Efficient representation of texture details in medical images by fusion of Ripplet and DDCT transformed images

Purpose: To evaluate and compare the performance of Ripplet Type-1 transform and directional discrete cosine transform (DDCT) and their combinations for improved representation of MRI images while preserving its fine features such as edges along the smooth curves and textures. Methods: In a novel image representation method based on fusion of Ripplet type-1 and conventional/directional DCT transforms, source images were enhanced in terms of visual quality using Ripplet and DDCT and their various combinations. The enhancement achieved was quantified on the basis of peak signal to noise ratio (PSNR), mean square error (MSE), structural content (SC), average difference (AD), maximum difference (MD), normalized cross correlation (NCC), and normalized absolute error (NAE). To determine the attributes of both transforms, these transforms were combined to represent the entire image as well. All the possible combinations were tested to present a complete study of combinations of the transforms and the contrasts were evaluated amongst all the combinations. Results: While using the direct combining method (DDCT) first and then the Ripplet method, a PSNR value of 32.3512 was obtained which is comparatively higher than the PSNR values of the other combinations. This novel designed technique gives PSNR value approximately equal to the PSNR’s of parent techniques. Along with this, it was able to preserve edge information, texture information and various other directional image features. The fusion of DDCT followed by the Ripplet reproduced the best images. Conclusion: The transformation of images using Ripplet followed by DDCT ensures a more efficient method for the representation of images with preservation of its fine details like edges and textures.

POSE ESTIMATION AND 3D RECONSTRUCTION USING SENSOR FUSION

A camera maps 3-dimensional (3D) world space to a 2-dimensional (2D) image space. In the process it loses the depth information, i.e., the distance from the camera focal point to the imaged objects. It is impossible to recover this information from a single image. However, by using two or more images from different viewing angles this information can be recovered, which in turn can be used to obtain the pose (position and orientation) of the camera. Using this pose, a 3D reconstruction of imaged objects in the world can be computed. Numerous algorithms have been proposed and implemented to solve the above problem; these algorithms are commonly called Structure from Motion (SfM). State-of-the-art SfM techniques have been shown to give promising results. However, unlike a Global Positioning System (GPS) or an Inertial Measurement Unit (IMU) which directly give the position and orientation respectively, the camera system estimates it after implementing SfM as mentioned above. This makes the pose obtained from a camera highly sensitive to the images captured and other effects, such as low lighting conditions, poor focus or improper viewing angles. In some applications, for example, an Unmanned Aerial Vehicle (UAV) inspecting a bridge or a robot mapping an environment using Simultaneous Localization and Mapping (SLAM), it is often difficult to capture images with ideal conditions. This report examines the use of SfM methods in such applications and the role of combining multiple sensors, viz., sensor fusion, to achieve more accurate and usable position and reconstruction information. This project investigates the role of sensor fusion in accurately estimating the pose of a camera for the application of 3D reconstruction of a scene. The first set of experiments is conducted in a motion capture room. These results are assumed as ground truth in order to evaluate the strengths and weaknesses of each sensor and to map their coordinate systems. Then a number of scenarios are targeted where SfM fails. The pose estimates obtained from SfM are replaced by those obtained from other sensors and the 3D reconstruction is completed. Quantitative and qualitative comparisons are made between the 3D reconstruction obtained by using only a camera versus that obtained by using the camera along with a LIDAR and/or an IMU. Additionally, the project also works towards the performance issue faced while handling large data sets of high-resolution images by implementing the system on the Superior high performance computing cluster at Michigan Technological University.

Improving the Performance of Database-Centric Applications Through Program Analysis

Thesis (Ph.D, Computing) -- Queen's University, 2016-09-30 09:55:51.506

Agustina Bessa-Luís et la "con-fusion des genres"

Résumé : Cette étude cherche à déconstruire l’idée selon laquelle, dans l’œuvre de l’auteure Agustina Bessa-Luís, une caractérisation forte des personnages féminins conduit nécessairement à un effacement et à une absence de figures masculines fortes, ceci afin de démontrer que, la zone d’ombre dans laquelle ces hommes s’inscrivent, est symptomatique de ce que l’auteure définit comme le « refus d’un destin » au masculin. En effet, en dépeignant des personnages masculins fuyants et « borderline », l’auteure révèle chez ses personnages de papier un trouble dans le genre, lié à une « désorientation » résolument queer.   Mots-clés : Subversion/déconstruction, identités de genre, l’un/l’autre, Dandysme, queer.

