Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Algorithms for Collision Detection and Ray Tracing of Deformable Meshes

Many applications in computer graphics and visualization are directly dependent on accurate and fast intersection queries. To prevent bodies passing directly through each other, the simulation system must be able to track touching or intersecting geometric primitives. In realtime graphics simulations, in which hundreds of thousands of geometric primitives are involved, highly efficient collision detection algorithms are needed. The efficient handling of deformable models constitutes a particular challenge to the simulation system, since the possibilities of precomputing efficient data structures are decreased dramatically. The same type of problem arises in interactive ray tracing, where a huge number of geometric intersections must be determined in just a fraction of a second. For these reasons, new efficient collision detection and ray tracing methods for deformable meshes are suggested in this thesis. The proposed solutions are based on bounding volume hierarchies which allow the models they represent to be deformed at every time step of the simulation. Different update methods to efficiently refit the bounding volumes in the hierarchies as the models deform are presented. The models considered are represented by polygon meshes that are either deformed by arbitrary vertex repositioning or by mesh morphing. The update methods postpone updates in the hierarchies until they are absolutely needed in order to avoid unnecessary updating work. The results from the experiments performed indicate that significant speed-ups can be achieved by using these new methods in comparison with approaches suggested previously. The thesis also shows that mesh morphing constitutes a specific example of a restricted type of deformation that allows particularly efficient hierarchical data structures, with expected sub-linear collision queries in the number of geometric primitives of the meshes.
Providing Support for the Movidius Myriad1 Platform in the SkePU Skeleton Programming Framework

The Movidius Myriad1 Platform is a multicore embedded platform primed to offer high performance and power efficiency for computer vision applications in mobile devices. The challenges of programming multicore environments are well known and skeleton programming offers a high-level programming alternative for parallel computing, intended to hide the complexities of the system from the programmer. The SkePU Skeleton Programming Framework includes backend implementations for CPU and GPU systems and it has the capacity to support more platforms by extending its backend implementations. With this master thesis project we aim to extend the SkePU Skeleton Programming Framework to provide support for execution in the Movidius Myriad1 embedded platform. Our SkePU backend for Myriad1 consists on a set of macros and functions to compose the different elements of a Myriad1 application, data communication structures to exchange data between the host systems and Myriad1, and a helper script and auxiliary files to generate a Myriad1 application.Evaluation and testing demonstrate that our backend is usable, however further optimizations are needed to obtain good performance that would make it practical to use in real life applications, particularly when it comes to data communication. As part of this project, we have outlined some improvements that could be applied to obtain better performance overall in the future, addressing the issues found with the methods of data communication.
Using Targeted Publicity to Reduce Opportunities for Bicycle Theft

Throughout Europe various policy targets have recently been proposed to encourage cycling as a sustainable transport alternative. From a criminological perspective, if successful, increases in the population of cyclists may generate increases in the number of opportunities for cycle theft. Although there is little research into bicycle theft compared with other volume crimes, analyses of data from the International Crime Victim Survey indicate that cyclists are around three times more likely to have their bike stolen than car owners their car or motorcyclists their motorbike. In relation to the described policy aims, theft and the fear of bicycle theft are found to discourage cycle use. Consequently, neglecting the crime risks associated with increased cycle usage might impede the achievement of otherwise commendable policy targets. Here we report the findings of two observational studies conducted in different areas to better understand how cyclists park their bicycles in public spaces and whether a simple communication strategy might encourage them to lock in a more secure manner. The results of the first study, conducted across five sites in central London (England) indicated a statistically significant reduction in `bad' locking practices and increases in both `good' and `ok' locking practices at those sites receiving intervention. No changes were observed at the control site. Study 2 was conducted in Brighton, England, and constituted a replication of Study 1. A similar pattern of results was observed. The implications of the findings for preventing bicycle theft, the importance of implementability and maintainability in crime prevention initiatives, and the use of publicity in the prevention of crime are discussed.
A Domain Specific Search Engine With Explicit Document Relations

