Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing choral intonation in unaccompanied tonal music: a curriculum and pedagogical approach to teach choirs to sing in just intonation

IX ACKNOWLEDGEMENTS . X LIST OF TABLES . XI LIST OF FIGURES . XIV LIST OF AUDIO AND VISUAL RECORDINGS . XVI GLOSSARY OF TERMS AND ABBREVIATIONS . XVII CHAPTER 1: INTRODUCTION . 1 Personal Rationale . 1 The Problem . 2 Reasons for the Problem . 3 Just Intonation: A Partial Solution to the Problem . 6 Research Aim . 18 Implementation of the Approach . 19 Evaluation of the Approach . 19 CHAPTER 2: REVIEW OF THE LITERATURE AND RELATED STUDIES 20 The Purpose . 20 The Review Process. 20 Reasons for Intonation Problems in Choirs . 24 Solutions to Intonation Problems in Choirs . 25 ENHANCING CHORAL INTONATION Volume 1: Thesis iii References to Just Intonation . 27 Just Intonation: A Tool for Tuning Unaccompanied Choral Music . 32 Just Ratios and Intonations . 32 Harmonics . 34 Tune-Up Process. 36 Resultant Tones . 40 Summation Tones. 41 Difference Tones. 43 Tuning Systems . 45 Equal Temperament. 46 Quarter-Comma Meantone Temperament. 48 Pythagorean Temperament. 49 Just Intonation. 51 Curricula and Pedagogical Approaches for Teaching Just Intonation to Choirs . 55 Approach 1: Zoltán Kodály and Pál Kardos (Hungary) . 55 Approach 2: Ross Duffin (USA). 58 Approach 3: James Jordan, Michael Mehaffey and Marilyn Shenenberger (USA) . 58 Approach 4: Per-Gunnar Alldahl (Sweden) . 59 Summary . 61 CHAPTER 3: CURRICULUM AND PEDAGOGY . 62 Part 1: The Creation of the Curriculum and Pedagogy . 63 AWJITS: Their Development . 64 Analysis. 67 ENHANCING CHORAL INTONATION Volume 1: Thesis iv Application . 69 The Underpinning Processes and Conventions. 71 The Learning Environment. 71 The Conductor. 72 Score and Rehearsal Preparation Process. 74 Chorister Placement and Choir Formations. 74 Teaching and Learning Process. 75 Just Intonation. 75 Listening. 75 Tuning Process. 76 Acoustical Adaptation Process. 80 Keyboards. 81 Part 2: The Score and Rehearsal Preparation Process . 82 Score Analyses and Annotations . 83 Modulations. 83 No modulations. 84 Momentary modulations. 85 Established modulations. 87 Just Intonation Calculations. 90 Orientation Notes. 95 Intonation Bases. 96 The origin base. 99 The progressive base. 99 The zero base. 100 Calculation of cents and assignment of AWJITS. 106 Origins. 106 Subsidiaries. 107 Roots. 110 Harmony and non-harmony notes. 113 Secondary dominant chords. 115 Pivot chords. 116 Notational adjustments. 116 ENHANCING CHORAL INTONATION Volume 1: Thesis v Preparation of Notes . 118 Part 3: The Teaching and Learning Model . 120 Assessment . 120 The Foundation Stage . 121 The Orientation Phase. 122 The Accuracy Phase. 122 The Text Phase. 122 The Technical Phase. 124 The Intonation Stage . 125 The Initiation Phase. 126 Just ratios and intonations. 127 Matching harmonics. 127 Reading AWJITS. 128 Tuning different intonations of pitch classes. 132 Stabilising modulations. 137 The Familiarisation Phase. 141 The Realisation Phase.
Female Spectators, Agency, and the Politics of Pleasure: An Historical Case Study from Australian Rules Football

Abstract This paper explores descriptions, commentary and critiques regarding the Melbourne women who came to follow Australian Rules football with notable passion in the late 1800s and early 1900s. While it is known that the press represented female spectators in various ways, the depictions of the women who shouted and ‘barracked’ in a manner similar to the men have not been studied in detail. This paper aims to redress this by drawing on the women’s and ‘social’ pages of Melbourne newspapers, especially those of the ‘Ladies Letters’ published in Melbourne Punch. Purportedly written by upper class women, these letters provide an intriguing perspective on the zealous spectator culture that was emerging around Australian Rules football, the women who were a key part of this culture, and the broader debates and politics around women’s rights and gender identity. At issue are intersecting questions of pleasure, rationality, class, gender and race that shed light on the new cultural category of the ‘barracker’.
Empirical Study of a Probabilistic Network Model for Retrieving Traceability Links

