Miracle-dz/UniFAR-FTUs huggingface dataset:
From Blues to Latin Just in Time: A rhythmic analysis

Just in Time (Lopes, 2003) is an empirically devised rhythmic analytic model which assesses the operation and qualities of rhythm and metre, and their interaction with other parameters. This paper will investigate the operation of the durational parameters in the jazz standard ‘Unit Seven’ by Sam Jones, as performed by the Wes Montgomery Quartet (Verve 823 448-2, 1984). This piece was chosen for two basic reasons. First, its position as mainstream jazz allows an assessment of the rhythmic operation in a highly kinetic genre. Second, it includes a section in binary metre which provides different metric contexts in the same piece, therefore broadening the spectrum of the analysis. The consistent use of particular rhythmic constructions supports the arguments concerning the importance of the durational parameters in the kinetic quality and structural definition of a piece, while the assessment of the ongoing dialogue between pitch and durational parameters demonstrates the importance of the durational structure of music.
SOUND CHANGE AND SYLLABIFICATION:The Interlanguage of Korean Speakers Studying Indonesian

Second language (L2) learners tend to apply their first language (L1) patterns over the second language (L2) when practicing the L2(Kager, 2004, p. 23): what is known as the Language Transfer or Interference and the language is known as Interlanguage. This is quite normal and can obviously be observed in the earliest stage of L2 learning. The paper aims on describing the Korean sound system interference to Indonesian. The data is obtained from Korean speakers (KSs) studying Indonesian. Korean and Indonesian are two different languages, relatively unrelated. They have some distinct consonants and vowels in their consonants and vowels inventories. The incorrect pronunciation of Indonesian can be described in terms of sound change and syllabification with reference to Korean sound pattern. Syllable internal structure modifications are performed by KSs. In terms of sound change, the language transfer can be categorized into segment addition, deletion, and feature change. In consequence, the number of syllable might change.One might perceive the interlanguage as a type error, but in this paper, I consider the interference as an inevitable effort of studying L2.
Integrating fast network communication with a user-level thread scheduler

In operating systems, traditional methods of network communication incur high overheads and usually block the process performing the communication. This means that if a process has some communication in progress, it cannot perform further computation until the communication is complete, even though the CPU is free to be used during this time. This dissertation deals with the integration of a communication system with a user-level thread scheduler. In this way, while one user-level thread is waiting for a particular communication operation to complete, other user-level threads can perform some computation, effectively overlapping communication with computation.
git-reviewed: A Distributed Peer Review Tool & User Study

Software peer review has been considered the basis of an effective procedure for examining software artifacts, identifying defects and increasing the efficiency of software firms for decades. The process of peer reviewing allows reviewers to check their co-worker's work, which helps in determining if a standard for a system has been maintained or achieved by the person whose work is being reviewed. The result of this process is a high quality working product that will likely reduce further maintenance effort. There is a large number of code review tools available in the market as of today, which assist in the reviewing task. All these tools are centralized, with the reviews and discussions being stored either on a mailing list or a server. In contrast, the code that makes up a software system is increasingly being stored in a distributed version control system (e.g. Git). In an effort to determine if distributed peer review is a tenable idea, we develop a peer review tool, git-reviewed, which replicates the working model of Git by incorporating reviews into the current Git architecture. git-reviewed is a lightweight and a truly distributed peer review tool, which eliminates a centralized server or a mailing list to store the review discussions. We model our use case based on the Linux kernel, which is a large open source project. git-reviewed has been designed to keep the current development and reviewing practices followed by the Linux kernel developers within the open source environment intact. We also provide better traceability by linking the review discussions on the mailing lists and the changes made in the Git repository. git-reviewed was evaluated by software developers working on large open source projects, (e.g. Linux, PostgreSQL, Git), whose feedback helped us improve our tool and determine if distributed reviewing works in practice.
AUTOMATING LINEAR TEXT PLACEMENT WITHIN DENSE FEATURE NETWORKS

In preparation for the 2000 census, the Census Bureau plans to provide maps with address information to local governments for review and update. The algorithms that have been used by the Census Bureau in the past have not been flexible enough to pl'ace this kind of text readably on small-scale maps. This paper describes a new non-interactive algorithm which has been developed at the Census Bureau. This algorithm simultaneously considers all the address range text which must be plotted in a certain area of the map and can make incremental adjustments to the location of each text item in the set in order to position it for maximum clarity before any positions are fixed. The flexibility that this approach provides has already made it possible to produce maps that display address ranges, census block numbers, and linear features and their names at a scale significantly smaller than comparable maps produced for the 1990 Census.
Addressing challenges in inferring preferences from current-session data

