Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and implementation of a reliable reconfigurable real-time operating system (R3TOS)

Twenty-first century Field-Programmable Gate Arrays (FPGAs) are no longer used for implementing simple “glue logic” functions. They have become complex arrays of reconfigurable logic resources and memories as well as highly optimised functional blocks, capable of implementing large systems on a single chip. Moreover, Dynamic Partial Reconfiguration (DPR) capability permits to adjust some logic resources on the chip at runtime, whilst the rest are still performing active computations. During the last few years, DPR has become a hot research topic with the objective of building more reliable, efficient and powerful electronic systems. For instance, DPR can be used to mitigate spontaneously occurring bit upsets provoked by radiation, or to jiggle around the FPGA resources which progressively get damaged as the silicon ages. Moreover, DPR is the enabling technology for a new computing paradigm which combines computation in time and space. In Reconfigurable Computing (RC), a battery of computation-specific circuits (“hardware tasks”) are swapped in and out of the FPGA on demand to hold a continuous stream of input operands, computation and output results. Multitasking, adaptation and specialisation are key properties in RC, as multiple swappable tasks can run concurrently at different positions on chip, each with custom data-paths for efficient execution of specific computations. As a result, considerable computational throughput can be achieved even at low clock frequencies. However, DPR penetration in the commercial market is still testimonial, mainly due to the lack of suitable high-level design tools to exploit this technology. Indeed, currently, special skills are required to successfully develop a dynamically reconfigurable application. In light of the above, this thesis aims at bridging the gap between high-level application and low-level DPR technology. Its main objective is to develop Operating System (OS)-like support for high-level software-centric application developers in order to exploit the benefits brought about by DPR technology, without having to deal with the complex low-level hardware details. The developed solution in this thesis is named as R3TOS, which stands for Reliable Reconfigurable Real-Time Operating System. R3TOS defines a flexible infrastructure for reliably executing reconfigurable hardware-based applications under real-time constraints. In R3TOS, the hardware tasks are scheduled in order to meet their computation deadlines and allocated to non-damaged resources, keeping the system fault-free at all times. In addition, R3TOS envisages a computing framework whereby both hardware and software tasks coexist in a seamless manner, allowing the user to access the advanced computation capabilities of modern reconfigurable hardware from a software “look and feel” environment. This thesis covers all of the design and implementation aspects of R3TOS. The thesis proposes a novel EDF-based scheduling algorithm, two novel task allocation heuristics (EAC and EVC) and a novel task allocation strategy…
The Use of Microsoft Kinect for Human Movement Analysis

The purpose of this study was to provide evidence of reliability and validity for the use of a Microsoft Kinect system to measure displacement in human movement analysis. Three dimensional (3D) video motion systems are commonly used to analyze human movement kinematics of body joints and segments for many diverse applications related to gait analysis, rehabilitation, sports performance, medical robotics, and biofeedback. These systems, however, have certain drawbacks pertaining to the use of markers, calibration time, number of cameras, and high cost. Microsoft Kinect systems create 3D images and are low cost, portable, not markers required, and easy to set up. They lack, however, evidence of reliability and validity for human movement kinematics analysis. Twenty-six participants were recruited for this study. Peak Motus version 9 and Microsoft Kinect system with customized skeleton software were used to collect data from each subject sitting on a platform moving horizontally at the speed of 2.4 meters per minute. The Peak Motus system demonstrated higher degree of reliability for all body joints when compared to the Kinect system. In terms of validity evidence, the Kinect system demonstrated a stronger agreement to the Peak Motus system for the left and right knee joints. The results of this study support the literature and indicate that the Kinect system has potential to be used as a tool to measure and analyze human movement kinematics.
Exploratory Data Analytics for Information Discovery in a Network Structure

Abstract : This report presents an analytic strategy for visual exploration of multidimensional data. Node position in a network structure is determined by projecting from the high-dimensional data (HDD) space to a low-dimensional latent space. Clustering of node position vectors may result for making inferences. Dimensionality reduction by feature extraction of HDD for visualization is performed using a parametric Student's t-distribution for stochastic neighbor embedding (t-SNE). The resultant t-SNE network of nodes for a Euclidean space can now be examined using visual analytics technology-navigation/interaction within the visualization of the data. Scene content is described using the Extensible 3-D (X3D) graphics application programming interface. The immersive profile of an X3D scene allows for navigation within the data for possible information discovery. Such an approach may provide for a better understanding of data and facilitate analytical reasoning that would otherwise be difficult in an exclusively textual context.
Enhanced Approximated SURF Model For Object Recognition