Requirements traceability provides critical support in helping manage the evolution of software systems. Establishing and maintaining trace links is an arduous problem requiring intensive human effort when traces need to be established manually. Automatic retrieval tools can help maintain traceability links by dynamically identifying traces between artifacts. In order to effectively reduce the effort involved in evaluating the correctness of the retrieved links such automatic tools must achieve high retrieval performance. This paper presents results of experimental studies to analyze the performance of a dynamic trace retrieval approach implementing a probabilistic information retrieval network. The experiments are conducted on three different datasets. An implementation of the retrieval approach described in the paper involves the definition of a small training set for which correct traces are previously defined. This can be accomplished by either using past knowledge or by manually evaluating the traces in the generated training set. A study explores the effect of different sized training sets on the retrieval performance of the automatic tool. A second study analyzes methods for defining confidence values, which are attached to each (un)retrieved trace to indicate how confident we are that the dynamically retrieved trace represents a true link, or vice versa that the link that are not retrieved by the tool are in fact false links. The results of this research are beneficial for enhancing the utility and performance of dynamic tracing tools.
A Model of the Acquisition of Spatial-Relation Concepts and Words

This paper is about the acquisition of spatial relations, both conceptual and linguistic. Spatial relations, we propose, are defined by correlations across different perceptual modalities. The nature of the correlations that define a relation determines how hard learning a word for that relation will be. We present a connectionist model that learns about relations in two phases, a pre-linguistic phase in which concepts are organized according to the perceptual input, and a linguistic phase, in which preexisting concepts are re-organized under the influence of words. This model accounts for the order in which spatial relation terms are learned by children.
Triage protein fold prediction

We have constructed, in a completely automated fashion, a new structure template library for threading that represents 358 distinct SCOP folds where each model is mathematically represented as a Hidden Markov model (HMM). Because the large number of models in the library can potentially dilute the prediction measure, a new triage method for fold prediction is employed. In the first step of the triage method, the most probable structural class is predicted using a set of manually constructed, high‐level, generalized structural HMMs that represent seven general protein structural classes: all‐α, all‐β, α/β, α+β, irregular small metal‐binding, transmembrane β‐barrel, and transmembrane α‐helical. In the second step, only those fold models belonging to the determined structural class are selected for the final fold prediction. This triage method gave more predictions as well as more correct predictions compared with a simple prediction method that lacks the initial classification step. Two different schemes of assigning Bayesian model priors are presented and discussed. Proteins 2002;48:654–663. © 2002 Wiley‐Liss, Inc.
Trust-based fusion of classifiers for static code analysis

Static code analysis tools automatically generate alerts for potential software faults that can lead to failures. However, developers are usually exposed to a large number of alerts. Moreover, some of these alerts are subject to false positives and there is a lack of resources to inspect all the alerts manually. To address this problem, numerous approaches have been proposed for automatically ranking or classifying the alerts based on their likelihood of reporting a critical fault. One of the promising approaches is the application of machine learning techniques to classify alerts based on a set of artifact characteristics. The effectiveness of many different classifiers and artifact characteristics have been evaluated for this application domain. However, the effectiveness of classifier fusion methods have not been investigated yet. In this work, we evaluate several existing classifier fusion approaches in the context of an industrial case study to classify the alerts generated for a digital TV software. In addition, we employ a trust-based classifier fusion method. We observed that our approach can increase the accuracy of classification by up to 4%.
How Children Process Overregularizations : Evidence from Event-Related Brain Potentials *

This study examines the mental processes involved in children’s on-line recognition of inflected word forms using event-related potentials (ERPs). 60 children in three age groups (20 six-to-seven-year olds, 20 eight-to-nine-year olds, 20 eleven-to-twelve-year olds) and 23 adults (tested in a previous study) listened to sentences containing correct or incorrect German noun plural forms. In the two older child groups as well as in the adult group, overregularized plural forms elicited brain responses that are characteristic of combinatorial (grammatical) violations. We also found that ERP components associated with language processing change from child to adult with respect to their onsets and their topography. The ERP violation effects obtained for overregularizations suggest that children (aged eight years and above) and adults employ morphological computation for processing purposes, consistent with dual-mechanism models of inflection. The observed differences between children’s and adults’ ERP responses are argued to result from children’s smaller lexicon and from slower and less efficient processing.
Iterative Airline Scheduling

