Miracle-dz/UniFAR-FTUs huggingface dataset:
THE COMMUNICATIVE VALUE OF FILLED PAUSES IN SPONTANEOUS SPEECH

THE COMMUNICATIVE VALUE OF FILLED PAUSES IN SPONTANEOUS SPEECH by RALPH LEON ROSE Filled pauses (FPs, e.g. er, erm) and other hesitation phenomena are ever-present elements of spontaneous speech and have been the subject of various psycholinguistic studies. However, recommendations have been sparse for language teaching; consequently little attention is given to FPs in English Language Teaching course materials. The present research addresses this gap. A systematic analysis of hesitation phenomena in a mini-corpus of spontaneous speech supports earlier research on FPs, but suggests a refinement: although researchers have generally combined open and closed FPs (er and erm, respectively), this study suggests they are independent. Recommendations are given on approaches to FPs in the language classroom. It is suggested that a focus on FPs may benefit listening comprehension by encouraging students to make use of speakers’ pause time to process input. FPs may further benefit speaking ability by helping students to hold their conversational turns and to improve their apparent fluency. Specific activities designed to improve both listening and speaking skills are given.
Effects of arterial geometry on aneurysm growth: three-dimensional computational fluid dynamics study.

OBJECT Few researchers have quantified the role of arterial geometry in the pathogenesis of saccular cerebral aneurysms. The authors investigated the effects of parent artery geometry on aneurysm hemodynamics and assessed the implications relative to aneurysm growth and treatment effectiveness. METHODS The hemodynamics of three-dimensional saccular aneurysms arising from the lateral wall of arteries with varying arterial curves (starting with a straight vessel model) and neck sizes were studied using a computational fluid dynamics analysis. The effects of these geometric parameters on hemodynamic parameters, including flow velocity, aneurysm wall shear stress (WSS), and area of elevated WSS during the cardiac cycle (time-dependent impact zone), were quantified. Unlike simulations involving aneurysms located on straight arteries, blood flow inertia (centrifugal effects) rather than viscous diffusion was the predominant force driving blood into aneurysm sacs on curved arteries. As the degree of arterial curvature increased, flow impingement on the distal side of the neck intensified, leading to elevations in the WSS and enlargement of the impact zone at the distal side of the aneurysm neck. CONCLUSIONS Based on these simulations the authors postulate that lateral saccular aneurysms located on more curved arteries are subjected to higher hemodynamic stresses. Saccular aneurysms with wider necks have larger impact zones. The large impact zone at the distal side of the aneurysm neck correlates well with other findings, implicating this zone as the most likely site of aneurysm growth or regrowth of treated lesions. To protect against high hemodynamic stresses, protection of the distal side of the aneurysm neck from flow impingement is critical.
Compact size dual-polarized WLL base-station antenna using aperture coupled microstrip patches

The commercialization of the WLL (wireless local loop) system has been accelerated in many countries with the expansion of wireless technology. In most cases, a dipole array antenna or corporate feed microstrip array antenna is used for WLL base-stations. They are quite large, bulky, and heavy. In this paper, a compact size dual-polarized WLL base-station array antenna using aperture coupled microstrip patches connected with a series traveling-wave feed line is proposed. It meets the requirements of the WLL base-station antenna, its size is about 150/spl times/700/spl times/80 mm (compact design), and its measured isolation between the two ports is approximately 40 dB for the WLL frequency range of 2.3 GHz-2.4 GHz. In addition, the SLL (side lobe level) of the designed 1 W Chebyshev array antenna is about 20 dB (greater than the typical requirement of 15 dB).
An Investigation of Depressed Speech Detection: Features and Normalization

In recent years, the problem of automatic detection of mental illness from the speech signal has gained some initial interest, however questions remaining include how speech segments should be selected, what features provide good discrimination, and what benefits feature normalization might bring given the speaker-specific nature of mental disorders. In this paper, these questions are addressed empirically using classifier configurations employed in emotion recognition from speech, evaluated on a 47-speaker depressed/neutral read sentence speech database. Results demonstrate that (1) detailed spectral features are well suited to the task, (2) speaker normalization provides benefits mainly for less detailed features, and (3) dynamic information appears to provide little benefit. Classification accuracy using a combination of MFCC and formant based features approached 80% for this database.
An energy-efficient algorithm for connected target coverage problem in wireless sensor networks

