Miracle-dz/UniFAR-FTUs huggingface dataset:
Maximal rank likelihood as an optimization function for speech recognition

Researchhas shownthatrankstatistics derivedfromcontext-dependent state likelihood can provide robust speech recognition. In previous work, empirical distributions were used to characterize the rank statistics. We present parametric models of the state rank and the rank likelihood, and then based on them, present a new objective function, Maximal Rank Likelihood (MRL), for estimating parameters in a HMM based speech recognition system. The objective function optimizes the average logarithm of the rank likelihood of training/adaptation data. It is a discriminative based estimation process and hence makes the training criterion close to the decoding criterion. Three applications of MRL are discussed. First one is a Linear Discriminative Projection, which optimizes the objective function using all training data and projects feature vectors into a discriminative space with a reduced dimension. The second and third applications are a feature space transformation and a model space transformation, respectively, for adaptation. The transformations are optimized to maximize the rank likelihood of the adaptation data. The experimental results show that the MRL adaptation algorithms outperform the MLLR adaptation.
Software Development Practices, Software Complexity, and Software Maintenance Performance: a Field Study

Software maintenance claims a large proportion of organizational resources. It is thought that many maintenance problems derive from inadequate software design and development practices. Poor design choices can result in complex software that is costly to support and difficult to change. However, it is difficult to assess the actual maintenance performance effects of software development practices because their impact is realized over the software life cycle. To estimate the impact of development activities in a more practical time frame, this research develops a two-stage model in which software complexity is a key intermediate variable that links design and development decisions to their downstream effects on software maintenance. The research analyzes data collected from a national mass merchandising retailer on 29 software enhancement projects and 23 software applications in a large IBM COBOL environment. Results indicate that the use of a code generator in development is associated with increased software complexity and software enhancement project effort. The use of packaged software is associated with decreased software complexity and software enhancement effort. These results suggest an important link between software development practices and maintenance performance.
On the reliability of the fractal dimension measure of solar magnetic features and on its variation with solar activity

Context. Several studies have investigated the fractal and multifractal nature of magnetic features in the solar photosphere and its variation with the solar magnetic activity cycle. Aims. Here we extend those studies by examining the fractal geometry of bright magnetic features at higher atmospheric levels, specifically in the solar chromosphere. We analyze structures identified in CaIIK images obtained with the Precision Solar Photometric Telescopes (PSPTs) at Osservatorio Astronomico di Roma (OAR) and Mauna Loa Solar Observatory (MLSO). Methods. Fractal dimension estimates depend on the estimator employed, the quality of the images, and the structure identification techniques used. We examine both real and simulated data and employ two different perimeter-area estimators in order to understand the sensitivity of the deduced fractal properties to pixelization and image quality. Results. The fractal dimension of bright "magnetic" features in CaIIK images ranges between values of 1.2 and 1.7 for small and large structures respectively. This size dependency largely reflects the importance of image pixelization in the measurement of small objects. The fractal dimension of chromospheric features does not show any clear systematic variation with time over the period examined, the descending phase of solar cycle 23. Conclusions. These conclusions, and the analysis of both real and synthetic images on which they are based, are important in the interpretation of previously reported results.
A WCDMA Multiband Power Amplifier Module With Si-CMOS/GaAs-HBT Hybrid Power-Stage Configuration

