Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic pitch accent prediction for text-to-speech synthesis

Determining pitch accents in a sentence is a key task for a text-to-speech (TTS) system. We describe some methods for pitch accent assignment which make use of features that contain information about a complete phrase or sentence, in contrast to most previous work which has focused on using features local to a syllable or word. Pitch accent prediction is performed using three different techniques: N-gram models of syllable sequences, dynamic programming to match sequences of features, and decision trees. Using a C4.5 decision tree trained on a wide range of features, most notably each word's orthographic form and information extracted from the syntactic parse of the sentence, our feature set achieved a balanced error rate of 46.6%. This compares with the feature set used in [11] which had a balanced error rate of 55.55%.
Recognition of unconstrained handwritten numerals using biorthogonal spline wavelets

The work proposes a novel approach for recognition of unconstrained handwritten numerals using the biorthogonal spline wavelets Cohen-Daubechies-Feauveau (CDF) 3/7 as a feature extractor and a multilayer cluster neural network as a classifier. Experiments with the CENPARMI database show that this method yields good results.
Psychoacoustic Models and Non-Linear Human Hearing

Non-linearity in the human ear can cause audible distortion not present in the original signal. Such distortion is generated within the ear by inter-modulation of a spectral complex, itself containing possible masked components. When psychoacoustic codecs remove these supposedly masked components, the in-ear-generated distortion is also removed, and so our listening experience is modified. In this paper, the in-ear distortion is quantified and a method suggested for predicting the in-ear distortion arising from an audio signal. The potential performance gains due to incorporating this knowledge into an audio codec are assessed.
Belt-type Wireless and Non-contact Electrocardiogram Monitoring System Using Flexible Active Electrode

Electrocardiogram (ECG) measurement using capacitively coupled electrode is a well-know method to get the ECG signal without direct skin-contact. In this paper, the belt-type system which measures ECG without direct skin-contact is designed and tested. The system consists of developed flexible active electrode (FAE), a driven-right-leg electrode and a module for signal processing and data acquisition. The FAE has the merit of enlarging contact area. It helps to increase signal-to-noise ratio (SNR) compared to rigid and flat electrode. The measured ECG data are transmitted to a laptop computer using a Bluetooth device. The feasibility of applying the developed system to ambulatory ECG monitoring was validated by measuring ECG data during a treadmill exercise at the speed of 5km/h and 7km/h. As a result, ECG obatained from the developed wearable belt-type system was stable if a person was in a state without excessive motion. Our system is wireless and capable of non-contact ECG measurement so that it is adequate for long-term ECG monitoring.
Automatic Collocation Suggestion in Academic Writing

In recent years, collocation has been widely acknowledged as an essential characteristic to distinguish native speakers from non-native speakers. Research on academic writing has also shown that collocations are not only common but serve a particularly important discourse function within the academic community. In our study, we propose a machine learning approach to implementing an online collocation writing assistant. We use a data-driven classifier to provide collocation suggestions to improve word choices, based on the result of classification. The system generates and ranks suggestions to assist learners' collocation usages in their academic writing with satisfactory results.
An algorithmic mitigation of large spurious interprocedural cycles in static analysis

We present a simple algorithmic extension of the approximate call‐strings approach to mitigate substantial performance degradation caused by spurious interprocedural cycles. Spurious interprocedural cycles are, in a realistic setting, the key reasons for why approximate call‐return semantics in both context‐sensitive and ‐insensitive static analysis can make the analysis much slower than expected. In the approximate call‐strings‐based context‐sensitive static analysis, because the number of distinguished contexts is finite, multiple call‐contexts are inevitably joined at the entry of a procedure and the output at the exit is propagated to multiple return‐sites. We found that these multiple returns frequently create a single large cycle (we call it ‘butterfly cycle’) covering almost all parts of the program and such a spurious cycle makes analyses very slow and inaccurate. Our simple algorithmic technique (within the fixpoint iteration algorithm) identifies and prunes these spurious interprocedural flows. The technique's effectiveness is proven by experiments with a realistic C analyzer to reduce the analysis time by 7–96%. As the technique is algorithmic, it can be easily applicable to existing analyses without changing the underlying abstract semantics, it is orthogonal to the underlying abstract semantics' context‐sensitivity, and its correctness is obvious. Copyright © 2010 John Wiley & Sons, Ltd.
A context-dependent cost effectiveness indicator for software development

