Miracle-dz/UniFAR-FTUs huggingface dataset:
A Conditional Random Field Framework for Robust and Scalable Audio-to-Score Matching

In this paper, we introduce the use of conditional random fields (CRFs) for the audio-to-score alignment task. This framework encompasses the statistical models which are used in the literature and allows for more flexible dependency structures. In particular, it allows observation functions to be computed from several analysis frames. Three different CRF models are proposed for our task, for different choices of tradeoff between accuracy and complexity. Three types of features are used, characterizing the local harmony, note attacks and tempo. We also propose a novel hierarchical approach, which takes advantage of the score structure for an approximate decoding of the statistical model. This strategy reduces the complexity, yielding a better overall efficiency than the classic beam search method used in HMM-based models. Experiments run on a large database of classical piano and popular music exhibit very accurate alignments. Indeed, with the best performing system, more than 95% of the note onsets are detected with a precision finer than 100 ms. We additionally show how the proposed framework can be modified in order to be robust to possible structural differences between the score and the musical performance.
The shifting phenological landscape: Within‐ and between‐species variation in leaf emergence in a mixed‐deciduous woodland

Abstract Many organisms rely on synchronizing the timing of their life‐history events with those of other trophic levels—known as phenological matching—for survival or successful reproduction. In temperate deciduous forests, the extent of matching with the budburst date of key tree species is of particular relevance for many herbivorous insects and, in turn, insectivorous birds. In order to understand the ecological and evolutionary forces operating in these systems, we require knowledge of the factors influencing leaf emergence of tree communities. However, little is known about how phenology at the level of individual trees varies across landscapes, or how consistent this spatial variation is between different tree species. Here, we use field observations, collected over 2 years, to characterize within‐ and between‐species differences in spring phenology for 825 trees of six species (Quercus robur, Fraxinus excelsior, Fagus sylvatica, Betula pendula, Corylus avellana, and Acer pseudoplatanus) in a 385‐ha woodland. We explore environmental predictors of individual variation in budburst date and bud development rate and establish how these phenological traits vary over space. Trees of all species showed markedly consistent individual differences in their budburst timing. Bud development rate also varied considerably between individuals and was repeatable in oak, beech, and sycamore. We identified multiple predictors of budburst date including altitude, local temperature, and soil type, but none were universal across species. Furthermore, we found no evidence for interspecific covariance of phenology over space within the woodland. These analyses suggest that phenological landscapes are highly complex, varying over small spatial scales both within and between species. Such spatial variation in vegetation phenology is likely to influence patterns of selection on phenology within populations of consumers. Knowledge of the factors shaping the phenological environments experienced by animals is therefore likely to be key in understanding how these evolutionary processes operate.
Annotated dynamic texture graph

We introduce annotated dynamic texture graph (ADTG) for nonlinear motion synthesis, with applications to learning models of human pose and motion from capture data. Our method is based on clustering the motion data into motion primitives that capture local dynamical characteristics - dynamic texture, modeling the dynamics in each cluster using linear dynamic system (LDS), annotating those LDS' which have clear meaning and calculating the cross-entropy between frames of LDS' to construct a directed graph which has two-level structure. The lower level retain the detail and nuance of live motion, while the higher level generalizes motion and encapsulates connections among LDS'. Our results show that this framework can generates lifelike, controllable motion in interactive environments.
Structure and assembly of an augmented Sm-like archaeal protein 14-mer

To better understand the roles of Sm proteins in forming the cores of many RNA-processing ribonucleoproteins, we determined the crystal structure of an atypical Sm-like archaeal protein (SmAP3) in which the conserved Sm domain is augmented by a previously uncharacterized, mixed α/β C-terminal domain. The structure reveals an unexpected SmAP3 14-mer that is perforated by a cylindrical pore and is bound to 14 cadmium (Cd2+) ions. Individual heptamers adopt either “apical” or “equatorial” conformations that chelate Cd2+ differently. SmAP3 forms supraheptameric oligomers (SmAP3)n = 7,14,28 in solution, and assembly of the asymmetric 14-mer is modulated by differential divalent cation-binding in apical and equatorial subunits. Phylogenetic and sequence analyses substantiate SmAP3s as a unique subset of SmAPs. These results distinguish SmAP3s from other Sm proteins and provide a model for the structure and properties of Sm proteins >100 residues in length, e.g., several human Sm proteins.
The Wage Gap between Francophones and Anglophones: A Canadian Perspective, 1970-2000

