Miracle-dz/UniFAR-FTUs huggingface dataset:
Iterative Clustering Approach for Text Independent Speaker Identification using Multiple Features

The main objective of this paper is to explore the effectiveness of features for identifying speakers. We propose features such as line spectral frequency (LSF), differential line spectral frequency (DLSF), mel frequency cepstral coefficients (MFCC), discrete cosine transform cepstrum (DCTC), perceptual linear predictive cepstrum (PLP) and mel frequency perceptual linear predictive cepstrum (MF-PLP). These features are captured and training models are developed by K-means clustering procedure. A speaker identification system is evaluated on noise added test speeches and the experimental results reveal the performance of the proposed algorithm in identifying speakers based on minimum distance between test features and clusters and also highlight the best choice of feature set among all the proposed features for 50 speakers chosen randomly from ldquoTIMITrdquo database. In this work, F-ratio is computed as a theoretical measure to validate the experimental results.
Large-scale distributed sorting for GPU-based heterogeneous supercomputers

Splitter-based parallel sorting algorithms are known to be highly efficient for distributed sorting due to their low communication complexity. Although using GPU accelerators could help to reduce the computation cost in general, their effectiveness in distributed sorting algorithms on large-scale heterogeneous GPU-based systems remains unclear. We investigate applicability of using GPU devices to the splitter-based algorithms and extend HykSort, an existing splitter-based algorithm by offloading costly computation phases to GPUs. We also handle GPU memory overflows by introducing an iterative approach which sorts multiple chunks and merges them into one array. We evaluate the performance of our implementation with local sort acceleration on the TSUBAME2.5 supercomputer that comprises over 4000 NVIDIA K20x GPUs. Performance evaluation of weak scaling shows that we achieve 389 times speedup with 0.25TB/s throughput when sorting 4TB 64bit integer on 1024 nodes compared to running on 1 node; on the other hand, for CPU vs. GPU comparison, our implementation achieves only 1.40 times speedup using 1024 nodes. Detailed analysis however reveals that the limitation is almost entirely due to the bottleneck in CPU-GPU host-to-device bandwidth. With orders of magnitude improvements planned for next generation GPUs, the performance boost will be tremendous in accordance with other successful GPU accelerations.
Extracting Arabic semantic graph from Aljazeera.net

Collaborative knowledge bases such as Wikipedia and Wiktionary became valuable lexical semantic resources with a high influence in diverse Natural Language Processing tasks. Although Arabic collaborative knowledge bases are in general poorly informatized and significantly different from traditional linguistic knowledge bases in various respects. Aljazeera.net is professionally edited and has rich semantic structure. It constitutes an asset, an impediment and a challenge for research in Arabic Natural Language Processing. This paper addresses one such major impediment, namely the lack of suitable tools to access the knowledge stored in these large semantic knowledge bases. We present a framework designed for mining the explicit and implicit lexical semantic information impeded in the structure and the content of Aljazeera.net. Furthermore, it provides an efficient and structured access to the resulted semantic graph. This framework will be freely available for research purposes to meet the needs of Arabic Natural Language Processing community.
XQuery Evaluation with Relevance Ranking in Structured Peer-to-Peer Systems

This paper addresses the problem of publishing, indexing, and querying large XML data repositories distributed over an existing peer-to-peer (P2P) service infrastructure. Our architecture scales gracefully to the network and data sizes by supporting thousands of nodes, massive data, and frequent queries and updates. It is fully distributed, fault tolerant and self-organizing, and handles complex queries efficiently, even those queries that use full-text search, approximate matching, and inter-document relationships. It also provides balanced workload and storage, low search traffic and latency, and low maintenance overhead. The novelty of our framework is that it is both a sophisticated data management and an IR system. It extends state-ofthe-art database technologies, such as XML indexing and advanced XQuery processing, to work in a distributed P2P environment. It also adapts modern IR query processing techniques to facilitate XML relevance ranking based on distributed inverted lists. We report on a prototype implementation, which is used to analyze the various costs involved in indexing XML data and answering queries.
Application of errorless learning in adult acquired brain injury rehabilitation