A major concern in wireless sensor networks is to maximize network lifetime while maintaining a high quality of services (QOS) such as target coverage and network connectivity. Communication and sensing consume energy, therefore efficient power management can extend network lifetime. in this paper we consider a large number of static sensor nodes are deployed in order to monitor a number of target points in the region. each target point may be redundantly covered by multiple sensors. one approach to conserve energy is to organize the deployed sensors into subsets of sensors, or sensor covers such that each subset can cover all targets in the region and each sensor to be activated is connected to the Base Station (BS). This subsets activated successively and only the sensors from active subset are responsible for monitoring all targets. The more sensor covers can be found, the longer network lifetime can be prolonged. finding maximum number of sensor covers can be solved via transformation to the connected set covers (CSC) problem, wich has been proved to be NP-complete. for this optimization problem, existing algorithms either get unsatisfactory solutions and in most cases take exponential time complexity. In this paper we propose a heuristic solution to solve the CSC problem. the simulation results show that the proposed algorithm can get acceptable solutions with polynomial computation time and can improve the performance of the Greedy-CSC heuristic algorithm in solution quality and it has better performance than IP-CSC heuristic in large scenarios.
POS Tagger and Chunker for Tamil Language

This paper presents the Part Of Speech tagger and Chunker for Tamil using Machine learning techniques. Part Of Speech tagging and chunking are the fundamental processing steps for any language processing task. Part of speech (POS) tagging is the process of labeling automatic annotation of syntactic categories for each word in a corpus. Chunking is the task of identifying and segmenting the text into syntactically correlated word groups. These are done by the machine learning techniques, where the linguistical knowledge is automatically extracted from the annotated corpus. We have developed our own tagset for annotating the corpus, which is used for training and testing the POS tagger generator and the chunker. The present tagset consists of thirty-two tags for POS and nine tags for chunking. A corpus size of two hundred and twenty five thousand words was used for training and testing the accuracy of the POS tagger and Chunker. We found that SVM based machine learning tool affords the most encouraging result for Tamil POS tagger (95.64%) and chunker (95.82%).
Gene interaction and modularisation in a model for gene-regulated development

Using a developmental genotype-phenotype map can possibly alleviate the scaling difficulties of EC, which are fundamental to applications such as EHW. We propose a simple model for gene-regulated development in combination with genetic algorithms, which is based on fundamental biological principles on the one hand, and allows investigation of concepts such as modularisation and evolvability. We propose activation propagation as a possible mechanism which genes interact in a gene-regulated development model. Based on this principle weights are assigned to genetic interactions between genes, the collection of which can be used to identify genetic modules. These modules are similar to the idea of genetic cascades in biology. Properties of these modules such as their sharing of genes, and the implications within development are discussed. We advocate the concept of propagation modules as a possible source of further investigation into the evolvability of gene-regulated development in the scope of genetic algorithms.
Validation of PC-based Sound Card with Biopac for Digitalization of ECG Recording in Short-term HRV Analysis

Background: Heart rate variability (HRV) analysis is a simple and noninvasive technique capable of assessing autonomic nervous system modulation on heart rate (HR) in healthy as well as disease conditions. The aim of the present study was to compare (validate) the HRV using a temporal series of electrocardiograms (ECG) obtained by simple analog amplifier with PC-based sound card (audacity) and Biopac MP36 module. Materials and Methods: Based on the inclusion criteria, 120 healthy participants, including 72 males and 48 females, participated in the present study. Following standard protocol, 5-min ECG was recorded after 10 min of supine rest by Portable simple analog amplifier PC-based sound card as well as by Biopac module with surface electrodes in Leads II position simultaneously. All the ECG data was visually screened and was found to be free of ectopic beats and noise. RR intervals from both ECG recordings were analyzed separately in Kubios software. Short-term HRV indexes in both time and frequency domain were used. Results: The unpaired Student′s t-test and Pearson correlation coefficient test were used for the analysis using the R statistical software. No statistically significant differences were observed when comparing the values analyzed by means of the two devices for HRV. Correlation analysis revealed perfect positive correlation (r = 0.99, P < 0.001) between the values in time and frequency domain obtained by the devices. Conclusion: On the basis of the results of the present study, we suggest that the calculation of HRV values in the time and frequency domains by RR series obtained from the PC-based sound card is probably as reliable as those obtained by the gold standard Biopac MP36.
Prediction of the bonding states of cysteines Using the support vector machines based on multiple feature vectors and cysteine state sequences

The support vector machine (SVM) method is used to predict the bonding states of cysteines. Besides using local descriptors such as the local sequences, we include global information, such as amino acid compositions and the patterns of the states of cysteines (bonded or nonbonded), or cysteine state sequences, of the proteins. We found that SVM based on local sequences or global amino acid compositions yielded similar prediction accuracies for the data set comprising 4136 cysteine‐containing segments extracted from 969 nonhomologous proteins. However, the SVM method based on multiple feature vectors (combining local sequences and global amino acid compositions) significantly improves the prediction accuracy, from 80% to 86%. If coupled with cysteine state sequences, SVM based on multiple feature vectors yields 90% in overall prediction accuracy and a 0.77 Matthews correlation coefficient, around 10% and 22% higher than the corresponding values obtained by SVM based on local sequence information. Proteins 2004;55:000–000. © 2004 Wiley‐Liss, Inc.
Study of active duty military for pulmonary disease related to environmental deployment exposures (STAMPEDE).