Rôle du gène de fusion MLL-ENL dans le développement et le maintien du phénotype leucémique

Les translocations chromosomiques du gène MLL sont connues pour mener au développement de leucémies aiguës. La translocation avec un de ses partenaires de fusion les plus communs, ENL, peut engendrer des leucémies aiguës de plusieurs types différents pour cette même translocation. Une fois la leucémogenèse initiée par la fusion MLL-ENL, son rôle quant au maintien du phénotype leucémique n’est pas encore bien connu à ce jour. Pour mieux comprendre l’importance de MLL-ENL après la leucémogenèse, des cellules souches/progénitrices de sang de cordon ombilical humain purifiées ont ainsi été transduites par un virus exprimant le gène de fusion MLL-ENL bordé par des sites LoxP ainsi que le marqueur eGFP. Ces cellules infectées ont ensuite été injectées dans notre modèle de souris immunodéficientes irradiées et placées sous observation pendant 24 semaines pour voir le développement de leucémies aiguës. Elles ont alors été sacrifiées et les cellules la moelle osseuse et de la rate ont ensuite été analysées par cytométrie en flux pour déterminer si la xénogreffe a engendré une leucémie dans notre modèle ainsi que le phénotype de celle-ci. Les souris injectées par les cellules infectées par le MLL-ENL ont généré uniquement des leucémies lymphoïdes aiguës de type B. Les cellules de ces leucémies primaires isolées ont été par la suite infectées par un lentivirus exprimant la cre-recombinase et le marqueur BFP afin d’exciser le gène MLL-ENL des cellules leucémiques grâce aux sites LoxP. Les cellules ont ensuite été triées pour le marqueur BFP et injectées dans des souris secondaires pour de voir si les cellules leucémiques souches pouvaient toujours régénérer la leucémie. Les conséquences de l’absence de MLL-ENL dans le maintien du phénotype leucémique n’ont cependant pas pu être vérifiées à cause d’une erreur dans la séquence de la cre-recombinase, mais nous avons observé la régénération des leucémies secondaires.

Shopper Centric Category Management in Convenience Stores: a Qualitative Study

The literature shows that category management is an important concept and tool for retailers and suppliers, but that there is a trend to move to a more shopper-centric category management approach, linked to the shoppermarketing approach. However, the knowledge on this issue is scarce on some retailing sectors, like convenience stores. The present study is focused on convenience stores, with the main purpose of finding out to what extent non-major food retailers successfully adopt a shopper-centric category management. The study is relevant in order to evaluate if a more shopper-centric approach is adequate to smaller companies/stores. To accomplish that goal, an exploratory qualitative study was conducted among convenience store retailers and suppliers. Six semistructured face-to-face interviews were conducted with Commercial Directors and Trade Marketing Managers. This data was complemented with thirteen interviews with shopper marketing experts. The data was analyzed using thematic content analysis technique, identifying themes, categories, subcategories, units of meaning and relations. The results revealed that convenience store retailers use some of the principles and techniques of the shopper-marketing and shopper-centric category management approaches, which they do in a non-standardized and non-formal approach or process. Their suppliers (the manufacturers) do it in a more formal and structured manner, probably as a result of previous interaction with major supermarkets chains. Both direct and indirect evidences of a shopper-centric approach were found, which, however, were slight, discrete and not formal.

Inertial and magnetic sensors for upper limb kinematics: modeling, calibration, sensor fusion and clinical applications

The primary aim of the research activity presented in this PhD thesis was the development of an innovative hardware and software solution for creating a unique tool for kinematics and electromyographic analysis of the human body in an ecological setting. For this purpose, innovative algorithms have been proposed regarding different aspects of inertial and magnetic data elaboration: magnetometer calibration and magnetic field mapping (Chapter 2), data calibration (Chapter 3) and sensor-fusion algorithm. Topics that may conflict with the confidentiality agreement between University of Bologna and NCS Lab will not be covered in this thesis. After developing and testing the wireless platform, research activities were focused on its clinical validation. The first clinical study aimed to evaluate the intra and interobserver reproducibility in order to evaluate three-dimensional humero-scapulo-thoracic kinematics in an outpatient setting (Chapter 4). A second study aimed to evaluate the effect of Latissimus Dorsi Tendon Transfer on shoulder kinematics and Latissimus Dorsi activation in humerus intra - extra rotations (Chapter 5). Results from both clinical studies have demonstrated the ability of the developed platform to enter into daily clinical practice, providing useful information for patients' rehabilitation.

