Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of license selection on open source software quality

Cotton, Benjamin J. M.S., Purdue University, December 2014. Impact of license selection on open source software quality. Major Professor: Kevin C. Dittman. Open source software plays an important part in the modern world, powering businesses large and small. However, little work has been done to evaluate the quality of open source software. Two di↵erent license paradigms exist within the open source world, and this study examines the di↵erence in software quality between them. In this thesis, the author uses technical debt as a measure of software quality. Eighty open source projects (40 from each paradigm) were downloaded from the popular open source hosting website SourceForge. Using complexity, code duplication, comments, and unit test coverage as inputs to the SonarQube technical debt model, each project was evaluated. The technical debt was normalized based on the cyclomatic complexity and the paradigms were compared with the Mann-Whitney test. The results showed a clear di↵erence between the two paradigms. However, the results presented in this thesis are only a starting point. The collected data suggest that the programming language used in a project has an impact on the project’s quality. In addition, SonarQube plugins for the popular C and C++ languages were beyond the budget of this work, excluding many projects from consideration. This thesis closes with several suggestions for further avenues of investigation.
Artistic ideation based on computer vision methods

This paper analyzes the automatic classification of scenes that are the basis of the ideation and the designing of the sculptural production of an artist. The main purpose is to evaluate the per- formance of the Bag-of-Features methods, in the challenging task of categorizing scenes when scenes differ in semantics rather than the objects they contain. We have employed a kernel-based recognition method that works by computing rough geometric correspondence on a global scale using the pyramid matching scheme introduced by Lazebnik (7). Results are promising, on average the score is about 70%. Experiments suggest that the automatic categorization of images based on computer vision methods can provide objective principles in cataloging images. Image representation is a very important element for image classification, annotation, seg- mentation or retrieval. Nearly all the methods in computer vision which deals with image content representation resort to features capable of representing image content in a compact way. Local features based representation can produce a versatile and robust image representa- tion capable of representing global and local content at the same time. Describing an object or scene using local features computed at interest locations makes the description robust to par- tial occlusion and image transformation. This results from the local character of the features and their invariance to image transformations. The bag-of-visterms (BOV) is an image representation built from automatically extracted and quantized local descriptors referred to as visterms in the remainder of this paper. The BOV representation, which is derived from these local features, has been shown to be one of the best image representations in several tasks. The main objective of this study is assessing the performance of SIFT descriptors, BOV representation and spatial pyramid matching for automatic analysis of images that are the basis of the ideation and designing of art work. Additionally, we explore the capability of this kind of modelization to become useful for the production of software based art.
Multimedia encryption and watermarking

to Multimedia Security. - Digital Rights Management for Multimedia. - Multimedia Cryptography. - to Multimedia Encryption. - An Overview of Modern Cryptography. - Important Modern Cryptosystems. - Image Encryption Algorithms. - Video Encryption Algorithms. - Speech and Audio Encryption. - Visual and Audio Secret Sharing. - Multimedia Watermarking. - to Watermarking. - Applications of Digital Watermarking. - Digital Watermarking Concepts. - Digital Watermarking and Binary Images. - Two-Level Marks: Design. - Two-Level Marks: Implementations. - Future of Watermarking.
Applied Differential Privacy in the Smart Grid

Privacy is an important guarantee to give to users in order for them to agree to release their, possibly sensitive, data for scientific or commercial purposes. However, guaranteeing privacy is not a trivial task. Previously there have been several cases where released data was believed to have been anonymized, where it later proved not to be anonymous at all [28, 38]. One methodology to be able to release anonymized calculations is differential privacy, where controlled noise is added to the calculation before it is release. However, there exists a trade-off between the privacy and the accuracy of the results when differential privacy is used. Previous work has mostly focused on differential privacy in theory, but there also exists work that applies differential privacy to a use case [32]. However, the utility of the differentially private results have not previously been evaluated when using only counting queries. In this thesis differential privacy is applied to one use case found in the smart grid, an evolved version of the electricity grid, to show that differential privacy is applicable in practice and not only in theory. The particular use case in this thesis compares a differentially private sum to the true sum, to estimate the error introduced by applying differential privacy. The results demonstrate that differential privacy shows promise also for realistic usage, providing privacy while still producing accurate results compared to the true results without differential privacy applied. For a setup with 1,000 simulated households, the best results for the mean error is between 0.42% and 0.59%, and the spread of the error ranged from 0% to 2.07%. All of these results have a confidence interval of 95%.
Contrast in phonology : theory, perception, acquisition