The current web consists of documents that are highly heterogeneous and hard for machines to understand. The SemanticWeb is a progressive movement of the Word Wide Web, aiming at converting the current web of unstructured documents to the web of data. In the Semantic Web, web documents are annotated with metadata using standardized ontology language. These annotated documents are directly processable by machines and it highly improves their usability and usefulness. In Ericsson, similar problems occur. There are massive documents being created with well-defined structures. Though these documents are about domain specific knowledge and can have rich relations, they are currently managed by a traditional search engine, which ignores the rich domain specific information and presents few data to users. Motivated by the Semantic Web, we aim to find standard ways to process these documents, extract rich domain specific information and annotate these data to documents with formal markup languages. We propose this project to develop a domain specific search engine for processing different documents and building explicit relations for them. This research project consists of the three main focuses: examining different domain specific documents and finding ways to extract their metadata; integrating a text search engine with an ontology server; exploring novel ways to build relations for documents. We implement this system and demonstrate its functions. As a prototype, the system provides required features and will be extended in the future.
A Class of Spherical Penrose-Like Tilings with Connections to Virus Protein Patterns and Modular Sculpture

The focus of this paper is a class of symmetrically patterned spherical polyhedra we call “Twarock-Konevtsova” (T-K) tilings, which were first applied to the study of viruses. We start by defining the more general concept of a “wrapping paper pattern,” and T-K tilings (along with one other virus tiling) are outlined as a subset of them. T-K tilings are then considered as “spherical Penrose tilings” and a pair of algorithms for generating them is described. We believe they present good source material for mathematical sculpture, especially modular origami, having intriguing features such as consistent edge lengths and a limited selection of angles in their constituent faces. We conclude by looking at existing examples of T-K tilings in mathematical sculpture and consider different directions they could be taken in.
The Platform-Aware Compilation Environment (PACE)

Abstract : The PACE Project investigated the feasibility of using a combination of characterization-driven optimization, feedback-directed optimization, and automatic selection of transformations to retarget an optimizing compiler to new computer systems. This report provides an overview of the design, the implementation, and the ways in which the PACE components advanced the state of the art in compilation, in performance measurement and attribution, in portable measurement of system characteristics, and in machine learning.
1 – Context in Application and Modelling – an Empirical Approach

In a qualitative-orientated empirical study the effect of context on the student's approach towards real world problems is investigated. First results show that contexts given in a task can internally be reconstructed in very different ways. It is also shown that both, the student's affective proximity to the context and the student's real world knowledge can have fostering but also hindering effects on his or her performance.
Endocentric structuring of projection-free syntax

1. List of abbreviations, pix 2. Acknowledgments, pxi-xii 3. 1. Preface, p1-5 4. 2. Bare phrase structure and cyclic derivation by phase, in Light of Minimal Computation, p7-63 5. 3. Minimal head detection in projection-free syntax, p65-139 6. 4. Cyclic Spell-Out of projection-free syntax, p141-190 7. 5. Full Interpretation all the way through, p191-225 8. 6. Conclusion, p227-231 9. Appendix: List of propositions, p233-240 10. References, p241-258 11. Author index, p259-? 12. Subject index, p?
Quality of experience for adaptive streaming using HTTP Dynamic Streaming

This thesis investigates how to establish the relationship between OSI layer 7 parameters of video streaming and the QoE of the user, and to evaluate which methods are most tting for the estimation of QoE. The project is made in cooperation with LTH and Acreo, and is a part of the Next generation over-the-top multimedia services (NOTTS) 7and the Eco system for Future Media Distribution (EFRAIM) project. The underlying techniques, which form the environment of our research of estimating the QoE, is adaptive bitrate streaming over TCP. The purpose is to investigate how a service, that provides a user with the means to benchmark the received quality of the Over the top (OTT) streaming service, can be built and distributed. Today there exists no such service that takes the viewers subjective opinion into consideration. There have been extensive research on some connected elds and issues but none with a unied solution to streaming adaptive bitrate video over TCP with its particular behavior and eect caused on the streamed video. In this report we evaluated two dierent methods of prediction of QoE, Pause Intensity based on the number of pauses and their length during playback, and a Linear bitrate model based on the average bitrate quality and its standard deviation. We also made a small user test with our streaming client software to evaluate the two methods to decide which one is the most benecial to use. The test showed that although one of the most irritating playback deficiencies is when pauses occur, the linear bitrate model delivered the most accurate predictions.
A Local Tuning Scheme of RED using Genetic Algorithm for Efficient Network Management in Muti-Core CPU Environment