Introduction Generating effective online recommendations is an important and challenging issue in electronic commerce. The benefits of improving recommender accuracy by even a small amount are substantial. For example, the recent announcement by NetFlix of a $1 million prize for a system that can improve on the accuracy of their current recommender by 10% points clearly to the commercial importance and value of effective recommendations (http://www.netflixprize.com). Research on the dominant approaches to recommendation focuses on making more effective use of large data sets. For example, collaborative filtering research seeks to improve algorithms that compare user characteristics or behavior to other users and recommending items that similar users have preferred or purchased. Advances in recommendation quality in this area are incremental (Herlocker et al., 2004). In addition, such approaches tend to be obtrusive, requiring considerable effort from users to be effective (e.g., having a user rate many items to generate effective recommendations) and raising privacy and security concerns. Moreover, they do not accommodate additional, different preference-related data that might be relevant in a given situation. In light of such issues, we have developed DESIRE, a recommender system that requires only a relatively small amount of single-session data to make recommendations that reflect inferred preferences in a specific session or context (Parsons et al., 2004). DESIRE uses viewing time as an indicator of preference toward an item being viewed. The system decomposes items by attributes, and infers preferences toward values (numeric or categorical) based on time spent viewing a set of items having a reasonable distribution of attribute values. Recommendations are made by calculating a weighted desirability measure for each item in a repository based on the inferred preferences for values of its attributes. The system has been tested in the laboratory with promising results. During testing, we identified two challenges that merit attention in doing research on recommenders using session data and profile-based recommendations. First, because such systems are primarily intended to infer current preferences from current data, they must function with the very limited data that might be provided during a session (e.g., inferring preferences from a small sample of viewed items). In this context, it is critically important to embed prior knowledge of the relative importance of attributes to a specific preference context. Moreover, the relative importance of attributes is likely to be product and situation specific. Second, in an online setting, preference is only one of many factors that affect viewing time for an item or page. Thus, to make effective recommendations with limited data, it is necessary to statistically control for known effects of other factors on viewing time and isolate the viewing time – preference relationship. In this research, we present initial approaches to addressing each of these two challenges.
Fostering Preschoolers' Narrative Comprehension through Inference Making and Story Reenactment Training

1 1. CHAPTER 1: INTRODUCTION 4 1.1 Promoting Inference Making Abilities: Focus on Structure vs. Focus on Text 9 1.1.1 Story Grammar Training Programs: Focus on Structural Inferences 10 1.1.2 Text-based Inference Training: Focus on Text 26 1.1.3 Combination of Story Grammar and Text-based Inference Training.34 1.1. 4 Is there an optimal type of inference training for preschoolers? 36 1.2 Other Strategies that Foster Preschoolers’ Narrative Comprehension: Retelling vs. Reenactment 38 1.2.1 Story Retelling 38 1.2.2 Story Reenactment 40 1.2. 3 Pulling it all together: Would reenacment affect comprehension differently according to the inference strategy being fostered? 43 1.3 The Current Study 45 1.3. 1 Other Factors for Engaging Preschoolers in Book Reading Activities.50 1.3. 2. Hypotheses and Predictions 55 2. CHAPTER 2: METHOD 57 2.1 Participants 57 2.2 Study Design and Procedure 57
The language of first-order logic - including the Macintosh version of Tarski's world 4.0, Third Edition

The Language of First-Order Logic is a complete introduction to first-order symbolic logic, consisting of a computer program and a text. The program, an aid to learning and using symbolic notation, allows one to construct symbolic sentences and possible worlds, and verify that a sentence is well formed. The truth or falsity of a sentence can be determined by playing a deductive game with the computer.
GPU acceleration of matrix-based methods in computational electromagnetics

