Miracle-dz/UniFAR-FTUs huggingface dataset:
HMM-based estimation of unreliable spectral components for noise robust speech recognition

This paper presents a novel approach for reconstructing unreliable spectral components, which utilizes HMM-based missing feature algorithms, and applies them to noise robust speech recognition. The proposed technique uses the forwardbackward algorithm to estimate corrupt spectrographic data based on nearby reliable features, noisy observations, and on an underlying statistical model. The estimation process can be applied based on intra-channel information, intra-feature information, or a combination of both. The overall system is shown to provide vast improvements for the Consonant Challenge Database [1], for both MFCCs and PLP features, when using an oracle mask. Moreover, through downsampling of statistical models [2], the required complexity of the system is greatly reduced with negligible effects on results.
A unified formulation of behavioral semantics for SysML models

In order to cope with the complexity of today's system designs, higher levels of abstraction are considered. Modeling languages such as SysML provide adequate description means for an abstract specification of the structure and the behavior of a system to be implemented. Due to its sufficient degree of formality, SysML additionally allows for performing several automated test and verification tasks. For these tasks, however, a formal encoding of the behavioral model semantics is required; this is typically achieved by generating initial state conditions as well as the transition relation from the model. Since SysML provides a multitude of alternative or complementary notations, this poses a significant challenge to the development of corresponding tool support. In this paper, we therefore propose an alternative approach to the generation of transition relations: In a first step, a model-to-model transformation is applied which unifies the behavioral descriptions into one single notation, namely operations allocated in blocks and specified by pre- and post-conditions. Afterwards, only pre- and post-conditions as well as some auxiliary constraints for fixing semantic variation points need to be considered when generating the transition relation. The approach presented here has been evaluated in the development of industrial tools supporting bounded model checking and model-based test generation.
A model for spectra-based software diagnosis

This article presents an improved approach to assist diagnosis of failures in software (fault localisation) by ranking program statements or blocks in accordance with to how likely they are to be buggy. We present a very simple single-bug program to model the problem. By examining different possible execution paths through this model program over a number of test cases, the effectiveness of different proposed spectral ranking methods can be evaluated in idealised conditions. The results are remarkably consistent to those arrived at empirically using the Siemens test suite and Space benchmarks. The model also helps identify groups of metrics that are equivalent for ranking. Due to the simplicity of the model, an optimal ranking method can be devised. This new method out-performs previously proposed methods for the model program, the Siemens test suite and Space. It also helps provide insight into other ranking methods.
Hypo‐osmolar sucrose oral rehydration solutions in acute diarrhoea: a pilot study

Based on studies showing improved absorption of hypo‐osmolar oral rehydration solutions (ORS) with reduced glucose and sodium concentration, a hypo‐osmolar ORS with sucrose replacing glucose (sodium 60, potassium 15, chloride 60, citrate 5, sucrose 58mmoll−1, calculated osmolality 198mOsmkg−1) was compared with mildly hyperosmolar glucose ORS (WHO) in 46 children aged 6–30 months with acute diarrhoea and dehydration. In the hypo‐osmolar sucrose ORS group (n = 18) faecal output was less by 30% during the initial 24 and 48 h compared with controls, suggesting better absorption. Sucrose may be a suitable alternative to glucose in an absorption‐efficient hypo‐osmolar ORS.
Throughput-optimal random access with order-optimal delay

In this paper, we consider CSMA policies for scheduling packet transmissions in multihop wireless networks with one-hop traffic. The main contribution of the paper is to propose a novel CSMA policy, called Unlocking CSMA (U-CSMA), that enables to obtain both high throughput and low packet delays in large wireless networks. More precisely, we show that for torus interference graph topologies with one-hop traffic, U-CSMA is throughput optimal and achieves order-optimal delay. For one-hop traffic, the delay performance is defined to be order-optimal if the delay stays bounded as the network-size increases. Simulations that we conducted suggest that (a) U-CSMA is throughput-optimal and achieves order-optimal delay for general geometric interference graphs and (b) that U-CSMA can be combined with congestion control algorithms to maximize the network-wide utility and obtain order-optimal delay. To the best of our knowledge, this is the first time that a simple distributed scheduling policy has been proposed that is both throughput/utility optimal and achieves order-optimal delay.
Incorporating soft computing techniques into a probabilistic intrusion detection system