This paper describes a newly developed Si/GaAs hybrid multiband power amplifier module (MB-PAM) that supports major quad wideband code division multiple access (WCDMA) bands (Bands 5, 8, 2, and 1) for handset applications. With four dies (two GaAs-HBT dies, one GaAs-HEMT die, and one CMOS die) and several surface-mount devices, the hybrid MB-PAM accommodates two amplifier chains and two single-pole double-throw HEMT band-select switches on a 5 mm × 5.5 mm laminate, covering 824-915 and 1850-1980 MHz. Each amplifier chain has two switchable signal paths corresponding to dual (high and low) power modes [high-power mode (HPM) and low-power mode (LPM)] for saving battery current in practical handset use. One of the main features of this MB-PAM is the integration of driver stages, RF switches, and their bias control circuits on the CMOS die for pursuing cost reduction. Only the two output power stages are fabricated in a GaA-HBT process. Measurements conducted under the condition of a 3.4-V supply voltage and a WCDMA (Third Generation Partnership Project Release 99) modulated signal are as follows. Owing to optimized linear design and broadband output matching design, the hybrid MB-PAM achieves a power-added efficiency (PAE) as high as 39%-40% at 28 dBm of output power (Pout) over 824-915 MHz in the HPM while maintaining a ±5-MHz-offset adjacent channel leakage power ratio (ACLR1) to less than -39 dBc. In the LPM, PAE of 15% at a Pout of 17 dBm is obtained while ACLR1 of less than -40 dBc is maintained. For 1850-1980 MHz, the MB-PAM delivers 35% of PAE with ACLR1 of less than -40 dBc at 28 dBm of Pout in the HPM and 15% PAE at 17.5 dBm of Pout in the LPM.
Directed remembering: Subliminal cues alter nonconscious memory strategies

Much research on memory function has focused on changes in recognition performance brought about by differences in the processes engaged during encoding. In most of this work, participants either receive explicit instructions to remember particular items or they perform orienting (i.e., encoding) tasks that support different levels of memory performance. In daily life, however, the retention or dismissal of information often occurs without conscious intent, thereby suggesting an alternative, nonconscious route through which purposive remembering and forgetting can occur. Based on this line of reasoning, we speculated that recognition performance in a standard item-based forgetting paradigm may be moderated by subliminal cues that trigger the automatic activation of different mnemonic strategies. We report the results of two experiments that supported this prediction. In each experiment, the basic item-based forgetting effect was replicated, but via the subliminal presentation of “remember” and “forget” cues. In addition, cue-dependent differences in memory performance were traced to the operation of a covert rehearsal mechanism during encoding. We consider the implications of these findings for the non-conscious operation of memory processes in everyday life.
A New Algorithm for Removal of High-Density Salt and Pepper Noises

To improve the performance of high-density salt and pepper noise denoising, a new detail preserving median filter algorithm is proposed in this paper. The method replaces only corrupted pixels by either the trimmed median or the average of previously processed neighborhood pixels, while uncorrupted pixels remain unchanged. Experimental results clearly show that the proposed algorithm outperforms many of the existing methods in terms of visual quality and quantitative measures. The advantage of the proposed method is that it works well for high-density salt & pepper noise even up to a noise density of 90%.
Exploring, exposing, and exploiting emails to include human factors in software engineering

Researchers mine software repositories to support software maintenance and evolution. The analysis of the structured data, mainly source code and changes, has several benefits and offers precise results. This data, however, leaves communication in the background, and does not permit a deep investigation of the human factor, which is crucial in software engineering. Software repositories also archive documents, such as emails or comments, that are used to exchange knowledge among people - we call it "people-centric information. " By covering this data, we include the human factor in our analysis, yet its unstructured nature makes it currently sub-exploited. Our work, by focusing on email communication and by implementing the necessary tools, investigates methods for exploring, exposing, and exploiting unstructured data. We believe it is possible to close the gap between development and communication, extract opinions, habits, and views of developers, and link implementation to its rationale; we see in a future where software analysis and development is routinely augmented with people-centric information.
Residential Mobility, Housing Wealth and the Labour Market

UK commentators have noted for some time that the structure of the UK housing market may be detrimental to labour market flexibility. The early 1990s experience of negative housing equity which affected over 20% of home buyers may have “locked” home owners into property, reducing mobility and worsening further the flexibility of the labour market. The present paper uses UK household longitudinal data (BHPS) for the early 1990s, and estimates single and competing risk discrete time duration models of residence duration to investigate these issues. Strong evidence for the negative impact on mobility of negative equity is found, along with results that suggest that the home-owners do not tend to move in response to changing labour market conditions. Negative equity in the early 1990s therefore exacerbated housing market related rigidities in the job matching process.
Re-reading, Re-writing, and Re-imagining Texts: Critical Literacy in a Kindergarten Classroom

