Miracle-dz/UniFAR-FTUs huggingface dataset:
A Tag-Based, Logical Access-Control Framework for Personal File Sharing

People store and share ever-increasing numbers of digital documents, photos, and other files, both on personal devices and within online services. In this environment, proper access control is critical to help users obtain the benefits of sharing varied content with different groups of people while avoiding trouble at work, embarrassment, identity theft, and other problems related to unintended disclosure. Current approaches often fail, either because they insufficiently protect data or because they confuse users about policy specification. Historically, correctly managing access control has proven difficult, timeconsuming, and error-prone, even for experts; to make matters worse, access control remains a secondary task most non-experts are unwilling to spend significant time on. To solve this problem, access control for file-sharing tools and services should provide verifiable security, make policy configuration andmanagement simple and understandable for users, reduce the risk of user error, and minimize the required user effort. This thesis presents three user studies that provide insight into people’s access-control needs and preferences. Drawing on the results of these studies, I present Penumbra, a prototype distributed file system that combines semantic, tag-based policy specification with logicbased access control, flexibly supporting intuitive policies while providing high assurance of correctness. Penumbra is evaluated using a set of detailed, realistic case studies drawn from the presented user studies. Using microbenchmarks and traces generated from the case studies, Penumbra can enforce users’ policies with overhead less than 5% for most system calls. Finally, I present lessons learned, which can inform the further development of usable access-control mechanisms both for sharing files and in the broader context of personal data.
Designing a 3D Navigation System Using Cognitive Factors

This paper focuses on the measurement and the mathematical definition of cognitive parameters of designing a navigation systembased on these parameters. The nausea level due to different velocities of a 3D scene, the user head rotation around Yaw, Roll and Pitch axes, the delay between navigation device stimuli and the 3D display movement are measured. Appropriate mathematical functions are ﬁtted to the measurements. A sickness level is deﬁned as an accumulation of a nausea level due to the velocity and the delay. Assigning an analog control button on the navigation device will help the user to adjust the speed. The records of the test-bed and practical experiments prove the effectiveness of this kind of design. Moreover, due to the parametric design of the system, any maloperation can be readjusted with further inquiries over the speciﬁc applications. In addition, any amendment or modiﬁcation performance can be compared with the parametric criteria.
Evaluating variations on program slicing for debugging (data-flow, ada)

Debugging and maintaining computer programs is a difficult and time consuming task. The traditional methods used by a programmer to understand a program such as reading program text, reading program documentation, ad hoc testing with different inputs, or dynamic tracing, often overwhelm the programmer with details that have nothing to do with what he wants to know. A solution to this information overload problem is to reduce the amount of detail a programmer sees by an application of data-flow analysis, program slicing, that can be used to transform a large program into a smaller one containing only those statements relevant to the computation of a given output. Debugging tools have evolved through three generations. The first generation of tools produced information such as core dumps and instruction execution traces in terms of the underlying hardware. The second generation of debugging tools, often called symbolic debuggers, produced program state and history information in terms of the programming language being used. A third generation of debugging tools that attempt to locate faulty statements for the programmer has begun to emerge. The goal of this thesis was to evaluate program slicing as a debugging tool. To evaluate slicing we built a visually oriented, source-language independent, third generation debugging tool called Focus that can interactively compute and display program slices of FORTRAN and Ada programs. Focus was evaluated by comparing debugging performance between two groups of graduate student programmers. We also developed a method for combining program slices, called program dicing, to identify likely locations for faults within a program slice. Program dicing was evaluated by first introducing random errors into correct programs and then using program dicing to isolate the now incorrect statement. We found that dicing could eliminate from 93 to 98 percent of program statements from consideration while debugging a 118 line program. A second evaluation of dicing was made by comparing debugging performance between two groups of experienced student programmers. We found a significant improvement in the time to locate a program fault for subjects using dicing.
Toward design and integration of a novel 6-DOF haptic device

Haptic user interface is an electro-mechanical device that interfaces the user via the sense of touch to the virtual or remote tele-operation environment. This thesis is aimed to develop a haptic user interface device that is able to provide assistance in medical surgery. A novel design hybrid 6-DOF manipulator arm has been utilized for such application. We proposed mathematical models of the manipulator arm. We designed and developed electronic interface and application software for the device. We conducted experimental studies to evaluate the performance of the proposed haptic user interface. Results demonstrated the performance of the kinematic mapping of the device and compared the computed haptic force feedback with the measured force/moment data located at the stylus of the device. In addition, we implemented gravity compensation and passivity controller methods to enhance the stability of the haptic rendering. Results indicated significant improvement in stability and also suggested future development.
Enhancing User Queries in Scientific Visualization with Distribution Information