The wage gap between Francophone and Anglophone men from 1970 and 2000 fell by 25 percentage points within Quebec, but only by 10 points Canada-wide, largely because the wages of Quebec Anglophones fell by 15 points relative to other Canadian Anglophones. Accordingly, the Canadian measure of the Francophone gap better reflects the changing welfare of Francophones than the Quebec measure. Over half of the reduction in the Canadian Francophone wage gap is explained by rising Francophone education levels. In Quebec, the declining number and relative wages of Anglophone workers is best explained by a falling demand for English-speaking labour.
Stereo Processing of HRSC Mars Express Images by Semi-Global Matching

The High Resolution Stereo Camera (HRSC) is one of the instruments on-board ESA's Mars Express probe. It is used for visual and three dimensional mapping of the Martian surface. Airborne versions of the HRSC have been used for mapping Earth's surface from flight altitudes between 1500m and 5000m in resolutions up to 15cm/pixel. Stereo matching is one of the most critical steps for the generation of Digital Elevation Models (DEM) from HRSC images, as it is generally ambiguous and ill posed. Most difficult to handle are often low textured areas, sharp depth discontinuities and large occlusions. Depth discontinuities and occlusions are typical for urban scenes (e.g. cities), but also for rough terrain. Additionally, computation time is critical due to the huge amount of high resolution data. Local, correlation based stereo matching methods are often employed due to their efficiency. However, they are well known for having problems at low textures and blurring depth discontinuities, depending on the size and shape of the correlation window. Global energy minimization approaches have been shown to perform much better due to pixel-wise matching, supported by a discontinuity preserving smoothness constraint. However, the complexity and run-time of global methods is usually very high. The Semi-Global Matching (SGM) method [1] combines the best features of both strategies. It has been shown [1, 2] that its performance is comparable to that of some of the best stereo matching methods, but its complexity is that of typical local methods, i.e. linear to the number of pixels and the disparity range. The SGM method has been applied to the stereo matching problem of terrestrial HRSC images [3]. All pixels are projected onto a common surface for creating nine 2D pushbroom images from each of the nine sensor lines. The camera positions and orientations along the flight path are used for calculating epipolar lines, along which stereo matching is performed. The explicit calculation of epipolar lines is necessary for minimizing computation time, as pushbroom images can generally not be corrected such that epipolar lines are exactly straight [3]. A Mutual Information based matching cost is used by SGM, which makes matching insensitive against many radiometric transformations that often occur in practice. Furthermore, it even allows to perform matching between radiometrically different (e.g. color) channels, which is done for increasing redundancy and decreases matching errors. The method has been implemented on a processing cluster, which allows DEM and true ortho image generation of hundred of square kilometers in resolutions of 20cm/pixel within just a few days. Around 14000 km² of terrestrial HRSC data have been processed up to now. The results are generally very good, especially for difficult scenes like cities. It is obvious that the same processing strategies could be advantageous for Martian HRSC data too. This paper describes all processing steps for the creation of DEM's and true ortho images from Martian HRSC data. The unprojected HRSC images and the corresponding external
To Improve the Performance of Secondary Structure Prediction by Soft Computing Technique

Proteins, one of the basic building blocks of all the organisms, need exploratory techniques to predict its complex structures. Machine learning technique such as neural network has been widely used in predicting secondary structures of amino acid sequences. Today, the main aim is to improve the performance of secondary structure predictions by learning a predictive model trained on known structures. Multi-layered feed forward neural network model is trained with the help of hidden layer and by varying sliding window size to determine optimal window size giving highest accuracy. Binary bit encoding scheme is used to encode input training sequence in 3 state DSSP codes. The current efficiency achieved through this technique has reached up to 70% . The experimental results reveal that the following proposed algorithm yields an improved performance with an accuracy of 80%. Proteins are a class of nitrogenous organic compounds made up of one or more long chains of amino acids and are one of the most basic components in all organisms. On the smallest level, proteins are made up of linear sequences of twenty natural amino acids joined together with the help of peptide or covalent bonds. This forms the Primary structure of proteins. Secondary structure of sequences is formed when linear chain of primary structure begins to twist. In an amino acid chain, each amino acid interacts with other amino acids to form three sub-structures-alpha helix, beta sheets and coils. When amino acids begin to twist and fold even more and form bonds using disulphide bridges a three dimensional structure is formed. This three dimensional structure of a single protein molecule or a polypeptide chain is called tertiary structure. The quaternary structure is the final dimensional structure formed by all the polypeptide chains making up protein. It is composed of two or more sub units of tertiary structures. A. Biological Neural Network A neuron is a fundamental unit of a neural network. It consists of 3 parts - dendrites, soma and axon. Dendrites are the tree-like structure that receives the electrical signal from the adjacent units, where each line is connected to one neuron. Axon is a single, long connection extending from the cell body and carrying the signals from the neuron. The end of the axon splits into fine strands. At the end of axon, the contact to the dendrites is made through a synapse. It is through synapse that the neuron introduces its signals to the other nearby neurons. A neuron fires an electrical impulse only if certain condition is met. If the sum of the input signals into one neuron surpasses a certain threshold, the neuron transmits this electrical signal along the axon.
Scalable RDF Views of Relational Databases through Partial Evaluation