There are a lot of industrial applications that can be solved competitively by hard computing, while still requiring the tolerance for imprecision and uncertainty that can be exploited by soft computing. This paper presents a novel intrusion detection system (IDS) that models normal behaviors with hidden Markov models (HMM) and attempts to detect intrusions by noting significant deviations from the models. Among several soft computing techniques neural network and fuzzy logic are incorporated into the system to achieve robustness and flexibility. The self-organizing map (SOM) determines the optimal measures of audit data and reduces them into appropriate size for efficient modeling by HMM. Based on several models with different measures, fuzzy logic makes the final decision of whether current behavior is abnormal or not. Experimental results with some real audit data show that the proposed fusion produces a viable intrusion detection system. Fuzzy rules that utilize the models based on the measures of system call, file access, and the combination of them produce more reliable performance.
Payment Instrument Characteristics: A Repertory Grid Analysis

Over the last decade, we have witnessed payment innovations that fundamentally have changed the ways we pay. Payment innovations, such as mobile payments and on-line banking, include characteristics or features that are essential to understand if we want to know how and why payers choose among payment innovations. Using the Repertory Grid technique to explore 15 payers’ perception of six payment instruments, including coins, banknotes, debit cards, credit cards, mobile payments, and on-line banking, we identify 16 payment characteristics. The characteristics aggregate seventy-six unique features. Many of the characteristics and one of the categories are completely novel and unaccounted for in previous works.
Large mesh simplification using processing sequences

In this paper we show how out-of-core mesh processing techniques can be adapted to perform their computations based on the new processing sequence paradigm (Isenburg, et al., 2003), using mesh simplification as an example. We believe that this processing concept will also prove useful for other tasks, such a parameterization, remeshing, or smoothing, for which currently only in-core solutions exist. A processing sequence represents a mesh as a particular interleaved ordering of indexed triangles and vertices. This representation allows streaming very large meshes through main memory while maintaining information about the visitation status of edges and vertices. At any time, only a small portion of the mesh is kept in-core, with the bulk of the mesh data residing on disk. Mesh access is restricted to a fixed traversal order, but full connectivity and geometry information is available for the active elements of the traversal. This provides seamless and highly efficient out-of-core access to very large meshes for algorithms that can adapt their computations to this fixed ordering. The two abstractions that are naturally supported by this representation are boundary-based and buffer-based processing. We illustrate both abstractions by adapting two different simplification methods to perform their computation using a prototype of our mesh processing sequence API. Both algorithms benefit from using processing sequences in terms of improved quality, more efficient execution, and smaller memory footprints.
Authentication Analysis of the 802.11i Protocol

—IEEE has designed 802.11i protocol to address the security issues in wireless local area networks. Formal analysis is important to ensure that the protocols work properly without having to resort to tedious testing and debugging which can only show the presence of errors, never their absence. In this paper, we present the formal veriﬁcation of an abstract protocol model of 802.11i. We translate the 802.11i protocol into the Strand Space Model and then prove the authentication property of the resulting model using the Strand Space formalism. The intruder in our model is imbued with powerful capabilities and repercussions to possible attacks are evaluated. Our analysis proves that the authentication of 802.11i is not compromised in the presented model. We further demonstrate how changes in our model will yield a successful man-in-the-middle attack.
Human Mobility Modelling Based on Dense Transit Areas Detection with Opportunistic Sensing

With the advent of smartphones, opportunistic mobile crowdsensing has become an instrumental approach to perceive large-scale urban dynamics. In this context, the present work presents a novel approach based on such a sensing paradigm to automatically identify and monitor the areas of a city comprising most of the human transit. Unlike previous approaches, the system performs such detection in real time at the same time the opportunistic sensing is carried out. Furthermore, a novel multilayered grill partitioning to represent such areas is stated. Finally, the proposal is evaluated by means of a real-world dataset.
Climatic similarity and biological exchange in the worldwide airline transportation network