Product quality, development productivity, and staffing needs are main cost drivers in software development. In particular the tension between productivity and quality makes it difficult to gauge the relative cost-effectiveness of a software development using separate quality and productivity measures. The paper proposes a one-stop cost-effectiveness indicator that resolves the tension between these two cost drivers, by combining productivity, quality, and staffing needs through an economic criterion. Contextspecific instances of the indicator can be used as key performance measures to rank comparable software projects or as dependent variables to evaluate development techniques whose effectiveness hinge on the tradeoff between their relative productivity and quality benefits. The use of the indicator is demonstrated by applying it to the findings of two empirical studies.
Caspase activation in retinas of diabetic and galactosemic mice and diabetic patients.

Apoptosis of retinal capillary cells begins early in diabetes and likely contributes to the capillary obliteration that is an important feature of diabetic retinopathy. Caspases are proteolytic enzymes that are closely involved in the induction and execution phases of apoptosis, but their role in the development of diabetic retinopathy has not been studied previously. Our study focused on the measurement of activities of multiple caspases in retinas of mice at different durations of diabetes. Several caspases (including caspases-1, -2, -6, -8, and -9) were activated as early as 2 months of diabetes. The caspases activity pattern changed with increasing duration of disease, suggesting a slowly developing caspases cascade. Activities of executioner caspases (e.g., cas-6 and -3) became elevated after longer duration of diabetes, and the induction of cas-3 activity was associated with the duration of diabetes at which capillary cells begin to show evidence of undergoing apoptosis. Retinas from patients with type 2 diabetes likewise showed a significant increase in activities of cas-1, -3, -4, and -6. For comparison, retinal caspases were also measured in experimental galactosemia, another model that develops a diabetic-like retinopathy. The pattern of caspases activation differed between diabetes and galactosemia, but cas-1 activity became elevated soon after elevation of blood hexose concentration in both. Caspases offer new therapeutic targets to test the role of apoptosis in the development of diabetic retinopathy.
Decision Trees and Genetic Programming in Synthesis of FourBar Mechanisms

Kinematic synthesis of four bar mechanisms is a design probl em that is difficult to solve by generative methods. The present approach is a variant based method that combines the genetic programming and decision tree learning methods. The aim of the research is to give a structural description fo r the class of mechanisms that produce desired coupler curve s. For finding and characterizing feasible regions of the desig n pace constructive induction is used. The new features are created by genetic programming.
On The Value of Leave-One-Out Cross-Validation Bounds

A long-standing problem in classification is the determination of the regularization parameter. Nearly every classification algorithm uses a parameter (or set of parameters) to control classifier complexity. Crossvalidation on the training set is usually done to determine the regularization parameter(s). [1] proved a leave-one-out cross-validation (LOOCV) bound for a class of kernel classifiers. [2] extended the bound to Regularized Least Squares Classification (RLSC). We provide the (trivial) extension to multiclass. Our contribution is empirical work. We evaluate the bound’s usefulness as a selector for the regularization parameter for RLSC. We find that it works extremely poorly on the data set we experimented with (20 Newsgroups); the LOOCV bound consistently selects a regularization parameter that is too large.
Time Driven Activity-Based Costing : Konsep Akuntansi Manajemen yang Akurat dalam Menghadapi Lingkungan yang Dinamis dan Bisnis Global