Enabling Human Centric Smart Campuses via Edge Computing and Connected Objects

Early definitions of Smart Building focused almost entirely on the technology aspect and did not suggest user interaction at all. Indeed, today we would attribute it more to the concept of the automated building. In this sense, control of comfort conditions inside buildings is a problem that is being well investigated, since it has a direct effect on users’ productivity and an indirect effect on energy saving. Therefore, from the users’ perspective, a typical environment can be considered comfortable, if it’s capable of providing adequate thermal comfort, visual comfort and indoor air quality conditions and acoustic comfort. In the last years, the scientific community has dealt with many challenges, especially from a technological point of view. For instance, smart sensing devices, the internet, and communication technologies have enabled a new paradigm called Edge computing that brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth. This has allowed us to improve services, sustainability and decision making. Many solutions have been implemented such as smart classrooms, controlling the thermal condition of the building, monitoring HVAC data for energy-efficient of the campus and so forth. Though these projects provide to the realization of smart campus, a framework for smart campus is yet to be determined. These new technologies have also introduced new research challenges: within this thesis work, some of the principal open challenges will be faced, proposing a new conceptual framework, technologies and tools to move forward the actual implementation of smart campuses. Keeping in mind, several problems known in the literature have been investigated: the occupancy detection, noise monitoring for acoustic comfort, context awareness inside the building, wayfinding indoor, strategic deployment for air quality and books preserving.

Development, mechanical characterization and qualification in liquid lead of stainless steels for structural applications in the future fission and fusion nuclear reactors

The research activity carried out in the Brasimone Research Center of ENEA concerns the development and mechanical characterization of steels conceived as structural materials for future fission reactors (Heavy Liquid Metal IV Generation reactors: MYRRHA and ALFRED) and for the future fusion reactor DEMO. Within this framework, two parallel lines of research have been carried out: (i) characterization in liquid lead of steels and weldings for the components of the IV Generation fission reactors (GIV) by means of creep and SSRT (Slow Strain Rate Tensile) tests; (ii) development and screening on mechanical properties of RAFM (Reduced Activation Ferritic Martensitic) steels to be employed as structural materials of the future DEMO fusion reactor. The doctoral work represents therefore a comprehensive report of the research carried out on nuclear materials both from the point of view of the qualification of existing (commercial) materials for their application in the typical environmental conditions of 4th generation fission reactors operating with lead as coolant, and from the point of view of the metallurgical study (with annexed microstructural and mechanical characterization of the selected compositions / Thermo Mechanical Treatment (TMT) options) of new compositional variants to be proposed for the “Breeding Blanket” of the future DEMO Fusion Reactor.

Optimization of an innovative T6 heat treatment for the AlSi10Mg alloy processed by Laser-based Powder Bed Fusion: effect on microstructure, mechanical properties, and tribological behavior

Laser-based Powder Bed Fusion (L-PBF) technology is one of the most commonly used metal Additive Manufacturing (AM) techniques to produce highly customized and value-added parts. The AlSi10Mg alloy has received more attention in the L-PBF process due to its good printability, high strength/weight ratio, corrosion resistance, and relatively low cost. However, a deep understanding of the effect of heat treatments on this alloy's metastable microstructure is still required for developing tailored heat treatments for the L-PBF AlSi10Mg alloy to overcome the limits of the as-built condition. Several authors have already investigated the effects of conventional heat treatment on the microstructure and mechanical behavior of the L-PBF AlSi10Mg alloy but often overlooked the peculiarities of the starting supersatured and ultrafine microstructure induced by rapid solidification. For this reason, the effects of innovative T6 heat treatment (T6R) on the microstructure and mechanical behavior of the L-PBF AlSi10Mg alloy were assessed. The short solution soaking time (10 min) and the relatively low temperature (510 °C) reduced the typical porosity growth at high temperatures and led to a homogeneous distribution of fine globular Si particles in the Al matrix. In addition, it increased the amount of Mg and Si in the solid solution available for precipitation hardening during the aging step. The mechanical (at room temperature and 200 °C) and tribological properties of the T6R alloy were evaluated and compared with other solutions, especially with an optimized direct-aged alloy (T5 alloy). Results showed that the innovative T6R alloy exhibits the best mechanical trade-off between strength and ductility, the highest fatigue strength among the analyzed conditions, and interesting tribological behavior. Furthermore, the high-temperature mechanical performances of the heat-treated L-PBF AlSi10Mg alloy make it suitable for structural components operating in mild service conditions at 200 °C.