In airline scheduling a variety of planning and operational decision problems have to be solved. We consider the problems aircraft routing and crew pairing: Aircraft and crew must be allocated to flights in a schedule in a minimal cost way. Although these problems are not independent, they are usually formulated as independent mathematical optimisation models and solved sequentially. This approach might lead to a suboptimal allocation of aircraft and crew, since a solution of one of the problems may restrict the solution of the problem solved later. Also, when minimal cost solutions are used in operations, a short delay of one flight can cause very severe disruptions of the schedule later in the day. We generate solutions that incur small costs and are also robust to typical stochastic variability in airline operations. We solve the two original problems iteratively. Starting from a minimal cost solution, we produce a series of solutions which are increasingly robust. Using data from domestic airline schedules we evaluate the benefits of the approach as well as the trade-off between cost and robustness. We extend our approach considering the aircraft routing problem together with two crew pairing problems, one for technical crew and one for flight attendants.
On the Relationship between Abduction and Deduction

n a The aim of this paper is at analyzing from various points of view the relationships betwee bduction and deduction. In particular, we consider a meta-level definition of abduction in l d terms of deduction, similar to various definitions proposed in the literature, and an object-leve efinition in which abductive conclusions are expressed as a logical consequence of the obser. T vations and of a simple transformation of the domain theory based on predicate completion he equivalence between the two definitions is proved for domain theories of considerable s expressive power. The object-level characterization we propose uses very simple forms of rea oning and the equivalence result allows us to make explicit some of the assumptions underly-
Development of a dual burn-in policy for semiconductor products based on the number of defective neighborhood chips

Most of the previous studies on developing an optimal burn-in policy for semiconductor products only deal with the burn-in process itself and little is concerned with utilizing the information on the quality levels of chips before being subjected to burn-in. Developed in this paper is a dual burn-in policy in which the number of chips (d) which do not pass the wafer probe (WP) test and lie in the neighborhood of a reference chip is utilized as an indicator on the quality level of that reference chip. The dual burn-in policy first classifies the chips which pass the WP test into two groups using a boundary value of d, and then each group is subject to burn-in for its own duration. For a certain type of 256M DRAM product, the performance of the proposed dual burn-in policy is compared to that of the single burn-in policy in which all chips are subjected to the burn-in of the same duration without considering d. The analysis results show that, for the cases considered, the proposed dual burn-in policy is more cost-effective than the single burn-in policy, implying that the additional information from the WP test is beneficial to establishing an efficient burn-in policy in semiconductor manufacturing.
Hierarchical variational Bayesian matrix co-factorization

Matrix co-factorization involves jointly decomposing several data matrices to approximate each data matrix as a product of two factor matrices, sharing some factor matrices in the factorization. We have recently developed variational Bayesian matrix co-factorization where factor matrices are inferred by computing variational posterior distributions in the case of Gaussian likelihood with Gaussian prior placed on factor matrices. Empirical Bayesian method was used, so hyperparameters are set to specific values determined by maximizing marginal likelihood. In this paper we present a hierarchical Bayesian model for matrix co-factorization in which we derive a variational inference algorithm to approximately compute posterior distributions over factor matrices as well as hyperparameters, placing Gaussian-Wishart prior on hyperparameters. Numerical experiments on MovieLens data demonstrate that the hierarchical variational Bayesian matrix co-factorization alleviates the over-fitting better than the empirical variational Bayesian matrix co-factorization, leading to the improved performance in terms of MAE and RMSE.
A Data Complexity Analysis on Imbalanced Datasets and an Alternative Imbalance Recovering Strategy

The imbalance dataset problem arises in many domains, such as Web page search, scam sites detection. In this paper, we propose an alternative re-sampling approach to deal with imbalance datasets. We demonstrate this approach with a concrete implementation and it has shown promising results when compared to other standard approaches that deals with imbalance dataset. We have also performed an analysis of the data complexity to help understand imbalanced dataset, which has also shown to be a promising approach
Combating Implicit Bias With Meditation

We investigated the effects of a mindfulness meditation and loving-kindness meditation on implicit bias as well as the cognitive and emotional pathways through which these techniques act. We did this through a lab experiment in the Wharton Behavioral Lab in January 2017. We randomized 224 participants into three groups: a mindfulness meditation group, a loving-kindness meditation group, and a mind-wandering control group. After receiving one of the inductions, participants completed an Implicit Association Test measuring implicit bias against people with disabilities (IAT: Greenwald et al.,1988), as well as a set of survey questions. Although we were unable to demonstrate a reduction in overall implicit bias scores, we found a significant reduction in error percentage on the IAT for participants in the loving-kindness meditation group as compared to the control group. This effect was mediated by state compassion and positive state pleasantness, and is suggestive of reduced implicit bias.
Molecular Docking and Structure-Based Drug Design Strategies

Pharmaceutical research has successfully incorporated a wealth of molecular modeling methods, within a variety of drug discovery programs, to study complex biological and chemical systems. The integration of computational and experimental strategies has been of great value in the identification and development of novel promising compounds. Broadly used in modern drug design, molecular docking methods explore the ligand conformations adopted within the binding sites of macromolecular targets. This approach also estimates the ligand-receptor binding free energy by evaluating critical phenomena involved in the intermolecular recognition process. Today, as a variety of docking algorithms are available, an understanding of the advantages and limitations of each method is of fundamental importance in the development of effective strategies and the generation of relevant results. The purpose of this review is to examine current molecular docking strategies used in drug discovery and medicinal chemistry, exploring the advances in the field and the role played by the integration of structure- and ligand-based methods.
A general algorithm for triangular meshes simplification