This paper describes how the concept of Management Accounting, particularly the time-driven activity-based costing (TD-ABC) can be applied in calculating the cost ) is realistic. Cost becomes a very important element in calculating the earnings and net earnings were reported. The errors in the calculation of cost (cost) would result in a pricing mistake. TD-ABC is a new concept of management accounting. The emergence of TD-ABC is expected to eliminate the vulnerabilities that exist on the concept of the previous concepts such as ABC. TD-ABC concept is usually applied to companies with sophisticated accounting information systems were applicable to the Company as at the Farm Bryon ranch. , Corp and Small and Medium Enterprises. Therefore it can be said TD-ABC can be applied in a dynamic environment and globalisasi and shifting corporate objective function in order to satisfy customer demand management accounting to do more
Preparation and Characterization of Nanoliposomes Entrapping Medium-Chain Fatty Acids and Vitamin C by Lyophilization

The complex nanoliposomes encapsulating both a hydrophilic drug vitamin C (vit C) and hydrophobic drug medium-chain fatty acids (MCFAs) was prepared by combining double emulsion method with dynamic high pressure microfluidization. The complex nanoliposomes was further freeze-dried under −86 °C for 48 h with sucrose at the sucrose/lipids ratio of 2:1(w/w) in order to enhance its stability. The freeze-dried complex nanoliposomes under the suitable conditions exhibited high entrapment efficiency of MCFAs (44.26 ± 3.34)%, relatively high entrapment efficiency of vit C (62.25 ± 3.43)%, low average size diameter (110.4 ± 7.28) nm and good storage stability at 4 °C for 60 days with slight changes in mean particle diameter and drug entrapment efficiencies. The results of transmission electron microscopy of freeze-dried complex nanoliposomes also showed that the freeze-dried samples with sucrose were stable without great increase in their particle sizes and without destroying their spherical shape. The results indicated that sucrose presented well protection effects in MCFAs-vit C complex nanoliposomes, suggesting the possibility of further usage in commercial liposomes.
Effective image noise removal based on difference eigenvalue

Preservation of fine feature of an image is essential during the process of noise removal, especially via some types of smoothing such as using diffusion process-based methods to enhance images. In this paper, we present a new edge indicator called difference eigenvalue to measure image gradient magnitude in the diffusion process. Based on the eigenvalues of the Hessian matrix, the difference eigenvalue manifest itself in terms of structural information of an image. We adapt the new edge indicator to a diffusion model to achieve a better balance between noise removal and detail preservation. Experiments on both synthetic and real images show that the new model can obtain good results and outperforms existing methods.
SAR image despeckling based on G0 distribution and nonlocal TV regularization

In this paper, we propose a new model for synthetic aperture radar (SAR) image despeckling based on the G0 statistical distribution and nonlocal total variation regularization. By taking the distribution of the backscatter into account, a new data fidelity term is derived by the maximum a posteriori Bayesian rule. Combining the new fidelity term with the nonlocal total variation regularization gives a new variational model for SAR image despeckling. The primal-dual algorithm framework is then used to solve the new variational problem. Experimental results on real SAR images demonstrate the validity of the proposed method.
Ionic selectivity of native ATP‐activated (P2X) receptor channels in dissociated neurones from rat parasympathetic ganglia

1 The relative permeability of the native P2X receptor channel to monovalent and divalent inorganic and organic cations was determined from reversal potential measurements of ATP‐evoked currents in parasympathetic neurones dissociated from rat submandibular ganglia using the dialysed whole‐cell patch clamp technique. 2 The P2X receptor‐channel exhibited weak selectivity among the alkali metals with a selectivity sequence of Na+ > Li+ > Cs+ > Rb+ > K+, and permeability ratios relative to Cs+ (PX/PCs) ranging from 1.11 to 0.86. 3 The selectivity for the divalent alkaline earth cations was also weak with the sequence Ca2+ > Sr2+ > Ba2+ > Mn2+ > Mg2+. ATP‐evoked currents were strongly inhibited when the extracellular divalent cation concentration was increased. 4 The calculated permeability ratios of different ammonium cations are higher than those of the alkali metal cations. The permeability sequence obtained for the saturated organic cations is inversely correlated with the size of the cation. The unsaturated organic cations have a higher permeability than that predicted by molecular size. 5 Acidification to pH 6.2 increased the ATP‐induced current amplitude twofold, whereas alkalization to 8.2 and 9.2 markedly reduced current amplitude. Cell dialysis with either anti‐P2X2 and/or anti‐P2X4 but not anti‐P2X1 antibodies attenuated the ATP‐evoked current amplitude. Taken together, these data are consistent with homomeric and/or heteromeric P2X2 and P2X4 receptor subtypes expressed in rat submandibular neurones. 6 The permeability ratios for the series of monovalent organic cations, with the exception of unsaturated cations, were approximately related to the ionic size. The relative permeabilities of the monovalent inoganic and organic cations tested are similar to those reported previously for cloned rat P2X2 receptors expressed in mammalian cells.
Adapting the Sample Size in Texture Synthesis