Recent increases in the rates of biological invasion and spread of infectious diseases have been linked to the continued expansion of the worldwide airline transportation network (WAN). Here, the global structure of the WAN is analysed in terms of climatic similarity to illuminate the risk of deliberate or accidental movements of climatically sensitive organisms around the world. From over 44 000 flight routes, we show, for each month of an average year, (i) those scheduled routes that link the most spatially distant but climatically similar airports, (ii) the climatically best-connected airports, and (iii) clusters of airports with similar climatic features. The way in which traffic volumes alter these findings is also examined. Climatic similarity across the WAN is skewed (most geographically close airports are climatically similar) but heavy-tailed (there are considerable numbers of geographically distant but climatically similar airports), with climate similarity highest in the June–August period, matching the annual peak in air traffic. Climatically matched, geographically distant airports form subnetworks within the WAN that change throughout the year. Further, the incorporation of passenger and freight traffic data highlight at greater risk of invasion those airports that are climatically well connected by numerous high capacity routes.
Personalidad y síndromes clínicos: Un estudio con el mcmi-iii basado en una muestra española: un estudio con el mcmi-iii basado en una muestra española

Este trabajo presenta una investigacion con 7011 pacientes a los que se les ha aplicado el Inventario Clinico Multiaxial de Millon (MCMI-III) en Espana. Se estudia la prevalencia y porcentajes de los rasgos clinicos de personalidad y de sindromes clinicos encontrandose mayor frecuencia de rasgos de personalidad compulsiva, narcisista e histrionica y, como sindromes clinicos, del sindrome de ansiedad. Se analiza la prevalencia segun el sexo, hallando(a) mayor frecuencia de hombres en los rasgos/sindromes narcisista, paranoide, antisocial, esquizoide, trastorno del pensamiento, abuso de sustancias y abuso de alcohol; y (b) mayor frecuencia de mujeres en las personalidades depresiva, dependiente, evitativa, limite, negativista, y agresivo-sadica, y en los trastornos distimico, somatomorfo, y trastorno de estres postraumatico. Ademas, se presentan los coeficientes de correlacion entre las escalas del Eje II y las del Eje I, controlando el efecto de la variable sexo. Todas las escalas de personalidad correlacionaron con los sindromes clinicos de manera significativa (las escalas compulsiva, narcisista e histrionica correlacionaban en sentido negativo).
Interactive learning of heterogeneous visual concepts with local features

In the context of computer-assisted plant identification we are facing challenging information retrieval problems because of the very high within-class variability and of the limited number of training examples. To address these problems, we suggest a new interactive learning approach that combines similarity-based retrieval and re-ranking by SVM using local feature distributions. This approach leads to improved sample selection, allowing to obtain better results.
Applying a Pairwise Coverage Criterion to Scenario-Based Testing

Some scenario-based testing approaches propose to express a test suite as a regular expression (called scenario or pattern). It specifies a set of valid sequences of operations in a abstract way. When the regular expression is "unfold", test sequences are obtained. Usually, the unfolding is done in an exhaustive way, which can result in a combinatorial explosion. In this article, we explore a pairwise coverage criterion to select a subset of test sequences satisfying the pattern, in order to decrease the number of test sequences. The originality of the approach lies in the fact that the pairwise criterion is applied to the instantiated method calls (and not on the parameters). We applied this strategy to generate unit tests for Java classes. The quality of the test suites is evaluated with a mutation analysis and compared to test suites randomly generated.
ML-PDA: Advances and a New Multitarget Approach

