Statistical Mechanics of the Community Detection Problem: Theory and Application

We study phase transitions in spin glass type systems and in related computational problems. In the current work, we focus on the community detection problem when cast in terms of a general Potts spin glass type problem. We report on phase transitions between solvable and unsolvable regimes. Solvable region may further split into easy and hard phases. Spin glass type phase transitions appear at both low and high temperatures. Low temperature transitions correspond to an order by disorder type effect wherein fluctuations render the system ordered or solvable. Separate transitions appear at higher temperatures into a disordered: or an unsolvable) phases. Different sorts of randomness lead to disparate behaviors. We illustrate the spin glass character of both transitions and report on memory effects. We further relate Potts type spin systems to mechanical analogs and suggest how chaotic-type behavior in general thermodynamic systems can indeed naturally arise in hard-computational problems and spin-glasses. In this work, we also examine large networks: with a power law distribution in cluster size) that have a large number of communities. We infer that large systems at a constant ratio of q to the number of nodes N asymptotically tend toward insolvability in the limit of large N for any positive temperature. We further employ multivariate Tutte polynomials to show that increasing q emulates increasing T for a general Potts model, leading to a similar stability region at low T. We further apply the replica inference based Potts model method to unsupervised image segmentation on multiple scales. This approach was inspired by the statistical mechanics problem of community detection and its phase diagram. The problem is cast as identifying tightly bound clusters against a background. Within our multiresolution approach, we compute information theory based correlations among multiple solutions of the same graph over a range of resolutions. Significant multiresolution structures are identified by replica correlations as manifest in information overlaps. With the aid of these correlations as well as thermodynamic measures, the phase diagram of the corresponding Potts model is analyzed both at zero and finite temperatures. Optimal parameters corresponding to a sensible unsupervised segmentation correspond to the easy phase of the Potts model. Our algorithm is fast and shown to be at least as accurate as the best algorithms to date and to be especially suited to the detection of camouflage images

Computer vision models in surveillance robotics

2009/2010In questa Tesi, abbiamo sviluppato algoritmi che usano l’informazione visiva per eseguire, in tempo reale, individuazione, riconoscimento e classificazione di oggetti in movimento, indipendentemente dalle condizioni ambientali e con l’accurattezza migliore. A tal fine, abbiamo sviluppato diversi concetti di visione artificial, cioè l'identificazione degli oggetti di interesse in tutta la scena visiva (monoculare o stereo), e la loro classificazione. Nel corso della ricerca, sono stati provati diversi approcci, inclusa l’individuazione di possibili candidati tramite la segmentazione di immagini con classificatori deboli e centroidi, algoritmi per la segmentazione di immagini rafforzate tramite informazioni stereo e riduzione del rumore, combinazione di popolari caratteristiche quali quelle invarianti a fattori di scala (SIFT) combinate con informazioni di distanza. Abbiamo sviluppato due grandi categorie di soluzioni associate al tipo di sistema usato. Con camera mobile, abbiamo favorito l’individuazione di oggetti conosciuti tramite scansione dell’immagine; con camera fissa abbiamo anche utilizzato algoritmi per l’individuazione degli oggetti in primo piano ed in movimento (foreground detection). Nel caso di “foreground detection”, il tasso di individuazione e classificazione aumenta se la qualita’ degli oggetti estratti e’ alta. Noi proponiamo metodi per ridurre gli effetti dell’ombra, illuminazione e movimenti ripetitivi prodotti dagli oggetti in movimento. Un aspetto importante studiato e’ la possibilita’ di usare algoritmi per l’individuazione di oggetti in movimento tramite camera mobile. Soluzioni efficienti stanno diventando sempre piu’ complesse, ma anche gli strumenti di calcolo per elaborare gli algoritmi sono piu’ potenti e negli anni recenti, le architetture delle schede video (GPU) offrono un grande potenziale. Abbiamo proposto una soluzione per architettura GPU di una gestione delle immagini di sfondo, al fine di aumentare le prestazioni di individuazione. In questa Tesi abbiamo studiato l’individuazione ed inseguimento di persone for applicazioni come la prevenzione di situazione di rischio (attraversamento delle strade), e conteggio per l’analisi del traffico. Noi abbiamo studiato questi problemi ed esplorato vari aspetti dell’individuazione delle persone, gruppi ed individuazione in scenari affollati. Comunque, in un ambiente generico, e’ impossibile predire la configurazione di oggetti che saranno catturati dalla telecamera. In questi casi, e’ richiesto di “astrarre il concetto” di oggetti. Con questo requisito in mente, abbiamo esplorato le proprieta’ dei metodi stocastici e mostrano che buoni tassi di classificazione possono essere ottenuti a condizione che l’insieme di addestramento sia abbastanza grande. Una struttura flessibile deve essere in grado di individuare le regioni in movimento e riconoscere gli oggetti di interesse. Abbiamo sviluppato una struttura per la gestione dei problemi di individuazione e classificazione. Rispetto ad altri metodi, i metodi proposti offrono una struttura flessibile per l’individuazione e classificazione degli oggetti, e che puo’ essere usata in modo efficiente in diversi ambienti interni ed esterni.XXII Cicl

