Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust speaker identification in noisy environment using cross diagonal GTF-ICA feature

In this paper, we present a novel feature specifically designed for speaker identification in noisy environments. Gammatone auditory filterbank and independent component analysis (GTF-ICA) feature emphasises the difference in the statistical structures of the human cochlea frequency bands among speakers. This method results in significant improvements in the identification accuracy over the conventional methods when speech is corrupted by additive noise and when the training and testing environments are mismatched. However GTF-ICA imposes high computation cost in comparison to the other features. The proposed feature alleviates the computation by considering the cross diagonal elements of GTF-ICA feature matrix used with the Gaussian mixture models (GMM). The proposed algorithm is more computationally efficient than our pervious one. In addition, it increases the identification rate in noisy and mismatched environments.
Analysis of Ultra-tight GPS/INS Integrated System for Navigation Performance

The concept of integrating GPS and INS systems in ultra-tight mode has been presented in this paper. The advantages of ultra-tight integrated system over the loosely and tightly coupled systems have been discussed in detail. An extended Kalman filter was designed to evaluate the system's performance. Simulation experiments have been conducted to assess the performance, and the results suggest that the various algorithms and the statistical assumptions carried out are valid.
Inductive Teaching and Learning Methods: Definitions, Comparisons, and Research Bases

Traditional engineering instruction is deductive, beginning with theories and progressing to the applications of those theories. Alternative teaching approaches are more inductive. Topics are introduced by presenting specific observations, case studies or problems, and theories are taught or the students are helped to discover them only after the need to know them has been established. This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem‐based learning, project‐based learning, case‐based teaching, discovery learning, and just‐in‐time teaching. The paper defines each method, highlights commonalities and specific differences, and reviews research on the effectiveness of the methods. While the strength of the evidence varies from one method to another, inductive methods are consistently found to be at least equal to, and in general more effective than, traditional deductive methods for achieving a broad range of learning outcomes.
RACKING FOR PUNJABI LANGUAGE

This paper introduces Topic Tracking for Punjabi language. Text mining is a field that automatically extracts previously unknown and useful information from unstructured textual data. It has strong connections with natural language processing. NLP has produced technologies that teach computers natural language so that they may analyze, understand and even generate text. Topic tracking is one of the technologies that has been developed and can be used in the text mining process. The main purpose of topic tracking is to identify and follow events presented in multiple news sources, including newswires, radio and TV broadcasts. It collects dispersed information together and makes it easy for user to get a general understanding. Not much work has been done in Topic tracking for Indian Languages in general and Punjabi in particular. First we survey various approaches available for Topic Tracking, then represent our approach for Punjabi. The experimental results are shown.
Expression Profile and Clinical Significance of MicroRNAs in Papillary Thyroid Carcinoma

This study screened microRNAs (miRNAs) that are abnormally expressed in papillary thyroid carcinoma (PTC) tissues to identify PTC and nodular goiter and the degree of PTC malignancy. A total of 51 thyroid tumor tissue specimens paired with adjacent normal thyroid tissues were obtained from the Department of Surgical Oncology of Hangzhou First People’s Hospital from June-December 2011. miRNA expression profiles were examined by microarrays and validated by quantitative real-time PCR (qRT-PCR). Expression levels of the miRNAs were analyzed to assess if they were associated with selected clinicopathological features. Eleven miRNAs were significantly differentially expressed between nodular goiter and PTC and between highly invasive and low invasive PTC. miR-199b-5p and miR-30a-3p were significantly differentially expressed among the three groups. miR-30a-3p, miR-122-5p, miR-136-5p, miR-146b-5p and miR-199b-5p were selected for further study by qRT-PCR and miR-146b-5p, miR-199b-5p and miR-30a-3p were different between the PTC and nodular goiter groups. miR-199b-5p was over-expressed in PTC patients with extrathyroidal invasion and cervical lymph node metastasis. In conclusion miR-146b-5p, miR-30a-3p, and miR-199b-5p may serve as biomarkers for the diagnosis of PTC and miR-199b-5p is associated with PTC invasiveness.
Cosmic ray signals from mini black holes in models with extra dimensions: an analytical/Monte Carlo study

It is shown that the partial and total multiplicities and the lateral distributions of the shower particles can distinguish between events produced by the evaporation of mini black holes from normal ones with the same energy due, for instance, to a primary-proton - nucleon collision. The analysis is performed via a large scale simulation of the resulting cascades in the two cases over the entire range (1015−1019 eV) of ultra high energies, for several values of the number of large extra dimensions, for a variety of altitudes of the initial interaction and with the energy losses in the bulk taken into account. The electromagnetic/hadronic ratio is strongly fluctuating and, thus, not conclusive for the altitudes considered. The relevance of these results to a possible black hole interpretation of the Centauro events is commented upon.
The relative contributions of stereo, lighting, and background scenes in promoting 3D depth visualization

