Miracle-dz/UniFAR-FTUs huggingface dataset:
Template-based Chord Recognition : Influence of the Chord Types

This paper describes a fast and efficient template-based chord recognition method. We introduce three chord models taking into account one or more harmonics for the notes of the chord. The use of pre-determined chord models enables to consider several types of chords (major, minor, dominant seventh, minor seventh, augmented, diminished.). After extracting a chromagram from the signal, the detected chord over a frame is the one minimizing a measure offit between the chromagram frame and the chord templates. Several popular measures in the probability and signal processing field are considered for our task. In order to take into account the time persistence, we perform a post-processing filtering over the recognition criteria. The transcription tool is evaluated on the 13 Beatles albums with different chord types and compared to state-of-theart chord recognition methods. We particularly focus on the influence of the chord types considered over the performances of the system. Experimental results show that our method outperforms the state-of-the-art and more importantly is less computationally demanding than the other evaluated systems.
Rc Interconnect Synthesis-a Moment Fitting Approach

Presently, delays due to the physical interconnect between logic gates account for large portions of the overall path delays. For this reason, synthesis of the logic gate fanout structure is of paramount importance during performance optimization. This paper presents a methodology for on-chip RC interconnect synthesis. Moment sensitivities are used to vary the wire widths of the branches in an RC interconnect tree to achieve performance targets. In this paper, signal slopes and delays at critical fanout nodes are the targets, and the impact on total metal area is considered. An O(MN2) procedure for computing the exact moment sensitivities in an RC tree is described.
Triangulating Point Clouds with Spherical Topology

Triangulating a set of scattered 3D points is a common approach to surface reconstruction from unorganized point clouds. Be- sides several Voronoi-based and incremental algorithms, a recently pre- sented technique parameterizes the sample points and uses a Delaunay triangulation of the parameter points in the parameter domain. This method is limited to reconstructing surfaces that are homeomorphic to a disc, and we show how it can be extended to handle spherical topology as well.
Quantitative Analysis of Differential Proteome Expression in Epithelial-to-Mesenchymal Transition of Bladder Epithelial Cells Using SILAC Method

Epithelial-to-mesenchymal transition (EMT) is an essential biological process involved in embryonic development, cancer progression, and metastatic diseases. EMT has often been used as a model for elucidating the mechanisms that underlie bladder cancer progression. However, no study to date has addressed the quantitative global variation of proteins in EMT using normal and non-malignant bladder cells. We treated normal bladder epithelial HCV29 cells and low grade nonmuscle invasive bladder cancer KK47 cells with transforming growth factor-beta (TGF-β) to establish an EMT model, and studied non-treated and treated HCV29 and KK47 cells by the stable isotope labeling amino acids in cell culture (SILAC) method. Labeled proteins were analyzed by 2D ultrahigh-resolution liquid chromatography/LTQ Orbitrap mass spectrometry. Among a total of 2994 unique identified and annotated proteins in HCV29 and KK47 cells undergoing EMT, 48 and 56 proteins, respectively, were significantly upregulated, and 106 and 24 proteins were significantly downregulated. Gene ontology (GO) term analysis and pathways analysis indicated that the differentially regulated proteins were involved mainly in enhancement of DNA maintenance and inhibition of cell-cell adhesion. Proteomes were compared for bladder cell EMT vs. bladder cancer cells, revealing 16 proteins that displayed similar changes in the two situations. Studies are in progress to further characterize these 16 proteins and their biological functions in EMT.
Performance analysis of stochastic network coverage with limited mobility

We analyze the ability of a stochastic coverage algorithm to achieve both accurate threat-based coverage and effective information capture. When mobile sensors are used to cover the region over time, the goal of threat-based coverage is to allocate the sensors' coverage time between the subregions in proportion to their threat levels. We show that, in contrast to prior results on mobile coverage for maximizing simple event capture, limiting mobility by strategically pausing the sensor is important for threat-based coverage of physical world monitoring. Besides being energy efficient, pausing has two desirable effects. First, it can improve the accuracy of the threat-based coverage, in particular, the accuracy increases monotonically with a pause time parameter, and a large enough parameter will ensure exact matching of the sensor's coverage profile with the region's threat profile. Second, diverse natural phenomena require a non-negligible sensing time to overcome statistical uncertainties posed by the random nature of the phenomena. Suitable pausing allows a subregion to be observed long enough for reliable results.
Checking system rules using system-specific, programmer-written compiler extensions

