Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of the Cherenkov TOF whole-body PET scanner using GATE simulation. (Conception du scanner TEP Tchérenkov, corps entier, temps de vol en utilisant un logiciel de simulation GATE)

In this thesis we present the conception and performance studies of the foreseen Cherenkov whole-body positron emission scanner with time-of-flight potential (PECHE project). Our results and conclusions are based on the GATE simulation for following scanner configurations: lead fluoride crystal coupled with micro-channel-plate photomultiplier. This crystal is characterized by high density, transparency for photons in ultraviolet region, and one of the highest photoelectric fraction of about 46%. The chosen photomultiplier is fast, pixelized detector of a large size with a reasonable quantum efficiency, of 25% for 400 nm photon wavelength. Due to these properties, it is possible to create an efficient 511-keV gamma detector with a crystal thickness of the order of 10 mm(one interaction length) and hence minimize the length and dispersion of the photon trajectories, leading to better time resolution. We considered different configurations of the elementary detectors such as crystal thicknesses of 10 and 20 mm, the detector ring diameter of 80 and 90 cm, various options of the crystal coating (black, diffuse white and polished) and two optical interfaces (molecular bonding and conventional assembling with an optical gel). As an optimal configuration we chose a three-ring pet scanner with diameter of the ring 80 cm, 10 mm-thick crystal, protected with lead shielding. Molecular bonding gives better photo-collection if compare with configuration with optical gel. We estimated the potential of the foreseen scanner following the prescription of the NEMA NU 2-2012 standard. In particular, we evaluated the noise equivalent count rate (NECR), spatial resolution, image contrast recovery coefficients versus background variability for the NEMA image quality phantom. Reconstruction of images is done using iterative TOF algorithm implemented in the recently developed open source reconstruction platform CASToR. We concluded that due to an excellent TOF resolution a crystal-based Cherenkov whole-body scanner could achieve performances comparable with a conventional, scintillation-based tomograph. The use of the Cherenkov radiation allows to achieve even much better TOF resolution, but currently it is limited by the transit time spread of the existing photomultipliers, a low number of the detected optical photons, and a limited photon collection efficiency in a crystal. Limitations identified in this study will be addressed in the future development of the improved photodetector using the PbWO₄ radiator, which allows to conceive a whole-body PET scanner with an excellent TOF performance.
Sine-fitting software for IEEE Standards 1057 and 1241

The author demonstrates software that performs the calculations related to the sine-fit tests of IEEE Standard 1057-94 for digital waveform recorders and IEEE Standard 1241 for analog to digital converters, which is currently in preparation. He shows example outputs and explains how to use these outputs determine the important characteristics of the device under test (DUT).
Gait analysis for freezing detection in patients with movement disorder using three dimensional acceleration system

Due to the aging process, the aftereffect of an accident or the problems in brain, some people can experience difficulties in walking. It could be helpful in the treatment of these individuals suffering walking difficulties to monitor their movement. The unconstrained activity monitoring system (U-AMS) was developed to monitor the body's acceleration. It can be attached easily and doesn't interfere with daily activity. The hardware consists of 3-axis accelerometer, which records data for long periods of time. The movement image was simultaneously recorded by a camcorder. To collect data from U-AMS and analyze them, several programs were developed. The data were transferred to a computer by RS-232 module and displayed through viewing program made by MFC (Microsoft, USA). The analyzing program, which links viewing program to MATLAB (Mathworks, USA), analyzes the data to detect movement disorder. In this paper, freezing, which is characterized as start hesitation. , was the target disorder. Using the different characteristics in frequency domain between freezing and normal gait, freezing appearances were detected. By comparing with movement image, the accuracy of the freezing detection was verified to have a good performance.
Zeylanidiummanasiae, a new species of Podostemaceae based on molecular and morphological data from Kerala, India

Abstract We present the description of Zeylanidiummanasiae (Podostemaceae), a new species from Kerala, India, which is proposed based on molecular, macro- and micromorphological data. This species is characterised by its ribbon-like dichotomous thallus, floriferous shoots produced along the margins and dichotomy of the thallus, inflorescence with two bracts, unequal stigmatic lobes, ellipsoid fruits and large seeds.
A model based approach to assignment of myocardial fibre orientation