Tumor burden as assessed by 18 F FDG PET scan as predictive biomarker for immune checkpoint blockers in advanced NSCLC - a multi centric study

Introduction Only a proportion of patients with advanced NSCLC benefit from Immune checkpoint blockers (ICBs). No biomarker is validated to choose between ICBs monotherapy or in combination with chemotherapy (Chemo-ICB) when PD-L1 expression is above 50%. The aim of the present study is to validate the biomarker validity of total Metabolic Tumor Volume (tMTV) as assessed by 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography ([18F]FDG-PET) Material and methods This is a multicentric retrospective study. Patients with advanced NSCLC treated with ICBs, chemotherapy plus ICBs and chemotherapy were enrolled in 12 institutions from 4 countries. Inclusion criteria was a positive PET scan performed within 42 days from treatment start. TMTV was analyzed at each center based on a 42% SUVmax threshold. High tMTV was defined ad tMTV>median Results 493 patients were included, 163 treated with ICBs alone, 236 with chemo-ICBs and 94 with CT. No correlation was found between PD-L1 expression and tMTV. Median PFS for patients with high tMTV (100.1 cm3) was 3.26 months (95% CI 1.94–6.38) vs 14.70 (95% CI 11.51–22.59) for those with low tMTV (p=0.0005). Similarly median OS for pts with high tMTV was 11.4 months (95% CI 8.42 – 19.1) vs 33.1 months for those with low tMTV (95% CI 22.59 – NA), p .00067. In chemo-ICBs treated patients no correlation was found for OS (p = 0.11) and a borderline correlation was found for PFS (p=0.059). Patients with high tMTV and PD-L1 ≥ 50% had a better PFS when treated with combination of chemotherapy and ICBs respect to ICBs alone, with 3.26 months (95% CI 1.94 – 5.79) for ICBs vs 11.94 (95% CI 5.75 – NA) for Chemo ICBs (p = 0.043). Conclusion tMTV is predictive of ICBs benefit, not to CT benefit. tMTV can help to select the best upfront strategy in patients with high tMTV.

Applied deep learning and data science with a human-centric and data-centric approach

The term Artificial intelligence acquired a lot of baggage since its introduction and in its current incarnation is synonymous with Deep Learning. The sudden availability of data and computing resources has opened the gates to myriads of applications. Not all are created equal though, and problems might arise especially for fields not closely related to the tasks that pertain tech companies that spearheaded DL. The perspective of practitioners seems to be changing, however. Human-Centric AI emerged in the last few years as a new way of thinking DL and AI applications from the ground up, with a special attention at their relationship with humans. The goal is designing a system that can gracefully integrate in already established workflows, as in many real-world scenarios AI may not be good enough to completely replace its humans. Often this replacement may even be unneeded or undesirable. Another important perspective comes from, Andrew Ng, a DL pioneer, who recently started shifting the focus of development from “better models” towards better, and smaller, data. He defined his approach Data-Centric AI. Without downplaying the importance of pushing the state of the art in DL, we must recognize that if the goal is creating a tool for humans to use, more raw performance may not align with more utility for the final user. A Human-Centric approach is compatible with a Data-Centric one, and we find that the two overlap nicely when human expertise is used as the driving force behind data quality. This thesis documents a series of case-studies where these approaches were employed, to different extents, to guide the design and implementation of intelligent systems. We found human expertise proved crucial in improving datasets and models. The last chapter includes a slight deviation, with studies on the pandemic, still preserving the human and data centric perspective.