This work considers the acceleration of matrix-based computational electromagnetic (CEM) techniques using graphics processing units (GPUs). These massively parallel processors have gained much support since late 2006, with software tools such as CUDA and OpenCL greatly simplifying the process of harnessing the computational power of these devices. As with any advances in computation, the use of these devices enables the modelling of more complex problems, which in turn should give rise to better solutions to a number of global challenges faced at present. For the purpose of this dissertation, CUDA is used in an investigation of the acceleration of two methods in CEM that are used to tackle a variety of problems. The first of these is the Method of Moments (MOM) which is typically used to model radiation and scattering problems, with the latter begin considered here. For the CUDA acceleration of the MOM presented here, the assembly and subsequent solution of the matrix equation associated with the method are considered. This is done for both single and double precision floating point matrices. For the solution of the matrix equation, general dense linear algebra techniques are used, which allow for the use of a vast expanse of existing knowledge on the subject. This also means that implementations developed here along with the results presented are immediately applicable to the same wide array of applications where these methods are employed. Both the assembly and solution of the matrix equation implementations presented result in significant speedups over multi-core CPU implementations, with speedups of up to 300× and 10×, respectively, being measured. The implementations presented also overcome one of the major limitations in the use of GPUs as accelerators – that of limited memory capacity – with problems up to 16 times larger than would normally be possible being solved. The second matrix-based technique considered is the Finite Element Method (FEM), which allows for the accurate modelling of complex geometric structures including non-uniform dielectric and magnetic properties of materials, and is particularly well suited to handling bounded structures such as waveguide. In this work the CUDA acceleration of the cutoff and dispersion analysis of three waveguide configurations is presented. The modelling of these problems using an open-source software package, FEniCS, is also discussed. Once again, the problem can be approached from a linear algebra perspective, with the formulation in this case resulting in a generalised eigenvalue (GEV) problem. For the problems considered, a total solution speedup of up to 7× is measured for the solution of the generalised eigenvalue problem, with up to 22× being attained for the solution of the standard eigenvalue problem that forms part of the GEV problem.
Next generation mobile care solution

Customer care has evolved over the years. In the pursuit for cost effective options that would result in reducing the cost on maintaining a large customer support team, IVR was developed to provide automated response based on a selection made by the user. Though IVR did reduce the number of support staff, the use of an expensive communication line was not economical. The cost involved in IVR coupled with the need for self care strategies and increase in the number of mobile handset users lead to the development of mobile self care strategies. Current mobile care solutions mimic the IVR scenarios and only provide a mobile application which gives the response which was previously given by the IVR. The only difference is the visual interface rather than the audio response. This type of solution does not utilize the features provided by mobile technology in offering mobile based support. This paper defines the logical architecture for the next generation mobile care solution that performs event based mobile care and proactive mobile care, in addition to the usual selection based care. Use cases are presented, from enterprise context as well as telecom service provider context on how best to offer mobile care. The paper also details the interactions with enterprise systems and gives an overview on the development of advanced features like voice based selection. The paper concludes with a discussion on the scope of future work, after detailing a strategy for implementation and the key factors to be considered while defining a strategy.
Extended Partial Parsing for Lexicalized Tree Grammars

Existing parsing algorithms for Lexicalized Tree Grammars (LTG) formalisms (LTAG, TIG, DTG, . ) are adaptations of algorithms initially dedicated to Context Free Grammars (CFG). They do not really take into account the fact that we do not use context free rules but partial parsing trees that we try to combine. Moreover the lexicalization raises up the important problem of multiplication of structures, a problem which does not exist in CFG. This paper presents parsing techniques for LTG taking into account these two fundamental features. Our approach focuses on robust and pratical purposes. Our parsing algorithm results in more extended partial parsing when the global parsing fails and in an interesting average complexity compared with others bottom-up algorithms.
Fusion of myoelectric and near-infrared signals for prostheses control

Assistive tools for mobility and manipulation require sophisticated control interfaces, tailored to the capacity of the user while compensating limitations, such as muscle fatigue. The key to control-transparency for the patient, safety and security during operation, and real-time performance of the assistive device are astute sensors. In this contribution we bring forward a novel sensor, in which we combine a myoelectric and a near-infrared sensor, to detect muscle exertions for the real-time control of assistive devices. Since our research of over more than a decade now focuses on the electronic control of prostheses for the upper-extremity, as used by patients with either above- or below elbow amputations, we provide solid examples from this domain. As the presented technology can clearly be used to control also many other assistive devices, we predominantly indicate it for individuals who cannot directly use body-powered devices for their daily activities. For the successful application of our sensors, a patient is only required to willingly isolate the contraction of extant muscles, for which a minimal-threshold myoelectric or reflected near-infrared signal can be measured cutaneously. Experiments with the miniature sensors show, that the combined sensor works very well and the spatial resolution surpasses that of existing devices. Furthermore, the fused signal can be readily used as input to a classifier and allows to adjust for the effects of muscle fatigue.
A Simulation Environment for Real-Time Shared-Memory Architecture

CERTIFICATE This is to certify that the thesis titled A Simulation Environment for Real-Time Shared-Memory Architecture submitted by Santashil Pal Chaudhuri, to the Department of Computer Science and Engineering, in partial fulfillment for the award of the degree of Bachelor of Technology is a bonafide record of work carried out by him under our supervision and guidance. The thesis has fulfilled all the requirements as per the regulations of this institute and, in our opinion, has reached the standard needed for submission. 1 Acknowledgement I am greatly indebted to my supervisors Dr. Anupam Basu and Dr. R. Badrinath for their invaluable guidance and encouragement throughout the course of this work. I would like to use this opportunity to extend my thanks to all my classmates for creating a wonderful environment in the software laboratory.
Performance evaluation of selective summary cache via simulations

