Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust syllable segmentation and its application to syllable-centric continuous speech recognition

The focus of this paper is two-fold: (a) to develop a knowledge-based robust syllable segmentation algorithm and (b) to establish the importance of accurate segmentation in both the training and testing phases of a speech recognition system. A robust segmentation algorithm for segmenting the speech signal into syllables is first developed. This uses a non-statistical technique that is based on group delay(GD) segmentation and Vowel Onset point(VOP) detection. The transcription corresponding to the utterance is syllabified using rules. This produces an annotation for the train data. The annotated train data is then used to train a syllable-based speech recognition system. The test signal is also segmented using the proposed algorithm. This segmentation information is then incorporated into the linguistic search space to reduce both computational complexity and word error rate(WER). WER's of 4.4% and 21.2% are reported on the TIMIT and NTIMIT databases respectively.
Simultaneous wavelet estimation and deconvolution of reflection seismic signals

The problem of simultaneous wavelet estimation and deconvolution is investigated with a Bayesian approach under the assumption that the reflectivity obeys a Bernoulli-Gaussian distribution. Unknown quantities, including the seismic wavelet, the reflection sequence, and the statistical parameters of reflection sequence and noise are all treated as realizations of random variables endowed with suitable prior distributions. Instead of deterministic procedures that can be quite computationally burdensome, a simple Monte Carlo method, called Gibbs sampler, is employed to produce random samples iteratively from the joint posterior distribution of the unknowns. Modifications are made in the Gibbs sampler to overcome the ambiguity problems inherent in seismic deconvolution. Simple averages of the random samples are used to approximate the minimum mean-squared error (MMSE) estimates of the unknowns. Numerical examples are given to demonstrate the performance of the method.
Nonlinear Acoustic Echo Cancellation Using a Nonlinear Postprocessor With a Linearly Constrained Affine Projection Algorithm

This brief presents a nonlinear acoustic echo cancellation algorithm comprising a postprocessor that can model the saturation-type nonlinear distortion of a microphone circuit. To support fast adaptation to the acoustic echo environment, the linear filter is adapted using an affine projection algorithm where the reference input vectors subject to linear operation are dynamically selected to update the coefficient vector. We consider the hard-clipper and sigmoid functions for the postprocessor, and their parameters are adaptively updated using the least-mean-square algorithm. The simulation results confirm that the proposed algorithm achieves fast and stable convergence under saturation-type microphone distortion, and it can have better performance than conventional algorithms.
Getting the right design and the design right

We present a study comparing usability testing of a single interface versus three functionally equivalent but stylistically distinct designs. We found that when presented with a single design, users give significantly higher ratings and were more reluctant to criticize than when presented with the same design in a group of three. Our results imply that by presenting users with alternative design solutions, subjective ratings are less prone to inflation and give rise to more and stronger criticisms when appropriate. Contrary to our expectations, our results also suggest that usability testing by itself, even when multiple designs are presented, is not an effective vehicle for soliciting constructive suggestions about how to improve the design from end users. It is a means to identify problems, not provide solutions.
Germline Mutations and Polymorphisms in the Origins of Cancers in Women

Several female malignancies including breast, ovarian, and endometrial cancers can be characterized based on known somatic and germline mutations. Initiation and propagation of tumors reflect underlying genomic alterations such as mutations, polymorphisms, and copy number variations found in genes of multiple cellular pathways. The contributions of any single genetic variation or mutation in a population depend on its frequency and penetrance as well as tissue-specific functionality. Genome wide association studies, fluorescence in situ hybridization, comparative genomic hybridization, and candidate gene studies have enumerated genetic contributors to cancers in women. These include p53, BRCA1, BRCA2, STK11, PTEN, CHEK2, ATM, BRIP1, PALB2, FGFR2, TGFB1, MDM2, MDM4 as well as several other chromosomal loci. Based on the heterogeneity within a specific tumor type, a combination of genomic alterations defines the cancer subtype, biologic behavior, and in some cases, response to therapeutics. Consideration of tumor heterogeneity is therefore important in the critical analysis of gene associations in cancer.
Corrected model for "predicting the relative performance of CPU"

In the era of cloud computing and virtualization it is ever more important to model performance of computing systems. An algorithm for finding functions to describe relative performance using sample CPU rating system from www.spec. org was proposed by Debbie Sheetz, Lying Song and Anatoliy Rikun. A major error in the primary model equation of the algorithm, proposed by Sheetz et al. is reported here. The fundamental cause of the error and its implication is explained. The validity of the data presented in several tables were analyzed against the error in the main theory. Correct form of the equation is presented. The corrected model is applied to a new set of performance data and the results are validated by comparing some predictions with measured data.
Constructing an Indoor Floor Plan Using Crowdsourcing Based on Magnetic Fingerprinting