Developed over 15 years ago, the maximum-likelihood-probabilistic data association target tracking algorithm has been demonstrated to be effective in tracking very low observable (VLO) targets where target signal-to-noise ratios (SNRs) require very low detection processing thresholds to reliably give target detections. However, this algorithm has had limitations, which in many cases would preclude use in real-time tracking applications. In this paper, we describe three recent advances in the ML-PDA algorithm which make it suitable for real-time tracking. First we look at two recently reported techniques for finding the ML-PDA track estimate which improves computational efficiency by one order of magnitude. Next we review a method for validating ML-PDA track estimates based on the Neyman-Pearson lemma which gives improved reliability in track validation over previous methods. As our main contribution, we extend ML-PDA from a single-target tracker to a multitarget tracker and compare its performance to that of the probabilistic multihypothesis tracker (PMHT).
Performance analysis of linear precoders and SVD in downlink MassiveMIMO Frequency selective channels

3G/4G wireless systems employed multiple antennas at both the transmitter and receiver offered significant gains over single-antenna systems. MassiveMIMO (MM) is one of the 5G technologies, which supports to increase the demand for high speed data, capacity, energy efficiency and spectral efficiency. It is known that space-time multiplexing and/or coding offer attractive means of combating fading and increases the capacity in a multi-antenna communication. In this paper, MM downlink scenario is considered. Performance analysis using conventional precoders like Matched Filter (MF), Zero Forcing (ZF), Regularized Beamforming (RBF) and Minimum Mean Square Error (MMSE) with Singular Value Decomposition (SVD) based balanced equalizer are studied in spatio-temporal environment. Signal to Interference Ratio (SINR) and Bit-Error Rate (BER) are used as performance measures. Monte-Carlo simulations are carried out to compute BER and SINR in MATLAB.
The use of simulation for training teamwork skills in health care: how low can you go?

High fidelity simulation has become a popular technique for training teamwork skills in high risk industries such as aviation, health care, and nuclear power production. Simulation is a powerful training tool because it allows the trainer to systematically control the schedule of practice, presentation of feedback, and introduction (or suppression) of environmental distractions within a safe, controlled learning environment. Unfortunately, many within the training community have begun to use the terms simulation and high fidelity simulation almost synonymously. This is unfortunate because doing so overemphasises the instructional technology to the detriment of more substantive issues, such as the training’s goals, content, and design. It also perpetuates several myths: simulation fidelity is unidimensional, or higher levels of simulation fidelity lead to increased training effectiveness. The authors propose a typology of simulation fidelity and provide examples of how the different classes of simulation have been successfully used to train teamwork skills in high risk industries. Guidelines are also provided to maximise the usefulness of simulation for training teamwork skills in health care.
Pulmonary gene delivery by chitosan-pDNA complex powder prepared by a supercritical carbon dioxide process.

Chitosan-plasmid DNA (pDNA) complex powders as a pulmonary gene delivery system were prepared with a supercritical carbon dioxide (CO(2)) process and their in vivo activity was evaluated. The powders with mannitol as a carrier were prepared by dispersing aqueous solutions of a luciferase expression plasmid driven by the cytomegalovirus promoter (pCMV-Luc) with or without chitosan as a cationic vector in a supercritical CO(2)/ethanol admixture. The supercritical CO(2) process with a V-shaped nozzle successfully produced chitosan-pDNA powders. The addition of chitosan suppressed the degradation of pCMV-Luc during the supercritical CO(2) process and increased the yield of powders. The luciferase activity in mouse lung was evaluated after pulmonary administration of the powders or pCMV-Luc solutions. The chitosan-pDNA powders increased the luciferase activity in mouse lung compared with pCMV-Luc powders without chitosan or pCMV-Luc solutions with or without chitosan. The chitosan-pDNA powder with an N/P ratio = 5 increased the luciferase activity to 2700% of that of the pCMV-Luc solution. These results suggest that gene powder with chitosan is a useful pulmonary gene delivery system.
Legitimating Identities: How Institutional Logics Motivate Organizational Name Choices