A model based method is presented to assign the fibre orientation in the human heart. The approach uses anatomical models, which are derivable from medical tomographic images. These models describe the geometry of the atria and ventricles. The approach extends the models by applying information from morphological measurements, which examine the fibre orientation for the different anatomical structures in the dissected normal hearts. The orientation of myocardial fibres is interpolated based on restrictions, which are determined with automatic methods inside and on the surface of myocardial structures. For each structure a different rulebased method is chosen. The method is illustrated with an exemplary anatomical model, which was constructed with techniques of digital image processing based on the Visible Female data set.
Event-based social media data mining

The exponential growth of social media data requires scalable, effective and robust technologies to manage and index them. Event is one of the most important cues to recall people’s past memory. With the development of Web 2.0, many event-based information sharing sites are appearing online, and a wide variety of events are scheduled and described by several social online services. The study of the relation between social media and events could leverage the event domain knowledge and ontologies to formulate the raised problems, and it could also exploit multimodal features to mine the patterns deeply, hence gain better performance compared with some other methods. In this thesis, we study the problem of mining relations between events and social media data. There are mainly three problems that are well investigated. The first problem is event enrichment, in which we investigate how to leverage the social media to events illustration. The second problem is event discovery, which focuses on discovering event patterns from social media stream. We propose burst detection and topic model based methods to find events from the spatial and temporal labeled social media. The third problem is visual event modeling, which studies the problem of automatically collecting training samples to model the visualization of events. The solution of collecting both of the positive and negative samples is also derived from the analysis of social media context. Thanks to the approaches proposed in this thesis, the intrinsic relationship between social media and events are deeply investigated, which provides a way to explore and organize online medias effectively.
Multiprocessor cache memory performance: characterization and optimization

Good cache memory performance is critical to achieving high CPU utilization in shared-memory multiprocessors. Reliably characterizing the performance of multiprocessor caches is hard, however, for it often requires experimental measurements on real machines across several workload domains. In this dissertation, we characterize some of the major sources of cache performance degradation, namely data sharing, operating system activity, and poor reuse of cache state in multiprogrammed workloads. We use data from a hardware performance monitor in a high-performance 4-CPU multiprocessor running scientific, engineering, software-development, and database workloads. While some of the misses on shared data result from the intrinsic inter-CPU communication required by the application, the rest, false sharing misses, are a consequence of the way data sharing interacts with multi-word cache blocks. We separate false sharing misses from the remaining, true sharing misses. We find that, while applications suffer false sharing, their miss rate is also affected by the poor spatial locality of true sharing. To reduce the miss rate, we then evaluate optimizations of the layout of shared data in cache blocks. We discover three major sources of operating system misses: instruction fetches, block operations (copy and clear), and process migration. Instruction misses are more commonplace than suspected. They are often caused by operating system self-interference in the cache. Hence, we propose optimizing the layout of the operating system code and consider increasing the cache associativity. The effect of misses in block operations can be partially eliminated by using special support for these operations. Finally, process migration misses are a consequence of the poor reuse of cache state in multiprogrammed workloads. In multiprogrammed workloads, the cache state built up by a process may be lost when the process is preempted, either because intervening processes destroy the state or because the process migrates to another CPU. We evaluate affinity scheduling, a technique that increases the reuse of cache state by encouraging processes to run on the CPUs whose caches keep useful state. We show that affinity scheduling attains most of the increase in cache state reuse possible in the workloads. Overall, affinity scheduling produces moderate speedups at nearly no cost.
Code Division Multiple Access applied to fiber optic data transmission

Abstract : The potential for applying Code Division Multiple Access techniques to achieve simultaneous multichannel data transmission over a fiber optic data link is investigated. Initially, a slow speed data link at 1 kilobits per second is examined to verify the ability to perform data correlation on a two data stream system. Finally, a design for a high speed link operating at 166.7 kilobits per second is proposed.
Simulation of Human Visual Search in Cluttered Backgrounds

Work in progress at Georgia Tech to develop a model of human pattern perception, visual search, and detection is reviewed. The model's algorithms are based on research on low-level visual processes. Recent advances in that field have led to the development of computational models of the image processing performed by the visual system from the cornea to the striate cortex. The model also incorporates recent advances from research on visual search. The organization of the model is described, and the results of some preliminary tests are presented.
A Parallel Approach For High Utility Patterns Mining From Distributed Databases