This chapter reviews the evidence from these studies of errorless (EL) learning in people with acquired brain injury, excluding those who present with language disorders and those with Korsakoff's syndrome. It describes the evidence for EL learning as a function of study design. Group studies are also classified in terms of the types of task used, so that the nature of the tasks for which a benefit of EL learning has been demonstrated is clear. Furthermore, studies are also discussed in relation to the type of test of learning used, and the specific form of the EL learning technique, noting that some might be described as "error-minimising" rather than "errorless". An issue for the word-list studies is they rely on cued recall to facilitate recollection. A small number of studies have used word-list paradigms to investigate learning methods that differ from the standard EL learning format.
Development of the robot system for the process improvement of the castings of the runner and gate cutting

In this paper, we propose a robotic system for the automatic cutting of castings for gas turbine runner and gate. It requires a lot of time and effort of the cutting operating by the operator because of this product materials are tough and compact. In order to overcome this difficulty, we propose a robotic system that can automatically identify and respond to the condition of the product and replacing the cutting tools. We verify the practicality of the proposed robotic system is applied to the actual cutting and grinding operations.
Automated ISA branch coverage analysis and test case generation for retargetable instruction set simulators

Processor design tools integrate in their workflows generators for instruction set simulators (ISS) from architecture descriptions. However, it is difficult to validate the correctness of these simu-lators. ISA coverage analysis is insufficient to isolate modelling faults, which might only be exposed in corner cases. We present a novel ISA branch coverage analysis, which considers every possible execution path within an instruction and, on demand, generates new test cases to cover the missing paths. We have applied this analysis to industry standard EEMBC and SPEC CPU2006 benchmarks and show that for an ARM V5T model neither of these benchmark suites provides a sufficient ISA coverage to exercise every path through each instruction of the whole instruction set.
The Expression of Plasma Membrane Ca2+ Pump Isoforms in Cerebellar Granule Neurons Is Modulated by Ca2+ *

Plasma membrane Ca2+ ATPase (PMCA) pump isoforms 2, 3, and 1CII are expressed in large amounts in the cerebellum of adult rats but only minimally in neonatal cerebellum. These isoforms were almost undetectable in rat neonatal cerebellar granule cells 1–3 days after plating, but they became highly expressed after 7–9 days of culturing under membrane depolarizing conditions (25 mm KCl). The behavior of isoform 4 was different: it was clearly detectable in adult cerebellum but was down-regulated by the depolarizing conditions in cultured cells. 25 mmKCl-activated l-type Ca2+ channels, significantly increasing cytosolic Ca2+. Changes in the concentration of Ca2+ in the culturing medium affected the expression of the pumps. l-type Ca2+ channel blockers abolished both the up-regulation of the PMCA1CII, 2, and 3 isoforms and the down-regulation of PMCA4 isoform. When granule cells were cultured in high concentrations ofN-methyl-d-aspartic acid, a condition that increased cytosolic Ca2+ through the activation of glutamate-operated Ca2+ channels, up-regulation of PMCA1CII, 2, and 3 and down-regulation of PMCA4 was also observed. The activity of the isoforms was estimated by measuring the phosphoenzyme intermediate of their reaction cycle: the up-regulated isoforms, the activity of which was barely detectable at plating time, accounted for a large portion of the total PMCA activity of the cells. No up-regulation of the sarcoplasmic/endoplasmic reticulum calcium pump was induced by the depolarizing conditions.
Deep biomarkers of human aging: Application of deep neural networks to biomarker development