A large number of indoor positioning systems have recently been developed to cater for various location-based services. Indoor maps are a prerequisite of such indoor positioning systems; however, indoor maps are currently non-existent for most indoor environments. Construction of an indoor map by external experts excludes quick deployment and prevents widespread utilization of indoor localization systems. Here, we propose an algorithm for the automatic construction of an indoor floor plan, together with a magnetic fingerprint map of unmapped buildings using crowdsourced smartphone data. For floor plan construction, our system combines the use of dead reckoning technology, an observation model with geomagnetic signals, and trajectory fusion based on an affinity propagation algorithm. To obtain the indoor paths, the magnetic trajectory data obtained through crowdsourcing were first clustered using dynamic time warping similarity criteria. The trajectories were inferred from odometry tracing, and those belonging to the same cluster in the magnetic trajectory domain were then fused. Fusing these data effectively eliminates the inherent tracking errors originating from noisy sensors; as a result, we obtained highly accurate indoor paths. One advantage of our system is that no additional hardware such as a laser rangefinder or wheel encoder is required. Experimental results demonstrate that our proposed algorithm successfully constructs indoor floor plans with 0.48 m accuracy, which could benefit location-based services which lack indoor maps.
An Opportunistic Service Differentiation Routing Protocol for Cognitive Radio Networks

Cognitive Radio (CR) is a new paradigm that enable nodes to exploit unoccupied frequency spectrum for transmissions. Cognitive Radio Networks (CRNs) have been proposed to enable wireless mesh networks to communicate via dynamic channels. Many existing research consider routing in static CRNs with relatively stable communication channel where the duration of the availability of the communication channel is much longer than the communication time. However, there is limited routing related research in dynamic CRNs where the average available duration of the communication channel can be much shorter than the communication time. To address this, we propose a cross-layer cognitive routing protocol, the Opportunistic Service Differentiation Routing Protocol (OSDRP) for the dynamic CRNs. OSDRP discovers the minimum delay - maximum stability route in CRNs by considering the availability of spectrum opportunity in addition to switching delay and queuing delay across primary user networks. In addition, service differentiation is achieved through a combination of transmit power control and opportunistic routing. Simulation results demonstrate that OSDRP can achieve much better performance in terms of lower delay compared to other existing routing protocols in various scenarios.
Simple nomograms to calculate sample size in diagnostic studies

Objectives: To produce an easily understood and accessible tool for use by researchers in diagnostic studies. Diagnostic studies should have sample size calculations performed, but in practice, they are performed infrequently. This may be due to a reluctance on the part of researchers to use mathematical formulae. Methods: Using a spreadsheet, we derived nomograms for calculating the number of patients required to determine the precision of a test’s sensitivity or specificity. Results: The nomograms could be easily used to determine the sensitivity and specificity of a test. Conclusions: In addition to being easy to use, the nomogram allows deduction of a missing parameter (number of patients, confidence intervals, prevalence, or sensitivity/specificity) if the other three are known. The nomogram can also be used retrospectively by the reader of published research as a rough estimating tool for sample size calculations.
The Effects of Epinephrine on Lidocaine Spinal Anesthesia: A Cross-Over Study

The efficacy of epinephrine for prolonging the duration of lidocaine spinal anesthesia remains controversial.Seven volunteers were randomized in a double-blind manner to receive two 50-mg lidocaine (in dextrose 7.5%) spinal anesthetics with and without epinephrine (0.2 mg). Sensory analgesia was assessed with transcutaneous electrical stimulation (TES) equivalent to surgical incision and compared to standard pinprick dermatomal levels. Motor block was assessed with surface electromyography (EMG) and isometric force dynamometry. Intravenous fluids were administered by a standardized regimen, and time until ability to void was determined. Addition of epinephrine significantly prolonged duration of surgical anesthesia in the lumbar and sacral dermatomes by an average of 16-29 min (P = 0.03), but not in thoracic dermatomes. Although there was a trend toward prolongation of motor block with addition of epinephrine, this did not reach statistical significance. Epinephrine significantly prolonged duration until ability to void from 153 +/- 27 to 234 +/- 50 min (P = 0.0001). Thus, addition of epinephrine to lidocaine may be indicated to prolong duration of anesthesia for lower body operations. However, delayed recovery of ability to void may also prolong time until discharge after ambulatory surgery. (Anesth Analg 1995;80:735-9)
Visualisation and Quantitative Analysis of the Rodent Malaria Liver Stage by Real Time Imaging