Starting from a sample of a given size, texture synthesis algorithms are used to create larger texture images. A good algorithm produces synthesized textures that are pixelwise different but perceptually indistinguishable from the original image. The sample image should be chosen ensuring that it contains a number of pattern repetitions sufficient to produce valuable synthesis results. Since textures can be characterized by patterns of different dimensions, this must be done in an adaptive way. In this article, we propose a method that automatically adapts the sample size for natural textures synthesis, according to the different patterns dimensions. The method is based on the measure of the spatial dependence between the texture pixel values. This measure is used to estimate the size of the smallest texture window that is still perceived as texture by human observers. The sample size is determined from this measure by applying a multiplicative factor that depends on the algorithm used for synthesis. We perform a simple subjective experiment to estimate this factor for three different synthesis algorithms. We show that the measure of spatial dependence based on the correlation between pixels performs well when it is used to adapt the sample size.
Contextual Semantic Parsing using Crowdsourced Spatial Descriptions

We describe a contextual parser for the Robot Commands Treebank, a new crowdsourced resource. In contrast to previous semantic parsers that select the most-probable parse, we consider the different problem of parsing using additional situational context to disambiguate between different readings of a sentence. We show that multiple semantic analyses can be searched using dynamic programming via interaction with a spatial planner, to guide the parsing process. We are able to parse sentences in near linear-time by ruling out analyses early on that are incompatible with spatial context. We report a 34% upper bound on accuracy, as our planner correctly processes spatial context for 3,394 out of 10,000 sentences. However, our parser achieves a 96.53% exact-match score for parsing within the subset of sentences recognized by the planner, compared to 82.14% for a non-contextual parser.
Real-time detection of moving objects by a mobile robot with an omnidirectional camera

Mobile robots equipped with an omnidirectional camera have gained a considerable attention over the last decade. Having an entire view of the scene can be very advantageous in numerous applications as all information is stored in a single frame. This paper is primarily concerned with detection of moving objects from optical flow field in cluttered indoor environments, which is necessary for safe navigation and collision avoidance. The algorithm is based on the comparison of the measured optical flow vectors with the generated ones. As depth information is not available, a novel method is proposed which iteratively generates optical flow vectors for different possible real world coordinates of the objects in the scene. This is necessary in order to incorporate motion estimates given by motor encoders. Back-projecting into image is then used to generate synthetic optical flow vectors needed for comparison. The algorithm was tested on a real system and was able to successfully localize a moving object under both artificial and natural lighting. The proposed algorithm can be implemented in real-time on any system with known calibrated model of the omnidirectional sensor and reliable motion estimation.
SoyNet: a database of co-functional networks for soybean Glycine max

Soybean (Glycine max) is a legume crop with substantial economic value, providing a source of oil and protein for humans and livestock. More than 50% of edible oils consumed globally are derived from this crop. Soybean plants are also important for soil fertility, as they fix atmospheric nitrogen by symbiosis with microorganisms. The latest soybean genome annotation (version 2.0) lists 56 044 coding genes, yet their functional contributions to crop traits remain mostly unknown. Co-functional networks have proven useful for identifying genes that are involved in a particular pathway or phenotype with various network algorithms. Here, we present SoyNet (available at www.inetbio.org/soynet), a database of co-functional networks for G. max and a companion web server for network-based functional predictions. SoyNet maps 1 940 284 co-functional links between 40 812 soybean genes (72.8% of the coding genome), which were inferred from 21 distinct types of genomics data including 734 microarrays and 290 RNA-seq samples from soybean. SoyNet provides a new route to functional investigation of the soybean genome, elucidating genes and pathways of agricultural importance.
An adaptive PAM-4 5 Gb/s backplane transceiver in 0.25 /spl mu/m CMOS