One of the major impediments in human aging research is the absence of a comprehensive and actionable set of biomarkers that may be targeted and measured to track the effectiveness of therapeutic interventions. In this study, we designed a modular ensemble of 21 deep neural networks (DNNs) of varying depth, structure and optimization to predict human chronological age using a basic blood test. To train the DNNs, we used over 60,000 samples from common blood biochemistry and cell count tests from routine health exams performed by a single laboratory and linked to chronological age and sex. The best performing DNN in the ensemble demonstrated 81.5 % epsilon-accuracy r = 0.90 with R2 = 0.80 and MAE = 6.07 years in predicting chronological age within a 10 year frame, while the entire ensemble achieved 83.5% epsilon-accuracy r = 0.91 with R2 = 0.82 and MAE = 5.55 years. The ensemble also identified the 5 most important markers for predicting human chronological age: albumin, glucose, alkaline phosphatase, urea and erythrocytes. To allow for public testing and evaluate real-life performance of the predictor, we developed an online system available at http://www.aging. ai. The ensemble approach may facilitate integration of multi-modal data linked to chronological age and sex that may lead to simple, minimally invasive, and affordable methods of tracking integrated biomarkers of aging in humans and performing cross-species feature importance analysis.
An improved Normalized Cross Correlation algorithm for object tracking

This work describes a novel algorithm for real time tracking of imaging targets in video sequence. Normalized Cross Correlation based on Box-Filtering (NCC-BF) is a widely used algorithm in practice. But NCC-BF still has lots of redundancies in exhaustive template matching process. Thus we put forward a sufficient termination condition based on an adaptive lower bound threshold function in this paper, and we have proved that if this termination condition is verified, the correlation score at current position must lower than the maximum correlation obtained in previous, thus the template can be proceed with next reference position with out executing the rest of operations in current position. So the redundancy in NCC-Based object tracking can be efficiently reduced by our novel termination condition described in this paper. The experimental results of our new algorithm and actual CPU time are reported.
Lost or fond? Effects of nostalgia on sad mood recovery vary by attachment insecurity

Nostalgia involves a fond recollection of people and events lost to time. Growing evidence indicates that nostalgia may ameliorate negative affective states such as loneliness and boredom. However, the effect of nostalgia on sadness is unknown, and there is little research on how social connectedness might impact nostalgia's effects. Grounded in a theoretical framework whereby people with lower levels of attachment insecurity benefit more from nostalgia, we exposed participants to a mortality-related sad mood and then randomly assigned them to reflect on a nostalgic or an ordinary event memory. We examined changes in mood and electrodermal activity (EDA) and found that nostalgic versus ordinary event memories led to a blunted recovery from sad mood, but that this effect was moderated by degree of attachment insecurity, such that participants with low insecurity benefited from nostalgia whereas people with high insecurity did not. These findings suggest that nostalgia's benefits may be tied to the degree of confidence one has in one's social relationships.
The Thermostable Direct Hemolysin from Grimontia hollisae Causes Acute Hepatotoxicity In Vitro and In Vivo

Background G. hollisae thermostable direct hemolysin (Gh-TDH) is produced by most strains of G. hollisae. This toxin has been reported to be absorbed in the intestines in humans. Secondary liver injury might be caused by venous return of the toxin through the portal system. We aimed to firstly analyze the in vitro and in vivo hepatotoxicity of Gh-TDH. Methods Liver cells (primary human non-cancer cell and FL83B mouse cells) were treated and mice (BALB/c) were fed with this toxin to investigate its hepatotoxicity. Morphological examination and cytotoxicity assays using liver cells were also performed. Fluorescein isothiocyanate-conjugated toxin was used to analyze the localization of this protein in liver cells. Mice were subjected to liver function measurements and liver biopsies following toxin treatment and wild-type bacterial infection. PET (positron emission tomography)/CT (computed tomography) images were taken to assess liver metabolism during acute injury and recovery. Results The effect of hepatotoxicity was dose and time dependent. Cellular localization showed that the toxin was initially located around the cellular margins and subsequently entered the nucleus. Liver function measurements and liver biopsies of the mice following treatment with toxin or infection with wild-type Grimontia hollisae showed elevated levels of transaminases and damage to the periportal area, respectively. The PET/CT images revealed that the reconstruction of the liver continued for at least one week after exposure to a single dose of the toxin or bacterial infection. Conclusions The hepatotoxicity of Gh-TDH was firstly demonstrated. The damage was located in the periportal area of the liver, and the liver became functionally insufficient.
A 2D Fiducial Tracking Method based on Topological Region Adjacency and Angle Information