The quantitative analysis of Plasmodium development in the liver in laboratory animals in cultured cells is hampered by low parasite infection rates and the complicated methods required to monitor intracellular development. As a consequence, this important phase of the parasite's life cycle has been poorly studied compared to blood stages, for example in screening anti-malarial drugs. Here we report the use of a transgenic P. berghei parasite, PbGFP-Luccon, expressing the bioluminescent reporter protein luciferase to visualize and quantify parasite development in liver cells both in culture and in live mice using real-time luminescence imaging. The reporter-parasite based quantification in cultured hepatocytes by real-time imaging or using a microplate reader correlates very well with established quantitative RT-PCR methods. For the first time the liver stage of Plasmodium is visualized in whole bodies of live mice and we were able to discriminate as few as 1–5 infected hepatocytes per liver in mice using 2D-imaging and to identify individual infected hepatocytes by 3D-imaging. The analysis of liver infections by whole body imaging shows a good correlation with quantitative RT-PCR analysis of extracted livers. The luminescence-based analysis of the effects of various drugs on in vitro hepatocyte infection shows that this method can effectively be used for in vitro screening of compounds targeting Plasmodium liver stages. Furthermore, by analysing the effect of primaquine and tafenoquine in vivo we demonstrate the applicability of real time imaging to assess parasite drug sensitivity in the liver. The simplicity and speed of quantitative analysis of liver-stage development by real-time imaging compared to the PCR methodologies, as well as the possibility to analyse liver development in live mice without surgery, opens up new possibilities for research on Plasmodium liver infections and for validating the effect of drugs and vaccines on the liver stage of Plasmodium.
Pupillary Response to Auditory Stimuli in Depressive State

Background: Previous reports indicate that depressed individuals have worse memory for negative information than other types of information. They tend to ruminate upon negative information with high sensitivity. Depressive subjects also tend to display greater sustained pupil dilation in response to negative information. Methods: We evaluated pupil diameter with charge coupled device (CCD) infrared camera while scoring depressive scale in 41 healthy elderly subjects. Six kinds of sounds were used as auditory stimuli with characters of startle-eliciting. The measurements of pupil were made in a rested state and done twice with pre- and post-auditory and light stimulations. The indexes of pupil responses were dilations for auditory stimulations and contractions for light stimulations. Results: The pupil diameter stimulated by emotional sound “glasses broken on the floor” was solely positive correlated with depressive score. The pupil contractions for light stimuli were weakly negative correlated with depressive score. Conclusion: Some emotional sounds with negative information could cause pupil dilation in depressive participants. This sound “glasses broken on the floor” would be a biological marker assistant to depressive diagnosis. J Neurol Res. 2016;6(1):8-11 doi: http://dx.doi. org/10.14740/jnr364w
Learning Recognition of Ambiguous Proper Names in Hindi

An ambiguous proper name is a name which is also a valid dictionary word with a meaning of its own when used in the text. For example in English, the word 'bush' in 'Mr. Bush' is a proper name whereas in 'a dense bush' it is a lexical entity. Almost all proper names in Hindi have a meaning and find an entry in the dictionary. Recognition of named entities finds wide application in MT, IR and several other NLP tasks. While there have been a number of investigations on Hindi NER in general, no work has been reported exclusively on ambiguous proper nouns which are more difficult to deal with. This paper presents a methodology for recognizing ambiguous proper names in Hindi using hybridization of a rule-base and statistical CRF based machine learning using morphological and context features. The methodology yields a F-score of 71.6%.
Assessing Reading Metacognitive Strategy Awareness of Young Children: The Reading Metacognitive Strategy Picture Protocol

The Reading Metacognitive Strategy Picture Protocol (RMSPP) is an informal, authentic, naturalistic diagnostic tool for classroom teachers and clinicians to use with children as young as kindergarten to assess students’ knowledge and awareness of metacognitive strategies. This article describes the RMSPP and how it was implemented in one informal project with 139 kindergarten – third graders, illustrating the usefulness of this picture protocol response technique with young children.
Implementation Issues in Adding Force Feedback to the X Desktop

This paper describes implementation issues encountered in a project to add force feedback to the X Window System desktop in an attempt to add true “feel” to the window system’s “look and feel”. Haptic additions to the interface include adding ridges around icons and menu items to aid interaction, alignment guides for moving windows, and a number of other enhancements to window manipulation. The issues discussed here include the precise descriptions of the forces computed, as well as lower-level issues such as how to achieve those forces with GHOST.
Teachers' and administrators' perceptions of the antecedents of school dropout among English language learners at selected Texas schools