More powerful contemporary computer hardware has enabled the development and exploration of a wide variety of techniques to depict spatial characteristics of computer-generated objects in three-dimensional (3D) space. Particularly, the role of stereoscopic viewing and the use of object motion to reflect the position and size of objects in 3D space have been extensively studied. However, the effective use of computer-rendered object shadows to provide spatial information about the relative position and size of objects in virtual space has not. Subjects perform two tasks with 3D geometric patterns of objects presented on a computer screen: (1) positioning the object to complete a symmetrical geometric figure and (2) resizing the object to match the size of other objects. Performance accuracy and speed are recorded under the following conditions: (1) objects casting shadows on and off, (2) shadows from one or two light sources (nested within the shadows-on condition), (3) stereoscopic and monoscopic viewing, and (4) different scene backgrounds: flat plane (i.e., floor), “stair-step” floor with no walls, and floor with walls (i.e., room). The use of object shadows as depth cues enhances the accuracy (but not the speed) of object positioning, but does not enhance either the accuracy or the speed of object resizing. Moreover, the object shadows are not as effective as stereoscopic viewing in facilitating both positioning-task and resizing-task performances. Furthermore, task performances degrade with the stair-step scene background and when the number of shadowing light sources increases from one to two. This research was sponsored by the Advanced Visual Tools and Architectures in Code 588 and by the Scientific Visualization Studio in Code 935 of the Goddard Space Flight Center (GSFC) of the National Aeronautics and Space Administration (NASA) in Greenbelt, Maryland, USA.
Touchscreen Everywhere: On Transferring a Normal Planar Surface to a Touch-Sensitive Display

We address how a human-computer interface with small device size, large display, and touch-input facility can be made possible by a mere projector and camera. The realization is through the use of a properly embedded structured light sensing scheme that enables a regular light-colored table surface to serve the dual roles of both a projection screen and a touch-sensitive display surface. A random binary pattern is employed to code structured light in pixel accuracy, which is embedded into the regular projection display in a way that the user perceives only regular display but not the structured pattern hidden in the display. With the projection display on the table surface being imaged by a camera, the observed image data, plus the known projection content, can work together to probe the 3-D workspace immediately above the table surface, like deciding if there is a finger present and if the finger touches the table surface, and if so, at what position on the table surface the contact is made. All the decisions hinge upon a careful calibration of the projector-camera-table surface system, intelligent segmentation of the hand in the image data, and exploitation of the homography mapping existing between the projector's display panel and the camera's image plane. Extensive experimentation including evaluation of the display quality, hand segmentation accuracy, touch detection accuracy, trajectory tracking accuracy, multitouch capability and system efficiency are shown to illustrate the feasibility of the proposed realization.
The Role of Family in a Dietary Risk Reduction Intervention for Cardiovascular Disease

Diet is an essential strategy for the prevention of primary and secondary cardiovascular disease (CVD) events. The objectives were to examine: how families at increased risk of CVD perceived personal risk, their motivations to make dietary changes, their understanding of diet, and the influence of other family members. Individuals (>18 years) who completed an Australian family-based CVD risk reduction program were invited to a semi-structured telephone interview. Responses were recorded, transcribed verbatim and analysed using a systematic deductive approach with coding derived from key concepts developed as part of the interview structure. Seventeen participants from eight families were interviewed (aged 18–70 years, 47% male, five with CVD diagnosis). Key themes indicated both intrinsic and extrinsic motivations to improve heart health, variations in risk perception, recognition of the role diet plays in heart health, and the extent of family influences on eating patterns. Discrepancies between perceived and actual CVD risk perception impacted on perceived “need” to modify current dietary patterns towards heart health recommendations. Therefore, strategies not reliant on risk perception are needed to engage those with low risk perception. This could involve identifying and accessing the family “ringleader” to influence involvement and capitalising on personal accountability to other family members.
Visuo-Haptic Interactions in Unilateral Spatial Neglect: The Cross Modal Judd Illusion

Unilateral spatial neglect (USN) has been mainly investigated in the visual modality; only few studies compared spatial neglect across different sensory modalities, and explored their multisensory interactions, with controversial results. We investigated the integration between vision and haptics, through a bisection task of a cross modal illusion, the Judd variant of the Müller-Lyer illusion. We examined right-brain-damaged patients with (n = 7) and without (n = 7) left USN, and neurologically unimpaired participants (n = 14) in the bisection of Judd stimuli under visual, haptic, and visuo-haptic presentation. Neglect patients showed the characteristic rightward bias in the bisection of the baseline stimuli in the visual modality, but not in the haptic and visuo-haptic conditions. The illusory effects were preserved in each group and in each modality, indicating that the processing of the cross modal illusion is independent of the presence of deficits of spatial attention and representation. Spatial neglect can be modality-specific, but visual and tactile sensory inputs are properly integrated.
Finite mixture models and model-based clustering

