Computer simulations of two-dimensional colloidal crystals in confinement

Monte Carlo simulations are used to study the effect of confinement on a crystal of point particles interacting with an inverse power law potential in d=2 dimensions. This system can describe colloidal particles at the air-water interface, a model system for experimental study of two-dimensional melting. It is shown that the state of the system (a strip of width D) depends very sensitively on the precise boundary conditions at the two ``walls'' providing the confinement. If one uses a corrugated boundary commensurate with the order of the bulk triangular crystalline structure, both orientational order and positional order is enhanced, and such surface-induced order persists near the boundaries also at temperatures where the system in the bulk is in its fluid state. However, using smooth repulsive boundaries as walls providing the confinement, only the orientational order is enhanced, but positional (quasi-) long range order is destroyed: The mean-square displacement of two particles n lattice parameters apart in the y-direction along the walls then crosses over from the logarithmic increase (characteristic for $d=2$) to a linear increase (characteristic for d=1). The strip then exhibits a vanishing shear modulus. These results are interpreted in terms of a phenomenological harmonic theory. Also the effect of incommensurability of the strip width D with the triangular lattice structure is discussed, and a comparison with surface effects on phase transitions in simple Ising- and XY-models is made

Optimising thin-film solar cells by computer simulations

CIGS-Dünnschichtsolarzellen verbinden hohe Effizienz mit niedrigen Kosten und sind damit eine aussichtsreiche Photovoltaik-Technologie. Das Verständnis des Absorbermaterials CIGS ist allerdings noch lückenhaft und benötigt weitere Forschung. In dieser Dissertation werden Computersimulationen vorgestellt, die erheblich zum besseren Verständnis von CIGS beitragen. Es wurden die beiden Systeme Cu(In,Ga)Se2 und (Cu,In,Vac)Se betrachtet. Die Gesamtenergie der Systeme wurde in Clusterentwicklungen ausgedrückt, die auf der Basis von ab initio Dichtefunktionalrechnungen erstellt wurden. Damit war es möglich Monte Carlo (MC)-Simulationen durchzuführen. Kanonische MC-Simulationen von Cu(In,Ga)Se2 zeigen das temperaturabhängige Verhalten der In-Ga-Verteilung. In der Nähe der Raumtemperatur findet ein Übergang von einer geordneten zu einer ungeordneten Phase statt. Unterhalb separiert das System in CuInSe2 und CuGaSe2. Oberhalb existiert eine gemischte Phase mit inhomogen verteilten In- und Ga-Clustern. Mit steigender Temperatur verkleinern sich die Cluster und die Homogenität nimmt zu. Bei allen Temperaturen, bis hin zur Produktionstemperatur der Solarzellen (¼ 870 K), ist In-reiches CIGS homogener als Ga-reiches CIGS. Das (Cu,In,Vac)Se-System wurde mit kanonischen und großkanonischen MC-Simulationen untersucht. Hier findet sich für das CuIn5Se8-Teilsystem ein Übergang von einer geordneten zu einer ungeordneten Phase bei T0 = 279 K. Großkanonische Simulationen mit vorgegebenen Werten für die chemischen Potentiale von Cu und In wurden verwendet, um die Konzentrations- Landschaft und damit die sich ergebenden Stöchiometrien zu bestimmen. Stabilitätsbereiche wurden für stöchiometrisches CuInSe2 und für die Defektphasen CuIn5Se8 und CuIn3Se5 bei einer Temperatur von 174 K identifiziert. Die Bereiche für die Defektphasen sind bei T = 696 K verschwunden. Die Konzentrations-Landschaft reproduziert auch die leicht Cu-armen Stöchiometrien, die bei Solarzellen mit guten Effizienzen experimentell beobachtet werden. Die Simulationsergebnisse können verwendet werden, um den industriellen CIGS-Produktionspr

Mental states monitoring through passive Brain-Computer Interface systems

The monitoring of cognitive functions aims at gaining information about the current cognitive state of the user by decoding brain signals. In recent years, this approach allowed to acquire valuable information about the cognitive aspects regarding the interaction of humans with external world. From this consideration, researchers started to consider passive application of brain–computer interface (BCI) in order to provide a novel input modality for technical systems solely based on brain activity. The objective of this thesis is to demonstrate how the passive Brain Computer Interfaces (BCIs) applications can be used to assess the mental states of the users, in order to improve the human machine interaction. Two main studies has been proposed. The first one allows to investigate whatever the Event Related Potentials (ERPs) morphological variations can be used to predict the users’ mental states (e.g. attentional resources, mental workload) during different reactive BCI tasks (e.g. P300-based BCIs), and if these information can predict the subjects’ performance in performing the tasks. In the second study, a passive BCI system able to online estimate the mental workload of the user by relying on the combination of the EEG and the ECG biosignals has been proposed. The latter study has been performed by simulating an operative scenario, in which the occurrence of errors or lack of performance could have significant consequences. The results showed that the proposed system is able to estimate online the mental workload of the subjects discriminating three different difficulty level of the tasks ensuring a high reliability.