Teachers’ and Administrators’ Perceptions of the Antecedents of School Dropout among English Language Learners at Selected Texas Schools. (May 2010) Jonathan Jacob Doll, B.A., Syracuse University; M.Ed., University of Alaska Co-Chairs of Advisory Committee: Dr. Zohreh Eslami Dr. Lynne Walters This study examined teachers’ and administrators’ perceptions of English language learner dropout antecedents at 95 secondary schools in Texas targeting two goals. First, perceptions of ninth-grade dropout were assessed to identify push, pull, or falling-out factors of dropout. Push factors include school-related consequences like attendance or disciplinary infractions. Pull factors include out-of-school enticements like jobs and family. Finally, fall factors refer to student disconnection with school leading to dropout. Second, four categories of dropout factors (student demographics, student experiences, school factors, and instructional practices) were tested to see which had the highest perceived rank. The first research question assessed ninth-grade academic engagement and dropout antecedents among ELL dropouts. Engagement factors including persistence and previous preparation for high school were perceived as highly important qualities while discipline problems were a major challenge. Falling-out factors were perceived at the highest rank in causing ninth-grade ELL dropout. Among falling-out factors, lack of
The time assignment system of ASTRO-H

ASTRO-H is an X-ray astronomy satellite to be launched in 2014. The data acquisition system of this mission is realized with a standard network protocol, SpaceWire. Although the protocol itself is well designed, a new concept to grantee the quality of service will be installed to the ASTRO-H data acquisition system. Therefore, the verification of the design of the concept is essential in the initial phase of the development. The time assignment function is one of the important issues for the SpaceWire development. The accuracy of the absolute time of about 30 µs is required from science goals. The key point of the time assignment with SpaceWire network in the ASTRO-H system is how accurately sharing the time information. In this paper, our design of the time distribution and assignment system for ASTRO-H is shown. The results of our measurements of timing accuracy are also presented to show that the design will fulfill the goal of absolute timing accuracy.
Making Snowflakes Like Stocks: Stretching, Bending and Positioning to Make Financial Market Analogies Work in Online Advertising

Analogies to financial markets have proven powerful in establishing novel or potentially controversial business concepts, even in contexts that deviate significantly from financial markets. This phenomenon challenges theory that suggests analogies work best when elements from a source and target domain map closely to each other. To develop a theory that explains how organizations make initially imperfect analogies “work,” we use a case study of online advertising exchanges, a market-inspired model for buying and selling online advertising space. We find that as organizations stretch an initially misfitting exchange analogy from financial markets to online advertising, they iteratively bend their activities in superficial, structural, and generative ways to match the analogy and position themselves for advantage in the new space being created. Whereas prior studies emphasize shared cognition about familiar domains as the reason why analogies work, our study offers a dynamic account in which stretching, bending, and positioning combine to not only establish the financial market analogy but also subtly change the understanding of markets.
On the distance to the giant component along a straight line in a two-dimensional percolation model

The supercritical regime of a percolation model refers to the range of probabilities (discrete) or densities (continuous) above a critical value for which there exists a unique unbounded cluster almost surely. In this paper, we provide an upper bound to the linear distance from the origin to this giant connected component for both the discrete and the continuous (Boolean) model in two-dimensions. By modeling a dense wireless sensor network with a supercritical Boolean model, our result bounds the distance traveled by a target moving in a straight line before it is detected by a node who can relay the alert through a multihop path to the sink. This result incorporates a solidified definition of detection requiring that the intrusion alert successfully reach the central authority.
Ant Colony Optimization and hypergraph covering problems

Ant Colony Optimization (ACO) is a very popular metaheuristic for solving computationally hard combinatorial optimization problems. Runtime analysis of ACO with respect to various pseudo-boolean functions and different graph based combinatorial optimization problems has been taken up in recent years. In this paper, we investigate the runtime behavior of an MMAS*(Max-Min Ant System) ACO algorithm on some well known hypergraph covering problems that are NP-Hard. In particular, we have addressed the Minimum Edge Cover problem, the Minimum Vertex Cover problem and the Maximum Weak-Independent Set problem. The influence of pheromone values and heuristic information on the running time is analysed. The results indicate that the heuristic information has greater impact towards improving the expected optimization time as compared to pheromone values. For certain instances of hypergraphs, we show that the MMAS* algorithm gives a constant order expected optimization time when the dominance of heuristic information is suitably increased.
Identification of many microRNAs that copurify with polyribosomes in mammalian neurons

Localized translation in mammalian dendrites may play a role in synaptic plasticity and contribute to the molecular basis for learning and memory. The regulatory mechanisms that control localized translation in neurons are not well understood. We propose a role for microRNAs (miRNAs), a class of noncoding RNAs, as mediators of neuronal translational regulation. We have identified 86 miRNAs expressed in mammalian neurons, of which 40 have not previously been reported. A subset of these miRNAs exhibits temporally regulated expression in cortical cultures. Moreover, all of the miRNAs that were tested cofractionate with polyribosomes, the sites of active translation. These findings indicate that a large, diverse population of miRNAs may function to regulate translation in mammalian neurons.