This paper describes a novel backplane transceiver, which uses PAM-4 (pulse amplitude modulated four level) signalling and continuously adaptive transmit based equalization to move 5 Gcb/s (channel bits per second) across typical FR-4 backplanes for total distances of up to 50 inches through two sets of backplane connectors. The paper focuses on the implementation of the equalizer and the adaptation algorithms, and includes measured results. The 17 mm/sup 2/ device is implemented in a 0.25 /spl mu/m CMOS process, operates on 2.5 V and 3.3 V supplies and consumes 1.2 W.
Joint Program on the Science and Policy of Global Change Feedbacks Affecting the Response of the Thermohaline Circulation to Increasing CO 2 . A Study with a Model of Intermediate Complexity

A three-dimensional ocean model with an idealized geometry and coarse resolution coupled to a twodimensional (zonally-averaged) statistical-dynamical atmospheric model is used to simulate the response of the thermohaline circulation to increasing CO2 concentration in the atmosphere. The relative role of different factors in slowing down the thermohaline circulation was studied by performing simulations with ocean only and partially coupled models. The computational efficiency of the model allows an extensive and thorough study of the causes of changes in the strength of the thermohaline circulation, through a large number of extended runs. The increase in the atmosphere-to-ocean surface heat fluxes is shown to be the dominant factor in both causing the weakening of the circulation in response to an increasing external forcing as well as in controlling the subsequent recovery. Changes in the zonal distribution of heat fluxes serve as a positive feedback for both decrease and recovery of the meridional overturning, and turn out to be as important as changes in the zonal-mean values of heat fluxes. We also demonstrate that the recovery of the circulation in the ocean model cannot be sustained without feedbacks from the atmosphere. The dependency of global and regional responses on parameterization of eddy mixing, namely the Gent-McWilliams parameterization scheme versus horizontal diffusion, is also discussed.
Delayed Upregulation of ATP P2X3 Receptors of Trigeminal Sensory Neurons by Calcitonin Gene-Related Peptide

Recent evidence indicates a key role for the neuropeptide calcitonin gene-related peptide (CGRP) in migraine pain, as demonstrated by the strong analgesic action of CGRP receptor antagonists, although the mechanisms of this effect remain unclear. Most trigeminal nociceptive neurons releasing CGRP also express ATP-activated purinergic P2X3 receptors to transduce pain. To understand whether the CGRP action involves P2X3 receptor modulation, the model of trigeminal nociceptive neurons in culture was used to examine the long-term action of this peptide. Although 79% of CGRP-binding neurons expressed P2X3 receptors, acute application of CGRP did not change P2X3 receptor function. Nevertheless, after 1 h of CGRP treatment, strong enhancement of the amplitude of P2X3 receptor currents was observed together with accelerated recovery from desensitization. Receptor upregulation persisted up to 10 h (despite CGRP washout), was accompanied by increased P2X3 gene transcription, and was fully prevented by the CGRP antagonist CGRP8–37. Surface biotinylation showed CGRP augmented P2X3 receptor expression, consistent with confocal microscopy data indicating enhanced P2X3 immunoreactivity beneath the neuronal membrane. These results suggest that CGRP stimulated trafficking of P2X3 receptors to the cell-surface membrane. Using pharmacological tools, we demonstrated that this effect of CGRP was dependent on protein kinase A and PKC activation and was prevented by the trafficking inhibitor brefeldin A. Capsaicin-sensitive TRPV1 vanilloid receptors were not upregulated. The present data demonstrate a new form of selective, slow upregulation of nociceptive P2X3 receptors on trigeminal neurons by CGRP. This mechanism might contribute to pain sensitization and represents a model of neuronal plasticity in response to a migraine mediator.