This book takes contrast, an issue that has been central to phonological theory since Saussure, as its central theme, making explicit its importance to phonological theory, perception, and acquisition. The volume brings together a number of different contemporary approaches to the theory of contrast, including chapters set within more abstract representation-based theories, as well as chapters that focus on functional phonetic theories and perceptual constraints.This book will be of interest to phonologists, phoneticians, psycholinguists, researchers in first and second language acquisition, and cognitive scientists interested in current thinking on this exciting topic.
Audio-coupled video content understanding of unconstrained video sequences

Unconstrained video understanding is a difficult task. The main aim of this thesis is to recognise the nature of objects, activities and environment in a given video clip using both audio and video information. Traditionally, audio and video information has not been applied together for solving such complex task, and for the first time we propose, develop, implement and test a new framework of multi-modal (audio and video) data analysis for context understanding and labelling of unconstrained videos. The framework relies on feature selection techniques and introduces a novel algorithm (PCFS) that is faster than the well-established SFFS algorithm. We use the framework for studying the benefits of combining audio and video information in a number of different problems. We begin by developing two independent content recognition modules. The first one is based on image sequence analysis alone, and uses a range of colour, shape, texture and statistical features from image regions with a trained classifier to recognise the identity of objects, activities and environment present. The second module uses audio information only, and recognises activities and environment. Both of these approaches are preceded by detailed pre-processing to ensure that correct video segments containing both audio and video content are present, and that the developed system can be made robust to changes in camera movement, illumination, random object behaviour etc. For both audio and video analysis, we use a hierarchical approach of multi-stage classification such that difficult classification tasks can be decomposed into simpler and smaller tasks. When combining both modalities, we compare fusion techniques at different levels of integration and propose a novel algorithm that combines advantages of both feature and decision-level fusion. The analysis is evaluated on a large amount of test data comprising unconstrained videos collected for this work. We finally, propose a decision correction algorithm which shows that further steps towards combining multi-modal classification information effectively with semantic knowledge generates the best possible results.
Modules and Dialects as Objects in Grace

Grace is a gradually typed, object-oriented language for use in education; consonant with that use, we have tried to keep Grace as simple and straightforward as possible. Grace needs a module system for several reasons: to teach students about modular program design, to organise large programs, especially its self-hosted implementation, to provide access to resources defined in other languages, and to support different “dialects” — language subsets, or domain specific languages, for particular parts of the curriculum. Grace already has several organising constructs; this paper describes how Grace uses two of them, objects and lexical scope, to provide modules and dialects.
Metamorphic Malware Detection using Subgraph Matching

In the recent years, malicious codes called malware are having shown significant increase due to the code obfuscation to evade detection mechanisms. When the code obfuscation technique is applied to malwares, they can change their instruction sequence and also even their signature. These malwares which have same functionality and different appearance are able to evade signature-based AV products. Thus, AV venders paid large amount of cost to analyze and classify malware for generating the new signature. In this paper, we propose a novel approach for detecting metamorphic malwares. The proposed mechanism first converts malware's API call sequences to call graph through dynamic analysis. After that, the callgraph is converted to semantic signature using 128 abstract nodes. Finally, we extract all subgraphs and analyze how similar two malware's behaviors are through subgraph similarity. To validate proposed mechanism, we use 273 real-world malwares include obfuscated malware and analyze 10,100 comparison results. In the evaluation, all metamorphic malwares are classified correctly, and similar module behaviors among different malwares are also discovered.
Parallel For Loops on Heterogeneous Resources

In recent years, Graphics Processing Units (GPUs) have piqued the interest of researchers in scientific computing. Their immense floating point throughput and massive parallelism make them ideal for not just graphical applications, but many general algorithms as well. Load balancing applications and taking advantage of all computational resources in a machine is a difficult challenge, especially when the resources are heterogeneous. This dissertation presents the clUtil library, which vastly simplifies developing OpenCL applications for heterogeneous systems. The core focus of this dissertation lies in clUtil’s ParallelFor construct and our novel PINA scheduler which can efficiently load balance work onto multiple GPUs and CPUs simultaneously.
Processus gaussiens pour la séparation de sources et le codage informé

La separation de sources est la tâche qui consiste a recuperer plusieurs signaux dont on observe un ou plusieurs melanges. Ce probleme est particulierement difficile et de maniere a rendre la separation possible, toute information supplementaire connue sur les sources ou le melange doit pouvoir etre prise en compte. Dans cette these, je propose un formalisme general permettant d’inclure de telles connaissances dans les problemes de separation, ou une source est modelisee comme la realisation d’un processus gaussien. L’approche a de nombreux interets : elle generalise une grande partie des methodes actuelles, elle permet la prise en compte de nombreux a priori et les parametres du modele peuvent etre estimes efficacement. Ce cadre theorique est applique a la separation informee de sources audio, ou la separation est assistee d'une information annexe calculee en amont de la separation, lors d’une phase preliminaire ou a la fois le melange et les sources sont disponibles. Pour peu que cette information puisse se coder efficacement, cela rend possible des applications comme le karaoke ou la manipulation des differents instruments au sein d'un mix a un cout en debit bien plus faible que celui requis par la transmission separee des sources. Ce probleme de la separation informee s’apparente fortement a un probleme de codage multicanal. Cette analogie permet de placer la separation informee dans un cadre theorique plus global ou elle devient un probleme de codage particulier et beneficie a ce titre des resultats classiques de la theorie du codage, qui permettent d’optimiser efficacement les performances.
Bilingual First Language Acquisition