Scientific visualization is concerned with the graphical portrayal of data. Using symbols, color, and natural perceptual cues, humans gain insight into collections of raw numbers that may not be as efficiently processed in non-graphical formats. For simple data, visualization may require only a simple mapping between numeric values and a color scale. But modern scientific, economic, and social data is far from simple. Multiple variables, duration of time, fine resolutions, and wide sampling have yielded data sets of unprecedented complexity. The mapping between such data and its visual appearance is difficult to define. The works described here attempt to make defining this mapping more manageable to users of visualization software. We describe three tools to assist users in finding features of interest in familiar, probabilistic terms. The first tool is an expressive query language in which the user can describe features using criteria based on the frequency distribution of values in local neighborhoods. The query language is closely integrated with the visualization to provide meaningful insight into the matching data and feedback to guide modification of query parameters. The second tool targets the investigation of high-dimensional aspatial data. A common technique called parallel coordinates is extended to three dimensions in order to make relationships between variables more apparent. A semiautomatic method of finding compelling viewpoints of the data in 3-D space is introduced. The user defines what features are compelling in terms of a view’s image space distribution of color and depth values. Lastly, we describe a novel frequency histogram called a periograph for displaying cyclic temporal data. Through periographs, users inspect seasonal trends and their variations through time.
Algorithms-- ESA 2012 : 20th Annual European Symposium, Ljubljana, Slovenia, September 10-12, 2012. Proceedings

Algorithm engineering. - algorithmic aspects of networks. - algorithmic game theory. - approximation algorithms. - computational biology. - computational finance. - computational geometry. - combinatorial optimization. - data compression. - data structures. -databases and information retrieval. - distributed and parallel computing. - graph algorithms. - hierarchical memories. - heuristics and meta-heuristics. - mathematical programming. - mobile computing. - on-line algorithms. - parameterized complexity. - pattern matching, quantum computing. - randomized algorithms. - scheduling and resource allocation problems. - streaming algorithms.
Directions for Shingled-Write and Two-Dimensional Magnetic Recording System Architectures: Synergies with Solid-State Disks (CMU-PDL-09-104)

Summary: Shingled-writing and two-dimensional magnetic recording, TDMR, will change core characteristics of magnetic disk operation and require systems software be adapted appropriately. Because a band of adjacent tracks overlap one another, they must be written in a specific order. Once overlapped, a track cannot be updated in place, because the tracks overlapping it will be overwritten by the update. If this behavior is exposed to operating systems directly, there will be very low acceptance of these products. However, disk controller software can emulate full compliance with existing interfaces, and may be able to mask almost all performance implications as well.
A parallel image generation algorithm based on photon map partitioning

Photon mapping attracts much attention as an excellent image generation technique that can simulate various lighting effects such as indirect illumination and caustics obtained only by the global illumination model. Although photon mapping can generate high-quality images, it requires more expensive calculations and a large memory capacity. In this paper, we present a new parallel photon mapping algorithm to solve the problems regarding the computing time and memory requirement. The proposed algorithm can effectively parallelize photon map construction and photon search by distributing partial photon maps among processing elements of a parallel computer. As a photon map is partitioned, only a part of the photon map is assigned to each processing element. Therefore, each processing element does not require a large memory space even if the entire photon map is quite huge. We implement the proposed algorithm using MPI and evaluate it through experiments on a parallel computer. The experimental results indicate that our algorithm can significantly reduce the rendering time of photon mapping as the number of processing elements increases, and can also save the memory space.
Sistema de resumen automático accesible vía Web service

En este proyecto se presenta un sistema de resumen automatico que utiliza el metodo de las cadenas lexicas. Se ha implementado como un modulo para FreeLing, que es una libreria open source de analisis linguistico, y hecho accesible via web service en TextServer, la plataforma de webservices de TALP.
Multiresolution modeling and visualization of volume data

A scalar volumetric dataset is regarded as a sampled version of a function mapping points from a three dimensional domain into a four-dimensional space. We present a multiresolution model for the representation and visualization of volume data that is based on a decomposition of the three-dimensional domain into tetrahedra. Multiresolution is achieved by incorporating a large number of tetrahedralizations that represent the original function at different precisions in the framework of a unified compact model. The model is built through an adaptive incremen tal approach driven by local coherence. The model supports efficient extraction of isosurfaces, and visualization through projective techniques with adaptive resolution levels, as well as the development of progressive and multiresolution rendering approaches. Experimental results on different datasets are reported
Natural Language Identification using Corpus-Based Models