BabelNet e il problema della Word Sense Disambiguation

La Word Sense Disambiguation è un problema informatico appartenente al campo di studi del Natural Language Processing, che consiste nel determinare il senso di una parola a seconda del contesto in cui essa viene utilizzata. Se un processo del genere può apparire banale per un essere umano, può risultare d'altra parte straordinariamente complicato se si cerca di codificarlo in una serie di istruzioni esguibili da una macchina. Il primo e principale problema necessario da affrontare per farlo è quello della conoscenza: per operare una disambiguazione sui termini di un testo, un computer deve poter attingere da un lessico che sia il più possibile coerente con quello di un essere umano. Sebbene esistano altri modi di agire in questo caso, quello di creare una fonte di conoscenza machine-readable è certamente il metodo che permette di affrontare il problema in maniera più diretta. Nel corso di questa tesi si cercherà, come prima cosa, di spiegare in cosa consiste la Word Sense Disambiguation, tramite una descrizione breve ma il più possibile dettagliata del problema. Nel capitolo 1 esso viene presentato partendo da alcuni cenni storici, per poi passare alla descrizione dei componenti fondamentali da tenere in considerazione durante il lavoro. Verranno illustrati concetti ripresi in seguito, che spaziano dalla normalizzazione del testo in input fino al riassunto dei metodi di classificazione comunemente usati in questo campo. Il capitolo 2 è invece dedicato alla descrizione di BabelNet, una risorsa lessico-semantica multilingua di recente costruzione nata all'Università La Sapienza di Roma. Verranno innanzitutto descritte le due fonti da cui BabelNet attinge la propria conoscenza, WordNet e Wikipedia. In seguito saranno illustrati i passi della sua creazione, dal mapping tra le due risorse base fino alla definizione di tutte le relazioni che legano gli insiemi di termini all'interno del lessico. Infine viene proposta una serie di esperimenti che mira a mettere BabelNet su un banco di prova, prima per verificare la consistenza del suo metodo di costruzione, poi per confrontarla, in termini di prestazioni, con altri sistemi allo stato dell'arte sottoponendola a diversi task estrapolati dai SemEval, eventi internazionali dedicati alla valutazione dei problemi WSD, che definiscono di fatto gli standard di questo campo. Nel capitolo finale vengono sviluppate alcune considerazioni sulla disambiguazione, introdotte da un elenco dei principali campi applicativi del problema. Vengono in questa sede delineati i possibili sviluppi futuri della ricerca, ma anche i problemi noti e le strade recentemente intraprese per cercare di portare le prestazioni della Word Sense Disambiguation oltre i limiti finora definiti.

Geometrical optimization of a short-stem hip implant for the reduction of proximal stress shielding (ottimizzazione geometrica di uno stelo corto di protesi d?anca per la riduzione della schermatura del carico prossimale)

Nowadays the number of hip joints arthroplasty operations continues to increase because the elderly population is growing. Moreover, the global life expectancy is increasing and people adopt a more active way of life. For this reasons, the demand of implant revision operations is becoming more frequent. The operation procedure includes the surgical removal of the old implant and its substitution with a new one. Every time a new implant is inserted, it generates an alteration in the internal femur strain distribution, jeopardizing the remodeling process with the possibility of bone tissue loss. This is of major concern, particularly in the proximal Gruen zones, which are considered critical for implant stability and longevity. Today, different implant designs exist in the market; however there is not a clear understanding of which are the best implant design parameters to achieve mechanical optimal conditions. The aim of the study is to investigate the stress shielding effect generated by different implant design parameters on proximal femur, evaluating which ranges of those parameters lead to the most physiological conditions.

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

A Portable Image Overlay Projection Device for Computer-Aided Open Liver Surgery

Image overlay projection is a form of augmented reality that allows surgeons to view underlying anatomical structures directly on the patient surface. It improves intuitiveness of computer-aided surgery by removing the need for sight diversion between the patient and a display screen and has been reported to assist in 3-D understanding of anatomical structures and the identification of target and critical structures. Challenges in the development of image overlay technologies for surgery remain in the projection setup. Calibration, patient registration, view direction, and projection obstruction remain unsolved limitations to image overlay techniques. In this paper, we propose a novel, portable, and handheld-navigated image overlay device based on miniature laser projection technology that allows images of 3-D patient-specific models to be projected directly onto the organ surface intraoperatively without the need for intrusive hardware around the surgical site. The device can be integrated into a navigation system, thereby exploiting existing patient registration and model generation solutions. The position of the device is tracked by the navigation system’s position sensor and used to project geometrically correct images from any position within the workspace of the navigation system. The projector was calibrated using modified camera calibration techniques and images for projection are rendered using a virtual camera defined by the projectors extrinsic parameters. Verification of the device’s projection accuracy concluded a mean projection error of 1.3 mm. Visibility testing of the projection performed on pig liver tissue found the device suitable for the display of anatomical structures on the organ surface. The feasibility of use within the surgical workflow was assessed during open liver surgery. We show that the device could be quickly and unobtrusively deployed within the sterile environment.

Computer-assisted femoral head-neck osteochondroplasty using a surgical milling device an in vitro accuracy study

Surgical navigation might increase the safety of osteochondroplasty procedures in patients with femoroacetabular impingement. Feasibility and accuracy of navigation of a surgical reaming device were assessed. Three-dimensional models of 18 identical sawbone femora and 5 cadaver hips were created. Custom software was used to plan and perform repeated computer-assisted osteochondroplasty procedures using a navigated burr. Postoperative 3-dimensional models were created and compared with the preoperative models. A Bland-Altmann analysis assessing α angle and offset ratio accuracy showed even distribution along the zero line with narrow confidence intervals. No differences in α angle and offset ratio accuracy (P = 0.486 and P = 0.2) were detected between both observers. Planning and conduction of navigated osteochondroplasty using a surgical reaming device is feasible and accurate.