Systems software such as OS kernels, embedded systems, and libraries must obey many rules for both correctness and performance. Common examples include "accesses to variable A must be guarded by lock B," "system calls must check user pointers for validity before using them," and "message handlers should free their buffers as quickly as possible to allow greater parallelism. " Unfortunately, adherence to these rules is largely unchecked. This paper attacks this problem by showing how system implementors can use meta-level compilation (MC) to write simple, system-specific compiler extensions that automatically check their code for rule violations. By melding domain-specific knowledge with the automatic machinery of compilers, MC brings the benefits of language-level checking and optimizing to the higher, "meta" level of the systems implemented in these languages. This paper demonstrates the effectiveness of the MC approach by applying it to four complex, real systems: Linux, OpenBSD, the Xok exokernel, and the FLASH machine's embedded software. MC extensions found roughly 500 errors in these systems and led to numerous kernel patches. Most extensions were less than a hundred lines of code and written by implementors who had a limited understanding of the systems checked.
Microwave Synthesis, Basic Spectral and Biological Evaluation of Some Copper (II) Mesoporphyrinic Complexes

Cu(II) complexes with asymmetrical and symmetrical porphyrinic ligands were synthesized with superior yields using microwave irradiation. The paper presents the synthesis of 5-(3-hydroxyphenyl)-10,15,20-tris-(4-carboxymethylphenyl)-21,23-Cu(II)-porphine in comparison to its symmetrical complex 5,10,15,20-meso-tetrakis-(4-carboxy-methylphenyl)-21,23-Cu(II) porphine. The two compounds were characterized by FT-IR, UV–Vis and EPR spectroscopy, which fully confirmed the structures. The spectral molecular absorption properties of the porphyrinic complexes were studied in organic solvents (methanol, ethanol, iso-propanol, dimethyl sulfoxide, dimethylformamide and methylene chloride), and the influence of the solvent polarity on the absorbance maxima is described. In order to establish their future potential in biomedical applications preliminary toxicological studies consisting of viability and proliferation of standard tumor cell lines (MCF7 and B16) testing was performed. The obtained results indicate a low toxicity for both compounds and further recommends them for testing in light activation protocols.
RGB-D Multi-view System Calibration for Full 3D Scene Reconstruction

One of the most crucial requirements for building a multi-view system is the estimation of relative poses of all cameras. An approach tailored for a RGB-D cameras based multi-view system is missing. We propose BAICP+ which combines Bundle Adjustment (BA) and Iterative Closest Point (ICP) algorithms to take into account both 2D visual and 3D shape information in one minimization formulation to estimate relative pose parameters of each camera. BAICP+ is generic enough to take different types of visual features into account and can be easily adapted to varying quality of 2D and 3D data. We perform experiments on real and simulated data. Results show that with the right weighting factor BAICP+ has an optimal performance when compared to BA and ICP used independently or sequentially.
Inferring 3D structure with a statistical image-based shape model

We present an image-based approach to infer 3D structure parameters using a probabilistic "shape+structure" model. The 3D shape of an object class is represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras, while structural features of interest on the object are denoted by a number of 3D locations. A prior density over the multiview shape and corresponding structure is constructed with a mixture of probabilistic principal components analyzers. Given a novel set of contours, we infer the unknown structure parameters from the new shape's Bayesian reconstruction. Model matching and parameter inference are done entirely in the image domain and require no explicit 3D construction. Our shape model enables accurate estimation of structure despite segmentation errors or missing views in the input silhouettes, and it works even with only a single input view. Using a training set of thousands of pedestrian images generated from a synthetic model, we can accurately infer the 3D locations of 19 joints on the body based on observed silhouette contours from real images.
Can prosody inform sentiment analysis? Experiments on short spoken reviews

While most online content is created using textual interfaces, recent improvements in speech recognition accuracy allows the creation of content through speech. This technology allows users to share reviews about entities of interest without any delay, using mobile devices. This paper builds on the previous work on textual sentiment analysis to investigate whether information in the speech signal can be used to predict sentiment from short spoken reviews. For this purpose we collected a short spoken reviews from 84 speakers. Results show that models trained on features characterizing the review's pitch significantly outperform a majority class baseline, without textual information. When taking text-based sentiment predictions into account, our results suggest that prosody can alleviate the effect of speech recognition errors on sentiment detection, however a larger dataset is needed to test whether this can be done without harming performance on low word error rates.
Pass-O: A Proposal to Improve the Security of Pattern Unlock Scheme