Computer vision applications like camera calibration, 3D reconstruction, and object recognition and image registration are becoming widely popular now a day. In this paper an enhanced model for speeded up robust features (SURF) is proposed by which the object recognition process will become three times faster than common SURF model The main idea is to use efficient data structures for both, the detector and the descriptor. The detection of interest regions is considerably speed-up by using an integral image for scale space computation. The descriptor which is based on orientation histograms is accelerated by the use of an integral orientation histogram. We present an analysis of the computational costs comparing both parts of our approach to the conventional method. Extensive experiments show a speed-up by a factor of eight while the matching and repeatability performance is decreased only slightly.
The Misplaced Adaptation to Individual Differences.

The current interest in an educational technology that stresses adaptation to individual student differences has resulted in such individualized systems as Individually Prescribed Instruction (IPI) and Computer Assisted Instruction (CAI) . However, such systems are not the answer to an avoidance of standardization of students. No one has yet resolved the basic dilemma between the cost in time-and-effort efficiency and the demands of test theory for validity and reliability of tests. This dilemma means that while good teaching items should have a low error factor in order to elicit the correct response and then reinforce it, good diagnostic items (needed for individualization) should not have a low error factor. Thus, good teaching items meet criteria incompatible with those met by good diagnostic items. This problem is not insurmountable, but none of the existing programs of individualized instruction have solved it. The most persuasive point against the existing programs is that they are individualized only in terms of what the student brings to the lesson; they still result in the production of uniformity. (MH) OAPARTMANT OF HMV% OLIGATION WILFAAI OFPUIWOFARMOAMON TWA URN RIPROOOCRO Num AS IMMO PROM THI MOON OR OROALMWMIN 10AMMMM IT FORM W WOW Oft OFINIONS VAUD 00 NOT NMI*ARMY RIFROPINT OPPICLM. MCI OF IOUCATION FOlITTION OA FOUCY THE MISPLACED ADAPTATION TO INDIVIDUAL DIFrERENCES1 JAMES C. HOLLAND UNIVERSITY OF PITTSBURGH Today there is a great deal of interest in an educational technology which stresses adaptation to individual differences. It is feared that programming and the increased processing of masses in the name of education will obliterate all divergence and individuality by making the student a mere replica of the standard student defined in our behavioral objectives. Emphasis on systems, such as Individually Prescribed Instruction or Computer Assisted Instruction, that adapt to differences is often taken as an answer to this problem. I suggest that it is not an answer. The fear of deadly uniformity is as great with so-called individualised instruction as without it. To adjust to individual differences in most IPI and CAI systems, continual small modifications of teaching-saquence are made as the result of repeated measures of individual differences. And, although this procedure is taken as "obviously" worthy, I suggest on the one hand, that there are little compelling data to support its "obvious" merit and on the other, that no one, as yet, has resolved a basic dilemma between the cost in efficiency (in terms of time and effort) and the demands of test theory for validity and reliability of tests. Caq limmq of testing. While the rationale for the design of teaching and test0) ing items in IPI and CAI is not often clearly stated and perhaps not $14 universally agreed upon, it seems that generally the rationale for teaching sequences draws directly on that of programmed instruction. First consider the question of cost efficiency versus reliability
Business Statistics Demystified

PART ONE: WHAT IS BUSINESS STATISTICS? Chapter 1: Statistics for Business Chapter 2: What Is Statistics? Chapter 3: What is Probability? PART TWO: PREPARING A STATISTICAL REPORT Chapter 4: What Is a Statistical Study? Chapter 5: Planning a Statistical Study Chapter 6: Getting the Data Chapter 7: Statistics Without Numbers: Graphs and Charts Chapter 8: Common Statistical Measures Chapter 9: A Difference That Makes a Difference: When Do Statistics Mean Something? Chapter 10: Reporting the Results PART THREE: STATISTICAL INFERENCE: BASIC PROCEDURES Chapter 11: Estimation: Summarizing Data About One Variable Chapter 12: Correlation and Regression Chapter 13: Group Differences: Analysis of Variance (ANOVA) and Designed Experiments Chapter 14: Nonparametric Statistics PART FOUR: MAKING BUSINESS DECISIONS Chapter 15: Creating Surveys Chapter 16: Forecasting Chapter 17: Quality Management APPENDIX A: BASIC MATH FOR STATISTICS APPENDIX B: ANSWERS TO QUIZZES AND EXAMS APPENDIX C: RESOURCES FOR LEARNING INDEX
Shared File Systems and Fibre Channel