Finite mixture models have a long history in statistics, hav- ing been used to model pupulation heterogeneity, generalize distributional assumptions, and lately, for providing a convenient yet formal framework for clustering and classication. This paper provides a detailed review into mixture models and model-based clustering. Recent trends in the area, as well as open problems are also discussed.
Approximated MLC shape matrix decomposition with interleaf collision constraint

Shape matrix decomposition is a subproblem in radiation therapy planning. A given fluence matrix A has to be decomposed into a sum of shape matrices corresponding to homogeneous fields that can be shaped by a multileaf collimator (MLC). We solve the problem of minimizing the delivery time for an approximation of A satisfying certain prescribed bounds, under the additional condition that the used MLC requires the interleaf collision constraint.
A Dynamical Model for Biological Data Clustering

In the middle of 1990s, Wang and coworkers proposed the oscillatory correlation theory [3], which can be summarized by the following rule: the neurons that process different features from the same object have the same underlying frequency of oscillation (synchronization), while neurons that represent different objects oscillate with different frequencies or at random (desynchronization). Many oscillatory correlation models have been developed and successfully applied to solve various problems. In this work, we apply the oscillatory correlation theory to cluster gene expression data. Clustering techniques have an important role in data analysis [2]. In this paper, we propose a new data clustering method based on dynamical system modelling. It is a network consisting of interacting elements, each of them representing an attribute vector of an input data. As the system runs, each element receives attractions from other elements within a certain region. Those attractions, determined by predefined similarity measure, drive the element to converge to their corresponding cluster center. Ambiguous elements that receive forces from more than one group, will leave all other groups and fix themselves in only one group, which has stronger attraction to them. The main advantages of the model are that it can achieve multi-scale data clustering, it does not need to previously know the number of clusters and the mechanism of adaptive changing of data point makes the model robust enough to classify ambiguous elements. In order to validate the proposed model, we show how it can be used for clustering of biological data. For such, Experimental results obtained with a microarray gene expression data set generated from leukemia tissues is used [1]. The results obtained are very promising, but due to lack of space, they are not presented in this abstract.
Anomaly detection of domain name system (DNS) query traffic at top level domain servers

Major network events can be reflected on domain name system (DNS) traffic at the top level server on the DNS hierarchical structure. This paper pursues a novel approach to detect the DNS traffic anomaly of 5.19 events in China at CN top level domain server using covariance analysis. We normalize, expand and average the covariance changes for different length of time slice to enhance the robustness of detection. Feature anomaly is detected based on clustering analysis of covariance change anomaly. To improve the accuracy and reduce the complexity of the k –means algorithm, an initial cluster selection technique is proposed and its performance is analyzed. Transient anomaly and time span anomaly are defined and an efficient real time approximating algorithm is derived. We use an incremental computational method for covariance matrix. The computation and transmission scheme of feature values are analyzed and the process of the detecting algorithm is given. The traffic detecting results of 5.19 event shows that the approach can accurately detect the network anomaly.
Personality Changes after Deep Brain Stimulation in Parkinson's Disease

Objectives. Deep brain stimulation of the subthalamic nucleus (STN-DBS) is a recognized therapy that improves motor symptoms in advanced Parkinson's disease (PD). However, little is known about its impact on personality. To address this topic, we have assessed personality traits before and after STN-DBS in PD patients. Methods. Forty patients with advanced PD were assessed with the Temperament and Character Inventory (TCI): the Urgency, Premeditation, Perseverance, Sensation Seeking impulsive behaviour scale (UPPS), and the Neuroticism and Lie subscales of the Eysenck Personality Questionnaire (EPQ-N, EPQ-L) before surgery and after three months of STN-DBS. Collateral information obtained from the UPPS was also reported. Results. Despite improvement in motor function and reduction in dopaminergic dosage patients reported lower score on the TCI Persistence and Self-Transcendence scales, after three months of STN-DBS, compared to baseline (P = 0.006; P = 0.024). Relatives reported significantly increased scores on the UPPS Lack of Premeditation scale at follow-up (P = 0.027). Conclusion. STN-DBS in PD patients is associated with personality changes in the direction of increased impulsivity.
Mechanisms of cellular proteostasis: insights from single molecule approaches (226.3)