The graphical pattern unlock scheme which requires users to connect a minimum of 4 nodes on 3X3 grid is one of the most popular authentication mechanism on mobile devices. However prior research suggests that users' pattern choices are highly biased and hence vulnerable to guessing attacks. Moreover, 3X3 pattern choices are devoid of features such as longer stroke lengths, direction changes and intersections that are considered to be important in preventing shoulder-surfing attacks. We attribute these insecure practices to the geometry of the grid and its complicated drawing rules which prevent users from realising the full potential of graphical passwords. In this paper, we propose and explore an alternate circular layout referred to as Pass-O which unlike grid layout allows connection between any two nodes, thus simplifying the pattern drawing rules. Consequently, Pass-O produces a theoretical search space of 9,85,824, almost 2.5 times greater than 3X3 grid layout. We compare the security of 3X3 and Pass-O patterns theoretically as well as empirically. Theoretically, Pass-O patterns are uniform and have greater visual complexity due to large number of intersections. To perform empirical analysis, we conduct a large-scale web-based user study and collect more than 1,23,000 patterns from 21,053 users. After examining user-chosen 3X3 and Pass-O patterns across different metrics such as pattern length, stroke length, start point, end point, repetitions, number of direction changes and intersections, we find that Pass-O patterns are much more secure than 3X3 patterns.
Density Profiles of Cold Dark Matter Substructure: Implications for the Missing-Satellites Problem

The structural evolution of substructure in cold dark matter (CDM) models is investigated combining "low-resolution" satellites from cosmological N-body simulations of parent halos with N = 107 particles with high-resolution individual subhalos orbiting within a static host potential. We show that, as a result of mass loss, convergence in the central density profiles requires the initial satellites to be resolved with N = 107 particles and parsec-scale force resolution. We find that the density profiles of substructure halos can be well fitted with a power-law central slope that is unmodified by tidal forces even after the tidal stripping of over 99% of the initial mass and an exponential cutoff in the outer parts. The solution to the missing-satellites problem advocated by Stoehr et al. in 2002 relied on the flattening of the dark matter halo central density cusps by gravitational tides, enabling the observed satellites to be embedded within dark halos with maximum circular velocities as large as 60 km s-1. In contrast, our results suggest that tidal interactions do not provide the mechanism for associating the dwarf spheroidal (dSph) satellites of the Milky Way with the most massive substructure halos expected in a CDM universe. Motivated by the structure of our stripped satellites, we compare the predicted velocity dispersion profiles of Fornax and Draco to observations, assuming that they are embedded in CDM halos. We demonstrate that models with isotropic and tangentially anisotropic velocity distributions for the stellar component fit the data only if the surrounding dark matter halos have maximum circular velocities in the range 20-35 km s-1. If the dSphs are embedded within halos this large, then the overabundance of satellites within the concordance ΛCDM cosmological model is significantly alleviated, but this still does not provide the entire solution.
More Impacts of Economic Reform in Poland: Welfare Changes within a Consistent Framework

The costs of shortages and rationing are not captured by standard consumer price indices. In this study, the authors use the virtual prices for the rationed goods to calculate a new cost-of-living index (CLI). The results for Poland show that from 1987 to 1992 the CLI that ignores the rationing effects is biased upward from 3.6 to 6.99 percentage points per year. Compared to the welfare loss calculated by neglecting the rationing effects in the prereform period, the welfare loss that reflects the rationing is only 25 percent as large using external virtual prices, and only 15 percent as large using Hausman virtual prices.
Moving towards an integrated approach to molecular detection and identification of Toxoplasma gondii

SUMMARY The development of simple, sensitive and rapid methods for the detection and identification of Toxoplasma gondii is important for the diagnosis and epidemiological studies of the zoonotic disease toxoplasmosis. In the past 2 decades, molecular methods based on a variety of genetic markers have been developed, each with its advantages and limitations. The application of these methods has generated invaluable information to enhance our understanding of the epidemiology, population genetics and phylogeny of T. gondii. However, since most studies focused solely on the detection but not genetic characterization of T. gondii, the information obtained was limited. In this review, we discuss some widely used molecular methods and propose an integrated approach for the detection and identification of T. gondii, in order to generate maximum information for epidemiological, population and phylogenetic studies of this key pathogen.
MULTI-OBJECTIVE OPTIMIZATION BY SIMULATED ANNEALING APPLIED TO IMAGE RECONSTRUCTION BY ELECTRICAL IMPEDANCE TOMOGRAPHY

The image reconstruction from the Electrical Impedance Tomography (EIT) can be approached as an optimization problem, in which is desired to minimize the Euclidean distance between the potential values measured in the cross section of the body and the calculated values, for every pattern of current applied, through the modelling of the problem by the Finite Elements Method (FEM). It’s known, a priori, that this formulation is ill-posed, which increases dependence of the EIT to the reconstruction algorithm, which must has any regularization technique to improve the conditioning of the problem. Therefore, this project proposes the use of an Multi-Objective Optimization algorithm in order to find the set of optimal solutions to the problem, aiming the minimization both the Euclidean distance and a regularization parameter.
Ascertaining the Reality of Network Neutrality Violation in Backbone ISPs