Sensor Data Integrity Verification for Real-time and Resource Constrained Systems

Sensors are used in multiple applications that touch our lives and have become an integral part of modern life. They are used in building intelligent control systems in various industries like healthcare, transportation, consumer electronics, military, etc. Many mission-critical applications require sensor data to be secure and authentic. Sensor data security can be achieved using traditional solutions like cryptography and digital signatures, but these techniques are computationally intensive and cannot be easily applied to resource constrained systems. Low complexity data hiding techniques, on the contrary, are easy to implement and do not need substantial processing power or memory. In this applied research, we use and configure the established low complexity data hiding techniques from the multimedia forensics domain. These techniques are used to secure the sensor data transmissions in resource constrained and real-time environments such as an autonomous vehicle. We identify the areas in an autonomous vehicle that require sensor data integrity and propose suitable water-marking techniques to verify the integrity of the data and evaluate the performance of the proposed method against different attack vectors. In our proposed method, sensor data is embedded with application specific metadata and this process introduces some distortion. We analyze this embedding induced distortion and its impact on the overall sensor data quality to conclude that watermarking techniques, when properly configured, can solve sensor data integrity verification problems in an autonomous vehicle.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/167387/3/Raghavendar Changalvala Final Dissertation.pdfDescription of Raghavendar Changalvala Final Dissertation.pdf : Dissertatio

Experiments on Visual Acuity and the Visibility of Markings on the Ground in Long-duration Earth-Orbital Space Flight

Visual acuity and visibility of markings on ground in long duration earth orbital space fligh

Basic Astronomy Labs

Providing the tools and know-how to apply the principles of astronomy first-hand, these 43 laboratory exercises each contain an introduction that clearly shows budding astronomers why the particular topic of that lab is of interest and relevant to astronomy. About one-third of the exercises are devoted solely to observation, and no mathematics is required beyond simple high school algebra and trigonometry.Organizes exercises into six major topics—sky, optics and spectroscopy, celestial mechanics, solar system, stellar properties, and exploration and other topics—providing clear outlines of what is involved in the exercise, its purpose, and what procedures and apparatus are to be used. Offers variations on standard and popular exercises, and includes many that are new and innovative, such as The Messier List which helps users discover basic facts about the Milky Way Galaxy by plotting these objects on a star chart; Motions of Earth demonstrates just how fast the Earth is moving through space and in which direction it is going, and; Radioactivity and Time which measures the half-life of a short-lived isotope, and consider radioactive dating and heating of celestial bodies. Includes a guide to astronomical pronunciations, a guide to the constellations, spectral classifications, quotes on science, and more. For astronomers

Up-scalable plasmonic and diffractive nanostructures

Since most of the academic photonic and plasmonic nanostructures are based on slow and expensive electron beam lithography processes, there is a need for innovative alternatives suitable for industrial manufacturing. Large areas need to be patterned with a high throughput, which is for example achieved with roll-to-roll machines. Up-scalable designs of photonic and plasmonic nanostructures are therefore studied in this thesis. Typical industrial processes include embossing and evaporation, which are consequently used throughout the thesis. I propose oblique evaporation of high refractive index materials to render binary gratings highly efficient for first order transmission. Zinc sulfide coatings are employed to diffract close to 70% of unpolarized green light. Simulations further show that they can be encapsulated to protect them from environmental influences like humidity, wear or dust, while retaining their exceptional diffractive properties, which is very appealing for outdoor applications. I also show that thin metallic coatings can attain similar efficiencies for TE polarized light. The effect is asymmetric and shows a maximum at the Wood-Rayleigh anomaly, which results in orientation dependent coloration of the zero order as well as first order transmittances. A large part of the standard RGB gamut can be covered through proper adjustment of the grating parameters. Combination of zero order and first order effects allows creation of color appearances that switch when rotating or flipping the device. I finally present how floating images become apparent when a patterned light source like e.g. a mobile phone is used in conjunction with the metallized grating. Direct transfer of plasmonic technology from universities to industry is often not possible: in academia, metallic nanostructures often require a lateral resolution of a few nanometers, which is challenging to achieve in up-scalable processes. Thicknesses on the other hand can be controlled in this regime using evaporation techniques, which are hence powerful methods for high-throughput production. In this thesis, Fano-resonant, U-shaped nanowires are created with oblique metal deposition. In order to make them available for mass-production, aluminum is chosen as the plasmonic material. The surface integral equation method is used to investigate near-fields and charge distributions, which shed light onto the physics behind the present resonances. A surface plasmon polariton is found to couple to a localized plasmonic mode with a hexapolar charge distribution. It is finally shown that the Fano-resonance can be accurately tuned by adapting evaporation angle and metal thickness. These two parameters can easily be accessed and would allow for good control over the optical response even in an industrial environment. The applicability of the above insights is then demonstrated by creating a strain sensor. To that end, the process is transferred to a stretchable polymer and when elongating the structure perpendicular to the wires, the polymeric spacing between them is expanded. The sensitivity of the Fano-resonance to this change in inter-wire distance is investigated and a strong damping is observed. Through careful design, a clearly visible color switch from purple to green is achieved for elongations less than 20%. The sensor was deemed to be very durable, as no deterioration in the color or the spectral response was observed even after several strain cycles