It is not easy to set RED(Random Early Detection) parameter according to environment in managing Network Device. Especially, it is more difficult to set parameter in the case of maintaining the constant service rate according to the change of environment. In this paper, we hypothesize the router that has Multi-core CPU in output queue and propose AI RED(Artificial Intelligence RED), which directly induces Genetic Algorithm of Artificial Intelligence in the output queue that is appropriate to the optimization of parameter according to RED environment, which is automatically adaptive to workload. As a result, AI RED Is simpler and finer than FuRED(Fuzzy-Logic-based RED), and RED parameter that AI RED searches through simulations is more adaptive to environment than standard RED parameter, providing the effective service. Consequently, the automation of management of RED parameter can provide a manager with the enhancement of efficiency in Network management.
Aligning Controlled vocabularies for enabling semantic matching in a distributed knowledge management system

The underlying idea of the Semantic Web is that web content should be expressed not only in natural language but also in a language that can be unambiguously understood, interpreted and used by software agents, thus permitting them to find, share and integrate information more easily. The central notion of the Semantic Web's syntax are ontologies, shared vocabularies providing taxonomies of concepts, objects and relationships between them, which describe particular domains of knowledge. A vocabulary stores words, synonyms, word sense definitions (i.e. glosses), relations between word senses and concepts; such a vocabulary is generally referred to as the Controlled Vocabulary (CV) if choice or selection of terms are done by domain specialists. A facet is a distinct and dimensional feature of a concept or a term that allows a taxonomy, ontology or CV to be viewed or ordered in multiple ways, rather than in a single way. The facet is clearly defined, mutually exclusive, and composed of collectively exhaustive properties or characteristics of a domain. For example, a collection of rice might be represented using a name facet, place facet etc. This thesis presents a methodology for producing mappings between Controlled Vocabularies, based on a technique called \Hidden Semantic Matching". The \Hidden" word stands for it not relying on any sort of externally provided background knowledge. The sole exploited knowledge comes from the \semantic context" of the same CVs which are being matched. We build a facet for each concept of these CVs, considering more general concepts (broader terms), less general concepts (narrow terms) or related concepts (related terms). Together these form a concept facet (CF) which is then used to boost the matching process.
Syntactic Complexity in Persons with Multiple Sclerosis

SYNTACTIC COMPLEXITY IN PERSONS WITH MULTIPLE SCLEROSIS Katherine Alma King Department of Communication Disorders Master of Science Several studies using standardized tests have provided evidence for the presence of language disorders in persons with Multiple Sclerosis (MS) and have suggested that persons with MS may have language that is less complex. One aspect not thoroughly studied is that of syntactic complexity in naturalistic, conversational settings. The present study collected language samples from 10 adults with MS and 10 age-matched controls and compared scores on five quantitative measures derived from those samples. No significant differences were found between groups on any measure. This finding suggests that in mild cases of MS or during periods of remission, individuals may retain their ability to use complex language structures in naturalistic discourse. ACKNOWLEDGMENTS Many sources contributed to the completion of this thesis. This work was part of a larger study carried out by my fellow researcher Kristi Hollis. Kristi, you have been a pleasure to work with. I’ve appreciated your wisdom and experience, humor and down to earth character. Thank you so much to my outstanding thesis committee. Dr. Channell, you have made a daunting task accomplishable through your accessibility, patience, guidance, and encouragement. Thanks you for your tirelessness in answering questions, responding to emails, and editing drafts. I couldn’t have asked for a better mentor. Dr. Nissen, thank you for your flexibility and support. You have increased my appreciation for the importance of collaboration. Dr. Dromey, you have increased my appetite for knowledge and learning. You have instilled in me the importance of a rationale. I would like to thank countless friends and family, who willingly participated in this study in one form or another. I thank my colleagues. What an amazing group of women I have been enlightened and inspired by. Women I have laughed with, cried with, and eaten chocolate with. These are friends for life. Lastly, I would like to thank my family for their tireless inquisitions regarding when I would complete this thesis. I especially thank my mother, for picking up the phone in the middle of the night time and again to help me get through tears and fears as I submitted draft after draft. She has been a great support to me and has given countless time and prayers to this cause.
Toward Automating Web Protocol Configuration for a Programmable Logic Controller Emulator