The semantic web represents meta-data as a triple relation using the RDF data model. We have developed a system to process queries to RDF views of entire relational databases. Optimization of queries to such views is challenging because i) RDF views of entire relational databases become large unions, and ii) queries to the views are more general than relational database queries, making no clear distinction between data and schema. As queries need not be expressed in terms of a schema, it becomes critical to optimize not only data access time but also the time to perform the query optimization itself. We have developed novel query optimization techniques for scalable queries to RDF views of relational databases. Our optimization techniques are based on partial evaluation, a method for compile time evaluation of subexpressions. We show dramatic improvements in query optimization time when scaling the query size while still producing high quality execution plans. Our query optimization techniques enable execution of real-world queries to RDF views of relational databases.
Improving Route Stability and Overhead on AODV  Routing Protocol and Make it Usable for VANET

one of the most important routing protocols used in Ad hoc networks is AODV. This protocol is a reactive protocol that searches routes only when they are needed. It always exchanges control packets between neighbor nodes for routing. For reduction of control overheads and bandwidth consumption and make AODV usable for VANET, we have eliminated route discovery phase by restricting neighbor’s distance and number of discovered routes. This restriction leads to reduce most of control overheads. We make an improvement on AODV and propose PAODV as routing protocol. This protocol improves AODV control overheads and makes routes more stable. One of the technical differences between MANET and VANET is mobility model. Manhattan is the mobility model for VANET that we use to evaluate our method.
Cluster Analysis of Assessment in Anatomy and Physiology for Health Science Undergraduates.

Academic content common to health science programs is often taught to a mixed group of students; however, content assessment may be consistent for each discipline. This study used a retrospective cluster analysis on such a group, first to identify high and low achieving students, and second, to determine the distribution of students within clusters based on their chosen program of study. Using a two-step cluster analysis based on five summative assessment scores for 773 undergraduate students, three distinct groups of students were identified: these are described as High Achievers, Standard Achievers, and Low Achievers. High Achievers scored higher in all five assessments compared with Standard Achievers and Low Achievers (all P < 0.01). Also, Standard Achievers scored higher than Low Achievers in all assessments. Membership of the High Achievers cluster comprised 15% Midwives, 20% Nurses, 10% Occupational Therapists, 11% Paramedics, 24% Physiotherapists, and 21% Standard Pathway students. This novel approach provides an opportunity for quantitative reflection on assessment in a large group of students with diverse career aspirations. It may be used to distinguish levels of achievement relative to peers within a group and potentially identify students within a program of study in need of academic assistance.
Designing touch-enabled electronic flight bags in SAR helicopter operations

In order to benefit from potential reduced operational costs and crew workload airlines are increasingly interested in touchscreen-based Electronic Flight Bags (EFB). This paper focuses on the specific domain of Search and Rescue (SAR) Helicopters. A first set of results aiming to explore and understand potential benefits and challenges of an EFB in a SAR environment will be presented. A review of related work, operational observations and interviews with pilots were conducted to understand and specify the use context. Digital Human Modelling (DHM) software was used to determine physical constraints of an EFB in this type of flight deck. A scenario was developed which will be used in future to define features, content and functionality that a SAR pilot may wish to see in an EFB. Developed initial interface design guidelines are presented.
Half-resolution semi-global stereo matching

Semi-global matching is a popular choice for applications where dense and robust stereo estimation is required and real-time performance is crucial. It therefore plays an important role in vision-based driver assistance systems. The strength of the algorithm comes from the integration of multiple 1D energy paths which are minimized along eight different directions across the image domain. The contribution of this paper is twofold. First, a thorough evaluation of stereo matching quality is performed when the number of accumulation paths is reduced. Second, an alteration of semi-global matching is proposed that operates only on half of the image domain without losing disparity resolution. The evaluation is performed on four real-world driving sequences of 400 frames each, as well as on 396 frames of a synthetic image sequence where sub-pixel accurate ground truth is available. Results indicate that a reduction of accumulation paths is a very good option to improve the run-time performance without losing significant quality, even on sub-pixel level. Furthermore, operating semiglobal matching only on half the image yields almost identical results to the corresponding full path integration. This approach yields the potential to further speed up the runtime and could also be exploited for other alterations of the algorithm.
Nonlinear steering and braking control for vehicle rollover avoidance