Purposive three-dimensional reconstruction by means of a controlled environment

Retrieving 3D data using imaging devices is a relevant task for many applications in medical imaging, surveillance, industrial quality control, and others. As soon as we gain procedural control over parameters of the imaging device, we encounter the necessity of well-defined reconstruction goals and we need methods to achieve them. Hence, we enter next-best-view planning. In this work, we present a formalization of the abstract view planning problem and deal with different planning aspects, whereat we focus on using an intensity camera without active illumination. As one aspect of view planning, employing a controlled environment also provides the planning and reconstruction methods with additional information. We incorporate the additional knowledge of camera parameters into the Kanade-Lucas-Tomasi method used for feature tracking. The resulting Guided KLT tracking method benefits from a constrained optimization space and yields improved accuracy while regarding the uncertainty of the additional input. Serving other planning tasks dealing with known objects, we propose a method for coarse registration of 3D surface triangulations. By the means of exact surface moments of surface triangulations we establish invariant surface descriptors based on moment invariants. These descriptors allow to tackle tasks of surface registration, classification, retrieval, and clustering, which are also relevant to view planning. In the main part of this work, we present a modular, online approach to view planning for 3D reconstruction. Based on the outcome of the Guided KLT tracking, we design a planning module for accuracy optimization with respect to an extended E-criterion. Further planning modules endow non-discrete surface estimation and visibility analysis. The modular nature of the proposed planning system allows to address a wide range of specific instances of view planning. The theoretical findings in this work are underlined by experiments evaluating the relevant terms

Time, Space and Agency: A Dynamical Approach to Narrative in New-Media Artwork

This thesis proposes a dynamical approach to narrative creation as found in the so-called new-media art field. It focuses on catastrophic models in order to conceptualise, analyse, and create narrative forms with multiple media and diverse formats. It deals with the transmedial nature of story and the phenomena that make it so. In that respect it treats narrative as a basic mechanism for understanding the real world and communicate meaningful artistic forms. The dynamical models proposed here are applied on current and long-standing narrative inquiries by the author, and their effectiveness in constructing multimedia narratives is investigated. The results are presented in the practical aspect of this research which focuses mainly on using the proposed modelling narrative techniques in order to compose and effectively communicate, through contemporary art practices and the use of 3D game engine platforms, narrative forms framed in the new-media art field

KINE[SIS]TEM'17 From Nature to Architectural Matter

Kine[SiS]tem – From Kinesis + System. Kinesis is a non-linear movement or activity of an organism in response to a stimulus. A system is a set of interacting and interdependent agents forming a complex whole, delineated by its spatial and temporal boundaries, influenced by its environment. How can architectural systems moderate the external environment to enhance comfort conditions in a simple, sustainable and smart way? This is the starting question for the Kine[SiS]tem’17 – From Nature to Architectural Matter International Conference. For decades, architectural design was developed despite (and not with) the climate, based on mechanical heating and cooling. Today, the argument for net zero energy buildings needs very effective strategies to reduce energy requirements. The challenge ahead requires design processes that are built upon consolidated knowledge, make use of advanced technologies and are inspired by nature. These design processes should lead to responsive smart systems that deliver the best performance in each specific design scenario. To control solar radiation is one key factor in low-energy thermal comfort. Computational-controlled sensor-based kinetic surfaces are one of the possible answers to control solar energy in an effective way, within the scope of contradictory objectives throughout the year.FC