This article introduces the algorithm for simplification of 2D and 3D triangular meshes. The algorithm evaluates and removes vertices. A hash table is used to speed up the process of selecting the appropriate vertex for its removal. Therefore, this part of the algorithm is executed in constant time O(1). In spite of simplification, triangular mesh models still keep majority of their own essential characteristics. With simplification we also ease transfer of such models through the web.
Object tracking by the mean-shift of regional color distribution combined with the particle-filter algorithms

This paper presents a method for tracking a person in a video sequence in real time. In this method, the profile of color distribution characterises target's feature. It is invariant for rotation and scale changes. It is also robust to non-rigidity and partial occlusion of the target. We employ the mean-shift algorithm to track the target and to reduce the computational cost. Moreover, we incorporate the particle-filter into it to cope with a temporal occlusion of the target, and largely reduce the computational cost of the original particle-filter. Experiments show the availability of this method.
Fair distributed Congestion Control with transmit power for vehicular networks

We model the problem of beaconing congestion control as a Network Utility Maximization (NUM) transmit power allocation problem. We propose a distributed congestion control algorithm by transmit power adaptation called FCCP, which allows to dynamically select the appropriate fairness notion. Our results show that FCCP converges to the close proximity of the optimal value both in static and dynamic multihop scenarios while keeping the channel load at the desired level.
Hierarchical Higher Level Data Fusion using Fuzzy Hamming and Hypercube Clustering

Currently, analysts receive enormous amount of information from multiple sensors and resources. In addition to knowledge bases and traditional databases, enormous volumes of unstructured information are now available and are presented to the analyst [1], [35], [26]. This presents a significant challenge since different pieces of information from several heterogeneous data sources must be fused in order to generate conclusions relevant to the task at hand. The analyst is then left to sift through the information to analyze and interpret their contents and infer (uncover) what he or she is seeking. This process can be tedious and time-consuming and in many cases impractical when important events are unfolding rapidly. An automated means for this extraction of relevant pieces of information and their unification into a useful product for the analyst is much needed. In order to address the problems of data gathering, fusion and extraction, The Joint Directors of Laboratories (JDL) Data Fusion Sub-panel developed a fivelevel Data Fusion Model [36]. Level 1 on Object refinement seems to have received the most attention. Level one processing functions include: data alignment, association, tracking, and identification. Less mature are Level 2 processing [17], [30], situation assessment, which seeks a higher level of inference above level one processing, and Level 3 processing which performs threat/impact assessment. Threat assessment is an iterative process of fusing the combined activity and capability of enemy forces to infer their intentions and assess the threat that they pose. Level 1 is very often called as “low-level” processing, and the others as “high-level” processing. Higher level fusion problems are generally more difficult than level 1 because they involve higher dimensionality corresponding to the relationships among entities identified at level 1. Higher level fusion also concerns modeling behavior of aggregate entities, through the understanding of their individual behaviors and relationships. Some commonly recognized relationships are spatio-temporal relationships, part/whole relationships, organizational relationships, various causal relationships, semantic relationships, similarity relationships, etc. To represent these relationships we use (ARGs) Attributed Relational Graphs [11]. ARGs are rich data structures to represent level 1 objects along with higher level relationships as outlined above. In these ARGs, nodes represent people, organizations, location, individuals or facilities. Edges represent relationships like communication, radio, electronic, or telephone. Attributes store the details of each node and edge, like a individual’s name or an event’s time of occurrence. When we represent data as ARGs the problem of graph matching is of most importance when retrieving relevant information. In this research we enhance level 2 and 3 fusion capability through a new class of hierarchical models
Scheduling Distributable Real-Time Threads in Middleware

We present the Tempus real-time middleware. Tempus supports Real-Time CORBA 2.0’s distributable threads (DTs) as an end-to-end programming abstraction for distributed real-time systems. DTs in Tempus can have time constraints, including time/utility functions (TUFs), can have resource constraints, particularly mutual exclusion, and can be scheduled according to utility accrual (UA) disciplines. Tempus propagates the scheduling parameters of DT’s as they transit objects and hence perhaps node boundaries. Node-local instances of a UA scheduling algorithm use the propagated parameters to construct local schedules and resolve resource dependencies for local timeliness optimization, toward approximate, system-wide timeliness optimality. Tempus uses an application-level scheduling framework for node-local TUF/UA scheduling on real-time POSIX-compliant operating systems. Our experimental measurements demonstrate the effectiveness of the middleware in scheduling DTs.