This paper describes three approaches to the task of automatically identifying the language a text is written in. We conducted experiments to compare the success of each approach in identifying languages from a set of texts in Dutch/Friesian, English, French, Gaelic (Irish), German, Italian, Portuguese, Serbo-Croat and Spanish.
High-performance packet processing engines using set-associative memory architectures

The emergence of new optical transmission technologies has led to ultra-high Giga bits per second (Gbps) link speeds. In addition, the switch from 32-bit long IPv4 addresses to the 128-bit long IPv6 addresses is currently progressing. Both factors make it hard for new Internet routers and firewalls to keep up with wire-speed packet-processing. By packet-processing we mean three applications: packet forwarding, packet classification and deep packet inspection. In packet forwarding (PF), the router has to match the incoming packet's IP address against the forwarding table. It then directs each packet to its next hop toward its final destination. A packet classification (PC) engine examines a packet header by matching it against a database of rules, or filters, to obtain the best matching rule. Rules are associated with either an ``action'' (e.g., firewall) or a ``flow ID'' (e.g., quality of service or QoS). The last application is deep packet inspection (DPI) where the firewall has to inspect the actual packet payload for malware or network attacks. In this case, the payload is scanned against a database of rules, where each rule is either a plain text string or a regular expression. In this thesis, we introduce a family of hardware solutions that combine the above requirements. These solutions rely on a set-associative memory architecture that is called CA-RAM (Content Addressable-Random Access Memory). CA-RAM is a hardware implementation of hash tables with the property that each bucket of a hash table can be searched in one memory cycle. However, the classic hashing downsides have to be dealt with, such as collisions that lead to overflow and worst-case memory access time. The two standard solutions to the overflow problem are either to use some predefined probing (e.g., linear or quadratic) or to use multiple hash functions. We present new hash schemes that extend both aforementioned solutions to tackle the overflow problem efficiently. We show by experimenting with real IP lookup tables, synthetic packet classification rule sets and real DPI databases that our schemes outperform other previously proposed schemes.
The Autopointer: A New Augmented-Reality Device for Transfer of Planning Data into the Operating Room.

To transfer preoperatively planned data into the operating room (OR), registration is necessary as well as a method to localize the planned data in the OR. This data may comprise e.g. entry point positions into the human body in case of minimally invasive interventions or cutting trajectories. State of the art methods for localization are e.g.: • The robot itself is used as a pointing device (exploiting the forward kinematics) to position other devices and the workpiece with respect to each other. • An optically tracked pointer is used to find positions in the OR, assisted either by a VR representation of the scene where the pointer is visualized, or by simple commands ("move right/left/up/down."). • The plan is projected with e.g. video or laser projectors. This work presents a first prototype of the autopointer, a new patent pending device using a handheld optically tracked laser scanner to localize preoperatively planned data in the operating room (OR).
A Method for Estimation of Safe and Tight WCET in Multicore Memory Hierarchies

Multicore microprocessors have become the new way to improve the processor performance. Moreover, the multicore processor systems are currently the dominating computer resource in many products like mobile appliances, automotive and space-borne applications. However, the last category’s challenge is that tasks can have various degrees of criticality concerning the response times. Therefore, the aim of this Master’s Thesis is to develop a method to derive a safe (the task execution time can never be longer) and a tight (worst-case execution time is off the real execution time by typically a small factor) worst-case execution time estimates in multicore system with memory hierarchies. The produced method consists of an analytical model and gem5, which is a state-of-the-art computer architecture simulator. This Thesis has surprisingly discovered that the simulated multicore system’s throughput increases by close to linearly with the number of cores. This suggests that, contrary to common belief, it is possible to guarantee a safe worst-case execution time and still enjoy the increase in throughput offered by multicore systems. These findings are therefore encouraging for further investigations. Although, the outcome of this Thesis mainly focuses on LEON4FT, which is a SPARC V8 based System-on-a-Chip, it is also applicable to other multicore systems. Furthermore, the Thesis report introduces the previous studies’ arguments about the transition from uniprocessor to the multicore processors, memory hierarchies as well as worst-case execution time.
Transformative Pattern Learning

Abstract : Statistical analysis of relational data is a fundamental and novel problem in machine learning and data mining. Such analysis constructs useful statistical models from data about complex relationships among people, places, things, and events. Supported by this research contract, we uncovered fundamental challenges of statistical learning and inference in relational data, we designed and implemented new languages for expressing deterministic and probabilistic dependencies in such data, we developed new algorithms for learning probabilistic models, we implemented an open-source system for knowledge discovery in relational data containing over 40,000 lines of code that has been downloaded more than 1000 times, and we evaluated the utility of those algorithms by undertaking large and realistic applications.
What Next: Autonomous Photogrammetric Image Understanding?