Chapter 1 Introducing Bilingual First Language Acquisition Chapter 2 Bilingual children's language development: an overview Chapter 3 Research methods in BFLA Chapter 4 Socializing environments and BLFA Chapter 5 Sounds in BFLA Chapter 6 Words in BFLA Chapter 7 Sentences in BFLA Chapter 8 Harmonious bilingual development
Simultaneous Interpretation: A cognitive-pragmatic analysis

Simultaneous interpretation is among the most complex of human cognitive/linguistic activities. This study, which will interest practitioners and trainers as well as linguists, draws more on linguistics-based theories of cognition in communication (cognitive semantics and pragmatics) than on the traditional information-processing approaches of cognitive psychology, and shows SI to be a valuable source of data on language and cognition.Starting from semantic representations of input and output in samples of professional SI from Chinese and German into English, the analysis explains the classic phenomena – anticipation, restoration of the implicit-explicit balance, and communicative re-packaging (‘re-ostension’) of the discourse – in terms of an intermediate cognitive model in working memory, allowing a more unitary view of resource management in the SI task. Relevance-theoretic analysis of the input discourse reveals rich pragmatic information guiding the construction of the appropriate contexts and the speaker’s underlying intentionalities. The course of meaning assembly is reconstructed in annotated synchronised transcripts.
Wheat Productivity: Role of Farmers’ Nutritional Status

This follow-up study was carried out to investigate association of wheat productivity with the nutritional status of farmers in an agricultural area of North West Pakistan. A total of 1200 small scale farmers were randomly recruited and screened for nutrition status. Total of 226 farmers were found malnourished. An equal number of well-nourished farmers were randomly selected; detailed data on wheat yield and relevant confounding factors were collected interviewing groups. Multivariate linear regression analysis was performed to identify factors in relation to wheat yield. Comparing to well-nourished, malnourished farmers were more likely to report less wheat yield. Agricultural predictors that independently and significantly explained variation in wheat production included crop rotation, sowing time, and per acre agricultural inputs. Farmers' nutritional status; and dietary patterns further increased variance in wheat yield. The study findings reaffirmed the importance of farmers' nutritional status in predicting wheat yield.
Residual lignin distribution in bleached kraft pulp fibres

La distribution de la lignine residuelle sur les parois cellulaires des fibres de pâte kraft a ete mesuree apres un blanchiment en une seule etape. Les mesures des sections de fibres bromees ont ete prises a l'aide de la microscopie electronique a balayage par transmission avec analyse par rayons X a dispersion d'energie (STEM-EDXA). Les puissants oxydants ozone et dimethyldioxirane isole ont reagi plus rapidement avec le tissu des parois cellulaires exterieures [couches S3 et (P+S1)], tandis que la reaction avec la lignine dans la paroi interieure (S2) semblait ralentie par les limites du transfert de masse. Le peroxyde, le monoperoxysulfate, le bioxyde de chlore et le dimethyldioxirane genere in situ ont entraine une distribution uniforme de la lignine residuelle. Apres le blanchiment a l'oxygene, la lignine residuelle dans les couches S3 et (P+S1) etait plus importante que dans la couche S2, avec un rapport tres pres de celui de la pâte kraft initiale.
Musicians processing music: Measurement of brain potentials with EEG

Abstract In the present study, the EEG was recorded from the scalp of musicians while mentally active in their field. Analytic, creative and memory processes of the brain were observable using a special electrophysiological method called DC-potential recording. Music students listened to a sequence of four notes and subsequently were either to reverse the sequence (task 1 = analytic) or to compose a new continuation (task 2 = creative). In task 3, the initial segment of a well-known melody was presented and had to be continued (memory task). All tasks had to be solved mentally (imagery). In tasks 1 and 2, either tonal or atonal sequences were presented. While processing, the results show that the analytic task elicited the highest brain activity. The analytic task involved mainly parieto-temporal areas of both hemispheres, the left hemisphere showing a tendency for domination. The memory task produced predominant activity over the right hemisphere. The creative task caused the lowest brain activation and .
Wireless multimedia sensor networks, security and key management