This qualitative action research study focuses on the integration of critical literacy practices in a kindergarten classroom. Critical literacy recognizes that no texts are neutral, and that authors position their readers in particular ways. Thus critical literacy practices are those concerned with positioning readers to inquire into issues of language and power, and to disrupt, critique, and challenge texts. In this study, critical literacy was brought to life through a curriculum of rereading and revisiting texts over time. The study took place in the researcher’s kindergarten classroom, and follows students’ discussion, written responses, and dramatizations around texts read aloud in the classroom focusing on themes of power, justice, and equity. Data was collected across the school year, including fifty lessons. Data analysis such as coding, discourse analysis, and multimodal analysis was conducted during the year and informed instructional decisions. Data analysis also occurred after the year had ended and focused on identifying the different ways that students engaged in critical inquiry into the texts through rereading, rewriting, and reimagining scenes in the texts, as well as how the teacher was able to support students with engaging in critical literacy in the read-aloud setting. In particular, analysis of the read-aloud lessons documented ways that students were able to disrupt stereotypes, consider multiple perspectives, engage with sociopolitical issues, and take social action. Critical literacy is shown as a tool for accelerating young students’ literacy development, and students’ reading and writing skills are documented as they develop through rereading and responding to texts across the study. This study not only offers a sustained look at how young students can be scaffolded over time to engage in critical literacy practices, but also expands the notion of what types of literacy practices young students RE-READING, RE-WRITING, AND RE-IMAGINING TEXTS vii are capable of engaging in. Using the tools of process drama as a way to revisit and rethink read-alouds provides early childhood teachers a way to simultaneously engage their young students in rigorous critical thinking around texts that is also active, social, playful, and imaginative.
Predictors of Dating Violence Victimization in Out-of-school Female Adolescents

The purpose of this study was to identify the factors that explain dating violence victimization in out-of-school female adolescents. The data were collected from 171 out-of-school female students in the youth detention center, runaway youth shelter, protective disposition no.6 facilities in Korea. Child physical abuse, delinquency, dating relationship control, dating violence victimization were assessed using the structured questionnaires. The predictors of dating violence victimization were analyzed using the Binomial logistic regression. Child physical abuse (AOR=.1.05, p=.036), delinquency (AOR=.1.23, p=.016.), dating relationship control (AOR=.92, p=.012) and drinking frequency (AOR=.27, p=.038) were the significant predictors on in out-of-school female adolescents. The result will provide preliminary data and strategic to screen for dating violence victimization in out-of-school female adolescents. An adjusted education program should be developed in order to prevent dating violence victimization in out-of-school female adolescents.
Tutor learning using linear constraints in approximate dynamic programming

In adaptive control, agents interacting with Markov Decision Processes typically face two types of setups. In the first setup, the environment's model is known and dynamic programming and related methods are used to obtain the optimal control. In the second setup, the environment's model is unknown and reinforcement learning methods are used. In this work we investigate a new setup that is a mix of the two mentioned setups: only part of the environment's model is known and additional information regarding the environment is provided by a tutor. We formalize this problem using linear function approximation in order to overcome the “curse of dimensionality” phenomenon. In addition, using the Envelope Theorem, we show how one can tune the approximation basis in order to get a locally optimal results. Finally, the suggested methods are demonstrated in simulations.
Seizures Are Regulated by Ubiquitin-specific Peptidase 9 X-linked (USP9X), a De-Ubiquitinase