We describe a new method for 2D fiducial tracking. We use region adjacency information together with angles between regions to encode IDs inside fiducials, whereas previous research by Kaltenbrunner and Bencina utilize region adjacency tree. Our method supports a wide ID range and is fast enough to accommodate real-time video. It is also very robust against false positive detection.
High resolution simulations of unstable modes in a collisionless disc

We present N-body simulations of unstable spiral modes in a dynamically cool collisionless disc. We show that spiral modes grow in a thin collisionless disk in accordance with the analytical perturbation theory. We use the particle-mesh code superbox with nested grids to follow the evolution of unstable spirals that emerge from an unstable equilibrium state. We use a large number of particles (up to N = 40 × 10 6 ) and high-resolution spatial grids in our simulations (128 3 cells). These allow us to trace the dynamics of the unstable spiral modes until their wave amplitudes are saturated due to nonlinear effects. In general, the results of our simulations are in agreement with the analytical predictions. The growth rate and the pattern speed of the most unstable bar-mode measured in N-body simulations agree with the linear analysis. However the parameters of secondary unstable modes are in lesser agreement because of the still limited resolution of our simulations.
An Improved EEMD-based Framework for CPI Forecasting

Although the Empirical Mode Decomposition (EMD)-based decomposition and ensemble framework for time series forecasting has been widely used, the end effect of EMD has not been addressed adequately. This study proposed to incorporate Mirror Method (MM), capable of dealing with the problem of end effect, into a hybrid modeling framework with Ensemble Empirical Mode Decomposition (EEMD) and Support Vector Machines (SVMs) for Consumer Price Index (CPI) Forecasting. The monthly Chinese CPI series from Jan. 2000 to Nov. 2011, with a total 143 observations, were employed to justify the performance of the proposed framework. The results suggested that it performed better than all the selected counterparts in terms of RMSE and SMAPE.
Mosaicfaces: a discrete representation for face recognition

Most face recognition algorithms use a "distance- based" approach: gallery and probe images are projected into a low dimensional feature space and decisions about matching are based on distance in this space. In this paper we use a very different representation, where each face is approximated by a regular grid of patches (a mosaicface). Each of these patches is chosen from a library. Faces are now represented as a list of indices to this library. Since there is no obvious way to measure distance between two such lists, we use a probabilistic approach in which the observed face data is explained by a generative model. There are two phases: (i) Learning - we estimate library contents and associated variability (noise), (ii) Recognition - we evaluate the probability that probe and gallery images were generated from the same library patches. Our method performs significantly better than contemporary approaches in the presence of large illumination changes. Variation in viewing conditions is handled by extending this model to learn equivalences between multiple patch appearances. We demonstrate that our method provides a major improvement on the lighting subset of the XM2VTS database compared to "distance-based" methods.
Improved BER Performance for MIMO-OFDM Systems with Interference Using Joint Parameter Estimation Spatial Filtering Aided MAP Detection

This paper develops a joint maximum a posteriori (MAP) spatial filtering receiver by employing a joint parameter estimation approach for multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) modulation systems, which can achieve promising bit-error-rate (BER) performance in the presence of co-channel interference (CCI). For a MAP receiver to suppress the CCI, conventionally, this can be done in two ways: 1) spatio-temporal filtering (STF) the received signals prior to the fast Fourier transform (FFT), which we refer to it as preFFT-STF; 2) spatial filtering (SF) the received signals posterior to FFT, which is referred to as postFFT-SF. Simulation results show that the proposed scheme outperforms significantly both the preFFT-STF and postFFT-SF systems.
Training for polynomial segment model using the expectation maximization algorithm