Web caching is a mechanism used to store frequently accessed documents at a server closer to the users. In e-commerce applications and financial market services, information contained in the objects delivered by the origin server to the clients can rapidly change with time. Therefore, the challenge is not only to locate a cache that contains the required object but also to select the most current version of the object out of all the possible caches. While there are several approaches to locate the cached objects in the Internet in the case of static objects, the extension of these methods to rapidly changing objects is not straightforward. As such, we developed a new method called the selective summary cache to locate the best possible version of the object. In this paper, we present the simulation results that compare the performance of selective summary cache with that of the summary cache. Following on from the results of the simulations, we were able to introduce modifications to improve the performance of the selective summary cache.
TRUFFLES — A SECURE SERVICE FOR WIDESPREAD FILE SHARING

Truffles is a system meant to address some of the major issues that still make it difficult to share files between users at different sites. In particular, it addresses the problems associated with secure file sharing, and the problems of high administrative overhead. Truffles will combine facilities of the Ficus file system and TIS/PEM, a privacy enhanced mail system, to make file sharing considerably easier. Truffles must deal with several important security problems, including secure transport of data, authentication of the users sharing files, handling of different administrative domains, and permitting system administrators to control, flexibly, yet easily, what sorts of sharing are done. This paper describes these problems and the solutions Truffles will use.
Combinatorial Scientific Computing

Combinatorial Scientific Computing explores the latest research on creating algorithms and software tools to solve key combinatorial problems on large-scale high-performance computing architectures. It includes contributions from international researchers who are pioneers in designing software and applications for high-performance computing systems. The book offers a state-of-the-art overview of the latest research, tool development, and applications. It focuses on load balancing and parallelization on high-performance computers, large-scale optimization, algorithmic differentiation of numerical simulation code, sparse matrix software tools, and combinatorial challenges and applications in large-scale social networks. The authors unify these seemingly disparate areas through a common set of abstractions and algorithms based on combinatorics, graphs, and hypergraphs. Combinatorial algorithms have long played a crucial enabling role in scientific and engineering computations and their importance continues to grow with the demands of new applications and advanced architectures. By addressing current challenges in the field, this volume sets the stage for the accelerated development and deployment of fundamental enabling technologies in high-performance scientific computing.
A COMPARATIVE STUDY OF THE EFFICIENCY OF DIFFERENT MEASURES TO CLASSIFY ARABIC TEXT

The aim of this study is to find the optimal method that can be used to classify Arabic text among the six methods (inner product, cosine, Jaccard, Dice, Naive Bayesian, and Euclidean). Automatic text classification has been needed in many fields for a long time. Many methods are used to classify text. This study will investigate the use of TF-IDF to obtain document vector. A document vector will be used to compute and compare four different associative coefficients of the vector space model (VSM) based on the inner product, cosine, Jaccard and Dice, in order to find the best for Arabic text classification. We found that the cosine measure outperformed the other three associative coefficients of the VSM. Finally we compare the efficiencies of the cosine measure, Naive Bayesian, and Euclidean Measure to classify Arabic text. Experimental results on the same set of Arabic documents used before show that Naive Bayesian slightly outperforms the other methods. Comparison reported in this paper shows that the Naive Bayesian method surpasses the other five methods.
Accurate Gait Phase Detection using Surface Electromyographic Signals and Support Vector Machines

Modern components and materials allow creating increasingly complex, multi-functional prostheses with userspecific intelligent behavior. Complex behavior control, though, has to employ more accurate and precise models of the amputee and his prosthesis to be able to make use of the prosthesis’ complete functionality. In this work, we concentrate on the accurate phase detection within a fine-grained and state-full gait model for the continuous level gait. To this, we rely on four electromyography (EMG) sensors, placed at the thigh, and two force sensing resistors (FSR), placed below the heel and the toe. FSRs and a timed gait model are used to automatize EMG data recordings. Afterwards, gait model performance is verified using only EMG data. Here, we use support vector machines to detect muscular activity changes, indicating a new gait phase and therefore, a state switch within the gait model. We show that our approach generalizes well, even when using only 20 to 30 seconds for training. The gait model reaches accuracies of roughly 67% for an amputee and of 75% for a non-amputee individual when using a precise, seven phase level gait model.