RATIONALE Because of increased levels of airborne particulate matter in Southwest Asia, deployed military personnel are at risk for developing acute and chronic lung diseases. Increased respiratory symptoms are reported, but limited data exist on reported lung diseases. OBJECTIVES To evaluate new respiratory complaints in military personnel returning from Southwest Asia to determine potential etiologies for symptoms. METHODS Returning military personnel underwent a prospective standardized evaluation for deployment-related respiratory symptoms within 6 months of returning to their duty station. MEASUREMENTS AND MAIN RESULTS Prospective standardized evaluation included full pulmonary function testing, high-resolution chest tomography, methacholine challenge testing, and fiberoptic bronchoscopy with bronchoalveolar lavage. Other procedures including lung biopsy were performed if clinically indicated. Fifty patients completed the study procedures. A large percentage (42%) remained undiagnosed, including 12% with normal testing and an isolated increase in lavage neutrophils or lymphocytes. Twenty (40%) patients demonstrated some evidence of airway hyperreactivity to include eight who met asthma criteria and two with findings secondary to gastroesophageal reflux. Four (8%) additional patients had isolated reduced diffusing capacity and the remaining six had other miscellaneous airway disorders. No patients were identified with diffuse parenchymal disease on the basis of computed tomography imaging. A significant number (66%) of this cohort had underlying mental health and sleep disorders. CONCLUSIONS Evaluation of new respiratory symptoms in military personnel after service in Southwest Asia should focus on airway hyperreactivity from exposures to higher levels of ambient particulate matter. These patients may be difficult to diagnose and require close follow-up.
Functional polymorphism in the regulatory region of gelatinase B gene in relation to severity of coronary atherosclerosis.

BACKGROUND Gelatinase B, a matrix metalloproteinase that has proteolytic activity against connective tissue proteins, has been suggested to be important in the connective tissue remodeling processes associated with atherogenesis and plaque rupture. This study tested the hypothesis that sequence variation in the promoter region of the gelatinase B gene influences its expression, predisposing individuals carrying certain genetic variants to more severe atherosclerosis. METHODS AND RESULTS Single-strand conformation polymorphism analysis was carried out to search the promoter region of the gene encoding gelatinase B for naturally occurring genetic variation. As a result, an unreported common polymorphism was detected, which arose from a cytosine (C) to thymidine (T) transition at position -1562 relative to the start of transcription. Transient transfection experiments and DNA-protein interaction assays indicated that the T allele had a higher promoter activity than the C allele, which appeared to be due to preferential binding of a putative transcription repressor protein to the C allelic promoter. A sample of 584 male patients with myocardial infarction and 645 age-matched male healthy control subjects were genotyped. The allele frequencies were not significantly different between the cases and control subjects. However, in 374 patients with available angiographic data, 26% of those carrying 1 or 2 copies of the T allele had >50% stenosis in 3 coronary arteries, whereas only 15% of C/C homozygotes had triple-vessel disease. CONCLUSIONS These data suggest that this functional genetic variation influences gelatinase B gene promoter activity in an allele-specific manner and has an effect on atherosclerotic phenotype.
Multitask Multiclass Support Vector Machines

In this paper, we present a new classification method named multitask multiclass support vector machines based on the regularization principle. Our starting point is the recent success of multitask learning which has shown that learning multiple related tasks simultaneously can get better results than learning these tasks independently. We cast multitask multiclass problems as a constrained optimization problem with a quadratic objective function. Unlike most approaches which typically decompose a multitask multiclass problem into multiple multitask binary classification problems, our approach can learning multitask multiclass problems directly and effectively. This paper also derives the dual optimization which indicates the relations between tasks. The linear multitask multiclass learning method can be generalized to non-linear cases by the kernel trick. Experimental results indicate that the new approach can get encouraging results for multitask multiclass problems.
Analyzing myopic approaches for multi-agent communication