Epilepsy is a common disabling disease with complex, multifactorial genetic and environmental etiology. The small fraction of epilepsies subject to Mendelian inheritance offers key insight into epilepsy disease mechanisms; and pathologies brought on by mutations in a single gene can point the way to generalizable therapeutic strategies. Mutations in the PRICKLE genes can cause seizures in humans, zebrafish, mice, and flies, suggesting the seizure-suppression pathway is evolutionarily conserved. This pathway has never been targeted for novel anti-seizure treatments. Here, the mammalian PRICKLE-interactome was defined, identifying prickle-interacting proteins that localize to synapses and a novel interacting partner, USP9X, a substrate-specific de-ubiquitinase. PRICKLE and USP9X interact through their carboxy-termini; and USP9X de-ubiquitinates PRICKLE, protecting it from proteasomal degradation. In forebrain neurons of mice, USP9X deficiency reduced levels of Prickle2 protein. Genetic analysis suggests the same pathway regulates Prickle-mediated seizures. The seizure phenotype was suppressed in prickle mutant flies by the small-molecule USP9X inhibitor, Degrasyn/WP1130, or by reducing the dose of fat facets a USP9X orthologue. USP9X mutations were identified by resequencing a cohort of patients with epileptic encephalopathy, one patient harbored a de novo missense mutation and another a novel coding mutation. Both USP9X variants were outside the PRICKLE-interacting domain. These findings demonstrate that USP9X inhibition can suppress prickle-mediated seizure activity, and that USP9X variants may predispose to seizures. These studies point to a new target for anti-seizure therapy and illustrate the translational power of studying diseases in species across the evolutionary spectrum.
Comparative performances of stochastic competitive evolutionary neural tree (SCENT) with neural classifiers

A stochastic competitive evolutionary neural tree (SCENT) is described and evaluated against the best neural classifiers with equivalent functionality, using a collection of data sets chosen to provide a variety of clustering scenarios. SCENT is firstly shown to produce flat classifications at least as well as the other two neural classifiers used. Moreover its variability in performance over the data sets is shown to be small. In addition SCENT also produces a tree that can show any hierarchical structure contained in the data. For two real world data sets the tree captures hierarchical features of the data.
Dual material gate-all-around Fully Depleted SOI MOSFET with Strained Si / Ge Channel

After a lot of efforts to scale down the devices, now the scaling limits of device have reached i.e. it’s not possible to scale down the CMOS further. For further scaling of device we need to change the materials used for the gate and channel. In this paper different structures suggested by different authors are covered along with their benefits and limitations. A structure based on the Fully Depleted SOI Gate All around (FD SOI GAA) MOSFET with strained Si Channel has been suggested to overcome the scaling limits along with the QME consideration in modeling. Keywords-CMOS, FD, Gate-All-Around, Quantum Mechanical Effect, Scaling Effects, SOI, Strained Si.
Observed vertical distribution of tropospheric ozone during the Asian summertime monsoon

[1] We characterize the horizontal and vertical distribution of tropospheric ozone measured by the Tropospheric Emission Spectrometer (TES) over North Africa, the Middle East, and Asia. Studies have shown that the summertime circulation associated with the Asian monsoon significantly influences the spatial distribution of ozone and its precursors. However, there have been limited observations of the distribution of tropospheric ozone over this region. Over the Middle East, TES observations reveal abundances of ozone between 60 and 100 ppbv, with amounts over 80 ppbv typically occurring between 300 and 450 hPa, whereas over India, enhanced ozone abundances are near 300 hPa. Over central Asia, observed ozone amounts are 150–200 ppbv at altitudes near 300 hPa. These enhanced ozone abundances are observed in June and July, corresponding to the onset of the Asian monsoon, and begin to dissipate in August. Intercomparison of the TES data with ozone climatologies derived from the Measurements of Ozone and Water Vapor by in-Service Airbus Aircraft program show that the TES ozone is biased high by about 15% between 300 and 750 hPa, consistent with prior validation studies. Comparison of the assimilation of TES data into the GEOS-Chem model with assimilation of data from the Microwave Limb Sounder (MLS) and the Ozone Monitoring Instrument (OMI) into the Goddard Earth Observing System (GEOS-4) model shows consistency in the distribution of ozone. For example, at 7–8 km across North Africa, the Middle East, and Asia the bias between GEOS-Chem and the assimilated OMI and MLS fields was reduced from 6.8 to 1.4 ppbv following assimilation of the TES data.
An Iterative Meta-Lifecycle for Software Development, Evolution and Maintenance