Steering and braking control is applied to avoid rollover of road vehicles. The control concept presented is composed of three feedback loops: Continuous operation steering control, emergency steering control and emergency braking control. In continuous operation the roll rate and the roll acceleration are fed back by velocity scheduled gains to the front wheel steering angle. Thereby, the vehicle's roll damping is robustly improved for a wide range of speed and height of the center of gravity. The latter may change for example with a truck from ride to ride. A rollover coefficient is defined that basically depends on the lateral acceleration at the center of gravity of the vehicle's sprung mass. For critical values of this variable the emergency steering and braking system is activated. The rollover coefficient is also used for nonlinear feedback to the front wheel steering angle. The control concept is evaluated by linear sensitivity analysis and by simulations. Additionally, absolute stability of the steering control concept is verified using Popov's criterion.
Modulation of neural connectivity during tongue movement and reading

In a functional magnetic resonance imaging (fMRI) study, a novel connectivity analysis method termed within‐condition interregional covariance analysis (WICA) was introduced for investigation into brain modulation during tongue movement and reading Chinese pinyins and logographic characters. We found that performing a horizontal tongue movement task generated a specific brain module with hierarchical orders of neural computation. Such functional modularity was further examined during both overt and silent Chinese reading tasks. Our results showed that overt pinyin reading was associated with the following distributed regions involved in tongue movement: the primary motor cortex (M1), the supplementary motor area (SMA), Broca's area, and Wernicke's area. Furthermore, we have used the WICA and demonstrated task‐dependent covariance patterns that are strongly associated with the M1 mouth/tongue region, in which the Broca‐Wernicke pathway is implicated in a meaning access procedure based on assembled phonology, while the SMA‐Broca pathway is implicated in a meaning access procedure based on addressed phonology. Our functional connectivity analysis of the neural pathway involved in language processing may provide a basis for future studies of the dynamic neural network associated with language learning and reading in both developmental and disease conditions. Hum. Brain Mapping 18:222–232, 2003. © 2003 Wiley‐Liss, Inc.
Efficient Developments in Modeling and Optimization of Solid State Fermentation

ABSTRACT Artificial intelligence techniques are important tools for modelling and optimizing the solid-state fermentation (SSF) factors. The performance of fermentation processes is affected by numerous factors, including temperature, moisture content, agitation, inoculum level, carbon and nitrogen sources, etc. In this paper, the identification of non-linear relationship between fermentation factors and targeted objectives is performed, first, using the learning capabilities of a neural network (NN). Then, this approach is coupled with various artificial intelligence techniques to optimize the fermentation process, such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The effectiveness of different approaches is compared with the classical statistical techniques, such as Response Surface Methodology (RSM), that are increasingly being used. This paper presents the first attempt to adapt these approaches on the solid state fermentation process. The obtained results prove the effectiveness of the proposed approach. Particularly, we show that this approach leads to a significant improvement on the fermentation process performance.
Exploring the similarities between potential smoothing and simulated annealing

Simulated annealing and potential function smoothing are two widely used approaches for global energy optimization of molecular systems. Potential smoothing as implemented in the diffusion equation method has been applied to study partitioning of the potential energy surface (PES) for N‐Acetyl‐Ala‐Ala‐N‐Methylamide (CDAP) and the clustering of conformations on deformed surfaces. A deformable version of the united‐atom OPLS force field is described, and used to locate all local minima and conformational transition states on the CDAP surface. It is shown that the smoothing process clusters conformations in a manner consistent with the inherent structure of the undeformed PES. Smoothing deforms the original surface in three ways: structural shifting of individual minima, merging of adjacent minima, and energy crossings between unrelated minima. A master equation approach and explicit molecular dynamics trajectories are used to uncover similar features in the equilibrium probability distribution of CDAP minima as a function of temperature. Qualitative and quantitative correlations between the simulated annealing and potential smoothing approaches to enhanced conformational sampling are established. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 531–552, 2000
Location-aware expert system design for olive fruit fly spray control

1 Abstract— Location-awareness significantly enhances the functionality of ubiquitous computing services and applications, and enriches the way they interact with the users and resources in the environment. Many location-aware systems adapt the way they behave according to the context of the current location without explicit user intervention. The aim is to increase usage and effectiveness by taking environmental context of a specified location into account. and by outlining the factors and infrastructure that must be considered during the olive fruit fly spraying process. Based on this framework we can develop specific Location-aware services such as finding if the current area is to be sprayed, estimating the amount of the spraying solution that must be sprayed, abort for a reason the spraying process etc. These services aim in a more efficient and environmental friendly control of the olive fruit fly.