Shared file systems like Cray's SFS, DEC's VAXcluster file system, and Oracle's Parallel Server exploit network-attached storage by creating serverless distributed file systems that allow efficient, simultaneous access to shared, network-attached storage devices. In the past, these shared file system designs relied on proprietary networkattached storage like DEC's CI network or higher-cost interfaces like HiPPI, or used software to emulate shared storage networks. With the advent of Fibre Channel, a highvolume, open standard in network-attached storage interfaces is now available. In this paper we will review past work in traditional distributed file systems like NFS and AFS and work in shared file systems by Cray, DEC, CMU and others. New file system architectures for shared network storage will also be described. We will give a brief overview of Fibre Channel technology, describing its protocol layers, how higher level protocols like IP and SCSI are mapped to this protocol, and the topologies supported. Finally we will sketch the future evolution of network-attached storage as it moves from high-end, high-capacity requirements into mid-range and lowerend desktop computing. We believe these trends may be affected by Fibre Channel’s potential to function as both a network and storage interface.
PEARP, the Meteo-France Ensemble Prediction system

PEARP (Prevision d’Ensemble ARPEGE) is the Meteo-France short-range Ensemble Prediction System based of the ARPEGE/IFS software. PEARP is a global system and the varying resolution of ARPEGE allows to produce with one single system high resolution probabilistic forecasts over Western Europe and ensemble products for TC tracks over the Tropical Atlantic area and Indian Ocean as well. Initial uncertainty is taken into account by coupling a small Ensemble Data assimilation System with singular vectors technique and a multi-physics approach is used to represent model error.
Computational Framework for Small Animal SPECT Imaging: Simulation and Reconstruction

Small animal Single Photon Emission Computed Tomography (SPECT) has been an invaluable asset in biomedical science since this non-invasive imaging technique allows the longitudinal studies of animal models of human diseases. However, the image degradation caused by non-stationary collimator-detector response and single photon emitting nature of SPECT makes it difficult to provide a quantitative measure of 3D radio-pharmaceutical distribution inside the patient. Moreover, this problem exacerbates when an intra-peritoneal X-ray contrast agent is injected into a mouse for low-energy radiotracers. In this dissertation, we design and develop a complete computational framework for the entire SPECT scan procedure from the radio-pharmaceutical injection, image acquisition, attenuation and scatter correction, and to the image reconstruction. Using this framework, we solve several challenging problems in small animal SPECT imaging. In particular, we perform an in-depth analysis of photon attenuation and scatter in small SPECT imaging and evaluate the performance of correction methods under various imaging circumstances in terms of image quality and computational complexity. Furthermore, we propose various techniques to accelerate correction methods using computational accelerators. This research also implements and validates a solution for solving the cross-talk contamination problem in I-123 and I-125 by using the ratio of detected low and high energy I-123 activity to separate the mixed low energy I-123 and I-125 activities using our simulation framework. Iterative reconstruction methods produce an accurate image using an accurate system
Psycholinguistic assessments of language processing in aphasia (PALPA)

PALPA has been designed as a comprehensive psycholinguistic assessment of language processing in adult acquired aphasia. Intended both as a clinical instrument and research tool, PALPA is a set of resource materials enabling the user to select language tasks that can be tailored to the investigation of an individual patient's impaired and intact abilities. The detailed profile that results can be interpreted within current cognitive models of language. The materials consist of sixty rigorously controlled tests of components of language structure such as orthography and phonology, word and picture semantics and morphology and syntax. The tests make use of simple procedures such as lexical decision, repetition and picture naming and have been designed to assess spoken and written input and output modalities. Particular attention has been paid to practical use of the tests in the clinic and comprehensive guides have been included that help to suggest which selection of test may be appropriate for each aphasic person. Each test is also accompanied by detailed instructions of how and why it was constructed, how to use it, and by presenter's forms and marking sheets.
Preprocessing and statistical/structural feature extraction for handwritten numeral recognition