Modern organizations are significantly affected by the breakthroughs in the field of information technology. In particular, software systems play a critical role in supporting organizations operational and decisional processes. Given that the costs of development and maintenance of software constitute the largest part of the computerization cost, the survival of organizations depends heavily on the effectiveness of the software development process. However, software engineering is in crisis. This crisis, known as the ldquosoftware crisis", is characterized by economic and social ramifications and exacerbated by the complexity and uncertainty inherent in both software engineering and organizational processes supported by software. Many researchers believe that prototyping can reduce uncertainty and provide knowledge related to the future dynamic states of software systems before their construction. Nevertheless, few methods incorporating prototyping as a tool for reducing uncertainty have been proposed to date. In this paper, we propose a framework for an iterative development process which integrates software prototyping. This framework permits correcting some weaknesses of existing methods by emphasizing the multidimensional nature of the software and the multiplicity of actors involved in software development, maintenance, and use.
Influence Maximization in Social Networks: Towards an Optimal Algorithmic Solution

Diffusion is a fundamental graph process, underpinning such phenomena as epidemic disease contagion and the spread of innovation by word-of-mouth. We address the algorithmic problem of finding a set of k initial seed nodes in a network so that the expected size of the resulting cascade is maximized, under the standard independent cascade model of network diffusion. The promise of such an algorithm lies in applications to viral marketing. However, runtime is of critical importance in this endeavor due to the massive size and volatility of the relevant networks. Our main result is an algorithm for the influence maximization problem that obtains the nearoptimal approximation factor of (1 − 1 e − ǫ), for any ǫ > 0, in time O((m + n)ǫ logn) where n and m are the number of vertices and edges in the network. The runtime of our algorithm is independent of the number of seeds k and improves upon the previously best-known algorithms which run in time Ω(mnk ·POLY(ǫ)). Importantly, our algorithm is essentially runtime-optimal (up to a logarithmic factor) as we establish a lower bound of Ω(m+ n) on the runtime required to obtain a constant approximation. We then show how to modify our algorithm to allow a provable tradeoff between solution quality and runtime. We obtain an Θ( 1 β )-approximation in time O(n · a(G) log(n)/β) for any β > 1, where a(G) denotes the arboricity of the diffusion network G. In particular, for graphs with bounded arboricity (as is the case for many models of network formation and empirically observed social networks) our algorithm is nearly runtime-optimal (up to logarithmic factors) for any fixed seed size k. Our approach is based on a novel preprocessing scheme that generates a sparse hypergraph representation of the underlying network via sampling. We show that this representation makes it possible to efficiently estimate marginal influence in the original diffusion process with very few samples, and that the quality of this estimation degrades gracefully with reduced preprocessing time. Microsoft Research New England. Email: borgs@microsoft.com Department of Computer and Information Science, University of Pennsylvania. Email: brautbar@cis.upenn. edu Microsoft Research New England. Email: jchayes@microsoft.com Microsoft Research New England. Email: brlucier@microsoft.com
Anterior cruciate ligament injury in indoor ball games

Three videorecorded incidents of knee injuries inflicted during indoor ball games are reported. Injuries and especially anterior cruciate ligament ruptures seemed to be triggered in varus loaded knees by femural external rotation, or in valgus loaded knees by femural internal rotation with the pivot shifted to the lateral femurotibial compartment. The observations suggest that it may be to the players’ advantage to be trained in not letting their knees sag medially or laterally during side‐stepping or sudden changes in speed.