In recent years, the problem of high utility pattern mining become one of the most important research area in data mining. Traditional pattern mining algorithms may not find some most profitable, high priced patterns, due to their lower support. These algorithms reflect only statistical correlation, but it does not reflect semantic significance of the pattern. This gives reason to develop a mining model to find itemsets, which contributes to business organization with high profit. Hence, utility-based pattern mining technique has evolved and got much popularity in recent time. But all of the existing utility pattern mining algorithms are based on centralized database and today’s internet era databases are inherently distributed. This inherent distribution source of data and the voluminous in size emerges to develop scalable parallel and distributed algorithm for pattern mining. This paper proposed a parallel and distributed method for mining high utility patterns and also prune the irrelevant data or items. This method is designed in such a way so that it can efficiently generate high utility itemsets with less execution time in distributed environment. Keywords— Frequent pattern mining, High utility pattern mining, Distributed Database, Pruning.
Introduction to Information Retrieval: Scoring, term weighting, and the vector space model

Thus far, we have dealt with indexes that support Boolean queries: A document either matches or does not match a query. In the case of large document collections, the resulting number of matching documents can far exceed the number a human user could possibly sift through. Accordingly, it is essential for a search engine to rank-order the documents matching a query. To do this, the search engine computes, for each matching document, a score with respect to the query at hand. In this chapter, we initiate the study of assigning a score to a (query, document) pair. This chapter consists of three main ideas. We introduce parametric and zone indexes in Section 6.1, which serve two purposes. First, they allow us to index and retrieve documents by metadata, such as the language in which a document is written. Second, they give us a simple means for scoring (and thereby ranking) documents in response to a query. Next, in Section 6.2 we develop the idea of weighting the importance of a term in a document, based on the statistics of occurrence of the term. In Section 6.3, we show that by viewing each document as a vector of such weights, we can compute a score between a query and each document. This view is known as vector space scoring. Section 6.4 develops several variants of term-weighting for the vector space model. Chapter 7 develops computational aspects of vector space scoring and related topics.
Introduction to Privacy-Preserving Data Publishing: Concepts and Techniques

Gaining access to high-quality data is a vital necessity in knowledge-based decision making. But data in its raw form often contains sensitive information about individuals. Providing solutions to this problem, the methods and tools of privacy-preserving data publishing enable the publication of useful information while protecting data privacy. Introduction to Privacy-Preserving Data Publishing: Concepts and Techniques presents state-of-the-art information sharing and data integration methods that take into account privacy and data mining requirements. The first part of the book discusses the fundamentals of the field. In the second part, the authors present anonymization methods for preserving information utility for specific data mining tasks. The third part examines the privacy issues, privacy models, and anonymization methods for realistic and challenging data publishing scenarios. While the first three parts focus on anonymizing relational data, the last part studies the privacy threats, privacy models, and anonymization methods for complex data, including transaction, trajectory, social network, and textual data. This book not only explores privacy and information utility issues but also efficiency and scalability challenges. In many chapters, the authors highlight efficient and scalable methods and provide an analytical discussion to compare the strengths and weaknesses of different solutions.
Petri net-based semantics for verification and validation of workflow patterns

Modelling and performance analysis is one of the most important issues in business processes. Built on top of web protocols and XML language, web services are emerging as a high level framework for business-to-business relationships. UML can be used to model web services interactions and reengineered diagrams using Petri nets like semantics instead of state machines. Unfortunately, the standard has failed to define formal semantics. To address this issue, this paper provides a mapping from activities to Petri net models. Formalisations basing on UML and Petri nets of control-flow patterns for service composition are addressed. We propose a high-level class of Petri nets for describing the behaviour of scenarios of web services composition. Developed models support the strong dynamic and temporal aspects of these scenarios. Translation rules from flow patterns into Petri net models are provided. Finally an illustrative example is given to show the applicability of the proposed approach.
Survey of wireless network interfaces for mobile computing devices

The goal of mobile computing is to provide seamless connectivity to resources in a backbone wired network. It should make computing facilities at wireless end points, such as laptops, PDAs, and other hand held devices, comparable to their wire-line counterparts. The limited bandwidth and error prone nature of the wireless channel present many challenges to achieving this goal. Properly architected network interfaces can overcome some of the challenges. This paper examines system architectures of network interfaces used in several research test beds and commercial mobile computing systems. In particular, the paper examines the interface architectures of systems including Bell Labs's SWAN system, Xerox PARCTAB, Berkeley's Infopad, and Lucent's WaveLAN.
PM Electrical Machines Diagnostic - Methods Selected