Abstract : Industrial Control Systems (ICS) remain vulnerable through attack vectors that exist within programmable logic controllers (PLC). PLC emulators used as honeypots can provide insight into these vulnerabilities. Honeypots can sometimes deter attackers from real devices and log activity. A variety of PLC emulators exist, but require manual figuration to change their PLC pro le. This limits their flexibility for deployment. An automated process for configuring PLC emulators can open the door for emulation of many types of PLCs. This study investigates the feasibility of creating such a process. The research creates an automated process for figuring the web protocols of a Koyo DirectLogic PLC. The figuration process is a software program that collects information about the PLC and creates a behavior pro le. A generic web server then references that pro le in order to respond properly to requests. To measure the ability of the process, the resulting emulator is evaluated based on response accuracy and timing accuracy. In addition, the figuration time of the process itself is measured. For the accuracy measurements a workload of 1000 GET requests are sent to the index.html page of the PLC, and then to the emulator. These requests are sent at two rates: Slow and PLC Break. The emulator responses are then compared to those of the PLC baseline. Results show that the process completes in 9.8 seconds, on average. The resulting emulator responds with 97.79% accuracy across all trials. It responds 1.3 times faster than the real PLC at the Slow response rate, and 1.4 times faster at the PLC Break rate. Results indicate that the automated process is able to create an emulator with an accuracy that is comparable to a manually figured emulator. This supports the hypothesis that creating an automated process for figuring a PLC emulator with a high level of accuracy is feasible.
Interior permanent magnet synchronous machine high speed operation using field weakening control strategy

The paper deals with the analytical solution of the maximum torque per flux strategy for interior permanent magnet synchronous machine. The paper describes in detail, how to compute proper values of stator current components to be able to control the drive in a wide speed range. The developed flux weakening algorithm can be easily adapted to the controlled drive using its actual identified parameters. The algorithm was proved in simulation using a real PMSM control system.
Object apprehension using vision and touch

Researchers define object apprehension as the determination of the properties of an object and the relationships among these properties. They contrast this with recognition, which goes a step further to attach a label to the object as a whole. Apprehension is fundamental to manipulation. This is true whether the manipulation is being carried out by an autonomous robot or is the result of teleoperation involving sensory feedback. Researchers present an apprehension paradigm using both vision and touch. In this model, they define a representation for object apprehension in terms of a set of primitives and features, along with their relationships. This representation is the mechanism by which the data from the two modalities are combined. It is also the mechanism which drives the apprehension process.
Using Application-Specific Ontologies to Generate Grammar Rules in English, Hindi, and Spanish for a Web Interface

This thesis is concerned with the use of domain ontologies facilitating the generation of multilingual grammars, which furthermore can be integrated in the natural language understanding module of a communication system. In particular we work on grammars for supporting user queries when accessing the web in English, Hindi and Spanish in two scenarios: searching for a new medical specialist and looking for the information about cultural events in the city. Although there have been many works on communication systems supporting English and Spanish, this is not the case for Hindi language. For economical and cultural reasons there have not been many studies on the integration of Hindi language on communication systems. For this reason, our thesis also deals with the difficulty of working on a language for which not many studies have been done nor do existing resources exist. In order to facilitate the generation of linguistic resources for the three languages in different domains we propose a clear separation of the conceptual and linguistic knowledge, as well as a separation of general and domain-restricted knowledge bases, being conceptual knowledge. Conceptual knowledge is represented in ontologies and is reused across the three languages. Linguistic knowledge is language specific. General knowledge consists in general conceptual concepts represented in a general ontology and general linguistic knowledge can be represented as general grammars rules that can be reused across domains. For developing the grammar rules for each domain and language we use grammatical framework (GF), a powerful tool for writing multilingual grammars. One of the main advantages of this formalism is that favours a clear separation of conceptual and syntactic knowledge involved in a particular grammar: it represent the conceptual knowledge in a module called abstract grammar and the syntactic details in a separate but related module called concrete grammar. We define abstract grammar from ontologies and they are base to further developing the concrete grammar.
Learning LiNGAM based on data with more variables than observations

A very important topic in systems biology is developing statistical methods that automatically find causal relations in gene regulatory networks with no prior knowledge of causal connectivity. Many methods have been developed for time series data. However, discovery methods based on steady-state data are often necessary and preferable since obtaining time series data can be more expensive and/or infeasible for many biological systems. A conventional approach is causal Bayesian networks. However, estimation of Bayesian networks is ill-posed. In many cases it cannot uniquely identify the underlying causal network and only gives a large class of equivalent causal networks that cannot be distinguished between based on the data distribution. We propose a new discovery algorithm for uniquely identifying the underlying causal network of genes. To the best of our knowledge, the proposed method is the first algorithm for learning gene networks based on a fully identifiable causal model called LiNGAM. We here compare our algorithm with competing algorithms using artificially-generated data, although it is definitely better to test it based on real microarray gene expression data.