High-strength steels manufactured via Laser Powder Bed Fusion: effect of post-process heat treatments and surface finishing on microstructure and mechanical properties

Laser Powder Bed Fusion (LPBF) permits the manufacturing of parts with optimized geometry, enabling lightweight design of mechanical components in aerospace and automotive and the production of tools with conformal cooling channels. In order to produce parts with high strength-to-weight ratio, high-strength steels are required. To date, the most diffused high-strength steels for LPBF are hot-work tool steels, maraging and precipitation-hardening stainless steels, featuring different composition, feasibility and properties. Moreover, LPBF parts usually require a proper heat treatment and surface finishing, to develop the desired properties and reduce the high roughness resulting from LPBF. The present PhD thesis investigates the effect of different heat treatments and surface finishing on the microstructure and mechanical properties of a hot-work tool steel and a precipitation-hardening stainless steel manufactured via LPBF. The bibliographic section focuses on the main aspects of LPBF, hot-work tool steels and precipitation-hardening stainless steels. The experimental section is divided in two parts. Part A addresses the effect of different heat treatments and surface finishing on the microstructure, hardness, tensile and fatigue behaviour of a LPBF manufactured hot-work tool steel, to evaluate its feasibility for automotive and racing components. Results indicated the possibility to achieve high hardness and strength, comparable to the conventionally produced steel, but a great sensitivity of fatigue strength on defects and surface roughness resulting from LPBF. Part B investigates the effect of different heat treatments on the microstructure, hardness, tensile and notch-impact behaviour of a LPBF produced precipitation-hardening stainless steel, to assess its feasibility for tooling applications. Results indicated the possibility to achieve high hardness and strength also through a simple Direct Aging, enabling heat treatment simplification by exploiting the microstructural features resulting from LPBF.

Influenza dei difetti sul comportamento a fatica della lega AlSi10Mg prodotta con Laser Powder Bed Fusion

La tesi in oggetto ha lo scopo di valutare la fattibilità di sviluppare, sulla base di dati sperimentali, un metodo previsionale per il comportamento a fatica della lega AlSi10Mg prodotta mediante Laser Powder Bed Fusion, adattabile a componenti di dimensioni qualsiasi. La lega è stata trattata con invecchiamento diretto (T5) ottimizzato per ottenere una parziale riduzione delle tensioni residue senza comprometterne la durezza. Partendo da prove di fatica a flessione rotante condotte seguendo il metodo statistico Stair-Case per la definizione della resistenza a fatica, si vuole correlare il difetto killer, ossia quello che innesca la rottura del provino, alla caratterizzazione dei difetti condotta pre-prova con tomografia computerizzata ad alta risoluzione (µCT). Il difetto killer, osservato sulle superfici di frattura, viene analizzato in termini di dimensione, posizione e forma. Contemporaneamente è stato sviluppato un metodo per l’analisi dei difetti ottenuta con µCT tale da poter identificare quelli considerati più pericolosi, sulla base dello stato tensionale del campione, di posizione e dimensione dei difetti. Inoltre, è stata eseguita una caratterizzazione microstrutturale sulle sezioni trasversali dei campioni per valutare la quantità, dimensione e forma dei difetti e confrontarla con i dati di µCT. Per mostrare la relazione tra le dimensioni del difetto killer e la resistenza a fatica è stato adottato il diagramma di Kitagawa-Takahashi, con il modello di El Haddad. Dal confronto tra le metodologie è stata riscontrata una buona correlazione tra i difetti individuati come pericolosi dai dati di µCT e quelli che hanno effettivamente portato a rottura il campione, osservati in frattografia, supportando quindi la possibilità di sviluppare un metodo previsionale del comportamento a fatica. Quantitativamente, le dimensioni dei difetti killer sono nell’intervallo 90-130 µm e si trovano ad una distanza massima dalla superficie di non oltre 250 µm.

Dataset Fusion application on deep learning Object Detection task

Application of dataset fusion techniques to an object detection task, involving the use of deep learning as convolutional neural networks, to manage to create a single RCNN architecture able to inference with good performances on two distinct datasets with different domains.