Abstract—This paper presents a several diagnostic methods designed to electrical machines especially for permanent magnets (PM) machines. Those machines are commonly used in small wind and water systems and vehicles drives. Those methods are preferred by the author in periodic diagnostic of electrical machines. The special attention should be paid to diagnostic method of turn-to-turn insulation and vibrations. Both of those methods were created in Institute of Electrical Drives and Machines Komel. The vibration diagnostic method is the main thesis of author’s doctoral dissertation. This is method of determination the technical condition of PM electrical machine basing on its own signals is the subject of patent application No P.405669. Specific structural properties of machines excited by permanent magnets are used in this method electromotive force (EMF) generated due to vibrations. There was analysed number of publications which describe vibration diagnostic methods and tests of electrical machines with permanent magnets and there was no method found to determine the technical condition of such machine basing on their own signals.
On-Line Dense Visual Odometry with Depth Images using Normals Based Error Functions

In this thesis work, we present a method for dense visual odometry which uses depth images registration to compute the transformation between different poses. The registration algorithm proposed is able to match 3D point clouds extracted by depth images and can be seen as a variant of the generalized ICP algorithm based on a plane-to-plane metric. Substantially, we exploit the structure of the point clouds, in particular we take advantage of the information given by the surface normals of each point. A closed form solution is developed for the least-squares estimation problem used to register point clouds with normals. We developed a very fast implementation of the algorithm doing a fast computation of the normals by means of particular structures called integral images. Accepting to lose a bit of accuracy, these images allow the computation of a normal with constant time O(1). Furthermore, we speed up the data association phase by searching the correspondences in the images where the point clouds are reprojected. The images structure, rows and columns, is exploited to make data association reducing in this way the computation time. Despite a shallower search, the resulting set of correspondences is good. We have also implemented a merging method, based on the uncertainty of the Microsoft c © Kinect sensor, useful to reduce the number of points and the noise accumulated by the registration of multiple point clouds. Results obtained are showed taking in consideration experiments on different datasets representing different kinds of environment as domestic and office like environments. All datasets were acquired using a Microsoft c © Kinect or the Asus Xtion sensor.
The World is Open: How Web Technology Is Revolutionizing Education

Whether you are a scientist on a ship in Antarctic waters or a young girl in a Philippine village, you can learn whenever and whatever you want from whomever you are interested in learning it from. As technologies have become more available, even in the most remote reaches of the world, and as more people contribute a wealth of online resources, the education world has become open to anyone anywhere. In The World Is Open, education technology guru Curtis Bonk explores ten key trends that together make up the "WE-ALL-LEARN" framework for understanding the potential of technology's impact on learning in the 21st century: Web Searching in the World of e-Books E-Learning and Blended Learning Availability of Open Source and Free Software Leveraged Resources and OpenCourseWare Learning Object Repositories and Portals Learner Participation in Open Information Communities Electronic Collaboration Alternate Reality Learning Real-Time Mobility and Portability Networks of Personalized Learning In addition, this important resource contains compelling interviews that capture the diverse global nature of the open educational world from those who are creating new learning technologies as well as those who are using them to learn and teach in new ways. Using the dynamic "WE-ALL-LEARN" model, learners, educators, executives, administrators, instructors, and parents can tap into the power of Web technology and unleash a world of information.
Factors Influencing Usage of an Electronic Journal Collection at a Medium-Size University: An Eleven-Year Study

This paper reports the results of a quantitative analysis examining factors affecting electronic journal usage at the J.N. Desmarais Library of Laurentian University. This study covered an 11-year period, from 2000 to 2010. The number of full-text articles downloaded was compared to the size of the e-journal collection, the number of students, and the number of faculty members at the university, all of which exerted varying degrees of influence on the rate of use of e-journals. Pearson’s Product-Moment Correlation Coefficients were calculated to determine the strength of any existing linear relationship. Although the size of the e-journal collection did impact its level of use, there seems to be a “critical mass” which once reached will slow or stop any further increase in usage. Among the student population, the number of doctoral students demonstrated the strongest linear relationship to the use of the e-journal collection while the undergraduate population showed the least strong linear relationship. Faculty members were important users of the library’s e-journal collection but the linear relationship was not as strong as that observed for graduate students. In fact, faculty members demonstrated the least strong linear relationship of all segments of the Laurentian University community. It may be wise for the library to consult not only its faculty members but also its graduate students when seeking advice on collection building and management.