This paper tries to take up the challenge issued by the title given by the organizers of the photogrammetric week. Due to the vastness of the problem we do so in a selective manner. We focus on two aspects of image understanding with broad recent interest and bright scientific perspective, but also limitations which need to be overcome. These are particularly appearance based approaches for object extraction and classification as well as statistical and combinatorial modeling. We illustrate the paper with examples of our work on building facade interpretation resting on developments in threedimensional (3D) reconstruction from uncalibrated image sequences. Particularly, we introduce implicit shape models as well as Random Sample Consensus (RANSAC) and Markov Chain Monte Carlo (MCMC). We finally note, that in spite of the large progress in image understanding in recent years, the gap to what people would like to have still seems to widen
Introduction to Statistical Pattern Recognition-Second Edition

This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises.
BOR: a Pragmatic DAML+OIL Reasoner

This report outlines the implementation of a DAML+OIL reasoner within the OnTo Knowledge project. The reasoner has to work in tight connection with the SESAME RDF(S) repository and the Ontology Middleware Module implemented within the project. SESAME supports the storage, management, and querying of ontologies and instances in RDF(S) repositories using the RQL language and set of APIs. The document extends section 3 of [Kiryakov et al, 2002] and provides more implementation details on top of it. The appropriate evaluation framework ([DLBMark 2002]) is also discussed.
Contributions à l'évaluation des risques en assurance tempête et automobile

Dans cette these, nous etudions la garantie tempete consacree aux dommages causes par le vent et un developpement de l'assurance comportementale a travers le risque automobile. Nous associons des informations exterieures comme la vitesse du vent aux donnees de l'assurance. Nous proposons la construction d'un indice tempete pour completer et renforcer l'evaluation des degâts causes par les tempetes majeures. Nous definissons ensuite un partage du territoire francais en 6 zones tempetes, dependant des correlations extremes de vent, pour tester plusieurs scenarios. Ces differents tests et considerations nous permettent d'ameliorer notre indice tempete. Nous nous appuyons sur les modeles de la theorie des valeurs extremes pour montrer l'impact de la variabilite sur le calcul des periodes de retour et besoins en fonds propres. Nous soulignons ainsi les difficultes rencontrees pour degager des resultats robustes en lien avec les evenements extremes. Pour ce qui est de l'assurance automobile, nous testons differentes methodes pour repondre aux evolutions techniques et reglementaires. Nous caracterisons la partition homme / femme en utilisant la procedure logistique, l'analyse des correspondances multiples ou les arbres de classification. Nous montrons qu'il est possible de compenser l'absence de la variable sexe par d'autres informations specifiques a l'assure ou a son vehicule et en particulier l'utilisation de releves kilometriques. Enfin, nous nous interessons a l'experience acquise par les conducteurs novices. Nous etudions le comportement sur la route de l'assure pour creer de nouvelles classes de risques
Interactive Curves and Surfaces: A Multimedia Tutorial on CAGD, with Disks

From the Publisher: The growing importance of animation and 3D design has caused computer-aided geometric design (CAGD) to be of interest to a wide audience of programmers and designers. This interactive software/book tutorial teaches fundamental CAGD concepts and discusses the growing number of applications in such areas as geological modeling, molecular modeling, commercial advertising, and animation. Using interactive examples and animations to illustrate the mathematical concepts, this hands-on multimedia tutorial enables users without a substantial mathematical background to quickly gain intuition about CAGD. Interactive Curves and Surfaces guides you in Learning the uses of CAGD as it is applied in computer graphics and engineering. Creating curved lines and surfaces using Bezier curves, B-Splines, and parametric surface patches. Understanding the mathematical tools behind the generation of these objects, and the development of computer-based CAGD algorithms. Experimenting with powerful interactive test benches to explore the behavior and characteristics of the most popular CAGD curves. Application oriented readers will find this animated tutorial presentation more accessible than the standard formal texts on the subject.