perciò il 3° capitolo è dedicato alla metodologia sul monitoraggio dei flussi, mediante l’utilizzo di comuni traffic counter per le rilevazioni dei flussi veicolari. Dal monitoraggio è possibile ricavare informazioni sul numero di passaggi, periodi di punta, esistenza di percorsi preferiti, influenza delle condizioni climatiche, utili ai progettisti; si possono creare serie storiche di dati per controllare l’evoluzione della mobilità ciclabile e determinare l’esistenza di criticità dell’infrastruttura. L’efficacia della pianificazione ciclabile è legata al grado di soddisfazione dell’utente e all’appetibilità delle infrastrutture, perciò il progettista deve conoscere degli elementi che influenzano le scelte del ciclista. Nel 4° capitolo sono analizzate le tecniche e gli studi sulle scelte dell’itinerario dei ciclisti, e lo studio pilota fatto a Bologna per definire le variabili che influenzano le scelte dei ciclisti e il loro peso.

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.