Choosing when to communicate is a fundamental problem in multi-agent systems. This problem becomes particularly hard when communication is constrained and each agent has different partial information about the overall situation. Although computing the exact value of communication is intractable, it has been estimated using a standard myopic assumption. However, this assumption - that communication is only possible at the present time ntroduces error that can lead to poor agent behavior. We examine specific situations in which the myopic approach performs poorly and demonstrate an alternate approach that relaxes the assumption to improve the performance. The results provide an effective method for value-driven communication policies in multi-agent systems.
Experimental Studies of a Novel 6-DOF Haptic Device

This paper presents experimental studies for increasing transparencies in haptic interaction. In particular, the experimental results of this paper are concerned with the new design and the prototype of a 6DOF haptic device. This device consists of a passive/active spherical joint and the connecting serial link mechanisms. The gravity compensation is accomplished both mechanically and through feed-forward compensation. The passive spherical joint can mechanically compensate for the gravity loading of the spherical active links and the associated connected serial mechanism to the floating platform. It is shown that through implementation of passivity-based controller, closed-loop stability of the system can be achieved when interacting with increased stiffness of the virtual environment.
CONDITIONING DEFICITS OF CaM-KINASE TRANSGENIC DROSOPHILA MELANOGASTER IN A NEW EXCITATORY COURTSHIP ASSAY

Courtship suppression is an associative conditioning procedure in Drosophila melanogaster that is ethologically based and capable of being tested on individual flies. We have expanded the range of the courtship conditioning by developing an excitatory procedure in which male flies learn to associate a novel odor with the courtship stimulating cues of virgin females. Wild-type males normally court other mature males very little, but following training, the odor alone is able to elicit increased levels of courtship towards an object male. Flies expressing an inhibitor of calcium/calmodulin-dependent protein kinase II (CaMKII) were previously shown to have no retention one hour after training in the courtship suppression task, as manifested in their persistent courting of a virgin female. A possible trivial explanation for this response is that the CaMKII-inhibited fly strains ( ala1 and ala2 ) were merely hyperactive courters. The poor performance of these mutants in the new excitatory conditioning procedure confirms that their conditioning deficit results from a disruption of an associative mechanism per se.
Identifying usage anomalies for ECG-based sensor nodes

Body Sensor Networks (BSNs) are being used across a wider range of applications including healthcare ones where sensors may be attached to the body to sense certain properties including Electrocardiogram (ECG). The dependability of the systems is a key concern and is affected by the way in which it is used. For example, if the leads are loosely attached then the resulting signal will not be useful. It has been reported that the rate of such error is around 4% in the intensive care unit [8] when operating medical devices by trained professionals. The problem is made worse as the users of the systems are often not trained professionals. Some work has been performed on detecting anomalous signals. However, all of it has concentrated on anomalies caused by medical conditions (e.g arrhythmia). That is, to the best of our knowledge, no prior work has looked at anomalies caused by incorrect usage. In this paper a range of usage anomalies are defined in conjunction with a cardiologist and a lightweight algorithm is developed that achieves a high identification rate.
An efficient feature extraction methodology for blind image steganalysis using contourlet transform and Zernike moments

We propose an effective blind image steganalysis based on contourlet transform and Zernike moments that improves the detection accuracy of universal image steganalysis methods. The proposed method examines randomness in the test image to distinguish between the stego and non-stego images. The suspicious image is decomposed by contourlet transform, and then the absolute Zernike moments of contourlet subbands coefficients of the image and linear prediction error of each contourlet subband are extracted as features for steganalysis. These features are fed to a nonlinear SVM classifier with an RBF kernel to distinguish between cover and stego images. Experimental results show that the proposed features are highly sensitive to the change made by the embedding process to the statistical characteristics of the image. These results also reveal advantage of the proposed method over its counterpart stegan-alyzers, in cases of four popular jpeg steganography techniques. This improvement is mostly due to the greater noise sensitivity achieved using the Zernike moments that yield at least 3.5%-5% higher stego detection accuracy, relating to that of two baseline steganalyzers.
Energy Efficiency in LTE-A Network

Due to increase in the mobile users in a cell site, the operators are insisted to provide good coverage in terms of speed and coverage even in the cell edges. This leads to higher connectivity and operative of the mobile station, which requires higher energy to perform this task efficiently. A lot of cash inside the cell networks is being wasted, especially in the network's RBSs, in the form of electricity consumption – partially because the RBSs aren't getting used in the most desirable and green way, and in part due to the fact more green and stylish answers were developed to address a number of the RBS's features higher than the present day RBS's themselves. Operating costs are also being jacked up due to the growth of the carbon footprint of the LTE-A networks.