One of the difficulties in using the polynomial segment model (PSM) to capture the temporal correlations within a phonetic segment is the lack of an efficient training algorithm comparable with the Baum-Welch algorithm in HMM. In our previous paper, we introduced a recursive likelihood computation algorithm for PSM recognition which can perform Viterbi-style training. In this paper, we extend the recursive likelihood computation into a fast forward-backward PSM training algorithm that maximizes PSM likelihood. In addition, we introduce an improved PSM, dynamic multi-region PSM, that allows a data-driven alignment between observations and the segment trajectory. The dynamic multi-region PSM model outperforms HMM and traditional PSM in both phone classification and phone recognition tasks on the TIMIT corpus.
Quality-Based Price Discrimination and Tax Incidence: Evidence From Gasoline and Diesel Cars

The existing tax policies toward gasoline and diesel cars in European countries provide a unique opportunity to analyze quality-based price discrimination and the implied tax incidence. In my econometric framework, consumers choose the type of engine based on their annual mileage; prices are set by the manufacturers. The relative pricing of gasoline and diesel cars appears to be consistent with monopolistic price discrimination, effectively segmenting low-mileage from high-mileage consumers. On average, about 75% to 90% of the price differentials between gasoline and diesel cars can be explained by markup differences. I draw implications for the effectiveness and the revenue effects of tax policy.
Human cerebral microcirculation and oxygen saturation during propofol-induced reduction of bispectral index.

BACKGROUND Propofol reduces cerebral blood flow (CBF) secondary to cerebral metabolic depression. However, in vitro and in vivo studies demonstrate that propofol directly dilates the vascular smooth muscle. This study investigates the effects of propofol-induced changes in bispectral index (BIS) on cerebral microcirculation and oxygenation during craniotomies. METHODS In 21 craniotomy patients undergoing routine craniotomy, anaesthesia was maintained with propofol 4-10 mg kg⁻¹ h⁻¹ and remifentanil 0.1-0.4 µg kg⁻¹ min⁻¹. Propofol concentration was adjusted to achieve higher BIS (target 40) or lower BIS (target 20). Regional measurements of capillary venous blood flow (rvCBF), oxygen saturation (srvO₂), and haemoglobin amount (rvHb) at 2 mm (grey matter) and 8 mm (white matter) cerebral depth were randomly performed at higher and lower BIS by combined laser-Doppler flowmetry and spectroscopy. Calculations: approximated arteriovenous difference in oxygen content (avDO₂) and cerebral metabolic rate of oxygen (aCMRO₂). RESULTS mean values (sd). STATISTICS Mann-Whitney test (*P<0.05). Results Human cerebral microcirculation and oxygen saturation were assessed at propofol dosages 5.1 (2.3) mg kg⁻¹ h⁻¹ [BIS 40 (9)] and 7.8 (2.1) mg kg⁻¹ h⁻¹ [BIS 21 (7)]. Propofol-induced reduction in BIS resulted in increased srvO₂ (P=0.018), and decreased avDO₂ (P=0.025) and aCMRO(2) (P=0.022), in 2 mm cerebral depth, while rvCBF and rvHb remained unchanged. In 8 mm cerebral depth, srvO₂, rvCBF, rvHb, and also calculated parameters avDO₂ and aCMRO₂ remained unaltered. CONCLUSIONS Findings suggest alteration of the CBF/CMRO₂ ratio by propofol in cortical brain regions; therefore, it might be possible that propofol affects coupling of flow and metabolism in the cerebral microcirculation.
Teaching Digital Image Processing in an Application-Oriented College

With its broad application areas of exceptional social and economic value, digital image processing has gained wide popularity as an undergraduate course for students majoring in Computer Science and Technology. Also, it has stepped into many application-oriented colleges, which differ from common universities in teaching goals and characteristics of students. This paper presents some new teaching methods of Digital Image Processing in an application-oriented college. In classroom presentation, more vivid illustrations and less formula derivations are given. While in laboratory exercises, students are instructed to develop some basic image processing functions commonly used in daily digital lives. This acts as a main clue for the whole course: with the progress of classroom teaching, various image processing features are gradually added to the softwares developed by students themselves. Following these methods, students are stimulated and remarkable teaching results are achieved. Keywords-digital image processing; application-oriented; teaching method