On the Internet today, a growing number of QoS sensitive network applications exist, such as VoIP, imposing more stringent requirements on ISPs besides the basic reachability assurance. Thus, the demand on ISPs for Service Level Agreements (SLAs) with better guarantees is increasing. However, despite overprovisioning in core ISP networks, resource contention still exists leading to congestion and associated performance degradations. For example, residential broadband networks rate-limit or even block bandwidth intensive applications such as peer-to-peer file sharing thereby violating network neutrality. In addition, traffic associated with specific applications, such as Skype, could also be discriminated against for competitive business reasons. So far, little work has been done regarding the existence of traffic discrimination inside the core of the Internet. Due to the technical challenges and widespread impact, it seems somewhat inconceivable that ISPs are performing such finegrained discrimination based on the application content. Our study is the first to demonstrate evidence of network neutrality violations within backbone ISPs. We used a scalable and accurate monitoring system – NVLens – to detect traffic discrimination based on various factors such as application types, previous-hop, and next-hop ASes. We discuss the implication of such discrimination and how users can counter such unfair practices.
Ontology Contraction: Beyond the Propositional Paradise

The dynamic nature of ontology development has motivated the formal study of ontology evolution problem. This paper addresses contraction —the problem of retracting information that should no longer hold in an ontology. We survey existing model and formula based semantics to contraction and investigate their properties for the description logics DL-Lite and EL, which underpin the QL and EL profiles of OWL 2. Our results suggest that these contraction semantics, which are well-understood and well-behaved for propositional logics, are intrinsically problematical in the context of ontology languages. We believe that a starting point for addressing these problems might be the recent semantics proposed in [1].
Energy efficiency and spectral-efficiency tradeoff in downlink NOMA systems

Non-orthogonal multiple access (NOMA) has been investigated recently as a candidate radio access technology for the fifth generation (5G) mobile communication due to its high spectral efficiency (SE). Green radio (GR) which focuses on energy efficiency (EE) is becoming an inevitable trend. In this paper, we study the tradeoff between EE and SE in downlink NOMA systems. The tradeoff problem is formulated as an optimization problem in which the basic idea is to maximize EE under a satisfying minimum SE requirement. It is proved that the system EE is a strictly quasi-concave function of transmission power. By formulating the optimization problem as a bilayer optimization problem, the optimal solution to the optimization problem is obtained, including optimal power allocation coefficients among multiplexed users and optimal transmission power value. Simulation results are provided to further confirm our theoretical findings and the effectiveness of our proposed power allocation scheme for achieving a flexible tradeoff between EE and SE.
Scalable Estimation of Dirichlet Process Mixture Models on Distributed Data

We consider the estimation of Dirichlet Process Mixture Models (DPMMs) in distributed environments, where data are distributed across multiple computing nodes. A key advantage of Bayesian nonparametric models such as DPMMs is that they allow new components to be introduced on the fly as needed. This, however, posts an important challenge to distributed estimation -- how to handle new components efficiently and consistently. To tackle this problem, we propose a new estimation method, which allows new components to be created locally in individual computing nodes. Components corresponding to the same cluster will be identified and merged via a probabilistic consolidation scheme. In this way, we can maintain the consistency of estimation with very low communication cost. Experiments on large real-world data sets show that the proposed method can achieve high scalability in distributed and asynchronous environments without compromising the mixing performance.
Reducing the Dependence of Trust-Management Systems on PKI

Trust-management systems address the authorization probl em in distributed systems by defining a formal language for expressing authorization and access-c ontrol policies, and relying on an algorithm to determine when a specific request can be granted. For autho rizati n in distributed systems, trustmanagement systems offer several advantages over other app roaches, such as support for delegation and making authorization decisions in a decentralized mann er. This paper focuses on a popular trustmanagement system SPKI/SDSI. Although SPKI/SDSI is an attr active system for authorization in distributed systems, it has seen limited deployment. One of the major hurdles in deploying SPKI/SDSI is that it is PKI-based, i.e., every principal is required to ha ve public-private key pair. We present an approach that combines SPKI/SDSI with a widely-deployed au thentication system, Kerberos, to reduce reliance of SPKI/SDSI on PKI. In our approach, only sites nee d public-private key pairs. We believe that reducing the reliance of SPKI/SDSI on PKI will facilita te its wider deployment. We also have implemented a prototype of our technique.