We examine empirically how a key identity marker – an organization’s name -responds to reputational pressures over time. We theorize that institutional logics about naming standards in different historical periods function as social motives, eliciting conformity to the constitutive rules of the (name) game to legitimate organizational identities. In turn, organizational choices of names aggregate to create identity patterns for organizational fields that motivate organizations’ subsequent choices. We map two primary sets of institutional pressures on organizations’ name choices: historical norms at the macro (or broader societal) level and industry norms at the more micro (or immediate) level. We begin by examining historical changes in names from 1972 to 1988 and then show how dominant institutional logics affect name choices made by nearly 1600 organizations changing their names in the 1982-87 period. Our findings illustrate how institutional logics function as social motives for legitimating organizational identities and, in turn, how organizational identities are embedded in both immediate and broader social environments.
Targetable Signaling Pathway Mutations Are Associated with Malignant Phenotype in IDH-Mutant Gliomas

Purpose: Isocitrate dehydrogenase (IDH) gene mutations occur in low-grade and high-grade gliomas. We sought to identify the genetic basis of malignant phenotype heterogeneity in IDH-mutant gliomas. Methods: We prospectively implanted tumor specimens from 20 consecutive IDH1-mutant glioma resections into mouse brains and genotyped all resection specimens using a CLIA-certified molecular panel. Gliomas with cancer driver mutations were tested for sensitivity to targeted inhibitors in vitro. Associations between genomic alterations and outcomes were analyzed in patients. Results: By 10 months, 8 of 20 IDH1-mutant gliomas developed intracerebral xenografts. All xenografts maintained mutant IDH1 and high levels of 2-hydroxyglutarate on serial transplantation. All xenograft-producing gliomas harbored “lineage-defining” mutations in CIC (oligodendroglioma) or TP53 (astrocytoma), and 6 of 8 additionally had activating mutations in PIK3CA or amplification of PDGFRA, MET, or N-MYC. Only IDH1 and CIC/TP53 mutations were detected in non–xenograft-forming gliomas (P = 0.0007). Targeted inhibition of the additional alterations decreased proliferation in vitro. Moreover, we detected alterations in known cancer driver genes in 13.4% of IDH-mutant glioma patients, including PIK3CA, KRAS, AKT, or PTEN mutation or PDGFRA, MET, or N-MYC amplification. IDH/CIC mutant tumors were associated with PIK3CA/KRAS mutations whereas IDH/TP53 tumors correlated with PDGFRA/MET amplification. Presence of driver alterations at progression was associated with shorter subsequent progression-free survival (median 9.0 vs. 36.1 months; P = 0.0011). Conclusion: A subset of IDH-mutant gliomas with mutations in driver oncogenes has a more malignant phenotype in patients. Identification of these alterations may provide an opportunity for use of targeted therapies in these patients. Clin Cancer Res; 20(11); 2898–909. ©2014 AACR.
Analysis of Clock-Jitter Effects in Continuous-Time $\Delta \Sigma $ Modulators Using Discrete-Time Models

This paper proposes a simple discrete-time (DT) modeling technique for the rapid, yet accurate, simulation of the effect of clock jitter on the performance of continuous-time (CT) DeltaSigma modulators. The proposed DT modeling technique is derived from the impulse-invariant transform and is applicable to arbitrary-order lowpass and bandpass CT DeltaSigma modulators, with single-bit or multibit feedback digital-to-analog converters (DACs) employing delayed return-to-zero (RZ) or non-return-to-zero (NRZ) rectangular pulses. Its accuracy is independent of both the power spectrum of the clock jitter and the loop transfer function of the DeltaSigma modulator. The proposed DT modeling technique is validated (for both independent and accumulated clock-jitter errors) against accurate simulations in SIMULINK, using behavioral blocks developed to directly simulate RZ or NRZ DACs with clock jitter. It is subsequently applied to various CT DeltaSigma modulator architectures (low- pass and bandpass, with single-bit and multibit DACs) to study the relative effectiveness of different feedback-DAC pulsing schemes (NRZ, RZ, RZ with fixed on-time, and RZ with fixed off-time) in minimizing the modulator sensitivity to clock jitter. The performance of each architecture is compared as a function of clock jitter, thereby offering a valuable reference for selecting a rectangular feedback-DAC pulse shape when designing CT DeltaSigma analog-to-digital converters.