In this paper, efficient preprocessing and feature extraction algorithms are presented to achieve high accuracy for handwritten numeral recognition. In preprocessing stage, a connectivity-preserving smoothing algorithm is proposed which is executed after normalization. Afterwards, multiresolution statistical features are extracted from stroke contour by directional decomposition and multiscale filtering. Meanwhile, structural features are represented by horizontal crossing counts and horizontal distances between boundary profiles and corresponding convex hulls. The extracted features not only have powerful discriminating ability, but also are less sensitive to shape variation. The extracted features are inputted into a multilayer neural network for training and classification. The efficiency of the proposed method has been demonstrated in recognition experiments on constrained and unconstrained handwritten numerals. The recognition rate on CENPARMI data is as high as 98.00%.
PASSWORD PRACTICE : The effect of training on password practice

There are several concerning issues with passwords today; one of them being weak passwords, but password management also plays a big role e.g. when the users reuses passwords over several services or don't change their passwords on a regular basis. With the usage of passwords for several aspects of our daily lives comes the responsibility of trying to mitigate these issues, a role that often falls on to the users themselves. The usage of guidelines has proved helpful in this regard but still lacks important aspects. This paper suggests the usage of education in the form of a lecture to help with the problem. In this paper we conducted a study of password leaks, a literature analysis of the area around passwords and perform some qualitative interviews with different kinds of people with varying education and usage of passwords. The results from these studies will then lay the foundation for the lecture in the experiment part of the paper, two experiment groups will be used, one given a lecture as education on the matter and one control group not given any education. The study has showed that the usage of a lecture can help increase the entropy, average length of user‟s passwords. These results can be interpreted together with another study that did a similar experiment to that a lecture can be a more efficient way to teach users about passwords.
Computer Simulation in Physics and Engineering

This work is a needed reference for widely used techniques and methods of computer simulation in physics and other disciplines, such as materials science. The work conveys both: the theoretical foundations of computer simulation as well as applications and "tricks of the trade", that often are scattered across various papers. Thus it will meet a need and fill a gap for every scientist who needs computer simulations for his/her task at hand. In addition to being a reference, case studies and exercises for use as course reading are included.
Decentralized Fault Detection and Diagnosis in Large Linear Stochastic Systems

Due to the informational constraints, the computation and implementation of the Decentralized Fault Detection and Diagnosis (DFDD) algorithms are very complex. In this paper, we propose a new method for DFDD in large linear stochastic dynamical systems using an unknown input observer estimator scheme. We show that the Kalman filter—Genaralized Likelihood Ratio (GLR) test combination with our decentralized observer—estimator is similar to the approach of Willsky and Jones in centralized situations.
Cloud Computing Trace Characterization and Synthetic Workload Generation

Abstract : This thesis researches cloud computing workload characteristics and synthetic workload generation. A heuristic presented in the work guides the process of workload trace characterization and synthetic workload generation. Analysis of a cloud trace provides insight into client request behaviors and statistical parameters. A versatile workload generation tool creates client connections, controls request rates, defines number of jobs, produces tasks within each job, and manages task durations. The test system consists of multiple clients creating workloads and a server receiving request, all contained within a virtual machine environment. Statistical analysis verifies the synthetic workload experimental results are consistent with real workload behaviors and characteristics.
A New Simplified Federated Single Sign-on System

Federated single sign-on (FSSO) provides single sign-on across multiple domains. The literature shows that current FSSO systems do not incorporate the authentication systems of desktop systems, web-based services/applications and non-web based services/applications. This is a challenge for the end-users because they need to be authenticated multiple times (by multiple authentication systems) to access all three services. The work presented in this MPhil thesis addresses this challenge by developing a new simplified FSSO system that allows end-users to access desktop systems, web-based services/applications and non-web based services/applications using one authentication process. This new system achieves this using two major components: an “Authentication Infrastructure Integration Program (AIIP)” and an “Integration of Desktop Authentication and Web-based Authentication (IDAWA). ” The AIIP acquires Kerberos tickets (for end-users who have been authenticated by a Kerberos single sign-on system in one network domain) from Kerberos single sign-on systems in different network domains without establishing trust between these Kerberos single sign-on systems. The IDAWA is an extension to the web-based authentication systems (i.e. the web portal), and it authenticates end-users by verifying the end-users’ Kerberos tickets. This research also developed new criteria to determine which FSSO system can deliver true single sign-on to the end-users (i.e. allowing end-users to access desktop systems, web-based services/applications and non-web based services/applications using one authentication process). The evaluation shows that the new simplified FSSO system (i.e. the combination of AIIP and IDAWA) can deliver true single sign-on to the endusers. In addition, the evaluation shows the new simplified FSSO system has advantages over existing FSSO systems as it does not require additional modifications to network domains’ existing non-web based authentication infrastructures (i.e. Kerberos single signon systems) and their firewall rules.