Cells employ a variety of strategies to maintain the proteome homeostasis. Beginning during protein biogenesis, the ribosome itself and a number of molecular chaperones promote correct de novo folding of nascent proteins even before synthesis is complete. Another set of molecular chaperones helps to maintain proteins in their functional, native state. Polypeptides that are no longer needed or pose a threat to the cell, such as misfolded proteins and aggregates, are removed in an efficient and timely fashion by ATP‐dependent proteases. In this talk I will describe how the application of single‐molecule methods, in particular optical tweezers, is shedding new light on the molecular mechanisms of quality control during the life cycle of proteins.
Globular clusters in modified Newtonian dynamics: velocity-dispersion profiles from self-consistent models

We test the modified Newtonian dynamics (MOND) theory with the velocity dispersion profiles of Galactic globular clusters populating the outermost region of the Milky Way halo, where the Galactic acceleration is lower than the characteristic MOND acceleration a 0 . For this purpose, we constructed self-consistent, spherical models of stellar systems in MOND, which are the analogues of the Newtonian King models. The models are spatially limited, reproduce well the surface brightness profiles of globular clusters and have velocity dispersion profiles that differ remarkably in shape from the corresponding Newtonian models. We present dynamical models of six globular clusters, which can be used to efficiently test MOND with the available observing facilities. A comparison with recent spectroscopic data obtained for NGC 2419 suggests that the kinematics of this cluster might be hard to explain in MOND.
PCB-47 , PBDE-47 , and 6-OH-PBDE-47 Differentially Modulate Human GABAA and a 4 b 2 Nicotinic Acetylcholine Receptors

Polychlorinated biphenyls (PCBs) and the structurally related polybrominated diphenyl ethers (PBDEs) are abundant persistent organic pollutants that exert several comparable neurotoxic effects. Importantly, hydroxylated metabolites of PCBs and PBDEs have an increased neurotoxic potency. Recently, we demonstrated that PCBs can act as (partial) agonist on GABAA neurotransmitter receptors, with PCB-47 being the most potent congener. It is, however, unknown whether PBDE-47 and its metabolite 6-OH-PBDE-47 exert similar effects and if these effects are limited to GABAA receptors only. We therefore investigated effects of PCB-47, PBDE-47, and 6-OH-PBDE-47 on the inhibitory GABAA and excitatory a4b2 nicotinic acetylcholine (nACh) receptor expressed in Xenopus oocytes using the twoelectrode voltage-clamp technique. Since human exposure is generally not limited to individual compounds, experiments with binary mixtures were also performed. The results demonstrate that PCB-47 and 6-OH-PBDE-47 act as full and partial agonist on the GABAA receptor. However, both congeners act as antagonist on the nACh receptor. PBDE-47 does not affect either type of receptor. Binary mixtures of PCB-47 and 6-OH-PBDE-47 induced an additive activation as well as potentiation of GABAA receptors, whereas this mixture resulted in an additive inhibition of nACh receptors. Binary mixtures of PBDE-47 and 6-OH-PBDE-47 yielded similar effects as 6-OH-PBDE-47 alone. These findings demonstrate that GABAA and nACh receptors are affected differently by PCB-47 and 6-OH-PBDE-47, with inhibitory GABAA-mediated signaling being potentiated and excitatory a4b2 nACh–mediated signaling being inhibited. Considering these opposite actions and the additive interaction of the congeners, these effects are likely to be augmented in vivo.
Exploring the Competition between Proliferative and Invasive Cancer Phenotypes in a Continuous Spatial Model

Tumor is characterized by extensive heterogeneity with respect to its microenvironment and its genetic composition. We extend a previously developed monoclonal continuous spatial model of tumor growth to account for polyclonal cell populations and investigate the interplay between a more proliferative and a more invasive phenotype under different conditions. The model simulations demonstrate a transition from the dominance of the proliferative to the dominance of the invasive phenotype resembling malignant tumor progression and show a time period where both subpopulations are abundant. As the dominant phenotype switches from proliferative to invasive, the geometry of tumor changes from a compact and almost spherical shape to a more diffusive and fingered morphology with the proliferative phenotype to be restricted in the tumor bulk and the invasive to dominate at tumor edges. Different micro-environmental conditions and different phenotypic properties can promote or inhibit invasion demonstrating their mutual importance. The model provides a computational framework to investigate tumor heterogeneity and the constant interplay between the environment and the specific characteristics of phenotypes that should be taken into account for the prediction of tumor evolution, morphology and effective treatment.
A Society of Models for Video and Image Libraries

The average person with a computer will soon have access to the world's collections of digital video and images. However, unlike text that can be alphabetized or numbers that can be ordered, image and video has no general language to aid in its organization. Tools that can "see" and "understand" the content of imagery are still in their infancy, but they are now at the point where they can provide substantial assistance to users in navigating through visual media. This paper describes new tools based on "vision texture" for modeling image and video. The focus of this research is the use of a society of low-level models for performing relatively high-level tasks, such as retrieval and annotation of image and video libraries. This paper surveys recent and present research in this fast-growing area.