Wireless Multimedia Sensor Networks (WMSNs) have emerged and shifted the focus from the typical scalar wireless sensor networks to networks with multimedia devices that are capable to retrieve video, audio, images, as well as scalar sensor data. WMSNs are able to deliver multimedia content due to the availability of inexpensive CMOS cameras and microphones coupled with the significant progress in distributed signal processing and multimedia source coding techniques. These mentioned characteristics, challenges, and requirements of designing WMSNs open many research issues and future research directions to develop protocols, algorithms, architectures, devices, and testbeds to maximize the network lifetime while satisfying the quality of service requirements of the various applications. In this thesis dissertation, we outline the design challenges of WMSNs and we give a comprehensive discussion of the proposed architectures and protocols for the different layers of the communication protocol stack for WMSNs along with their open research issues. Also, we conduct a comparison among the existing WMSN hardware and testbeds based on their specifications and features along with complete classification based on their functionalities and capabilities. In addition, we introduce our complete classification for content security and contextual privacy in WSNs. Our focus in this field, after conducting a complete survey in WMSNs and event privacy in sensor networks, and earning the necessary knowledge of programming sensor motes such as Micaz and Stargate and running simulation using NS2, is to design suitable protocols meet the challenging requirements of WMSNs targeting especially the routing and MAC layers, secure the wirelessly exchange of data against external attacks using proper security algorithms: key management and secure routing, defend the network from internal attacks by using a light-weight intrusion detection technique, protect the contextual information from being leaked to unauthorized parties by adapting an event unobservability scheme, and evaluate the performance efficiency and energy consumption of employing the security algorithms over WMSNs.
Message passing algorithms for optimization

The max-product algorithm, which attempts to compute the most probable assignment (MAP) of a given probability distribution via a distributed, local message passing scheme, has recently found applications in convex minimization and combinatorial optimization. Unfortunately, the max-product algorithm is not guaranteed to converge and, even if it does, is not guaranteed to produce the MAP assignment. Many alternative message passing schemes have been proposed to overcome these difficulties (e.g. TEMP, MPLP, max-sum diffusion). These algorithms can be viewed as coordinate ascent schemes over different duals of a linear programming formulation of the MAP problem. If these algorithms converge to a unique assignment, then this assignment is guaranteed to be the maximum of the objective function. Although these algorithms provide stronger guarantees than max-product upon convergence, they do not always converge to a unique assignment, and in some instances, the dual optimization problem that results provides a trivial upper bound on the maximizing assignment. In this work, we provide a systematic study of message passing algorithms for the related problem of minimizing an arbitrary real-valued objective function: from graphical models to reparameterization, reparameterization to lower bounds, and from lower bounds to convergent message passing algorithms. We generalize the known results by providing conditions under which the assignments produced by message passing algorithms can correspond to local and global optima, by providing a combinatorial characterization of when these message passing schemes can actually solve the minimization problem, and by providing a new convergent and correct message passing algorithm, called the splitting algorithm, that contains many of the known convergent message passing algorithms as a special case. These ideas allow us to expand the usefulness of the splitting algorithm beyond the limits of other message passing algorithms. We show that there are examples of convex minimization problems on which convergent message passing algorithms fail to produce a minimizing assignment but that the splitting algorithm succeeds. We use graph covers and our conditions for local optimality to provide conditions under which the splitting algorithm can be used to solve general convex (as well as submodular) minimization problems. These observations lead us to a generalization of diagonal dominance for arbitrary convex functions.
ScoreSVG: A New Software Framework for Capturing the Semantic Meaning and Graphical Representation of Musical Scores Using JAVA2D, XML, and SVG

ScoreSVG implements a three-tiered software architecture that generates musical scores in scalable vector graphics (SVG), something no other known music editor has done. SVG is non-proprietary XML-based format that renders graphical content into a web browser equipped with a SVG plugin. Scores in SVG can be scripted to produce interactive music theory examples, or make other graphical score changes impossible in any other format. Large music score editors such as Finale and Sibelius output to proprietary file formats, or Postscript (.ps) files that are not interchangeable or modifiable once created. Open source efforts such as LilyPond or Guido require the user to learn a new text-based music format to get a PostScript music score. ScoreSVG converts the data from a user-friendly visual front end to GuidoXML, capturing the semantic meaning of the score, and then outputs the result in SVG using an XSL stylesheet and the Saxon 8.4 XSLT processor. INDEX WORDS: SVG, Music Notation, Music Editing, Java 2D Graphics, XSLT, Guido, XML SCORESVG: A NEW SOFTWARE FRAMEWORK FOR CAPTURING THE SEMANTIC MEANING AND GRAPHICAL REPRESENTATION OF MUSICAL SCORES USING JAVA2D, XML, AND SVG